United States 

Department of 

Agriculture 

Forest Service 

Southern 

Research Station 

General Technical 

Report SRS-5 

Hurricane Hugo: 

South Carolina Forest Land Research 

and Management Related to the Storrn 
We wish to express our appreciation to Mary Alice Cromer for her diligent, expert, word-processing work. She received the 

papers in a wide variety of &om printed journal pages to diskems and was able to read various types of wordprocessing, re-type, cut and paste, or scan and reformat and ultimately create this document. She corrected many inconsistencies 

not noticed by the editors. 

Also, we thank the United States Congress for special funding and the U.S. Department of Agriculture, Forest Service, Southern 

Research Station, for financial support. 

The use of trade or firm names in this publication is for reader information and does not imply endorsement of any product or 

service by the U.S. Department of Agriculture or other organizations represented here. 

September 1 996 

Southern Research Station 

P.O. Box 2680 

Asheville, North Carolina 28802 
HURRIC 

SOUTH CAROLINA FOREST 

AND MANAGEMENT RELATED TO THE ST0 

Editors : 

Jacqueline L. Haymond, Associate Professor 

and 

Dona1 D. Hook, Professor 

Department of Forest Resources 

Clemson University 

Clemson, South Carolina 

and 

William R. Harms, Senior Silviculturist 

USDA Forest Service 

Southern Research Station 

Forestry Sciences Laboratory 

Charleston, South Carolina 
TABLE OF COmEmS 

Page 

F'O ....................... vii 

ImRODUCTION ...................... viii 

EISTORICC~ BACKGRO 

History of Damaging Storms Affecting South Carolina Forests Including a 

Review of Hurricane Hugo's Impact on South Carolina Forests 

Job C. Purvis .......................... 2 

Impact of Hurricanes on Forests of the Atlantic and Gulf Coasts 

William H. Comer. ........................ 6 

Impact and Recovery of Gulf Coastal Forests from Hurricane Camille 

William Colvin ......................... 13 

DmGE ASSESSmmS 

Planning 

Short-Term Planning and Response to Forest Damage 

WrayE-Freeman ......................... 18 

Salvage of Storm Damaged Timber 

H.M. Lupold.. ......................... 21 

How to Evaluate and Manage Storm-Damaged Forest Areas 

Patrick J. Barry, Coleman Dogget t, Robert L. Anderson, and 

KennethM. Swain, Sr. ..................... 28 

Damage to Forasts 

Impact of Hurricane Hugo on the South Carolina Coastal Plain Forest 

Dona1 D. Hook, Marilyn A, Buford, and Thomas M. Williams .... 34 

Assessment of Hurricane Damage to the Santee Experimental Forest and 

the Francis Marion National Forest with a Geographic Information 

System 

Lawrence E. Nix, Donal D. Hook, James G. Williams, and 

DonaldVanBlaricom ...................... 44 

Hurricane Hugo Damage Assessment of Bottomland Hardwoods in South 

Carolina 

Kemeth Pi t tman, R. C. Kellison, and Russ Lea .......... 52 

Hurricane Hugo Wind Damage to Southeastern U.S. Coastal Forest Tree 

Species 

C. A. Gresham, T. M. Williams, and D. J. Lipscomb ......... 64 

Major Structural Damage Present Prior to Hurricane Hugo in Old-Growth 

Forest Trees at Four Holes Swamp, South Carolina 

M.J.DueverandJ.M.McCo1lorn. ................. 72 

Patterns of Initial and Delayed Mortality Caused by Hurricane Hugo in 

Four Old-Growth Forest Communities in Four Holes Swamp, South Carolina 

J. M. McColl om and M. J. Duever .................. 7 3 

Hurricane Hugo Effects on Old-Growth Floodplain Forest Communities at 

Four Holes Swamp, South Carolina 

Michael J. Duever and Jean M. McCollom ............. 74 

Hurricane Hugo Effects on Major Floodplain Forest Communities at Four 

Holes Swamp, South Carolina 

Michael J. Duever and Jean M. McCollom ............. 81 

Hurricane Hugo in a South Carolina Old-Growth Floodplain Forest: 

Environmental Effects 

Michael Duever and Jean McCol lorn ................ 82 

Hurricane Damage to an Old-Growth Floodplain Forest in the Southeast 

Rebecca R. Sharitz, Milda R. Vaitkus, and Allen E. Cook ..... 83 

Hurricane Damage to Old-Growth Forest in Congaree Swamp National 

Monument, South Carolina, U.S.A. 

Francis E. Putz and Rebecca R. Sharitz ............. 92 
Table of Contents (Continued) 

Page 

Hurricane Damage to the Canopy Species of a 24-Year-Old Seed Tree 

Regeneration Experiment in a Non-Alluvial Swamp 

David L. Gartner, Dona1 D. Hook, md Marilyn A. Buford ..... 101 

er Supplies, Salvage, and Use 

Damage, Harvest Operations, and Regeneration Activities Following 

Hurricane Hugo in South Carolina-Photographic Documentation 

Jeffrey L. Bauma, Robert G. Haight, Allan P. Marsinko, and 

Thomas J. Straka ........................ Hurricane Hugo: Effects on South Carolina's Forest Resource 

Raymond M. Sheffield and Michael T. Thompson .......... Hurricane Hugo: A South Carolina Update 

Allan P. C. Marsinko, Thomas J. Straka, and Jeffrey L. Baumann . . Effects of Hurricane Hugo on the Forests of North and South Carolina 

Michael T. Thompson ....................... Assessment of Hurricane Hugo Damage on State and Private Lands in 

South Carolina 

Michael C. Remion ........................ Hurricane Hugo-Damage Assessment Using Permanent Plot Remeasurement 

Raymond M. Sheffield ...................... Assessing Internal Hurricane Damage to Standing Pine Poletimber 

Timothy D. Faust, Mark Fuller, Robert H. McAlister, and 

Stanley J. Zarnoch ....................... Occurrence of Compression Wood in Hurricane-Stressed Pine Poletimber 

Timothy D. Faust, Mark Fuller, and Robert H. McAlister ..... A Method of Testing the Full Cross-Section of Wood in Tension 

Perpendicular to the Grain 

Timothy D. Faust, Mark Fuller, and James T. Rice ........ Effectiveness of Water Sprinkling for Long-Term Storage of HurricaneDowned Pine Timber 

JohH. SymeandJosephR. Saucier ............... Manufacture of Southern Pine Plywood from Hurricane Hugo Salvaged 

Logs Stored Under Water Sprinklers 

J.H. Syme, P.N. Peralta, and R.H. McAlister ........... Effect of Log Wet Storage Time on the Stiffness of Southern Pine 

Plywood (A Case Study) 

Robert H. McAlister, Alexander Clark 111, and Joseph R. Saucier . 

Emvironmental Inrgacts 

Disturbance Effects of Hurricane Hugo on a Pristine Coastal Landscape: 

North Inlet, South Carolina, USA 

L.R. Gardner, W.K. Michener, T.M. Williams, E.R. Blood, B. 

Kjerfve, L.A. Smock, D.J. Lipscomb, and C. Gresham ....... 226 

Estimation of Aboveground Biomass in a Hurricane-Impacted Coastal 

Plain Forest 

Richard K. Myers, David H. Van Lear, and F. Thomas Lloyd .... 244 

Compaction and Rutting During Harvesting Affect Better Drained Soils 

More Than Poorly Drained Soils on Wet Pine Flats 

W. Michael Aust, Mark D. Tippett, James A. Burger, and 

William H. HcKee, Jr. ..................... 253 

Soil Physical and Hydrological Changes Associated with Logging a 

Wet Pine Flat with Wide-Tired Skidders 

W. M. Aust, T. W. Reisinger, J.A. Burger, and B. J. Stokes ..... 261 

Changes in Bald Cypress-Swamp Tupelo Wetland Soil Chemistry Caused 

By Hurricane Hugo Induced Saltwater Inundation 

CharlesA. Gresham ....................... 266 
Table of Contents (Continued) 

Page 

Salt Water Movement Within the Water Table Aquifer Following 

Hurricane Hugo 

Thomas M. Willims ....................... 271 

$con&c and Social Impacts 

The Effect of Hurricane Hugo on Forest Practice Costs 

Allan P. Marsinko, Thomas J. Straka, and Jeffrey L. Bawam . A Financial Assessment of Capital-Extensive Management Alternatives 

for Storm-Damaged Timber 

Thomas J. Straka and James B. Baker ............. Site Preparation and Tree Planting Costs on Hurricane-Damaged 

Lands in South Carolina 

Thomas J. Straka, Allan P. Marsinko, Jeffrey L. Baumam, 

and Robert G. Haight .................... The Economics of Loblolly Pine Plantations Under Risk of Hurricane 

Damage 

Robert G. Haight, William D. Smith, and Thomas J. Straka . . The Impact of Hurricane Hugo on South Carolina's Timber Supply 

Robert Abt, John Burch, and Gerardo Pacheco ......... Hurricane Hugo: Timber Inventory, Price and Welfare Effects for 

South Carolina 

John R. Burch, Robert C. Abt, Gerardo Pacheco, T. Barton 

Lander, and Raymond M. Sheffield .............. The Effect of Hurricane Hugo on Timber Supply 

Allan P. Marsinko, Thomas J. Straka, and Robert G. Haight . . The Timber Situation in South Carolina's Northern Coastal Plain 

Three Years After Hugo 

Herbert A. Knight and Stephen K. Nodine ........... Assessing the Forest-Based Recreation Impacts of Hurricane Hugo 

in South Carolina 

William E. Hammitt, Robert D. Bixler, and Theresa A. Herrick 

Impacts of Hurricane Hugo on Private Landownersi Attitudes and 

Perceptions 

S.K. Nodine ......................... Impacts of Hugo Timber Damage on Primary Wood Manufacturers in 

South Carolina 

John H. Syme and Joseph R. Saucier ............. 

FOREST RESTOFUkTION 

Protection 

Post-Hurricane Hugo Forest Pest Populations and Damage (Impacto de las 

Poblaciones de Insectos Forestales Posterior a1 Huracan Hugo) 

Harry 0. Yates 111 and Thomas Miller .............. 380 

Recommendations for Salvage and Estimates for Rapidity of Invasion 

by Various Insects and Disease Organisms of Hurricane Hugo-Damaged 

Timber Resources 

Patrick J. Barry ........................ 385 

Red-Cockaded Woodpecker 

Hurricane Hugo's Initial Effects on Red-Cockaded Woodpeckers in the 

Francis Marion National Forest 

Robert G. Hooper, J. Craig Watson, and Ronald E.F. Escano .... 387 

Economic Valuation of the Red-Cockaded Woodpecker and Its Habitat 

Dixie Watts Reaves, Randall A. Kramer, and Thomas P. Holmes ... 391 

Effectiveness of Nest Boxes for Reducing Use of Red-Cockaded 

Woodpecker Cavities by Other Vertebrates 

Susan C. Loeb and Robert G. Hooper ............... 398 
Table of Contents (Continued) 

Page 

Characterisitcs of Ti r Stands Containing Sufficient Heartwood for 

Cavity Excavation by Red-Cockaded Woodpecker Clans 

AlexanderClark, I77 ...................... 399 

Restoration of the Red-Cockaded Woodpecker Population on the Francis 

Marion National Forest: Three Years Post Hugo 

J. Craig Watson, Robert G. Hooper, Danny L, Carlson, Milliam 

E. Taylor, and Timothy E. Hilling ............... 405 

Hurricanes and the Long-Term Management of the Red-Cockaded Woodpecker 

Robert G. Hooper and Colin J. McAdie .............. 417 

Impact of Hurricane Hugo on Cavity Trees of a Red-Cockaded Woodpecker 

Population and Natural Recovery After Two and a Half Years 

Donald J. Lipscow and Thorns 141. Willims ............ 437 

Regeneration 

Technology and Innovation. . .Key to Hugo Recovery 

D.N.Gerhardt .......................... 442 

Easing the Transition: Reducing the Cost of Reforesting Lands Damaged 

by Hurricane Hugo 

StephenK.Nodine. ....................... 447 

Management Alternatives Costs for Storm-Damaged Timber in the 

Southern United States 

C.D. Egbert, T.J. Straka, and A.P. Harsinko ........... 450 

Problems with Natural Regeneration on Hugo-Damaged Lands 

Joe Hamil ton, Jim Adkins, Jaime Teel, David Nagel, and 

PatrickLee .......................... 452 

Cypress Restoration in Salt-Milled Wetland Systems (South Carolina) 

William H. Comer and George Askew ............... 454 

Impact of Saltwater Flooding on Red Maple, Redbay, and Chinese 

Tallow Seedlings 

WilliamH. ComerandGeorgeR. Askew. ............. 456 

Artificial Regeneration of Baldcypress in Three South Carolina 

Forested Wetland Areas After Huricane Hugo 

William H. Comer ........................ 461 

Third-Year Results from a Test of Longleaf Pine (Pinus palustris Mill.) 

Seed Sources on the Francis Marion National Forest 

Earl R. Sluder ......................... 466 

Note: Response of Baldcypress and Loblolly Pine Seedlings to ShortTerm Saltwater Flooding 

WilliamH. ComerandGeorgeR.Askew. ............. 475 

Long-Term Recovery of Plantation-Grown Loblolly Pine from Hurricane 

Damage 

P.H. Dudam dnd D.M. Bourgeois ................. 48 0 

Economics of Low Density Stand Management 

Stephen K. Nodine ........................ 491 

Final Report: An Evaluation of the Post-Hugo Forest Recovery Programs: 

Salvage, Wildfire Hazard Mitigation, and Reforestation 

Marie Lynn Miranda ....................... 498 
Hurricane Hugo was probably one of the most destructive hurricanes to assault the 

forests of the Eastern United States in recorded history. Four and one-half million 

acres were damaged in North Carolina and South Carolina, an estimated 21.4 billion 

board feet of timber were destroyed or dmaged, and several federally listed 

endangered species (red-cockaded woodpecker, bald eagle, and red wolf) were impacted. 

This toll does not include property d ge or hmn suffering in the United States or 

the destruction in Puerto Rico. Hurricane Hugo is probably the most studied and best 

documented hurricane ever to have reached landfall in the mainland. In addition to 

the reports in this compilation, more reports can be expected as on-going and new 

studies of forest damage, restoration, and rehabilitation are completed. 

We made no attempt to synthesize or summarize the papers in this publication because 

the topics covered are too diverse. However, we offer the following thoughts about 

how to lessen impacts of hurricanes on forests. 

Hurricanes are a natural, integral part of ecosystem processes in Eastern forests. 

Hurricanes occur infrequently and unpredictably; therefore, the significance of their 

impact on the forest tends to be quickly forgotten as the visible evidence of their 

effects fade from the landscape. The net result is that the next hurricane can be as 

destructive as the last hurricane. The land manager must remain aware of the risk of 

windstorms and use known silvicultural techniques to develop a wind-resistant forest. 

Although nothing can be done to protect forests against maximum catastrophic winds of 

Category 4 or 5 hurricanes, much of the damage from hurricanes comes from lesser 

winds, and forests can be managed to be more resistant to such winds. 

For example, several of the reports in this compilation, as well as reports published 

from studies of other hurricanes and windstorms, show that damage within stands from 

hurricane-force winds occurs predictably. The extent of damage is, for the most 

part, explained by age, size, and canopy position. Large crown-overstory trees 

suffer greater damage than trees in the lower canopy; and trees in young, dense 

stands generally suffer the least damage. These observations suggest that 

silvicultural intervention could produce stands of trees that are more wind 

resistant. 

Research has shown that trees grown in stands maintained in sufficiently open 

conditions so that healthy crowns and root systems develop are stronger and more 

windfirm. This means control of spacing by planting, weeding, or thinning enhances 

growth of desirable trees. Where forests are managed on short rotations of 30 years 

or less, there is probably little incentive to invest the necessary dollars to 

develop windfirm stands, but on public forest and parklands where large trees and 

old-growth stands are desired, more thought needs to be given to producing 

wind-resistant forests, 

vii 
INTRODUCTION 

During the months after Hurricane Hugo's landfall in South Carolina on Segteber 22, 

1989, hundreds of people became involved in salvage, recovery, and restoration of our 

forests. We turned to the lessons learned from previous hurricanes for guidance in 

our efforts. Unfortunately, published information on salvage, recovery, and 

restoration was limited, scattered, or difficult to obtain. We attempted to fill 

that information void by documenting our work in the aftermath of Hurricane Hugo in 

one book. We hope this publication will help those faced with similar challenges 

presented by future hurricanes. Much of the work reported here was done with special 

funding provided by the United States Congress. 

This compilation includes 69 published and previously unpublished articles relating 

to the effects of Hurricane Hugo, a Category 4 storm, on forests primarily in South 

Carolina. The articles record the response of the forests to the storm and the 

activities of those who cared for these forests. Broad topics include historical 

background, damage assessment, forest restoration, and evaluation of recovery 

programs. 

Seven years have passed since the storm. Some papers report findings from field work 

done immediately after the storm; others are based on later activities and effects. 

This book contains 1-page abstracts, comprehensive final reports, papers presented at 

professional meetings, journal articles, interim reports of work in progress, and 

otker types of articles. Readers will find indepth reports of scientific studies, 

discussions of management strategies, and suggestions for better problem resolution 

in similar catastrophes. The papers are organized according to dominant subject 

matter. Valuable suggestions for improving response activities often appear as a 

small part of many of the articles. 

The editors have attempted to capture all currently available information on forest 

research and management related to Hurricane Hugo in South Carolina. However, some 

articles were impractical to include, many of them have been referenced by authors or 

have been listed in the "Additional Reportsn section. In spite of our best efforts, 

we have probably excluded valuable information that we were unaware of at the time of 

printing. 

The editors did not verify the data presented in each article. No attempt was made 

to condense articles or remove repetition between articles. We have standardized the 

format for ease of reading and made minor editorial corrections in the text. Papers 

were not proofread by each author after final word processing. Therefore, the 

editors are responsible for such errors. 

viii 
HISTORICAL BACKGROUND 
HISTORY OF DAMAGING ST0 AFFECTING 

SOUTH CAROLINA FORESTS INCLUDING A REVIEW OF 

IIURRICANE HUGO'S IMPACT ON SOUTH CAROLINA FORESTS' 

John C. ~urvis' 

INTRODUCTION 

South Carolina forests are vulnerable 

to several types of storm damage ranging from thunderstorms, tornadoes, 

winter ice storms, and hurricanes. 

While some damage occurs each year, 

occasionally a major event such as the 

1967 ice storm, the 1984 tornadoes, or 

a major hurricane such as Hugo causes 

major damage to South Carolina forests. The purpose of this study is to 

look briefly at each of these weather 

hazards, using Hurricane Hugo as an 

example of the horrible impact di-unaging storms can exact on the forest 

industry of the state. 

PART ONE: HISTORY OF DAMAGING 

STORMS AFFECTING SOUTH CAROLINA 

FORESTS 

A. Thunderstorms are so frequent in 

South Carolina that their effect on 

the forest industry is usually 

accepted without undue concern. 

Damaging thunderstorms are more likely 

during the warmer part of the year, 

but they do occur throughout the year 

in every part of the state. Thunderstorm frequency varies from almost 60 

days per year in southern South 

Carolina to a minimum of about 45 days 

per year in the extreme northwestern 

part of the state. Thunderstorm 

damage to forests usually ranges from 

a few trees killed by lightning to 

occasionally scattered areas of 

localized wind damage. 

B. Freezing rain occurs almost 

every year in some part of the state. 

Fortunately, many occurrences are not 

' A paper presented at the 72nd Annual 

Meeting of the Appalachian Society of 

American Foresters held at Greenville, 

S.C., on January 20-22, 1993. 

John C. Purvis, S.C. Water Resources 

Board, 1201 Main Street, Suite 1100, 

Columbia, SC 29201. 

severe enough to cause extensive damage to forests. There are times, however, when an intense winter storm, 

accompanied by strong winds and large 

ice accumulations, causes major damage 

to the forestry industry. The most 

severe damage in recent years was in 

February 1969 when an ice storm caused 

major damage to South Carolina forests 

from Sumter County northeast through 

Chesterfield County. Timber losses 

were tremendous and power and telephone service were seriously disrupted 

aver a large area, 

C, Tornadoes are a definite hazard 

to forests in southeastern U.S. 

including South Carolina. On a local 

scale, it is the most destructive of 

all atmospheric phenomena. According 

to the American Meteorological Society 

(1959), the tornado is "a violently 

rotating column of air, pendant from a 

cumulonimbus cloud, and nearly always 

observable as a funnel cloud or tuba". 

During the last 40 years, there has 

been on the average 10 tornadoes per 

year within the state (Purvis, 1990). 

While many tornadoes affect only a 

small area, a few tornadoes travel 

many miles and produce significant 

damage to forests. A severe tornado 

has the power to cut a 1/2- to 1-mile 

wide swath over a path of many miles. 

Trees are broken and twisted by the 

violent winds, greatly reducing their 

salvage value. Several years ago, a 

tornado moved across Lancaster, 

Chesterfield and Marlboro Counties. 

Near Jefferson, S. C., the tornado 

passed through an original stand of 

timber. The owner had many times been 

approached by loggers to sell the 

tract because of its value. But after 

the storm, the large original pines 

were so broken up that no one wanted 

them. Another example of a tornado 

causing major tree damage was on April 

30, 1924. On that date, a violent 

tornado was first reported 11 miles 
northeast of Aiken, The storm moved 

rapidly northeastward to Darlington 

County causing major forest d 

over a 105-mile path that was estxmated at times to be more than 112- 

mile wide, The tornadoes of March 28, 

1984 were also particularly devastating to South Carolina forests. There 

were eleven tornadoes on that date 

over an area that stretched from 

Anderson County to Iiorry County. 

Although there was damage along the 

entire route, forests in Kershaw and 

Chesterfield Counties were hit hard, 

D. Hurricanes are an annual threat 

to South Carolina woodlands. There 

are on the average one or more hurricanes affecting southeast U,S, every 

three years. During any one year, 

there is an 18% chance of a hurricane 

penetrating the South Carolina coastline. There have been a few years 

such as 1959 when two or more hurricanes caused significant loss to South 

Carolina forests (Purvis and others, 

1990). 

Some hurricanes sther than Hugo that 

have produced major damage to South 

Carolina forests in recent years were 

Hazel in 1954, Gracie in 1959, and 

David in 1979, 

In order to appreciate the damage to 

forests that a hurricane can produce, 

it is important to understand the 

physical dimensions of this type of 

storm, A hurricane is a tropical 

cyclone that forms over the very warm 

waters of the world and moves with the 

prevailing winds within its immediate 

environment, The hurricane derives 

energy from the latent heat released 

by condensation of water vapor and, 

when fully developed in the Northern 

Hemisphere, consists of a giant 

counter-clockwise swirl of strong 

winds accompanied by clouds and heavy 

rains, The center of the hurricane, 

called the "eye", is a relatively calm 

area with little or no cloudiness and 

may vary in size from 5 to 10 miles in 

diameter to more than 30 miles, Immediately surrounding the eye are towering wall clouds, extremely heavy rains 

and high winds. Farther away from the 

center, the most intense rainfall and 

winds tend to be concentrated in giant 

spiral bands radiating in a counterclockwise fashion from the wall 

clouds, 

E. Wind Direction and Speed.--A 

hurricane is most fully developed 

while it is over the ocean but weakens 

as it moves over land, Forests 

directly in the path of the eye of a 

hurricane approaching the South 

Carolina coast from a southeast 

direction, would first experience 

increasing wind speeds, blowing from 

right to left, After the eye passes, 

the wind direction would reverse with 

the wind speed as high or higher than 

it was immediately ahead of the eye. 

The most extensive and widespread 

damage is usually on the right hand 

side of an advancing hurricane. 

Forests located to the right of the 

center would not experience a complete 

reversal in wind direction, The 

highest winds would be from the same 

general direction that the storm is 

moving. In other words, if the 

hurricane were headed in a northwesterly direction, the highest winds 

on the right hand side of the eye 

would likely be from an east to southeast direction. 

Forests to the left of the center 

should receive their highest wind 

speeds from the general direction to 

which the storm is headed. For 

example, if the hurricane were headed 

in a northerly direction, the highest 

wind speeds would likely be from a 

northerly direction. 

It should be emphasized, however, that 

outside the wall cloud area, the wind 

speeds are higher and cover a larger 

area to the right of the advancing 

hurricane eye than to the left. Also, 

as the storm moves inland and begins 

to weaken, the most intense activity 

is concentrated in spiral bands that 

rotate around the center in a counterclockwise fashion. This will produce 

localized areas of heavier damage 

within a widespread area of lesser 

damage. 

F. Hurricane Produced Storm Surge. 

--A hurricane moving over the ocean 

produces a higher water level that 

reaches a maximum to the right of the 

storm's center. This rapid rise in 

ocean level, or "storm surge", 

increases in height with the intensity 

of the hurricane. It is also important to note that the storm surge is 

added to the existing height of the 

ocean at the time of the arrival of 

the storm. Hence, if the hurricane 

were to arrive at the coast at time of 

high tide, the actual water level at 

the coast would be the height of the 

high tide plus the height of the storm 
surge, This sudden increase in the 

height of the ocean floods coastal 

areas that othemise would never be 

flooded, Fortunately, a major hurricane does not penetrate the South 

Carolina coastline very often; but 

when it does, salt water penetration 

is a threat to forests in the 

ate vicinity of the ocean. 

PART TWO: mmICME HUGO AS AN 

R E TO SOUTH 

CAE10LIISIA FORESTS BY HURRICAEJES 

Hurricane Hugo made landfall on the 

South Carolina Coast late on 

September 21, 1989 causing major damage to South Carolina forests, 

Hugo began as a cluster of thunderstorms moving off the west coast of 

Africa on September 9. As this system 

became better organized and surface 

pressures began to fall on September 

10, a tropical depression, centered 

125 miles southeast of the Cape Verde 

Islands, formed. This tropical 

depression became a tropical storm, 

named Hugo, on September 11 and by 

late on September 13 had gained 

sufficient strength to be classified a 

hurricane. Hugo continued to move 

westward but gradually turned to a 

west-northwest course during the next 

several days, Hugo struck Guadeloupe 

on September 17 as a Category 4 

hurricane passed across St. Croix of 

the Virgin Islands on September 18. 

The storm now moving on a northwesterly heading brushed Puerto Rico 

and continued to move in the general 

direction of the South Carolina Coast, 

A hurricane watch was issued for the 

South Carolina coast at 7 a.m., 

September 21, 1989. The weather began 

to worsen along the central South 

Carolina coast during the late 

afternoon of September 21 as the 

forward speed of the storm increased 

to 25 mph. Just before landfall, a 

reconnaissance measurement of 27.58 

inches and winds of 161 mph at an 

altitude of 12,000 feet were recorded 

--the basis of the estimate of the 

highest one-minute wind speed of 138 

mph at landfall. 

The eye of Hugo, measuring 20 miles in 

diameter, made landfall near 

Sullivan's Island, S.C. at midnight 

EoDoTe of September 21. The weather 

office in downtown Charleston measured 

a maximum sustained wind speed of 87 

mph with a peak gust of 108 mph, The 

highest winds, category 4, associated 

with Hugo were located in the Bulls 

Bay area of northeastern Charleston 

County, There the winds in combination with the local high tide, caused 

a highest water level of 20.2 feet 

National Geodetic Vertical Datum, just 

south of McClellanville. 

As Hugo moved inland over Lakes 

Moultrie and Marion, it began a 

gradual turn towards the northnorthwest, The center of the storm 

passed between Shaw Air Force Base in 

Sumter County and Eastover in Richland 

County, causing 109 mph gusts at Shaw 

and a small tornado west of the base. 

The dissipating hurricane then moved 

northward over Camden with gusts estimated at over 100 mph. The disorganized eye of Hugo continued northwestward over Lancaster and York counties 

reaching central and western North 

Carolina by daylight of September 22, 

1989, 

Hugo weakened as it moved across South 

Carolina; however, winds near the 

center were still of hurricane force 

along its entire path across the 

Fahetto State. Damaging winds with 

localized areas of more severe damage 

extended out from the hurricane's path 

as far east as Horry, Marlboro, and 

Chesterfield Counties, Damaging winds 

west of the disorganized eye's path 

covered a much smaller area with only 

minor forest damage reported west of 

southern Charleston County, Lexington 

County, and York County. 

The types of wind damage to forests 

varied, depending mostly on the location and direction of the forests from 

the path of the storm's center, Near 

the dissipating eye, and at times in 

spiral bands extending out from the 

eye, trees fell in various directions, 

However, generally on the eastern and 

western sides of the hurricanes path, 

the direction that the trees fell 

reflected the counterclockwise rotation of the wind around the center of 

the hurricane. 

Aerial and ground surveys conducted by 

the South Carolina Forestry Commission 

(R, M. Sheffield and M. T, Thompson, 

June 1992) identified 23 counties with 

substantial forest damage. There 

were, however, additional counties 

with lesser damage, The damage to 

South Carolina forests from Hugo, 

according to a study prepared for the 

Governor's Office (The Fontaine 

Company, 1991), was $1,181,000 

dollars, The report also stated that 
ted value of salvaged timber 

50,000 dollars. There are 

ely 6.5 million acres of 

in the 23 counties inventhe Forestry Comission. 

Sheffield and Thompson state that two 

thirds, or 4.5 million acres, of the 

forests within these 23 counties 

within the state suffered 

ge was most widespread 

near the coast and on the northeast 

side of the hurricane's eye as it 

moved northwest from its entry along 

the central South Carolina coast. In 

six counties (Berkeley, Clarendon, 

Florence, Lee, Smter , and 

Williamsburg), more than 90 percent of 

timberland was damaged. This severe 

daxnage was near and to the east of the 

path of Hugo's eye. 

Lowland hardwood stands sustained the 

highest incidence of damage. Lowland 

hardwood stands often contain large, 

shallow-rooted trees with large 

crowns, factors associated with 

increased susceptibility to wind 

damage (Barry and others, 1982; Hook 

and others, 1991). Of the hardwood 

varieties considered, red oak fared 

the worst and red maple the best 

(Sheffield and Thompson, June 1992). 

Declines in softwood inventory due to 

Hugo were recorded in all 23 counties 

inventoried, but declines were greatest in counties near the coast and 

along the path of the hurricane's eye. 

Of the softwood varieties considered, 

loblolly pines sustained the heaviest 

damage, while shortleaf pines suffered 

the least. The greatest losses were 

recorded in the larger diameter 

classes. Within the forest, wind 

speeds are much higher above the crown 

level than near the ground. The 

larger and taller trees are, therefore, subject to higher wind speeds 

than shorter ones nearby. 

the Southeast Regional Climate Center 

and South Carolina State Climatologist, provided access to the Center's 

records. Ms. Jennie Morris, Public 

Information Specialist, South Carolina 

Forestry Commission, researched past 

ge caused by freezing rain and 

loaned slides showing ice damage. 

Special thanks to Roy Hedden, Division 

of Agriculture and Natural Resources, 

Clexnson University, for materials 

furnished. 

LITERATUm CITED 

American kfeteorological Society. 1959. 

Glossary of Meteorology. p. 584-585. 

Grazulis, T.P. 1990. Significant 

Tornadoes 1880-1989, Vol 11. 

Environmental Films, 685 p. 

Morris, Jennie. 1993. Unpublished 

information and slides showing ice 

damage, South Carolina Forestry 

Commission. 

Purvis, J.C. and others. 1990. 

Hurricane Hugo. Climate Report G-37, 

Southeast ~egional Climate Center, 

82 p. 

. 1990. South Carolina Tornado 

Statistics. Southeast Regional Climate 

Center, 59 p. 

Sheffield, RIM.; Thompson, M.T. 1992. 

Hurricane Hugo, Effects on South 

Carolina's Forest Resource. Southeastern Forest Experiment Station 

Research Paper SE-284, 51 p. 

Reprinted with permission from 

Hurricane Hugo: Recovering from 

Disaster, Proceedings 72nd Annual 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Foresters, Greenville, SC, 

Jan. 20-22, 1993. Dr. Vernon L. 

Robinson, Sec-Treas, 2557 Abbott 

Circle, Seneca, SC 29678. 

The author wishes to express appreciation to all individuals who contributed to the completion of this publication. Mr. D. J. Smith, Director of 
IMPACT FORESTS 

D GULF COASTS 

William H. ~onner' 

Abstract--Coastal forests have developed along the Atlantic 

and Gulf coasts with hurricanes as aperiodic natural 

events, Hurricanes are not unusual or rare, but they are 

very difficult to predict. As a result, it is almost 

impossible to plan hurricane-related research activities. 

For past hurricane events, available literature has focused 

on the short-term effects of these storms. Only now are 

scientists beginning to recognize the importance of natural 

catastrophes as critical to ecosystem dynamics. Hurricane 

Hugo made landfall in South Carolina on September 21-22, 

1989. As a result of the damage suffered during this 

storm, an emphasis has been placed on long-term monitoring 

of the recovery of damaged ecosystems, 

INTRODUCTION 

Hurricanes are common, but unpredictable, occurrences on the Atlantic and 

Gulf coasts of the southeastern United 

States, There is evidence that indicates 160,000 to 320,000 hurricanes 

have occurred in the area of the 

Florida keys during the past two 

million years (Ball and others 1967). 

They occur about once every 20 years 

in south Florida (Lugo and others 

1976) and are even more common on the 

Gulf coast (Conner and others 1989). 

South Carolina experienced 38 hurricanes between 1700 and 1983, or 

approximately one every seven years 

(Dukes 1984). Paths have been plotted 

for several time periods. Figure 1 

shows hurricanes plotted for the years 

1886-1963. As can be seen in the 

figure, the Gulf coast has been hit by 

more hurricanes than the Atlantic 

coast. 

High winds are usually associated with 

hurricanes, but other forces include 

tidal storm surge and torrential 

rains. These latter forces are often 

more destructive than wind alone 

(Baker 1978). Hurricane winds cause 

defoliation, breakage, and windthrow 

in forests with the severity of damage 

related to storm intensity, forest 

Assistant Professor, Baruch Forest 

Science Institute of Clemson University, Box 596, Georgetown, SC 29442. 

structure, and soil conditions (Weaver 

1989). The storm surge ( a l s o c a l l e d 

storm tide, hurricane tide, or tidal 

wave) is a mound of water pushed ashore 

by the hurricane, In coastal locations, the combined flooding and 

pounding by waves can cause great 

damage (Baker 1978). Heavy rains 

associated with hurricanes can be both 

destructive and beneficial. Much 

damage has been caused in areas where 

large amounts of rain have caused 

flooding of tributaries and major 

streams, In contrast, crops in the 

southeastern United States have been 

saved from drought more than once by 

hurricane rains (Simpson and Riehl 

1981). Tropical cyclone-related 

rainfall contributes about 15% to mean 

seasonal precipitation in the Gulf of 

Mexico region, and up to 30% or more in 

some areas (Cry 1967, Meeder 1987). 

Despite the interest that hurricanes 

generate immediately following their 

destructive landfall, very little is 

actually known about their long-tern 

impacts on forested ecosystems, mainly 

because of the difficulty in planning 

hurricane-related research (Lugo and 

others 1983). It is difficult to study 

an area in anticipation of a hurricane 

since it cannot be predicted where or 

when one will occur, After a hurricane 

occurs, it takes time to design a study 

and get money allocated for that study. 

It is often easier to study something 

else and hope that someone else will 
Figure 1--Hurricanes crossing the Atlantic and Gulf coasts, 1886-1963 (modified 

from Baker 1978). 

follow up on the questions that have 

been raised, In this paper, I will 

attempt to synthesize what we know 

about the impacts of hurricanes on 

forests of the southeastern United 

States. special emphasis will be 

placed on ~urricane Hugo as it may 

provide the best opportunity for longtern ecological research in the coming 

years, 

IMPACT TO FORESTS 

Mangrove Forests 

Even though mangrove forests (see 

Table 1 for a listing of common and 

scientific names of tree species 

referred to in the text) represent a 

small portion of the total forested 

area of the southeastern United 

States, there is probably more information on impacts of hurricanes for 

this forest type than any other. 

Table 1--Scientific and common name of 

tree species referred to in the text, 

Scientific name common name 

Avicennia germinans L. Black mangrove 

Laguncularia racemosa (L.) 

Caertn. f. White mangrove 

Rhizophora mangle L . Red mangrove 

Taxodium distichum (L.) Rich. Baldcypress 

Taxodium distichum var. nutans (Ait.) Sweet Pondcypress 

Nyssa aquatica L. Water tupelo 

Nyssa sylvatica var . biflora (Walt. ) Sarg. swamp b lackgua 

Pinus elliottii Engelm. Slash pine 
Various hurricanes have caused up to 

90% mortality of mangroves in south 

Florida, and there seem to be differences in susceptibility between individual species of mangrove occupying 

the same general area (see Lugo and 

Snedaker 1974), Observations by 

Craighead and Gilbert (1962) suggest 

that hurricanes may, to some extent, 

control species composition within 

relatively large mngrove-dominated 

areas. Mangroves in the Gulf coastal 

area reach maturity in 20-25 years, 

coinciding with the mean frequency for 

major hurricanes in south Florida 

(Lugo and Snedaker 1974). Thus, 

hurricanes keep mangrove forests in a 

juvenile successional state, and net 

production over the long term is 

higher (Lugo and others 1976). 

Maxhuxu biomass, on the other hand, is 

limited by hurricanes, as exemplified 

by mangrove areas of Florida, Puerto 

Rico, and Mexico where biomass may be 

only one-half of that reported for 

Panama (Lugo and Snedaker 1974, 

Flores-Verdugo and others 1987). 

Another impact of hurricanes in the 

Everglades region of Florida is the 

construction of debris dams. High 

winds and waves literally roll up 

portions of mangrove swamps into long 

windrows of trees, grasses, aquatic 

plants and algae. These newly-formed 

ridges, with the added silt and peat, 

can impound large areas of freshwater 

dumped on the Everglades by the hurricanes, helping to prevent saltwater 

intrusion (Vogel 1980). At the same 

time, favorable conditions are created 

for mangrove reestablishment of newly 

exposed flats following hurricanes 

(Harlem 1979). 

Freshwater Forested Wetlands 

The ecological impacts of hurricanes 

on freshwater forested wetlands and 

upland coastal species are not well 

documented, The most often reported 

statistics include area affected, 

severity and type of damage, number of 

trees damaged, growing stock volume 

lost, and economic value of the timber 

lost. It has been shown repeatedly 

that coastal economies recover quickly 

following a major hurricane (Janiskee 

1990), but little information exists 

on the recovery of forest ecosystems 

(Conner and others 1989). 

Damage to forest types generally 

increases in the order pine > 

hardwood > swamp (Touliatos and Roth 

1971). However, there are exceptions 

as in Hurricane Camille (1969) in 

Mississippi, where Hedlund (1969) 

reported that both pine and hardwood 

were equally vu-lnerable. During 

Hurricane Donna, slash pine was one of 

the most resistant species in Florida 

(Craighead and ~ilbert 1962). A 

positive correlation between annual 

growth of slash pine on barrier islands 

along the Mississippi coast and 

hurricanes has even been reported 

(Stoneburner 1978). In addition, 

Stoneburner found that hurricaneinduced washover deposits stimulated 

gemination of pine seedlings by 

reducing the competitive shrub 

understory and exposing the mineral 

soil surface. Vogel (1980) hypothesized that hurricanes have replaced 

fire as a dominant perturbation that 

creates proper conditions for slash 

pine establishment. 

In swamp forests (dominated by baldcypress, pondcypress, water tupelo, and 

swamp blackgum), hurricanes are capable 

of defoliating, topping, and overturning trees, but it is the defective and 

hollow trees that usually break, and 

windthrow of these wetland species is 

generally rare (Craighead and Gilbert 

1962, Duever and others 1984, Hook and 

others 1991). Windthrow of bottomland 

species is more comn and may be 

related to shallow rooting in moist, 

soft soil (Gunter and Eleuteris 1973, 

Hedlund 1969). In south Florida, new 

leaf growth was unusually rapid for 

several species of trees and many 

species flowered a second time immediately following Hurricane Donna (1960; 

Vogel 1980). 

One aspect of hurricane-induced rains 

that has generally been overlooked is 

the role that hurricanes have in 

inducing high export of organic matter. 

Day and others (1977) reported that 

Hurricane Carmen (1974) caused litter 

fall to occur two months early in swamp 

forests of the Barataria Basin, 

Louisiana, and that a large pulse of 

carbon, nitrogen, and phosphorus was 

flushed from the area to the Barataria 

estuary following the storm. The 

material exported after the storm 

represented 20-30% of the total export 

for the year and the authors suggested 

that this input was important in 

stimulating the productivity of the 

Barataria estuary. 

HURRICANE HUGO 

Hurricane Hugo made landfall on the 

night of September 21-22, 1989, with 

the eye of the storm passing just north 

of Charleston, South Carolina. 
Estimated maximum sustained winds were 

54 ms-I at Charleston and destructive 

winds continued to do damage 325 km 

inland (Janiskee 1990). Although wind 

damage was widespread, a storm surge 

averaging approximately 3 m above sea 

level also caused major damage, Overall, Hugo was the costliest hurricane 

in history with nearly $7 billion in 

damage on the United States mainland 

alone (Case and Mayfield 1990)- 

The center of the hurricane followed a 

path as shown in Figure 2, causing 

damage to 1.8 million ha of forest 

(Hook and others 1991). This represents more area than that of Hurricane 

Camille (1969), Mount St. Helens 

(1980), and the 1988 Yellowstone fires 

combined. A nine-county area experienced a loss of 70.90% of its older, 

taller timber (Janiskee 1990). The 

most extreme forest damage occurred 

within the area impacted by the 

Moderate damage 

WMespread damage 

Overstory destroyed - Path of center of eye 

eyewall (area of very strong winds 

surrounding the eye of the hurricane), 

and pine and hardwood species exhibited 

little differences in their resistance 

to wind damage (Hook and others 1991). 

Outside of the eyewall, there was 

generally less damage to the bottomland 

and swamp species than to pines (Hook 

and others 1991, Sharitz and Putz 

1990), although in some areas oaks were 

damaged heavily. The major short-term 

effect to bottomland and swamp species 

was the loss of foliage and small 

branches. Sharitz and Putz (1990) also 

reported that trees that had previously 

suffered wind damage were more 

susceptible to new damage, 

In one way, the point of landfall and 

subsequent damage will be very beneficial to the scientific world. Directly 

in the path of the storm was the 

Francis Marion National Forest and the 

Santee Experimental Forest (Figure 3) 

Figure 2--Map of South Carolina showing the path of Hurricane Hugo and the area of 

damage . 
Figure 3--Map of South Carolina showing the location of areas discussed in text in 

relation to the path of Hurricane Hugo. 

where forest managernent/resource 

studies have been underway for over 50 

years. Since the storm, the U.S. 

Department of Agriculture Forest 

Service has implemented a program of 

research to learn about the storm's 

effects on the forest and to develop 

appropriate means to restore this 

ecosystem. Projects include: 

- recovery of wetland functions in 

watersheds, 

- ecophysiological and hydrologic 

studies of wetland forests and 

forest tree species impacted by 

tidal surge, 

- mitigation of salvage logging 

effects on wetland soils and 

wetland site productivity, 
- characterization of storm stress 

effects on trees and subsequent 

attack by insects and disease, 

- recovery of wildlife populations, and 

- wetland hardwood ecophysiology, 

restoration ecology, and 

silviculture. 

Hobcaw Forest, just 90 km northeast of 

Charleston, South Carolina, is another 

area of active research since the 

1960"s. Post-Hugo research efforts by 

Clemson University faculty are focusing on the recovery of wetland forests 

after inundation by storm surge. 

Studies include seedling and watershed 

response to saltwater, natural and 

artificial regeneration of impacted 

areas, productivity and nutrient 

cycling studies, soil and hydrologic 

changes, and modeling efforts. Other 

efforts in the state include long-term 

study plots in the Congaree National 

Swamp Monument (Rebecca Sharitz, 

Savannah River Ecology Laboratory, 

Aiken, South Carolina, pers. corn.) 

and Four Holes Swamp (Norman Brunswig, 

National Audubon Society, Harleyville, 

South Carolina, pers. corn,). 

CONCLUSIONS 

Hurricanes occur frequently and are 

thus a recurring aspect of coastal 

forest development, but their impacts 

have not been studied extensively. 

Only now are scientists beginning to 

recognize the importance of natural 

catastrophes as critical to the 

dynamics of ecosystems (Boucher 1990). 

When considered in the broader context 

of the functioning of coastal ecosystems, hurricanes could be considered a 

periodic disordering stress which 

causes alteration of the biological 

and physical structure, elimination of 

some habitats and creation of others, 

and high material fluxes (Conner and 

others 1989). Since coastal forests 

have developed in areas prone to 

hurricanes, it is likely that these 

forests have developed mechanisms to 

reestablish themselves rapidly 

following disturbance, as has been 

suggested for rain forests (Boucher 

1990). Research efforts initiated 

after Hurricane Hugo will help provide 

a better understanding of how coastal 

forests respond to and recover from 

large scale disturbance. 

BIBLIOGRAPHY 

Baker, S. 1978. Storms, people and 

property in coastal North Carolina. 

University of North Carolina Sea Grant 

Publication VNC-SG-78-15, Raleigh, 

North Carolina, USA. 82 pp. 

Ball, M.M.; Shinn, E.A.; Stockman, R.W. 

1967. The geologic effects of Hurricane 

Donna in south Florida. J. Geology 

75:583-597. 

Boucher, D.H. 1990. rowing back after 

hurricanes. BioScience 40:163-166. 

Case, B.; Mayfield, M. 1990. Atlantic 

hurricane season of 1989. Monthly 

Weather Review 118:1165-1177. 

Conner, W.H.; Day, J.W., Jr.; Baumann, 

R.H.; Randall, J.M. 1989. Influence of 

hurricanes on coastal ecosystems along 

the northern Gulf of Mexico. Wetlands 

Ecol. Manage. 1~45-56. 

Craighead, F.C.; Gilbert, V.C. 1962. 

The effects of Hurricane Donna on the 

vegetation of southern Florida. Q. J. 

Fla. Acad. Sci. 25:l-28. 

Cry, G.W. 1967. Effects of tropical 

cyclone rainfall on the distribution of 

precipitation over the eastern and 

southern United States. U.S. Dept. of 

Commerce, Washington, D.C. ESSA Prof. 

Paper No. 1. 65 pp. 

Day, J.W., Jr.; Butler, T.J.; Conner, 

W.H. 1977, Productivity and nutrient 

export studies in a cypress swamp and 

lake system in Louisiana. In: M.L. 

Wiley, ed., Estuarine Processes, Vol. 

11. pp. 255-269. Academic Press, NY. 

Duever, M.J.; Carlson, J.E.; Riopelle, 

L.A. 1984. Corkscrew Swamp: a virgin 

cypress strand. In: K.C. Ewe1 and H.T. 

Odum, eds., Cypress Swamps. pp. 334- 

348. University of Florida Press, 

Gainesville, FL. 

Dukes, E.K. 1984. The Savannah River 

Plant environment. E.I. du Pont de 

Nemours & Go., DP-1642. Savannah River 

Laboratory, Aiken, SC. 

Flores-Verdugo, F.J.; Day, J.W., Jr.; 

BriseEo-Duefias, R. 1987. Structure, 

litter fall, decomposition, and 

detritus dynamics of mangroves in a 

Mexican coastal lagoon with an 

ephemeral inlet. Mar. Ecol. 35:83-90. 
Gunter, G.; Eleuterius, L.N. 1973. 

Some effects of hurricanes on the 

terrestrial biota, with special 

reference to Camille. Gulf Res. Repts. 

4(2):174-185. 

Harlem, P.W. 1979. Aerial photographic 

interpretation of the historical 

changes in northern Biscayne Bay, 

Florida: 1925 to 1976. Sea Grant Tech. 

Bull. No. 40. 151 pp. 

Hedlund, A. 1969. Hurricane Camille's 

impact on Mississippi timber. Southern 

emn 219(2728):191-192. 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest. J. Coastal Res. SI-8:291-300. 

Janiskee, R.L. 1990. "Storm of the 

century": Hurricane Hugo and its 

impact on South Carolina. Southeastern 

Geographer 30~63-67. 

Lugo, A.E.; Snedaker, S.C. 1974. The 

ecology of mangroves. Ann. Review of 

Ecology and Systematics 5:39-54. 

Lugo, A.E.; Sell, M.; Snedaker, S.C. 

1976. Mangrove ecosystem analysis. 

Pages 113-145 in: Patten, B.C., ed., 

Systems Analysis and Simulation in 

Ecology. Academic Press, New York, 

USA. 

Lugo, A.E.; Applefield, M.; Pool, 

D.J.; McDonald, R.B. 1983. The impact 

of Hurricane David on the forests of 

Dominica. Can. J. For. Res. 13:201- 

211 . 

Sharitz, R.R.; Putz, F.E. 1990. Damage 

from Hurricane Hugo to the Congaree 

Swmp National Hanuunent, Unpublished 

manuscript. 11 pp. 

Simpson, R.H.; Riehl, N. 1981. The 

Hurricane and Its Impact. Louisiana 

State University Press, Baton Rouge, 

Louisiana, USA. 398 pp. 

Stoneburner, D.L. 1978. Evidence of 

hurricane influence on barrier island 

slash pine forests in the northern Gulf 

of Mexico. Am, Mild. Nat, 99:234-237, 

Touliatos, P.; Roth, E. 1971. Ten 

lessons from Camille. J. For. 69:285- 

289. 

Vogel, R.J. 1980. The ecological 

factors that produce perturbationdependent ecosystems. Pages 63-94 in: 

Cairns, J., Jr., ed., The Recovery 

Process in Damaged Ecosystems. Ann 

Arbor Science, MI. 

Weaver, P.L. 1989. Forest changes after 

hurricanes in Puerto Ricofs Luquillo 

mountains. Interciencia 14:181-192. 

Reprinted with permission from Aimlee 

D. Laderman, Editor, Swamp Research 

Center, P.O. Box 689, Woods Hole, MA 

02543. Accepted for publication in 

Coastally Restricted Forests, Oxford 

University Press (In Press). 

Meeder, J.F. 1987. Variable effects of 

hurricanes on the coast and adjacent 

marshes: a problem for land managers. 

Pages 337-374 in: Brodtmann, N.V., 

ed., Fourth Water Quality and Wetlands 

Management Conference Proceedings. 

New Orleans, Louisiana, USA. 
IMPACT AND RECOVERY OF GULF COASTAL FORESTS 

FROM HURRICANE CAMILLE' 

William colvin2 

[Hurricane Camille] was a killer, She 

ranuned onshore in the Bay St, Louis/ 

Pass Christian Area with winds in 

excess of 200 miles an hour, And she 

was pushing a 30-foot wall of water 

that wiped away hundreds of beautiful 

old beachfront homes and thriving 

businesses for a full two blocks back 

from the beach north of Highway 90, 

Before she lost hurricane force wind 

status, she would leave light to heavy 

damage across 15 of the state's 82 

counties (Figure 1). 

Amazingly, the great majority of our 

coastal highway live oaks "stood tall" 

through those fierce winds. They were 

stripped of all their leaves--many of 

them were debarked over a high percentage of their trunks--objects of all 

kinds were entangled in their branches 

or stuck into their main bole. 

In the ten days immediately after 

Camille hit, we (Mississippi Forestry 

Commission) had as many as 35 forestry 

crews performing vital clearing work 

along the coast, all the way from the 

Louisiana line to Biloxi. Well over 

400 man days were used. I well remember that the work became extremely 

dangerous at times, especially in 

areas with downed power lines crisscrossing the woods, People were 

hooking portable generators into their 

house wiring and electricity was 

bleeding back into the main crosscountry lines. It's a miracle that 

some of our people working to clear 

those lines weren't electrocuted! 

Camille spawned a dozen or more 

tornadoes as she traveled inland. I 

l~ditor's Note: This article is a 

synopsis of the author's slide 

presentation at the 72nd Annual 

Meeting of the Appalachian Society of 

American Foresters held at Greenville, 

SC, January 20-22, 1993, 

Z~illiam Colvin, Mississippi Forestry 

Conunission, Jackson, MS. 

particularly remember seeing several 

quarter-mile-wide paths crossing 1-59 

in Pearl River County. One funnel 

wiped out a tung nut orchard, In fact, 

the winds of Camille destroyed practically all of south Mississippi's tung 

orchards. But I visited the same area 

just two weeks ago to get a few "after" 

slides, and came upon Tung Ridge Ranch, 

A man from New York has begun an effort 

to re-start the tung oil business in 

Mississippi. They are planting several 

hundred acres back to tung trees and 

hope to bring that industry back to 

life--at not more than about 25 percent 

of its pre-Camille size, Keeping production at a reduced level will help 

hold prices at a level that will make 

the business profitable in today's 

world of synthetic paint additives, say 

those entrepreneurs. They are currently payikg two dollars-per bushel 

for tuns nuts collected by local people 

from remnant trees left along hedgerows 

and protected places after Camille. 

Before we leave Hancock Tower [in 

Hancock County], here's one more 

before/after sequence, This first shot 

was taken looking due west from the 

tower over the top of the quonset hut. 

As far as you could see, there were 

trees on the ground, I have no sure 

answer to why those trees you see 

standing were left by the wind. We 

looked closely at the base of some of 

these trees trying to figure it out. 

Apparently, trees on deep, sandy soils 

send their roots deeper for moisture 

and were anchored better--just a 

theory--who knows? It was interesting 

to see a thing we nicknamed the "zippo 

effect" at the base of many of these 

residual trees. You could stick a 

zippo lighter (the wide way) down below 

ground level next to these trees-- 

apparently this "wallowing out" around 

the base of the tree was caused by the 

winds fiercely whipping the trees in 

all directions, I'm sure you could 

find the same thing here in the Hugo 

area. Did this tear the root system 

apart? Apparently not to the extent 
S IMPSON SMfTH C LA RXE 

JA S PER 

Figure 1--The extent of Hurricane Camille. 
that it couldn't develop replacement 

roots to maintain the balance between 

the crow and the roots, Rem 

these trees also lost some crown to 

the winds. 

I should note here that many landowners were so discouraged by the 

er destruction wrought by Camille 

that they waited a long the to 

replant. Many didn't replant, 

choosing instead to let the ravaged 

area revert to woods pasture or to 

sell their property to real estate 

speculators. 

[Figure 2 illustrates the] extent of 

the overall timber losses we suffered 

from Camille. In 1967, we had about a 

billion cubic feet of pine growing 

stock in the nine counties hit hardest 

by Camille and about 435 million cubic 

feet of hardwood. Ten years later the 

forest survey shows we had only 868 

million cubic feet of pine and apparently our hardwood component had 

jumped to about 612 million--talk 

about a hardwood problemf Another 

decade later, we see pine growing 

stock making a comeback and hardwood 

dropping back somewhat. The 1987 

survey (combining the figures for nine 

counties) shows that we are back above 

our pre-Camille stocking of pine 

growing stock with hardwood growing 

stock continuing to increase. 

GROWING STOCK. 

Nine Hurricane Camille Damaged 

Counties 

Survey Pine Hardwood 

Year (million (million 

cu. ft.) cu. ft.) 

Figure 2--Forest growing stock in 

Hurricane Camille damaged counties, 

I've watched that area be healed by 

time and by landowners with vision who 

picked themselves up after the hurricane (some sooner than others) and did 

what it took to get their timberland 

back into production. As I drove 

through the lower half of those nine 

hardest hit counties a couple of weeks 

ago, I searched hard for a scene that 

would show clear signs of Hurricane 

Camille" savagery in 1969, I honestly 

could find none, All those 1969 

vintage trees that had been bowed 

severely, snapped or twisted off, had 

long since either been salvaged, 

straightened back up on their own, or 

been harvested. As far as the Gulf 

Coast forest is concerned, I think it 

is fully recovered. 

East of these nine Camille-scarred 

counties, where slightly less damaging 

Hurricane Frederic visited us in 1979, 

you can still find a few areas (particularly in the hardwood types) that 

show the effects of that storxn. I 

fully expect that by the turn of the 

century, you won't be able to see any 

appreciable signs of Frederic's meanness either. 

[Figure 31 shows the timber harvesting 

that has taken place in the nine-county 

area I've been discussing, I've 

included 1968 as a base year. The 

Camille effect shows up first, of 

course, in 1969 calendar year harvest 

records. It stays up around an average 

sf 185 million board feet of sawtimber 

until five years after Camille, then 

drops back to the pre-Camille level and 

below in 1988 and 1990. I think maybe 

a lot of "alive, but at-risk" sawtimber 

was being cut from 1970 to 1974. This 

would have raised our salvage figures 

somewhat, but we stopped keeping track 

of salvage after August 1970, so we 

don't know for sure just how much, I 

suspect that the closing of several 

sawmill operations in the Gulf Coast 

area in recent years is being reflected 

in those 1988 and 1990 figures. 

TIMBER HARVEST 1968-1990 

Nine Hurricane Camille Damaged Counties 

Year 

year 

1968 

1969 

1970 **** 

1974 

1978 

1988 

1990 

Sawlogs 

(mm bd* ft.) 

(mm bd. ft.) 

140.7 

191.8 

185.8 ***** 

142.0 

144.5 

136.2 

125.0 

PU lpwood 

( cords ) 

~ulpwood 

454,921 

738,976 

893,597 *** 

459,697 

479,990 

732,370 

891,640 

Figure 3--Timber harvest in Hurricane 

Camille damaged counties. 
Pulpwood harvesting since Camille has 

followed a similar pattern, peaking a 

little earlier, in 1970, and then 

dropping sharply down to pre-Camille 

levels in 1974, then rising to new 

heights in 1988 and '89 as raw prices 

surged and many stands planted 

ately following Camille reached full 

pulpwood and two-by-four (chip and 

saw) size. 

That's enough with the numbers. They 

tell a deceptively simple story of 

forest recovery. I certainly don't 

claim to have thoroughly looked at all 

the complex factors that went into the 

compilation of these figures. It 

would take months of research to 

really factor in all the reasons for 

these totals. Suffice it to say that 

forest disasters like Camille and 

Frederic and Hugo are no match for the 

healing hand of nature, the determined 

action of professional foresters with 

know-how, coupled with the will to 

recoup-and-recover of the great 

majority of landowners. 

Reprinted with permission from 

Hurricane Hugo r Recovering from 

Disaster, Proceedings 724 Annual 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Foresters, Greenville, SC, 

Jan. 20-22, 1993, p. 56-64. Dr. Vernon 

L. Robinson, Sec-Treas, 2557 

Abbott Circle, Seneca, SC 29678. 
DAMAGE ASSESSMENTS 
Planninu 

Abstract--The South Carolina Forestry Commission prepared 

for Hurricane Hugo by issuing information on care of stormtrees, by checking heavy and comunications equipnd by helping to staff Emergency Preparedness 

the night of the storm, During the immediate 

th, personnel and equipment cleared roads for 

traffic and an aerial forest damage survey was conducted. 

Long-range efforts included application to FEm for fire 

prevention/control funding assistance and formation of the 

Governor's Forest Disaster Salvage Council. 

Preparation for Hurricane Hugo's 

impact to South Carolina actually 

began several days prior to the 

storm's arrival. As soon as weather 

forecasts indicated the storm was 

likely to come ashore in South 

Carolina our Infomation and Education 

Section prepared and distributed to 

coastal districts a brochure on handling storm damaged yard trees entitled 

YOUR TREES AFTER HUGO. Additionally, 

we checked all motorized and communications equipment to see that it was 

well protected and as functional as 

possible. We also reviewed the 

agency's responsibility regarding our 

role in Emergency Preparedness and 

pre-selected personnel to be assigned 

to field and state headquarters of the 

Emergency Preparedness offices. 

On late Thursday, September 21, 1989, 

Hugo hit South Carolina. As it moved 

inland, our communication system 

became spotty and it became obvious we 

were experiencing an extremely 

destructive and far-reaching storm. 

By daylight on the 22nd, Comission 

personnel living in the stormfs path 

began assisting the public at the 

' A presentation at the 72nd Annual 

Meeting of the Appalachian Society of 

American Foresters held at Greenville, 

S. C,, on January 20-22, 1993, 

Assistant State Forester, South 

Carolina Forestry Commission, P.0, Box 

21707, Columbia, S. C 29221. 

local level. In spite of suffering 

damage to themselves, we estimate some 

155 Commission personnel with 89 tractoss (fire suppression units) were 

assisting. At the same time the state 

headquarters office began to mobilize 

personnel from four districts, two 

state forests and two nurseries. Dispatch of these personnel began almost 

immediately and continued through the 

next few days. Also, a Commission 

fixed-wing plane was dispatched to 

determine road conditions to help 

determine job assignments. 

Within two days the agency had roughly 

240 people (40 percent of its workforce) working in the recovery effort. 

Most of this effort involved opening 

roads and highways to allow travel. 

This road work had been pre-assigned to 

the Commission in the State's Disaster 

Plan. 

In our early dispatch of personnel into 

the stormfs area, several mistakes were 

made. We did not fully recognize that 

food, water, shelter and fuel would be 

scarce to unavailable in many areas. 

We had to do some rapid regrouping in 

order to get our personnel the items to 

allow them to be self sufficient. The 

main lesson learned is that you do not 

want to impose on the local population 

in any way during this type situation. 

Many of our personnel worked in the 

area for several weeks. Everyone did 

so willingly and felt that they were 

highly appreciated by the local 

population. 
One major assignment the Comission 

ass-& was to conduct a survey to 

ge to the timber 

resource. This survey began approximtely eight hours after the stom 

passed through and was completed in 

four days. 

Acting State Forester Jack Gould 

declared a Forest Disaster on 

Saturday, the 23rd, which gave the 

Comission official authority to (1) 

ge survey, (2) apply 

Comission resources on both public 

and private lands, (3) develop a 

salvage and utilization plan, and (4) 

coordinate all forestry interests. 

To conduct the timber damage survey we 

had used four-passenger high-wing 

aircraft carrying a pilot and two 

observers. The planes flew northsouth flight lines predetermined on 

county maps (scale 1" = 1 mile) at 

eight-mile intervals. Three damage 

classes (light-5%, moderate-25%, and 

heavy-60%) were used for softwood and 

three for hardwood (light-lo%, 

moderate-358, and heavy-70%). As the 

planes flew the lines, using Loran-C 

guidance, the observers documented 

damage. By late Monday we completed 

the required flying and computed the 

data using a computer program set up 

by one of our staff foresters. This 

data was used to determine a total 

damage percent for each county. This 

percent was applied to the 1986 South 

Carolina Forest Inventory Analysis 

(FIA) data for that county. A comparison of the survey results with an 

FIA survey completed several months 

following the storm is as follows: 

Commission Survey FIA Survey 

Acres Impacted 4,435,363 4,505,700 

Hardwood Sawtimber (WBF) 3,456,595 3,984,000 

Softwood Sawtimber (MBF) 3,304,666 6,319,000 

value3 $1,040,890,335 $1,181,457,000 

It is very obvious that our Commission 

Survey badly underestimated the softwood sawtimber. We became aware that 

this had probably happened as we spent 

time on the ground following the 

aerial survey. In view of the rapid 

need to get d ge figures we did not 

take enough time to determine correct 

damage categories. Overall, however, 

we feel our technique is a good system 

when you are faced with "cruising" 4.5 

million acres in less than four days. 

On Monday, day four, Acting State 

Forester Gould and the Chai 

South Carolina Foresters Council, Ken 

Bailey, set up a meeting of the Council 

for the following Thursday. This Council is made up of representatives from 

industry, the U. S. Forest Semice, 

Soil Conservation Service, the St C. 

Forestry Association, Consulting 

Foresters, Clemson University and the 

Forestry Comission. This group gave 

Gould a broad segment of the forestry 

cornunity that he could call upon to 

address the problems caused by Hugo. 

On Tuesday Governor Carroll Campbell 

used the timber survey damage information in a Press Conference. This gave 

clout to the fact that the forest land 

suffered a major loss. Up until this 

time it had been difficult to get the 

attention of the news media away from 

the immediate coastal problems, 

On Wednesday the 27th, we had our first 

encounter with the Federal Emergency 

Management Agency (FEMA). We recognized we had three major problems: (1) 

ediate problem with timber salvage and utilization, (2) within a few 

weeks or months we could encounter the 

most severe forest fire situation ever 

encountered in the South, and (3) over 

the long haul we had a massive reforestation effort on our hands. With the 

help of the U. S. Forest Service and 

the Governor's office, we negotiated 

for well over a month before FEMA 

finally agreed to assist us with our 

forest fire effort. They came through 

in a major way and have continued to 

assist into our fourth fire season. 

They have supported a massive fire 

prevention campaign, two fixed-wing 

airtankers, additional observation 

aircraft and the construction of 

roughly 4,000 miles of firebreaks 

located in high risk areas, 

On Thursday the 28thf the Foresters 

council met. Out of the efforts of 

this group the Governor was persuaded 

to declare an Executive Order creating 

the Governor's Forest Disaster Salvage 

Council, This Council, with Scott 

Wallinger as Chairman and Mac Lupold as 

Executive Director, coordinated a 

massive effort to utilize as much of 

the impacted resource as possible, 

Value damage includes pulpwood and 

damage to precommercial stands, 

SUIJ;IMARP 

I don't think anyone or any group can 

ever totally prepare and respond to an 
ency like Hurrica 

Carolina did a n 

and came up short 

ry, when faced by a disaster of 

this type, X suggest the following: 

1, Get all co~unications up to 

speed and be prepared for backup 

prior to the sto 

2, Count on the situation being 

worse than predicted, 

3. Assume utility services in the 

impacted area will be out an 

extended period, 

4, Have a generic Forest Disaster 

Plan in advance. 

5, Have an active body like South 

Carolina'e Foresters Council, 

6, Get the Governor's Office 

involved in the situation as 

rapidly as possible, 

7, Prepare personnel dispatched ta 

assist in the early on recovery 

effort to be self-sufficient. 

This my include food, water, 

fuel and basic shelter. 

8, Be prepared to work night and day 

for an extended time, 

Reprinted with permission from 

Hurricane Hugo t Recovering from 

Disaster, Proceedings 72nd Annual 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Forersters, Greenville, SC, 

Jan, 20-22, 1993. Dr. Vernon L, 

Robinson, Sec-Treas, 2557 Abbott 

Circle, Seneca, SC 29678. 
DAMAGED 

Abstract--All timber salvage efforts following natural 

disasters, including Hugo, should address these issues: 

(1) realistic damage assessment, (2) obtain broad-base 

support, (3) representative organizational structure, 

(4) quick response database of businesses and technical 

data, (5) identify usable material in damaged trees, 

(6) logging techniques and equipment modifications, (7) 

weather effects after storm, (8) use of wet log storage, 

(9) communications effort maybe the most important task, 

(10) government relations, (11) value timely statistics and 

attitude monitoring and (12) salvage time is limited. 

After nine months, 387 million cubic feet had been salvaged 

of the 3.5 billion estimated damaged (15.5% versus goal of 

25%). Over 100% of the pine goal was salvaged with only 

12% of the hardwoods. Good forest management is a mediator 

of damage exposure and salvage value received. Both state 

and federal sources of funds to support the Hugo salvage 

function were non-existent. The Hugo timber salvage was 

performed in the woods by many thousands of landowners, 

consultants, land managers, procurement foresters, loggers, 

equipment suppliers and primary wood-using industries 

working together. 

INTRODUCTION 

The salvage of Hugo-damaged trees in 

1989-90 for the maximum volume and 

value to the forest landowners for 

conversion into solid wood and paper 

products in South Carolina ceased just 

nine months following the storm. I 

believe the long-term salvage effort 

on nearly 1/3 of SCts forested acreage 

is still in its infancy. For the most 

part I will address the actual nine 

months of timber salvage, but reserve 

the right to make a few comments on 

the future, the fact that good forest 

management pays and forestry's 

communication/education status with 

the general public. I want to thank 

John Purvis for including the ETV tape 

A paper presented at the 72nd Annual 

Meeting of the Appalachian Society of 

American Foresters held at Greenville, 

SC, on January 20-22, 1993. * H. M. Lupold, Manager, Manufacturing 

Services, Wood Products, Federal Paper 

Board, Co., Inc., Riegelwood, NC. 

Executive Secretary, Governor's Forest 

Disaster Salvage Council, 1989-90. 

on the salvage in his presentation. 

You now have a feel for the woods 

condition and the magnitude of the 

problem. This allows me time to 

critique what we did and perhaps you 

might think about your own situation 

and possible forest disaster/salvage 

contingencies. 

DAMAGE ASSESSMENT 

To best relate the salvage efforts, I 

have selected twelve topics to discuss 

in some detail. The first of these is 

the "damage assessment" which Wray 

Freeman has so well presented. The 

outstanding thoroughness and timeliness 

of the SC Forestry Commission data 

assisted in gaining political, industry, agency and other forest community 

support. The volume, location and 

extent of damage assisted in forming 

the salvage committees, communication 

message, individual industry procurement policies, forest management 

approaches, salvage goals, and on and 

on. Certainly without the facts, an 

effective salvage program will never 

succeed. 
STROINQ SUPPORT BASE 

Bugo's $1 billion plus t 

mandated the highest political support 

by using the Governor's Office to open 

as many doors as possible. without-a 

my seeond sale consolidation 

of effort that may best sene the 

landowners and pr ry mod-using 

industries is lost. men you focus on 

a specific geographic area and consumer products, activities must be 

handled through a governmental sanctioned entity as far as anti-trust 

issues. An attorney was present from 

the State Consumer Affairs Office at 

most of our meetings. The salvage 

phase in the woods and at the mills 

necessitated land manager, logger and 

industry involvment because these 

functions are not part of the daily 

activities nor expertise of the 

governmental agencies. The SC 

Forestry Association assumed the lead 

role in organizing, monitoring and 

financing the Salvage Council's 

efforts. 

ORG~IZATION~ STRUCmW 

The extent of damage dictates the type 

of salvage structure required, be it 

an intensified use of existing groups 

or a formal structure with full-time 

emphasis and/or personnel. "Oraanizational structure" then, is the third 

salvage point, The objective of the 

Salvage Council was to recover the 

maximum volume and value to the forest 

landowners, To accomplish this the 

council formed four working committees: Utilization, Information, 

Statistics and Monitoring and 

Governmental Affairs, 

"Move the Wood" - Utilization Commit- 

- tee - Comprised landowners, managers, 

consultants, loggers, industry--solid 

wood and paper mills--hardwood and 

pine, equipment suppliers, railroad 

and trucking experts and several wood 

technologists, At one meeting 31 of 

ers were present. Fantast and support, Four subcornittees were developed specifically 

for the salvage effort, Utilization 

concentrated on the logging and milling activities within the salvage area 

and throughout SC. The 10 or so key 

people that usually control 80-85% of 

a statees procurment volume must be 

part of these committees, Out-of- 

- state insured that sawmills and pulp 

mills in other states knew of the 

salvage probl , opportunities, plans 

and export potentials, rans sport at ion 

concentrated on log trucks, rail, 

overseas shipping and barge methods, 

Storacze placed aphasis on wet storage 

of logs and look& at rough green and 

tion Out" - Info 

- tee - Basically used the Comunications 

ttes of the SCFA, Used existing - ttee structures when possible, We 

mented with PR personnel from the 

Farm Bureau, ASGS, SCS, Cl 

Dept of Agriculture. Most of the daily 

activities were centered at Cl-son 

Extension with a full-time writer who 

focused on the public and other interest group media, 

"Remove Barriers" - Government Affairs 

Committee, Comprised the SCFA Governmental Cornittee with the addition of 

the 2 Senators and 2 Representatives 

appointed to the Salvage Council. 

"Information In" - Statistics and 

Monitorina. Utilized personnel at the 

SC Forestry Commission, plus industry 

and consultants to track weekly salvage 

volumes, wet storage status and 

opinions from the field of salvage 

progress. 

The Executive Committee performed most 

of the detail activities usinq a 

smaller group, represented by-the 

committee chairmen, Funding was 

provided up-front by the SC Forestry 

Association and later $17,000 of the 

$25,000 expended was reimbursed from 

various Hugo relief funds in the 

Governor's Office. Expenses of the 

Forestry Commission for mailings, 

office space and phone, and at Clemson 

Extension for media expense were borne 

by each of these groups, 

DATABASES/TECBNIW LITERATUm 

Most of the committee early functions 

depended upon obtaining information or 

technical data from a variety of groups 

and then distributing this data to the 

same or other groups about all facets 

of the salvage* No comprehensive 

computer database of all these organizations existed. My 4th point concerns 

"orsanizational and- individual databases and technical literature 

libraries", To put it bluntly, will 

some entity step forward and take on 

the responsibility to prepare a standard format where all the forestrylwood 

product organizations and landowners 

throughout the southeast can be 

included and whatever sort is required 

can be quickly retrieved. This would 

have saved us 4 to 5 weeks, Research 

data and reports on past salvages need 
to be compiled and located in each 

state, 

BE USED? 

first questions asked is, 

"what can be used" by the sawmills, 

od plants and pulp mills, this 

my 5th and longest discussion 

abut the salvage, Xn the woods 

ed trees were usually found in 

three basic conditions: 

- Blodowns, with some of the root 

ball still in place, 

- Snap offs, at 3' to into the 

tops, and 

- Leaners, of all angles, 

From Camille {Mississippi-Alabm) in 

1969, the latest damage comparison to 

Hugo, those involved advised they were 

able to leave their blowdowns until 

last, and most lived through the 

summer with salvage up to a year 

later, With Hugo, pine blowdowns 

began to die in mid to late spring. 

Hardwoods were not far behind, Perhaps the roots were more severely 

stretched and damaged, the downing 

impact so much greater than with 

Camille. We were really counting on 

the blown over hardwoods to live for 

2-3 years, 

The completely broken-off trees, 

mostly pine, were reduced in most 

instances in value from sawtimber to 

pulpwood. Snags and broken tops could 

be used for sawlogs, if all the broken 

section and any other visible defects 

were cut out. A rule of thumb from 

Camille sawmillers held true in Hugo: 

on broken ends follow the visible 

split to its end and then go an additional 4'-6' and cut the stem. Even 

with this trim-back procedure, the 

chance of splits, shake and timber or 

compression breaks were possible, In 

the video, Chip Ingram showed you the 

results of a compression or timber 

break, 

A reduction in delivered prices for 

logs at the mill discounted for the 

chance of splits and breaks occurring 

in the lumber, Since hurricanes occur 

in the fall, blue stain and insects do 

not become a problem until spring. 

Toward the end, the pine pulpwood 

utilization indicators were--if the 

brown needles did not drop off or the 

bark fall off when you hit it with 

your foot, then use it. 

Host of the leaners were living when 

the USFS survey categorized the 

gelrisk classes 2 and 3, which were 

the least severe. Today, I see few 

ers still living, ff so, the 

ge value could reach $2 billion. 

The current Forest Service survey in 

progress will quantify what type tree 

ulthately dies from a hurricane of 

Hugo" intensity, 

Nearly 30 separate mailings over the 

9-month salvage were sent by the Exeeutive Secretary with outstanding assistance from the Forestry C 

over 500 persons or 

of the current info 

about the salvage. About 400 different 

buy-sell-want type interests were 

advertised in the "classified" listings 

as submitted to the Council, The 

Council encouraged wood-using industries within the damaged area, and in 

Georgia and North Carolina when possible, to divert from cutting nondamaged stands and concentrate on the 

salvage, Concerns of various landowners around the Francis Marion were 

discussed with the USFS with the intent 

to minimize the private land-owners 

salvage problems in that area, 

The 27% salvage results of Camille were 

reviewed in an effort to establish a 

Hugo goal. Hugo involved seven times 

more volume. Several industry procurement personnel participated in evaluating the potential salvage volumes 

using two different approaches: 

1. by analyzing what could be done 

from the woods and logging side 

with maximum out-of-statelexport 

consumption and normal weather 

conditions, and 

2, looking at the salvage from a 

manufacturing capacity, 2 years 

pine and 15 years hardwood on the 

ground. 

A blend of these two analyses determined the pine and hardwood levels, a 

25% salvage goal of the total cubic 

feet . Most of us felt just after the storm, 

as Eddie Drayton mentioned in the 

video, that the hardwoods could have 

lasted 2 to 3 years since so many were 

blown over with a good portion of the 

root system still intact, 

LOGGING 

"Logging", item #6, was a completely 

new chapter in timber harvesting as 

evident in the video. Tree shears were 

almost useless, Crews needed a chain 
saw per man to trim and cut through the entanglement to get to each snag, 

leaner or broken top. Production 

rates were reduced 1/2 to 113 of 

1 cut and skid. This resulted in 

ond reduction factor in landowner 

stumpage. A high percentage of SC 

loggers were concentrated in the 

salvage area and the reduced productivity could not support the full 

mnufacturing capacity, The 1 

od and paper mark 

ted by Bugo and r 

strong during the salvage period and 

the bottom did not occur until late 

1990. To meet the favorable market 

and mi11 capacities, additional outof-state loggers were secured. Tying 

up a logger for your specific needs 

was the name of the game. The legal 

road weight on log trucks was raised 

from 80,000f to 90,000# and was 

extended by the Governor two times 

until March 15th ("Hugo Timber Haulw 

sticker in video). Some of Hugo's 

broken mess could have been logged on 

the drier sites using short-wood 

crews, but the paper mills had 

converted almost completely to tree 

length with only a few out-of-state 

operations taking the 5' lengths. 

Only a few shortwood woodyards were 

reactivated. Shortwood rail cars were 

in excess. Be prepared for change-- 

Camille, 20 years earlier, was a 

short-wood operation. The hardest hit 

mills from Hugo logging were the 

single species hardwood operations 

that usually depend on a large logger 

to perform separations on the log deck 

for their needs. 

WJZATHIER CONDITIONS 

One factor controls the volume, 

species and length of time in a 

salvage more than any other, and that 

is the "WEATHER", point #7. It also 

controlled the attendance at this 

meeting, most mills have few to no 

logs. Hugo was considered a dry 

hurricane, very little rainfall prior 

to and during the storm. Once the 

family concerns and basic infrastructure of services and access were 

restored, the rains had set in and the 

15 inches in Sept er and October 

fully saturated s s throughout the 

coastal plain. Few trees remained to 

suck up water ing the nonnal 

October to Ilec er growth period. 

With loggers at half capacity due to 

the twisted mess, the rain-soaked soil 

severely limited usable logging sites. 

This limited logging capacity was 

apparent from November through 

January. Here again, if the timber 

could not be logged, it was worth 

nothing and on sites that could be, the 

landowner experienced additional stumpage discount. Landowners with deep 

sandy soils fared much better than the 

wet-site forest owners. As l a t e a s May 

and June, loggers were unsuccessful in 

harvesting tracts with 10 to 20 MBF/ 

acre due to soils still saturated, The 

black-water swamps were flooded much of 

the 9-month salvage period; and as is 

the normal case, once the red rivers 

subsided, some logging occurred in the 

Congaree, Hateree, Santee and Pee Dee 

Rivers which were really hit hard with 

blowdowns. These flooded swamps are 

the primary reason hardwoods were 

limited to only a 3.3 percent salvage 

performance. Pine reached 40 percent 

in 9 months (of the total CF damaged). 

We worked closely with SCS to clear 

drainage ditches. For forestry's 

benefit they did not move fast enough, 

nor complete enough distance. Most 

projects stopped before they got to the 

forested acreage. 

The combination of twisted damage and 

rain-soaked soils, despite the more 

than doubling of loggers in the area, 

limited the delivery of logs to primary 

mills to the extent they never created 

any excess until spring. Only 8 

percent of the salvage was shipped outof-state during the first three months 

and limited wet storage was initiated. 

Despite exerted efforts to ship logs, 

rough green lumber and chips out-ofstate or for export, the weather essentially restricted the logged volume for 

local or SC consumption. Since SCfs 

state ports are not traditional log, 

pole and lumber facilities, the port 

charges at two to three times Savannah 

and Mobile discouraged export, plus 

they were not willing to give up container space for wood products. Extra 

wide tires to improve flotation, helicopters (video), horses, oxen, etc. 

were all tried to escape the wet 

ground. By April we began to discourage the use of out-of-state loggers. 

If the rains weren't enough, then the 

80-degree weather in March and 90- 

degree in April told the tale that 

ended the salvage earlier than Camille. 

The final salvage chapter always ends 

with stain and borers in both the pine 

and hardwoods. The warm spring accelerated the stain presence and essentially ceased the salvage in June. 

Today, stain in lumber, although 

accepted in the SPIB grade rule, is not 

accepted by the treaters and the 

homeowner, DIY market f rorn an 

appearance standpoint. 
HET STOEUI,GE OF LOGS 

When your loggers aren't bringing in 

excess logs you tend not to think 

about "wet storaqe", emphasis #8. 

Most east side mills have had limited 

experience with wet log storage and 

therefore respond at the last possible 

moment. In late December all the 

technical publications in print on wet 

storage and a summary of the SC situation was distributed, A seminar with 

DHEC and USFS experts was held in 

January. DHEC variance allowed for 

immediate use of a properly designed 

site with subsequent reporting. This 

saved a normal 6 months application 

time. 

By April 46 potential sites had been 

identified to store 150 million BF and 

63,000 cords pine and hardwood and if 

fully filled would be worth $30 

million at pre-Hugo values. Several 

excellent studies since Hugo by 

Clemson and the USFS are available on 

wet storage design and product placement and in lumber and veneer quality. 

These publications should be selling 

at a premium since many mills in the 

Carolinas are talking about wet 

storage capability in late 1993 and 

1994. Log storage is really a simple 

operation--the key is, to store only 

good quality logs!! l ! 

In 1938, after the New England hurricane, 63 log pond sites were leased by 

the government to hold 500 million BF 

of timber to be purchased for resale 

to industry at a later date. That 

storm had the same volume of white 

pine damaged as Hugo with southern 

pine. We were totally unsuccessful in 

obtaining any federal or state funding 

for log storage or for loggers. 

If a tremendous surplus of logs had 

been available in early 1990, I 

believe our log-storage situation may 

have been completely different. A 

more visible response would have been 

made to satisfy this opportunity to 

provide value to the landowners and 

have logs for processing. You must 

place emphasis and pressure on areas 

with specific problems and support 

with factual impacts, The Santee 

Cooper lakes and sites on Francis 

Marion National Forest were investigated as potential government funded 

projects. 

CO~UISIICATIONS 

My 9th point is "Communications". 

Clemson Extension provided special 

amphasis and funding toward the 

comunications effort, Several technical publications were prepared about 

er and landowner meetings 

were held throughout the area. Special 

feature articles were released to the 

news media, It's sad when the newspapers no longer want to publish the 

plight of the landowner who may have 

lost tens and even hundreds of thousand 

of dollars, but jump at the opportunity 

to present something new or a single 

incident like horse logging, SC ETV 

assisted in several programs and video 

features. As hindsight, I believe the 

Council as a whole could have done more 

in these areas: 

- participated on more radio and TV 

talk shows, 

- weekly face-to-face contact with 

newspapers from Charleston to 

Charlotte, 

- feature writers need to be 

located in the salvage area at 

least in the case of a major 

storm like Hugo, 

- stronger message to private 

landowners to seek professional 

advice, and 

- stronger appeal to the general 

public, if that's possible. 

GOVERNMIENT AFFAIRS 

"Government Affairs", item #lo, 

obtained the higher truck weight and 

DHEC log storage variance early on. 

Attempts in Congress for legislation on 

reforestation, a CRP program, a casualty tax basis allowance, forest survey 

expense and storage funding failed to 

pass just prior to Thanksgiving. 

Several tours of the salvage were made 

for the Governor, Legislative Committees, FEMA and the USFS Washington 

office. FEMA was never supportive of 

specific funds for salvage operations. 

We did assist the Forestry Commission 

in its efforts for fire prevention and 

presuppression. Other attempts in 

Congress failed on a special crop loss 

(for timber) provision and further 

casualty tax allowances (most landowners had no basis in their timber and 

the loss was 100% out-of-pocket), With 

a shortage of state funds, the General 

Assembly never could justify allowances 

for a state casualty tax loss provision, ITC for reforestation, or specific funding for the salvage council. 

Just yesterday at a Forestry Association meeting, we discussed possible 
forest disaster (hurricanes, tornadoes 

and excessive wet weather) legislation 

that would autoraetically fall in place 

for low-interest loans and maybe a 25- 

to 50-basis casualty loss allowance. 

r salvage program should not 

sit back and wait on special government funding. All available state 

ts will be toward restoring the 

1 infrastructure, The salvage, 

ident of the lack of success we 

had in obtaining special funds or tax 

provisions, actually boils down to 

landowners, managers, loggers and 

ry manufacturers working 

together. 

STATISTICS MONITORING 

"Statistics and Monitorinq", point 

#11, is essential to track and 

evaluate the salvage progress. The 

adjusted volume evaluated all mills 

reporting, including out-of-state, 

with an 85 percent hard number 

participation. Industry finds this 

type information very useful during 

the salvage. I've included so far 

several statistical findings, here are 

some others: 

- After 9 months, salvaged 387 

million CF of 2.5 billion 

damaged, 15.5%. 62% of our 25% 

goal. The USFS Survey will tell 

the real story--volume damaged, 

salvaged and what type risk 

condition ultimately dies. 

- 10.1 percent shipped out-ofstate 

- Softwood sawtimber 

797 MMBF 100% goal 

Softwood pulpwood 

2.1 million cds 107% " 

Hardwood sawtimber 

64 MMBF 10% " 

Hardwood pulpwood 

508 thousand cds 15% " 

- Source, minimal accuracy: 

Private 49%, industry, 13%, 

goverment 18%, unknown 20%. 

LENGTE OF TIME 

My final and 12th coment is "lensth 

of timew. Damaged timber is a perish- able product. All of the factors I've 

mentioned above are constantly closing 

in on your efforts. The Council tried 

to take a can do approach--no time for 

lengthy studies or reports, but rather 

each day inform as many people in the 

field as possible of the opportunities, possible solutions, where to go 

for advice, and status of the salvage. 

SAiLVAblEil: MEDf 

I have intentionally left out several 

salvage pointers because they relate 

directly to the status of forest 

gement being practiced on any 

er tract at the time of a disaster 

--not just Hugo. Good forest ma 

mnt is an ongoing mediator of d 

exposure. Just think: problsales mean painted property lines with 

wide firebreaks; basic access; adequate culverts; maybe some gravel or 

ROC; sufficient drainage to remove 

excess water; being active in t 

sales means buyer contacts with early 

negotiations maybe at 85-95% pre-Hugo 

prices, rather than less than 50% 

later; managed smaller acreage stands; 

less exposure; longer interval for 

thinned trees to stiffen; no slickbark, old growth--a Hugo nemesis; 

performed control burning, hardwood 

reduction, good seed bed condition-- 

thus adequate natural regeneration. 

Observe much of Francis Marion today 

and lower Colleton and Charleston 

counties from Gracie in 1959. Thus, 

limited salvage volume at seduced 

price. Bulk of stands remain to manage 

for excellent future markets. Good 

mnagment paysl 

IMMEDIATE NEEDS OF PEOPLE AND 

INFRASTRUCTURE: GREATER THAN 

TIMBER LOSS 

With Hugo the Council approached the 

Governor, the Legislature, the US 

Congress and the people of SC with 

these facts: 

- $1 billion loss in timber and 

could possibly double when all 

the mortality is known, less than 

$100 million in salvage value. 

- Over $10 billion of potential 

forest products sales of lumber 

and paper will rot in the woods 

of SC . - SCfs ultimate loss could exceed 

$40 billion using all the 

multipliers in the economy. 

er Budget & Control 

Board estimate illustrated that 

timber was 75% of Sets unrecoverable Hugo loss. 

These unbelievable facts did little to 

bring about any viable programs to 

assist the private landowner. Once the 

San Francisco earthquake occurred our 

efforts in Washington conrpletely died. 
It is critical that the public understands what we are all abut, appreciates the wood and paper products they 

depend on daily, and we link the 

forest resource and our management 

activities to their need. The current 

efforts of the state Forestry Association and Comissions must be continued and expanded. With all 

disasters the iate aphasis will 

be toward people needs and cornunity 

infrastructure, not on forest salvage 

and renewal which are more long-term 

situations. 

The Salvage Council did not cut a 

single tree or haul any loads of logs. 

This was done by the efforts of tens 

of thousands of landowners, consultants, loggers, mill people, equipment 

suppliers, etc. I thank all of them 

for their support to the Council. 

Today we as foresters must take this 

tract called, "South Carolinaw and 

tvne out the state's forest and ask 

th; question what are we going to do 

with this one area comprising 36% of 

the state. It's a unique and different type of problem, Landowners and 

industry are going to suffer even more 

if we don't approach it as a special 

problem. The Foresters Council and/or 

the Salvage Council following the 

release of the new forest survey data 

must irmnediately address what most 

people fear as a worst case scenario 

for SC, 

The stataent of Sestt Wallinger, 

chairman of the Salvage Council, about 

the salvage efforts in 1989 still apply 

today in 1993 to the current Hugodamaged forest condition - "Seeking 

Unprecedented Solutions To 

Unprecedented Challenqes". 

Reprinted with permission from 

Hurricane Hugo: Recovering from 

Disaster, Proceedings 72nd Annual 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Foresters, Greenville, SC, 

Jan. 20-22, 1993. Dr. Vernon L. 

Robinson, Sec-Treas, 2557 Abbott 

Circle, Seneca, SC 29678, 
HO'W TO EVALUATE: AND 

Patrick J. I3arry1, Coleman IIoggett2, 

Robert L. hdersonl, and Kenneth Me Swain, ~r e3 

INTRODUCTION 

Hurricanes, tornadoes, and ice stom 

strike somewhere in the South almost 

every year. They cause extensive 

forest damage by uprooting, wounding, 

bending, and breaking trees. Standing 

water, which often accompanies hurricanes, can cause additional stress and 

mortality. When one of these natural 

disasters occurs, it is important to 

have a plan for managing damaged 

timber. 

Development of a storm damage management plan involves several systematic 

steps. As soon as possible, the area 

should be sketch mapped or aerial 

photographed. The next step is to 

ground check the damage to determine 

the need for salvage. Priorities for 

salvage will depend on location, 

amount and type of damage, and 

management objectives. This guide 

presents methods for managing 

storm-damaged trees to reduce growth 

loss, product degrade, and mortality. 

In the process, other factors such as 

threatened and endangered species must 

be considered. The information presented here will assist in setting 

priorities. 

SURVEY THE DWGE 

areas may be sketched on preexisting 

maps or photographs, or damaged areas 

may be aerially photographed. A planimeter or other device is then used to 

determine acres affected. 

Intensive surveys are designed to 

collect information on volumes of 

timber damaged and on conditions of 

surviving trees. Volumes of stormdamaged timber are difficult to 

estimate with aerial survey techniques 

because damaged trees are broken and 

twisted together. It is also difficult 

to determine tree condition from the 

air. Consequently, intensive surveys 

usually require ground-based plots for 

acceptable accuracy. The number and 

size of plots are determined by desired 

accuracy, and by time and personnel 

constraints. 

Tornado damage surveys are unique 

because the storm tracks are usually 

long and narrow with few surviving 

trees. Volumes of tornado damaged 

timber may be estimated by taking 

systematic plots on a transect parallel 

to the storm track but just outside the 

damage area. 

NOTE TYPES OF DAMAGE AND TAKE 

ACTION 

Two types of surveys, general and Breakage intensive, are needed to determine the Breakage is the most common type of 

extent of forest damage from a storm. storm damage. Its impact depends on 

the degree and pattern of damage as 

General surveys are designed to deter- well as the tree species involved. 

mine geographical area affected by 

storms. These are very quickly and Breakage inevitably lowers timber 

easily done from the air. Using values, Breaks are uneven by their 

aerial survey techniques, damaged nature and occur randomly alonq the 

tree bole. The random pattern-lowers 

' Entomologist, USDA Forest Service, 

Southern Region, Forest Health, 

Asheville, NC. 

Senior Staff Forester, North 

Carolina Forest Service, Raleigh, NC. ' Deputy Director, USDA Forest 

Service, Southern Region, Forest 

Health, Atlanta, GA. 

value since products are normally cut 

in specified lengths. Breakage also 

lowers value because difficulty in 

logging in broken timber slows productivity. Patterns are important when 

assessing breakage impact. When ice or 

strong gale-force winds break trees, 

break patterns are simple and limited 
to the area adjacent to the breakpoint. Hardwood trees are seldom 

killed by breakage. Even when tops 

are completely gone, new branches will 

sprout and the tree will recover. In 

hardwoods, the major problem is that 

breaks in the trunk or large branches 

(over 3 in. diameter) permit entry of 

stain and decay fungi. Stain will 

move vertically from the injury at a 

rate of 6 to 18 inches per year, and 

decay will follow the stain in 8 to 10 

months. 

Most species of pine will die if tops 

are completely broken and no live 

limbs remain, If three or more live 

limbs are left in the tops of loblolly 

or slash pines, the chance of survival 

is excellent (above 75 percent). One 

of the lateral branches in these trees 

will become the terminal, and in 8 to 

10 years the only sign of breakage 

will be a sharp crook in the bole at 

the point where the break occurred. 

These trees will experience growth 

losses, however. 

Recommendations 

For hardwoods, trees with broken tops 

or branches over 3 inches in diameter 

should be salvaged during the next 

scheduled harvest. High-value trees 

such as those in recreation areas and 

in yards should be properly pruned to 

promote rapid healing. 

For pines, if three live limbs or less 

remain, the trees should be harvested 

as quickly as practical. 

misted Trunks 

The cyclonic winds that are typical of 

tornadoes, and often accompany hurricanes, cause twisting and separation 

of wood fibers in the main stem. Logs 

from trees that have experienced this 

treatment may fall apart when sawn for 

lumber products. Trees twisted by 

cyclonic winds may appear normal, 

except that pines often have pitch flow 

along the trunk. 

Recommendations 

Trees with evidence of twist injury 

should be removed, since the problem 

will not disappear with time and 

considerable losses may be incurred 

during a later harvest. 

Root Damage 

If they are not salvaged promptly, 

uprooted trees probably will be 

degraded quickly by stains, decays, and 

secondary insects, such as Ips bark 

beetles, borers, powderpost beetles, 

and ambrosia beetles. The longer 

salvage is delayed, the greater the 

amount of degrade and weight loss from 

rapid drying. Degrade translates into 

a stumpage value loss. The amount of 

degrade that is acceptable to industry 

depends on the tree species and local 

markets. Table 1 shows the probable 

sequence of invasion by damaging 

organisms in storm-damaged timber. 

Root-s 

ately, 

over a 

,prung trees will not die immedibut will show decline symptoms 

period of several years. These 

trees may be invaded by root rot 

organisms and subjected to drought 

stress and insect attack. Root-sprung 

pines may be invaded by bark beetles 

and blue stain fungi. These pines can 

serve as prime habitat for the southern 

pine beetle and, if conditions become 

favorable, an outbreak could occur. 

They can also harbor high populations 

of turpentine beetles. 

Recommendations 

Trees with major root damage should be 

salvaged as soon as possible to avoid 

growth loss, product degrade, bark 

beetle attacks, and mortality. 

Table 1--Sequence of invasion of damaging organisms in storm-damaged timber 

Species Year 1 Year 2 

Pine Bark beetles, ambrosia beetles, Decay fungi 

sawyers, blue stain fungi, soft 

rot fungi 

oak and hickory Wood borers, ambrosia beetles, Sapwood decay fungi 

stains, soft rot fungi 

Other hardwoods Wood borers, ambrosia beetles, Sap and heartwood 

stains, soft rot fungi decay fungi 
Major Wounds , many trees sustain 

wounds caused by falling tops, 

adjacent uprooted trees, and mjor 

branch breakage. In hardmads, wounds 

that do not penetrate =re than 2 

inches into the sapmod and have less 

than 144 square inches of surface area 

will have only localized stain, but 

little decay. Wounds that exceed 

these limits will have stains and 

decay that move at the rates described 

for broken branches. Pine trees with 

major wounds to the lower bole and 

larger roots may be attacked by bark 

beetles . 

Recog~~~en&tione 

Trees with major wounds should be 

considered for removal during the next 

scheduled harvest, or they should be 

included in the salvage operation. 

Bent Trees 

Bent hardwoods usually are not 

attacked by insects or diseases 

because they are not in a stressed 

condition. Pine trees that are bent 

to the extent that cracks and resin 

flow occur may be invaded by bark 

beetles and disease-causing organisms. 

Recom~aendations 

Small trees (under 15 feet in height) 

usually straighten even after severe 

bending. Taller severely bent hardwoods should be removed during the 

salvage operation or the next scheduled harvest, Be sure to inspect large pine timber for pitch flow. 

Many large, green, standing trees may 

not be usable for veneer, poles, or 

lumber because of internal ring shake, 

splintering, and separation of the 

wood fibers. Often, the only external 

evidence of such damage is pitch or 

sap flow where the injury has broken 

the bark, These characteristics are 

often overlooked, and considerable 

losses are incurred during a later 

harvest. 

Standing Water 

In standing water, the dissolved 

oxygen is quickly depleted, so trees 

of most species are injured by prolonged flooding, particularly during 

the growing season. The loss of soil 

oxygen leads to root mortality and 

tree death. Trees weakened by standing water are often attacked by 

insects or affected by diseases. 

Forest mnagers may wish to favor 

shrubs include: buttonbuah, s 

deciduous holly, and swmp-iro 

CtE: !PO mDUCE PEST-UI,USlD 

LOSSES 

ge often increases the risk 

of pest outbreak by weakening the 

defenses of host trees, Pest infestations will not develop unless suitable 

host trees are available, 

effort should be made to r 

trations of susceptible host trees. A 

well-planned and executed salvage operation can greatly increase a 

stand's resistance to pest attacks, 

To ensure effective salvage, we 

recommend the following approach: 

1. Act quickly. Prompt salvage will 

help avoid losses from degrade 

and subsequent pest-caused 

mortality. 

Measure carefully the extent of 

ge before deciding on a 

salvage operation. A number of 

factors such as stand age, 

species, stocking, and management 

objectives will need to be 

considered, 

Salvage the most severely dmged 

timber first. Concentrate on the 

pine stands, because they are 

more susceptible than hardwoods 

to pest outbreaks. On deep sandy 

soils where a stand will be left, 

the stumps should be treated for 

annosus root rot control. During 

salvage avoid damage to residual 

trees. 

Complete salvage promptly and in 

one continuous operation. Bark 

beetle populations are more 

likely to build up in the slash 

and move into healthy trees if 

logging operations are prolonged 

or interrupted for periods of a 

month or more. (When salvage is 

delayed, a helpful guide is 

available for utilization of 

beetle-killed pine trees based on 

tree appearance. See Table 2.) 
Table 2--Utilization guidelines for beetle-killed pine treesL 

Product Class A Class B 

Trees with needles Trees with no needles, or no needles, most twigs and 

but twigs attached branches lost, and 

some broken tops 

Blue stain prohibits use. 

Dimension Can be used Should be kiln dried to prevent 

lumber2 with caution emergence of secondary insects. 

(structural ) LOM moisture content may dull saws and chipper knives faster than 

with sound wood and my require 

milder kiln schedule. Do not use where toughness is important. 

Decorative Can be used 

lumber boards 

and paneling 

Can be used 

Posts, poles, Not recommended 

piling 

Plywood Can be used 

Hardboard, Can be used 

particle-board, 

medium density 

fiberboard 

Can be used 

Pulp Can be used Can be used 

Fuelwood Can be used Can be used 

should be kiln dried. 

Toughness and preservative 

treatability may be highly 

variable. 

Adhesives and gluing practices 

my have to be adjusted. 

Low moisture content may affect 

some production schedules. 

Should be mixed with sound wood. 

Blue stain and low moisture 

content may affect pulping 

process and chemical or energy 

requiremnts. Should be mixed 

with sound wood, particularly 

where strength is important. 

Low moisture content increases 

heat value. 

For more informtion on utilization of beetle-killed trees, see "A Guide for Using Beetle-Killed 

Southern Pine Based on Tree Appearance", by Michael P. Levi, USDA Agriculture Handbook 572. 

For more information on economics of producing lumber from beetle-killed pines, see "A Mill 

Operator's Guide to Profit on Beetle-Killed Southern Pine", by S.A. Sinclair, USDA Agriculture 

Handbook 555. 

5. Follow the practices listed 

below to ensure that the 

residual material (slash) will 

dry quickly. Bark beetle 

infestations will not build up 

in dry material. 

a Cut a11 logs from seriously damaged trees to the 

minbm merchantable size 

and remove them from the 

area. 

. Lop and scatter all harvesting slash and tops 

into open areas when 

possible. 

Scatter large accumulations of slash away from 

the bases of residual 

trees, and into direct 

sunlight if possible. 

. Sever downed trees from 

roots that could keep them 

alive. 

6, Inspect large pines for pitch 

flow. Many large, green, standing pines may be unusable for 

veneer, poles, or lumber because 

of internal splintering and 

separation of the wood fibers. 

Often, the only external evidence of such damage is pitch 

flow where the bark has been 

broken, 

7, Follow the ratings of species 

resistance to insects and 

diseases in Table 3 when planning 

the salvage of timber, especially 

hardwoods. 
8. Consider deducting stom-d 

losses on income-tax returns. 

Landowners can ssure advice 

from local foresters, accountants, attorneys, or Internal 

Revenue Service agents concerning deductible losses, 

9. Check for pest activity after 

salvage operations are finished. 

Make periodic sumeys, either 

aerial or ground, of the 

residual stands to check for 

pest activity. These surveys 

ntay be required for up to 2 

years, Trees that are turning 

yellow, have pitch tubes on the 

bark, or red boring dust around 

the base, are probably affected 

by insects, diseases, or both. 

These trees should be considered 

for control activities, 

DAMACGE 

Tree species vary in their ability to 

withstand hurricane winds and salt 

damage, Wind resistance depends on 

the interaction of five factors: 

strength of the wood, shape and size 

of the crown, extent and depth of the 

root system, previous moisture conditions, and shape of the bole, 

No tree species has perfect wind resistance, but live oak, palm, pondcypress, 

and baldcypress are among the best, as 

shorn in Table 3, These trees combine 

deep root systems with buttressed 

trunks (low center of gravity). The 

wood of live oak is exceedingly strong 

and resilient. The crown is usually 

widespread, but this does not seem to 

negate its strong points, Cypress has 

relatively weak wood, but its erom is 

so sparse and its foliage so limber 

that it is also extremely windfirm. 

Shallow-rooted trees are easily 

uprooted, especially after the soil is 

saturated by heavy rains. Common 

shallow-rooted trees along the coast 

are dogwood, water oak, pecan, 

sweetbay, and red maple, Common 

deep-rooted trees are live oak, 

longleaf pine, and pondcypress and 

baldcypress. 

Trees growing in sandy soils are more 

deeply rooted than trees growing in 

soils with an inhibiting clay layer or 

a high water table, Although rooting 

habits vary according to the soil 

profile, each species has a characteristic pattern, Another factor to be 

considered is the height of the tree, 

The taller the tree, the greater is its 

chance of breaking, especially if the 

bole has little taper. For this 

reason, tall, slim slash and longleaf 

pines are extremely vulnerable, 

Table 3--Resistance of tree species to hurricane-related damage (in descending 

order of resistance) 

Flood 

tolerant Breakage Uprooting 

Deterioration 

Salt by insect 

and disease 

baldcypress 

pondcypress 

tupelo-gum 

sweetbay 

willow 

sweetgug 

sycaatore 

river birch 

cot tonwood 

green ash 

red maple 

pecan 

mulberry 

American elm 

silver maple 

water oak 

swamp chestnut 

magnolia 

hickory 

live oak 

palm 

baldcypress 

pondcypress 

swee tgum 

tuge lo-gum 

eimosa 

dogwood 

magnolia 

sweetbay 

southern red oak 

water oak 

sycamore 

longleaf pine 

slash pine 

loblolly pine 

redcedar 

oak hickory 

red maple 

pecan 

live oak 

palm 

baldcypress 

pondcypress 

tupelo-gum 

redcedar 

sweetgu 

sycamore 

longleaf pine 

aimosa 

southern red oak 

magnolia 

slash pine 

loblolly pine 

aweetbay 

water oak 

red maple 

dogwood 

hickory 

pecan 

live oak 

palm 

slash pine 

longleaf pine 

pondcypress 

loblolly pine 

redcedar 

tupelo-gum 

baldcypress 

sweetgum 

water oak 

sycamore 

sweetbay 

southern red oak 

hickory 

mimosa 

pecan 

magnolia 

red maple 

dogwood 

live oak 

palm 

sweetgum 

water oak 

sycamore 

baldcypress 

pondcypress 

southern red oak 

mgnolia 

tupelo-guln 

sweetbay 

hickory 

pecan 

redcedar 

red maple 

mimosa 

dogwood 

longleaf pine 

slash pine 

loblolly pine 
Open-crowned and lacy-foliaged trees, 

such as cypress and mimosa, offer less 

resistance to the wind, and thus are 

better able to survive. On the other 

hand, magnolia trees with their heavy, 

wind-catching foliage are windthrown 

more than their root system and bole 

structure would indicate, Palm trees 

offer little surface to the wind 

because they have almost no laterally 

extended crown and branches, This 

characteristic makes them fairly 

windfirm, despite their limited root 

systems. 

Based on these observations, the 

following preventive measures are 

reconunended to forest managers in 

hurricane-risk areas: 

1. Keep a balanced mixture of size 

and age classes to prevent a 

complete loss, Young trees are 

rarely damaged, because they 

tend to bend with the wind; old 

trees tend to break or uproot, 

Where feasible, stagger thinnings to limit exposure of the 

recently thinned areas. (During 

Hurricane Camille, recently 

thinned stands of pine with 

little taper were severely 

broken, while open stands and 

stands thinned several years 

earlier suffered less damage,) 

3, Manage for well-spaced, thrifty 

trees and, as much as possible, 

develop a spread of age classes 

to distribute the risk of wind 

damage. 

4, Consider planting longleaf pine 

in deep sandy soils, because 

longleaf has a deep taproot. 

5, When planting slash and loblolly, 

use an 8- by 8-foot or wider 

spacing. 

Winds often carry saltwater inland for 

a considerable distance. The leaves on 

trees saturated with saltwater turn 

brown and give the appearance of being 

burned. Most of these trees will not 

die and should not be cut. See Table 2 

for resistance among tree species. The 

trees may lose their leaves and some 

growth, but most of them will grow new 

leaves and recover, Check trees 

closely in the spring after salt damage 

for adequate recovery or possible bark 

beetle attack. Trees should be harvested if they have been attacked by 

bark beetles or if they have not put on 

new growth in the first full growing 

season after the damage occurred. 

Reprinted from USDA Forest Service 

Management Bulletin R8-MB 63. 
age to Forests 

IMPACT OF EURRICAMIE HUGO ON 

THE SOUTH CAROLINA COASTAL PLAIN FOREST 

Dona1 D. ~ook', Marilyn A. ~uford', and Thomas M. ~illiams' 

Abstract--The impact of Hurricane Hugo on the Coastal 

Plain forest is described using data from two experimental forests. The Santee Experimental Forest experienced the full force of the eyewall, sustaining extreme 

wind damage. On Hobcaw Forest, northeast of the area 

impacted by the eyewall, major damage was done by salt 

with some wind damage. The largest and tallest trees of 

all species were more severely damaged than were smaller 

trees. Within the area impacted by the eyewall, 89% of 

the longleaf pine trees, 91% of the loblolly pine trees, 

and 86% of the bottomland hardwood trees were broken or 

uprooted. outside the area of the eyewall, 17% of the 

longleaf pine, 52% of the loblolly pine and 20% of the 

bottomland hardwoods were broken or uprooted. Species 

differences in wind resistance were apparent outside the 

area affected by the eyewall. 

INTRODUCTION 

Hurricane Hugo came ashore across 

Sullivan's Island, South Carolina, at 

midnight EDST, September 21, 1989. 

When the storm made landfall, it was 

considered a Category 4 on the Saffir/ 

Simpson scale. At the coast near 

Bulls Bay, estimated maximum sustained 

surface winds were 54 meters per 

second (ms-') (121 miles per hour 

(mh-')) with possible extreme gusts to 

66 ms-' (147 mh-I). The eye of the 

storm was approximately 50 km in 

diameter with the eyewall affecting an 

area approximately 100 km wideq. The 

center of the hurricane followed the 

path indicated in Figure 1, inflicting 

timber and property damage across 23 

of South Carolina's 46 counties. 

Seven counties experienced extensive 

timber damage, 3 experienced moderate 

timber damage, and 13 counties 

suffered light timber damage. The 

storm was down-graded to tropical 

storm status after passing Charlotte, 

North Carolina, six hours after 

landfall, and ultimately crossed the 

Canada-United States border at Erie, 

Pennsylvania, 17 hours after landfall. 

In South Carolina, approximately 1.8 

million ha of forest land were damaged 

by wind and water. In comparison, the 

eruption of Mount St. Helens affected 

60,750 ha and the Yellowstone fires of 

1988 burned approximately 400,000 ha 

(Figure 2a,b). The amount of dead and 

downed wood is three times the annual 

harvest in the state. An estimated 

32.3 million cubic meters (6.7 billion 

board feet (bf)=) of sawtimber was 

damaged or destroyed. This is enough 

wood to build approximately 660,000 

average homes; enough to house almost 

the entire population of West Virginia 

or the city of Philadelphia (South 

Carolina Forestry Commission 1989). In 

comparison, the total harvest of lumber 

in the northern coastal plain of South 

Center for Forested Wetlands 

Research, Clemson University, 2730 

savannah Highway, Charleston, SC 29414 

Center for Forested Wetlands 

Research, USDA Forest Service, 

2730 Savannah Highway, Charleston, SC 

29414 

Belle W. Baruch Forest Science 

Institute, Clemson University, P.O. Box 

596, Georgetown, SC 29440 

Powell, M.D.; Dodge, P.; Black, M. 

1990. The landfall of Hurricane Hugo in 

the Carolinas. In preparation for 

Weather and Forecasting. 

A board foot (bf) is equivalent to a 

plank 1 inch thick and 12 inches 

square, 
Sontee Experimentai fhrest 

Hobcaw Forest 

100 Kilometers 

Figure 1--Map of South Carolina showing the path of Hurricane Hugo, the area 

impacted by it, and the locations of the Santee Experimental Forest and the 

Hobcaw Forest. 

Moderate Damage (Y 

Figure 2a--Map of South Carolina showing the area impacted by Hurricane Hugo 

with the area impacted by the eruption of Mount St. Helens superimposed. 
Moderate Damage 

Figure 2b--Map of South ~arolina showing the area impacted by ~urricane Hugo 

with the area impacted by the 1988 Yellowstone fires superimposed. 

Carolina during the 20-year peak 

exploitation period 1909-1929, was 

approximately 30.8 million m3 (6.4 

billion bf)6. As of this writing, 

intensive efforts have resulted in the 

salvage of 39% of the pine and 3.7% of 

the hardwood downed or damaged by the 

hurricane in South Carolina. 

The center of the eye passed within 8 

km of the 101,000 ha Francis Marion 

National Forest (FMNF). Nearly the 

entire FMNF was affected by the winds 

of the eyewall. Most of the wind 

damage in a hurricane occurs as a 

result of short duration gusts (2-4 

second), either the typical gusts 

associated with turbulence or the 

extreme gusts associated with the 

downdrafts from intense thunderstorms, 

most of which form in the eyewall and 

outer rainbands7. 

Throughout the region of severe 

damage, the sites of the extreme gusts 

described above are marked by areas 

0.25 ha to 7 ha in size where every 

tree was broken or uprooted. These 

spots of total destruction extended 

inland for more than 150 km. 

The Santee Experimental Forest 

(Santee) is located approximately 40 

km from the coast, on the west side of 

the FMNF~. Hobcaw Forest (Hobcaw) is 

approximately 90 km northeast of 

Charleston, near Georgetown, SC, 

positioned along the coast and immediately to the west of the North Inlet 

salt marsh (Figure The Santee and 

Hobcaw are sites of intensive forest 

research and offer a unique opportunity 

to examine the effects of a severe 

hurricane on the Coastal Plain forest. 

This paper describes the effect of a 

severe hurricane on the Atlantic 

Coastal Plain forest with specific 

examples from these two experimental 

forests. 

Reference to timber harvest of 

1909-1929. 

Powell and others. The landfall of 

Hurricane Hugo in the Carolinas. 

The Santee Experimental Forest is 

administered by the Southeastern Forest 

Experiment Station, Forest Service. 

United States Department of Agriculture, and serves as the primary outdoor 

laboratory for the Center for Forested 

Wetlands Research, Charleston, South 

Carolina. 

The Belle Baruch Forest Institute is 

managed by Clemson University and 

serves as an outdoor teaching and 

laboratory facility for all facets of 

forest environment research. 
SANTEE EXPERIMENT= FOREST 

Land Use History and 

Description 

During the eighteenth and nineteenth 

centuries, the area that is currently 

the Santee Experimental Forest contained parts of seven major plantations. Rice was the main money crop 

and the attendant diking structures 

and canals are still clearly evident 

on all the main creek bottoms on the 

forest. The remains of numerous tar 

kilns on the forest provide evidence 

of the extent of longleaf pine (Pinus 

palustris) and the importance of the 

naval stores industry which peaked 

between 1850 and 1880 (~rothingham and 

Nelson, 1944). Intensive timber 

removal began in the 1890's with the 

development of steam power, and continued for a period of 30 to 40 years 

throughout South Carolina and the 

southern forests, After the coastal 

forests were cut over, much of the 

land was abandoned or sold very 

cheaply. The U.S. Government purchased approximately 100,000 ha and 

President Franklin P. Roosevelt 

established the Francis Marion 

National Forest in 1936. In 1937, 

2000 ha were set aside as the Santee 

Experimental Forest. The area was 

enlarged to its present 2452 ha in 

1946. 

In the 53 years prior to Hugo, 190 

short- and long-term studies were 

conducted on the forest and over 400 

articles were published on the 

results. Major research areas were 

prescribed burning, regeneration and 

management of bottomland hardwoods, 

natural regeneration of pine stands, 

coastal watersheds, and threatened and 

endangered species (red-cockaded 

woodpecker, in particular). 

The soils of the Santee are primarily 

~lfisols and Ultisols with drainage 

ranging from very poorly to moderately 

well drained, and surface textures 

range from sandy loam to clay. The 

Alfisols generally occur in the drains 

and depressions and the Ultisols generally occur on the higher topographic 

positions, 

The Santee is a mosaic of Atlantic 

Coastal Plain forest types. The 

forest types present on the Santee 

Experimental Forest are: (1) mixed 

pine-hardwood--typically a mix of 

loblolly pine (P. taeda), sweetgum 

(Liquidambar styraciflua), southern 

red oak (Quercus falcata), white oak 

(Q. alba), and red maple (Acer 

rubrum); (2) loblolly pine--often has a 

midstory or understory of sweetgum, red 

maple, and willow oak (Q. phellos); (3) 

longleaf pine (P. pa1ustris)--often has 

an understory of turkey oak (Q. laevis) 

or blackjack oak (Q. marilandica); (4) 

mixed loblolly pine-longleaf pine; (5) 

upland hardwoods--white oak, southern 

red oak, and black oak (Q. velutina) ; 

(6) bottomland hardwoods--cherrybark 

oak (Q. falcata var, pagodaefolia) , swamp chestnut oak (Q. michauxii), 

sweetgum, red maple, Water oak (Q. 

nigra), willow oak, green ash (Fraxinus 

pennsylvanica), yellow-poplar 

(Liriodendron tulipifera), Shumard oak 

(Q. shumardii), black gum (Nyssa 

sylvatica) , and laurel oak (Q. 

laurifolia); and (7) creek swamp-- 

baldcypress (Taxodium distichurn) and 

water tupelo (N. aquatica). The area 

of each forest type is given in Table 

1. 

Table 1--Area by forest type on the 

Santee Experimental Forest and Hobcaw 

Forest. 

Area (ha) 

Santee 

Experimental Hobcaw 

Forest Type Forest Forest 

Mixed pine-hardwood 10 17 

Loblolly pine 702 

Longleaf pine 46 

Loblolly longleaf 195 

Upland hardwoods 312 

Bottomland hardwoods 15 2 

Creek swamp 28 

Damage 

In the path of the eyewall, the Santee 

suffered extreme wind damage. Over 80% 

of the trees were destroyed and nine 

long-term studies accounting for 221 

research years were prematurely terminated by the storm's passage. Prior to 

the hurricane, the volume of wood on an 

average ha in the experimental forest 

was 178 m3 (15,000 bflacre). Current 

estimates are that less than 24 m3/ha 

(2000 bf/acre) were left standing after 

the storm (Photo 1). Table 2, based on 

a survey incomplete as of this writing, 

gives the proportion of each species in 

each of 7 condition classes: (1) no 

apparent damage, (2) broken stem 

(broken below the base of the live 

crown), (3) broken top (broken above 

the base of the live crown), (4) 

leaning more than 45", (5) leaning 

30-45", (6) leaning 5-30", and (7) 

uprooted. The results in Table 2 are 

based on a survey of 137 trees from 
Photo l--Devastation of an 85-year-old loblolly pine (Pinus taeda) stand 

resulting from Hurricane Hugo on the Santee Experimental Forest in South 

Carolina. 

Table 2--Proportion of each species in each condition class. 

condition Class 

Species No Damage Broken Stem Broken Top Lean r45O Lean 30-4S0 Lean 5-30° Uprooted 

Ash 

Elm 

Hickory 

Ironwood 

Laurel oak 

Loblolly pine 

Red maple 

Red oaka 

Sweetgum 

White oak 

Yellow poplar 

" Cherrybark oak and Shumard oak. 

12.7 to 50.8 cm dbh, and do not contain the larger size classes of any of 

the species. The larger size classes 

of all species suffered greater damage 

than did trees in the smaller size 

classes. 

Using aerial photographs taken from an 

altitude of approximately 457 m, stem 

counts in mature stands were made to 

determine the proportion of loblolly 

pine, longleaf pine and bottomland 

hardwoods that were apparently 

undamaged, broken, and uprooted. 

The results are given in Figure 3. 

In these 80- to 110-year-old stands, 

this represents severe damage to 

approximately 124 of 166, 128 of 141, 
a $0 

C 

5 

9- 

0 10 C 

U 

LO 

a 20 

0 

Lonateaf Pine Loblolly Pine Bottomland 

Hardwoods 

Figure 3--Percentage of longleaf pine, 

loblolly pine, and bottomland hardwood 

stems on the Santee Experimental 

Forest that were uprooted, broken, and 

standing after Hurricane Hugo. 

and 67 of 77 trees/ha in the bottomland hardwood, loblolly pine, and 

longleaf pine groups, respectively. 

In general, the tallest and largest 

(dominant) trees experienced the most 

severe damage, Those suffering less 

damage were primarily in the midstory 

and not in the dominant canopy. 

Loblolly pine suffered the greatest 

amount of stem and top breakage. 

Shumard oak, cherrybark oak, and 

yellow poplar are relatively largecrowned and shallow-rooted and did not 

lose their foliage in the wind. These 

combined factors contributed to the 

large number of uprooted stems of 

these species (Photo 2). 

HOBCAW FOREST 

Land Use History and 

Description 

The Hobcaw Forest contained parts of 

13 plantations during the eighteenth 

and nineteenth centuries. As with the 

Santee during this time period, rice 

was a major crop and evidence of its 

culture is still apparent. The Hobcaw 

forest was purchased in 1905 by 

Barnard M. Baruch and, because it was 

maintained as a hunting preserve and 

winter retreat, it was not heavily 

logged during the early twentieth 

century. The property was willed to 

the colleges and universities of South 

Carolina by Belle W. Baruch in the 

1960's to be used for research and 

education in forestry, wildlife, and 

marine biology. 

Research efforts on the Hobcaw Forest 

began in the late 1960's and since that 

time have focused primarily on insects, 

wildlife, vegetation, hydrology, and 

forest regeneration techniques, Major 

research efforts have been made on the 

ecology and management of feral hogs, 

red-cockaded woodpeckers, fox 

squirrels, and songbirds. In addition, 

an important effort quantifying the 

hydrologic inputs from a managed 

coastal forest into the relatively 

undisturbed North Inlet estuary has 

been undertaken. 

The Hobcaw Forest is 3000 ha in size, 

and is primarily an old coastal pine 

forest. Pine and pine-hardwood stands 

occur on 2511 ha and contained 126,000 

m3 (26.1 million bf) of pine sawtimber 

and 35,900 m3 (18,000 cords) of pulpwood based on a 1986 inventory. Hardwood stands occur on 489 ha and contained 15,000 m3 (3.1 million bf) of 

hardwood sawtimber and 31,500 m3 

(15,800 cords) of pulpwood in 1986. 

The area in each forest type is given 

in Table 1 and the type descriptions 

are essentially those given for the 

Santee Experimental Forest. 

Soils on the forest have developed on 

sandy former beach ridge topography. 

Ridges are predominantly Leon (Aeric 

Haplaquods) and Centenary (Grossarenic 

Entic Haplohumods) and intermediate 

swales are primarily Lynn Haven (Typic 

Haplaquods) and Rutledge (Typic 

Humaquepts). 

Wind Damage 

Preliminary estimates of losses due to 

wind damage were 19,900 m3 (3.9 million 

bf) of pine sawtimber (10.9%), 1365 m3 

(684 cords) of pine pulpwood (4.5%), 

4650 m3 (912 thousand bf) of hardwood 

sawtimber (25.9%), and 15,130 m3 (7576 

cords) of hardwood pulpwood (39%). 

Wind damage was evaluated on the ground 

by 0.1 hectare strip plots located in 

each stand less than 20 ha and two 

plots in each stand over 20 ha for a 

total of 355 plots. In each plot all 

trees over 10 cm dbh (diameter at 

breast height--1.37 m above the soil 

surface) were tallied by species, 

diameter and one of eight damage codes: 

(1) undamaged, (2) defoliated, (3) 

bent, (4) branches broken, (5) top 

broken, (6) stem broken, (7) uprootedleaning, and (8) uprooted-on the 

ground. Trees in the "stem broken" 

category have the main stem broken 

between the ground and the first limb. 

Those in the "top broken" category have 
Photo 2--The remains of a red-cockaded woodpecker (Picoides borealis) colony 

site in a 100-year-old longleaf pine (Pinus palustris) stand on the Francis 

Marion National Forest in South Carolina after Hurricane Hugo. 

the main stem broken between the first 

limb and the terminal shoot. 

Uprooted-leaning trees were uprooted 

but fell into another tree and did not 

reach the ground. Uprooted-on the 

ground trees were uprooted and fell 

all the way to the ground. 

The ground survey was incomplete at 

the time of writing, but 119 plots 

were compiled to give preliminary 

indications of wind damage. The 

number of trees tallied in each 

species was proportional to the 

relative abundance of the species on 

the forest. Of the 4380 trees 

tallied, 2490 were loblolly pine, 520 

were longleaf pine, 440 were sweetgum, 

330 were laurel oak, 300 were black 

gum, 155 were water oak, 116 were live 

oak (Q, virginiana), 64 were southern 

red oak and 60 were cypress. 

proportion of stems undamaged ranged 

from highs of 73% in longleaf pine, 51% 

in live oak and 48% in loblolly pine to 

a low of 15% in water oak and 24% and 

26% in southern red and laurel oak, 

respectively. Alternatively, the 

portion of broken or uprooted stems 

varied from a low of 0 in live oak and 

cypress to highs of 22% in water oak 

and 18% in southern red and laurel oak. 

Tree species could be grouped by the 

mechanisms of resistance to wind 

damage. Live oaks have very strong 

wood and large spreading crowns.. Limbs 

were broken on 34% of the stems and 

tops were broken on 7% of the stems. 

Average diameters of stems with broken 

limbs (33.8 cm) and broken tops (37.5 

cm) were much larger than undamaged 

trees (22.1 cm). Defoliation was most 

common in cypress and black gum. 

With the exception of longleaf pine, Fifty percent of the cypress and 64% of 

the resistance to wind damage, by the black gum were defoliated. No 

species, was found to be similar to cypress and only 2.3% of black gum were 

the general list of wind resistance uprooted or broken. Average diameters 

found in Barry and others (1982). The of black gum with broken tops and stas 
was 42 cm compared to 28 cm for 

defoliated stems and 31 cm for 

undamaged stems. 

Three species of oak with tall growth 

form (water, laurel, and southern red) 

were the most severely damaged. For 

all three species more than 75% of all 

stems were damaged. Six percent of 

each species had stems broken but 

water oak (which usually grows on more 

poorly drained soils) had 18% uprooted 

compared to 128 f o r t h e other two 

species. Average diameters of 

undamaged trees were smaller than 

those of damaged trees, For example, 

undamaged water oak, laurel oak, and 

southern red oak had mean diameters of 

13.8 cm, 15.8 cm, and 17.3 cm, respectively, while uprooted and broken 

stems of water oak, laurel oak, and 

southern red oak had mean diameters of 

22 cm, 25 cm, and 35 cm, respectively. 

Longleaf pine resistance was better 

than would be expected from its rank 

in the list included in Barry and 

others (1982). Seventy three percent 

of all stems were undamaged and only 

5.2% were broken and uprooted. 

Undamaged stems averaged 29 cm in 

diameter while broken and uprooted 

trees averaged 39 cm in diameter. 

These results may be due to the 

unusual condition of longleaf pine on 

the forest. All stands of longleaf 

are over 70 years old. All but a few 

of these stands were cut in the 1950's 

and 1960's and had residual basal 

areas of 9 to 18 m2/ha (40 to 80 

ft2/acre) when the hurricane struck 

(Williams and Lipscomb, 1989). The 

longleaf pine trees on Hobcaw forest 

had been growing in open stands for 30 

to 40 years prior to the hurricane. 

Only 48% of loblolly pine stems were 

undamaged and those stems averaged 

16.4 cm in diameter. Eight percent of 

all loblolly stems were broken and 

uprooted and those were twice as 

large, averaging 32 cm in diameter, 

Loblolly pine was the only species 

that had enouqh stems to examine 

damage in each diameter class. 

Undamaged stems decrease progressively 

from 60% of all stems in the 10-20 cm 

class to <25% in the 50-60 cm class. 

Conversely, the uprooted and broken 

stems increase from <5% in the 10-20 

cm class to 30% in the 50-60 ern class. 

Spatial distribution of wind damage to 

the forest has been evaluated with 

large scale (1:6000 rf) aerial 

photographs taken on October 12th. 

Under 8x magnification, individual 

broken and uprooted trees can be 

identified on these photographs. Each 

of the forest stands was classed as 

lightly, moderately, or heavily damaged 

as determined by the portion of the 

stems in that stand identified on the 

photographs as broken or uprooted. 

Heavy damage was restricted mainly to 

poorly drained bottomland hardwood and 

pine-hardwood stands and to pine stands 

that had been thinned within the last 

three years. Light damage was found in 

cypress ponds and closed canopy pine 

stands. 

~idal Surge Damage 

Although wind damage was widespread, 

major damage was also done by salt, 

both windblown and carried by a storm 

surge approximately 3 meters above sea 

level. The hurricane struck the coast 

near the time of high tide. Most 

instruments on the eastern side of the 

forest were destroyed by the surge, but 

two water level recorders on shallow 

groundwater wells recorded elevations 

of the surge until floats emerged from 

the well tops. From the records and 

elevations of these two recorders it 

can be established the tide was from 

3.0 to 3.2 meters above sea level from 

2330 on September 21, 1989 to 0130 on 

September 22* 

Mortality due to salt water infiltration from the storm surge accounted for 

a loss of 22,200 m3 (4.6 million bf) of 

pine sawtimber (138), 11,400 m3 (5700 

cords) of pine pulpwood (33%), 1050 m3 

(226 thousand bf) of hardwood sawtimber 

(6.48) and 4200 m3 (2100 cords) of 

hardwood pulpwood (10.7%). Tree 

mortality became apparent in early 

December. Mortality was most 

pronounced in closed depressions 

and along either side of drainages near 

the southern end of the forest. Wet 

weather prior to the hurricane limited 

the amount of salt water that directly 

infiltrated during tidal inundation. 

The records from the operating wells 

with water level recorders and charts 

recovered from those made inoperative 

show that the water table in the 

aquifer was near the surface in all the 

depressions and within a meter of the 

surface at'the top of the ridges, Both 

the limited opportunity for imediate 

infiltration and the pattern of tree 

mortality suggest that infiltration of 

trapped water after the storm was the 

main mechanism of mortality. Along the 

southern end of the forest, ridges and 

swales of the relic beach ridge topography are pronounced. A series of 
north-south ridges extend from the 

western side of the salt marsh. Ridge 

tops are about 300 meters apart and 

are separated by swales about 50 

meters wide and 1 to 1.5 meters below 

the adjacent ridges. Each ridge is 

about 1 meter higher in elevation than 

the ridge to its east. The surge 

covered three ridges on the southern 

end of the forest. As the surge 

receded each ridge drained rapidly to 

the east. However, water within the 

swales was blocked by the next ridge 

to the east and drained slowly to the 

south in channels clogged with 

uprooted trees. 

In December, groundwater conductivity 

was measured on three transects of 

piezometers across a ridge swale 

watershed in the area covered with 

salt water. Conductivity in groundwater beneath the swale ranged from 10 

to 15 millimhos/cm while along the 

eastern ridge values of 3-5 millimhos/ 

cm were recorded. Franscois (1980) 

found many pine species could not 

survive when conductivity of soil 

water exceeded 5 millimhos/cm and very 

few plants could tolerate values 

higher than 10. On this one watershed 

the pattern of high salinity groundwater and tree mortality were similar. 

FUTURE PROBLEMS 

The greatest risks to the remaining 

trees are fire and insect attack. 

Normal amounts of fuel in the coastal 

plain forest are approximately 4-16 

metric tonslha. In the wake of the 

hurricane, fuel loads are in excess of 

135 metric tons/halO, greatly increasing both the danger of a large fire 

and the difficulty of suppression. 

Surveys of the FMNF show that insect 

infestation of the down and damaged 

trees is occurring. Table 3 shows the 

extent of infestation by 3 southern 

species of Ips. spp. bark beetles. 

Southern pine beetles (Dendroctonus 

frontalis) are beginning to be found 

in insect traps in the impacted area1'. 

Attacks of these insects are fatal. 

On the area of Hobcaw Forest impacted 

by the storm surge, large numbers of 

trees not killed by salt intrusion are 

now dying from attacks by southern 

pine beetle and Ips. 

SUNltJURY 

Within the eyewall, where winds were 

43 to 66 ms-', there was little 

difference between the wind resistance 

Table 3--dps. spp. bark beetle activity 

on the Francis Marion National Forest 

as of mid-April, 1990." 

Trees Tops Removed thrown 

Number trees sampled 0 5 2 4 5 2 3 

Number infested trees 0 5 2 42 2 3 

Percent infested 0 100 9 3 100 

" Trip report on bark beetle and other pest activity in 

Hugo damaged timber, Francis Marion National Forest, 

South Carolina. Patrick J. Barry, State and Private 

Forestry. May 18, 1990. 

of longleaf pine, loblolly pine, and 

bottomland hardwoods, with 89%, 91%, 

and 86% of the trees broken or 

uprooted, respectively. However, on 

Hobcaw Forest, about 100 km from the 

center of the eye, 73% of the longleaf 

pine was undamaged, 48% of loblolly 

pine was undamaged and 80% of the 

bottomland hardwoods were undamaged. 

Species resistance to wind damage was 

not meaningful within the area impacted 

by the eyewall of this Category 4 

hurricane. Outside of the eyewall, 

however, species resistance to wind 

damage greatly affects the composition 

of the remaining forest, 

ACKNOWLEDGMENTS 

The authors gratefully acknowledge 

Miles Lawrence, NOAA/National Weather 

Service, National Hurricane Center, 

Coral Gables, Florida, for information 

on the track and intensity of Hugo, and 

Mark P. ow ell, Meteorologist, NO=/ 

Environmental Research Laboratories, 

AoML/Hurricane Research Division, 

Miami, Florida, for the wind analysis 

used in this paper and for his patient 

explanations of wind patterns and 

behavior. The authors are indebted to 

Charles A. Gresham and Donald J, 

Lipscomb of the Belle W. Baruch Forest 

Science Institute, co-investigators on 

the damage survey of Hobcaw Forest for 

the use of that data. 

lo South Carolina Forestry Commission. 

Hurricane Hugo Update. April, 1990. 11 Barry, Patrick J. Trip report on 

bark beetle and other peat activity in 

Hugo damaged timber. Francis Marion 

National Forest, South ~arolina. 

United States, Department of Agriculture, Forest Service, Southeastern Area 

State and Private Forestry, Pest 

Management, May 18, 1990. 
LXTERAmRE CITED 

Barry, P.I.; Anderson, R.L.; Smith, 

K.W. 1982. How to evaluate and manage 

storm-damaged forest areas. Forestry 

Report SA-FR 20, United States Department of Agriculture, Forest Service, 

Southeastern Area Forest Pest Management, Asheville, North Carolina, 13 p. 

Franscois, L.E. 1980. Salt injury to 

ornamental shrubs and ground covers. 

United States Department of Agriculture Home and Garden Bulletin #231. 

U.S. Government Printing Office, 

Washington, D.C. 

Frothingham, E.H. and Nelson, R.M. 

1944. South Carolina forest resources 

and industries. United States Department of Agriculture, Miscellaneous 

Publication No. 552, 72 p. 

South Carolina Forestry Commission. 

1989. Hurricane Hugo Fact Sheet. 

September 26, 1989. 

Williams, T.M.; Lipscomb, D.I. 1989. 

Pine regeneration success of a private 

non-industrial land owner on the South 

Carolina Coast. Southern Journal of 

Applied Forestry 13:25-28. 

Reprinted with permission from Journal 

of Coastal Research SI#8, 291-300, 

Charles W. Finkl, Editor in Chief, 4310 

NE 25th Ave., Ft. Lauderdale, FL 33308 

USA. 
ASSESSmNT OF mRRICANE D 

PERImINTm F 

TION SYSTEM 

Lawrence E. Nix, Dona1 D. Hook, 

James G. Williams, and Donald Van S31aricom1 

INTRODUCTION 

The Santee Experhental Forest (SEF) 

experienced the full force of the 

eyewall of Hurricane Hugo and sustained extreme wind damage (Hook and 

others 1991). Preliminary estimates 

indicate that 80 percent of the trees 

on the experimental forest were blown 

down or damaged to the extent that 

they will not recover. Aerial photographs made immediately after the 

storm and subsequent measurements on a 

few plots show that the tallest and 

largest (dominant) trees were damaged 

most. Those trees in the midstory and 

young regeneration suffered less 

damage. Loblolly pine (Pinus taeda) 

appeared to suffer the greatest amount 

of stem and top breakage of any 

species on the forest. In contrast, 

losses of large-crowned hardwood 

species, such as Shumard oak (Quercus 

shumardii), cherrybark oak (Q. 

pagoda), and yellow poplar 

( Liriodendron tulipifera) , were 

primarily due to uprooting. 

Although reports are available on 

hurricane damage for other regions of 

the East and South, very little is 

available for the Carolinas. Furthermore, Hurricane Hugo was a category 4 

storm and affected a larger area and 

downed more timber than any previous 

natural catastrophe in the U.S. (Hook 

and others 1991). Thus, a unique 

opportunity exists to study the effect 

of a major storm on the forests of 

this region and help unravel the role 

'Associate Professor, Professor, and 

Coordinator of Planning and Research, 

respectively, Department of Forest 

Resources, and Research Associate, 

Strom Thurmond Institute, Clemson 

University, Clemson, SC 29634. 

that hurricanes play in shaping the 

forests of this region. 

Geographic Information Systems (GIs) 

were not available to help assess past 

hurricane damage. However, the newly 

acquired GIs of the Francis Marion 

National Forest (FMNF) proved to be 

helpful in making management decisions 

on Hugo recovery actions on the forest 

(Rivenbark 1990). Research has not 

fully explored the role that GIs can 

play in assessing damage, analyzing 

management choices, and evaluating the 

impact of hurricanes on the ecology of 

coastal forests (Mead and others 1990). 

This study attempted to determine the 

ability of GIs to analyze relationships 

between or among site, stand, management conditions, and approximate wind 

velocities as they related to damage 

classes on the SEF and FMNF. Since 

considerable historical and scientific 

data were available for many sites on 

the SEF, there was an opportunity and 

need to capitalize on this information 

to determine how prior site and stand 

characteristics influenced the level of 

hurricane damage to specific forest 

types. 

This study was limited to the SEF and 

selected forest types on the FMNF. 

Existing information on stand characteristics, species, soils, hydrology, 

and past management activity was used 

to determine if they were related to 

stand damage classes within the eyewall 

and progressively away from the eyewall 

to the northeast on the FMNF, This 

information allowed us to evaluate, in 

an indirect way, the factors that 

played significant roles in predisposing the forest to hurricane damage 

in relation to wind forces. Near the 

center of the eyewall, there was almost 

total destruction of all age classes. 
Influence of individual stand conditions and soilfsite differences 

appeared to be expressed as the 

distance from the eyewall increased to 

the northeast and wind speed 

decreased, The purpose of this study 

was to determine if GIs technology 

could effectively ferret out soil 

characteristics, prior stand conditions, hydrology, and prior management 

activities that influence the resistance of coastal forests to hurricane 

damage. 

mTERI&S AND mTHODS 

Low level aerial photographs of the 

SEF were taken and delineated for 

cover type, size and density by private contractor. This photography and 

its interpretation were used to help 

build a GIs database for the SEF. 

Pre-Hugo aerial photo stand delineations were digitized in Arc/Info@, a 

vector-based GIs software and, along 

with the USDA soils and the USDI 

National Wetlands Inventory maps, were 

overlaid with post-Hugo aerial photodelineations. An improved wetlands 

map was created by GIs overlay of 

digitized color-infrared aerial photos 

with a Global Positioning System 

(GPS)-augmented, field-corrected 

wetlands map, which was then "rubbersheetedw to conform to the compartment 

and hydrology base maps. Photo 

delineation of pre- and post-Hugo 

stands, photo estimation of stand 

density and product size classes and 

regression prediction of number of 

trees and basal area per acre, and 

timber volumes, done under separate 

contract, were used to develop a GIs 

database of stand damage based on 

difference in pre- and post-Hugo stand 

condition. GIs was used to evaluate 

the pre- and post-Hugo aerial photo 

stand cover type delineation. Once 

the wetlands had been delineated, 

overlaid and mapped, the data were 

entered into the existing GIs database 

for the SEF and used for analytical 

purposes to evaluate soil, stand, and 

previous management influence on 

hurricane damage. The GIs software, 

Arc/Info@, was used in conjunction 

with existing data on stands, soils, 

hydrology, prior management activities 

and wind speed to assess the following : 

1. spatial distribution of stand 

damage in relation to physical and chemical soil characteristics of delineated and mapped 

wetland landscapes on the SEF. 

2. species and stand characteristics that predispose stands to 

hurricane damage along a wind 

gradient on the FNNF. 

3. effect of prior stand management/ 

condition on hurricane damage. 

Specifically, for the SEF, stand, 

soils, wetlands, and hurricane wind 

field maps of the SEF were digitized 

into ~rc/Info@ and overlaid such that a 

large database (4500 entries) was 

created of the spatial coincidences of 

these factors. A revised, small-scale 

wind field map of Hugo on South 

Carolina, created from aerial damage 

surveys by T. Fujita of the University 

of Chicago (Powell and others 1991), 

was provided by the U.S. Forest Service 

Laboratory in Charleston, SC. Soils 

information and series polygons were 

digitized from USDA Soil Conservation 

Service county soil maps of the study 

area, In addition, compartment maps of 

an on-the-ground, post-Hugo damage 

assessment of the SEF, also provided by 

the Charleston Laboratory, were pointdigitized into the Arc/Info@ database. 

This assessment was an extensive ground 

sample consisting of 0.1 acre plots 

done along transects on approximately 3 

x 5 chain (66 feet) grids resulting in 

a theoretical digitized resolution of 

1.5 acres. Thiessen Polygon Logic was 

used with ~rc/~nfo@ to convert the 

ground points (plot centers) to a 

"cover type" polygon map equivalent to 

a "stand" map. We felt that this gave 

a better resolution, damage assessment 

and stand coverage than the post-Hugo 

photo delineations by the contractor. 

Stand damage was based on loss in basal 

area (difference in pre- and post-Hugo) 

as derived from the ground sample plots 

and separated into three classes of 

damage, light, medium and heavy. Relationship of the variables was examined 

by correlation analysis to provide a 

preliminary evaluation of the influence 

of predisposing site, stand, and wind 

speed factors. Stand variables examined were cover type, product size, 

basal area, and stand condition including density and size of trees (USDA 

Forest Service 1988). Soil variables 

used were standard soil series characteristics, e.g., surface texture and 

thickness, drainage class, depth to 

mottling, hydricity, and flooding 

propensity, frequency and duration. 

Wind speeds were spatially interpolated 

directly from the digitized wind field 

map using a 5th order polynomial in 

TIN@, an Arc/Info@ module. These 
interpolated wind speed values were 

assigned to the existing soils polygons in which they were located. 

There was little variation in wind 

speeds on the SEF, most exceeded 100 

miles per hour (mph). Also, resolution of the small-scale wind field map 

was low, approx tely f 10 chains. 

Subsequent to this analysis of the SEF 

ge, we received an extensive 

ArcfInfoet digital data set of the FMNF 

from the South Carolina National 

Forest Management Headquarters in 

Columbia. This data set was very 

large, producing 27,000 samples after 

overlaying the stand and soils maps 

with the interpolated wind speeds 

across the Witherbee and Wambaw 

Districts of the FMNF. Much of the 

same data as obtained for the SEF was 

included in the FMNF database, except 

that it was already digitized and 

polygonized into stand format with 

soil polygons within the stands. This 

data set had already been assigned 

stand damage classes based on differences in pre- and post-Hugo trees and 

basal area per acre. Only the pine 

cover types, mainly lobPolly and Pongleaf (P. palustris) pine, and the 

poletimber and sawtimber size stands 

had been examined and assigned a 

damage class. Removal of all non-pine 

stand samples from the data set left 

about 15,000 samples. Again, a 

preliminary correlation analysis of 

the data was performed to evaluate 

variable performance and rogue 

nonessential variables. 

Examination of the data revealed that 

there were many multiples of the same 

damage and stand condition class with 

different soil and wind speed values, 

thus, greatly diluting the influence 

of these variables on damage class. 

we consolidated all variables at the 

stand level, averaging continuous 

variables (soil surface thickness, 

depth to mottling, wind speed, etc.) 

and taking the mode of discontinuous 

variables (drainage class, texture, 

flooding frequency, etc.). These 

steps resulted in about 11,000 samples 

remaining, which were now simple stand 

polygons, with single values for all 

variables to be used in the analysis. 

The consolidation also more closely 

matched the resolution of the wind 

speed data. 

Discriminant Data Analysis 

The first step in the data analysis 

consisted of some minor editing 

and simple statistics. Means, 

correlations, and other s-ry statistics were run by d ge classes, by 

forest types, by s /site variables, 

wind speed and stand conditions (SAS 

1989). We determined that discriminant 

analysis would be the appropriate 

method by which to characterize the 

e classes (Afifi and Clark 1990, 

SAS 1989). By using the initial 

ry statistics and stepwise 

discriminant analysis, the following 

variables were selected for development 

of the discriminant function: 

Stand condition (STCN) 

Soil surface texture (SURFTEX) 

Soil surface thickness (SURFTHK) 

Soil depth to mottling (DEPMOT) 

Ratio of soil surface thickness 

to depth to mottling 

(THKMOT = SURFTHK/DEPMOT). 

The data set was stratified by wind 

speed into three wind speed classes and 

a separate discriminant function 

developed for each class. The wind 

speed classes are as follows: low = 

77-91 mph; medium = 92-105 mph; high = 

106-120 mph. 

It was very difficult to discriminate 

between the light and medium d 

classes on the FMNF using the 

data. Accuracies of classification 

ranged from 61 to 69 percent when all 

three damage classes were used. The 

heavy damage class was always classified with accuracies greater than 90 

percent, but the light and medium 

damage class accuracies were no more 

than 50 percent. Since the Wambaw 

District stands had not been assigned a 

medium damage class, pooling the light 

and medium damage classes resulted in 

considerable improvement in the 

accuracy of classification between a 

"heavy damage" class and a "light 

damage" class. 

The FMNF data set was divided into two 

parts, one for fitting the discriminant 

function and the other for crossvalidation of the resulting model 

(Afifi and Clark 1990). Separate 

discriminant functions were then 

developed for each wind speed class 

and checked for accuracy. In crossvalidation the discriminant function 

is computed for a set of samples, then 

used to classify a different set of 

samples to estimate the proportion of 

samples correctly classified. The 

FmF data were divided by extracting 

every other sample, resulting in about 

5,000 samples each in the two new data 

sets, one to be used to develop the 
discriminant function, the other for 

cross validation. 

RIESaTS 

Santee ~xperimental Forest 

A GIs database was developed in 

Arc/InfoO for the SEF and its forested 

wetlands and conveyed to the Forestry 

Sciences Lab in Charleston where one 

of the authors assisted in its installation on the resident ~rc/Info@ 

system. ~aving GPS-located ground 

points available greatly improved the 

wetlands mapping process. Pre- and 

post-Hugo photo stand delineations 

were compared by overlaying in 

ArcfInfoO. The results indicated that 

the contractor had a 20 percent error 

or difference between pre- and postHugo aerial photo delineations of 

cover types or stands. The error 

consisted mostly of post-Hugo delineation of hardwood cover types as pine 

cover types, with very few pine stands 

being delineated as hardwood on the 

post-Hugo photos. Part of this error 

resulted from using different delineation criteria with the post-Hugo 

photos. The post-Hugo delineations, 

which were very difficult to begin 

with because of the heavy damage (loss 

of overstory), were altered with GIs 

overlay to conform to the pre-Hugo 

stand/cover type delineations and used 

to develop the GIs database of the 

SEF. It would have been helpful if 

the photo-delineation of post-Hugo 

conditions could have been done with 

the aid of a GIs-generated, pre-Hugo 

overlay to outline the former stands 

and note their pre-Hugo cover type. 

The ground damage assessment of the 

SEF was overlaid onto the stand 

coverage and reconciled with the other 

sources of spatial information, such 

as the USDI Fish and Wildlife Services' NWI wetlands delineation, 

resulting in a well-delineated digital 

database to spatially analyze. 

Results of the initial correlation 

analysis, however, indicated no damage 

predictive capability of any stand or 

soil variable, as correlation coefficients were all less than 0.14. Stepwise regression analysis produced 

R-square values less than 0.02. 

Although disappointing, these results 

were not surprising in view of the 

extensive, heavy damage that occurred 

throughout the SEF. Wind speeds were 

at eyewall velocities (r 105 mph) 

throughout the SEF after Hugo's 

landfall (Hook and others 1991), and 

probably overwhelmed any inherent 

resistance to damage. 

Francis Marion National Forest 

Initial results of correlation analysis of the GlS-overlaid data from the 

Witherbee and Wambaw Districts of the 

FMNF were encouraging. At least one 

variable, stand condition class, a 

Forest Service characterization of the 

size and density of the trees (USDA 

Forest Service 1988), stood out as a 

good damage predictor variable. During 

stepwise regression analysis, variation 

in stand condition accounted for 48 

percent of the variation in stand 

damage; no other variable accounted for 

more than 1 percent of damage variation. Initial stepwise discriminant 

analysis (Afifi and Clark 1990, SAS 

1989) not only highlighted stand condition as a good predictor of damage, but 

also resulted in 90+ percent accuracy 

of predicting high damage. However, no 

separation of the light and medium 

damage classes was feasible as accuracies were 50 percent or less. After 

the light and medium damage class 

samples were combined into a "light" 

damage class, the discriminant functions immediately improved to a 93 

percent accuracy. 

After further refining the data sets by 

stratifying into 3 wind speed classes 

and rerunning the stepwise discriminant 

analysis, overall classification accuracy was 95 percent for the low and 

medium wind speeds and 85 percent for 

the high wind speed. In addition, 

variables other than stand condition, 

egg., soil surface thickness and texture, and depth to mottling, became 

statistically significant contributors 

to classification accuracy. 

The following discriminant functions 

were computed for each wind speed 

class. The notation follows Afifi and 

Clark (1990). 

Wind Discriminant 

Speed Function 

- Class Coefficients 

High Z = 1.16246 (STCN) - 

0.00427 (SURFTEX) - 0.04389 

(SURFTHK) + 0.03250 

(DEPMOT) + 0.54477 

(THKMOT), C = 9.67983 

Med Z = 3.10135 (STCN) - 

0.07802 (SURFTEX) - 0.02894 

(SURFTHK) + 0.05451 

(DEPMOT) + 0.09913 

(THKHOT), C = 27.22875 

Low Z = 2.73050 (STCN) + 

0.06318 (SURFTEX) + 0.01501 

(SURFTHK) + 0.01184 

(DEPMOT) + 0.02835 

(THKMOT), C = 23.91123 
For a new sample stand, the procedure 

is to calculate a Z-value for each 

wind speed class, compare the Z-value 

to C; if Z is greater than the appropriate C then the sample is classified 

gea class, otherwise the 

sample is classified as "heavy damage" 

class. 

The average error rate using the 

cross-validation procedure with wind 

sped classes was 9.4 percent. Incorporating the wind sped classes in the 

computation of the discriminant functions resulted in a 3.7 percent 

increase in accuracy. The reduced 

errors (.(= 5 percent) in the low and 

medium wind speed classes, which 

ranged from 77-91 mph and 92-105 mph, 

respectively, indicate that, as suspected, at less-than-eyewall velocities, the soil and site variables 

interact with the stand condition to 

improve prediction of damage class. 

The damage prediction error for the 

high wind speed class is nearly 15 

percent, which indicates an increasing 

potential for a hurricane to overwhelm 

the influence of stand, soil and site 

variables in resisting damage with 

winds exceeding 105 mph. Summary 

statistics (Tables 1-3) indicate that 

sparse sawtimber was damaged most, 

immature poletimber was damaged least 

and, of the soil variables, only 

surface thickness differed enough to 

have influenced stand resistance to 

wind damage at all windspeeds. 

DISCUSSION 

Assessment of forest damage caused by 

Hurricane Hugo was greatly facilitated 

by the development of an Arc/Info@ 

GIs-database for the SEF and FMNF. 

GIs overlay made it possible to assign 

wind speed and soil attributes to 

stands and evaluate their effects on 

damage resistance. The initial 

analysis of the SEF data indicated 

that wind speed at or near the eyewall 

of the hurricane was so great and 

ge so extensive that any inherent 

ge resistance features of the SEF 

stands, such as prior stand condition, 

soillsite variables, or the effect of 

small differences in wind speed had 

little or no mediating effect on the 

destructiveness of the high winds. 

The resolution of the database was 

sufficient to have detected any relationship between damage and stand 

factors if it existed, as stands and 

soil polygon data were at a resolution 

of at least f 3 chains (198 feet) and 

more likely were closer to the 30 

meter (a 100 feet) resolution of the 

digital soils data. 

The availability of the existing FMNF 

GIS database of stand condition class 

ge was very helpful and 

initial correlation analysis indicated 

that pre-Hugo stand condition was a 

strong predictor of resistance to wind 

ge. Overlay of soils and wind 

speed data made it possible to examine 

their effects on wind damage resistance 

of stands. Discriminant analysis 

resulted in excellent initial prediction of stand resistance to wind damage 

(85 percent accuracy). Stand condition 

continued to be the best predictor of 

stand resistance to hurricane wind 

damage (R* = 0.70). Reducing the 

damage classes to light and heavy and 

adding wind speed classes, improved 

overall damage prediction from 87 

percent to 92 percent accuracy. As 

wind speed increased, damage became 

more random, i.e., overall prediction 

of damage was less accurate (86 

percent) in the high windspeed class. 

The average stand condition incurring 

heavy damage across all wind speeds was 

6.14 or sparse sawtimber (Table 1). 

Nearly 90 percent of all heavily 

damaged stands were sparse sawtimber 

(Table 2). The average stand condition 

incurring light damage across all wind 

speeds was 10.83 or very close to 

immature poletimber (Table l), Over 80 

percent of all lightly damaged stands 

were immature poletimber or sawtimber 

(Table 3). It is obvious that larger, 

more widely-spaced pine sawtimber 

stands suffered the most damage from 

Hugo among the pine stand condition 

classes examined (Figure 1). It is 

equally as obvious that smaller, more 

closely-spaced pine poletimber stands 

were resistant to damage from Hugo's 

winds (Figure l), It is probable that 

the wedging or lifting effect of the 

denser, shorter, immature poletimbersized stands deflected the wind force 

upward and over them, while the mutual 

support of stems at close intervals 

provided some degree of protection from. 

breakage or uprooting, Stem flexibility might also have contributed to 

resistance to damage, especially that 

of wind breakage. 

Some of the soil/site variables might 

have differed enough to have caused 

some stand wind damage resistance 

(Table l), Soil surface thickness, 

depth to mottling, and surface 

thicknessldepth mottling differ 
Table 1. Mean pre-Hugo stand and site variables for wind speeds and damage 

classes used in the analysis of pine stand wind damage during Hugo on the 

Francis Marion National Forest.' 

WINCLS GE STCN SURFTEX SWTHR DEPMOT THKMOT 

ry Stats for 112 Data Set Used for Fitting Model 

High HD 6e1** 2e6N~ 14.1* 13. 5Ns 

High LT 10.0 2.5 15.4 14-0 

Med HD 6*1** 2.8, 11.8** 12. 7Ns loo** 

Med LT 11.2 2.6 15.1 13,O 1.2 

LOW HD 6e2** 10. I** 9*8** le2** 

Low LT 11.0 13.1 12.9 1.3 

Summary Stats for 1/2 Data Set Used for Cross-Validation 

High HD 6*1** 2*6** 14*5,, 13,4, leo** 

High LT 10.2 2.3 16.4 14.6 1.0 

Med HD Gel** 2*9** 11.9** 12.1* 1.1, 

Med LT 11.2 2.6 14.3 13.2 1.1 

LOW HD 6*2** 10.9,, ll.O** I*2** 

Low LT 10.9 13.0 12.2 1.3 

STCN = stand condition class; STCN 6 = sparse sawtimber; STCM 10 = 

mature sawtimber; STCN 11 = immature poletimber 

NS not significantly different at the .05 level of pr~bability within wind 

class * significantly different at the -05 level of probability within wind class ** significantly different at the .O1 level of probability within wind class 

SURFTEX = soil surface texture class; 1-8, sandy through clayey textures 

SURFTHK = soil surface thickness; range = 1-50 inches 

DEPMOT = soil depth to mottling; range = 3-50 inches 

THKMOT = soil surface thickness/depth to mottling; range = 0.05-3.00 

Table 2. Distribution of heavily damaged longleaf and loblolly stands among 

wind speed and stand condition classes on the Francis Marion National Forest 

after Hugo. 

Distribution (%) 

Wind speed No. Stands Sparse Sparse 

Covertype Class Heavily Damaged poletimber Sawtimber 

Longleaf (3,396) High 

Med 

Low 671 0.3 93.9 

SUBTOTAL 1499 4.6 88.8 

Loblolly (7,446) High 1199 7,O 91.6 

Med 1114 2-9 93.7 

Low 1191 15.4 79.6 

SUBTOTAL 3504 8.5 88.2 

Both (10,842) TOTAL 5003 7.3 88.3 
Table 3. Distribution of lightly damaged longleaf and loblolly stands among 

wind speed and stand condition classes on the Francis Marion National Forest 

after Hugo. 

Covertype 

Wind speed No. Stands 

Distribution I%) 

Stand Condition Code1 

class Lightly Damaged 10 11 12 All 

Wngleaf (3,396) High 553 15 49 31 95 

Med 545 5 38 57 90 

Low 799 30 20 49 99 

SUBTOTAL 1897 18 33 46 95 

Loblolly (7,446) High 602 0 52 20 722 

Med 1158 7 38 51 96 

Low 2182 12 45 39 96 

SUBTOTAL 3942 9 44 40 92 

Both (10,842) TOTAL 5839 12 40 42 93 

Stand condition codes are defined as follows: #10 - mature sawtimber; 

#11 - immature poletimber; #12 - immature sawtimber 

About 28% of the lightly damaged loblolly stands in the high wind class were 

in stand condition classes 5 and 6, sparse pole and sawtimber. No 

explanation for this anomaly has been forthcoming. 

Longleaf and Loblolly Pine 

(10,842 etands) 

Heavv Damaae 

/ 

Conditions / stana \ 

Light Damage \ 

Stand 

Conditions 

(5) 

Sparse Polea is) (11) 

Sparse Sawtimber Immature iPoles Immature Sawtimber Mature Sawtimber 

7.3% 88.3% 40% 42% 

Figure 1. Distribution of loblolly and longleaf pine stands among damage and 

prior stand conditions after Hugo on the Francis Marion National Forest. 
significantly between the high damage 

ge classes at low and 

peed (Table 1). Surface 

texture, a class variable, should not 

be considered in the same light as the 

other variables, as the small difference in values, though statistically 

significant, would provide no real 

difference in texture of the soil to 

contribute wind resistance to the 

stand. In addition, the small difference in any of the soil variable means 

at the highest windspeed could not 

have made any real difference in 

ge incurred. However, as much as 

2-3 inches difference in soil surface 

thickness and depth to mottling at 

low and medium wind speeds may have 

actually contributed some wind resistance to the FmF pine poletimber and 

sawtimber stands during Hugo. It is 

hoped that, eventually, damage classes 

will be assigned to the rest of the 

forest cover types on the FMNF so that 

a GIs-based assessment of the relationship between stand, soil, and site 

variables can be done for the hardwood 

stands, especially the bottomland and 

wetland stands. 

ACKNOWLEDGMENTS 

This study was largely supported by 

the USDA Forest Service Southeastern 

Forest Experiment Station. The 

authors gratefully acknowledge the 

provision of the large, essential 

digital data set of the Francis Marion 

National Forest by Don Norris, staff 

member at National Forest Management 

Headquarters in Columbia, SC. Appreciation is also extended to W. Harms 

and R. Wooper of the Forest Service's 

Charleston Laboratory for valuable 

review and discussions of this effort. 

LZTEIUllrliSfm CITED 

Afifi, A.A.; Clark, V. 1990. ComputerAided Multivariate Analysis, Second 

Edition. Van Nostrand Reinhold Co., New 

York, 505 p. 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Huga on 

the South Carolina coastal plain 

forest. J. Coastal Res., SI #8, 

PO 291-300. 

Mead, R.A.; Johnston, R.; Weaver, S.P. 

1990. Using GIs for assessing timber 

salvage recovery options and impacts 

related to resource management in the 

wake of Hurricane Hugo. USDA For. 

Serv., South. Reg., GIs Applic. Note 1. 

9 P. 

Powell, M.D.; Dodge, P.P.; Black, M.L. 

1991. The landfalL of Hurricane Hugo in 

the Carolinas: Surface wind distribution. Weather and Forecasting 6:379- 

399. 

Rivenbark, L. 1990. GIS makes hurricane 

recovery a breeze. Federal Computer 

Week, July 1990, p. 12 and 16. 

SAS Institute, Inc. 1989. SAs/STAT@ 

Guide for Personal Computers, Version 

6, 4th Edition, Vol, I. Cary, NC. 

943 p. 

USDA Forest Service. 1988. Field Book: 

Silvicultural Examination and Prescription. USDA Forest Service, Southern 

Region, Atlanta, GA. 35 p. 
GIE: ASSESS OF 

B IN SOUTH LINA 

Kenneth Pittman, Re C. Kellison, and Russ ~ea' 

Abstract--Of the 1.732 million acres of bottomland 

hardwoods in the 23-county area affected by Hurricane 

Hugo, 1.329 million acres suffered storm damage. 

However, the hardwood growing stock on the area was 

reduced by only six percent, from 5.1 to 4.8 billion 

cubic feet, from immediate mortality. Delayed mortality of hardwoods is expected to reduce the growing 

stock to an accumulated total of 20 percent which is 

comparable to the immediate mortality of softwoods. 

Trees of increasing diameter were more subject to 

windthrow than those of smaller size. Trees most 

subject to severe damage (windthrow) were the oaks, red 

maple, and yellow-poplar. The gums, occupying the 

swamps, were least damaged. Regardless of species, the 

stands most severely damaged were those of medium 

stocking; i.e., from 60 to 69 percent stocked. Recommendations are given for managing the damaged stands. 

INTRODUCTION 

Hurricane Hugo, packing winds of 135 

miles per hour, struck the mainland at 

Charleston, SC on September 21, 1989. 

Travelling northwestward, it wreaked 

havoc to all within its path until it 

exited the state at Rock Hill during 

the morning hours of September 22 

(Figure 1). 

Aerial and ground surveys by the South 

Carolina State Commission of Forestry 

showed there to be major damage to the 

forests in a 23-county area within the 

path of the storm (Figure 2). The 

surveys paved the way for timber 

salvage, fire- and pest-control 

measures and regeneration planning, 

but they did not provide quantitative 

data to show how the timber supply 

would be affected over the next 

several decades. That responsibility 

accrued to the Forest Inventory and 

Analysis (FIA) Research Work Unit at 

the Southeastern Forest Experiment 

Station, USDA Forest Service, 

Research Associate, School of 

Design, and Professors of Forestry, 

college of Forest Resources, North 

Carolina State University, Raleigh. 

Asheville, NC!. The survey conducted 

between February and June 1990 had the 

following objectives: (1) determine 

the volume of hurricane-related mortality and damage, (2) assess damage to 

merchantable and submerchantable pine 

plantations, and (3) quantify needed 

stand treatments resulting from the 

storm (Sheffield and Thompson 1992). 

As the objectives signify and as the 

results verify (Sheffield and Thompson 

1992), primary interest was on the pine 

resource, now and in the future. The 

hardwood data were further restricted 

because, in the summary results of 

Sheffield and Thompson (1992), the 

inventory of upland hardwoods was 

amalgamated with the bottomland hardwoods. Enough data exists, however, 

for us to quantify needed stand 

treatments (objective #3) for the 

bottoxnland hardwoods in the 23-county 

area. 

NEITHODS 

The post-Hugo (1990) inventory 

consisted of revisiting the 2,530 

permanent plots in the 23-county area 

that had been the basis for the sixth 

survey in 1986 of South Carolina's 

forest inventory (Figure 3). Only 730 
Figure 1--Peak winds (after Fijita damage directions; Powell, Dodge, and 

Black). 

Figure 2--South Carolina counties. 

53 
Figure 3--FIA plots for 23 SC counties. 

of the plots were located in bottomland hardwood stands (FIA forest site 

types 60--oak/gum/cypress, and 70-- 

elm/ash/cottonwood) (Figure 4), and 

all of those were in natural stands 

because commercial hardwood plantations do not exist in the area (Figure 

2). FIA sample plots are based upon a 

10-point cluster design. In most 

cases, five points are installed in a 

single forest condition using a basal 

area factor of 37.5 square feet per 

acre to sample trees 5.0 inches dbh 

and larger. Trees less than 5.0 

inches diameter at breast height (dbh) 

are tallied on 11300-acre fixed plots 

at each of the point centers. More 

detailed information about standard 

FIA field sampling procedures is 

available (Tansey and Hutchins 1988; 

USDA Forest Service 1991). 

In the natural hardwood stands, the 

post-Hugo field crews accounted for 

each tree that was 3.0 inches dbh and 

larger in 1986. This procedure 

provided assurance that any tree that 

had grown large enough to have merchantable volume by 1990 (5.0 inches 

dbh and larger) would be evaluated. 

Each tree was assigned to one of six 

categories: (1) live, without hurricane damage; (2) live, with hurricane 

damage; (3) dead, hurricane related; 

(4) dead, not hurricane related; (5) 

cut, not associated with the salvage of 

damaged stands; or (6) cut, associated 

with hurricane salvage or cleanup 

operation, regardless of whether the 

tree was utilized for a product. Live 

trees with hurricane damage were 

assessed for volume loss, percentage of 

crown missing, lean and bend, root 

damage, degree of damage to the tree 

bole, and salt burn (Sheffield and 

Thompson 1992). 

These assessments served as the basis 

for developing damagefrisk classes for 

the trees on each plot that had not 

been killed outright by the hurricane. 

The classes reflect the likelihood of 

tree survival and present (or potential) value degrade. The categories 

were: 

Class 1. High-risk tree with a high 

probability of dying in the near 
longleaf pine 

slash pine 

loblolly pine 

shortleaf pine 

virginia pine 

red cedar 

pond pine 

oak-pine 

1 50 (9794) oak-hickory 

1111 52 (32) chestnut oak 

57 (660) scrub oak 

60 (1 6322) oak-gum-cypress 

1111 70 (1 393) elm-ash-cottonwood 

Figure 4--Forest type. 

future. Damage and value loss are 

severe enough that this tree should 

not be retained in the stand. 

Class 2. Moderate-risk tree with 

elevated risk of mortality; serious 

current or potential loss of value; 

retention in the stand is questionable. 

Class 3. Low-risk tree that has a 

high probability of surviving, though 

not as high as an undamaged tree. 

Damage and value degrade are minimal. 

These trees should be retained in the 

stand in most management scenarios. 

Class 4. Healthy. No obvious hurricane damage. A tree with hidden or 

internal damage was included in this 

category. 

A complete assessment of current 

stocking and hurricane damage in very 

young natural stands was hampered 

because trees less than 3.0 inches dbh 

were not measured or sampled in 1990. 

Field crews did assess treatment 

opportunities in these stands, 

reflecting the degree of damage. The 

treatment opportunities included 

salvage cut, regeneration, thinning, 

and no action. 

AFFECTED AIREA AND VOLUME 

Of the 6.5 million acres of timberland 

in the 23-county area, 4.5 million 

acres suffered significant storm 

damage. Of this total, 1.732 million 

acres were in bottomland hardwoods of 

which 1.329 million acres (77 percent) 

suffered storm damage. Within the 

damaged area, 267,000 acres had stocking reduced below manageable levels 

from Class #1 injury. This area is 

enlarged to 380,000 and 491,000 acres 

when Class #2 and Class #3 injury is 

included. In summary, no damage 

occurred on 403,000 acres, mortality 

without salvage was complete on 87,000 

acres, salvage was effected on 17,000 

acres, 491,000 acres had stocking 

levels reduced below manageable levels 

from Class #1, #2 and #3 damage, and 

734,000 acres had damage levels below 

Class #3. 

On a volume basis, the inventory of the 

combined upland and bottomland hardwood 

growing stock was reduced from 5.1 to 
4.8 billion cubic feet (6 percent). 

Since the data were combined in the 

analysis and were not available as 

independent sets the assumption for 

this report is that the hurricane 

ge was comparable for bath upland 

and bottomland forest types. The 6 

percent hardwood loss is small in 

comparison to the loss of softwood 

growing stock where the comparable 

value is 21 percent, from 4.8 to 3.8 

billion cubic feet (Sheffield and 

Thompson 1992). The reasons for the 

reduced hardwood loss are: ( 1) low 

salvage cutting--49 million cubic feet 

compared to 376 million cubic feet for 

softwoods, and (2) softwood species 

died more quickly following windthrow, 

bole breakage and crown destruction. 

Many of the hardwood trees--even those 

severely damaged--continue to show 

signs of life for years afterward. 

Some of them will eventually succumb, 

and others will badly degrade over the 

years. The estimate is that about 20 

percent of the hardwoods will suffer 

hurricane-related mortality, comparable to the 21 percent of softwood 

mortality associated with Hurricane 

Hugo damage (Sheffield and Thompson 

1992). 

DAMZlGIEg: CHARACTERISTICS OF 

BOTTOMLAND HARDWOOD STANDS 

I. Physiography 

By the very nature of the hurricane, 

greatest damage was done nearest the 

coast (Figures 4, 5 and 6). Peak 

winds of greater than 65 m s-' were 

encountered in northern Charleston and 

southern Berkeley counties. An 

expanded area in the same two counties 

experienced winds of 60 m s-'. A third 

zone of slightly less intensity (50 m 

s-') encompassed nearly all of 

Charleston and Berkeley counties, 

northern Dorchester, southeastern 

Orangeburg, southern Clarendon, southeastern Calhoun; it pinched out in 

southern Sumter county. The three 

other bands of winds (40, 30, and 25 m 

s-') paralleled one another until they 

exited the state (Figure 1). Despite 

these well-defined wind zones, damage 

to the timber by physiographic class 

cannot be closely correlated because 

of the inclusion of bottomland and 

upland hardwoods into a single 

category. 

11. Tree Size/Diameter Class 

ge was associated with trees 

of increasing size of hardwoods, as 

measured by dbh, than for softwoods 

(Table 1). The 1990 inventory was 

calculated from the more complete 1986 

inventory in which adjustments were 

made for net growth, and regular and 

vals. The results for cubic 

volume are similar to those for sawtimber volume, so only the percentages 

for cubic volume are shown in Table 1. 

Reference is made to Sheffield and 

Thompson (1992), page 45 for cornparable percentages on sawtimber volume. 

In interpreting Table 1, it is emphasized that the mortality of softwoods 

averaged 21 percent across the range of 

diameter classes whereas that for 

hardwoods averaged only 6 percent. 

Among the live softwood trees, however, 

no trend is evident, by diameter class, 

in the percent of healthy trees or in 

those of Damage Class #I, #2 or #3. In 

contrast, the percentage of healthy 

hardwood trees decreases sharply from 

78 for the 6-inch class to 54 for the 

21-inch and larger class. Similarly, 

no trend is evident in the damage 

classes (Class #1, #2, #3) of softwoods 

whereas a distinct change is seen for 

hardwoods, especially for damage 

classes #1 and #3. The apparent 

reasons for these results are that the 

larger-crowned hardwood trees are less 

subject to stem breakage and more 

subject to wind-throw--often without 

immediate mortality--than are their 

softwood counterparts. In addition, 

the root systems of bottomland hardwoods will, on average, be more shallow 

than either upland hardwoods or softwoods. We were unable to test for this 

phenomenon in this exercise because the 

data of the two forest types were 

combined. 

111. Species 

In addition to diameter class, some 

species were more subject to hurricane 

damage than other species. This phenomenon is in contrast to the softwoods 

where the predominant pines of the area 

(loblolly, longleaf, pond and slash) of 

a given size and age class all suffered 

about the same mortality--from 25 to 30 

percent. The exception to this conclusion about softwoods is that baldcypress and pondcypress suffered only 

about 3 percent mortality. Those 

species are similar to many of the 

smaller-crowned hardwoods in that they 

can withstand tremendous wind forces 

without suffering stem breakage or wind 

throw. However, extreme epicormic 

branching has since been observed on 

these species, indicating that they 

were greatly stressed by the hurricane 

winds. 
deep sands 

xeric 

flatwoods 

rolling uplands 

narrow floodplain 

broad floodplains 

(544) mesic 

(236 1 ) deep swamps 

(2845) sma!! drains 

(2 1 25) bays and wet 

(1 044) hydric 

Figure 5--Physiography. 

1. 10 (4 13) 

13 (1 8) 

15 (409) 

16 (383) 

17 (269) 

m 18 (1 57) 

1. 19 (238) 

11 20 (71 7) 

m 21 (251) 

m 22 (635) 

23 (461) 

m 24 (448) 

25 (1 357) 

11111 26 (527) 

27 (868) 

28 (1 207) 

29 (503) 

30 (2566) 

31 (890) 

32 (1 704) 

33 (1 365) 

m 34 (1 354) 

35 (1 834) 

36 (2080) 

37 (1 938) 

38 (225 1 ) 

rzl 40 (33866) 

Figure 6--Damage class 

1.0 high damage 

1.3 

1.5 

1.6 

1.7 

1.8 

1.9 

2.0 

2.1 

2.2 

2.3 

2.4 

2.5 

2.6 

2.7 

2.8 

2.9 

3.0 

3.1 

3.2 

3.3 

3.4 

3.5 

3.6 

3.7 

3.8 

4.0 no damage 
Table l--Status of living softwood and hardwood trees following salvage operations 

in 1990, by dimeter class, for 23 counties in South Carolina affected by Hurricane 

Hugo. 

Diameter Healthy trees Class #la Class #2 Class #3 

class 

( inches ) Stwd Hdwd Stwd Hdwd Stwd Hdwd Stwd Hdwd 

5.0- 6.9 

7.0- 8.9 

9.0-10.9 

11.0-12.9 

13.0-14 9 

15.0-16.9 

17.0-18.9 

19.0-20.9 

21.0 & larger 

All classes 71 68 14 12 9 8 6 12 

a Class #I. High-risk tree; salvage. 

Class #2. Moderate-risk tree; harvest to prevent degrade. 

Class #3. Retain in stand though some degrade is likely. 

The hardwood species most subject to 

damage were the oaks, especially red 

oaks (Table 2). The observation is 

that those species were more common to 

the bottomlands (first bottoms and 

terraces) where they were likely of a 

larger diameter class, with concomitant large crown), and had a more 

shallow root system than their upland 

counter-parts because of a year-round 

high water table, Red maple also 

showed a propensity for severe wind 

damage. That damage is primarily of 

the wind-throw type since that species 

is common to the wet flats of bottomlands where it is characterized by a 

shallow root system. 

Yellow-poplar also suffered higher 

than average damage, as did ash 

(Fraxinus spp.). Both of these 

species or species groups encountered 

stem breakage as the major source of 

damage, as opposed to wind throw. 

Yellow-poplar is noted for its low 

density wood (average specific gravity 

of about -42 for old-growth trees, as 

opposed to about .60 for both red and 

white oaks), with its poor strength 

properties. The wood of ashes is 

known for its resiliency, but it is 

also brash, meaning that when enough 

force is applied for breakage that it 

shatters parallel to the grain. 

Baseball bats exhibit both of these 

characteristics which is why ash is 

preferred as an implement in our 

national pastime. 

Two classes of bottomland trees that 

suffered least damage were bay/ 

magnolia and tupelo/swamp black gum. 

Even though unique to water saturated 

soils, these species have deep root 

systems and, thus, they encountered 

almost no windthrow. The relative 

resistance of tupelo/blackguxn to wind 

damage is similar to that of bald 

cypress which is a common associate in 

the hydric soils of the Lower Coastal 

Plain. 

IV. Stand Density (Stocking) 

Hurricane damage to bottomland hardwoods appears to be worse in stands 

that were intermediate in stocking, as 

opposed to both high and low stocking 

(Table 3). For example, 43 percent of 

the stands that were identified as 

being 100 percent stocked at the time 

of Hurricane Hugo maintained that level 

of stocking following the storm. 

Similarly, stands that were stocked at 

the 30-39, 40-49, and 50-59 percent 

level before Hurricane Hugo retained 

stocking at that level 49, 46 and 50 

percent of the time. Conversely, 

stands with 60-69 percent stocking 

maintained that stocking in only 28 

percent of the cases. To a lesser 

extent, stands with 70-84 and 85-99 

percent stocking were also less able 
Table 2--Status of hardwood species following salvage operations in 1990 for 23 

counties in South Carolina affected by Hurricane Hugo. 

Species Healthy Class #la Class #2 Class #3 

trees 

Select white oaks 

Select red oaks 

Other white oaks 

Other red oaks 

Hickory 

Red maple 

Beech 

Sweetgum 

~upelo/black gum 

Ash 

Cottonwood 

Yellow-poplar 

Bay/magnolia 

Sycamore 

Elm 

All species 69 10 8 14 

a Class #l, High-risk tree; salvage. 

Class #2. Moderate-risk tree; harvest to prevent degrade. 

Class #3. Retain in stand though some degrade is likely, 

Table 3--Percentage comparison of the areas (acres) supporting different 

stocking classes at pre- and post-Hugo inventories for bottomland hardwoods in 

23 South Carolina counties. 

Pre-Hugo Post-Hugo Stocking (percent) 

Stocking 

(percent) 0-14 15-29 30-39 48-49 50-59 60-69 70-84 85-99 100+ 
to hold that stocking compared to 

densities at both lower and higher 

levels. The respective values for 

those two classes were 39 and 36 

percent. 

GEmm PmSCRIPTIONS 

Physiographic Class 

Using the convention of the FIA 

Research Work Unit, the physiographic 

classes supporting httomland hardwood 

in the 23-county area of South 

Carolina are as follows: 

Narrow Floodplains 

Floodplains less than 1/4 mile in 

total-width along rivers and streams. 

They include natural levees and first 

bottoms. These sites are normally 

well drained but are subject to 

occasional flooding during periods of 

heavy or extended precipitation. 

Associated species include sycamore, 

sweetgum, yellow-poplar, green ash, 

willow oak, southern red oak and, 

further inland, black walnut. 

Broad Floodplains 

Floodplains 1/4 mile or wider alona 

rivers and streams. They include * 

natural levees, first and second 

Bottoms and terraces, The mineral 

soils common to these sites are 

normally well drained but are subject 

to annual flooding, especially during 

periods of heavy or extended 

precipita-tion. Species associated 

with this class include cottonwood, 

sycamore, sweetgum, green ash, red 

maple, and cherrybark oak, and toward 

the fringes (terraces) water, willow, 

overcup and swamp chestnut oak. 

Deep Swamps 

Low, wet, flat forested areas, usually 

quite large in extent, which are 

flooded for long periods of time 

except during periods of extended 

drought. They are often associated 

with sizeable streams forming in the 

Lower Coastal Plain. Soil and 

moisture conditions are generally 

quite favorable for forest growth of 

selected species such as tupelo, swamp 

black gum, red maple, green ash, 

sweetgum, yellow-poplar and water, 

willow and laurel oak. Organic soils 

are common to these areas. 

Small Drains 

Narrow, streamlike, wet strands of 

forest land often without a welldefined stream channel. These areas 

are poorly drained or flooded throughout most of the year except during 

periods of extended drought. They 

often serve as drains for the adjacent 

higher ground, distal from the adjoining stream. Associated species include 

bald cypress, swamp black gum, sweetgum, green ash and red and loblolly 

bay. They are characterized by organic 

so+ls . 

Bays and Wet Poeosins 

Low, wet, boggy sites characterized by 

peaty or organic soils, Common species 

associates of these sites include swamp 

black gum, green and Carolina ash and 

loblolly and red bay. Pond pine is 

also common to these areas. 

Other Hydrie 

Includes areas of standing water in 

which there are inlets and outlets 

during stages of high water. Examples 

of these areas include oxbow lakes and 

cypress ponds. The predominant tree 

species are bald cypress, pond cypress 

and tupelo gum. 

Forest Types 

The species groups recognized by the 

FIA Research Work Unit for the bottomland hardwoods in the 23-county area 

affected by Hurricane Hugo are Oak-GumCypress and Eh-Ash-Cottonwood. Seven 

forest types are identified within the 

first group and four in the second 

(USDA Forest Service, FIA Research Work 

Unit, 1991). Their description 

follows: 

Oak-Gum-Cypress 

Swamp chestnut oak-cherrybark oak 

Swamp chestnut oak and cherrybark oak 

comprise a majority of the stocking. 

Associates include ash, hickory, white 

oak, shumard oak, black gum, sweetgum, 

American elm, winged elm, yellowpoplar, and American beech. The locations are alluvial flood plains of 

major rivers, usually in the Coastal 

Plain, where the soils are moist but 

seldom covered with standing water. 

Sweetclum-water oak-willow oak Sweetgum and water, willow and laurel oak, 

either singly or in combination make up 

this type. Associates include green 

ash, red maple, blackgum, over-cup oak 

and occasionally bald cypress. The 

Coastal Plain and lower Piedmont sites 

are low and moist which are representative of drains, poorly drained 

flatwoods, and swamp margins. 

Suqarberrv (hackberrvf-American elmclreen ash The three species comprise 

the majority of this forest type. They 

are joined by water oak, willow oak, 
laurel oak, sweetgum, water hickory 

and boxelder. The type is common on 

imperfectly drained soils of the first 

or second bottom of major rivers and 

streams in the Coastal Plain. 

Wercup oak-water hickory These two 

species comprise a majority of the 

stocking. The associates include 

green ash, hackberry, merican elm, 

and red maple, The type is comon to 

the Coastal Plain where it is found in 

poorly drained sloughs and depressions 

of first and second bottoms of rivers 

and primary streams. 

Cypress-water tupelo Bald cypress and 

water tupelo comprise the majority of 

the type: ~ssociates include green 

ash, red maple, swamp black gum, and 

sweetgum. The type is common to the 

Coastal Plain where flowing water is 

present for the better part of the 

year. The associates would be found 

on the periphery of the water body, or 

on hummocks or ridges within the 

confines . Sweetbay-black qum-red maple The 

associates of this species combination 

would include Atlantic white cedar, 

sweet bay, pond pine, slash pine and 

titi. The organic soils supporting 

this forest type which is unique to 

the Coastal Plain remain saturated 

through-out the year. 

Elm-Ash Cottonwood Group 

River birch-svcamore The type, common 

to the Upper Coastal Plain, Piedmont 

and low mountains, is most frequently 

found along stream margins, on 

recently disturbed land. River birch 

often forms pure stands in such 

situations with sycamore occurring as 

scattered trees which will eventually 

dominate. Associates include ash, 

sweetgum, red maple and yellow-poplar. 

Cottonwood This species infrequently 

occurs as a pure stand, but more commonly occurs in mixture with willow, 

white ash, green ash and sycamore, It 

is most commonly found on point bars 

and secondarily on recently disturbed, 

moist soil along streams and sloughs. 

It is most common to the Coastal 

Plain, but occurs in mixture with 

other species in the Piedmont and low 

mountains. 

Willow This species group almost 

always occurs in pure stands, often on 

point bars, and on recently disturbed 

soils adjacent to streams and sloughs 

where the surface water drainage has 

been adversely altered. On such sites, 

it often serves as a pioneer, giving 

stability to the site until other tree 

species of longer life become established. A comon pioneer associate is 

swamp cottonwood. 

Sycamore-peean-merican elm A mixed 

stand of the three species is sometimes observed, but a more common 

phenomenon is for a pure stand of 

either sycamore or pecan to occupy the 

site. Both species find their niche on 

abandoned bottomland fields or along 

logging roads where there has been 

recent disturbance. Sycamore is more 

common to the Piedmont and low 

mountains, on soils of good internal 

drainage, The latter two species are 

common to the Upper Coastal Plain on 

imperfectly drained soils. 

PRESSCRIPTXON 

Data collected and analyzed by the USDA 

Forest Service FIA Research Unit show 

almost no trends in the severity of 

hurricane damage to the bottomland 

hardwoods of the 23-county area of 

South Carolina. This conclusion 

applies specifically to the seven 

forest types that comprise the Oak-GumCypress Group and the four that 

comprise the Elm-Ash-Cottonwood Group. 

A number of these forest types commonly occur within one or more of the 

six physiographic types (narrow floodplains, broad floodplains, deep swamps, 

small drains, bays and wet pocosins, 

and other hydric) within the area. No 

consistency was found in the damage of 

a forest type either within or among 

physiographic types. 

There is evidence that the severity of 

damage was worse on trees of large 

size, i.e,, greater than 15 inches dbh 

(Table 1) and on species such as the 

red and white oaks, red maple and 

yellow-poplar (Table 2). As a result 

of their large size, the select red and 

white oaks were thought to be more 

prone to damage because of their 

proportionally larger crowns and 

because they more often occupy finetextured, imperfectly drained soils 

which are conducive to development of 

shallow root systems. 

Evidence also exists that stands of 

optimal stocking for tree growth and 

development were more subject to 

hurricane damage than those classes 

that would be considered understocked 

or overstocked (Table 3). A greater 

percentage of the stand area was 

reduced to the next lower levels of 
stocking when the pre-Hugo stocking 

was from 60 to 99 percent. The 60 to 

69 percent class appeared to be 

especially vulnerable* The cause of 

this phenomenon probably lies in the 

partial harvests of many of the 

bottomland hardwood stands, an undesired but ongoing practice where the 

best trees are removed at periodic 

intervals, 

With the general lack of trends in 

tree damage across physiographic and 

forest types, definitive prescriptions 

for timber stand improvement are left 

wanting, However, the following 

observations and recommendations 

should be helpful to the timberland 

owner in upgrading affected bottomland 

hardwood forest, 

1. The deep swamps, small drains, 

bays and wet pocosins and 

"other" hydric physiographic 

class offer the least opportunity for timber stand 

improvement. Even though 

considerable stem and crown 

breakage occurred in these 

types, relatively little 

windthrow was encountered. The 

lack of wind-throw is the result 

of the crown architecture of the 

species (columnar and single 

stemmed) and the deep rooting 

habit of the species. 

The year-round water saturated 

soils of these physiographic 

classes will largely prohibit 

ready access of wheeled or 

tracked logging equipment for 

anything much less than complete 

harvest of the timber. Therefore, little economic opportunity exists for upgrading 

these stands. 

2, The narrow floodplains of the 

Coastal Plain, Piedmont and low 

mountains offer the greatest 

opportunity for timber salvage 

as well as for timber stand 

improvement. These lands are 

generally accessible from the 

high banks* In addition, the 

soils within the floodplain are 

without standing water for all 

but a few weeks a year, 

The recommendation is to 

identify the older stands of 

marginal stocking for first 

entry. If the stands are 

severely damaged, the 

recommendation is to clearcut 

the timber, leaving only those 

trees that will have wildlife 

value but in low enough quantities that the ensuing seedling 

and sprout regeneration is not 

adversely affected, For stands 

less severely affected, i,e., 

where residual stands exist of 40 

ftZ/ ac basal area or more, 

salvage harvesting should be 

conducted as soon as practical to 

renrove the affected timber. The 

harvest should be scheduled 

during autumn to take advantage 

of existing seed crops, and to 

benefit from optimum traffic 

conditions that result from 

normal low rainfall of this 

season of the year, 

3, The broad floodplains offer 

similar opportunity for regeneration and timber stand 

improvement as do the narrow 

floodplains, The exception is 

that trafficability will be more 

restricted during the rainy 

seasons. Priorities for treatment of these areas are to 

concentrate on the older and 

poorly stocked portions of the 

stands, especially where large 

diameter oaks, and to a lesser 

extent, ash and yellow-poplar, 

make up a large component of the 

stand. 

The prescription for managing the 

damaged stands of this 

physiographic class perhaps 

carries more urgency than do the 

narrow floodplains* The reason 

is that the understory, shadetolerant species composition 

common to this class, i.e., 

ironwood, dogwood, redbay, 

American holly, and to a certain 

extent sugarberry, elm and 

boxelder, will benefit from the 

effects of the storm at the same 

time that the desired overstory 

species have been killed or 

variously damaged. In most 

salvage operations, whether a 

clearcut or a partial harvest, 

the understory species will have 

to be controlled to allow the 

light-demanding, overstory 

species to regenerate and 

develop, Control of the undesirables can be accomplished in a 

number of ways. Chain-saw felling, girdling, shearing and 

surface-applied or injected 

herbicides are proven methods of 

control. 
LITERATURE CITED 

Sheffield, Raymond M.; Thompson, 

Michael T. 1992. Hurricane Hugo: 

Effects on South Carolina's Forest 

Resource, USDA Forest Service Res. 

Pap. SE-284, Asheville, NC. 51 pp. 

Tansey, John 33.; Hutchina, Cecil C. Jr, 

1988, South Carolina's Forests, USDA 

Forest Service Resour, Bull, SE-103, 

Asheville, NC. 96 pp, 

USDA Forest Service. 1991. Field 

Instructions for the Southeast, 

Asheville, NC. 
E HUGO WIND 

COASTAI; FOMST TREE SPECIEX 

C. Ao Gresham, To Ho Williams, and D. Jo ~ipscomb' 

Abstract--One percent of Hobcaw Forest, a 3077 ha tract in 

south Carolina's lower coastal plain, was inventoried with 

fixed area plots within four months after the eye of 

Hurricane Hugo passed 97 km south of the forest. Results 

of this sampling confirmed our hypotheses that the amount 

and nature of hurricane wind damage differed among the tree 

species sampled. Approximately 73 percent of the 16,870 

trees inventoried were either not damaged or had light 

crown damage. Longleaf pine (Pinus palustris) was less 

damaged than loblolly pine (Pinus taeda) or pond pine 

( Pinus scrotina) . Bald cypress ( Taxodium distichum) 

suffered light crown damage. Upland oaks were more heavily 

damaged than the pine species. Live oak (Quercus 

virginiana) was less damaged than laurel oak (Quercus 

laurifolia) and water oak (Quercus nigra), Those tree 

spescies commonly found in the lower coastal plain (longleaf 

pine, bald cypress, and live oak) suffered less damage than 

species with larger natural ranges. 

INTRODUCTION 

On September 22, 1989, the eye of 

Hurricane Hugo came ashore 20 km east 

of Charleston, SC with estimated 

maximum sustained winds of 222 km/hr 

and a barometric pressure of 93.4 ma 

in Charleston (Purvis and others 

1990). It proceeded northwest (Figure 

1). In Georgetown, 97 km north of 

Charleston, the mean wind speed was 

estimated to be 87 km/hr with gusts of 

138 km/hr (Purvis and others 1990). 

Hobcaw Forest, 7 km southeast of 

Georgetown, was less damaged than 

forests closer to the hurricane's eye, 

but it was enough damaged to determine 

the sensitiv-ity of several coastal 

plain tree species and size classes to 

hurricane winds. This report 

summarizes the results of an intensive survey of tree damage in Hobcaw 

Forest immediately following Hurricane 

Hugo, The objective of the survey was 

to quantify hurricane wind damage to 

common tree species of Hobcaw Forest 

Associate Professor, Professor, and 

Forest Director, Department of Forest 

Resources, Baruch Forest Science 

Institute of Clemson University, P. 0. 

Box 596, Georgetown, SC 29442 U.S.A. 

to test the hypothesis that the damage 

was not similar among species and among 

size classes within species. We 

hypothesized that loblolly (Pinus taeda 

L.) and longleaf pine (Pinus palustris 

Miller) would exhibit different kinds 

of wind damage because of foliage and 

branch morphological differences, and 

that pond pine (Pinus serotina Michaux) 

and loblolly pine would be damaged in 

similar ways, because they are morphologically similar. Bald cypress 

(Taxodium distichum (Lo) Richard) has 

deciduous foliage and fine branches, 

unlike the other conifers, which could 

contribute to its previously observed 

ability to withstand strong winds. 

Water oak (Quercus nigra L,), Laurel 

oak (Quercus laurifolia Michaux), and 

southern red oak (Quercus falcata 

Michaux) grow taller, have an excurrent 

canopy! and would be more wind damage 

sensitive than live oak (Quercus 

virginiana Miller) with its deliquescent canopy. 

METHODS 

The study was conducted on the 3077 ha 

Hobcaw Forest (33 20' N, 79 15' W) 

which occupies the southern tip of the 

Waccamaw Peninsula in Georgetown 

County, South Carolina (Figure 1). 
North 

t 

Figure 1--Location of Hobcaw Forest in 

Georgetown County and South Carolina. 

The Georgetown area climate is characterized by mild winters and hot humid 

summers. Monthly mean January and 

August temperatures were 8°C and 23", 

respectively, and mean annual precipitation was 1300 mm for the period 

1951-1980 (NOAA 1981). 

Local topography is dominated by a 

series of Sangamon Age beach ridges 

with elevations ranging from 3-8 m 

above mean sea level (MSL) on the 

western side of the .forest and 1-2 m 

above MSL on the eastern side 

(Williams and Lipscomb 1981). Hobcaw 

Forest soils are sandy throughout, 

excessively to moderately well drained 

on the western side, and moderately to 

poorly drained on the eastern side 

(Stuckey 1982). 

Fifty-two arborescent species (nomenclature follows Radford and others 

1968) occur in Hobcaw Forest (Barry 

1968). Ridges are dominated by either 

longleaf pine with some shortleaf pine 

(Pinus eehinata Miller) occurring on 

older ridges, or by a mixture of oaks 

(Quercus L.) and hickories (Garya 

Nuttall). Inter-ridge areas are flat 

and support a mixture of loblolly pine, 

pond pine, or longleaf pine. Ephemeral 

streams drain inter-ridge areas and are 

bordered by forests of sweetgum 

(Liquidhar styraciflua L,), ash 

(Fraxinus L.), elm (Ulmus L.) and 

blackgum ( Njyssa sylvatiea var syl vatica 

Marshall). The top of the forest 

canopy averages 21 m high (unpublished 

data, Baruch Forest Science Institute). 

Pre-hurricane forest structure and 

composition resulted from repeated 

logging (Williams and Lipscomb 1983) 

and prescribed burning (Komarek 1981). 

From November 1989 to May 1990, we 

sampled hurricane damage to trees in 

293 of the 362 Hobcaw Forest stands 

delineated in 1965 for forest management purposes (unpublished data, Baruch 

Forest Science Institute). (Stands 

without minimum-sized [see below] trees 

or in which timber was salvaged were 

not sampled.) Stands varied in size 

from 0.6 ha to 44 ha and each had a 

relatively homogeneous canopy composition. Within each stand we inventoried 

a randomly located, 100 m by 10 m plot 

by recording species, diameter at 

breast height (dbh), and damage class 

of all live, woody stems greater than 

10 cm dbh. If 25 trees were not in the 

0.1 ha plot, it was extended until 25 

trees were inventoried in each plot. 

If a stand was larger than 20 ha, two 

plots in it, of at least 25 trees each, 

were inventoried. 

We visually estimated wind-related tree 

damage and assigned trees to one of the 

following damage classes, listed in 

order of increasing severity of damage: 

Undamaged: Bole unbent and 

vertical with little crown 

damage; 

Bent: Roots intact, lower bole 

vertical, upper bole not 

vertical; 

Limbs broken: Many limbs broken, 

terminal leader intact: 

Defoliated: Sparse foliage, with 

brown or dying foliage; 

Top broken: Many limbs broken, 

terminal leader broken; 

Broken: Bole broken between 

ground and crown base; 

Uprooted: Tree partially 

uprooted with bole leaning; 

Downed: Tree partially uprooted 

with bole lying on ground, 

These damage classes were grouped as 

follows for discussion purposes: 

undamaged trees, (class 1); light 
damage, bole bent or limbs broken 

(classes 2,3); moderate damage, 

defoliated or top broken (classes 

4,5); heavy damage, broken, uprooted 

or downed (classes 6,7,8). 

Basal area and stem density were 

calculated on a plot basis and 

averaged over 329 plots. An R X C 

G-test (Sokal and Rohlf 1981) was used 

to deternine pooled differences and 

homogeneity of number of stems among 

damage classes. Chi-square tests of 

independence in R x C contingency 

tables (Everitt 1977) were used to 

compare stem distributions among 

damage classes between two species. 

An alpha of 0.05 was used for all 

tests. 

RESULTS 

We tallied 16,870 stems in 329 0.1 ha 

plots which is 1.08 percent of the 

area of Hobcaw Forest. Average plot 

density was 506 stems ha-' and average 

plot basal area was 25.3 m2 ha-'. 

Severity of Damage 

Percents of st ge classes are 

n Table 1. Approx 

f the trees sampled were 

(24%) or were li 

) Moderately d 

gd trees were 1 

nt of the total, respectively. With the exception of live oak 

and swaap tupelo, hardwoods suffered 

ge than did pines. Longleaf pine was the least d 

pines with 87.7 percent of the stems 

not damaged or lightly damaged, compared to 73.5 percent for loblolly pine 

and 65.5 percent for pond pine. 

Approximately 84 percent of the bald 

cypress stems were not damaged (11.2%) 

or were lightly damaged (73.0%). 

Laurel oak, the most common upland 

hardwood, had 19.4 percent of the stems 

in the heavy damage group compared to 

7.8 percent for longleaf pine and 9.0 

percent for loblolly pine. 

Table 1--Variation by percent of stems for types of damage suffered by tree species 

in Hobcaw Forest, South Carolina, during Hurricane Hugo. The table shows the 

percent of stems in each damage class for each of the major tree species, and the 

percent of stems of each major species of the total number of stems of all tree 

species in the samples. Damage classes are grouped as shown into damage groups for 

discussion in the text. 

Damase Group 

Un- Light Moderate Heavy 

daaacred Damase Darnaqe Damacre 

Species Un- Bent Limbs De- TOP Bole Up- Downed Percent 

damaged broken foliated broken Broken rooted of total 

Longleaf 

pine 

Loblolly 

pine 

Pond pine 

Bald 

cypress 

Blackgum 

Sweetgum 

Swamp 

tupelo 

Laurel 

oak 

Live 

oak 

Water 

oak 

Average 23.9 4.2 44.8 8.6 7.4 3.5 5.0 2.7 
Live oak and swamp tupelo had a larger 

percent of stems not damaged or 

lightly damagd than water oak and 

laurel oak, which had a larger percent 

of stems heavily damaged (Table 1). 

Twenty-seven percent of the live oak 

stems were undamaged compared to 16 

percent for both water oak and laurel 

oak. Swamp tupelo had the highest 

percent of stems lightly damaged 

(86.6%). 

Stem Number Distribution Among 

Damage Classes 

Table 2 summarizes the results of the 

G-test for stem count distribution 

among damage classes. The heterogeneity test indicated that at least one 

species did not fit the damage distribution for all species combined. 

Individual G-test statistics indicated 

that 12 of 14 species tested did not 

fit the overall damage distribution. 

Chi-square tests indicated similarities between damage distributions of 

pairs of species. Among conifers, 

damage distributions between loblolly 

pine and pond pine were not significantly different. Damage distributions of laurel oak and water oak were 

not significantly different and the 

distributions of live oak and southern 

red oak were not significantly different. The damage distributions of 

southern red oak and hickory (pri- marily Carya tomentosa [Poiret] 

Nuttall) were not significantly 

different as also indicated by the 

G-test (Table 2). 

Non-significant differences between 

ge distributions of a pine and 

hardwood were live oak and loblolly 

pine and longleaf pine and southern red 

oak. All other pairwise tests of 

apparently similar damage distributions resulted in significant 

chi-square statistics indicating 

different distributions. 

Basal mea Distribution 

e 

3 s the percent basal 

area distribution among damage classes 

for the more abundant species sampled. 

Because basal area integrates both dbh 

and stem density this analysis gives a 

better picture of tree biomass damaged 

than does the analysis based on stem 

counts. 

Among the pines, the percent of basal 

area in the heavy damage group was 42.6 

percent for pond pine, compared to 11.2 

percent and 16.8 percent for longleaf 

pine and loblolly pine, respectively. 

Longleaf pine had approximately twice 

the basal area undamaged than did 

loblolly (39.4% and 19.3%, 

respectively). 

Live oak was one tenth as damaged in 

terms of basal area as either laurel or 

water oak. Only 3.3 percent of the 

live oak basal area was in the heavy 

damage group compared to 32.1 percent 

for laurel oak and 34.6 percent for 

water oak. The following species had 

more basal area in the light damage 

groups than in the other groups: swamp 

Table 2--G-test statistics for stem counts among damage classes testing the 

following hypothesized percent distribution among damage classes 1-8, respectively: 

24.5, 4.2, 45.6, 8.5, 7.5, 3.0, 4.5, 2.2. The hypothesized distribution was the 

damage distribution for all species (** = P < .01). 

Tests df G Species df G 

Pooled 7 3 . 3 

Heterogenity 91 2189.9** 

Total 98 2193.2** 

longleaf pine 

loblolly pine 

pond pine 

bald cypress 

blackgum 

sweetgum 

swamp tupelo 

ash 

hickory 

laurel oak 

live oak 

southern red oak 

water oak 

turkey oak 
tupelo (88.5%), bald cypress (84.3%), 

live oak (66.7%), sweetgum (60,1%), 

and blackgm (53.4%). 

D e as a Function of Tree 

D ter 

In general, the larger dbh trees were 

ged and smaller dbh trees 

ged or lightly 

blolly pine typified this 

pattern, except that the moderately 

damaged trees were about the same dbh 

as the undamaged and lightly damaged 

trees (Figure 2). Longleaf pine was 

unique among the pines in that the 

smallest trees had heavy crown damage, 

and the undamaged and lightly damaged 

trees were intermediate in dbh. 

Laurel oak and water oak were similar 

in terms of kinds of damage suffered 

by trees of different sizes (Figure 

3). The smaller dbh trees were either 

undamaged or bent. The larger dbh 

trees had the top broken or were in 

the heavy damage group. The smallest 

live oak trees were bent, and the 

undamaged live oak trees were larger 

than the bent trees. Like laurel oak 

and water oak, the larger live oak 

trees had the top broken or the bole 

broken. However, uprooted live oak 

trees were larger than uprooted laurel 

oak and water oak, and downed live oak 

trees were smaller than downed laurel 

oak and water oak. 

DISCUSSION 

We considered the sum of the percent 

basal area in the undamaged and 

lightly damaged groups (undamaged, 

bent, and 1-s broken damage classes 

of Table 3) for a species to be an 

index of that speciesf ability to 

resist hurricane wind damage. Those 

species with 80 percent or more basal 

area undamaged or lightly damaged are, 

from least to most damaged, swamp 

tupelo, bald cypress, longleaf pine, 

and live oak. 

Likewise, we considered the sum of the 

percent basal area in the heavy damage 

ge classes (bole broken, 

uprooted or downed of Table 3) for a 

species to be an index of a speciesf 

sensitivity to hurricane wind damage. 

Loblolly Pine 

205 

Figure 2--Average dbh of pine stems by damage class. Damage classes were 

grouped as follows: undamaged trees 

(damage class 1); light damage, bole 

bent or limbs broken (classes 2,3); 

moderate damage, defoliated or top 

broken (classes 4,5); heavy damage, 

broken, uprooted or downed (classes 

6,7,8). Shortleaf pine did not have 

any stems in five of the eight damage 

groups and was not included in the 

figure, Error bars show two standard 

errors above and below means, Sample 

sizes are indicated above error bars, 
encountered in this study can be 

classified as either resistant or 

sensitive, and other studies support 

- 40 this classification. 

E 

0 Touliatos and Roth (1971) reported that - live oak, pond cypress ( Taxodim 

20 sacendens Brongn,) and bald cypress had 

very high wind resistance. They also 

Cl reported that loblolly pine, longleaf 

pine, southern red oak, and water oak 

had low resistance to breakage, which 

agrees with our data of Table 3. 

Laurel Oak 52 5? 

Water Oak 

25 22 

Figure 3--Average dbh of oak stems by 

damage class. Damage classes were 

grouped as follows: undamaged trees 

(damage class 1); light damage, bole 

bent or limbs broken (classes 2,3); 

moderate damage, defoliated or top 

broken (classes 4,5); heavy damage, 

broken, uprooted or downed (classes 

6,7,8): Species with less than 100 

stems xnventoried are not included in 

the figure. Error bars show two 

standard errors above and below means. 

Sample sizes are indicated above error 

bars , 

In order of decreasing basal area in 

the heavy damage group, pond pine, 

water oak and laurel oak had 43 

percent, 35 percent and 32 percent of 

their respective basal area heavily 

damaged. From the hurricane wind 

damage resistance and sensitivity 

indices, the more abundant species 

This differential resistance of southeastern United States forest species to 

wind damage was also reported for 

tornado-generated high winds 

(Glitzenstein and Harcombe 1988). They 

reported that 73 percent, 73 percent, 

and 66 percent, of the surviving 

southern red oak, water oak, and 

swatetgum, respectively, were badly 

damaged compared to 1.6 percent of the 

loblolly pine and 0 percent of the 

longleaf pine. They also reported that 

destruction of individuals in the 

larger diameter classes significantly 

reduced the average diameter of intact 

trees. These same patterns sf differential species sensitivity to wind 

damage and hi,gher sensitivity of larger 

trees to wind damage were reported for 

a southeastern U.S. Fagus-Magnolia 

forest (Harcombe and Marks 1983). 

Tropical tree species also exhibit 

differential resistance to hurricane 

wind damage and suffer more damage in 

the larger diameter classes (Lugo and 

others 1983, Putz and others 1983). 

Wind damage integrates species, site, 

and stand characteristics which prohibits direct assignment of a single 

cause of damage to an individual 

species. However, resistance and 

sensitivity to hurricane wind damage of 

the more abundant species of this study 

were associated with morphological and 

anatomical properties of the species. 

The resistance of swamp tupelo and 

cypress was probably related to the 

presence of buttressed boles (Touliatos 

and Roth 1971, Putz and others 1983), 

and the deciduous habit of cypress 

greatly reduced the surface area 

exposed to high winds, We noticed that 

cypress foliage was browning, as it 

does before leaf fall, just before the 

hurricane struck. The damage resistance of longleaf pine could be related 

to firm anchorage provided by the large 

taproot and widespread lateral root 

system. Our excavations of longleaf 

pine root systems (unpublished data, 

Baruch Forest Science Institute) 
Table 3--Variation by percent of basal area for types of d ge suffered by tree 

species in Hobcaw Forest, South Carolina uring Hurricane Hugo. The table shows 

the percent of st- basal area in each d ge class for each of the mjor trem 

species, and the percent of stem basal a jor species of the total stern 

basal area of all tree species in the s-1 classes are grouped as shown 

into damage groups for discussion in the text. 

Daaaqe Oroup 

Un- Light erato Heavy 

daaurrqed Da&kqe Damage 

Species Un- Bent Linibs De- Top Bole Up- Downed Percent 

damaged broken foliated broken Broken rooted of total 

Longleaf 

pine 

Loblolly 

pine 

Pond pine 

Bald 

cypress 

Blackgum 

Sweetgum 

Swamp 

tupelo 

Laurel 

oak 

Live oak 

Water oak 

Average 17.0 2.1 52.9 6.9 6.0 5.2 5.5 4.6 

indicated that longleaf pine taproots 

extended two meters vertically in the 

soil and the lateral root system 

extended up to six meters horizontally 

from the taproot. The resistance of 

live oak has been related to the low 

deliquescent canopy and high wood 

strength and resilience (Touliatos and 

Roth 1971). The crowns of the larger 

live oaks were level with or below 

crowns of associated laurel and water 

oaks . The hurricane wind damage sensitivity 

of pond pine was probably related to 

its shallow root system, which 

developed in high water table soils. 

Pond pine had the highest percent of 

stems blown down (8.3%). A high 

percent of water oak and laurel oak 

stems were blown over (8.0% and 6.2%, 

respectively) which may be related to 

the observed shallow, diffuse root 

system. These oaks are tall at 

maturity (15-18 m, Harrar and Harrar 

1962) and thus were more exposed to 

high winds than were smaller trees. 

It is interesting to note that the 

more hurricane-wind-resistant species 

are co~nly found in the lower coastal 

plain, where the frequency of hurricanes is higher than further inland. 

More wide-spread species, not particularly associated with the coastal 

plain, were more vulnerable. Longleaf 

pine, bald cypress and live oak trees 

commonly live at least a century (bald 

cypress trees live 400-600 years, 

Fowells 1965), and are commonly found 

in South Carolina's lower coastal plain 

(Radford and others 1968). With an 

average hurricane recurrence interval 

of 5.8 years (Purvis 1973), these trees 

would be exposed to 17 hurricanes 

during a 100-year lifetime. During the 

past 110 years four hurricanes as 

severe as Hugo struck South Carolina 

(Purvis 1973). Therefore, it is 

possible that hurricanes have exerted 

selection pressure on traits of some 

tree species that are common in forests 

frequently darnaged by hurricanes. 

LITERATURE CITED 

Barry, JON. 1968. A survey of the 

native vascular plants of the Baruch 

PlantatAon. Masters Thesis, Dept. of 

Biology, University of South Carolina, 

Columbia, SC. 
Everitt, BoS. 1977. The Analysis of 

Contingency Tables, Halsted Press, 

John Wiley & Sons, NY. 

Fowells, H.A. 1965, Silvics of Forest 

Trees of the United States USDA, 

Agriculture Handbook No. 271. 

Washington, IX1. 

Glitzenstein, Jose; Harcombe, P.A, 

1988. Effeets of the Dec 

tornado on forest vegetation of the 

Big Thicket, southeast Texas, U,S.A, 

Forest Ecology and Management 

25:269-290. 

Harcombe, P.Ae; Marks, POL. 1983. Five 

years of tree death in a FagusMagnolia forest, southeast Texas 

(USA). Oecologia 57x49-54. 

Harrar, E.S.; Harrar, J.G. 1962. Guide 

to Southern Trees. Dover Publications 

Inc. NY. 

Komarek, E.V. 1981. History of 

prescribed fire and controlled burning 

in wildlife management in the South, 

pp. 1-t4. In Wood, G.W. (ed). 

Prescr~bed Fire and Wildlife in 

Southern Forests. Belle W. Baruch 

Forest Science Institute, Clemson 

University, Georgetown, SC. 

Lugo, A.E.; Applefield, M.; Pool, 

D.J.; McDonald, R.B. 1983. The impact 

of Hurricane David on the forests of 

Dominica. Can. J. For. Res. 

13:201-211. 

NOAA. 1981. Climatography of the 

United States No. 20, Georgetown, SC. 

National Climatic Data Center, 

Asheville, NC. 

Purvis, J.C. 1973. Hurricanes, 

Disaster Preparedness Agency, 

Columbia, SC. 

Pumis, J.C.; Sidlow, S.F.; Smith, 

D.J.; Tyler, W.; Turner, I. 1990. 

Hurricane Hugo. te Reprt G-37, 

South Carolina Resources 

Comission, Col 

Putz, FOE,; Coley, P.D.; Lu, KO; 

Montalvo, A*; Aiello, A. 1983. 

Uprooting and snapping of trees: 

structural deteminants and ecological 

c8nsq~en~es. Can. J. For. Res, 

13:lOll-1020. 

Radford, A.E.; Ahles, H.E.; Bell, C.R. 

1968. Manual of the Vascular flora of 

the Carolinas, Univ. of North Carolina 

Press, Chapel Hill, NC. 

Sokal, R.R.; Rohlf, F.J. 1981. 

Biometry. 2nd edition, W.H. Freeman, 

NY 

Stuckey, B.N. 1982. Soil survey of 

Georgetown County, South Carolina. Soil 

Conservation Service, Georgetown, SC. 

Touliatos, P.; Roth, E. 1971. 

Hurricanes and trees: ten lessons from 

Camille. Journal of Forestry 

69:285-289. 

Williams, TOM.; Lipscomb, D.J. 1981. 

Water table rise after cutting on 

coastal plain soils. Southern Journal 

of Applied Forestry 5:46-48. 

Williams, T.M. and D.J. Lipscomb. 1983. 

Logging history of Hobcaw Forest. 

Forestry Bulletin No. 38, Department of 

Forestry, Clemson University, Clemson 

SC . 

Reprinted with pemission from 

Biotropica 23~420-426 published by the 

Association for Tropical Biology, Inc. 

Special Issue edited by Dr. Lawrence 

Walker (and others), Biology Dept., 

Univ. of Puerto Rico, Rio Piedras, 

Puerto Rico 00931. 
MAJOR STRUCT'IJ 

HURRICAME HUGO IN -GROWTH FOREST TREES AT 

FOUR HOLE 

M. J. Duever and J. M. ~c~ollorn' 

Abstract--While measuring impacts of Hurricane Hugo, we 

assessed characteristics of trees that might have 

increased their susceptibility to damage. This 

included evidence of previous major damage, such as 

major branch loss and bent, uprooted, or broken boles. 

Previous damage varied from 21-91% as a function of 

species and from 25-75% as a function of site. For 

certain species previous damage was infrequent 

(21-29%), and these species showed low survival (0-2%) 

among trees affected by Hurricane Hugo. Other species 

exhibited a high frequency of previous damage (86-87%), 

and had a high percentage of individuals (80-100%) that 

survived despite being affected by the hurricane. Age 

was related to frequency of previous damage for most 

species. Different areas of the swamp have distinct 

disturbance histories as evidenced by sites in the same 

area having similar percentages of individuals with 

previous damage, regardless of habitat type and species 

composition. 

Reprinted with permission from Supplement to Bulletin of the Ecological Society 

of America 73(2):161. Abstracts. Dr. Allen M. Solomon, Editor, ESA Bulletin, 

USEPA-ERL, 200 SW 35th St., Corvallis, OR 97330. 

' National Audubon Society, Naples, FL 33964, USA. 
PATTERNS OF INITIAL AND DELAYED MORTALITY CAUSED BY 

HURRICmE HUGO IN FOUR OLD-GR fI I!YxtESfLT C NITIES 

IN FOUR HOLES S P, SOUTH CAROLINA 

Jo Mo McCollom and Mo Jo ~uever' 

Abstract--Initial (Fall 1989) and delayed (Fall 1991 & 

1992) mortality data were collected for 1233 trees >15 

cm dbh in 16 plots damaged by Hurricane Hugo. Though 

22% of the trees were killed, species composition two 

years after Hugo was quite similar to pre-hurricane 

conditions, The ratio of trees killed initially to all 

trees of a species.showed a strong positive correlation 

with species arrayed along a topographic gradient. 

However, delayed mortality was much more equally distributed along the topographic gradient. Initial and 

delayed mortality patterns varied with type of damage 

incurred, such as major branch loss and bent, uprooted, 

or broken boles. Overall and initial mortality rates 

increased only slightly with diameter, while delayed 

mortality decreased slightly. 

Reprinted with permission from Supplement to Bulletin of the Ecological Society 

of America 73(2):266. Abstracts. Dr. Allen M. Solomon, Editor, ESA Bulletin, 

USEPA-ERL, 200 SW 35th St., Corvallis, OR 97330. 

Ecosystem Studies, National Audubon Society, Naples, FL 33964, USA. 
ICIURRICANE HUGO EFFECTS OH 

OLD-GROmH FLO0DPL.rZllIN FOREST C NITIES AT 

FOUR HOLES S SOUTH CAROLINA' 

Michael J. Duever and Jean M. Mc~ollom~ 

ABSTRACT--We assessed hurricane damage and mortality of 

1233 canopy trees (26 in dbh) in sixteen plots within 

the old growth floodplain forest in Four Holes Swamp. 

Sixty percent of the trees sustained major damage, and 

22% had died within two growing seasons as a result of 

the hurricane, Higher elevation Ridge Bottom forest 

plots sustained the greatest damage (81%) and highest 

mortality (47%), while the lower Cypress/Tupelo forest 

plots had the least (43% and 4%, respectively), and 

mid-elevation Hardwood Bottomland forests were intermediate (64% and 24%, respectively). Among the more 

comon species in our plots, water oak (Quercus nigra 

L.) and spruce pine (Pinus glabra Walt,) had the 

largest percentage sf individuals damaged (193%), and 

baldcypress (Taxodium distichum (L.) Rich), blackgum 

(Nyssa sylvatica var. biflora (Walt.) Sarg.), water 

tupelo (Nyssa aquatica L.), and Carolina ash (Fraxinus 

caroliniana Mill.) had the smallest (147%). After two 

growing seasons, spruce pine had by far the greatest 

percent mortality (91%) of individuals alive at the 

time of the hurricane, and water tupelo and blackgum 

the lowest (1% and 3%, respectively). The dominant 

type of damage was main stem break (50% of affected 

trees). However, of the different types of damage, 70% 

of uprooted trees died and only 35% of the main stem 

broken trees died. Mortality among trees with major 

branch loss and bent stems has been less than 10%. 

Hurricane Hugo effects were not randomly distributed 

through the forest. While other factors may be 

involved, species present, and possibly community type, 

influence the kinds and degree of effects. 

XNTRODUCTX 

In recent years there has been an 

increasing awareness of the role 

natural perturbations play in ecosystem dynamics. The concept that 

nature, undisturbed by man, is maintained in an equilibrium condition is 

being replaced with the concept that 

Paper presented at the Seventh 

Biennial Silvicultural Research 

Conference, Mobile, AL, November 17- 

19, 1992. 

Director, National Audubon Society 

and Ecosystem Studies Program, 

National Audubon Society, Naples, 

Florida. 

ecosystems are unstable, and different 

portions of them are changing at different rates under the influence of one 

or more types of disturbance (Runkle 

1982, Pickett and White 1985). Major 

perturbations can in a matter of hours 

or weeks produce more change in an 

ecosystem than would occur during 

normal everyday processes over periods 

of decades or even centuries (Hook and 

others 1991, Whigham and others 1991). 

Documenting how these events interact 

with other natural processes to produce 

the earth's varied landscapes is 

critical to our understanding of how 

existing ecosystems have come into 

being and are likely to change in the 

future. 
Nurricanes represent one type of 

severe perturbation that produces 

major changes in natural landscapes 

(Sheffield and Thompson 1992, McCollom 

and Duever 1992). They are regular 

visitors to the southeastern United 

States, although there may be many 

years between visits to any particular 

area (Neumann 1987, Duever and others 

9n Press) . 

er 22, 1989, the eye of 

Hurricane Hugo, passed over National 

Audubon Society's Francis Beidler 

Forest in South Carolina, which contains the largest stand of old-growth 

baldcypress and water tupelo in the 

world (Brunswig and Winton 1978). An 

average of wind speeds estimated by 

sparks of Clemson University for four 

cities (Camden, Sumter, Summerville, 

and Charleston) bracketing Beidler 

Forest along the hurricane's path 

place estimated mean hourly wind speed 

at 72 mph with gusts up to 115 mph 

(Purvis and others 1990). Rainfall 

associated with the hurricane was 4-5 

inches (Purvis and others 1990). 

The 6000 ac sanctuary contains approximately 1700 ac of old-growth forested 

wetlands which is one of the last remnants of the undisturbed floodplain 

forests that once laced the southeastern coastal plain. As one moves 

up the approximately 5-ft topographic 

and moisture gradient within the 

floodplain, the major swamp forest 

types include cypress-tupelo swamp on 

the lowest sites, bottomland hardwood 

swamp at intermediate elevations, and 

a mixed hardwood-pine community on low 

ridges within the swamp (Porcher 

1981) . Our initial Hurricane Hugo field 

studies in December 1989, included an 

overflight of Four Holes Swamp to 

assess damage to the forest. The 

strongest impression that resulted 

from this flight was of the patchiness 

of the storm's more severe effects. 

This led us to formulate a series of 

hypotheses as to the reasons for this 

patchiness. The first was that it 

resulted from random severe wind 

gusts. However, if the pattern of 

minor and major effects were not 

random, then they must be related to 

certain characteristics of these 

sites. In this paper, we will discuss 

hurricane damage to and mortality of 

canopy trees among the major community 

types and the more common canopy tree 

species present at Four Holes Swamp. 

METHODS 

Sixteen 0.5 ac plots were established 

in old-growth stands of the three major 

forested wetland habitats listed above. 

All trees 6 in dbh or larger were 

identified to species where possible, tagged, and diameters recorded. It was 

not possible to determine species for 

elms (Ulmus sp. ) and ashes (Fraxinus) 

except for Carolina ash. Ordination 

and clustering analyses of plot and 

species data matrices using Cornell 

Ecology Programs DECORANA, TWINSPAN, 

and COMPCLUS (Duever and McCollom, 

1992) were used to determine which 

plots should be grouped into comunity 

types and which species were most 

closely associated with those communities. 

Trees affected by the hurricane were 

classified into four damage types, 

listed here from most to least severe: 

main stem broken, uprooting, major 

branch loss (branches broken off at or 

near main stem), or bent trunk. Trees 

sustaining several types of damage were 

assigned to the most severe type of 

damage category. 

Data on mortality were collected following the hurricane and at the end of 

the first and second growing seasons 

after the hurricane. 

RESULTS 

Damage 

Sixty percent of the 1233 trees over 6 

in dbh in our plots were damaged by the 

hurricane (Table 1). Half of the 

damaged trees were in the break category. Uprooting and major branch loss 

each represented 22% of the damage, 

while bent trunks were uncommon. 

The percent trees damaged at a site 

generally followed the topographic and 

moisture gradient, with more affected 

at drier sites. The highest elevation 

community, the Ridge Bottom, sustained 

damage to 81% of the trees (Table 1). 

Half of the tree damage was broken 

boles and one third of the trees were 

uprooted. This community had the 

smallest proportion of damaged trees 

with bent trunks or major branch loss. 

Moving downslope, 64% of the Bottomland 

Hardwood community trees were damaged. 

Broken boles were less common in this 

conununity than in the other two comunities, representing only 43% of damaged 

trees. Uprooting and major branch loss 

categories each claimed one quarter of 
Table 1. Damage and Mortality in three old-growth floodplain cornunities from 

16 plots at Beidler Forest Sanctuary, South Carolina. 

No 

No . Trees 

No. Trees 2 Years Dmqe 

Cornunity Plots Before After Total Break Uprooted Branches Bent 

Ridge Bottom 4 220 117 178 90 60 22 6 

Bottomland Hardwood 8 6 12 467 393 166 95 98 34 

Cypress/Tupelo 4 401 383 174 116 10 42 6 

TOTAL 16 1,233 967 745 372 165 162 46 

No . No. Trees 

No. Trees 2 Years Mortality 

Plots Before After Total Break Uprooted Branches Bent 

Ridge Bottom 4 220 117 103 55 43 4 1 

Bottomland Bardwood 8 6 12 34 145' 63 66 10 3 

Cypress/Tupelo 4 401 383 18 11 6 1 0 

TOTAL 16 1,233 967 266 129 115 15 4 

Three trees died that did not fit in any damage category. 

the damaged trees. The Bottomland 

Hardwood community also had the 

highest proportion of bent trees, 9% 

compared to 3% in the other two 

communities. 

At the bottom of the topographic gradient, the Cypress/Tupelo community 

had the lowest percent damaged trees, 

44%. Two thirds of the damage to this 

community was due to broken boles, the 

highest proportion of any community. 

This community also had virtually no 

uprooting, with only 6% of the damaged 

trees falling into that category. 

Species responded quite differently to 

the hurricane. Of the 14 most common 

species (N215), the two species which 

sustained the most damage were found 

mainly on the higher elevation sites. 

Over 90% of the water oak and spruce 

pine were damaged. The common species 

found mainly in the deeper parts of 

the swamp sustained the least damage. 

Carolina ash, blackgum, baldcypress, 

and water tupelo each had less than 

50% damaged individuals (Table 2). 

The two most common species, water 

tupelo (N=215) and laurel oak (Quercus 

laurifolia Michx.) (N=214), sustained 

47% and 66% damage, respectively. 

For most species, the most common type 

of damage was broken boles. Of the 

more common species, water oak, pignut 

hickory (Carya glabra (Mill.) Sweet), 

American hornbeam (Carpinus caroliniana 

Walt.), and red maple (Acer rubrum L.) 

had about equal numbers of uprooted 

trees and broken boles. Swamp chestnut 

oak (Quercus michauxii Nutt.) and the 

elms had similar numbers of individuals 

among the three most severe damage 

types: broken bole, uprooting, and 

major branch loss. Baldcypress had 

more trees with major branch damage 

than all other damage categories 

combined. However, it must be 

remembered that our sampling strategy 

only recorded the most severe damage 

for each individual. Thus, other 

species that had broken or uprooted 

stems could also have lost major 

branches, but this information would 

not have been included in our records. 

Mortality 

Two years after the hurricane, 78% of 

the 1233 trees sampled were still alive 

(Table 1). Deaths occurring 

immediately after the hurricane 

included 13% of all trees (N-160). 

Subsequent mortality through the end of 

the second post-hurricane growing season included an additional 8% (N=101). 
Though broken boles were the most common type of d ge and accounted for 

the most wrtality in te 

bers, uprooting was most likely to be 

fatal, with 70% of all uprooted trees 

dying by the end of the second growing 

season (Table 1). Mortality among 

trees with either broken branches or 

was less than 10%. Mortality patterns in the three forested 

community types followed a pattern 

similar to damage along the topographic gradient. Mortality for all 

trees was lowest in the deeper 

Cypress/Tupelo community sites, 

ranging from 1-10% in the four study 

plots at the end of two growing 

seasons after the hurricane (Table 1). 

Midway up the topographic gradient, 

the eight Bottomland Hardwood sites 

had mortality between 9% and 42%. The 

highest mortality was at the higher 

elevation Ridge Bottom sites, ranging 

from 38% to 52% in the four plots. 

Mortality was highest for trees in 

the main stem broken damage category 

in both the Ridge Bottom and Cypress/ 

Tupelo cornrnunities, while in the 

Bottomland Hardwood community mortality was more equally divided 

between broken boles and uprooted 

trees (Table 1). 

Total Mortality for individual species 

ranged from only 1% for water tupelo 

(N=215) to 91% for spruce pine (N=43) 

(Table 2). For species with 215 

individuals, percent Total Mortality 

was highest for species most commonly 

associated with the Ridge Bottom 

community, the first five species 

listed in Table 2, and lowest for 

species most commonly found in the 

Cypress/~upelo community, the last 

four species listed in Table 2. 

The two most common conifers, baldcypress and spruce pine, died primarily of broken boles. Hardwood 

mortality was generally associated 

about equally with broken boles and 

uprooting. However, blackgum, water 

tupelo, and Carolina ash, which were 

common in the Cypress/Tupelo community, had so little mortality that 

it is difficult to ascribe it to any 

particular type of damage. Water oak, 

swamp chestnut oak, red maple, and 

ashes all died primarily as a result 

of uprooting. Swamp chestnut oak, 

American hornbeam, and elms had a 

relatively high percent mortality 

associated with major branch loss. 

Two years after the hurricane, species 

composition of trees equal to or 

greater than 6 in dbh, viewed as the 

proportion of n ers of one species to 

another, was quite similar to prehurricane conditions. Exceptions were 

laurel oak whose numbers had decreased 

from 213 to 141, and particularly 

spruce pine, which had decreased from 

43 to 4 live individuals. 

DISCUSSZON 

The results of our analyses of canopy 

tree damage and mortality among the 

various community types and species 

present in the old growth forest at 

Four Holes Swamp clearly indicated that 

the pattern of storm effects did not 

result solely from random wind gusts. 

There was a consistent pattern of more 

severe damage and mortality on the 

higher Ridge Bottom sites and much less 

effect on the lower Cypress/Tupelo 

sites. Also, the species exhibiting 

the most severe effects were most 

common on the higher Ridge Bottom 

sites, and those with the fewest 

impacts were the species that were 

dominant on the lower Cypress/Tupelo 

sites. 

Putz and Sharitz (1991) reported that 

the more severe effects of Hurricane 

Hugo on trees in the Congaree Swamp 

were associated with certain species 

and community types. Their slough 

community would be comparable with our 

Cypress/Tupelo community, and, as at 

Four Holes Swamp, was much less 

impacted by the storm than was the 

bottomland hardwood community. They 

found that bottomland hardwood species 

were equally prone to being uprooted or 

to suffering stem breakage, whereas in 

the slough sites stem breakage was more 

common than uprooting. This was the 

same pattern of damage that we found in 

Four Holes Swamp. 

Gresham and others (1991) reported that 

Hurricane Hugo damage to the Hobcaw 

Forest along the South Carolina coast 

was largely a function of the species 

present. The species most and least 

affected were quite similar in our 

respective studies. They reported that 

baldcypress, water tupelo, and blackgum 

were the least affected species, and 

that pond pine (Pinus serotina Wichx.), 

possibly comparable to spruce pine at 

Four Holes Swamp, and water and laurel 

oaks were by far the most affected 

species. They did note that several 

other upland species, including 
Table 2, Damage and mortality for dominant species from 16 plots in the oldgrowth floodplain forest at Beidler Forest Sanctuary, South Carolina. 

No. 

No. Tress 

Trees 2 Years 

Dominant Species (~>15)" Before After 

Water Oak, Quercus nigra 4 7 

Spruce Pine, Pinus glabra 4 3 

Pignut Hickory, Carya glabra 26 

Swamp Chestnut Oak, Quercus nrichauxii 24 

American hornbeam, Carpinus caroliniana 47 

rican or Winged), Ulmus sp. 62 

Sweetgun, Liquidambar styraciflua 115 

Red Maple, Acer rubrum 6 5 

Laurel Oak, Quercus laurifolia 2 14 

Ash (all sp. but water ash), Fraxinus sp. 70 

Blackgum, Nyssa syl vatica var , biflora 94 

Baldcypress, Taxodium distichum 136 

Water Tupelo, Nyssa aquatica 2 15 

Carolina Ash, Fraxinus caroliniana 15 

TOTAL for Dominant Species Only 1,173 924 701 352 153 152 4 4 

No. 

No. Trees 

Trees 2 Years Mortality 

Dominant Species (P15)' Before After Total Break Uprooted Branches Bent 

Water Oak, Quercus nigra 47 

Spruce Pine, Pinus glabra 4 3 

Pignut Hickory, Carya glabra 2 6 

Swamp Chestnut Oak, Quercus michauxii 2 4 

American hornbeam, Carpinus caroliniana 47 

Elm (American or Winged), Ulmus sp. 6 2 

Sweetgum, Liquidambar styraciflua 115 

Red Maple, Acer rubrum 65 

Laurel Oak, Quercus laurifolia 214 

Ash (all sp. but water ash), Fraxinus sp. 70 

Blackgum, N'yssa sylvatica var . biflora 94 

Baldcypress, Taxodium distichum 136 

Water Tupelo, Nyssa aquatica 2 15 

Carolina Ash, Fraxinus caroliniana 15 

TOTAL for Dominant Species Only 1,173 924 249 121 110 12 4 

Species not listed, in order of dominances overcup oak (Quercus lyrata Walt.), common persimmon 

(Diospyros virginiana L.), redbay (Persea borbonia (L.) Spreng.), loblolly pine (Pinus taeda L.), 

water-elm (Planera aquatica J. F. Gmel.), American holly (Ilex opaca Ait, var. opaca), sugarberry 

(Celtis laevigata Willd.), water hickory (Carya aquatica (Michx. f.) Nutt.), cherrybark oak 

(Quercus falcata var. pagodifolia Ell.), red buckeye (Aesculus pavia L.), and waterlocust 

(Gleditsia aquatica Marsh.). * One tree died that did not fit in any damage category. 
longleaf pine (Pinus palustris Mill.), 

loblolly pine (Pinus taeda L.), and 

live oak (Quercus virginiana Mill.), 

suffered relatively little damage. 

These genera at Four Holes Swamp 

tended to be among the more severely 

affected species, suggesting that 

vulnerability to hurricane impacts is 

related more to species than generic 

composition. 

Whigham and others (1991) also 

observed a differential mortality 

among dominant tree species during the 

two years after Hurricane Gilbert 

passed over their study sites in 

Quintana Roo, Mexico. Mortality 

associated with the storm varied from 

1.4 - 31.3% among the different 

species. More individuals died from 

breaks in both Quintana Roo and Four 

Holes Swamp but branch damage caused 

the second most mortality in Quintana 

Roo, while at Four Holes death due to 

uprooting was the next most common. 

If we look at percent mortality among 

the damage classes by dividing the 

number that died within a damage class 

by the total number in that damage 

class, results for the two studies are 

quite similar. For Quintana Roo and 

Four Holes Swamp respectively, uprooting produced the highest mortality 

(43%, 70%), trunks snapped produced 

28% and 35% mortality, and major 

branch loss resulted in only 6% and 9% 

mortality. These similarities are 

quite suiprising given that the 

species present on their tropical 

sites were much different from the 

temperate species we studied. 

A variety of factors undoubtedly play 

a significant role in determining 

damage to and mortality of canopy 

trees from hurricanes. Among these 

factors, species present on a site 

appears to have a major influence on 

the kinds and degree of effects. 

Community type also appears to be 

closely associated with hurricane 

impacts. However, it is difficult to 

decide whether these effects are 

intrinsically related to integrated 

community characteristics or are more 

a function of specific aspects of the 

community, such as species present or 

substrate or hydrologic characteristics. 

ACKNOmEDCEmNTS 

Portions of this research were funded 

jointly by USDA Forest Service Cooperative Research Agreement No. 29-738 

and National Audubon Society. We would 

like to thank Norm Brunswig and Mike 

Dawson from Beidler Forest for their 

generous help in many aspects of this 

effort. 

LITEEUIWREI CITED 

Brunswig, N.L.; Winton, S.G. 1978. The 

Francis Beidler Forest in Four Holes 

Swamp. New York, NY: National Audubon 

Society. 26 p. 

Duever, M.J.; McCollom, J.N. 1992. 

Initial and delayed mortality of canopy 

trees in an old-growth forested wetland 

following Hurricane Hugo. Final Report 

for USDA-Forest Service Southeastern 

Forest Experiment Station Cooperative 

Research Agreement No. 29-738. Naples, 

FL: Ecosystem Research Unit, National 

Audubon Society. 91 p. 

Duever, M.J.; Meeder, J.F.; Meeder, 

L.C.; McCollom, J.M. In Press. The 

climate of South Florida and its role 

in shaping the Everglades ecosystem. In 

Proceedings of the Everglades Symposium, Spatial and Temporal Patterns as 

Guidelines for Ecosystem Restoration, 

Key Largo, Florida, October 22-27, 

1989. 53 p. 

Gresham, C.A.; Williams, TOM.; 

Lipscomb, D.J. 1991. Hurricane Hugo 

Wind Damage to Southeastern U.S. 

Coastal Forest Tree Species. Biotropica 

23(4a):420-26. 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest. Journal of Coastal Research 

Special Issue Number 8:291-300. 

McCollom, J.M.; Duever, M.J. 1992. 

Patterns of initial and delayed 

mortality caused by ~urricane Hugo in 

Four Holes Swamp, South Carolina. 

Supplement to Bulletin of the 

Ecological Society of America. 

73(2):266. 

Neumann, C.J.; Jarvinen, B.R.; Pike, 

A.C.; Ehs, J.Do 1987. Tropical 

cyclones of the North Atlantic Ocean 

1871-1986. Historical Climatology 

Series 6-2. 3rd Revision. Asheville, 

NC: National Climatic Data Center. 

186 p. 

Pickett, S.T.A.; White, P.S. 1985. The 

ecology of natural disturbance and 

patch dynamics. Orlando, FL: Academic 

Press. 472 p. 
Porcher, ROD. 1981. The vascular flora 

of the Francis Beidler Forest in Four 

Holes Swamp, Berkeley and Dorchester 

counties, South Carolina. Castanea 

46:248-80. 

Purvis, J.C.; Sidlow, SoFo; Smith, 

D.J.! Tyler, W.; Turner, I. 1990. 

te Report G-37. 

arolina Water 

Resources Comission. 82 p. 

Putz, F.E.; Sharitz, RoR* 1991. 

Hurricane damage to old-growth forest 

in Congaree Swamp National Monument, 

South Carolina, U.S.A. Canadian 

Journal of Forest Research 21~1765- 

1770. 

Runkle, J.R. 1982. Patterns of 

disturbance in some old-growth mesic 

forests of eastern North America. 

Ecology 63(5):1533-46. 

Sheffield, R.M.; Thompson, MOT. 1992, 

Hurricane Hugo effects on South 

Carolina's forest resource. ResoPap. 

SE-284, Asheville, NC: USDA Forest 

Service, Southeastern Forest Experiment 

Station, 51 p, 

nhighm, D.F.; 0 ted, I.; Cano, E,C.; 

Hamon, M.E. 1991. The impact of 

Hurricane Gilbert on trees, litterfall, 

and mody debris in a dry tropical 

forest in the northeastern Yucatan 

Peninsula. Biotropica 23(Qa):434-41. 

Reprinted with permission from 

Proceedings of the Seventh Biennial 

Southern Silvicultural Research 

Conference, Mobile, AL, Nov. 17-19, 

1992. Published by the USDA For. Sen. 

SFES Gen. Tech. Rep. 50-93, July 1993, 

PO 197-2020 
HURRICANE HUGO EFFECTS ON 

CO ITIES AT FOUR HOLES SWAMP, SOUTH CAROLINA 

Michael J. Duever and Jean M. ~c~ollorn' 

Abstract--We assessed effects on trees (>I5 cm dbh) in 

100 X 20 m plots. Results show 56-66% of trees 

exhibited major effects in 3 plots (18% in another). 

Of affected trees, 35-49% were killed in bottomland 

hardwood plots but only 0-10% in cypress-tupelo plots, 

and 40-49% were directly affected by hurricane winds as 

opposed to falling trees in 3 plots (79% in another). 

Conununity type, soil type, and water depth were not 

related to degree of site impact. Upwind sites were 

more impacted than downwind sites, and sites adjacent 

to a clearcut along the upwind side of the swamp were 

most affected. Cypress, blackgum, sweetgum, and 

hickory had the smallest number of individuals affected 

(32-33%); laurel oak, red maple, elms, pines, and 

overcup oak the largest (66-88%); tupelo, chestnut oak, 

and ashes were intermediate (46-50%). Of affected 

trees, 100% of pines were killed; tupelo gum, blackgum, 

chestnut oak, and hickory had 0-2% mortality; while for 

others it was 25-36%. The dominant type of effect was 

stem breakage (61% of affected trees). 

Reprinted with permission from Supplemental Bulletin of the Ecological Society 

of America 72(2):104. Abstracts. Dr. Allen M. Solomon, Editor, ESA Bulletin, 

USEPA-ERL, 200 SW 35th St., Corvallis, OR 97330. 

National Audubon Society, Maples, FL 33964, USA. 
Michael Duever and Jean McCollom 

Abstract--We assessed hurricane effects on trees (>I5 

cm dbh) in six 2000 m2 plots. Numbers of individuals in 

a plot varied from 62 to 105. Results show 53-58% of 

trees exhibited major effects in four higher elevation 

plots, with 18 and 66% in two lower elevation plots. 

Of affected trees, 49% were killed on the highest site 

(ridge bottom), 21035% on three intermediate elevation 

sites (bottomland hardwood), and only 8.8% on the 

lowest sites (cypress-tupelo). Of affected trees, 

39.79% were directly affected by hurricane winds as 

opposed to falling trees at the various sites. 

Cypress, black gum, and sweetgum had the smallest 

percentage of individuals affected (33%-37%); red 

maple, pines, and overcup and chestnut oak the largest 

(65-80%); and tupelo, laurel and water oak, ehs, 

hickory, and ashes were intermediate (45-58%). After 

one growing season, of affected trees 100% of pines 

were dead; tupelo, red maple, and black gum had 8% 

mortality; while for other species mortality was 

20-43%. The dominant type of effect was main stem 

breakage (54% of affected trees), although of the 

different types of damage classes, 60% of uprooted 

trees died. Impacts were related (directly) to tree 

diameter and height, but not crown size. Our analyses 

to date indicate that Hurricane Hugo impacts were a 

function of community type, species composition, and 

tree size. 

Reprinted with permission from Proceedings of 19th Annual Natural Areas 

Conference. Abstracts. Published by Indiana Department of Natural Resources 

Division of Natural Preserves and the Natural Areas Association. Dr. David N. 

Paddock, Executive Director, Natural Areas Association, 180 Fox Street, 

Nukwonago, WI 43149. 

' Research Ecologists, Ecosystem Research Unit, National Audubon Society, 

Naples, FL 33964, USA. 
HURRICANE DAMAGE TO AN OLD-GROWTH FLOODPLAIN FOREST 

IN THE SOUTHEAST& 

Rebecca Re Sharitz, Milda Re Vaitkus and Allen E. cook2 

Abstract--The old-growth forests of the Congaree Swamp 

National Monument, an 8988 ha floodplain tract in South 

Carolina, were damaged by Hurricane Hugo in 1989. The 

effects of the hurricane on forest structure and species 

composition were examined in ten 1.0 ha plots established 

in the winter months following the storm. Trees and large 

saplings (stems 2 2.5 cm in diameter) were tagged and 

measured, mapped, and the nature and extent of the damage 

was recorded. Effects of the hurricane were greater in 

bottomland hardwood forest communities (37% of trees seriously damaged) than in adjacent forested sloughs (10%). 

Among the hardwoods, highest damage was sustained by 

several oak species (61%), especially laurel oak (Quercus 

laurifolia Michx.) and willow oak (Q. phellos L.). Broken 

boles and uprooted trees were common. Extensive branch loss 

occurred in sweetgum (Liquidambar styraciflua L., 24%) and 

ash (Fraxinus spp., 26%). In contrast, the dominant slough 

canopy trees, water tupelo (Nyssa aguatica L.) and baldcypress (Taxodium distichum (L.) Rich) sustained low damage 

(9% and 3% of the trees). Broken boles and severe branch 

loss occurred most frequently. Regeneration in the canopy 

gaps was dominated by early-successional species in the 

hardwood forests, but not in the sloughs. Thus, the structure of the bottomland hardwood forests was altered by the 

hurricane, but the slough communities were not greatly 

changed. 

Introduction Glitzenstein and Harcombe 1988, Platt 

Large-scale disturbances are important and Schwartz 1990). Such stonns are a 

in shaping forest community structure, normal, although episodic, part of the 

composition and successional pro- climatic regime of the South Atlantic 

cesses. Early European travelers in Coastal Plain. 

the southeastern united States (such 

as Thomas Nairne in 1708) recorded the 

damaging effects of hurricanes to 

forests (Moore 1988), and recent 

studies of southeastern forests have 

examined the influence of hurricanes 

and tornadoes on stand composition and 

patch dynamics (e.g. Vogel 1980, 

Paper presented at Seventh Biennial 

Southern Silvicultural Research 

Conference, Mobile, AL, Nov. 17-18, 

1992. 

* Professor, Department of Botany, 

University of Georgia, Athens, GA; 

Research Coordinators, Savannah River 

Ecology Laboratory, Aiken, SC. 

On September 21-22, 1989, Hurricane 

Hugo came ashore 20 km northeast of 

Charleston, SC. As the storm traveled 

inland, winds in excess of 155 km/hr 

struck the old-growth floodplain 

forests of the Congaree Swamp National 

Monument, causing significant damage 

(Putz and Sharitz 1991). Within the 

last 110 years, four other hurricanes 

as severe as Hugo were recorded in 

South Carolina (Purvis 1973) and many 

less severe storms have occurred. 

Several of these have tracked near the 

Congaree Swamp. Thus, it is likely 

that the structure of this forest, as 

well as other mature southeastern 

forests, may have been shaped by 

repeated wind-related disturbances. 
We have initiated a study of long-term 

forest community dynamics in the oldgrowth forests of the Congaree Swantp 

National Monument. Included in this 

research is an exmination of the 

effects of Hurricane Hugo. Our objectives were to evaluate the hurricane 

ge to these mature forests, and to 

establish a baseline for study of 

forest recovery processes. 

Methods 

The Congaree Swamp National Monument 

encompasses 8988 ha of swamps and 

bottomland forests on the floodplain 

of the Congaree River in central South 

Carolina. It lies within the Coastal 

Plain, just southeast of the fall 

line. For many years much of the 

property was privately owned and was 

protected from logging. In 1976, the 

tract was acquired by the National 

Park Service as a National Monument, 

Large areas of the floodplain support 

old-growth forests that show little or 

no signs of logging or other recent 

human disturbance. 

The forests of the Congaree Swamp 

National Monument are relatively 

diverse. In a 1975 survey of the 

vegetation, Gaddy and Smathers (1980) 

reported more than 45 tree species and 

distinguished 29 plant coxnmunities. 

The most extensive are a variety of 

mixed bottomland hardwood forests that 

are found on subhydric and mesic 

sites, and the baldcypress/tupelo 

forests that occur in hydric sites 

such as sloughs and large depressions. 

They described the forests as usually 

having 100% canopy coverage of old and 

middle-aged trees. Because the forests were allowed to grow undisturbed 

on optimum soil conditions, they contain an unusual number of large trees 

with canopy heights of 30-50 m. A 

number of state and national record 

trees were reported (Gaddy 1977). 

During the winter months following 

Hurricane Hugo, we established ten 

10,000 mZ (1 ha) plots (each divided 

into 25 400 m2 subplots) in different 

forest coxnmunities within the Monument. Six plots were located in 

bottomland hardwood communities and 

four in slough coxnmunities, Within 

each plot, all trees (r 10 cm diameter 

at breast height, dbh) were tagged, 

their diameters measured, and their 

locations mapped. Trees were measured 

at 140 cm above ground except for 

those species that develop a pronounced butt swell. These were 

measured 200 cm above the ground or, 

if necessary, 50 cm above the top of 

the swell. In the sloughs, all saplings (2.5-16 cm dbh) within each plot 

were also tagged and measured. Because 

of the high densities of saplings in 

the bottomland hardwood comunities, 

only five subplots within each 1 ha 

plot were sampled. 

ge to trees and saplings 

was classified by type and severity. 

Moderate to severe damage included loss 

of major branches, bending of the'stem 

or bole, breakage of the bole (snapoff, considered more severe if the 

break was nearer to the ground) and 

uprooting (tip-up, partial or total). 

Throughout the forest, the canopy was 

opened by wind-induced defoliation and 

loss of small branches. This type of 

mild damage was not quantified, 

Percent damage by diameter size class 

was examined using ANOVA in a randomized complete block design. The subplots were used as blocks and the total 

number of trees of all species in each 

size class was used as a weighting factor. A least-squares means procedure, 

followed by a Bonferroni contrast of 

least-squares means, was used to assess 

significant differences between diarneter size classes (Miller 1986). All 

statistical analyses were performed 

using the Statistical Analysis System 

(SAS Institute Inc. 1989). 

Seedlings and small saplings (all 

individuals 0-140 cm high or >140 cm 

high - q2.5 cm dbh) were examined in 

two of the bottomland hardwood and two 

of the slough plots. In each of these, 

30 circular subplots (radius 3.26 m) 

were established, giving a total area 

sampled of 0.1 ha per plot. Seedlings 

and small saplings were inventoried at 

the end of the second and third growing 

seasons following the hurricane; only 

third year data are reported here. 

Results 

Pre-hurricane Forest Structure 

The pre-hurricane structure of the 

forests can be inferred since the 

survey included all trees judged to 

have been alive at the time of the 

storm. The six bottomland hardwood 

plots were dominated by sweetgum in the 

canopy, along with sugarberry (Celtis 

laevigata Willd. ) , American elm ( Ulmus 

americana L.), ash (chiefly green ash, 

Fraxinus pennsylvanica Marsh,) and oaks 

(laurel oak, willow oak, Q. phellos L.; 

swamp chestnut oak, p. michauxii Nutt,; 

cherrybark oak, Q. falcata var. 

pagodifolia Ell., Shumard oak, Q. 
shmardii Buckl. and water oak, Q. 

nigra L.) (Table 1). While never 

achieving high densities, the oaks 

were widely distributed throughout 

five of the six plots. Loblolly pine 

(Pinus taeda L.) was abundant in only 

one of the plots. The understory was 

characterized by holly (merican 

holly, Xlex opaca Ait.), puss 

decidua Walt.), American hornbeam 

(Carpinus caroliniana Walt.), pawpaw 

(Ashina triloba (L.) Dunal.) and 

abundant red maple (Acer rubrum L,) 

and box elder (A. negundo L,). 

Table 1. Dominant overstory and 

understory species in bottomland 

hardwood plots, 

Density (stemsfha) 

Trees' Saplingsz 

(r1Ocm dbh) (22.5-10cm dbh) 

LiqSEEF 

styraciflua 

Celtis laevigata 

Ulmus americana 

Fraxinus spp. 

Quercus spp. 

Pinus taeda 

Understory 

rlex opaca 

Ilex decidua 

Carpinus 

caroliniana 

Asimina triloba 

Acer rubrum 

Acer negundo 

Other species 23.4 36.6 

Total denmity 432.2 622.5 

based on 6 - 10,000m~lots 

based on 30 - 400m2 subplots 

Slough plots had a canopy of tupelo, 

either water or swamp tupelo (N. 

sylvatiea var. biflora (Walt. ) Sarg. ) , and baldcypress (Table 2). Scattered 

individuals of sweetgum were found, as 

well as laurel oak and overcup oak 

(Quercus lyrata L.). The understory 

was chiefly red maple and Carolina ash 

(F. caroliniana Mill.). Many of the 

maples, sweetgums and oaks grew on the 

slough edges or on elevated microsites 

that were less flooded. 

Tree density was higher in the slough 

plots than in the bottomland hardwood 

plots, but the density of saplings was 

lower in the sloughs (Tables 1 and 2)- 

The distribution of individuals of 

different sizes in the two forest 

communities also differed (Fig. 1). 

The bottomland hardwood plots were 

dominated by small diameter size class 

Table 2. Dominant overstory and understory species in slough plots. 

Density (stem/ha) 

Trees' SaplingsZ 

(210cm dbh) (r2.5-10cm dbh) 

Overs tory 

Nyssa aquatica 286.0 61.5 

Myssa sylvatica 

bi f 1 ora 139.3 18.5 

Taxodium distich- 89.5 8.0 

Liquidambar 

styracif l ua 20.0 21.5 

Quercus spp. 14.0 12.8 

Ulmus americana 3.0 4.0 

Unders tor 

Aced 26.8 32.3 

Fraxinus 

caroliniana 21.3 

Planera aquatica 9.3 

Ilex opaca 9.0 

Carpinus 

caroliniana 8.8 

Ilex decidua 0.3 

Other species 6.7 48.9 

Total density 634.0 378.8 

based on 4 - 10,OOOmZ plots 

Vased on 100 - 400a2 subplots 

BLH 

Diameter size class (cm) 

Figure 1. Density (stems/ha) by diameter class of trees and saplings in 

bottomland (BLH) and slough (SL) plots. 
individuals; saplings comprised 59% of 

the stems per hectare. There were 

also some trees in the very large size 

classes with diameters greater than 75 

cm, In the sloughs, 37% of the stems 

per hectare were saplings, and more 

than half (54%) were in small to 

intermediate size classes (10 to 50 cm 

dbh). There were fewer very large 

trees in the slough plots than in the 

bottomland hardwood plots, 

Within each forest type, size distributions of the dominant canopy species 

also differed. For example, in the 

bottomland hardwood plots there were 

many more sweetgum trees than saplings 

(Table 1)- In contrast, sugarberry 

and the oaks had higher proportions of 

saplings. There were several very 

large oaks of diameters greater than 

100 cm. Importantly, the loblolly 

pines were all large trees with no 

saplings occurring. In the slough 

plots, tupelo saplings were abundant 

(especially water tupelo) but there 

were fewer saplings of baldcypress 

(Table 2 ) . Hurricane Damage 

Damage from the storm was more severe 

in the bottomland hardwood forest 

communities than in the sloughs. A 

total of 36.7% of the individuals in 

the bottomland hardwood plots were 

moderately to severely damaged (Table 

3), compared with only 10.0% of those 

in the slough plots (Table 4). In 

both forest communities, damage 

increased with tree size (Fig. 2). 

For example, 17% of the bottomland 

hardwood saplings (2.5-10 cm dbh) were 

damaged, compared with 60% of the 

largest trees (>lo0 cm dbh). In 

addition, the type of damage to the 

hardwood species tended to be more 

severe in larger individuals, many of 

which were broken off near the base or 

completely uprooted. In the sloughs, 

damage was relatively low (5-10% of 

the individuals) in all but the 

largest size class (Fig. 2). Most of 

the heavily damaged large trees in the 

sloughs had severe branch loss or 

snapped off boles, 

In both forest communities, the type 

of damage differed by species. In the 

bottomland hardwood plots (Table 3), 

loss of branches was the most common 

form of damage to sweetgum in the 

canopy (23.6% of all individuals). 

Ash and elm in the canopy also lost 

many branches, as did the oaks, 

Between 11-18% of trees of all canopy 

species were snapped off. The oaks 

Diameter Size Class 

Figure 2. Mean percent damage (f 

standard error) by diameter size class 

to trees and saplings in bottomland 

hardwood (BLH) and slough (SL) plots. 

Different lower case letters denote 

significant (p<0.05) classes within BL8 

and SL plots, based on pair-wise 

comparisons, 

sustained the greatest total damage 

(61.2% of all individuals), chiefly due 

to uprooting (28.9%) and snapping 

(17,0%), Of the pines, 12.2% were 

uprooted and 12.2% snapped off. Many 

of the understory trees were broken 

beneath damaged overstory trees, Red 

maple and boxelder sustained the 

greatest damage (about 25% of the stems 

snapped off). 

In the slough plots, effects of the 

hurricane on canopy dominants was less 

severe (Table 4). In the two tupelo 

species, damage was 9.0-13.2%, and only 

3.1% of the baldcypress were damaged. 

Most of the damage was in the form of 

branch loss or stem breakage. Sweetgums, oaks and elms tended to have 

higher percentages of tip-ups. The 

understory species, especially red 

maple, American hornbeam and possumhaw 

lost branches or were bent or snapped, 

probably due to large debris falling 

from the canopy. 
Table 3. Percent damage to dominant overstory and understory species in bottomland 

hardwood plots. 

Percent Damaqe 

Projected 

Total Branch mortal 

damaged" loss Bending Snap off Tip up damage 

Overstory 

Liquidambar s tyracif 1 ua 

Celtis laevigata 

Vlmus americana 

Fraxinus spp. 

Quercus spp. 

Pinus taeda 

Understory 

Ilex opaca 

Xlex decidua 

Carpinus carol iniana 

Asimina tril oba 

Acer rubrum 

Acer negundo 

Average for all species 36.7 10.4 5.4 12.3 7 . 9 8.6 

" May include additional darnage not shown in other coab 

Table 4. Percent damage to dominant overstory and understory species in slough 

plots . 

Percent Damase 

Projected 

Total Branch mortal 

damaged" loss Bending Snap off Tip up damage 

Overstorv 

Nyssa aquatica 

Nyssa sylvatica biflora 

Taxodiua distichum 

Liquidambar styraciflua 

Quercus spp. 

Ulmus americana 

Understory 

Acer rubrum 

Fraxinus caroliniana 

Planera aquatica 

Ilex opaca 

Carpinus carol iniana 

Ilex decidua 

Average for all species 10.0 3.4 1.8 4.1 0.7 1.2 

* May include additional damage not shown in other columns. 
Projected mortality of injured trees 

was based on trpe and severity of 

ge. Trees broken off within 2 m 

of the ground and those completely 

uprooted were considered likely to 

die. In the bottomland hardwood plots 

(Table 3), the oaks had the highest 

level of projected mortality (33.4%). 

Most of this mortality resulted from 

uprooting. Pines also showed relatively high projected mortality 

(12.2%). This estimate is probably 

low, since many pines snapped off 

higher than 2 m will not survive. 

other overstory dominants had much 

lower expected mortality (3.5-9.5%). 

Although half of the ash trees in the 

plots were damaged, only 3.5% are 

expected to die. In the understory, 

the most abundant species, American 

holly, sustained the least expected 

damage (4.1% mortality). Red maple 

had the highest projected mortality 

(17.5%), although this may be an overestimate as individuals completely 

tipped up have been observed to survive if a sufficient number of roots 

remain intact. 

In the slough plots, estimated msrtality of dominant canopy species was 

low (0.3-0.5% for baldcypress and the 

tupelos). Almost all of the mortality 

resulted from snapped boles (Table 4). 

Possumhaw had the highest projected 

mortality (5.1%) of the understory 

species. Only about 2.5% of the 

understory dominants, red maple and 

Carolina ash, are expected to die. 

Forest Regeneration 

An examination of the densities of 

seedlings and small saplings (advance 

regeneration) of the major species 

gives an indication of the recovery 

potential of the forest. In the 

bottomland hardwood plots, regeneration was dominated by understory 

species such as pawpaw, although 

American hornbeam and red maple 

seedlings were also abundant (Table 

5). Seedlings and small saplings of 

the canopy dominant species were present but much less abundant. There 

were relatively few oak seedlings and 

none of pine. Likewise, there were 

few seedlings of the dominant understory species, American holly and 

possumhaw. In contrast, in the slough 

plots seedling densities were lower, 

but regeneration was characterized by 

the canopy and understory dominant 

species (Table 6). 

It appears that in the highly 

disturbed bottomland hardwood forest 

Table 5. Dominant overstory and understory seedling and small sapling 

species in httomland hardwood plots, 

Density (sterns/ha)* 

(0 - 140cm high, 

140cm high - 2.5cm dbh) 

Overstory 

Liquidambar styraciflua 

~ejtis 1 aevigata 

Ulmus spp. 

Fraxinus spp. 

Quercus spp. 

Pinus taeda 

Understory 

Ilex opaca 

Ilex decidua 

Carpinus caroliniana 

Asimina triloba 

Acer rubrum 

Acer negundo 

Lindera benzoin 

Crataegus spp. 

Ligustrum sinense 

Other species 

Total density 

* based on 60 - 33.3m2 plots 

Table 6. Dominant overstory and understory seedling species in slough plots. 

Density (stem/ha)* 

(0 - 140cm high, 

140cm high - 2.5cm dbh) 

Overstory 

Nyssa spp. 

Taxodium distichum 

Liquidambar styraciflua 7 5 

Quercus app. 270 

Vlmus spp. 1,415 

Celtis spp. 225 

Unders tor 

Acer ru+ Fraxinus spp. 

Planera aquatica 

Ilex opaca 

Carpinus caroliniana 

Ilex decidua 

Itea virginica 

Other species 

Total density 

* based on 60 - 33.38' plots 

communities, the canopy gaps are becoming dominated by rapidly growing successional species, especially pawpaw. 

The appropriate conditions for pine 

regeneration have not been met in this 

forest for some years, either before or 

following the hurricane. In the 

sloughs where damage was much less, 

seedling populations are similar to the 

overstory and understory composition. 
Discussion 

The old-growth mixed bottomland 

hardwood forest cornunities of the 

Congaree Swamp National Monument were 

much more severely d 

cane Hugo than were 

munities. At the time of the hurrileaf senescence prior to 

a1 abscission was beginning for 

many of the deciduous species. It is 

possible that the defoliation of baldcypress and the defoliation and branch 

loss of the tupelo trees reduced their 

wind resistance. In addition, the 

buttressed boles of these species may 

have decreased the likelihood of 

uprooting. Similarly, sweetgum, elm 

and ash in the bottomland hardwood 

cornunities were defoliated and lost 

large branches but were less frequently uprooted than other canopy 

species that had not begun leaf 

senescence. The tardily deciduous 

oaks, such as laurel oak and water 

oak, and the pines were the most 

susceptible to windthrow. Differences 

in root architecture may also be 

important; although little is known 

about the rooting patterns of these 

floodplain species, the uprooted oaks 

were observed to have been very 

shallowly rooted. 

Similar species responses were 

observed elsewhere in the southeastern 

U.S. in the path of Hurricane Hugo 

(Gresham et al. 1991, Hook et al. 

1991, Duever and McCollom 1992, 

Sheffield and Thompson 1992). In the 

Hobcaw Forest of eastern South 

Carolina, baldcypress suffered light 

crown damage, whereas laurel and water 

oak were cornonly uprooted or snapped 

off (Gresham et al. 1991). Duever and 

McCollom (1992) also reported greater 

damage to oaks and pines than to baldcypress in the Four Holes Swamp forest 

north of Charleston. Also, the greatest damage from high winds often 

occurs to the larger sized trees 

(Glitzenstein and Harcombe 1888, 

Gresham et al. 1991). In the oldgrowth bottomland hardwood forest 

comtnunities of the Congaree Swamp, 

however, extensive secondary damage 

also occurred to small and mediumsized stems that were crushed beneath 

large overstory trees. 

that had become established in the 

sloughs. Many were growing on stumps, 

logs, or other elevated microsites that 

may not have served as stable rooting 

substrates. The hurricane actually 

reduced the diversity in the slough 

cornunities by having a disproportionally larger effect on invading bottomland or transitional species than on 

comunity dominants. 

In the bottomland hardwood communities, 

projected mortality of canopy trees is 

much greater than in the sloughs. Half 

of the damaged oaks are expected to die 

(33.4% of all stems). It is also 

likely that none of the loblolly pines 

that were snapped off or uprooted 

(24.4%) will survive. The hurricane 

changed the stand composition in the 

bottomland hardwood cornunities by 

reducing the presence of oaks and pine 

in the overstory and also lowering the 

abundance of certain understory 

species, such as red maple and American 

hornbeam. 

It is expected that tree mortality from 

the hurricane will continue as severely 

damaged individuals gradually die. 

Repeated sampling in the Four Holes 

Swamp forest has shown this to be the 

case (M. J. Duever, personal comunication). Damaged trees also may be more 

susceptible to insect or fungal infestation or other disease. Furthermore, 

since hurricanes are a normal part of 

the climatic regime of the southeastern 

U.S., trees weakened in one storm may 

be pre-disposed to future damage. In 

the Congaree forest, Putz and Sharitz 

(1991) noted that many of the trees 

damaged by Hurricane Hugo showed evidence of prior mechanical damage or 

disease. 

Forest recovery from such disturbance 

is by regrowth and sprouting of damaged 

individuals, release and rapid growth 

of established seedlings and saplings 

(advance regeneration), and germination 

and establishment of new seedlings. 

Following a hurricane, light intensity - at the forest floor should increase not 

only in canopy gaps, but also beneath 

surviving trees (Canham et al. 1989). 

Thus, both light-demanding and shadetolerant species can potentially regenerate. In the bottomland hardwood 

Mortality of the overstory trees is forests of the Congaree Swamp, the 

expected to be relatively low in the regeneration is dominated by rapidly 

slough comtnunities. Less than one growing successional species, espepercent of the baldcypress and tupelo cially pawpaw and red maple. Pretrees were damaged so severely that viously established saplings of several 

they are likely to die. Mortality was of the canopy dominants, especially 

higher for the sweetgum, oaks and elm sweetgum, sugarberry and elm, are also 
expected to grow rapidly in the 

increased light environment. Conversely, pine sedlings are not 

expected to become established. 

Although disturbances may increase the 

variety of microsites for seedling 

establishment (Schupp et al. 1989), 

the abundant coarse woody debris in 

many of the gaps may limit establishment of new seedlings by shading the 

forest floor and also providing structure for growth of light-demanding 

vines. Thus, in the bottomland hardwood communities, the removal of pines 

and large oaks and the invasion of 

canopy gaps by early-successional 

species have resulted in short-term 

changes in the forest composition. 

Recovery of the slough communities, 

where damage to the canopy trees was 

generally less severe, should be 

relatively rapid as a result of branch 

sprouting and- canopy regrowth of 

damaged baldcypress and tupelo trees. 

Seedling populations were similar in 

composition to the canopy and subcanopy, and thus there is not expected 

to be a major change in forest 

structure in the sloughs. 

Acknowledgments 

This study was supported by contract 

DE-AC09-76SR00-819 between the U.S. 

Department of Energy and the University of Georgia's Savannah River 

Ecology Laboratory, and by contract 

agreement CA-5000-9-8020, #lo with the 

University of Georgia and the U. S. 

Department of Interior National Park 

Service. We thank the many individuals 

who worked with us on this study, 

especially R. H. Jones and N. Pedersen 

of Auburn University who collected the 

seedling data, F.E. Putz of the 

University of Florida who participated 

in the initial design, and R. A. Clark 

of the Congaree Swamp National Monument who assisted with local procedures. We appreciate the comments of 

K.W. McLeod and A.F. Schnabel on this 

manuscript. 

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W.J.; Runkle, J.R.; Spies, T.A.; 

White, P.S. 1989. Light regimes 

beneath closed canopies and tree-fall 

gaps in temperate and tropical 

forests. Canadian Journal of Forest 

Research 20~620-631. 

Duever, M.J.: McCollom, J.M. 1992. 

Hurricane ~ugo effects- on old-growth 

floodplain forest comunities at Four 

~oles-swamp, South Carolina. p. 29, 

In: Seventh Biennial Southern Silvicultural Research Conference Abstracts; 

er 17-18; Mobile, AL. 

Gaddy, L.L. 1977. Notes on the flora of 

the Congaree River flood-plain, 

Rickland County, South Carolina. 

Castanea 42~103-106. 

Gaddy, L.L.; Smathers, G.A. 1980. The 

vegetation of the Congaree Swamp 

National Monument. Veroff. Geobot. 

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Heft (1980). 171-182. 

Glitzenstein, J.S.; Harcombe, P.A. 

1988. Effects of the December 1983 

tornado on forest vegetation of the Big 

Thicket, Southeast Texas, U.S.A. Forest 

Ecology and Management 25:269-290. 

Gresham, C.A.; Williams, T.M.; 

Lipscomb, D.J. 1991. Hurricane Hugo 

wind damage to southeastern U.S. 

coastal forest tree species. 

Biotropica 23:420-426. 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest. Journal of Coastal Research, 

Special Issue 8t291-300. 

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of applied statistics. New York, NY: 

John Wiley and Sons. 317 p. 

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Muskhogean Journals. The 1708 

Expedition to the Mississippi River. 

Jackson, MS: University Press of 

Mississippi. 92 p. 

Platt, W.J.; Schwartz, M.W. 1990. 

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229. In: Myers, R.; Ewel, J. (eds); 

Ecosystems of Florida. Orlando, FL: 

University of Central Florida Press. 

765 p. 

Purvis, J.C. 1973. Hurricanes. 

Columbia, SC: Disaster Preparedness 

Agency. 52 p. 

Putz, F.E.; Sharitz, R.R. 1991. 

Hurricane damage to old-growth forest 

in Congaree Swamp National Monument, 

South Carolina, U.S.A. Canadian Journal 

of Forest Research 21:1765-1770. 
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User's Guide, Version 6, Fourth Edition, Volume 2, Cary, NC: SAS Institute Inc. 846 p. 

Schupp, E.W.; Howe, H.F.; Augsburger, 

C.R.; Levey, D,J. 1989. Arrival and 

survival in tropical treefall gaps. 

Ecology 70:562-564. 

Sheffield, R.M.; Thompson, M.T. 1992. 

Hurricane Hugo. Effects on South 

Carolina's Forest Resource. USDA 

Forest Service, Research Paper SE-284. 

51 p. 

Vogel, R.J. 1980. The ecological 

factors that produce perturbationdependent ecosystms. pp. 63-94. In: 

Cairns, J. Jr, (ed.). The Recovery 

Process in Damaged Ecosystems. Ann 

Arbor, MI: Ann Arbor Science, 167 p. 

Reprinted with permission from 

Proceedings of the Seventh Biennial 

southern Sil vicul tural Research 

Conference, Mobile, RL, Nov. 17-19, 

1992. Published by the USDA For. Serv. 

SFES Gen. Tech. Rep. SO-93, July 1993, 

p. 203-2100 
FOREST 

SOUTH CAROLINA, U.S.A.' 

Francis E. Putz and Rebecca R. sharitz2 

Abstract--Hurricane Hugo caused much damage to the oldgrowth forests of the Congaree Swamp National Monument, but 

most of the damage to trees >20 cm dbh consisted of crown 

breakage and defoliation. Serious damage (>25% of crown 

lost, snapped trunk, or uprooted) was more common in mixed 

bottomland forest (49% of trees seriously damaged) than in 

adjacent sloughs dominated by Taxodium distichum (L.) L.C. 

Rich. and Nyssa aguatica L. (19% of trees seriously damaged). Of the trees >20 cm dbh, about 12% were uprooted in 

the bottomland forest, whereas only 2% were uprooted in 

sloughs. The storm reduced diversity in sloughs because 

most trees of species characteristic of better drained 

sites, and especially those rooted on nurse logs and other 

unstable elevated microsites, were uprooted. Dynamics of 

the entire forest were greatly influenced by the capacity 

of most tree species to recover vegetatively after suffering even severe crown and stem damage. Trees with 

resprouted crowns, however, were particularly likely to be 

broken, presumably owing to the presence of stem rots and 

architecturally unsound branching patterns. 

INTRODUCTION 

Hurricanes and other large-scale 

disturbances strongly influence the 

structure, composition, and successional processes of many forests (Lugo 

and others 1983; Runkle 1985; Webb 

1988; Boucher 1990). Such disturbances often set back succession by 

providing regeneration opportunities 

for early successional species 

(Clements 1916). Several recent 

studies have shown, however, that 

disturbance may also accelerate 

succession by damaging pioneer trees 

in the canopy and releasing the 

advanced regeneration of later 

Putz, F. E., and Sharitz, R. R. 

1991. Hurricane damage to old-growth 

forest in Congaree Swamp National 

Honument, South Carolina, U,S.A. Can. 

J. For. Res. 21:1765-1770. 

Department of Botany, University of 

Florida, Gainesville, FL 32611-2009, 

U.S.A.; Savannah River Ecology 

Laboratory, Drawer E, Aiken, SC 29809, 

UaSeAe 

successional species (Abrams and Scott 

1989; Veblen and others 1989). In 

either case, disturbances, especially 

those that are spatially heterogeneous 

in intensity, often contribute to the 

maintenance of species diversity by 

providing a diversity of regeneration 

opportunities (Grubb 1977). 

On September 21, 1989, winds in excess 

of 155 km/h from Hurricane Hugo struck 

the old-growth bottomland hardwood and 

the Taxodium distichum (L.) L.C. Rich. 

and Nyssa aquatica L. (cypress tupelo) 

dominated swamp forest in the Congaree 

Swamp National Monument. Several days 

after the storm we conducted a census 

to evaluate the effect of Hurricane 

Hugo on forest structure and species 

composition in one of the largest 

tracts of old-growth forest in eastern 

North America. In this paper, we contrast the stormfs impacts on old-growth 

bottomland forest and adjacent forested 

sloughs and focus on the frequency and 

type of damage suffered by canopy trees 

of different species. 
STnX SITE mTHODS 

The Congaree S National Monument 

encompasses 6125 ha of swamps and 

bottomland forests on the floodplain 

of the Congaree River in central South 

Carolina, Much of the Monument is 

growth forest with no signs of 

n disturbance for at least 100 

years and numerous record-size trees 

(Gaddy 1977, Gaddy and Smathers 1980). 

The vegetation is extremely diverse 

and includes extensive areas of mixed 

bottomland hardwoods with the following common tree species (nomenclature 

follows Radford and others 1968): 

Liquidambar styraciflua L. (sweetgum), 

Celtis laevigata Nutto (hackberry), 

Ifex opaca Ait. (American holly), 

Carpinus ceroliniana Walt. (American 

hornbeam), and Fraxinus pennsylvanica 

Marsh. (red ash). Pinus taeda L. 

(loblolly pine) is locally dominant in 

a few bottomland areas in the Monument. Also common in slightly lower 

elevation areas are forested sloughs 

dominated by N. aquatica (water 

tupelo) and T. distichum (bald 

cypress), with scattered Carya 

aquatica (Michx. f) Nutto (water 

hickory), Acer rubrum L. (red maple), 

and Planera aquatica J.F. -el. (water 

eb), The sloughs are inundated 

several months per year, whereas the 

bottomlands flood only occasionally. 

To assess damage attributable to 

Hurricane Hugo, we censused trees >20 

cm dbh (diameter at 1,4 m or above 

buttresses and butt swell) in 0.2-ha 

(20 x 100 rn) plots in old-growth 

bottomland forest and forested sloughs 

throughout the Monument (Figure 1). 

Plots were located by selecting a place 

on a reserve map on the basis of 

accessibility, determining if the area 

was large enough to include an entire 

slough or bottomland forest plot, and 

selecting one plot corner in a haphazard fashion. Sampling was completed within 10 days after the storm. 

Twenty-one plots were censused (total 

area = 4.2 ha), 12 in bottomland forest 

and 9 in forested sloughs. To increase 

the accuracy of damage estimates for 

the less abundant slough species, we 

censused all trees other than No 

aquatica and T. distichum in five 

additional sloughs. Additionally, we 

increased the sample size for P. taeda 

trees to 100 by censusing all trees >20 

cm dbh of this species within 20 m of 

the boardwalk through the central 

portion of the Monument. 

Figure 1--The Congaree Swamp National Monument indicating the locations of the 

sample plots with black boxes. The monument is approximately 145 km from the 

Atlantic Ocean. 
Each tree was identified to species, 

measured for dbh, and classified as 

one of the followingt having suffered 

no serious damage (e.g., only defoliated), uprooted, partially uprooted, 

trunk snapped below the lowermost live 

branch, or having lost major portions 

of its crown (25.50% and 50%). We 

also noted whether the trees showed 

obvious signs of having suffered 

previous damage, presence of heart 

rot, and height of stem breakage. 

Indications that a tree had suffered 

but recovered from serious mechanical 

damage prior to Hurricane Hugo 

included the presence of broken stem 

remains and abrupt irregularities in 

stem shape, criteria identical with 

those used by Putz and Brokaw (1989). 

The relationships between different 

types of damage and tree size (dbh), 

tree species, prior damage, and habitat were determined by log likelihood 

ratio analyses of data from the 0.2-ha 

plots (G-tests with Williams' correction; Sokal and Rohlf 1981). Owing to 

the small numbers of damaged trees in 

some plots, analysis was based on 

combined data Prom all plots in a 

vegetation type. 

others 1989). Although there were 25 

uprooted trees in nine slough plots, 

none were of the dominant species T. 

digtichum or Af. aquatica. Furthermore, during the 8 days of field 

surveys we observed only one uprooted 

T. distichm anywhere in the Monuraent. 

There were no clear relationships 

between type of damage and tree size 

(Table 2), but trees with obvious signs 

of having suffered but recovered from 

previous stem breakage had a high 

probability of being damaged during 

Hurricane Hugo (Table 3). 

Hurricane Hugo reduced canopy tree 

diversity in Taxodium-Nyssa sloughs by 

uprooting a disproportionately high 

number of trees of species other than 

the dominants (Table 4). None of the 

104 T. distichum or 404 N. aquatica 

trees in the plots were uprooted. Of 

the few uprooted trees in sloughs, most 

were members of species characteristic 

of slough margins and other higher 

elevation and better drained sites. 

Most species that occurred in both 

sloughs and bottomland forest suffered 

higher incidences of uprooting in the 

sloughs (Table 4). About half of the 

uprooted trees in sloughs were clearly 

rooted on fallen logs, tip-up mounds 

from previously uprooted trees, or 

Forested Sloughs other-elevated-and mechanically 

Although Hurricane Hugo caused sub- unstable microsites. This was 

stantial losses of leaves and small particularly true for A. rubrum trees, 

branches, only about 19% of the trees many of which were uprooted or leaning 

in forested sloughs suffered serious over due presumably to shifting of the 

damage (>25% crown loss; Table I). nurse logs on which they often perched. 

uprooting was particularly unco&on in 

the sloughs. This was surprising Bottomland Forest 

since trees in swamps are generally Among-plot variation in tree density 

thought to be prone to uprooting due and in the proportion of damaged trees 

to their shallow root systems and low were very large in the bottomland hardsoil shear strength (Schaetzl and woods. Densities of trees >20 cm dbh 

Table 1--Damage suffered by trees during Hurricane Hugo in 0.2-ha (20 X 100 m) 

plots in forested sloughs. 

Plot No, 

12345678 9 Totala 

Total no. of trees >20 cm dbh 21 83 83 81 89 63 51 67 120 658 

Totalno.oftreesseriouslydmaged 6 11 26 22 11 19 8 11 11 125(19.0) 

No, of uprooted trees 01220600 1 12( 1.8) 

No, of partially uprooted trees 01731100 0 13( 2,O) 

No. of snapped trees 61976506 3 43( 6.5) 

No. of trees with >50% crown loss 04630112 1 18( 2,7) 

No.oftreeswith25-50%crownloss 0 4 2 7 4 6 7 3 6 39( 5.9) 

NOTE8 Trees were considered seriously damaged if they lost more than 25% of their crown. 

Plots were in the southeastern (plots 1-6) and central (plots 7-9) portions of the Congaree 

Swamp National Monument. a Percentages of total are noted in parentheses. 
Table 2--Number of trees that snapped, uprooted (including trees partially 

uprooted), suffered substantial crown damage, or remained relatively undamaged (but 

may have suffered defoliation) during Hurricane Hugo. 

dbh Snapped Uprooted Crown loss >25% Undamaged 

0-40 cm 

0-80 crn 

80 cm 

P 

Forested 

14( 4.6) 

9( 2.9) 

2( 4.3) 

sloughs 

21( 6.9) 

30( 9,?) 

5(10,9) 

ns ns 

Bottomland forest 

41(13.7) 39(13,0) 

31(17.0) 39(21.4) 

2( 5..6) ll(30.6) 

<0.001 <0.01 

NOTE: Data are from nine 0.2-ha plots in forested sloughs and twelve 0.2-ha plots 

in bottomland forest in the Congaree Swamp National Monument. Percentages of all 

trees in a size class are noted in parentheses. Probabilities that the incidence 

of damage varied with tree size class are based on log likelihood ratio tests. 

Table 3--Incidence of serious damage in 0.2-ha plots to trees >20 crn dbh that 

either showed signs or showed no clear sign of having suffered serious damage prior 

to Hurricane Hugo in Taxodium-Nyssa sloughs and bottomland hardwoods. 

No. of trees 

seriously damaged 

No. of trees 

not seriously damaged 

Slough trees 

Previously damaged 

Not previously damaged 

Bottomland hardwoods 

Previously damaged 

Not previously damaged 

NOTE: Probabilities are based on log likelihood ratio tests. Percentages of all 

trees in a damage class are noted in parentheses. 
Table 4--Uprooting frequencies for trees >20 cm dbh growing in forested sloughs and 

bottomland forests. 

Sloughs, 

frequency 

(uprootedltotal) 

Bottomland, 

frequency 

(uprootedltotal) 

Liquidambar styraciflua 

Acer rub 

Fraxinus pennsyl vanica 

Carya aquatiea 

Ulmus americana 

Populus heterophyllaA Platanus occidentalisA 

Quareus falcata 

var . pagodi foliaA 

NOTE: Probabilities are based on tests. Slough data from the 0.2-ha plots were 

augmented by a census of five additional sloughs. 

Sample sizes too small for statistical analysis. 

ranged from 34 to 6410.2 ha, and the 

proportion of uprooted and snapped 

trees ranged from 4 to 50%. This 

extreme heterogeneity was undoubtably 

due in part to the specific (but 

unknown) paths of Hurricane Hugo and 

was presumably also influenced by 

stand structure and history of 

previous damage. 

Approximately half of the trees in the 

bottomland plots suffered serious 

damage, but only about 30% were 

uprooted or snapped (Table 5). Trees 

in bottomland forests seem equally 

prone to being uprooted and to suffering stem breakage. Among large trees 

(NO cm dbh), the incidences of snapping and uprooting were low but 

serious crown damage was common (Table 

2); apparently a tree that loses a 

large portion of its crown is unlikely 

to suffer more serious damage. Alternatively, trees that resist windthrow 

may therefore be likely to receive 

heavy damage to their crowns. Many of 

the large trees appeared to have sustained, but recovered from, substantial damage prior to Hurricane Hugo. 

Trees that had recovered from serious 

damage prior to Hurricane Hugo suffered a very high probability of 

sustaining damage during the Hurricane 

(Table 3). The major short-term 

effect of Hurricane Hugo in bottomland 

hardwood forest, as in sloughs, was 

loss of much foliage and many small 

branches. 

Pinus taeda in Bottomland Forest 

Of the 100 P. taeda trees >20 cm dbh 

censused, only 46 escaped serious 

damage from Hurricane Hugo (Table 6). 

Uprooting and snapping were about 

equally common (21 and 28 trees, 

respectively). Most of the broken 

(snapped) trees had heart rot, but we 

suspect that many of the undamaged and 

uprooted trees were likewise infected. 

Damage to trees was severe in areas 

where P. taeda trees were common. This 

seemed mostly because when large P. 

taeda trees were either uprooted or 

snapped, they caused a great deal of 

damage to their neighbors. 

DISCUSSION 

Forests of the Congaree Swamp National 

Monument were severely disturbed by 

Hurricane Hugo, but the type and extent 

of tree damage varied with forest type. 

Throughout the area the canopy was 

opened by wind-induced defoliation; 

since this occurred only a few weeks 

prior to normal autumnal leaf abscission, the immediate deleterious effects 

on tree vigor were probably minor. 

Trees in bottomland forests, particularly where there were large individuals of P. taeda, often suffered much 

more serious damage. About half of the 

bottomland trees were uprooted, 

snapped, or had lost a substantial 

number of larqe branches. This contrasts markedly with the slightly more 

low-lying and poorly drained sloughs, 

where uprooting was particularly rare. 
Table 5--Tree damage in bottomland hardwood forests of the Congaree Swamp National 

Monument attributable to Hurricane Hugo. 

Plot No. 

2 3 4 5 6 7 8'9 101112 

Total no. of trees >20 ern dbh 37 41 50 38 36 34 38 64 49 51 37 44 519 

Total no. of trees seriously damaged 18 22 26 18 20 31 14 40 4 24 10 24 253(48.7) 

No. of uprooted trees 3 2 5 2 511 017 14 311 64(12.3) 

No, of partially uprooted trees 312011000000 10( 1.9) 

No. of snapped trees 612 9 7 6 4 515 17 711 gO(17.4) 

No, of trees with >SO% crown loss 222445350600 33( 6.4) 

No, of trees with 25-50% crown loss 4585410632702 56(10.8) 

NWt The plots were each 0.2 ha (20 x 100 m) and were located in the southeastern portion (plots 1-6) 

and central portions of the Monument (plots 7-12). Trees that lost more than 25% of their crowns were considered to be seriously damaged. 

Plot 8 contained seven snapped and three uprooted Pinus taeda. 

Percentages of total are noted in parentheses. 

Table 6--Damage suffered by Pinus taeda >20 cm dbh in the Congaree Swamp National 

Monument during Hurricane Hugo. 

No. of No. of No. of trees No. of trees No. of trees 

Total no. snapped uprooted with 25-50% with >50% with no serious 

dbh (cm) of trees trees trees crown loss crown loss damage 

Total 100 28 2 1 3 2 46 

NOTE: No Pinus taeda trees 20-40 cm dbh were encountered. 

To some extent the differences can be 

attributed to characteristics of the 

dominants of the latter, T. distichum 

and N. aquatica. Trees in sloughs 

might also have been sheltered from 

the wind by the surrounding forest, 

but the elevational range was 

generally <1 m. Furthermore, the tops 

of the crowns of many slough trees 

were often level with or higher than 

the canopy of the adjacent bottomland 

forest. 

Observations of T. distichum rooting 

patterns in Florida revealed that the 

trees often develop several "sinker" 

roots that penetrate to greater depths 

than the rest of the root system (K. 

Ewel, personal comunication). The 

root system ball of the one uprooted 

T. distichum tree we encountered 

exposed numerous downward growing 

roots at a depth of about 1 m. Such a 

root system may effectively anchor T. 

distichurn trees in the frequently 

inundated soils of the sloughs and 

thus account for their persistence 

during strong winds. Uprooting and 

trunk snapping of T. distichum may be 

rare because the large trees have 

strong wood and because T. distichum 

trees normally display little leaf area 

relative to trunk diameter (Brown 1981) 

and thus have low wind resistance. 

Defoliation and crown breakage by wind 

may in part account for the infrequency of uprooting and snapping of 

weak-wooded species such N, aquatica. 

After a tree loses leaves and branches, 

its wind resistance is substantially 

decreased and the probability of more 

serious damage is reduced. Although we 

did not conduct a quantitative survey, 

defoliation appeared to be particularly 

severe in N. aquatica. 

In contrast with the dominant slough 

species, many of the rarer tree species 

in this community suffered disproportionately high probabilities of being 

uprooted during Hurricane Hugo. The 

reasons for this phenomenon undoubtedly 

vary from species to species, but 
overall it suggests that by growing in 

sloughs the trees had exceeded the 

bounds of their ecological tolerance 

range. For several decades prior to 

Hurricane Hugo, however, these colonizers from better drained habitats 

survived in the sloughs by rooting on 

elevated microsites, like nurse logs 

and tip-up mounds. When confronted 

with mechanical stresses of the magnitude imposed by the storm, their root 

systems or the substratum upon which 

they were perched proved unequal to 

the task of providing structural 

support. A consequence of the concentration of damage on species other 

than TI distichum and N. aquatica is 

that canopy diversity was reduced and 

dominance by these two species was 

increased by Hurricane Hugo. In T. 

distichum dominated swamps elsewhere 

in southeastern United States, dominance is maintained in part by 

occasional fires that disproportionately damage the rarer species (Ewe1 

and Mitsch 1978). 

A large proportion of trees in the 

Congaree Swamp National Monument had 

obviously suffered severe mechanical 

damage prior to Hurricane Hugo (Table 

3). Damage and subsequent recovery 

was evident in the crown and bole 

structure of many trees, particularly 

in the larger N. aquatica. Previous 

mechanical damage is likely to have 

contributed to the incidence and 

severity of attack by heartrot fungi; 

trees with heart rot are very susceptible to further damage even if the 

crown resprouts. Susceptibility to 

damage is also increased if resprouted 

branches form v-shaped crotches with 

entrapped bark or other architecturally unsound crown morphologies. 

To the extent that trees that cause 

canopy gaps resprout and close the 

openings they created, frequencies of 

canopy tree replacement are reduced. 

Heightened probabilities of repeated 

canopy-opening events near previously 

broken but recovered trees, however, 

may be reflected in the distribution 

and growth of understory species. 

Although breakage and resprouting 

seems to be a major process in the 

dynamics of other forests (Foster 

1988, Webb 1988, Putz and Brokaw 1989, 

Boucher 1990), this is the first 

report of a positive feedback mechanism enhancing the likelihood of 

repeated damage and recovery. In 

complete contrast, however, resprouting does not occur in Rhizophora 

apiculata Blme dominated mangrove 

forests in southeast Asia, where even 

minor mechanical d gs leads to tree 

death within 10-15 years (Putz and Chan 

1986). 

Among commercial tree species in North 

America, both T, distichum and N. 

aquatica are rated by foresters as 

relatively resistant to hurricane 

damage (Barry and others 1982). Along 

with Sabal palmetto Lodd, ex J.S. 

Shult. & J.H. Shult. (palm cabbage) and 

Quercus virginiana Mill. (live oak), T. 

distich- is ranked as highly resistant 

to uprooting and breakage. Nyssa 

aquatica is considered to be less 

resistant than T, distichum but is 

ranked as less prone to uprooting and 

breakage than are most Quercus spp., 

Pinus spp., and Carya spp. Observations in forested areas elsewhere on 

the South Carolina coastal plain 

(Francis Marion Forest and Santee 

Experimental Forest) have also revealed 

far more extensive damage to forest 

dominated by Pinus spp. and Quercus 

spp. than to stands of Taxodium and 

Nyssa (personal observation). 

In the absence of fire, even the extensive damage of Hurricane Hugo to 

bottomland forests may not be followed 

by substantial P. taeda regeneration in 

the Congaree Swamp National Monument 

(Hough and Forbes 1943, Glitzenstein 

and others 1986, Foster 1988). In the 

area dominated by large P. taeda trees, 

there were few individuals <40 cm dbh. 

Trees that survived the storm will 

probably be subjected to severe attack 

by beetles that will breed in the 

downed timber and in damaged but 

standing trees. Annual ring counts of 

three fallen P. taeda trees (90, 101, 

and 113 cm dbh) were about 156, 157, 

and 180 years old, respectively, and 

grew extremely slowly (<1 miyear) 

during the last 20 years. This 

suggests that conditions were suitable 

for P. taeda recruitment during the 

mid-1800s but have deteriorated 

subsequently. The understory of 

Arundinaria gigantea (Walter) Muhl. 

(switchcane), vines, shrubs, and small 

broad-leaved trees is likely to 

increase in density where the canopy 

was radically opened by Hurricane Hugo. 

Furthermore, thick mats of litter and 

organic matter still cover the ground, 

except where mineral soil was exposed 

by uprooted trees. Fire is a distinct 

possibility, however, especially now 

with heavy fuel loads in much of the 

bottomland forest. 
It became evident in the course of our 

damage survey that the forests of the 

Congaree Swamp National Monument have 

suffered severe storms several times 

during the last few decades. We 

expect that in response to Hurricane 

Hugo and other storms, changes in tree 

species composition will be buffered 

by the capacity of hardwoods to 

resprout even after suffering severe 

damage, In sloughs, storms such as 

Hurricane Hugo reduce canopy tree 

species diversity and foster the 

dominance of T. distichurn and N, 

aquatica by uprooting trees of other 

species. Because of the susceptibility of resprouted trees to woodrotting organisms and further 

mechanical damage, the effects of 

Hurricane Hugo will be evident for 

many decades. These long-term effects 

will be concentrated in areas where 

trees have vegetatively recovered from 

severe mechanical damage. 

ACKNOWLEDGEMENTS 

It was a great pleasure to conduct 

fieldwork in the Congaree Swamp 

National Monument, particularly with 

the willing and able assistance of 

numerous people, but especially J. 

Titus, P. Megonigal, and K. Moorhead. 

The cooperation of the Monument staff 

was greatly appreciated, We also 

thank S. Porth for sharing with us his 

knowledge of this lovely forest. The 

manuscript benefitted from the comments of M. Davis, P. Anderson, D. 

Hibbs, and G, Schupp. 

LITERATURE CITED 

Abrams, M.D.; Scott, M.L. 1989. 

Disturbance-mediated accelerated 

succession in two Michigan forest 

types, For, Sci. 35:42-49. 

Barry, POI,; Anderson, R.L.; Swain, 

K.M., Sr. 1982. How to evaluate and 

manage storm-damaged forest areas. 

USDA For. Sen. Southeast. Area For. 

Rep. (Sept.) SA-FR 20. 

Boucher, D.H. 1990. Growing back after 

hurricanes. BioScience 40:163-166. 

Brown, S, 1981, A comparison of the 

structure, primary productivity, and 

transpiration of cypress ecosystems in 

Florida, Ecol. Monogr. 51:403-427. 

Clements, FOE, 1916. Plant succession: 

an analysis of the development of 

vegetation. Carnegie Inst. Wash. Publ. 

242. 

Ewel, K.C.; Mitsch, W.J, 1978. The 

effects of fire on species composition 

in cypress dome ecosystas, Fla. Sci. 

41:25-31. 

Foster, D.R. 1988. Disturbance history, 

community organization and vegetation 

dynamics of the old-growth Pisgah 

forest, southwestern New Hampshire, 

U.S.A. J, EcoI,. 76~405-434. 

Gaddy, L.L. 1977. Notes on the flora of 

the Congaree River floodplain, Richland 

County, South Carolina. Castanea 

42~103-106. 

Gaddy, L.L.; Smathers, G.A. 1980. The 

vegetation of the Congaree Swamp 

National Monument. Veroeff. Geobot. 

Inst, Eidg. Tech. Hochsch. Stift. 

Ruebel Zuer. 69:171-182. 

Glitzenstein, J.S.; Harcombe, P.A.; 

Streng, D.R. 1986. Disturbance, 

succession, and maintenance of species 

diversity in an east Texas forest, 

Ecol. Monogr. 56:243-258, 

Grubb, PoJo 1977. The maintenance of 

species richness in plant communities: 

the importance of the regeneration 

niche. Biol. Rev. Cambridge Philos, 

SOC. 52:107-145. 

Hough, A.F.; Forbes, R.D. 1943. The 

ecology and silvics of forests in the 

high plateaus of Pennsylvania. Ecol. 

Monogr. 13:299-320. 

Lugo, A.E.; Applefield, M.; Pool, D.J.; 

McDonald, ROB. 1983. The impact of 

Hurricane David on forests of Dominica. 

Can. J. For. Res. 13:201-211. 

Putz, FOE,; Brokaw, N.V.L. 1989. 

sprouting of broken trees on Barro 

Colorado Island, Panama. Ecology 

703508-512. 

Putz, F.E.; Chan, HOT. 1986. Tree 

growth, dynamics, and productivity in a 

mature mangrove forest in Malaysia. 

For. Ecol. Manage. 17:211-230. 

Radford, A.E.; Ahles, HOE.; Bell, C.R. 

1968. Manual of the vascular flora of 

the Carolinas. University of North 

Carolina Press, Chapel Hill. 

Runkle, J.R. 1985. Disturbance regimes 

in temperate forests. In The ecology of 

natural disturbance and patch dynamics. 

Edited by S.T.A. Pickett and P.S. 

White, Academic Press, New York. 

pp. 17-34. 
Schaetzl, R.J.; Johnson, D.L.; Burns, Webb, S.L. 1988. Windstorm damage and 

S.P.; Small, T.W. 1989. Tree microsite colonization in two Minnesota 

uprmting: review of terminology, forests. Can. J. For. Res. 

process, and enviromental 18:1186-1195. 

hplications. Can. J. For. Res. 

19: 1-11. 

Sokal, R.R.; Rohlf, F.J. 1981. 

Biometry. 2nd ed. Freeman and Company, 

New York . Veblen, T.T.; Badley, R.S.; Reid, 

H.S.; Rebertus, A.J. 1989. Blowdown 

and stand development in a Colorado 

subalpine forest. Can. J. For. Res. 

19:1218-1225. 

Reprinted with permission from Canadian 

Journal of Forest Research 21:1765- 

1770. Mrs. Aldyth Holmes, Director, 

Research Journals, National Research 

Council of Canada, Ottawa, Ontario KIA 

OR6. 
GE TO THE CANOPY SPECIES OF 

A 24-YEAR-OLD SEED TREE REGENERATION 

EXPERIIJIENT IN A NON-ALLUVIAI; SMMP 

David L. Gartner, Dona1 Do Hook, and Marilyn Ao ~uford' 

Abstract--In the mid 1960's a 500-acre non-alluvial swamp 

on the Francis Marion National Forest in South Carolina 

was experimentally regenerated. The five treatments 

were: 1) clearcut, 2) leave 15 seed trees per acre, 3) 

leave 30 seed trees per acre, 4) leave 90 seed trees per 

acre, and 5) an uncut control. All seed trees were 

approximately 90-year-old swamp tupelo (Nyssa sylvatica 

var biflora) and averaged 14 inches in diameter at breast 

height, 

On September 21, 1989, the area was hit by Hurricane 

Hugo, and was within the high impact zone (Hook and 

others, 1991). In the winter of 1992, data were 

collected from the study area to determine if the stands 

resulting from the various harvesting treatments were 

impacted differently by the hurricane. 

Of the five main tree species, loblolly pine (Pinus taeda 

L.) received the most damage, followed by swamp tupelo, 

red maple (Acer rubrum), sweetbay (Magnolia virginiana), 

and bald cypress (Taxodium distichum) in decreasing order 

of damage. Most of the damage to swamp tupelo, red 

maple, sweetbay, and bald cypress was bent stems, with 

some broken stems. Loblolly pine stems were primarily 

broken or uprooted resulting in greater than 50 percent 

direct mortality for this species. 

Hurricane damage differed significantly from that of the 

uncut control treatment for only a few treatment species 

combinations. The results followed two general patterns: 

1) for bald cypress, red maple, swamp tupelo, and 

sweetbay, the harvested treatments had a higher 

percentage of stems in the Bent category than the uncut 

control, and 2) for loblolly pine, the harvested 

treatments had a higher percentage of stems in the 

Broken, Uprooted, and Dead categories than the uncut 

control. 

"athematical Statistician, Southeastern Forest Experiment Station, Forest 

Service, U.S, Department of Agriculture, Charleston, SC; Professor of Forestry, 

Clemson University, Clemson, SC; and Research Forester, Southeastern Forest 

Experiment Station, Forest Service, U.S. Department of Agriculture, Research 

Triangle Park, NC. 
INTRODUCTION 

A seed tree regeneration experhent 

was established in 1963 in a 500-acre 

non-alluvial swamp on the Francis 

Harion National Forest in South 

Carolina, The area is knom as Bluebird Swamp, The study area was an 

approx-tely 90-year-old even-aged 

stand of swamp tupelo (Nyssa sylvatica 

var biffsra) and bald cypress 

( Taxodium distichurn), The stand 

contained 245 st per acre that were 

5 inches or greater in diameter, and 

averaged 168 square feet of basal area 

per acre in 1963. The Bayboro soil 

series (clayey, mixed, thermic Umbric 

Paleaquults) covers the entire site 

and is listed as hydric soil (USDA 

Soil Conservation Service, 1991). 

The study was designed as a randonized 

complete block with three blocks and 

five treatments. The five treatments 

were: clearcut, leave 15 seed trees 

per acre, leave 30 seed trees per 

acre, leave 90 seed trees per acre, 

and an uncut control, All seed trees 

were swamp tupelo and were spaced as 

evenly as possible within the treatment area. Fifteen 4-%acre plots 

were laid out in the swamp during the 

sununer of 1963. Block 1 was located 

above a logging access road that was 

built across the swamp in the fall of 

1965 and Blocks 2 and 3 were located 

below the road. Block 1 was harvested 

during the dormant season of 1965-66, 

Block 2 in 1966-67, and Block 3 in 

1967-68, The harvest was done under a 

regular USDA Forest Service contract 

and rubber-tired skidders were used to 

log the area. During the growing 

season prior to each harvest, all 

plots of each block were mist-blown 

with 2,4,5-T to kill a heavy understory, Larger undesirable trees were 

poisoned by injecting them with 

2,4,5-T, Following logging, swamp 

tupelo stumps were sprayed with a 1:30 

solution of the 2,4,5-T esters and 

diesel o i l t o prevent sprouting 

(DeBell and Auld, 1971). 

On September 21, 1989, the area was 

hit by Hurricane Hugo, and was within 

the high impact zone (Hook and others, 

1991). The pre-Hugo average basal 

area across all plots, including 

remnant seed trees, was approximately 

115 square feet per acre (range 106.1 

- 126.7). The basal area, exclusive 

of remnant seed trees, ranged from 110 

square feet per acre in the clearcut 

plots to 27.5 square feet in the 

control plota. Swamp tupelo and red 

maple (Acer rubra) dominated the 

regeneration in terns sf n 

stas, In the harvested treatments, 

loblolly pine (Pinus taeda L,) contributed a major portion (at least 30 

percent) of the basal area, See Book 

and others (in press) for a more 

detailed description of the stand. 

OBJECTIVES 

We report on the treatment differences 

in the amount and type of hurricane 

damage received by the major tree 

species. 

METHODS 

In the summer of 1992, three 0.1-acre 

circular plots were randomly established within the central one-acre area 

of each original treatment plot for a 

total of 45 plots, For all stems 4.5 

feet and taller, species and diameter 

at-breast height (dbh) were recorded. 

Hurricane damage was documented for 

each stem as to whether it was bent, 

broken, uprooted, and/or dead. All 

blown down or broken loblolly pine 

stems were measured at breast height 

and recorded as dead in each plot, The 

damage classes are not mutually exclusive, so some stems were recorded in 

more than one damage class, The percent of stems in each damage class was 

calculated for each species from the 

sums of the data from the three subplots at the treatment plot level. 

These percentages were then analyzed by 

an ANOVA. 

There was no apparent regeneration 

between Hurricane Hugo and when the 

measurements were taken except sprouts 

from bent and broken stems, These 

sprouts were removed from the data set 

for this analysis. 

]RESULTS 

Effects of Species 

of the five main canopy tree species, 

swamp tupelo had the highest percentage 

of damaged stems with 73.5 percent. 

Loblolly pine had the second highest 

percentage with 63-5 percent. Red 

maple (Acer rubrum) had only 49.0 

percent damaged stems. Sweetbay 

(Magnof ia virginiana) had 32.6 percent 

damaged stems. Bald cypress received 

the least damage with 20.7 percent 

damaged stems. Bald cypress, red 

maple, swamp tupelo, and sweetbay 

reacted similarly in that the damage 

consisted primarily of bent stems with 

some broken stems (Table 1)- The 

damage to loblolly pine consisted 
Table 1--Percent of stems damaged. 

Species Bent Broken Uprooted Dead 

Swamp Tupelo 73.5a 56.9a 22.5a O.lb O*lb 

Red filaple 49.0ab 45 . 2a 4.3b 1.2b 0.2b 

Sweetbay 37.6bc 36.7ab 1.3b O.Ob O.Ob 

Bald Cypress 20.7~ 18.2bc 2.5b O.Ob O.Ob 

EoblolPy Pine 63.5ab 14.6~ 23. Pa 29.2a 51.5a 

Letters indicate species that are not significantly different from each other 

within a damage category using Tukey's procedure (Steel and Torrie, 1980). 

primarily of uprooted and broken stems 

which caused a much higher direct 

mortality rate than observed for any 

other species. The ranking of species 

by the amount of damage received 

follows the ranking by Barry and 

others (1982) as shown in Table 2. 

Table 2--Ranking of species from least 

to most susceptible to hurricane 

damage. 

Bluebird Swamp Barry and Others (1982) 

Bald Cypress 

Sweetbay 

Red Maple 

Swamp Tupelo 

Loblolly Pine 

analyzed using Dunnett's test for 

treatment means being different from a 

control mean (Steel and Torrie, 1980). 

The 15 seed trees and 90 seed trees 

treatment means in the All Damaged 

category are significantly different 

from the control treatment mean (alpha = 0.05), along with the 90 seed tree 

treatment mean in the Bent category. 

Table 3--The effect of regeneration 

treatments on the percent of stems 

damaged by Hurricane Hugo. All five 

major canopy species combined. 

Bald Cypress 

Sweetbay 

Loblolly Pine 

Red Maple 

Treatment Means (percent) 

Damage Clear 15 3 0 9 0 Control 

Class -cut Trees Trees Trees 

Because the hardwood stems resprout 

and cypress stems suffered little 

damage, the hurricane will probably 

not affect the hardwood and cypress 

composition of the stand. However, 

there probably will be a large 

reduction in the proportion of 

loblolly pine in the regenerating 

stand, as reported in Hook and others 

(in press). 

Effects of Treatments 

Table 3 shows how the combined canopy 

species in the regenerating stands in 

the different harvesting treatments 

were affected by Hurricane Hugo, When 

testing for differences in the percent 

of damaged trees, the main effect for 

treatments was not significant. Means 

for each treatment showed that the 

harvested treatments usually congregated around an average that was 

higher than the mean for the control 

treatment. These differences between 

individual harvested treatment means 

and the control treatment means were 

All 65.4 66.0* 59.4 70.4* 54.8 

Bent 50.8 50.0 49.3 58.8* 43.3 

Broke 16.3 21.3 12.2 15.8 15.4 

Uproot 1.5 1.4 .8 1.0 .5 

Dead 1.9 2.0 .9 1.1 .2 

* Treatment mean significantly different from 

control mean via Dunnett's test at p = .05. 

For the individual species, there is a 

general pattern of the harvest treatment means being larger than the uncut 

control treatment means for the A11 

Damage category. For bald cypress 

(Table 4), red maple (Table S), swamp 

tupelo (Table 6), and sweetbay (Table 

7), the pattern of the harvest treatment means being larger than the uncut 

control treatment means also holds for 

the Bent category. The swamp tupelo 90 

seed tree treatment All Damage category 

mean is significantly different from 

the control mean at the alpha = .05 

using Dunnett's test, For loblolly 

pine (Table 8), the pattern holds for 

all of the damage categories except the 

Bent category, For loblolly pine 

clearcut treatment All Damage category 
was significantly different from the 

control treatment mean, 

Table 4--The effect of regeneration 

treaments on the percent of stems 

ged by Hurricane Hugo, 

Bald Cypress 

Treatment Means (percent) 

15 3 0 90 Control 

Class -cut Trees Trees Trees 

All 30.5 30.0 40.2 12.4 11.3 

Bent 29.3 26.6 39.0 1.3 11.3 

Broke 1.2 3.1 1.2 11.1 -00 

Uproot .00 .OO .OO -00 . 00 

Dead .OO -00 .OO .OO . 00 

* Treatment mean significantly different from 

control mean via Dunnett's test at p = .05. 

Table 5--The effect of regeneration 

treatments on the percent of stems 

damaged by Hurricane Hugo. 

Red Maple 

Treatment Means (percent) 

Damage Clear 15 30 90 Control 

Class -cut Trees Trees Trees 

All 52.4 52.1 49.7 58.7 37.3 

Bent 47.7 46,6 47.9 55.2 32.9 

Broke 3.96 5.76 3.00 4.82 4.05 

Uproot 1.73 2.11 .74 1.09 1.23 

Dead .54 .OO .OO .OO .OO 

* Treatment mean significantly different from 

control mean via Dunnett's test at p = .05. 

Table 6--The effect of regeneration 

treatments on the percent of stems 

damaged by Hurricane Hugo, 

Swamp Tupelo 

Treatment Means (percent) Damage Clear 15 3 0 9 0 Control 

Class -cut Trees Trees Trees 

All 71.3 75.8 63.8 81.7* 46.8 

Bent 55.6 55,6 52.0 65.2 36.3 

Broke 19.0 27.7 15.2 23.6 16.2 

Uproot .22 .33 .03 .I7 .OO 

Dead .33 .11 '00 .OO -00 

Table 7--The effect of regeneration 

treatments on the percent of stems 

ged by Hurricane Hugo, 

€Wee tbay 

class -cut Trees Trees Trees 

A1 1 62.1 46.1 21.5 53.6 32.8 

Bent 62.1 43.7 21.5 53.6 16.1 

Broke .OO 4.3 .OO .OO 16.7 

Uproot .OO -00 .OO . 00 '00 

Dead . 00 .OO .OO . 00 -00 

* Treatment aman significantly different from 

control mean via Dunnett's test at p 1 .05. 

Table 8--The effect of regeneration 

treatments on the percent of stems 

damaged by Hurricane Hugo. 

Loblolly Pine 

Damage 

Class 

Treatment Means (percent) 

Clear 15 3 0 9 0 Control 

-cut Trees Trees Trees 

All 

Bent 

Broke 

Uproot 

Dead 

* Treatment mean significantly different from 

control mean via Dunnett's test at p = .05. 

SUMMARY 

Loblolly pine received the most damage, 

followed by swamp tupelo, red maple, 

sweetbay, and bald cypress. Most of 

the damage to swamp tupelo, red maple, 

sweetbay, and bald cypress was in the 

form of bent stems with very little 

mortality. The damage to loblolly pine 

was primarily in the form of uprooted 

and broken stems leading to a high 

(over 50 percent) mortality rate, A 

higher percentage of stems were damaged 

on the treatment plots than on the 

control plots, 

ACKNO~EDG~NTS 

We would like to thank Beth Davis and 

Andrew Huglin, who did the field work. 

* Treatment mean significantly different from 

control mean via Dunnett's test at p .05. 
LITERATORE CITED 

Barry, Patrick J.; Anderson, Robert 

Lo; Swain, Kenneth Nof Sr. 1982. How 

to evaluate and manage storm-damaged 

forest areas. Forestry Report SA-FR 

20. Asheville, NC: U.S. Department of 

Agriculture, Forest Service, Southeastern Area. 15 pp. 

DeBell. D.S.; Auld, I.D. 1971. Establishment of swamp tupelo seedlings 

after regeneration cuts. Forest 

Service Research Note SE-164. 

Asheville, NC: U.S. Department of 

Agricultre, Forest Service, Southeastern Forest Experiment Station. 

7 PP. 

Hook, Dona1 D.; Buford, Marilyn A*; 

Hams, William R. 1989. Effect of 

residual trees on natural regeneration 

in a tupelo cypress swamp after 24 

years. In: 7th Biennial Southern 

Silvicultural Research Conference* 

USDA Forest Service, Southern Forest 

Experiment Station, Gen. Tech. Rep. 

SO-93, pa 87-96, 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest. Journal of Coastal Research. 

SI 8:291-300. 

Steel, Robert; Torrie, James. 1980. 

Principles and Procedures of Statistics. Second Edition. New York, New 

York. HcGraw-Hill Book Co. 

USDA Soil Conservation Service. 1991. 

Hydric soils of the United States. In 

cooperation with National Technical 

Committee for Hydric Soils. Misc. Pub. 
GE, HARVEST OPERATIONS, AND REGENERATION ACTIVITIES 

FOLLOWING HURRICANE HUGO IN SOUTH CAROLINA-- 

PHOTOGRAPHIC DOCWENTATION 

Jeffrey L. Baumann, Robert G. Haight, 

Allan P. Marsinko, and Thomas J. strakal 

Abstract--Hurricane Hugo damaged 4.5 million acres of South 

Carolina forest land in 1989. Nearly 900 million board 

feet of sawtimber and nearly 2.6 million cords of pulpwood 

was salvaged from the damaged forest land. Approximately 

1.2 million acres needed reforestation. Muck of this 

acreage required site preparation. As a result many unique 

conditions were present in 1989 and the early 1990's in 

terns of damage, harvesting and regeneration. 

This article includes representative photographs of much of 

the damage and many of the activities. Unusual activities 

are also included; for example, wet storage of salvaged 

logs, helicopter logging, horse logging, and planting of 

v-bladed strips. 

Related activities are also included. Probably the most 

interesting example involves the Francis Marion National 

Forest red-cockaded w~odpecker (RCW) population. Prior to 

the hurricane, the forest had 477 family groups of RCWfs. 

Hurricane Hugo destroyed 87 percent of the RCW cavity trees 

and more than 50 percent of the pine sawtimber used as 

foraging habitat and for cavity trees. Nearly two-thirds 

of the birds were killed. Photographs document the damage 

and an interesting method of developing new tree cavities. 

These photographs and related descriptions serve as basic 

documentation of the effect of Hurricane Hugo on South 

Carolina's forest resource, the early efforts to salvage 

damaged timber, and the reforestation activities that 

followed the hurricane. They provide an idea of the damage 

that can be expected after such a hurricane and the type of 

effort required to re-establish a stom-damaged forest. 

Note that the article "Site Preparation and Tree Planting 

Costs on Hurricane-Damaged Lands in South Carolina" by 

Straka, Marsinko, Baumann, and Haight in this publication 

contains five photographs of site preparation activities 

following Hurricane Hugo. 

'Jeffrey L. Baumann, South Carolina Forestry Commission, Box 21707, Columbia, SC 

29221; Robert G. Haight, USDA Forest Service, North Central Forest Experiment 

Station, 1992 Folwell Ave., St. Paul, MN 55108; Allan P. Marsinko and Thomas J. 

Straka, Department of Forest Resources, Clemson University, Clemson, SC 29634- 

1003. 

106 
Typical Hurricane Hugo damage in a pine sawtimber stand. Tree snag in front 

has a "Gimme 12" campaign poster on it requesting the public to postpone any 

outdoor burning for a 12-month period. 

Hurricane Hugo damage around one of the many homes. 
3. Hurricane Hugo severely damaged the timber resource of the Francis Marion 

National Forest, once home of the second largest population of the endangered 

red-cockaded woodpecker. 

4. Aerial shot of some of the many acres affected by Hurricane Hugo. 
Even with salvage, much of the timber resource is not usable. 
6. Young pine plantations were not spared the brunt of the hurricane force 

winds. Many plantations displayed the characteristic lean caused by the 

prolonged exposure to 75+ miles per hour winds. Fortunately, over time, 

these young trees straightened up. 

7. A good example of the twisting effect the hurricane winds had on trees. 

Loggers were forced to extensively utilize chain saws in harvesting which 

slowed the salvage effort. 
Most trees developed "ring shakes" which made them unusable for poles, veneer 

logs and sawtimber. Most ended up for pulpwood; landowners received on 

average only 10 cents on the dollar of pre-Hugo timber value. 

All methods of logging were utilized to salvage as much timber as possible. 

Here mule logging is used on a sensitive site. 
10. Higher tech methods like helicopter logging were also utilized. 
11. Road weight limits were raised for logging trucks to help maximize salvage 

efforts, 

12. A large amount of wood needed to be salvaged over a short period of time. 

Mill capacity was exceeded. Wet storage was promoted and utilized to 

"preserve" wood quality until it could reach the saw. 

1'13 
13. Many acres would regenerate naturally over the next few years. There was a 

good seed crop of loblolly pine and many stands had advance regeneration of 

longleaf pine. 
14. Other stands needed help through site preparation and artificial 

regeneration. 

15. Through Federal Emergency Management Agency (FEW) funds, John Deere 750 

tractors were leased by the Forestry Commission and private contractors were 

hired to establish pre-suppression firebreaks around homes and communities. 

115 
16. Private contractors were also utilized in fire suppression work to construct 

firebreaks through the heavy debris left by Hurricane Hugo. 
17. FEMA funded the use of CE-215 aerial tankers from Canadair to help suppress 

wildfires in the areas affected by Hurricane Hugo, 

18. Hurricane-damaged timber. 
19. Before-Hugo and arter-mgo photographs showing hurricane damage. 

118 
20. Following the hurricane, artificial cavities were used to provide nesting 

sites for red-cockaded woodpeckers. A chainsaw was used to cut a hole in a 

live pine and the insert was placed in the hole. Cracks around the insert 

were filled with wood filler and the artificial cavity painted to blend with 

the tree (USDA Forest Service). 
21. Hurricane-damaged timber. 
23, Hurricane-damaged timber. 

24, Nurricane-damaged timber, 
E BUCO: EFFECTS ON 

SOUTB CAROLINA'S FOREST RESOURCE 

Raymond M. Sheffield and Michael T. ~hompson' 

INTRODUCTION 

On September 21, 1989, Hurricane Hugo 

struck the coast of South Carolina 

near Charleston with sustained winds 

of 135 miles per hour. The storm 

moved northwest toward Rock Hill and 

exited the state with winds still at 

or near hurricane strength. Hugo has 

since been widely acknowledged as the 

greatest single forest disaster in the 

staters history, 

Aerial and ground surveys conducted by 

the South Carolina Forestry Commission 

identified 23 counties with substantial forest damage. Damage estimates 

from this aerial survey guided the 

salvage of damaged t er, the establishment of fire control measures, and 

initial planning for reforestation. 

It was evident, however, that more 

comprehensive and objective data on 

the damage to the forest resource were 

needed to assess changes in wood 

supply, plan for necessary wood 

procurement shifts, and to guide longterm forest resource programs, 

The Forestry Commission requested that 

the Forest Inventory and Analysis 

(FIA) Research Work Unit at the Southeastern Forest Experiment Station 

conduct a special inventory of the 

forest resource in the damaged area. 

The previous full-scale inventory of 

South ~arolina was completed in 1986 

(Tansey and Hutchins 1988). During 

the fall of 1989 and early 1990, 

objectives were established, field 

procedures developed, funds secured, 

and field crews assembled. The 

objectives of the inventory were to: 

(1) determine the volume of hurricanerelated mortality and damage, (2) 

assess damage to merchantable and 

submerchantable pine plantations, and 

(3) quantify needed stand treatments 

resulting from the storm. 

Resource Analyst and Forester, 

Forest Inventory and Analysis, 

Asheville, North Carolina 

This report presents results, our 

interpretations, and documents the 

procedures used in the collection and 

analysis of the data. 

Sampling Procedures 

The sample plots used in the Hugo 

inventory included 2,530 permanent 

plots established in the 23 counties 

during the sixth survey of South 

Carolina in 1986 (Figure 1). FIA 

sample plots are based upon a 10-point 

cluster design. In most cases, five 

points are installed in a single forest 

condition using a basal area factor of 

37.5 square feet per acre to sample 

trees 5.0 inches d.b.h. and larger. 

Trees less than 5.0 inches d.b.h. are 

tallied on 1/300-acre fixed plots at 

each of the point centers. More 

detailed information about standard FIA 

field sampling procedures is available 

(Tansey and Hutchins 1988; USDA Forest 

Service 1991). Between February 1990 

and June 1990, each of the 2,530 ground 

samples was relocated and assessed for 

hurricane- and nonhurricane-related 

changes since 1986. 

Figure P--Distribution of 2,530 

timberland sample locations that were 

remeasured and evaluated for hurricane 

damage. 
In accordance with the objectives, 

sampling procedures differed for 

natural and planted stands. In 

natural stands, field crews accounted 

for each tree that was 3.0 inches 

d.b,h* and larger in 1986. This 

procedure provided assurance that any 

tree that had grown large enough to 

have merchantable volume (5.0 inches 

d,b,h* and larger) would be evaluated. 

Each tree was assigned to one of six 

categories: (1) live, without hurricane damage; (2) live, with hurricane 

damage; (3) dead, hurricane related; 

(4) dead, not hurricane related; (5) 

cut, not associated with the salvage 

of damaged stands; or (6) cut, associated with hurricane salvage or cleanup 

operation, regardless of whether the 

tree was utilized for a product, Live 

trees with hurricane damage were 

assessed for volume loss, percentage 

of crown missing, lean and bend, root 

damage, degree of damage to the tree 

bole, and salt burn. Data-collection 

procedures are documented in more 

detail in Appendix A. 

In planted stands, data-collection 

procedures differed from those in 

natural stands in two respects: (1) 

field crews accounted for all trees 

that were 1.0-inch d,b.h, and larger 

in 1986; and (2) planted pine trees 

that had grown from less than 1.0 inch 

d.b.h, to greater than 1.0 inch and 

free-to-grow pine seedlings were 

tallied on 1/300-acre fixed plots 

around each of the point centers. 

These data were necessary to assess 

current stocking and damage levels in 

young plantations. 

The collection of updated stand 

descriptive information was minimized. 

Items such as ownership, stand size, 

forest type, and stand age were not 

updated or reclassified. The use of 

these stand descriptors in this report 

reflects classifications made in the 

sixth inventory in 1986. Current 

stand origin (planted or natural) was 

noted. Field crews also recorded the 

treatments andlor disturbances, 

including hurricane damage, that had 

occurred in each stand since 1986. 

Finally, crews assessed treatment 

opportunities at each plot--salvage 

cuts, regeneration, thinning, etc.-- 

along with the potential for natural 

pine regeneration. 

Data Limitations 

Since procedures were designed to 

provide data focused on hurricane 

damage, many estimates and 

classifications were carried forward 

from the 1986 inventory. Estimates of 

ti&erland area were not updated for 

this inventory; thus, no change in 

timberland area is factored into the 

volume change estimates. Forest type, 

ownership, stand size, and age were not 

re-estimated. The reader should be 

aware that tables displaying these 

stand and area descriptors may differ 

somewhat from true conditions in 1990. 

For example, major land transactions 

since 1986 that would affect the 

acreage by ownership are not reflected 

in tables or illustrations in this 

report. All displays of age class or 

stand type portray 1986 conditions 

prior to any cutting, treatment, or 

hurricane disturbance. An exception 

was made when planting was noted on a 

plot, Then, the broad stand type was 

changed to pine plantation and a zero 

(0) age class was assigned, 

A complete assessment of current stocking and hurricane damage in very young 

natural stands was hampered because no 

trees less than 3.0 inches d.b.h. were 

measured or sampled there in 1990. 

Field crews did assess treatment opportunities in these stands, reflecting 

the degree of damage inflicted. 

Finally, the Hurricane Hugo inventory 

is limited to providing updated volume 

statistics for the 23 counties identified as sustaining significant damage. 

Volume estimates for the entire state 

cannot be estimated directly from these 

data. 

Classification of Live-Tree 

Damages 

The inventory procedures were designed 

to estimate inventory change in the 

selected counties and to meaningfully 

describe damage to the existing inventory. The new inventory includes all 

merchantable trees that were alive at 

the time field crews visited each 

ground location. All types of significant damage to sample trees were 

recorded to best describe the condition 

of each tree. A logical classification 

system was needed to accurately assess 

and illustrate the true extent of 

damage, but no suitable one was known 

to exist. The challenge was to place 

each tree into a meaningful category 

that would provide a reasonable 

description of damage severity and risk 

of dying in the near future. Draft 

criteria were developed for different 

categories of tree size, species group, 

and stand type to place each tree in 

the appropriate class of damage. The 
criteria were submitted to 20 individuals or organizations for review. 

Review coments were received from 13 

individuals or organizations, and 

final criteria were developed. These 

criteria and a description of evaluation methodology are in Appendix B. 

The damage/risk classes were designed 

to reflect the likelihood of tree 

survival and present (or potential) 

value degrade. The categories are: 

Class 1--High-risk tree with a high 

probability of dying in the near 

future. Damage and value loss are 

severe enough that this tree should 

not be retained in the stand. 

Class 2--Moderatemrisk tree with elevated risk of mortality; serious 

current or potential loss of value; 

retention in the stand is 

questionable. 

Class 3--Low-risk tree that has a high 

probability of surviving, though not 

as high as an undamaged tree. Damage 

and value degrade are minimal--these 

trees should be retained in the stand 

in most management scenarios. 

Healthy--No obvious hurricane damage. 

A tree with hidden or internal damage 

would be included here. 

The damage/risk evaluation process 

placed trees into discrete categories. 

We recognize that, in reality, damaged 

trees belong on a continuum ranging 

from "not damaged" to "nearly dead." 

Our process was uncomfortably subjective. We found only a limited number 

of research studies for guidance 

(Barry and others 1982; Brewer and 

Linnartz 1973). We defend it primarily on the basis that it seems 

practical. We hope that our detailed 

description of methods will help in 

understanding Hugo damage and will 

lead to improvements in damage estimation techniques in the future. 

Affected Area and Volume 

This chapter s arizes our estimates 

of the amount and location of timberland that was significantly affected 

by Hurricane Hugo. It also provides 

estimates of the losses of softwood 

and hardwood timber volumes. Additional data on damage are in Appendix A 

More Than 4.5 Million Acres 

Damaged 

The reinventory indicates that 4.5 

million acres, or two-thirds of the 6.5 

million acres of timberland in the 23 

counties, were damaged by Hurricane 

Hugo (Appendix Table C.21). About 37 

percent of South Carolina's timberland 

sustained some storm damage. 

Timberland damage was most widespread 

near the coast and on the northeast 

side of the hurricane's eye as it moved 

in a northwesterly direction. Figure 2 

shows the generalized distribution and 

extent of hurricane damage in South 

~arolina. One should not conclude, 

however, that all stands in the area 

shown as damaged sustained damage or 

that damage does not exist in the 

unshaded areas. Representations of 

damaged timberland were created by 

drawing Thiessen polygons (Newton and 

Bower 1990) around each ground location 

classed as having hurricane damage. 

Adjacent polygons depicting damage were 

merged into a single polygon by deleting interior polygon lines. Undamaged 

timberland and nonforest plot locations 

are portrayed as undamaged on the map, 

Therefore, the higher incidence of 

nonforest land in the central portion 

of the state lends an appearance of 

less damage there than in the lower 

coastal plain or in the more heavily 

forested areas to the north. 

Figure 2--A generalized distribution of 

timberland in South Carolina damaged by 

Hurricane Hugo. Note: Not all stands 

in shaded areas sustained damage, and 

damage occurred in unshaded areas. 
Burricane Hugo damaged more than 90 

percent of the timberland in six 

counties--Berkeley, Clarendon, 

Florence, Lee, Sumter, and 

Williamsburg, The distribution of 

damage suggests that there probably 

was damage in some counties not 

reinventoried, most notably Colleton 

and Lexington Counties. The damage in 

these counties was acknowledged prior 

to the field work; they were omitted 

because of the limited extent of 

damage and increased data-collection 

effort required. 

Substantial hurricane damage was found 

in a11 stand types and broad management types (Appendix Table C.21), 

Sixty-two percent of the pine plantation acreage was affected, compared 

with 68 percent for natural pine and 

oak-pine stands, and 64 percent for 

upland hardwood stands. Lowland hardwood stands sustained the highest 

incidence of damage--77 percent. Lowland hardwood stands often contain 

large, shallow-rooted trees with large 

crowns, factors associated with 

increased susceptibility to wind 

damage (Barry and others 1982; Hook 

and others 1991). Across all stand 

types, the damage incidence rate 

averaged 76 percent for stands 

classified as sawtimber size, 67 

percent for pole-timber, and 59 

percent for sapling-seedling. 

Timberland in public ownership was the 

most severely affected in terms of 

acres damaged--79 percent of the 

acreage controlled by public agencies 

sustained some hurricane damage 

(Appendix Table C.21). One factor 

contributinq to the high incidence is 

the large concentration of National 

Forest in the most severely affected 

area near the coast in Berkeley and 

Charleston Counties. Another reason 

for the high rate of damage on public 

land is that the older stands and 

larger trees characteristic of public 

forests are more susceptible to wind 

damage. Tall, large-diameter trees 

sustained more damage than smaller 

trees. Forest industry land and 

nonindustrial private forest (NIPF) 

land were both equally affected by the 

hurricane; 68 percent of the acreage 

in these two classes was affected. 

Softwood Inventory Reduced by 

21 Percent 

Hurricane Hugo reduced the inventory 

of softwood growing stock by 21 

percent, from an estimated 4.8 billion 

cubic feet that existed prior to the 

storm to 3.8 billion cubic feet (Figure 

3 and Appendix Table C.1). Some 376 

million cubic feet of Hugo-damaged 

softwoods were salvaged, and 632 

million cubic feet were killed but not 

salvaged. The extent and nature of 

damages to trees that were not killed 

will be discussed later. Softwood 

sawtimber volume declined from an 

estimated 19 billion board feet to 14 

billion board feet, a drop of more than 

25 percent (Appendix Table C.3). 

>Peg Grots Regular Regular Pra-Hugo Hvpo Hugo 1990 

inventory prortn cut mortalfly inventary salvage martallfy tnvenlory 

Figure 3--Change in volume of softwood 

growing stock, by component of change. 

Not all the volume classed as salvage 

was utilized for wood products. Our 

total includes all damaged trees that 

were cut after the hurricane. Some of 

these trees were cut in cleanup operations in which the stems were not 

utilized, and some were cut but not 

utilized during salvage operations. 

The South Carolina Governor's Forest 

Disaster Salvage Council tracked actual 

salvage volumes removed for product use 

and can provide final statistics. 

The pre-Hugo estimate of softwood 

inventory was developed by adding 

estimates of gross growth (1 billion 

cubic feet) to the 4.8 billion cubic 

feet present in 1986 and subtracting 

non-Hugo-related softwood removals (900 

million cubic feet) and mortality {lOO 

million cubic feet). We are fairly 

certain that softwood volume changed 

little from 1986 until Hugo struck, but 

we acknowledge that errors are associated with the computation. For 

instance, field crews encountered some 

difficulty in determining whether a 

tree was cut prior to the hurricane or 

whether it was removed during a stormrelated salvage operation. Also, some 

growth occurred between the time Hugo 

struck and the date of plot measurement the next spring; this volume 

increment was assumed to be minimal. 
In establishing the pre-Hugo inventory, all growth was assigned to the 

period before the storm" occurrence, 

To more accurately describe storm 

impacts in the text, all losses and 

changes are related to the pre-Hugo 

inventory rather than the 1986 inventory. This rule is not strictly 

adhered to in the appendix tables, but 

the values reported and their bases 

for change are well defined in the 

tables. 

Declines in softwood inventory were 

recorded in all 23 counties, but 

declines were greatest in counties 

near the coast and along the path of 

the hurricane's eye (Figure 4), More 

moderate losses occurred in counties 

more distant from the path. Six 

counties--Berkeley (49 percent), 

Charleston (47 percent), Clarendon (45 

percent), Sumter (44 percent), 

Lancaster (35 percent), and Lee (34 

percent)--lost more than one-third of 

their pre-Hugo softwood inventory, 

Berkeley and Charleston Counties alone 

accounted for 43 percent of the Hugorelated drop in softwood inventory. 

Pre-Hugo 

Post-Hugo 

Figure 4--Pre- and post-Hugo softwood 

growing-stock inventories, by county. 

Declines in softwood inventory varied 

considerably among the major ownership 

categories (Appendix Tables C.7 and 

C.9). The most severe loss occurred 

on land controlled by public agencies. 

Volume of softwood growing stock fell 

34 percent to 451 million cubic feet 

on public land, Public land, which 

accounted for only 14 percent of the 

pre-Hugo softwood inventory, sustained 

23 percent of the softwood volume loss. 

More than one-third of the total softwood mortality caused by the hurricane 

occurred on publicly owned t 

about 204 million cubic feet. The 

location of National Forest land in the 

storrnfs path and the larger-thanaverage size of trees on this land 

explain the heavy losses sustained 

there, The volume of softwood growing 

stock dropped by only 12 percent to 907 

million cubic feet on timberland controlled by forest industry. The percentage reduction was smallest for this 

owner category. In this region a high 

proportion of forest industry holdings 

are in young pine plantations. Of the 

1.6 million acres of forest industry 

timberland, about a fourth was in 

planted pine stands under 20 years old 

in 1986. The small trees in the 

planted stands sustained considerably 

less damage and mortality than larger 

trees in older stands. Hugo-related 

salvage also was relatively small on 

industry land. Forest industry land 

supplied only 11 percent of all Hugorelated softwood growing-stock 

removals. Softwood inventory held by 

NIPF owners was reduced by 21 percent 

from 3.1 to 2.4 billion cubic feet. 

No yellow pine species was especially 

resistant to the hurricane's winds 

(Figure 5 and Appendix Tables C.17 and 

C.19). Loblolly pine inventory fell by 

22 percent in the wake of Hugo to 2.5 

billion cubic feet. By far the most 

abundant species in the region, loblolly pine accounted for 72 percent of 

the decline in softwood inventory. 

Volume of longleaf pine fell by 25 

percent to 303 million cubic feet, 

Slash and pond pine volumes declined by 

27 and 29 percent to 146 and 180 

million cubic feet, respectively. 

Shortleaf pine experienced a smaller 

decline of 13 percent to 205 million 

cubic feet. However, shortleaf occurrence is concentrated in the areas away 

from the coast. 

Cypress survived the hurricane surprisingly well. The inventory of 

cypress fell by only 3 percent to 355 

million cubic feet. Putz and Sharitz 

(1991) also found that cypress was able 

to withstand the hurricane's winds 

better than most species in the 

Congaree Swamp. 

Softwood volume declined across the 

entire range of diameter classes 

(Figure 6 and Appendix Tables C.13 and 

C.15). Volume declined by 8 percent 
BiitMn cubtc he% 

3.5 111111 Pro-Hugo j 

Figure 5--Pre- and post-Hugo softwood 

growing-stock inventories, by species. 

kl$tlion CUC~~C feet 

a00 ;Ip- I 

6 8 10 s 12 14 16 18 20. 

Diameter id.b.h.) class 

m Pie-Hugo 1990 Rnvantory 

Figure 6--Pre- and post-Hugo softwood 

growing-stock inventories, by diameter 

class, 

in the 6-inch class, by 11 percent in 

the 8-inch class, and by 16 percent in 

the 10-inch class, Reductions ranging 

from 22 to 32 percent were recorded in 

the larger diameter classes. The high 

losses in the larger size classes show 

that large pines were particularly 

susceptible to bole breakage, windthrow, and subsequent mortality. 

Further Softwood Mortality 

Losses Likely 

Observations of damaged trees not 

killed by the stom suggest that 

substantial additional softwood 

mortality is likely in the next few 

years. Of the 3.8 billion cubic feet 

of softwood growing stock classified 

as live timber (post-Hugo inventory), 

29 percent, or nearly 1.1 billion 

cubic feet, was damaged to some extent 

(Appendix Table C.5). Almost half of 

this damaged volume was in the lowest 

risk category--class 3. However, 

nearly 0.6 billion cubic feet was in 

trees classed as moderate or high 

risk. No attempt will be made here to 

estimate the additional mortality that 

is likely to occur. The rate of loss 

will depend on factors such as weather, 

insects, disease, and further salvage 

efforts. However, the potential for 

additional mortality of several hundred 

thousand cubic feet is present. 

As with mortality, damage to live trees 

was greatest on public forests (Appendix Tables 6.11 and C.12). Hore than 

36 percent of the 1990 softwood inventory on public land was damaged to some 

degree with severe and moderate damage 

(classes 1 and 2) present on 22 percent 

of the post-Hugo softwood inventory. 

About 36 percent of the post-Hugo 

softwood inventory on forest industry 

forests was damaged, but 19 percent was 

in the class 3 or low-risk group. Some 

26 percent of the post-Hugo softwood 

volume on NIPF land was damaged; 6 

percent was in the class 1 category, 8 

percent in class 2, and 12 percent in 

class 3. 

Softwood Damage Summary 

Damage to softwood growing-stock (using 

the pre-Hugo inventory as a base) is 

summarized in Figure 7. About 8 

percent of the pre-Hugo inventory was 

removed in salvage operations, and 

another 13 percent (0.6 billion cubic 

feet) was dead at the time of plot 

remeasurement. Hugo-related mortality 

will continue to accumulate for a 

number of years. Some 23 percent of 

the softwood inventory before Hugo is 

in damaged living trees. About 2.7 

billion cubic feet, or only 56 percent 

of the pre-Hugo inventory, was classed 

as "healthy," or having no obvious 

storm-related damage, Thus, softwood 

inventory losses to Hurricane Hugo 

range somewhere between the 21 percent 

(1.0 billion cubic feet) killed 

directly or salvaged immediately after 

the storm and the 44 percent (2.1 

billion cubic feet) killed, salvaged, 

or damaged. A reasonable estimate of 

softwood loss is around 30 percent of 

pre-Hugo inventory (1.4 billion cubic 

feet), 

Pre-Hugo inventory = 4.8 billion cubic feet 

Figure 7--Summary of hurricane losses 

and damage to the pre-Hugo softwood 

inventory. 
Hardwood Inventory Reduced by 6 

Percent 

Hurricane Hugo reduced the inventory 

of hardwood growing stock in the 23 

counties by 6 percent to 4.8 billion 

cubic feet (Figure 8 and Appendix 

Table (2.2). Sawt er losses were 

similar in magnitude (Appendix Table 

C.4). An estimated 5.1 billion cubic 

feet of hardwood growing stock was 

present prior to Hugo, up from 5.0 

billion cubic feet in 1986. Hardwood 

inventory reductions were attributed 

to 270 million cubic feet of Hugorelated mortality and to only 49 

million cubic feet of salvage. These 

losses are small in comparison with 

softwood losses for two reasons. 

First, there was little hardwood 

salvage cutting--most of the efforts 

to salvage dead and damaged timber 

focused on pine species. Second, 

softwood species died more quickly 

after windthrow, bole breakage, or 

loss of limbs, whereas hardwood 

species were generally still alive, 

Even windthrown hardwoods and those 

that lost their entire crown were 

sprouting new growth the spring after 

the storm. Many of these severely 

damaged hardwoods will die, and the 

wood in those that do not will be 

degraded badly. 

Yiiion cubtc feet 

I 

I 

1906 Gr0.8 ReguI#r Regular Pre-NWO Hugo Hugo 1990 

rnrnnlory prorth cut morlllity mwnlory r#ivsgr mortality mwntory 

Figure 8--Change in volume of hardwood 

growing stock, by component of change. 

Geographically, the distribution of 

hardwood volume loss followed essentially the same pattern as for softwoods (Figure 9). The counties with 

the most severe declines in hardwood 

volume are near the coast and along 

the path of the hurricane's eye. Lee 

County lost 34 percent of its hardwood 

inventory, whereas Charleston lost 16 

percent, and Berkeley 14 percent. 

Among ownership classes, public land 

sustained the most severe reductions 

in hardwood volume (Appendix Tables 

C.8 and 6.10). The hardwood inventory 

controlled by public owners declined by 

16 percent to 237 million cubic feet, 

That controlled by forest industry 

decreased by 5 percent from less than 

1.1 to about 1.0 billion cubic feet, 

Hardwood inventory on NIPF land dropped 

6 percent from 3.8 to 3.6 billion cubic 

feat--near the average for all ownership categories. 

Pre-Hugo 

Post-Hugo 

Figure 9--Pre- and post-Hugo hardwood 

growing-stock inventories, by county. 

Large hardwoods were the most prone to 

hurricane-related mortality (Figure 10 

and Appendix Tables C.14 and C.16). 

The inventory of hardwoods 20 inches 

d.b.h. and larger dropped by 9 percent, 

whereas reductions were more modest for 

smaller trees, Volumes of all major 

hardwood species in the region 

decreased (Figure 11 and Appendix 

Tables C.18 and C.20). Red oaks 

suffered the most severe drop of 10 

percent to 1.0 billion cubic feet. The 

sweetgum inventory declined by 6 

percent to 1.0 billion cubic feet, 

Volume of tupelo and blackgum--the 

predominant hardwood species group in 

the region--dropped 3 percent to 1.1 

billion cubic feet. Volume of all 

white oaks dropped 7 percent to 420 

million cubic feet. The small loss of 

blackgum and tupelo relative to other 

hardwoods is consistent with findings 

of a study in the Congaree Swamp (Putz 

and Sharitz 1991). 

Very Heavy Hardwood Damage 

Severely damaged hardwoods did not die 

as quickly after the storm as did 

softwoods. As a result, hardwood 
6 8 10 12 14 16 18 20- 

Dtameter id.b.h.) class 

Figure 10--Pre- and post-Hugo hardwood 

growing-stock inventories, by diameter 

class. 

Billton cubic tee1 

I I n $re-nu*. , l 

Red Whbte TuDElO/ Sr*.tqum Y.tlaw- Red 

00k oak biackgum ooplar ma~te 

Figure 11--Pre- and post-Hugo hardwood 

growing-stock inventories, by species. 

mortality understates the real 

terrible blow to the hardwood 

resource. That blow is expressed 

primarily in the figures for damaged, 

living trees. Thirty-two percent of 

the post-Hugo hardwood inventory is 

damaged to some degree (Appendix Table 

C.5). Damaged trees contain 5.3 

billion board feet of hardwood sawtimber. About 12 percent of the 1990 

hardwood growing stock is in high-risk 

trees. Only 6 percent of the softwood 

inventory is in this class. Eight 

percent of the hardwood volume is in 

class 2 trees and 12 percent is in 

class 3 trees. 

Public lands contained the highest 

proportion of damaged hardwood volume 

--51 percent of the post-Hugo hardwood 

inventory on public forests was 

damaged to some degree (Appendix 

Tables C.11 and C.12). National 

Forests were most severely damaged; 60 

percent of the 1990 hardwood inventory 

was damaged, and two-thirds of the 

damaged volume is in trees in classes 

1 and 2, On both forest industry and 

NIPF land, about 31 percent of the 

1990 hardwood inventory was damaged 

after the storm. 

Wigh-risk (class If trees are more 

prevalent with increasing diameter for 

hardwoods (Appendix Table C.14). Less 

than 10 percent of the volume in hardwood trees 15.0 inches d.b.h. and 

smaller was classified as high risk. 

For hardwoods larger than 15.0 inches, 

the proportion in class 1 averaged 18 

percent, and it exceeded 21 percent for 

the largest trees. The proportions of 

damaged hardwoods in classes 2 and 3 

did not change substantially across the 

range of diameter classes. 

Red oaks appear to have suffered the 

most (Appendix Table G.18). About 42 

percent of the 1990 red oak inventory 

was damaged, and one-half of the 

affected trees was in class 1. Some 31 

percent of white oak volume was 

affected, and 14 percent was in class 1 

trees. In contrast, only about 22 

percent of the tupelo and blackgum 

volume was damaged and most of this 

volume was in class 3 trees. About 304 

million cubic feet, or 29 percent, of 

the sweetgum volume was damaged; 40 

percent of yellow-poplar volume was 

damaged; and 42 percent of the soft 

maple volume was damaged. 

Hardwood Damage Summary 

The fate of the pre-Hugo hardwood 

inventory is outlined in Flgure 12. 

The volume present before the storm was 

about 5.1 billion cubic feet. Only 5 

percent of the pre-Hugo inventory, or 

270 million cubic feet, was in trees 

that were killed outright by the storm. 

Only 1 percent was removed in salvage 

operations. Almost 577 million cubic 

feet, or 11 percent, of the pre-Hugo 

inventory is now in class 1 trees. 

Another 385 million cubic feet, or 8 

percent, is in class 2 trees and some 

577 million cubic feet is in class 3 

trees, After subtracting out all Hugorelated damage, salvage, and mortality, 

about 3.3 billion cubic feet, or 64 

percent, of the pre-Hugo hardwood 

inventory remains in an undamaged 

state. 

Although the immediate loss of hardwoods to Hugo was relatively small (0.3 

billion cubic feet of mortality and 

salvage volume), the potential for 

additional hardwood mortality and 

degrade is very high. A reasonable 

estimate of total hardwood damage is 

about 20 percent of the pre-Hugo 

hardwood volume, or 1.0 billion cubic 

feet, While hardwood mortality will 
. . 

Cress i 

40% 

Healtny 

81% Class 2 23% 

crass 3 

------------.- ......................... 57% 

Saivage iB 

Pre-Hugo inventory * 5.1 billion cubic feet 

Figure 12--Surfunary of hurricane losses 

and damage to the pre-Hugo hardwood 

inventory, 

not likely escalate to this level, 

loss estimates of this magnitude are 

justified because of the value loss 

associated with many of the windrelated damages. 

Stand Condition Assessment 

By any reasonable standard, the timber 

damage caused by Hurricane Hugo was 

catastrophic, But people are resilient, and they know that timber is a 

renewable resource. The people of 

South Carolina want to know what must 

be done to get their forests back to 

normal, And while their forests are 

recovering, they want to know what the 

effects on the timber industry will 

be. Answers to those questions depend 

on accurate descriptions of stand 

conditions before and after the storm. 

We estimated the stocking of manageable stand (crop) trees just prior to 

Hurricane Hugo by the method described 

below. The term "stocking" as used 

here refers to the degree of occupancy 

of the land by trees as compared with 

a minimum standard required to fully 

utilize the growth potential of the 

land. Values used are expressed in 

percentage of full stocking. 

(I) Stocking of all tally trees on 

each plot was summarized to establish 

the baseline stocking level of each 

plot at the time of the 1986 inventory. Only trees 3.0 inches d.b.h. 

and larger in natural stands and 1.0 

inch in planted stands were tallied. 

Furthermore, only trees that were 

coded as being part of a manageable 

stand were considered; if a manageable 

stand did not exist in 1986, stocking 

of all growing-stock trees was 

(2) Trees that were cut or died 

after the 1986 inventory but before 

Hugo were subtracted from the 1986 

baseline stocking to establish the preHugo condition or stocking for the 

stand. 

Trees killed by the storm or salvaged 

soon after are no problem--they must be 

deducted to estimate current stocking. 

Assessment of current stocking, however, requires some conjecture about 

how many of the trees damaged by the 

storm will make satisfactory crop trees 

through the end of the timber rotation. 

Damage to live trees ranges from 

relatively minor to major and life 

threatening. Three different assumptions about damaged trees were made: 

1. All damaged trees (risk classes 

1, 2, and 3) are unsatisfactory for 

future stocking (maximum stocking 

reduction). 

2. Only class 1 and class 2 trees 

are unsatisfactory (average reduction). 

3. Only class 1 trees are 

unsatisfactory (minimum reduction). 

Trees that were classed as acceptable 

in 1986 and were not damaged by the 

storm, plus those trees with light 

levels of damage, were all considered 

to be acceptable to retain in the stand 

until the end of a rotation. Different 

minimum levels of pre- and post-Hugo 

manageable stand stocking were used for 

assessments of regeneration needs and 

timber supply impacts. 

Regeneration Needs Soar 

previous assessments of regeneration 

treatment opportunity have used 60- 

percent stocking as a minimum for 

determining whether a manageable stand 

exists (Tansey and Hutchins 1988). In 

1986, the 23 counties reinventoried 

contained approximately 1.0 million 

acres of timberland judged to be in 

need of regeneration. In this 

analysis, we have used the same 

standard for our baseline estimate of 

added regeneration treatment opportunity. Stands that moved from greater 

than 60-percent stocking with manageable stand trees to less than 60 

percent were included in the s 

additional acres needing regeneration. 

Pre- and post-Hugo stocking values 

different from these can also be used 

to estimate regeneration needs, and an 

example of this flexibility is demonstrated. 

Depending on which live-tree damages 

were included as stocking reductions, 

the acreage reduced below minimum- 
stocking standards ranged from 0.8 to 

1.5 million acres (Table I). Using 

the minbum-stocking-reduction 

scenario discussed above, 0.8 million 

acres shifted from more than 60 

percent stocked with crop trees to 

less than 60 percent stocked. Under 

the average discount, 1.2 million 

acres were damaged severely enough to 

place them into a regeneration needs 

category. If all damaged trees are 

used as discounts (maximum discount), 

1.5 million acres shift into a poorly 

stocked category. Considering this 

range, the acreage needing regeneration in these 23 counties has very 

likely more than doubled because of 

hurricane-related damages. 

The average discount option probably 

yields the most realistic estimate of 

regeneration needs. Under the maximum 

discount, many acres are classed as 

poorly stocked based on fairly minor 

damages such as small portions of 

crown missing or minor degrees of lean 

and bend, On the other hand, the 

minimum discount probably understates 

the area of timberland where the need 

to start over exists. To a large 

extent, the decision to regenerate 

will depend upon the individual 

landowner's view of what constitutes 

an acceptable stand. 

Under the average discount, stocking 

was reduced sufficiently on about onefourth of the 4.5 million affected 

acres to warrant stand regeneration. 

Hugo added significant opportunities 

for regeneration in all types of 

stands. About 29 percent of damaged 

pine plantations were determined to be 

less than adequately stocked' with 

acceptable trees based upon the defined 

standards. This proportion is as high 

as that for lowland hardwood and somewhat higher than that for natural pine 

stands (27 percent). The relatively 

high proportion of plantations classed 

as poorly stocked is partially attributable to the more complete evaluation 

of all potential crop trees in these 

stands as compared with natural stands. 

In general, however, the timber expectations of the owners of plantations 

probably exceed the expectations of the 

owners of natural stands. 

Other minimum levels of stocking for 

pre-Hugo and post-Hugo conditions could 

be used to estimate the acreages of 

regeneration opportunities. Many 

stands that are moderately stocked with 

acceptable trees become more fully 

stocked as the trees grow and as 

natural regeneration becomes established (Baker 1989). We did not 

attempt to conduct a more complete 

Table I--Area of timberland reduced below a manageable stand using different 

stocking discounts, by broad management class, for 23 counties in South Carolina, 

1986-1990 

Broad 

management 

class 

Stocking reduced below 

manaqeable levels usinq: 

All Damaged Mimima 1 Average Maximum 

classes area discounta discountb discount" 

Pine plantation 

Thousand acres 

118.5 220.2 

Natural pine 1,773.8 1,252.9 255.5 332.9 436.1 

Oak-pine 832.4 545 , 4 67.8 105.5 135,1 

Upland hardwood 989.2 634.7 102.0 119.0 147.9 

Lowland hardwood 1,731.9 1,329.0 267.1 379.5 490.5 

ALL classes 6,536.0 4,508.7 810.9 1,157.1 1,539.3 

" Stocking reduction consists of Hugo mortality, Hugo salvage, and class 1 livetree damage. 

Stocking reduction consists of Hugo mortality, Hugo salvage, and classes 1 and 2 

live-tree damage. 

" Stocking reduction consists of Hugo mortality, Hugo salvage, and classes 1, 2, 

and 3 live-tree damage. 
evaluation of regeneration needs, 

Decisions about acceptable stocking 

are predicated upon many variables, 

among them site quality, forest type, 

management objectives, rotation age, 

and the mix of damages of various 

degrees and types. However, we do 

provide a detailed s ry of acreage 

by stand type that displays the preHugo and post-Hugo stocking categories 

(Appendix Table C.22). Hugo stocking 

reductions in this table are based 

upon the average discount option 

discussed above, 

An example of how one might use 

different combinations of pre- and 

post-Hugo stocking values to assess 

damage is presented in Table 11. 

Values in boldface type, corresponding 

to pre-Hugo stocking levels of 60 

percent or greater and post-Hugo 

stocking of less than 60 percent, are 

those presented in Table I under 

average discount, An alternative 

assessment of added regeneration 

opportunity created by Hugo damage is 

indicated by a s ary of acreage 

below and to the left of the stairstep 

line through the body of the table. 

Here, a sliding scale is used to 

define acceptable. The result 

depends, to a degree, on pre-Hugo 

stocking. For instance, stands with a 

pre-Hugo stocking of 50-59 percent are 

not included in a regeneration 

scenario unless stocking has been 

reduced below 40 percent. Stands 85-99 

percent stocked would have to be 

reduced below 50 percent post-Hugo 

stocking. This assessment of added 

regeneration needs yields an estimate 

of 1.3 million acres, about the same as 

the estimate using the traditional 60- 

percent threshold. Appendix Table C.22 

contains similar data by stand type so 

readers can conduct their own evaluations. 

Regardless of the process and stocking 

guidelines used to estimate regeneration needs, it is obvious that Hugo 

added greatly to the already large 

backlog of acreage that lacked a 

manageable stand of trees. The 

additional area easily exceeds 1 

million acres. In addition, the 

estimates presented here are low 

because small trees in natural stands 

(< 3.0 inches d.b,h,) were not reinventoried and losses of them were not 

discounted. 

The extent to which natural regeneration will be able to rehabilitate 

damaged stands cannot be assessed using 

the Hugo inventory data. Plots were 

visited too soon after the storm for 

natural regeneration to have become 

established. These assessments will be 

made in a few years during the next 

full-scale inventory of South Carolina, 

scheduled for completion by 1993. 

Table 11--Area of timberland by pre- and post-Hugo stocking percentage for 

manageable stand trees, for 23 counties in South Carolina, 1986-1990a 

Pre-Hugo 

stocking All Post-Huqo stockinq (percent) 

(percent) classes 0-14 15-29 30-39 40-49 50-59 60-69 70-84 85-99 100+ 

Thousand acres 

0-14 1,294.3 1,294.3 

loo+ 1,166.3 89.5 45.4 41.2 26.2 44.9 144.4 104.1 126.7 643.9 

All 

classes 6,536.0 1,872.5 712.1 587.9 560.6 546.1 529.7 633.4 449.8 643.9 

" Based on trees 3.0 inches d.b,h. and larger in natural stands; all stems, 

including new planted stems, in plantations, 
Future Timber Supplies Altered 

We attempted to roughly assess the 

effects of the observed damage to 

stands on the region's future timber 

supplies. Our analysis did not 

include a sophisticated projection 

model. Rather, we assigned each 

sample stand to a damage class in a 

process similar to that used for the 

regeneration analysis. Three damage 

classes were assigned: no damage, 

light damage, and moderate/heavy 

damage. Stands that were harvested 

since 1986, but before the hurricane 

struck, were identified and portrayed 

as a separate category, Magnitude of 

stocking reduction was the primary 

consideration in placing each sample 

plot in one of the hurricane damage 

categories. The "no damage" category 

was assigned based upon field crew 

observation on the ground; this 

classification was cross-checked 

against tree tally to verify that no 

hurricane-damaged trees were present. 

The remaining stands were assigned to 

one of two damage groups based upon 

the severity of the stocking reduction 

attributed to hurricane damage. 

Liqht damaqe: 

1. Sample plots where pre-Hugo 

stockinq was already below 30 percent 

2. Sample plots where post-Hugo 

stocking remained above 75 percent of 

full stocking. 

3. Sample plot with stocking standards between 1 and 2, where less than 

one-half of pre-Hugo stocking was lost 

and stocking reduction as a percentage 

of full stocking did not exceed 30 

percentage points. 

Moderate to heavy damaqe: 

All damaged stands not assigned 

to "light" damage were classified as 

moderate/heavy damage. 

The distribution of damaged acreage is 

depicted in age profiles (Figure 13). 

Classifications of stand age and type 

are based on 1986 conditions in most 

cases. Changes in these classifications that would be expected with 

timber cutting, natural disturbances, 

or stand development were not 

accounted for. Stands harvested 

between 1986 and 1990 are identified 

as a separate category in the profiles 

so that the timber supply impacts of 

recently harvested stands can be 

evaluated concurrently with the 

impacts of hurricane damage. When 

Legend 

Undameged !%%$ Light 

Moderate to heavy Hame~ted (1986-90) 

(a) Pine c.iantafions 

ciass (yea-) 

38+ 6 33-37 

28-52 1 

I 23-27 

18-22 

13-i7 

8-12 

r -7 

0 

0 

Thousand acres 

jb) Natural pine 

f Thousand acres 

(c) Oak-pine/hardwood 

Age class 

81 + 

71-80 

Thousand acres 

Figure 13--Stand-age profiles for pine 

plantations, natural pine stands, and 

oak-pine/hardwood stands, by degree of 

hurricane damage. 

planting occurred on a sample plot 

between 1986 and 1990, the sample was 

assigned to pine plantation, age class 

0. Pine plantations were assigned to a 

5-year class, whereas natural stands 

were assigned to 10-year age classes. 

More than 261,000 acres out of 1.2 

million acres of pine plantations in 

the 23 counties were classed as 

moderately to heavily damaged (Figure 

13a). On these areas, Hugo reduced 

manageable stand stocking by 70 percent 

based on the average stocking-reduction 

criteria discussed previously. These 
stands were left with an average 

stocking of healthy and class 3 

damaged trees of only 28 percent of 

full stocking. Almost one-third of 

the nonharvested plantations age 15 

and above were classed as moderately 

to heavily dmaged, 

Another 475,000 acres (39 percent of 

all plantations) were classed as 

lightly damaged, In these stands, 

Hugo reduced pre-Hugo stocking by an 

average of 16 percent, However, 

stocking of healthy and class 3 

damaged trees in these stands averaged 

81 percent of full stocking--an adequate amount for long-term development 

of acceptable trees. Pine plantations 

established since 1986 (age class 0) 

and those in age classes 5 and 10 

account for almost four-fifths of the 

undamaged pine plantations. 

About 400,000 acres of stands classed 

as natural pine in 1986, and not 

subsequently harvested, were moderately to heavily damaged (Figure 13b). 

This acreage represents 25 percent of 

all nonharvested natural pine stands. 

The hurricane reduced manageable stand 

stocking for this group by-77 percent, 

leaving an average of only one-fifth 

of full stocking. As with plantations, losses were concentrated in age 

classes that have the highest volumes. 

Almost one-third of all unharvested, 

natural pine stands greater than 20 

years old were moderately to heavily 

damaged. In contrast, only 7 percent 

of natural pine stands less than 20 

years old were so classified. 

Light damage was inflicted on 743,000 

acres of nonharvested natural pine 

stands. These stands are found across 

the range of age classes but make up 

more than one-half of each of the 

three youngest age classes for natural 

pine. Natural pine stands in this 

category lost 11 percent of their preHugo stocking to the hurricane. 

About 17 percent of the stands in oakpine and hardwood forest types in 

1986, and not subsequently harvested, 

were moderately to heavily damaged 

(Figure 13c). Altogether, some 

582,000 acres of hardwood-dominated 

timberland were so classified, These 

severely damaged stands were concentrated in the 41-50 and older age 

classes. Almost 29 percent of hardwood and oak-pine stands past age 40 

were moderately to heavily damaged, 

Only 7 percent of stands less than 40 

years old were placed in that 

category. In moderately to heavily 

damaged hardwood and oak-pine stands, 

Hugo reduced stocking by an average 66 

percent. The residual stands (comprised of healthy and class 3 damaged 

trees) averaged only 26 percent of full 

stocking. 

More than one-half (1.8 million acres) 

of oak-pine and hardwood stands were 

lightly damaged. The hurricane reduced 

manageable stand stocking there by 15 

percent. The remaining 1.0 million 

acres did not sustain any hurricane 

damage. Oak-pine and hardwood forests 

that were not damaged or were lightly 

damaged were distributed across all age 

classes, but they were more highly 

concentrated in the younger age 

classes. 

Geographically, forest stands with 

moderate to heavy damage were distributed in a similar fashion to the 

volume-loss distributions shown earlier 

(Figure 14). Moderately to heavily 

damaged stands are concentrated near 

the coast and to the northeast side of 

the hurricane's path. 

Figure 14--A generalized distribution 

of timberland in South Carolina damaged 

by Hurricane Hugo, by degree of damage, 

From a timber supply standpoint, 

Hurricane Hugo had an immediate impact 

by damaging old, high-volume stands 

more severely than young, low-volume 

stands. The age structure of the 

forests was instantly skewed toward 

more young stands. The hurricane also 

reduced the stocking of residual trees 

on relatively large areas to a level 

that requires the establishment of a 

new, vigorous stand to restore longterm productivity. Regenerating new 

stands over large areas through planting and natural means will further tilt 
the age structure toward young stands. 

Concentrations of very young stands 

bode we11 for growth and inven-tory 

changes 15 to 20 years in the future. 

In the interim, however, timber 

supplies have been severely compromised in the 23 counties. The 

impact is, and will be, especially 

severe for both softwood and hardwood 

solid-wood-product industries, Much 

depends upon the degree to which (1) 

trees can respond to the varying 

degrees of damage without losing 

substantial value f o r t h e i r best use; 

and (2) damaged timber can be utilized 

and make a viable contribution to 

timber supplies in the short term. 

Based on levels of damage depicted in 

the age profiles, potential timber 

supplies for the next 10 to 20 years 

have been reduced by 20-30 percent in 

the 23 counties, Manufacturers that 

depend on medium- to large-diameter 

trees will be impacted for a considerably longer period of time. Supply reductions could easily exceed 30 

percent for manufacturers that cannot 

utilize damaged timber. 

LITERALTURE: CITED 

Baker, James B. 1989. Recovery and 

development of understocked loblollyshortleaf pine stands. Southern 

Journal of Applied Forestry 13(3):132- 

139. 

Barry, Patrick J.; Anderson, Robert 

L.; Swain, Kenneth M. 1982. How to 

evaluate and manage storm-damaged 

forest areas. For. Rep. SA-FR 20. 

Atlanta, GA: U,S. Department of 

Agriculture, Forest Service, Forest 

Pest Management. 15 pp. 

Brewer, Conrad W,; Linnartz, Norwin El 

1973. The recovery of hurricane-bent 

loblolly pine. LSU For. Note 104. 

Baton Rouge, LA: Louisiana State 

University. 2 pp. 

Hook, Donal D.; Buford, Marilyn A.; 

Williams, Thomas M. 1991. Impact of 

Hurricane Hugo on the South Carolina 

coastal plain forest. Journal of 

Coastal Research, Spec. Issue 8:291- 

300. 

Newton, Carlton M.; Bower, Steven T. 

1990. Spatial analysis of forest 

inventory data, In: LaBau, Vernon 3.; 

Cunia, Tiberius, tech. eds. State-ofthe-art methodology of forest inventory: a symposium proceedings; 1989 

July 30-August 5; Syracuse, NY, Gen. 

Tech. Rep. PNW-GTR-263. Portland, OR: 

U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research 

Station: 369-378. 

Putz, Frances E.; Sharitz, Rebecca R. 

1991. Hurricane damage to old-growth 

forest in Congaree Swamp National 

Monument, South Carolina, U.S.A. 

Canadian Journal of Forest Research 

21~1765-1770. 

Tansey, John B.; Hutchins, Cecil C., 

Jr. 1988. South Carolina's forests. 

Resour. Bull. SE-103. Asheville, NC: 

U.S. Department of Agriculture, Forest 

Service, Southeastern Forest Experiment Station. 96 pp. 

U.S. Department of Agriculture, Forest 

Service. 1991. Field instructions for 

the Southeast. Asheville, NC: U.S. 

Department of Agriculture, Forest 

Service, Southeastern Forest Experiment 

Station. 

APPENDIX A: DATA-COLLECTION 

PROCEDURES 

In the 23 damaged counties, field crews 

relocated 2,530 permanent sample plots 

that were established in timberland in 

previous inventories. At each sample, 

crews recorded information about the 

condition of the stand, noting any 

treatments or disturbances that had 

occurred since the previous inventory 

in 1986. In addition, each stand was 

visually assessed for evidence of 

hurricane damage of any severity. Land 

use changes, windthrow orientation, and 

a description of the potential for 

natural pine regeneration were also 

recorded, 

In natural stands, all trees 3.0 inches 

d.b.h. and larger at the time of the 

1986 inventory were relocated. These 

trees were determined to be either 

alive, timber removals, or mortality. 

Live trees were evaluated for several 
storm-related damages. If a tree had 

died since the 1986 inventory, its 

death was attributed to the hurricane 

or to other natural causes, Likewise, 

trees removed from timberland by human 

activity were separated into regular 

removals and hurricane-related salvage 

operations, 

In planted stands, all trees 1.0 inch 

d,b+h+ and larger in 1986 were 

accounted for and evaluated in the 

same manner as above, In addition, 

pine trees that had grown from less 

than 1.0 inch d*b.h, to 1.0 inch or 

larger and all pine seedlings that 

were considered part of a manageable 

stand were tallied on 1/300-acre fixed 

plots at each of the five sample point 

centers, These "new" pine tally trees 

were also assessed for hurricane 

damage. 

Stand Condition Variables 

The following items were recorded for 

each sample: 

Stand oriqin, This code identified 

stands that had evidence of planting 

or seeding. 

. This code specified 

whether or not hurricane damage was 

evident in the sample stand. It did 

not indicate the severity of the 

damage. 

Past treatment. Up to three past 

treatments were coded by using 

standard FIA procedures, Only 

treatments that occurred between the 

1986 survey and the hurricane survey 

were recorded, 

Past disturbance* Any significant 

natural or human-caused disturbance 

such as disease, insects, or prescribed fire that occurred after the 

1986 survey was identified (not 

including hurricane damage). 

Treatment opportunity. At each sample 

location, field crews determined what 

treatments, if any, were needed to 

improve existing conditions in the 

stand. Possible recommendations 

included salvage, harvest, thinning, 

other stand improvement cuttings, 

stand conversion, regeneration, and no 

treatment, 

Potential natural pine reqeneration. 

This item was coded to describe the 

potential of hurricane-damaged stands 

to regenerate naturally with pine. 

The coding basically described three 

situations: stands that had adequate 

existing regeneration, stands with an 

adequate seed source (minimum basal 

area of 10 ft2/acre), or stands that 

did not have an adequate seed source. 

Nonforest plot (Optional Item 1). This 

item identified those samples that were 

cleared to a nonforest land use since 

1986. 

Throw orientation (Optional Item 22. 

Field crews, using standard FIA codes 

for aspect description, coded the 

predominant orientation of down or 

leaning trees on the sample acre. 

Tree Variables 

The following variables were recorded 

for individual trees on each plot: 

Tree history. Each tree tallied was 

assigned to one of six categories: (1) 

pine ingrowth, tallied only in plantations; (2) live tree with damage; (3) 

mortality caused by the hurricane; (4) 

mortality not caused by the hurricane; 

(5) tree removed from timberland, not 

associated with a salvage cutting 

operation; and (6) tree removed as a 

result of a salvage cutting or cleanup 

operation. Live trees without damage 

were not entered on the field forms; 

information for these trees was 

extracted from computer files for the 

1986 inventory. 

Species. A three-digit standard FIA 

species code was assigned to each tree 

tallied, 

Old d.b.h. The d.b.h. assigned in the 

1986 survey was transferred to the 

tally sheet used in the Hugo inventory. 

Tree class. A tree class code was 

assigned to each live tree tallied 

using FIA merchantability standards. 

Tree class was not changed from that 

coded in the 1986 survey unless it 

changed as a result of hurricaneinflicted damage. 

Cubic-volume loss. An estimate of the 

percentage of the tree's merchantable 

volume missing because of hurricane 

damage. 

Percentaqe of crown missinq. An estimate of the percentage of live-tree 

crown lost because of hurricane-related 

damage. The crown ratio code noted in 

the 1986 survey was used as a base for 

making this determination. 
Terminal leader missinq. The absence 

of the tree's terminal leader was 

recorded if the breakage was caused by 

the storm. 

Bole condition. Any damage to the 

bole of the tree was coded if the 

damage was caused by the hurricane. 

On a priority basis, injuries were 

coded as: (0) no damage, (1) split or 

twisted bole, (2) debris driven into 

tree, and (3) tree bole skinned 

through cambium, 

Tree lean. The angle of lean was 

recorded for each live tree. Lean was 

defined as the degree from which the 

first 12-foot section of the tree 

varied from the vertical axis. A code 

of "00" was recorded for a tree with 

no deviation from vertical axis 

associated with hurricane winds. A 

code of "90" was used to describe a 

live tree lying on the ground. 

Tree bend. Tree bend was coded in the 

same manner as tree lean except it was 

measured from the ground to the tip of 

the tree, 

Distance to breakaqe. If the bole of 

a tree was broken due to wind damage, 

the distance in feet from the 1-foot 

stump to the point of breakage was 

recorded. 

Root damaqe, The field crews looked 

for any evidence that the tree's root 

syst&had been damaged by the storm. 

Root injuries were recorded as: (1) 

no root damage, (2) roots exposed 

(root sprung), and (3) root damage 

below ground. 

Cut-mortality period. For each tree 

tallied that had either died or was 

cut before the hurricane (tree history 

6 or 8), a code was assigned to 

describe when the mortality or removal 

occurred. If the mortality or removal 

occurred within the past year, a 1 was 

recorded; 2 years ago, a 2 was 

recorded. 

Salt burn. Field crews assigned a 

code to indicate the presence of crown 

damage from airborne saltwater spray, 

The brown or red foliage associated 

with this damage was treated as 

missing crown. 

APPENDIX B: PROCEDURES AND 

CRITERIA FOR ASSIGNING TmES 

WITH HURRICANE DANAGE INTO 

GE: RISK CATEWRIES 

The 1990 inventory includes all trees 

that were alive at the time field crews 

visited each sample location. Several 

kinds of damage were tallied during the 

Hugo inventory and they can occur 

singly or in multiples in any combination. This appendix documents the 

procedures and criteria used to assign 

trees to categories of damage that 

reflect the tree's risk of dying or its 

present or potential value loss. 

Damage/Risk Class Definition 

The damagelrisk classes utilized are 

defined below. The terms "class 1," 

"class 2, ** and "class 3" are used 

instead of descriptive adjectives such 

as "severe," "moderate," or "light" so 

that users will review the definitions 

and criteria and attach descriptions 

that fit each person's assessment and 

use of the data. 

Class Description 

1 High-risk trees with a high 

probability of mortality in 

the near future. Damage is 

so severe that retention in 

the stand until the end of 

a rotation is not feasible. 

Moderate-risk trees with an 

elevated risk of dying 

soon. Death is not as 

"Imminent" as in class 1. 

Damage significantly 

degrades present or potential value, especially for 

high-value uses such as 

sawlogs and veneer logs. 

Tree growth is likely to be 

reduced for a number of 

years due to damages such 

as loss of crown or root 

damage. Retention in the 

stand is questionable and 

depends on tree and stand 

age, product objectives, 

ete. 

Low-risk trees with a high 

probability of survival. 

Damage elevates the risk of 

mortality, but reduced 

growth and value degrade 

will probably be minimal. 

Trees without obvious 

hurricane damage. 
Criteria and Evaluation 

Procedure 

Criteria for assigning trees to 

damagelrisk classes are provided for 

the following combinations of species, 

stand type, and tree size or age 

class: 

Softwood species in planted stands-- * Less than 5 years old 

* 5-20 years old 

21 years and older 

Softwood species in natural stands-- 

* Saplings (1.0-4.9 inches) * Poletimber (5.0-8.9 inches) 

Sawtimber (9.0 inches & 

larger ) 

Hardwood species in all stands-- * Saplings (1.0-4.9 inches) 

Poletimber (5.0-10.9 inches) 

* Sawtimber (11.0 inches & 

larger ) 

Class 4 (healthy) was assigned 

if no obvious hurricane damage was 

present, 

Class 1 was assigned if one (or 

more) qualifying damage was present. 

When listed, associated damages were 

treated as a required combination with 

the primary condition. 

If the criteria for assignment 

to class 1 were not met, then criteria 

for class 2 were evaluated in the same 

manner as described above. 

If no damages listed for class 

2 were present, then damage assignment 

defaulted to class 3. 

The damage variables coded for each 

tree and used in the damage/risk 

classification process are described in 

Appendix A. 

The following procedure was used to 

make the damage/risk class assignment 

for each tree. 

Table 8.1--Damage/risk class criteria for softwood species in pine plantations less 

than 5 years old 

Damage/risk 

class Primary condition Associated condition 

4 (healthy) No obvious damage 

Crown loss r 75% 

Root sprung 

Split/twisted bole 

Lean/bend r 60 degrees 

Salt burn present 

Volume loss (residual trees) 

r 30% 

Crown loss 40-74% 

Lean/bend 15-59 degrees 

Salt burn present 

Volume loss (residual trees) 

10-29% 

Terminal leader broken out 

Crown loss 1-39% 

Root damage below ground 

Skinned bole/other bole damage 

Lean/bend 1-14 degrees 

Volume loss (residual trees) 

1-98 

Crown loss r 30% 

Crown loss < 30% 
Table B.2--Damage/risk class criteria for softwood species in pine plantations 5-20 

years old 

llamagelrisk 

class Primary condition Associated condition 

4 (healthy) No obvious damage 

1 Crown loss r 75% 

Root sprung 

Split/twisted bole 

Leanlbend 2 45 degrees 

Salt burn present 

Volume loss 2 30% 

Crown loss r 50% 

Crown loss r 30% 

Crown loss 40-74% 

~ean/bend 15-44 degrees 

~plitftwisted bole Crown loss < 50% 

Skinned bole/other bole damage Crown loss r 25% 

Salt burn present Crown loss < 30% 

Terminal leader broken out 

Volume loss 5-29% 

Crown loss 1-39% 

Root damage below ground 

Skinned bolefother bole damage Crown loss < 25% 

Lean/bend 1-14 degrees 

Volume loss 1-48 

Table B.3--Damage/risk class criteria for softwood species in pine plantations 

greater than 20 years old 

Damage/risk 

class Primary condition Associated condition 

4 (healthy) No obvious damage 

Crown loss 2 75% 

Root sprung 

~plit/twisted bole 

Leanibend r 35 degrees 

Salt burn present 

Volume loss r 30% 

Crown loss r 50% 

Crown loss r 30% 

Crown loss 40-748 

Leanfbend 15-34 degrees 

splitftwisted bole Crown loss < 50% 

Skinned bolefother bole damage Crown loss r 25% 

Salt burn present Crown loss < 30% 

Volume loss 5-29% 

Crown loss 1-39% 

Root damage below ground 

Skinned bole/other bole damage Crown loss < 25% 

~eanfbend 1-14 degrees 

Terminal leader broken out 

Volume loss 1-4% 
Table B.4--Damage/risk class criteria for softwood saplings (1.0-4.9 inches d.b.h.) 

in natural stands 

class Primary condition Associated condition 

-- - 

4 (healthy) No obvious damage 

Crown loss r 75% 

Crown loss r 50% 

Root sprung 

Splitltwisted bole 

Salt burn present 

Leanfbend r 45 degrees 

Dominant/codominant trees 

Intemediatelsuppressed trees 

Crown loss 2 50% 

Crown loss r 30% 

Crown loss 40-74% Dominant/codominant trees 

Crown loss 25-49% Intermediate/suppressed trees 

splitltwisted bole Crown loss < 50% 

Skinned bole/other bole damage Crown loss 2 25% 

Lean/bend 15-44 degrees 

Salt burn present Crown loss < 30% 

Terminal leader broken out 

Crown loss 1-39% Dominant/codominant trees 

Crown loss 1-25% Intermediate/suppressed trees 

Root damage below ground 

Skinned bole/other bole damage Crown loss < 25% 

Leadbend 1-14 degrees 

Table B.5--Damage/risk class criteria for softwood poletimber (5.0-8.9 inches 

d.b.h.) in natural stands 

- - 

Damage/risk 

class Primary condition Associated condition 

-- 

4 (healthy) No obvious damage 

Crown loss r 75% 

Crown loss r 50% 

Root sprung 

Split/twisted bole 

Lean/bend r 45 degrees 

Salt burn present 

Volume loss r 30% 

Dominant/codominant trees 

Intermediate/suppressed trees 

Crown loss r 50% 

Crown loss r 30% 

Crown loss 40-74% Dominant/codominant trees 

Crown loss 25-49% Intermediateisuppressed trees 

Split/twisted bole Crown loss < 50% 

Skinned bolefother bole damage Crown loss L 258 

Leanlbend 15-44 degrees 

Salt burn present Crown loss < 30% 

Volume loss 5-29% 

Terminal leader broken out 

Crown loss 1-39% Dominanticodominant trees 

Crown loss 1-25% Intermediate/suppressed trees 

Root damage below ground 

Skinned bole/other bole damage Crown loss < 25% 

Lean/bend 1-14 degrees 

Volume loss 1-4% 
Table B.6--Damage/risk class criteria for softwood sawtimber (9.0 inches d.b.h. and 

larger) in natural stands 

Damagelrisk 

class Primary condition ~ssociated condition 

4 (healthy) No obvious damage 

Crown loss r 75% 

Crown loss r 50% 

Root sprung 

~plitltwisted bole 

~ean/bend 2 35 degrees 

Salt burn present 

Volume loss r 30% 

Dominant/eodominant trees 

Intermediatefsuppressed trees 

Crown loss r 50% 

Crown loss z 30% 

Crown loss 40-74% Dominantfcodominant trees 

Crown loss 25-49% Intermediate/suppressed trees 

Split/twisted bole Crown loss < 50% 

Skinned bole/other bole damage Crown loss r 25% 

Lean/bend 15-34 degrees 

Salt burn present Crown loss < 30% 

Volume loss 5-29% 

Crown loss 1-39% Dominant/codominant trees 

Crown loss 1-25% Intermediate/suppressed trees 

Root damage below ground 

Skinned bole/other bole damage Crown loss < 25% 

Lean/bend 1-14 degrees 

'Terminal leader broken out 

Volume loss 1-4% 

Table B.7--~amage/risk class criteria for hardwood saplings (1.0-4.9 inches d.b.h.) 

Damage/risk 

class Primary condition Associated condition 

4 (healthy) No obvious damage 

Crown loss 2 90% 

Root sprung 

Split/twisted bole 

Lean/bend 2 75 degrees 

Crown loss 45-89% 

~plit/twisted bole 

Skinned bole/other bole damage 

~ean/bend 15-74 degrees 

Leanfbend z 45 degrees 

Crown loss r 75% 

Crown loss < 758 

Crown loss 1-44% 

Root damage below ground 

Leadbend 1-14 degrees 

Terminal leader broken out 
Table B.8--Damage/risk class criteria for hardwood poletimber (5.0-10.9 inches 

d.b.h. ) 

Damagelrisk 

class Primary condition Associated condition 

4 (healthy) No obvious damage 

Crown loss r 90% 

Root sprung 

Split/twisted bole 

Leanibend r 60 degrees 

Volume loss r 30% 

Leanlbend 2 35 degrees 

Crown loss r 75%, or 

Bole breakage in lower 20 ft 

Crown loss 45-89% 

Root sprung Lean/bend < 35 degrees 

Split/twisted bole Crown loss < 75%, or 

Bole breakage above lower 

20 ft 

Skinned bole/other bole damage 

Leadbend 15-59 degrees 

Volume loss 5-29% 

Crown loss 1-44% 

Root damage below ground 

Leadbend 1-14 degrees 

Terminal leader broken out 

Volume loss 1-48 

Table B.9--Damage/risk class criteria for hardwood sawtimber (11.0 inches d.b.h. 

and larger) 

Damage/risk 

class Primary condition Associated condition 

-- - - - - - - 

4 (healthy) No obvious damage 

Crown loss > 90% 

Root sprung 

Splitltwisted bole 

Leadbend r 45 degrees 

Volume loss r 30% 

Crown loss 45-89% 

Root sprung 

Split/twisted bole 

Skinned bolelother bole damage 

Lean/bend 15-44 degrees 

Volume loss 5-29% 

Crown loss 1-44% 

Root damage below ground 

Lean/bend 1-14 degrees 

Terminal leader broken out 

Volume loss 1-4% 

Lean/bend r 25 degrees 

Crown loss r 758, or 

Bole breakage in lower 20 ft 

Leanlbend < 25 degrees 

Crown loss < 75%, or 

Bole breakage above Lower 
Appendix C: Detailed Tables 

Table C.1--Period change in volune of soft t of change, 

for 23 comties in South Carolina, 1986-1990 

1986 Gross Regular W ugo Net Regular Hugo Net 1990 

County inventory growth mortality mortality growth removals removals change inventory ' I 86.) (GG (Mr) (Mh 1 (NG) (TR,) URh) (NC) ('90) 

Berkeley 

Calhoun 

Charleston 

Chester 

Chesterfield 

Clarendon 

Darl ington 

Di 1 lon 

Dorchester 

Fairf ield 

Florence 

Georgetown 

Horry 

Kershaw 

Lancaster 

Lee 

Marion 

Mar 1 boro 

Orangeburg 

Richland 

Sunter 

Williamsburg 

York 

Total 

Thousand cubic feet 

212,364 -110,174 49,770 

17,782 4,453 23,709 

112,201 -72,893 34,329 

15,992 36,492 27,939 

13,737 32,632 21,357 

35,522 -16,025 17,752 

6,563 8,952 11,404 

2,051 14,698 11,044 

20,689 6,042 53,544 

867 78,515 68,972 

18,659 18,612 78,253 

29,100 19,429 69,430 

4,883 57,726 71,594 

13,941 26,083 65,993 

19,332 22,830 46,096 

15,963 -3,320 14,788 

4,930 18,557 35,361 

2,845 16,659 9,648 

14,837 16,399 68,385 

4,288 27,800 38,963 

31,405 -5,880 18,278 

28,513 17,806 40,336 

5.625 37,017 37,760 

632,089 252,410 914,705 

NG = GG - - Hh 

NC = NG - TRr - TRh 

190 = Ig6 + NC 

Pre-Hugo inventory = ra6 + GG - Mr - TRr 
grwirrg stock on tihrlenf, by cmty 4 c t of change, 

for 23 camties in South Carolina, 1986-1990 

1986 Gross Regular Hugo Net Regular Hugo Net 1990 

inventory growth mortality mortality growth removals removals change inventory 

('86) (GG) (Hr) (Mh) (NG) (TRr) (TRh) (NC) (I90) 

Berkeley 

Ca lhoun 

Charleston 

Chester 

Chesterfield 

C 1 arendon 

Darl ington 

Di 1 Lon 

Dorchester 

fairfield 

F lorence 

Georgetown 

Horry 

Kershaw 

Lancaster 

Lee 

Mar ion 

Harlboro 

Orangeburg 

Richland 

Sunter 

Williamsburg 

York 

Total 

Thousand cubic feet 

- -- - 

NG = CG - Mr - Hh 

NC = NC - TRr - TRh 

190 = Ig6 + NC 

Pre-Hugo inventory = Ig6 + GG - Hr - TRr 
Table C.3--Period change in voltme of soft sa*ti*f ti*riad, by c~ty and caqxmmt of change, 

for 23 comties in South Carolina, 1986-1990 

1986 Gross Regular Hugo Net Regular Hugo Net 1990 

County inventory growth mortality mortality growth removals removals change inventory 

( '86) (GG (Mr 1 (Mh 1 (NG) (TR,) (TRh) (NC) ('90) 

Berkeley 

Ca 1 houn 

Charleston 

Chester 

Chesterfield 

C 1 arendon 

Dart ington 

Di l ton 

Dorchester 

Fai rf ield 

Florence 

Georgetown 

Horry 

Kershaw 

Lancas ter 

Lee 

Mar ion 

Marl boro 

Orangeburg 

Richland 

Sumter 

Williarnsburg 

York 

Total 

Thousand board feet 

NG = GG - Mr - Mh 

NC = NG - TRr - TRh 

IgO = Ig6 + NC 

Pre-Hugo inventory = Ig6 + GG - Mr - TRr 
~&te C.4--Period ch savtilrt#r on tirtSrertd, by cmty and c 

for 23 camties in S-h Carolina, 15W-1990 

1986 Gross Regular Hugo Net Regular Hugo Net 1990 

County inventory growth mortality mortality growth removals removals change inventory 

('86) (GG? (Mr (Mh ) (NG) (TRr) (TRh) (NC) ( '90) 

Thousand board feet 

Berkeley 1,018,776 136,093 1,778 148,919 -14,604 62,807 17,616 -95,027 923,749 

Ca 1 houn 272,262 47,983 8,944 6,717 32,322 10,276 - - 22,046 294,308 

Charleston 580,532 98,285 8,504 135,829 -46,048 6,563 2,359 -54,970 525,562 

Chester 347,994 74,016 22,747 - - 51,269 87,830 - - -36,561 311,433 

Chesterfield 563,124 102,595 8,995 20,747 72,853 104,544 6,581 -38,272 524,852 

C larendon 731,638 111,183 5,805 80,820 24,558 124,594 24,318 -124,354 607,284 

Dar 1 ington 330,963 45,281 20,080 24,282 919 34,284 4,398 -37,763 293,200 

Di 1 lon 452,454 87,923 10,011 4,606 73,306 25,212 - - 48,094 500,548 

Dorchester 856,940 120,240 5,823 102,641 11,776 171,302 17,054 -176,580 680,360 

Fairf ield 395,366 97,931 11,014 7,508 79,409 67,804 - - 1 1,605 407,971 

Florence 833,389 144,036 16,968 18,621 108,447 101,370 11,406 -4,329 829,060 

Georgetown 766,458 122,049 3,606 52,253 66,190 41,442 - - 24,748 791,206 

Horry 1,388,656 230,958 37,015 17,706 1 76,237 105,446 2,234 68,557 1,457,213 

Kershaw 386,776 74,687 1,845 9,650 63,192 15,353 10,288 37,55 1 424,327 

Lancaster 316,751 60,101 2,613 11,512 45,976 59,701 5,808 -19,533 297,218 

Lee 287,548 40,512 11,089 97,252 -67,829 2,305 35,931 -106,065 181,483 

Mar i on 910,854 148,097 28,013 16,062 104,022 133,392 - - -29,370 881,484 

Mar lboro 520,285 108,559 26,789 4,693 77,077 35,886 - - 41,191 561,476 

Orangeburg 1,054,692 192,056 17,905 76,142 98,009 205,605 - - - 107,596 947,096 

Richland 667,731 121,999 3,913 - - 118,086 120,226 - - -2,140 665,591 

Sunter 832,963 106,070 6,869 73,646 25,555 129,359 1,275 -105,079 727,884 

Uilliamsburg 1,064,967 156,556 20,462 44,165 91,929 96,356 24,755 -29,182 1,035,785 

York 362.376 106,140 10.970 21.248 73.922 53,044 - - 20.878 383,254 

Total 14,944,495 2,533,350 291,758 975,019 1,266,573 1,794,701 164,023 -692,151 14,252,344 

NG = GG - Mr - Mh 

NC NG - TRr - TRh 

= + NC 

Pre-Hugo inventory = Ig6 + GO - Mr - TRr 
Table c.5--Distribution of 1990 iwmtofy of gr~ing stock, by cwtty, species group, and 

for 23 emties in South Carotina 

softwoods Hardwoods 

Percentage of inventory in-- Percentage of inventory in-- County 1990 1990 

Inventory Healthy Class 3 Class 2 Class I Inventory Healthy Class 3 Class 2 Class 1 

trees trees trees trees trees trees trees trees 

Thousand Thousand 

cubic feet Percent cubic feet Percent 

Berkeley 303,074 30 28 24 18 300,743 33 18 2 1 28 

Ca 1 houn 91,384 97 1 2 93,724 96 - - - - 1 3 

Charleston 163,631 64 9 13 14 187,601 53 17 17 13 

- - Chester 220,557 98 - - 2 133,505 98 1 1 - - 

Chesterfield 207,172 69 28 2 1 177,759 43 39 7 11 

C Larendon 

Darl ington 

Di l ion 

Dorchester 

Fairf ield 

Florence 

Georgetown 

Horry 

Kershaw 

Lancaster 

Lee 

Marion 

Mar l boro 

Orangeburg 

Richland 

Sumter 

Uiliiamsburg 

York 

Total 
 able C-&--Distribution of 1990 inventory of sautimber, by courty, species grq, and 

for 23 cmties in South Carolina 

Softwoods Hardwoods 

Percentage of inventory in-- Percentage of inventory in-- County 1990 1990 

Inventory Healthy Class 3 Class 2 Class 1 Inventory Healthy Class 3 Class 2 Class 1 

trees trees trees trees trees trees trees trees 

Thousand 

board feet Percent 

Thousand 

board feet Percent 

Ber ke 1 ey 955,235 32 29 20 19 923,749 31 16 22 31 

Calhoun 331,540 98 1 - - 1 294,308 94 - - 1 5 

Charleston 721,511 63 9 12 16 525,562 46 21 18 15 

Chester 751,047 98 - - - - 2 311,433 97 2 1 - - Chesterfield 704,706 69 27 2 2 524,852 43 39 4 14 

C Larendon 316,406 35 25 14 26 607,284 25 8 11 56 

Darlington 417,315 97 - - 2 1 293,200 72 2 12 14 

Di 1 lon 454,855 It30 - - - - - - 500,548 90 - - 1 9 

Dorchester 739,958 72 9 11 8 680,360 58 10 15 17 

Fairf ield 976,943 100 - - - - - - 407,971 100 - - - - - - 

Florence 756,689 53 30 9 8 829,060 43 29 5 23 

Georgetown 871,509 60 9 21 10 791,206 59 14 10 17 

Horry 1,664,517 60 25 14 I 1,457,213 64 23 7 6 

Kershaw 382,141 79 11 5 5 424,327 51 13 6 30 

Lancaster 237,251 78 1 1 20 297,218 76 1 5 18 

Lee 217,426 77 6 10 7 181,483 54 11 15 2 0 

Marion 640,947 94 2 2 2 881,484 87 2 3 8 

Mar 1 boro 353,404 94 3 2 1 561,476 94 4 - - 2 

Orangeburg 601,142 88 9 2 1 947,096 91 3 4 2 

Richland 551,740 90 8 1 1 665,591 80 14 1 5 

Sumter 300,913 47 19 15 19 727,884 49 8 15 28 

Ui 11 iamsburg 849,n9 39 42 9 10 1,035,785 34 27 12 2 7 

York 484.481 86 10 1 3 383.254 88 - - 4 8 

Total 14,278,455 72 14 8 6 14,252,344 63 13 8 16 
Table C.7--Period change in volune of soft graing stock on tiarberlanf, by c t of change and 

owrership class, for 23 coulties in Swth Carolina, 1986-1990 

1 nventory i tem 

A1 l National Other Forest Farmer Miscellaneous 

ownerships forest pub1 ic industry private 

-- 

Thousand cubic feet 

1986 Inventory (IB6) 

Gross growth (GG) 

Regular mortality (M,) 

Hugo mortality (Mh) 

Net growth (NG) 

Regular removals (TR,) 

Hugo removals (TRh) 

Net change (NC) 

1990 Inventory (I90) 

NG = GG - Mr - Mh 

NC = NG - TRr - TRh 

190 = Is6 + NC 

Pre-Hugo inventory = 186 + GG 

Table C.8--Period change in volune of har&ood growing stock on timberland, by coqxment of change 

and ownership class, for 23 coulties in Swth Carolina, 1986-1990 

Inventory item A1 1 National Other Forest Farmer Miscellaneous 

ownerships forest public industry private 

1986 Inventory (I ) 86 

Gross growth (GG) 

Regular mortality (Mr) 

Hugo mortality (Mh) 

Net growth (NG) 

Regular removals (TRr) 

Hugo removals (TRh) 

Net change (NC) 

1990 Inventory (I ) 90 

Thousand cubic feet 

NG = GG - Mr - Mh 

NC NG - TRr - TRh 

190 = Ia6 + NC 

Pre-Hugo inventory = IB6 + GG - Mr - TRr 
Table C.9--Period change in voltme of soft sawtimber on tirrrberlend, by c t of change and 

ownership class, for 23 cwnties in South Carolina, 1986-1990 

Inventory item A1 1 National Other Forest Farmer Miscellaneous 

ownerships forest public industry private 

1986 Inventory (Ig6) 

Gross growth (GG) 

Regular mortality (Mr) 

Hugo mortality (Mh) 

Net growth (NG) 

Regular removals (TRr) 

Hugo removals (TRh) 

Net change (NC) 

1990 Inventory (Ig0) 

Thousand board feet 

1,623,832 1,069,257 3,492,092 

266,259 226,353 1,013,555 

23,437 15,112 44,469 

918,303 161,893 333,279 

-675,481 49,348 635,807 

132,220 136,555 1,150,044 

60,708 86,005 127,903 

-868,409 -173,212 -642,140 - 

755,423 896,045 2,849,952 

NG = GG - Mr - Mh 

NC = NG - TRr - TRh 

190 = Ig6 + NC 

Pre-Hugo inventory = Ig6 + GG - Mr - TRr 

Table C.10--Period change in volune of hardmod sawtimber on timberland, by conponent of change and 

ownership class, for 23 cwnties in Swth Carolina, 1986-1990 

Inventory item A1 1 National Other Forest Farmer Miscellaneous 

ownerships forest pub1 ic industry private 

1986 Inventory (Ig6) 

Gross growth (GG) 

Regular mortality (M ) 

r 

Hugo mortality (Mh) 

Net growth (NG) 

Regular removals (TRr) 

Hugo removals (TRh) 

Net change (NG) 

1990 Inventory 

Thousand board feet 

179,228 3,541,280 4,258,998 

28,403 572,192 785,093 

- - 70,386 98,878 

18,178 168,079 262,298 

10,225 333,727 423,917 

12,030 553,137 399,157 

- - 4,850 81,951 

-1,805 -224,260 -57,191 

177,423 3,317,020 4,201,807 

Pre-Hugo inventory = Ig6 + GG - Hr - TRr 
iabte C.11--Distributim of 1990 inventory of growing stock, by ownership class, species group, and 

for 23 ccxnties in South Carolina 

Softwoods Hardwoods 

Percentage of inventory in-- Percentage of inventory in-- 

Ownership class 1990 1990 

Inventory Healthy Class 3 Class 2 Class 1 Inventory Healthy Class 3 Class 2 Class 1 

trees trees trees trees trees trees trees trees 

Thousand 

cubic feet Percent 

Thousand 

cubic feet Percent 

National forest 196,607 55 12 22 1 I 149,212 40 21 20 19 

Other publ ic 254,612 70 16 8 6 87,477 64 11 11 14 

Forest industry 907,363 64 19 11 6 1,010,020 70 12 7 11 

Farmer 957,789 75 13 7 5 1,478,842 68 12 7 13 

Miscellaneousprivate 1,460,727 74 11 8 7 2,081,476 70 11 7 12 

A 1 1 ownerships 3,777,098 71 14 9 6 4,807,027 68 12 8 12 

Table C.12--Distribution of 1990 inventory of sautimber, by ownership class, species group, and damage class, 

for 23 counties in South Carolina 

Softwoods Hardwoods 

Ownership class Percentage of inventory in-- Percentage of inventory in-- 

1990 1990 

Inventory Healthy Class 3 Class 2 Class 1 Inventory Healthy Class 3 Class 2 Class 1 

trees trees trees trees trees trees trees trees 

Thousand 

board feet 

National forest 755,423 58 

Other pub1 i c 896,045 70 

Forest industry 2,849,952 66 

Farmer 4,017,523 75 

Miscel Laneous private 5,759,512 73 

A 1 L ownerships 14,278,455 72 

Thousand 

Percent board feet Percent 
Table ~,13--Change in wlur? of soft growing stack on tirrberlanj, by diameter class, for 23 camties in 

South Carolina, 1986-1990 

Diameter class 1990 inventory in-- 1 986 Net 

( inches at breast 1990 

change Inventory Healthy Class 3 Class 2 Class 1 height) trees trees trees trees 

5.0-6.9 

7.0-8.9 

9.0-10.9 

11 .O-12.9 

13.0-14.9 

15.0-16.9 

17.0-18.9 

19.0-20.9 

21.0 and larger 

Att classes 

Thousand cubic feet Percent 

429,755 -65,092 364,663 68 13 13 6 

636,017 - 53,320 582,697 71 12 12 5 

750,921 -138,543 612,378 73 14 8 5 

768,374 -227,552 540,822 72 14 6 8 

670,699 -151,324 519,375 72 14 7 7 

546,665 -154,674 391,991 72 15 7 6 

390,308 - 99,269 291,039 69 15 9 7 

255,152 -63,967 191,185 74 13 7 6 

367.215 -84,267 282.948 66 17 11 6 

4,815,106 -1,038,008 3,777,098 71 14 9 6 

Table C-14--Change in volune of harchrood growing stock on timberland, by diameter class, for 23 counties in 

South Carolina, 1986-1990 

Diameter class 1990 inventory in-- 

(inches at breast 1986 Net 1990 

height) Inventory change Inventory Healthy Class3 Class 2 Class 1 

trees trees trees trees 

5.0-6.9 

7.0-8.9 

9.0-10.9 

11 -0-12.9 

13.0-14.9 

15.0-16.9 

17.0-18.9 

19.0-20.9 

21.0 and larger 

AlC classes 

Thousand cubic feet Percent 

473,665 -26,509 447,156 78 8 7 7 

604,044 8,979 613,023 75 11 8 6 

659,619 -9,128 650,491 72 11 8 9 

71 1,364 - 66,034 645,330 71 10 7 12 

642,148 -6,502 635,646 73 I I 6 10 

544,058 -32,429 511,629 64 14 7 15 

432,505 -27,642 404,863 62 14 7 I7 

292,547 -10,185 282,362 60 13 9 18 

642.313 -25,786 616,527 54 14 11 2 1 

5,002,263 -195,236 4,807,027 68 12 8 12 
Table 6.15--Change in volune of softuood sawtimber on timberland, by diameter class, for 23 cowties in 

sauth Carolina, 1986-1990 

1990 inventory in-- 

Diameter ciass 1986 Net (inches at breast inventory 

1990 

change Inventory Heal thy Class 3 CLass 2 Class 1 

height) trees trees trees trees 

Thousand board feet Percent 

9.0-10.9 2,733,479 -497,748 2,235,731 74 13 8 5 

11 -0-12.9 3,480,059 -1,024,486 2,455,573 72 14 6 8 

13.0-1.4.9 3,446,844 -781,009 2,665,835 72 14 7 7 

15.0-16.9 3,052,743 -861,508 2,191,235 72 15 7 6 

17.0-18.9 2,318,662 -597,629 1,721,033 69 15 9 7 

19.0-20.9 1,576,250 -401,458 1,174,792 74 13 7 6 

21.0 and larger 

All classes 18,009,272 -4,=0,817 14,278,455 72 14 8 6 

Table C-36--Change in volutle of harduod sawtihr on ti*rland, try dit~leter class, for 3 cornti= in 

South Carolim, 1986-1990 

Diameter class 1990 inventory in-- 

1986 ( inches at breast Net 1990 

height) change l nventory Healthy Class 3 Class 2 Class 1 

trees trees trees trees 

Thousand board feet 

11.0-12.9 2,453,516 -214,030 2,239,486 70 

13,O-14-9 2,603,726 -11,132 2,592,594 72 

15.0-16.9 2,478,661 - 138,623 2,340,038 64 

17.0-18.9 2,124,710 -131,826 1 ,992,884 62 

19-0-20.9 1,536,842 -56,647 1,480,195 5 9 

21.0 and larger 3,747,040 -139,893 3,607,147 5 3 

Alt classes 14,944,495 -692,151 14,252,344 63 

Percent 
graving stock on ti+rld, ltty spies, for 23 coutties in 

South Carolina, 1986-1990 

Species 

1990 inventory in-- 

1986 Net 1990 

Inventory change Inventory Heal thy Class 3 Class2 Class1 

trees trees trees trees 

Longleaf pine 

Slash pine 

Short leaf pine 

Loblol ly pine 

Pond pine 

Virginia pine 

Pitch pine 

Table Mountain pine 

Spruce pine 

Sand pine 

Eastern white pine 

Eastern hemlock 

Spruce and fir 

Baldcypress 

Pondcypress 

Cedars 

ALL species 

Thousand cubic feet 

451,329 -148,690 302,639 80 8 

195,053 -49,239 145,814 68 19 

244,145 -39,025 205,120 85 7 

3,173,218 -684,412 2,488,806 69 15 

277,260 -97,505 179,755 5 9 15 

54,852 -2,940 51,912 79 4 

- - - - - - - - - - 

Percent 
Table C.18--Change in volune of harduood growing stock on tiraberland, by species, for 23 comties in 

South Carolina, 1986-1990 

- 

1990 inventory in-- 

1986 Net 1990 Spec i es Inventory change Inventory Healthy Class 3 Class 2 Class 1 

trees trees trees trees 

Select white oaks 

Se 1 ec t red oaks 

Chestnut oak 

Other white oaks 

Other red oaks 

Hickory 

Ye1 low birch 

Hard maple 

Soft mapl e 

Beech 

Sweetgum 

Tupelo and blackgum 

Ash 

Cottonwood 

Basswood 

Ye1 low-poplar 

Bay and magnolia 

Black cherry 

Black walnut 

Sycamore 

Black locust 

E lm 

Other eastern 

hardwoods 

Thousand cubic feet 

272,297 -4,575 267,722 

92,266 -9,072 83,194 

- - - - - - 

159,951 -8,096 151,855 

997,617 -68,770 928,847 

162,474 -12,027 150,447 

- - - - - - 

1,524 253 1 ,777 

379,354 8,598 387,952 

7,159 -81 7,078 

1,094,447 -44,362 1,050,085 

1,152,982 -19,399 1,133,583 

168,598 -11,422 157,176 

34,812 -2,114 32,698 

275 58 333 

246,737 -1 1,649 235,088 

16,306 1,091 17,397 

9,649 1 94 9,843 

3,179 290 3,469 

26,500 -6,049 20,451 

- - - - - - 

All species 5,002,263 -195,236 4,807,027 

Percent 
Tale c.19--Change in volume of softwood sawtinher on tieberland, by species, for 23 emties in 

south Carolina, 1986-199Q 

Spec i es 

1990 inventory in-- 

1986 Net 1990 

I nventory change Inventory Heal thy Class3 Class2 Class1 

trees trees trees trees 

Thousand board feet Percent 

Longleaf pine 1,971,710 -683,707 1,288,003 80 9 4 7 

Stash pine 476,183 -133,231 342,952 74 15 3 8 

Shortleaf pine 644,400 -135,583 508,817 84 7 1 8 

Loblol ly pine 12,939,294 -3,327,718 9,611,576 69 16 9 6 

Pond pine 1,095,182 -399,830 695,352 5 9 13 15 13 

Virginia pine 142,686 2,082 144,768 80 2 2 16 

Pitch pine - - - - - - - - - - - - - - 

Table Mountain pine - - - - - - - - - - - - - - 

Spruce pine 85,748 -15,586 70,162 69 18 - - 13 

Sand pine - - - - - - - - - - - - - - 

Eastern white pine - - - - - - - - - - - - - - 

Eastern hemlock - - - - - - - - - - - - - - 

Spruce and fir - - - - - - - - - - - - - - 

Baldcypress 1 ,342,624 -33,448 1,309,176 76 14 5 5 

Pondcypress 256,991 1,363 258,354 76 14 7 3 

Cedars 54,454 -5,159 49,295 84 6 - - 10 

At1 species 19,009,272 -4,730,817 14,278,455 72 14 8 6 
Table C.20--Change in volune of harducmd sautinrber on tint>erland, by species, for 23 cmties in 

South Carolina, 1986-1990 

Species 

1990 inventory in-- 

1986 Net 1990 

Inventory change Inventory Heal thy CLass3 Class2 Class1 

trees trees trees trees 

Thousand board feet Percent 

Select white oaks 829,475 -32,877 796,598 64 12 5 

Select red oaks 349,767 -31,137 318,630 54 12 5 

Chestnut oak - - - - - - - - - - - - 

Other white oaks 505,941 -23,157 482,784 5 6 12 13 

Other red oaks 3,142,149 -306,073 2,836,076 49 13 10 

Hickory 504,622 -91,285 413,337 5 8 8 8 

Yellow birch - - - - - - - - - - - - 

Hard maple 1,981 497 2,478 100 - - - - 

Soft maple 824,432 - 18,253 806,179 45 14 16 

Beech 16,393 333 16,726 50 - - 24 

Sweet gum 3,067,063 -97,404 2,969,659 66 16 8 

Tupelo and blackgum 3,586,932 6,144 3,593,076 77 12 6 

Ash 471 ,183 -14,355 456,828 62 13 10 

Cottonwood 136,056 305 136,361 69 18 10 

Basswood - - - - - - - - - - - - 

Ye1 low-poplar 914,192 -35,830 878,362 57 14 8 

Bay and magnol i a 15,565 5 84 16,149 7 1 - - 10 

Black cherry 6,437 -1,445 4,992 100 - - - - 

Black walnut 5,699 1,707 7,406 64 36 - - 

Sycamore 114,364 - 28,433 85,931 75 - - 4 

Black locust - - - - - - - - - - - - 

Elm 202,674 -10,621 192,053 69 13 6 

Other eastern 

hardwoods 249.5 70 -10.851 238'71 9 73 6 5 

All species 14,944,495 -692,151 14,252,344 63 13 8 
Table C-21--Area of tihrland, by ownership class, hurricane ge status, and previwr; std 

type, for 23 counties in South Carolina 

Ownership class 

and 

damage status 

A1 l Previous stand type 

stand Pine Natura 1 Oak- Upland Lowland 

types plantation pine pine hardwood harciwood 

Pthl ic 

No damage 

Damaged 

- Acres 

Total 532,861 86,488 249,825 64,367 32.294 99,887 

Forest industry 

No damage 516,688 266,733 76,771 50,316 38,532 84,336 

Damaged 1,092,775 449,281 166,864 79,131 68,046 329,453 

Total 1 ,609,463 716,014 243,635 129,447 106,578 413.789 

Nonindustrial private 

No damage 

Damaged 

Total 

All ounerships 

No damage 2,027,238 461 ,947 520,869 287,047 354,458 402,917 

Damaged 4,508,737 746,719 1,252,907 545,362 634,731 1,329,018 

Total 6,535,975 1,208,666 1,773,776 832,409 989,189 1,731,935 
Table C.22--Area of tinberland, by broad management ctass and pre- and post-Hugo stocking percentage for mam~eable 

stand trees, for Z3 comties in Smth Carolina 

Broad management class I Post-Wugo stocking (percent) 

arid pte-Hugo stocking 

(~ercent 0-14 15-29 30-39 40-49 50-59 60-69 70-84 85-99 100+ 

Pine ptantatiorrs 

All classes 

- Acres 

50,543 50,543 

25,410 7,156 18,254 

15,305 -. - - 15,305 

51,701 14,180 - - 2,460 35,061 

54,082 9,807 12,947 7,607 2,336 21,385 

65,571 7,107 - - - - 5,042 12,995 40,427 

177,808 14,534 7,955 18,665 22,167 10,352 14,423 89,712 

170,663 10,536 9,751 - - 4,640 7,798 7,377 30,046 100,515 

597.583 30.W5 10,321 18.711 14.375 15.191 22.341 48.520 45,899 392.180 

1.208.666 143.908 59,228 62.748 83,621 67.721 84.568 168,278 146.414 392.180 

Natural pine 

All classes 

All classes 

Upland hardwood 

Atl classes 

Bottomland hardwood 

All classes 

All classes 

All classes 
mmICME HUGO: A SOlliTH CmOLINA UPDATE 

Allan P.C. Marsinko, Thomas J. Straka, 

and Jeffrey L. ~aumann' 

In September of 1989, Hurricane Hugo 

cut a wide swath of destruction from 

just north of Charleston, South 

Carolina, through Charlotte, North 

Carolina. This class 4 hurricane 

devastated more than one-third of 

South Carolina (Figure 1) as it took 

human lives, destroyed buildings, 

downed power lines, and damaged roads. 

The economic costs exceeded $5 

billion. 

Allan P.C. Marsinko and Thomas J. 

Straka are associate professors, 

Department of Forest Resources, 

Clexnson University, Lehotsky Hall, 

Clemson, South Carolina 29634-1003; 

and Jeffery L. Baumann is senior staff 

forester, South Carolina Forestry 

Comission, Columbia. 

m Severe 

III Heavy 

B@&! Moderate 

Figure 1--Path of Hurricane Huga 

through South Carolina. 
Although many of the events of 

er 21 and 22 were widely 

zed, the effect on forestland 

was less well known, The hurricane 

ged more than $1 billion of timber 

and destroyed valuable wildlife habitat, The Francis Marion National 

Forest, which contained abundant 

mature timber and a thriving redcockaded woodpecker population, was 

hit particularly hard, Across 23 

counties, 32% of the pine and 22% of 

the hardwood were damaged--equivalent 

to four years of timber output, 

(Unless otherwise noted, information 

is based on current estimates by the 

South Carolina Forestry Coxmission.) 

After Mediate transportation and 

housing needs had been attended to, 

resources and concerns shifted to 

salvage and public safety due to fire 

danger, The next major concerns 

included fire prevention, reforestation, and rebuilding the economies of 

affected areas, More than three years 

later, we can begin to evaluate the 

effectiveness of these efforts, 

FIRST STEPS 

The forestry cornunity reacted 

quickly, The South Carolina Forestry 

Commission began an aerial survey of 

the damage the day after the hurricane, Consultants Mediately began 

conducting appraisals and sales, 

Forest industry undertook salvage 

efforts and attempted to identify 

methods of and locations for storing 

salvaged logs until they could be 

processed. State and federal agencies 

worked with salvage operations and 

information-gathering. State agencies 

provided salvage, price, and tax 

inf ormation, 

On September 23, South Carolina State 

Forester Jack Gould declared a forest 

disaster and requested an emergency 

meeting of the Foresters Council, an 

organization of state forestry 

leaders, As a result a salvage plan 

was drawn up and the governor's office 

was contacted for assistance. 

Governor Campbell issued an executive 

order on October 5 creating the 

Governor's Forest Disaster Salvage 

Council to coordinate efforts to 

harvest and salvage damaged timber, 

with an emphasis on recovering as much 

as possible. 

Four subgroups were established. The 

Utilization Committee had responsibility to "move the wood." It contacted in-state and out-of-state 

timber companies in order to increase 

utilization of damaged wood, Sprinkler systems and water storage systas 

for timber were encouraged. The committee coordinated logging crews, chip 

exports, and rail and highway transportation. 

The Information Committee developed a 

network to inform residents, landowners, and the general public about 

salvage efforts. The Government 

Affairs Comittee supported state and 

federal legislation to enhance salvage 

operations and forest regeneration, 

For example, it worked to temporarily 

increase gross weight limits for log 

trucks; promoted congressional action 

to give financial assistance to landowners; and obtained regulatory exemption for temporary sprinkler and water 

storage permits. The Statistics and 

Monitoring Committee established a data 

collection system to monitor salvage 

operations. 

SALVAGE OPERATIONS 

More than $1 billion worth of timber 

was damaged (Table l), though figures 

vary according to differing assumptions about what constitutes a loss. 

The hurricane caused considerable loss 

of sawtimber value, as much had to be 

processed as pulpwood or composition 

products. In addition, growing stock 

decreased significantly in average 

volume per acre (Figure 2) and net 

annual growth (Figure 3), with the 

Francis Marion National Forest most 

severely affected. 

In response to a critical shortage of 

loggers and processing facilities, a 

top priority for the Salvage Council 

was recruiting out-of-state loggers and 

finding out-of-state markets. But 

difficult and dangerous working conditions, along with unusually wet 

weather, made recruiting and retaining 

loggers a problem, 

Hugo left many areas covered with large 

timber debris, which prevented traditional mechanized harvesting, Helicopter logging was minimal, The 

relatively slow rate of chainsaw harvesting, the vast amount of damaged 

timber, limited availability of harvesting crews, and restrictions imposed 

by wet sites combined to decrease the 

amount of wood salvaged. Slightly more 

than 25% of the damaged wood was salvaged following Hurricane Camille on 

Mississippi's Gulf Coast in 1969, 

Because Hurricane Hugo caused more 

damage than Camille and wood-handling 
Table 1--Damage to timber in South Carolina from Hurricane Hugo. 

Volume Dollar value 

Sawtimber Pulpwood 

(af) ( cords ) Pulpwood 

Pine 6318,892 6,130,620 890,964,000 91,959,000 

Hardwood 3,984,003 7,038,029 163,341,000 35,190,000 

Total 10,302,895 13,168,649 1,054,308,000 127,149,000 

Source: South Carolina Forestry Co~ission data, 

I 

Cubic feetiacre 

Sohood, 1986 

'- iSoftwood, 1990 

Hardwood, 1986 

Hardwood, 1990 

Ownership class 

Figure 2--Average volume per acre of 

growing stock by owner and species in 

areas affected by Hurricane Hugo 

(Egbert and others 1992). 

facilities were not proportionally 

greater, the salvage goal was set at 

25% (625 million cubic feet) of the 

original rough damage estimates. 

Overall, 62% of this goal was met 

(Table 2)--or 15% of the total damage. 

The increased logging activity amid 

hazardous conditions resulted in eight 

deaths by March 1990 (South Carolina 

Forestry 1990). This is about four 

times as many deaths as would normally 

occur during the same period. However, it should be noted that considerably more wood than usual was 

removed during this period, Also, at 

least two of the eight deaths appear 

to have occurred in residential areas, 

Cubrc feeti 

acrdyear 

too 1 

Statewide potential 

growth, 1986 

r-- Statew~de actual ILL! growth, 1986 

Hugo area actual 

growth, 1990 

Ownership class 

Figure 3--Effect of Hurricane Hugo on 

South Carolina timberland productivity 

in 23 counties (Egbert and others 

1992). Potential growth based on 

Forest Survey definition of net annual 

growth. 

and one occurred when a log rolled off 

a truck (pers. comun., J. Knight, 

Occupational Safety and Health Administration, Columbia, South Carolina, 

1993). Two additional deaths were 

associated with helicopter logging, a 

technique not often used in this area, 

Of the wood salvaged, 49% came from 

the forests of nonindustrial private 

owners; 18% came from public land; and 

13% was salvaged from industry acres, 

The source of the raaining 20% is not 

known. About 90% of the salvaged 

timber was used in-state, 
Table 2--Volume of salvaged timber 

(387,450,045 cubic feet) relative to 

salvage goal (625,000,000 cubic feet). 

Volume Percent 

of goal 

Softwood 

Sawtimber (mbf ) 797,130 99.64 

Pulpwood (cords) 2,090,376 106.65 

Hardwood 

Sawtimber (mbf ) 64,365 10.38 

Pulpwood (cords) 507,726 15.16 

Source: South Carolina Forestry 

Commission data, 

Activity in the timber market affected 

nonindustrial private forest (NIPF) 

landownersf ability to salvage wood. 

Those who had not sold timber within 

the last few years were at a disadvantage in securing contracts (Nodine 

1992). 

Landowners who tried to salvage timber 

were often dissatisfied with logger 

performance and damage to residual 

trees. Market conditions were poor, 

and owners suffered financially. 

Higher logging costs, the extent of 

the damage, and the nature of the 

damage (which changed much sawtimber 

into a lower quality product) resulted 

in stumpage prices dropping to 20%-50% 

of prehurricane levels. Immediately 

after the storm, a few landowners gave 

their timber to loggers just to get 

the land cleared. 

WET STORAGE OF SALVAGED LOGS 

One of the first concerns of the 

Governor's Forest Disaster Salvage 

Council was securing facilities for 

wet storage of salvaged logs, since 

the large volume of harvested logs was 

expected to exceed the short-term 

capacity of converting plants. Industry was asked to identify potential 

storage areas (rock quarries, lakes, 

ponds, dry-land sprinklered sites) 

that could be reached by truck or 

rail. By December 1989, 30 potential 

sites had been identified with a total 

storage capacity of 160 million board 

feet, or 20% of the anticipated pine 

salvage volume of 800 million board 

feet. The South Carolina Department 

of Health and Environmental Control 

temlporarily allowed mills to bypass 

the pennit procedure for specified 

sprinkler systems. 

By the end of 1989, however, few logs 

had been placed in water storage. Wet 

weather hampered logging, so mills were 

able to process almost all of the logs 

harvested. Response increased in 1990, 

and an estimated 140 million board feet 

of salvaged pine logs and 6 million 

board feet of hardwood logs were stored 

under sprinklers. Logs were typically 

stored in rows or piles 10-25 feet 

high. Standard irrigation sprinklers 

applied a continuous spray. Logs were 

normally stored for several months, and 

in some cases more than one year, 

before being processed. 

Sprinkler storage proved to be an 

effective and low-cost retention 

method. As long as enough water was 

applied to maintain the required 

moisture levels, it prevented insect 

and fungal attack on freshly harvested 

logs and stopped further activity on 

logs infested prior to storage, No 

serious problems were encountered in 

processing these logs into lumber, 

veneer, and plywood, and no product 

degrade could be attributed to 

sprinkler storage (Syme and others 

1992). 

REFOmSTATION 

About one-quarter of the damaged area 

required reforestation (Table 3). 

This required a major commitment of 

resources. Most of the damage--and 

most of the area in need of reforestation--belonged to NIPF landowners. By 

mid-1990, 81% of NIPF landowners had 

not made plans for reforestation, Most 

of those who attempted to salvage 

timber felt reforestation was necessary and were interested in doing so, 

but felt they should not have to bear 

the full cost (Nodine 1992). 

Table 3--Effects of Hurricane Hugo on 

South Carolina forestland. 

Acres Acres needing 

Ownership class affected reforestation 

Nonindustrial 

private 

landowners 2,995,604 720,100 

Forestindustry 1,092,775 263,600 

Public 420,358 173,400 

Total 4,508,737 1,157,100 

Source: Sheffield and Thompson 1992. 

NIPF owners were offered a free 

reforestation examination via the 

Hurricane Hugo Technical Assistance 

Program ("Gimme Green"). The federal 
goverment provided $5 million to promate reforestation and give technical 

assistance. More than 1,000 landowners requested the fre 

310,000 acres* By the s 

state service foresters and 24 contracted consulting firms had serviced 

all requests* Of 223,000 acres 

inspected, 82% were in pine; of these, 

54% were adequately stocked; 2% were 

understocked but could be rehabilitated; 21% had or could be managed for 

natural regeneration; and 23% needed 

artificial reforestation* The second 

phase of Ginnne Green, begun in January 

1993, offered a free reforestation 

exam to every landowner with more than 

10 acres in an eight-county area. By the end of February 1993, 1,000 additional requests had been received. 

The Hugo Incentive Program (HIP), 

designed and administered by the 

Forestry Commission, provided $3 

million in federal funds as direct 

cost-share assistance for NIPF landowners affected by Hurricane Hugo. It 

paid approx-tely 75% of the total 

reforestation cost. During a two-week 

period in March 1991, 1,017 individuals applied for assistance under 

HIP, requesting more than $16 million. 

As of February 1993, 534 requests had 

been funded for $3 million, and almost 

$2 million had been paid to landowners 

who completed the work. Congress has 

appropriated an additional $3 million 

for this program, thus finding an 

additional 382 requests. By June 1993 

there were 1,180 requests. 

Reforestation costs are higher than 

normal due to the large amounts of 

residual vegetation. Mechanical site 

preparation costs were higher than on 

undamaged lands, and they rose with 

increased residual vegetation 

(Marsinko and others 1993). Chemical 

site preparation costs tended to be 

about average, although they also rose 

with increasing levels of residual 

vegetation, 

Hurricane Hugo changed NIPF landownersQttitudes (Nodine 19921. 

ut one-third had relied on iheir 

forestland as a primary or secondary 

source of income. After Hugo, income 

expectations shifted farther into the 

future or disappeared altogether. 

Land use priorities shifted from 

timber production to holding the land 

as an invesbent. Private owners had 

SUBSEQUEm HAZARDS 

As mentioned earlier, much of the 

damaged wood was not or could not be 

salvaged. This increased the danger of 

fire and insect infestations. The fire 

danger was and still is significant, 

with the potential to damage dwellings 

and commercial structures as well as 

timber* After the salvage operation 

mare than 2 billion cubic feet of 

damaged timber remained available as 

fuel. Fires in this debris could 

jeopardize remaining merchantable and 

unmerchantable timber. The South 

Carolina Forestry Commission acted to 

reduce the risk by restricting or 

banning outdoor burning and by plowing 

massive firebreaks. The commission 

received approximately $15 million from 

the Federal Emergency Management Agency 

(F-) to lease additional fire sup- pression equipment and heavy equipment 

to plow firebreaks through downed 

timber. Almost 5,000 miles of firebreaks involving 6,000 landowners were 

established to protect 94 communities. 

The state also instituted programs to 

heighten public awareness of fire 

danger and reduce the incidence of 

fires. One of these, Gimme 12 ("Give 

me 12 months of minimal wood or debris 

burning"), was an extensive fire prevention campaign financed by $1 million 

from FENA, With paid media advertising, direct mail to affected residents, 

student packets, and a complete range 

of promotional products and events, it 

has been described as one of the most 

intensive fire prevention campaigns in 

the history of the United States. 

During the four years prior to the 

hurricane, the counties most extensively damaged by Hugo had the highest 

arson rates. In the two years following the hurricane, the percentage of 

incendiary fires was lower overall. 

The percentage of fires caused by 

debris burning increased (mostly in the 

extensively damaged area), probably due 

to the fuel buildup, However, the 

er of fires per year was lower 

throughout the state (Table 4). 

The risk-reducing actions were aided by 

two relatively wet seasons following 

Hugo. In addition, destruction of 

trees caused the water table to rise 

and the soil to become more moist than 

usual, which may have further reduced 

the risk. 

problems arranging t ECONOMIC EFFECTS operations and were not expected to 

make large capital expenditures to The long-term hpact of Hurricane Hugo 

reforest their lands. is expected to be significant* The 
Table 4--Mean annual number of fires 

before and after Hurricane Hugo. 

Fires Fires 

Per par 

year, year, t 

1986-89 1990-91 cha~~ge 

1,463 1,110 -24 4 80 387 -19 

1,447 1,034 -29 

Total (affected area) 3,390 2,531 -25 

State total 5,480 3,852 -30 

Source r South Carolina Forestry Cdssion annual 

reports for 1986-91. 

buying radius of most of the 43 sawmills in the affected area is 75 miles 

or less. The entire buying area of 

some sawmills was within the damaged 

zone. Although not all the timber was 

destroyed, three mills had closed by 

mid-1992 and others are expected to 

follow (Syme and Saucier 1992). Pulp 

mills in the affected area reacted 

quickly to ensure their supply by 

establishing or increasing procurement 

activities in the undamaged areas of 

South Carolina, as well a s i n Georgia 

and North Carolina. 

Figure 4 and Figure 5 illustrate the 

price relationships for pine sawtimber 

and pulpwood before and after Hugo. 

One plausible explanation for the 

numbers is offered here. Although 

damage was confined to the midlands 

and the coastal plain, prices were 

affected statewide. Immediately after 

the hurricane, prices in the most 

affected areas dropped by half. Hugo 

flooded the market with timber, likely 

forcing prices downward. But prices 

rose the following year. Unusually 

large quantities of timber entered the 

market when Hugo hit; many mills may 

have expected a decreased future 

supply--a timber glut in one year 

resulting in a shortage (or perceived 

shortage) the following year--so 

prices rose. Prices later approached 

pre-Hugo levels as the market began to 

stabilize and other sources of timber 

became apparent. 

Even though the upland area of the 

state was spared by Hugo, prices 

appear to have been affected in 

similar ways. Sawtimber from the 

coastal plain usually does not find 

its way into the upland area, but some 

upland sawmills did process salvaged 

er, This could have lowered 

upland sawtimber prices, although 

upland prices fluctuated considerably 

just prior to Hugo. The confusion and 

uncertainty could have contributed to 

1s 1189 1110 N89 190 1190 11190 ff80 191 IS91 Ill91 NSl 

QUARTER 

Figure 4--Pine sawtimber prices before 

and after Hurricane Hugo (Timber Mart 

South 1990, 1991, 1992). 

ZC, 

UPLAND MIDWOS WhSTN PWN SOOTH AVG !-m- - -1 

0 1 I 

Ills 1169 111fiS NW 180 1190 Ill80 NSU 191 1191 lll@l N91 

QUARTER 

I 

Figure 5--Pine pulpwood prices before 

and after Hurricane Hugo (Timber Mart 

South 1990, 1991, 1992). 

the disproportionate rise in upland 

prices the year after Hugo, which 

disappeared as quickly as it appeared. 

Pulpwood in the upland area is routinely shipped to mills in the area 

affected by Hugo. The glut caused by 

Hugo temporarily decreased the need for 

this pulpwood, and upland prices 

dropped. The longer term shortage 

caused pulpwood prices to increase in 

the affected areas and more pulpwood 

was purchased from the upland area, 

driving prices higher. 

Post-Hugo harvesting costs were higher 

than normal, which would reduce stumpage prices for sawtimber and pulpwood. 

Anticipation of splits and breaks in 
er would be expected to result in 

lower delivered prices for logs 

(Lupld 1993) and would, in turn 

reduce stumpage prices for sawt 

Nearby processors whose t 

were not affected benefit 

hurricane, They were able to buy 

salvaged timber at depres 

while holding their om t 

future use--when prices were higher 

due to the expected shortage. These 

purchases enabled more timber to be 

salvaged than would otherwise have 

occurred and might have provided some 

price support for damaged timber, 

The net effect in South Carolina, 

however, is expected to be negative, 

It will take years before timber 

production in the affected region 

approaches prehurricane levels, Some 

small and medium-sized mills will 

close, removing their economic 

benefits from rural communities. 

Larger, diversified mills and pulp 

mills should survive, even though 

their costs might be higher and 

community benefits lower. 

WILDLIFE AND RESEARCH 

Hurricane Hugs had a devastating 

impact on the Francis Marion National 

Forest red-cockaded woodpecker (RCW) 

population, Prior to the hurricane, 

the forest had 477 family groups of 

RCWs and was considered to have the 

healthiest population in the world 

(Hooper and others 1991). Hugo 

destroyed 87% of the RCW cavity trees 

and more than 50% of the pine sawtimber used as foraging habitat and 

for cavity trees. Sixty-three percent 

of the birds were killed (Hooper and 

others 1990). 

As the result of a coordinated restoration effort, the RCW population has 

made considerable progress in the last 

three years (Watson and others, in 

press). Timber salvage operations 

were designed to aid the RCW by 

retaining all pines greater than 10 

inches in diameter that were leaning 

less than 45 degrees and still had a 

crown, Salvage also reduced the heavy 

fuel loads, Prescribed burning, a 

critical part of RCW management, was 

almost back to pre-Hugo levels by 

1992. 

To replace lost cavities, three 

methods were used: drilling new 

cavities, drilling startholes (Copeyon 

1990, Taylor and Hooper 1991), and 

placing wooden inserts directly into 

living trees (Allen 1991). ut 300 

of sach type were created, and 809 are 

currently used (Carlson 1991). The RCW 

eased from about 

iately after the 

stom to 320 family groups. The effect 

of Hugo on foraging habitat is still 

being analyzed. 

Gray squirrel populations were also 

severely affected. In general, 

however, heavy wildlife mortality was 

not documented. Cely (1991) concluded 

that Hugo's primary effects on wildlife 

will result from alterations to coastal 

and forested habitats, The openings 

created by Hugo will help some species 

and harm others; and some will benefit 

at the direct expense of others, 

some species, including the principal 

game animals, received a mixed blessing, Deer, for example, will find more 

browse created by increased openings, but will suffer during the winter from 

the loss of mast-producing trees, Turkeys have lost hard mast-production and 

roosting sites, but their poults should 

benefit from increased insect production in blowdown areas. Thus Hugo 

could present future challenges to game 

managers. 

Hugo and other catastrophic occurrences 

reveal the risks associated with current methods of protecting rare and 

endangered species. When these are 

confined to a few protected areas, the 

destruction of one such area can 

severely damage an entire population. 

As it moved through South Carolina, the 

hurricane's path also crossed experimental forest areas containing ongoing 

research projects. On the Santee 

Experimental Forest, nine long-term 

studies accounting for 221 research 

years were prematurely terminated (Hook 

and others 1991). As a result of the 

hurricane, however, a number of new 

studies were initiated, ranging from 

meteorological and biological aspects 

to economic effects to building design. 

LESSONS LEARNED 

Much of the response to forest damage 

was based on documentation from 

Hurricane Camille 20 years earlier, 

There will be other hurricanes, and 

they will damage forests, Information 

about Hugo will likely be used when 

these occur. 

Based on experience to date, it is 

apparent that more funds would have 

benefitted the reforestation effort. 
It is also becoming clear that reforestation following a disaster should 

be a long-term effort. Hurricane Hugo 

devastated homes and other property as 

well as forests. Initially, repairs 

to houses and other facilities along 

er salvage took priority. As 

a result, some NIPF landowners are 

just beginning to consider regeneration. 

One of the principal lessons taught by 

Hugo was that planning prior to a 

disaster is extremely important. A 

salvage plan would have helped. Salvage Council member Lupold (1993) 

noted that a computerized database 

containing information about forestry 

and wood products organizations and 

landowners would have saved the council four to five weeks by facilitating 

the gathering of information. Syme 

and others (1992) indicated that the 

lack of planned water storage sites 

was a significant problem and recommended that wet log storage facilities 

be part of a disaster plan. 

Plans that include a disaster response 

manual, up-to-date databases, and a 

compilation of disast 

research would be of 

To maintain their value, plans should 

be updated periodically. Land use and 

regulations change. Technological 

changes can affect the use of computerized databases as well as logging 

methods. For example, much of the 

wood salvaged from Hurricane Camille 

was cut by shortwood loggers. Wood 

damaged by Hurricane Hugo was often 

well suited to this type of logging, 

but few shortwood loggers were 

available by 1989. 

Immediate and extensive action on the 

part of many people resulted in the 

salvage of much timber, Quick and 

effective action saved many redcockaded woodpeckers. Continuing 

efforts have reduced the risk of fire 

and enhanced reforestation efforts. 

The wildlife population is recovering 

and adapting to its altered environment, Reforestation has begun and 

forest industry is adapting to changes 

in the forest and the timber market. 

More than three years later, salvage 

operations have concluded but reforestation efforts continue. The most 

obvious lesson is that a disaster 

response plan, continually updated, 

could have helped responses to 

Hurricane Hugo and would be valuable 

if-=ox when--the next disaster 

strikes. 

LITERATURE: CITED 

Allen, D.H. 1991. An insert technique 

for constructing artificial redcockaded woodpecker cavities. USDA For. 

Serv. Gen. Tech. Rep. SE-73. 19 p. 

Carlson, D.L. 1991. Post Hugo wildlife 

managment on the Francis Marion 

National Forest. Unpubl. pap., 70th 

annual meeting, Appalachian Society of 

American Foresters, Charleston, SC. 

Cely, J.E. 1991. Wildlife effects of 

Hurricane Hugo. J. Coastal Res. Spec. 

Issue 8:319-76. 

Copeyon, C.K. 1990. A technique for 

constructing cavities for the redcockaded woodpecker. Wildl. Soc. Bull. 

18~303-11. 

Egbert, C.D.; Morris, J.A.; Nodine, 

S.K.; Straka, T.J. 1992. Forestry and 

South Carolina's forest resources: 

their economic importance. Clemson 

Univ. Coop. Ext. Circ. 675. 44 p. 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest. J. Coastal Res. Spec. Issue 

8:291-300. 

Hooper, R.G.; Krusac, D.L.; Carlson, 

D.L. 1991. An increase in a population 

of red-cockaded woodpeckers. Wildl. 

SOC. Bull. 19(3):277-86. 

Hooper, R.G.; Watson, J.; Escano, E.F. 

1990. Hurricane Hugo's initial effects 

on red-cockaded woodpeckers in the 

Francis Marion National Forest. In 

Transactions, 55th North American 

wildlife natural resources conference, 

p. 220-24. Wildl. Manage. Inst., 

Washington, D.C. 

Lupold, H.M. 1993. Salvage of storm 

damaged timber. In Proceedings, 72nd 

annual meeting and regional technical 

conference, Appalachian Society of 

American Foresters, p. 65-74. Appal. 

Soc. Am, For,, Seneca, SC. 

Marsinko, A.P.; Straka, T,J.; Baumann, 

J.L. 1993. The effect of Hurricane Hugo 

on forest practice costs. In Proceedings, 72nd annual meeting and regional 

technical conference, Appalachian 

Society of American Foresters, p. 1-5. 

Appal. Soe. Am. For., Seneca, SC. 

Nodine, SIR, 1992. Forest landowners' 

responses to Hurricane Hugo. Clemson 

Univ., Clemson, SC. For, Wes. Ser. 47. 

37 p. 
Sheffield, R.H.; Thompson, M.T. 1992. 

Hurricane Hugo: effects on South 

Carolina's forest resource. USDA For. 

Serv, Res. Pap. SE-284. 51 p. 

South Carolina Forestry, 1990. Record 

r of Hugo related logging deaths 

reported, SC For 10(3):1,12. 

Syme, J.H.; Peralta, P.N.; McAlister, 

ROB, 1992, Water storage and processing of Hurricane Hugo salvage logs 

at Georgia Pacific Corporation's 

Russellville Plywood plant. Plywood 

Res. Found., Tacoma, HA. 38 p. 

Syme, J.H.; Saucier, J.R. 1992. Impact 

of Hugo timber damage on primary wood 

manufacturers in South Carolina. USDA 

For. Serv. Gen. Tech. Rep. SE-80, 

28 p. 

Taylor, W.E.; Hooper, R.G. 1991, A 

modification of Copeyon's drilling 

technique for making artificial 

red-cockaded woodpecker cavities. 

USDA For. Serv. Gen. Tech. Rep. 

SE-72. 31 p, 

Timber Mart South. 1990, 1991, 1992. 

Fourth quarter reports for 1989, 1990, 

1991, Timber Mart South, Highlands, SC. 

Watson, J.C.; Hooper, R.G.; Carlson, 

D.L.; Taylor, W.E.; Milling, T.C. 

Restoration of the red-cockaded 

woodpecker on the Francis Marion 

National Forest: three years post-Hugo. 

In Proceedings, third red-cockaded 

woodpecker spposium, D.L. Kulhavy, R. 

Costa, and R.G. Hooper, eds. (In 

press. ) 

Reprinted with permission from Journal 

of Forestry 91(9):9-13,15,17 published 

by the Society of American Foresters, 

5400 Grosvenor Lane, Bethesda, MI) 

20814-2198. Not for further 

reproduction. 
EFFECTS OF HURRICANE HUGO ON THE FORESTS OF 

NORTH AND SOUTH CAROLINA' r 

Michael T. ~hompson~ 

Abstract--The reinventory indicates that 4.5 million acres 

of timberland in a 23-county area in South Carolina, and 

1.6 million acres in a 27-county area in North Carolina 

were damaged by Hurricane Hugo (Sheffield and Thompson 

1992). Significant damage occurred in 55 percent of the 

pine plantations, 60 percent of the natural pine stands, 55 

percent of the oak-pine stands, 43 percent of the upland 

hardwood stands, and 74 percent of the lowland hardwood 

stands. Lowland hardwood stands typically contain large 

shallow-rooted trees with large crowns, which are highly 

susceptible to wind damage, Public timberland in South 

Carolina suffered a very high rate of damage (79 percent). 

Much of the National Forest land in the study area was in 

the direct path of the hurricane. The pre-Hugo inventory 

of softwood growing stock was reduced by 16 percent to 6.2 

billion cubic feet; and the pre-Hugo inventory of hardwood 

growing stock by 4 percent to 9.9 billion cubic feet in the 

50-county area. The reductions in inventories of both 

softwoods and hardwoods were most severe on public land. 

Large-diameter trees suffered a higher rate of mortality 

and damage than smaller trees. Of the 6.2 billion cubic 

feet of softwood growing stock that survived the storm, 20 

percent, or 1.2 billion cubic feet, was damaged to some 

extent. Almost 0.7 billion cubic feet were in trees 

classed as moderately to severely damaged. Nearly 1.8 

billion cubic feet, or 18 percent, of the hardwood inventory after Hugo was damaged. About 12 percent of the 

hardwood volume was in trees with moderate to severe 

damage. As a result of the hurricane, an additional 1 

million acres of timberland in South Carolina and 0.4 

million acres in North Carolina were identified as needing 

regeneration. 

LITEmTJa CITED 

Sheffield, Raymond M.; Thompson, Michael T. 1992. Hurricane Hugo: effects on South 

Carolina's forest resource, USDA For. Serv. Res. Pap. SE-284. Southeast, For. Exp. 

Stn., Asheville, NC. 51 pp. 

Reprinted with permission from Hurricane Hugo: Recovering fron Disaster, 

Proceedings 72nd Annual Meeting and Regional Technical Conference, Appalachian 

Society of American Foresters, Greenville, SC, Jan. 20-22, 1993. Dr. Vernon L. 

Robinson, See-Treas, 2557 Abbott Circle, Seneca, SC 29678. 

A paper presented at the 72nd Annual Meeting of the Appalachian Society of 

American Foresters held in Greenville, SC, on January 20-22, 1993. 

Michael T. Thompson is a Forester, USDA Forest Service, Southeastern Forest 

Experiment Station, P.O. Box 2560, Asheville, NC 28802. 
ASSESSmNT OF ~RRICAINE mGO I1 

STATE AND PRIVATE LANDS IN SOUTH CAROLINA 

Michael C, ~ernionl 

INTRODUCTION 

Hurricane Hugo has been labeled the 

most economically devastating natural 

disaster ever to strike the continent 

of North America. The damage to 

timberlands alone in South Carolina 

exceeds the combined losses of timber 

caused by Hurricane Camille and 

Frederick, the Yellowstone fires of 

1988, and the volcanic eruption of 

Mount St. Helens. The magnitude of 

devastation caused by Hugo is incomprehensiblel In South Carolina, the 

storm left in its wake; 41 deaths, 

5,343 homes destroyed with another 

18,600 sustaining major damage, 18,000 

miles of roads and highways blocked by 

domed timber, and the destruction of 

enough timber to construct 660,000 new 

homes. total damage in South Carolina 

is estimated at $5 billion. The use 

of aerial, infrared photography 

provided by the United States Forest 

Service (USFS) will be an invaluable 

resource in assessing damage caused by 

the storm and planning rehabilitation 

efforts related to the storm. 

DAMAGE ASSESSMENT 

Timber 

Hurricane Hugo struck South Carolina's 

coast on Friday, September 22, 1989 at 

12:Ol A.M., Eastern Standard Time. 

The eye of the storm hit the Isle of 

Palms located approximately seven 

miles due east of Charleston, South 

Carolina. The intensity of the storm 

was rated as a category 4 with sustained winds of 139 miles per hour 

(mph). After entering the mainland, 

the storm followed a northward track 

passing through Sunter, SC, located 90 

miles inland, and travelled onward to 

Charlotte, MC, located approxi-mately 

190 miles north-northwest of the Isle 

of Palms. Windspeed was measured at 

109 mph in Sumter, SC 

South Carolina Forestry Commission, 

P. 0. Box 21707, Columbia, SC 29221. 

On the afternoon of September 22, 1989, 

the South Carolina Forestry Comission 

(SCFC) began initial timber damage 

appraisals using two light aircraft 

employing the aerial sketch-mapping 

technique. Flight line intervals were 

5 strips on both sides of the aircraft. 

The damage categories recorded were no 

damage, light, moderate and heavy 

timber damage. The aerial surveys were 

completed on September 24, 1990. 

Tables 1 and 2 reflect the findings of 

these surveys relative to the estimated 

impact of the storm on the timber 

resource and subsequent timber landmass 

in South Carolina. 

Approximately 36% of South Carolina's 

total 12.2 million acres of forested 

land was damaged by the hurricane. A 

total of 23 counties received varying 

degrees of timber damage encompassing 

60 percent of the total land base in 

the state. The damage to sawtimber 

represents 2.5 and 16 years worth of 

annual pine and hardwood timber harvest, respectively. Of the total 

merchantable hardwood and pine inventory in South Carolina, Hugo destroyed: 

- 10% of the pine sawtimber 

- 13% of the hardwood sawtimber 

- 5% of the pine pulpwood 

- 18% of the hardwood pulpwood 

Reforestation 

Reforestation needs relative to the 

storm's damage are displayed in Table 

3. 

Of the 4.4 million acres of forested 

land impacted by Hugo, 1.3 million 

acres were totally destroyed and will 

require reforestation. The rehabilitation of damaged timberlands through 

reforestation will be a monumental 

task. Several Hugo bills addressing 

reforestation assistance are presently 

pending in the United States CongressThey are: 
Table 1--Timberland damaged by Hugo.* 

Degree of Damage Number of Counties Acres Percent of Total 

Heavy 

Moderate 

Light 

* (Ownership pattern: 64% private, 10% government, 26% industry) 

Table 2--Hugo timber damage assessment. 

Product Units Value 

Pine Sawtimber 

Hardwood Sawtimber 

Pine Pulpwood 

Hardwood Pulpwood 

Young Growth ~stimate 

3,305,000,000 bd.ft. $ 581,603,692 

3,457,000,000 bd.ft. 231,591,882 

4,249,000 cords 63,736,517 

l6,OOl,OOO cords 80,003,672 

unmerchantable 83,954,672 

TOTAL ---------- $1,040,890,335 

Table 3--Reforestation needs related to Hugo. 

ownership Acres Damaged Acres ~equiring Reforestation 

Private Landowners 

Forest Industry 

Other Corporate 

State Ownership 

Federal Ownership 

TOTAL 

- The Hugo Reforestation Act which 

provides authorization for $100 

million in cost-share assistance 

to landowners wishing to 

re-establish timber stands 

damaged by the hurricane. 

- The Emergency Reforestation Act 

(5.2043) which provides for a 

long-term $300 million program 

to help reforest timberlands 

damaged by Hugo, a cost-sharing 

program to pay 75 percent of 

reforestation costs to owners of 

timber stands that suffer damage 

due to a natural disaster, and 

the establishment of an mergency 

Reforestation Committee to 

develop subsequent program 

regulations. 

- The Hurricane Hugo Tax Assistance 

Act (5.1748) which provides for a 

deduction for timberland owners 

based on the fair market value of 

the timber, the amortization of 

reforestation expenses up to 

$30,000 and the proceeds from the 

sale of damaged timber be treated 

as an "involuntary conversion" so 
the proceeds can be reinvested 

in reforestation. 

Insects and Dfsease 

The area of iate concern to forest mnagers owing the hu 

was the invasion of d 

various insect- and d~sease-c 

organism* Of particular concern was 

the rate of infestation of d 

er by engraver beetles and 

blue stain fungi, Historically, these 

two organism, through their mode of 

action, have been responsible for 

hastening the loss of product utility 

of pine sawtimber following hurricane 

damage, 

To monitor the activity of these 

pests, the SCFC and the USFS, Forest 

Pest Hanagexnent, established 12 plots 

in the damaged area, Figure 1 illustrates the rate of infestation over a 

5-month period. 

Due to unseasonably warm weather during 

January and February, the rate of 

infestation dr tically increasd, It 

ted that this increase will 

the loss of 2 

longevity of the pine t 

pests being monitored in the Hugo area 

include black turpentine beetle, 

southern pine beetle, reproduction 

weevils, and annosus root rot, 

Salvage 

er 23, 1989, a forest 

disaster was officially declared in 

South Carolina, Subsequently, the 

Governor of South Carolina created the 

Governor's Forest Disaster Salvage 

Council on October 6, 1989, The 

primary objective of the council is to 

promote effective use of the destroyed 

timber through public awareness and 

open coxnmunications between affected 

Landowners, cooperating agencies, and 

the forest industry, 

r 3 The results of salvage efforts through aid-March, 1990 are displayed in Table 

4. 

Due to the rapid invasion of insect and 

disease organisms, it is estimated that 

major salvage efforts will subside by 

late June, 1990. It is presently 

estimated that only 15 percent of the 

total damaged timber will be salvaged 

at the culmination of the project, 

Figure 1, Pine infestation by Ips aad 

blue stain after Hugo, 

Table 4--Hugo timber salvage as of March 14, 1990.* 

Product Damaged Units Salvaged Units % salvaged 

Pine Sawtimber 3,305,000,000 

(bd* ft*) 

Hardwood Sawtimber 3,457,000,000 

(bd. ft*) 

Pine Pulpwood 4,249,000 

(cords ) 

Hardwood Pulpwood 16,001,000 

(cords ) 

408,442,710 

(bd. ft*) 

26,762,820 

(bd* ft.) 

1,035,865 

(cords ) 

214,838 

(cords ) 

--- -- - 

TOTAL ------- ------- 9.2% 

* (Sources: 71% private, 14% industry, 15% government) 

172 
Fire 

Through the assistance of Federal 

Emergency Management Act (FEHA) funds, 

the SCFC has launched a major forest 

fire prevention and suppression 

campaign. This is a combined effort 

of many state, federal, and local 

agencies to prevent the loss of life 

and property within the Hugo area. 

This federally funded project is 

scheduled to end on September 30, 

1990. 

APPLICATIONS OF AERIAL 

PHOTOCIUIPHY 

On October 4, 1989, the USFS Aerial 

Survey Team (Region 8, Atlanta, 

Georgia) began photographing counties 

impacted by Hugo. The survey team has 

completed photography in 15 of the 23 

affected counties. The photography is 

color, infra-red taken at a scale of 

1:12,000. The primary purpose of the 

aerial photographic mission is to 

provide photography for current and 

future assessment of insect and 

disease impact on the timber resource 

within the Hugo area. However, this 

photography has proven to be a 

valuable resource for a diversity of 

other uses by private landowners, 

forest managers, and agencies dealing 

with various facets of Hugo's 

destruction. 

Some additional applications of the 

Hugo aerial photography are: 

- Stream bed rehabilitation (SCS - 

USDA) 

- Forest Inventory Analysis (USFS 

- USDA) 

- Casualty loss determination 

- Insurance claims documentation 

Reforestation efforts - federal 

and state subsidy programs 

Fuels management (fire 

prevention) 

Fire suppression 

Tax re-assessment 

Road maintenance and 

rehabilitation 

Sand dune renourishment 

Historical reference 

Timber Salvage - debris removal 

ACICNOmEDCmNTS 

On behalf of the citizens of South 

Carolina, I want to thank the many 

people from across this country and 

abroad for assisting the Hugo victims 

in our state. These people gave freely 

of their time, talents and financial 

resources to help us recover from this 

devastating storm. The assistance of 

the many UsFS employees who detailed to 

South Carolina to assist in the rehabilitation efforts is also greatly 

appreciated. Special appreciation is 

extended to the USFS Aerial Survey 

Team, Forest Pest Management, Region 8, 

Atlanta, Georgia. This team has made 

many personal sacrifices and worked 

under strenuous conditions to provide 

the forest landowners in South Carolina 

with resource photography. Their cooperative spirit is to be commended! 

Reprinted with permission from the 

Proceedings of the Third Biennial 

Remote Sensing Conference, Tucson, AZ, 

April 1990. Dr. Jerry D. Greer, 

Editor, P.O. Box 1026, McCall, ID 

83638-1026. 
m=ICM]E: EN GE MSESSmm USING 

PE ENT PLOT REMEASUREMENT' 

Raymond M. sheffield2 

Abstract--A network of 3,500 permanent ground plots was 

utilized to assess damage from a major hurricane that 

struck the Southeastern United States in 1989. Hurricane Hugo inflicted varying degrees of forest damage 

across an area of 4.4 million hectares. This paper 

summarizes data collection and analytical procedures 

used to assess forest damage across this area. Results 

that are easily provided from remeasurement of permanent 

plots are highlighted. Advantages and disadvantages of 

ground-based pe nent plot assessment systems are highlighted. 

INTRODUCTION 

Hurricane Hugo struck the Southeastern 

United States in September 1989 with 

winds of 217 kilometers per hour, or 

60 meters per second (Powell, Dodge, 

and Black 1991). Hugo extensively 

damaged forest stands in North 

Carolina and South Carolina. It 

significantly altered forest conditions and inventory volumes and 

rendered many short- and long-term 

forestry resource programs obsolete. 

Forestry agencies in the two states 

conducted aerial and ground reconnaissance surveys to determine the extent 

of the damage. Their observations and 

subjective estimates were adequate for 

planning initial responses, but they 

needed more quantitative measures for 

long-term planning. 

The South Carolina Forestry Comission 

asked the Forest Inventory and 

Analysis (FIA) Research Work Unit at 

the Southeastern Forest Experiment 

A paper presented at the IUFRO 

Conference on Inventory and Management 

in the Context of Catastrophic Events, 

University Park, PA, on June 21-24, 

1993. 

Supervisory Research Forester, 

Southeastern Forest Experiment 

Station, P. 0. Box 2680, Asheville, NC 

28802. 

Station to conduct a special inventory 

of forests in that staters affected 

area. This damage assessment was later 

expanded to include a large portion of 

North Carolina (Figure 1). The area of 

timberland in the study region totaled 

4.4 million hectares. Utilizing a previously established network of permanent ground plots throughout this 

region, FIA designed damage inventory 

procedures to: (I) quantify-the extent 

of damage and describe associated stand 

conditions, (2) determine the volume of 

hurricane-related mortality and damage 

to live trees, and (3) provide an 

estimate of current inventory volume. 

METHODS 

FIA is a research activity of the USDA 

Forest Service. Its mission is to 

comprehensively inventory the status 

and trends of the country's diverse 

forest ecosystems, their use, and their 

health (U. S. Department of Agriculture, Forest Service 1992). Six 

regional FIA units maintain a network 

of permanent samples on forest land 

across the United States. More than 

3,500 of these permanent plots were in 

North and South Carolina counties 

damaged by Hurricane Hugo. Prior to 

the hurricane, these ground plots had 

been visited and measured last in 1984 

in North Carolina and 1986 in South 

Carolina. 
Figure 1--Area in North Carolina and 

South Carolina reinventoried for 

hurricane damage to timberland. 

Field Procedures 

Data collection procedures are briefly 

summarized in this paper; details are 

available in a report by Sheffield and 

Thompson (1992). Two-person crews 

visited each sampling location in 

1990, 5 to 9 months after Hurricane 

Hugo struck. Each tree above a 

minimum diameter at 1.4 meters above 

the ground was relocated. The minimum 

diameter used was 7.6 centimeters for 

trees in natural stands and 2,5 

centimeters for trees in planted 

stands. Each tree was assigned one of 

the following six tree histories: 

tree alive without hurricane damage 

* tree alive with hurricane damage 

* tree dead (hurricane related) 

* tree dead (other causes) 

tree cut, associated with hurricane 

salvage efforts 

tree cut, associated with normal 

harvest operations 

For all live trees with hurricane 

damage, specific classes of damage 

were noted. Damage classes were: 

+ leaning or bending (degrees from 

vertical ) 

* root system d 

ge to tree bole 

loss of tree crown 

Any codination of these could be 

assigned to a tree; multiple damages, 

such as severe lean and exposed root 

systems, were common. 

Analytical Procedures 

Standard protocols for the analysis of 

data from a damage inventory are not 

available, One must adjust methods to 

account for the magnitude of loss and 

the specific goals that have been 

specified, After Hugo, we wanted to 

quantitatively estimate damage to 

individual trees and to stands of 

trees. Little published data were 

available in the literature to assist 

in this process, so various approaches 

to solving these problems were used, 

In a ground-based damage inventory, the 

types of damage to individual trees 

must be categorized, Damage may be so 

minor that the tree's value, growth, 

and probability of survival are not 

affected. Conversely, damage may be so 

severe that the tree's value has been 

destroyed, its growth potential reduced 

to a fraction of normal, or its survival chances severely reduced, Guidelines for assigning meaningful categories of damage were not found in the 

literature, so we developed our own 

classification framework, Our design 

permits decisions about individual 

trees to be made on the basis of value, 

likely contribution, and development in 

the future. Detailed criteria for 

assignment of softwood and hardwood 

trees into four damage categories were 

developed and modified based on review 

by more than a dozen individuals, 

Sheffield and Thompson (1992) describe 

the process and the criteria, Here I 

present the damage/risk classes used 

and a brief description of levels of 

tree damage in each class. 

Class 1. High-risk tree with a high 

probability of dying in the near 

future. Damage and value loss are 

severe enough that this tree should not 

be retained in the stand, 

Class 2. Moderate-risk tree with 

elevated risk of mortality, Damage and 

value loss are substantial enough to 

make the retention of this tree in the 

stand questionable, Retention depends 

upon management objectives, stand and 

rotation age, and product objectives. 
Class 3. Low-risk tree with a high 

probability of survival. D 

vates the risk of mrtality slightly, 

but reduced growth and value degrade 

are minimal. This tree should be 

retained in the stand under mast 

manlagernent scenarios. 

Healthy. No obvious hurricane damage, 

A tree with hidden or internal d 

wuld be classed as healthy. 

The assessment of stand conditions 

depends on the condition of individual 

ining in the stand. Thus, 

the decision to regenerate or salvage 

requires sound judgments about individual trees and about the level of 

residual stocking needed for an 

acceptable stand. One must also 

determine which categories of damage 

are acceptable for inclusion in 

minhum residual stocking. In the 

analysis of damage from Hurricane 

Hugo, I used the three broad categories of damage to trees in different 

ways to estimate lower- and upperbound values for timberland area by 

condition class and treatment opportunity. For example, in South 

Carolina the estimate of timberland 

area needing regeneration because of 

Hurricane Hugo ranged from 328,000 to 

623,000 hectares depending on which 

live tree damages were used to 

discount existing stocking in the 

stand (Sheffield and Thompson 1992). 

RESULTS AVAILABLE FROM 

PERMANENT PLOTS 

Damage inventories utilizing permanent 

plot remeasurement can provide a 

wealth of information to the resource 

manager or analyst. The classifications and resource items that can be 

displayed depend in part on the 

classifications that have been made 

prior-to the damage event. Forest 

type and age, for example, are sometimes difficult to assess after severe 

damage or salvage has occurred. The 

following is a brief summary of the 

kinds of results that were available 

in the Hurricane Hugo damage assessment. 

(1) Areal extent of damase. Timberland area damaged can be estimated and 

displayed for political or administrative units, ownership categories, 

forest types, or any other stand 

classification available from the 

existing inventory. Information about 

the impact on the age structure of the 

forest is often needed to evaluate 

timber supply impacts. Figure 2 shows 

how the age structure of natural pine 

stands in South Carolina were affected 

by Hugo. Maps showing the geographic 

extent and distribution of forest 

ge are also easily produced (Figure 

3). If the coordinates of each Dermanent sampling point are known, a-geographic information system can overlay 

tion about stand damage severity 

with other layers. In Figure 3, state 

and county boundaries and the path of 

the hurricane's eye are shown along 

with damage. Inventory results such as 

this map are similar to products developed from satellite imagery. Groundbased inventories, however, can provide 

more quantitative estimates of timber 

volumes associated with conditions on 

the ground, 

Age class (years) 

81 + I 

21 -30 

11-20 

0-10 

0 50 1 00 150 200 

Thousand hectares 

Undamaged Light 

0 Moderate fo heavy Harvested (1986-90) 

Figure 2--Stand-age profile for natural 

pine stands in South Carolina, by 

degree of hurricane damage. 

(2) Inventory updates. The remeasurement of all merchantable-size trees 

facilitates accurate estimates of 

current inventory volume, change since 

the previous sample measurment, and 

volume loss due to the damaging event. 

Figure 4 summarizes volume change for 

softwood species in South Carolina. In 

this example, softwood volume totaled 

136 million cubic meters in 1986 and 

had dropped to 107 million cubic meters 

ip 1990. Mortality and timber salvage 

due to hurricane damage accounted for 

29 million cubic meters, Inventory 

updates such as this can be summarized 

by ownership class, stand condition, 

political or geographic unit, species, 

or tree size. 
Light Damage 

Moderate/Heav y Damage 

Figure 3--A generalized distribution of timberland in South Carolina damaged by 

Hurricane Hugo, by degree of damage. 

Million cubic meters 

150 j 

I -50 1 t 1 I 

t 986 Cross Regular Regular Pre-Hugo Hugo Hugo t 990 

inventory growth cut mortality inventory salvage mortality inventory 

(3) Damaqe severity in live trees. 

Estimates of the prevalence and 

severity of damag;s to the current 

inventory of live trees are needed 

to predict future mortality. If 

substantial numbers of live trees are 

classed as severely damaged (class I), 

mortality is likely to remain high for 

a long time (Figure 5). In this 

example, 68 percent of the hardwood 

volume in South Carolina was classed as 

healthy and 32 percent damaged. About 

37 percent of the damaged trees were 

classed as severely damaged (class 1). 

If these trees die, an additional 

reduction in inventory volume of around 

12 percent can be anticipated. 

Figure 4--Change in volume of softwood 

growing stock in South Carolina, by 

component of change. 
Class f 

37% 

Health:, Class 2 

68% 259, 

Class 3 58% 

Figure 5--Incidence of damage in postHugo hardwood growing stock in South 

Carolina, by damagelrisk class. 

(4) Estimates of treatment opportunities. For long- and short-term planning, estimates of stand treatment 

needs for regional areas are essential 

after catastrophic events such as 

hurricanes. The classifications 

described earlier help in estimation 

of the forest areas needing 

regeneration, salvage, and other 

treatments. 

PERMANENT PLOT DAMAGE 

ASSESSNENT--31lDVANTAGES AND 

DISADVANTAGES 

Advantages 

A network of permanent ground samples 

offers five obvious advantages over 

other methods such as remote sensing 

for forest damage assessment: 

(I) Forest conditions that existed 

before the catastrophic event are 

known. 

(2) Quantitative estimates of volume 

loss and damage are direct outputs 

from the system, and can be provided 

for critical subsets of the overall 

resource. 

(3) Up-to-date estimates of inventory 

volumes are provided. 

(4) Ground-based inventories set the 

stage for subsequent remeasurements to 

estimate recovery. 

(5) Ground-based inventories provide 

precise values needed to validate the 

tes that can be mde with 

remote sensing data. 

Disadvantages 

(1) Depending on the inventory objectives, ground-based activity can be 

more costly than other inventory 

methods. 

(2) Results may take longer to produce 

because field visits are so time 

consuming. 

(3) A satisfactory network of permanent plots for producing reliable 

results may not exist. 

(4) Large numbers of samples may be 

needed. 

LITERATURIE CXTED 

Powell, Mark D.; Dodge, Peter P.; 

Black, Michael L. 1991. The landfall of 

Hurricane Hugo in the Carolinas: 

surface wind distribution. Weather and 

Forecasting 6:379-399. 

SheffiePd, Raymond M.; Thompson, 

Michael T. 1992. Hurricane Hugo: 

effects on South Carolina's forest 

resource. Res. Pap. SE-284. Asheville, 

NC: U.S. Department of Agriculture, 

Forest Service, Southeastern Forest 

Experiment Station. 51 p. 

U.S. Department of Agriculture, Forest 

Service. 1992. Forest Service resource 

inventories: an overview. Washington, 

DC. 39 p. 

Reprinted with permission from Proc. 

IUFRO Conf. on Inventory and Management 

in the Context of Catastrophic Events, 

Penn State University Park, PA, June 

21-24, 1993. Dr. Wayne A. Myers, School 

of Forest Resources, Penn State Univ., 

University Park, PA 16802. 
ASSESSING INTERNAL HURRICANE D 

STMDING PINE POLETIN1BER 

Timothy D. Faust, ark Puller, Robert H. McAlister, 

and Stanley J. %arnochl 

Abstract--Two test methods were used to assess type, 

location, and degree of internal stem damage to standing 

pine poletimber (5.0-8.9 inches diameter at breast height, 

DBH) caused by Hurricane Hugo. A total of sixty trees (15 

from each of the four Forest Inventory Analysis [FIA] 

damage classes) were taken from three sites in the Francis 

Marion National Forest. Internal damage was expected in the 

form of ring shake and compression failure. Five stem 

sections (A through E) were taken from each tree at different heights. From each section, specimens were cut from 

four quadrants (Tension, Compression, Left, and Right) 

relative to the wind direction during the storm, for toughness and tension (perpendicular to the grain) testing. A 

total of 2,147 toughness specimens were tested. A total of 

273 specimens were tested in tension perpendicular to the 

grain. The dependent variables analyzed were toughness, 

tension strength and specific gravity with FIA damage class 

as the whole plot factor. 

Although there was an increasing trend in toughness from 

damage class 1 through 4, analysis of variance showed 

damage class not to be a significant effect on toughness. 

Stem section and quadrant were found to be significant on 

toughness. Much of the variation in toughness due to stem 

section may be attributed to the effects of juvenile wood 

differences with tree height. Also a high occurrence of 

reaction wood in quadrant C (side of the tree away from the 

wind) would contribute to lower toughness strength. Similarly, specific gravity (SG) values showed an overall 

increase from damage class 1 through 4. Specific gravity 

of damage classes 1 and 4 was found to be significantly 

different. Statistical analysis showed no apparent relationship between damage class and tension strength perpendicular to the grain. 

The lack of evidence for internal damage is relatively 

unimportant compared to the evidence of change in the wood 

properties from the formation of reaction wood. In leaning 

stems (FIA damage classes 2,3,4), reaction wood should 

continue to form. In straight trees, reaction wood formed 

in the two growth seasons following the storm but it is 

unclear whether it will continue to form. The results lead 

to the conclusion that stands with leaning stems should be 

harvested and replanted. 

Timothy D. Faust, Associate Professor, and Mark Fuller, Graduate Assistant, D. B. 

Warnell School of Forest Resources, University of Georgia, Athens, GA 30602; Robert 

He McAlister, Forest Products Technologist, and Stanley J. Zarnoch, Mathematical 

Statistician, US Forest Service, Southeastern Forest Experiment Station, Forestry 

Sciences Laboratory, Athens, GA 30602. 
INTRODUCTION 

er 22, 1989, Hurricane Hugo 

South Carolina coast with 

sustained winds of 135 mph and gusts 

up to 175 mph. In the fall of 1989 

the Forest Inventory and Analysis 

(FIA) Research Work Unit at the Southeastern Forest Experiment Station 

began a special inventory of the areas 

ged by Hugo. A classification 

system was needed which would assign 

hurricane damaged trees to discrete 

categories based on the amount of 

inflicted damage. The objective was 

to "provide a reasonable description 

of damage severity" and estimate the 

probability of mortality in the near 

future (Sheffield and Thompson, 1992). 

The criteria for damage class were 

empirically derived and a system of 

four damage classes emerged (Table 1). 

Hugo caused extensive immediate d 

to the Francis Marion National Fo 

with an estimated 75% of all marketable trees (DBH > 5.0) on the ground 

(Ehinger, 1990). The FIA damage class 

system was devised and implemented in 

an effort to quantify the damage 

inflicted on the forest resource and 

to help foresters decide on the proper 

management strategies for the remaining stands. However, there were 

questions still unanswered. What 

possible long range effects did Hugo 

have on the remaining 25%? In the 

case of poletimber (5.0-8.9 DBH) a 

question which naturally arose was 

"Should storm damaged poletimber be 

allowed to mature into sawtimber?" 

Internal damage to the stem in the 

form of ring shake and compression 

failures could reduce the utility of 

these trees for high value products 

such as structural lumber. Such 

damage may not be evident until 

processing of the lumber is completed, 

adding further to the costs of 

utilizing these trees. A~SO, if stems 

with internal damage do enter the 

market, a significant liability risk 

due to increased failure rates will 

us, sawtimber from interged stems should be sold for 

pulp chips, a lower value product. 

Traditionally storm damage has been 

classified in terms of visual damage 

such as snapping of the trunk, 

uprooting, and bending (Webb, 1988). 

Similarly, Mayer (1988) defined four 

types of storm damage as: Stem 

breakage, stock (base of stem) 

breakage, root breakage, and tree 

throw. There have been other studies 

which differentiate only between tree 

throw and stem breakage. Although it 

is apparent that high winds could cause 

e to tree stems, little 

lable on the subge class system 

classification in 

terms of apparent storm damage and 

potential mortality allows only for 

conjecture as to the degree of internal 

ge. Although the FIA damage 

class system is only approximate, it is 

a very practical classification system 

which brings us a step closer to understanding the nature of storm-damaged 

timber. What is needed is correlation 

between this visual damage classification system and actual internal damage 

as measured by mechanical testing and 

visual observation. 

0BJlE:CTIVE 

The objective of this study was to 

assess type, location and degree of 

internal stem damage to standing pine 

poletimber and to relate this damage to 

the FIA damage classes. Internal 

damage in the form of compression 

failures, ring shake and reaction wood 

were examined by toughness tests, 

tension perpendicular to the grain 

tests and visual observation of 

reaction wood formation, respectively. 

Wood specific gravity was measured at 

each location and analyzed with the 

mechanical properties. A summary of 

the study variables is presented in 

Table 1. 

METHODS AND MATERIALS 

A total of sixty poletimber-sized trees 

consisting of longleaf pine (Pinus 

palustris Dim.) and loblolly pine 

(Pinus taeda L.) was taken from natural 

stands in the Francis Marion National 

Forest near McClellanville, South 

Carolina, in August of 1991. To avoid 

the possibility of site bias, the trees 

were taken from three different sites. 

er of the FIA research work unit 

select the trees for the study 

which consisted of 15 trees in each FIA 

ge class. Five stem sections were 

cut from each selected tree, as 

described below, and brought to the 

laboratory for further processing. In 

an attapt to obtain the best group of 

samples from each stem it was first 

necessary to determine the point along 

the stem most likely to sustain wind 

ge; the critical stress point 

(CSP). Observations in the field were 

used to determine the critical stress 

the average height of broken 

er-sized stems in close 

proxbity to the sample tree. Using 

this value of critical stregs point, 
Table 1--Summary of study variables 

Variable 

ge Class (FIA) 

Quadrant 

Section (tree height) 

Replicates 

Response Variable 

Mechanical properties 

Physical properties 

Levels 

1 - High risk of mortality in the near future. 

Tree lean is greater than 45O, 

2 - Moderate risk of mortality, damage may 

degrade value for use as sawlogs or 

plylogs. Tree lean 15O to 44O, 

3 - High probability of survival, risk of reduced 

growth and value degrade is minimal. Tree 

lean is less than 15". 

4 - No obvious wind damage. Tree is 

essentially straight. 

T - side of tree facing the wind during the 

storm (under tension stress), 

C - Side of tree opposite the wind direction 

(under compression stress), 

L - Left side of tree facing opposite the wind 

(under shear stress). 

R - Right side of tree facing opposite the wind 

(under shear stress), 

A - Breast height 

B - 3 feet below critical stress point 

C - Critical stress point (CSP) 

D - 3 feet above critical stress point 

E - One foot below base of crown 

15 trees per damage class 

Procedure 

Toughness (ASTM D143-93) 

Tension perpendicular to the grain (ASTM 

D143-93 ) 

Specific gravity 

Reaction Wood Present or absent 

the five 24-inch stem sections (see 

Figure 1) were cut on center at: 

A - Breast height 

B - 3 feet below critical stress point 

C - Critical stress point (CSP) 

D - 3 feet above critical stress point 

E - One foot below base of crown. 

It was expected that internal damage 

to the trees was in the form of compression failures, ring shake and 

reaction wood. Compression failures 

would be indicated by toughness testing as specified in ASTM D-143-93. 

Ring shake would be indicated by 

tension perpendicular to grain tests 

as specified in ASTM D-143-93, while 

the presence of reaction wood was 

determined by visual inspection of the 

outer 2 growth rings. 

Section 

Base of crown 

- I foot 

CSP + 3 feet 

Critical Stress 

Point (CSP) 

CSP - 3 feet 

Breast heiaht 

Poletimber (5.0 - 8.9 " DBH) 

' Pith 

Figure 1--Location of sections within 

the tree stem. 
The five stem sections were cross-cut 

into two 12-inch sections. Toughness 

specimens were taken from one of these 

12-inch sections and tension perpendicular spechens from the other 

(Figure 21, Each section was divided 

into 4 quadrants on the crosssectional plane such that 2 quadrants 

were parallel to the wind direction 

during the stom and the other 2 were 

consequently perpendicular to the wind 

direction* The quadrants parallel to 

the wind direction experienced the 

severest tension stress on the side of 

the tree facing the wind and severest 

compression stress on the side away 

from the wind. Toughness and tension 

perpendicular specimens were cut from 

each quadrant. Only straight-grained 

specimens free of knots were kept for 

testing* Reaction wood was present in 

many of the position 1 (specimen 

closest to cambium and bark) toughness 

specimens. Care was taken during 

processing to remove as little wood 

from the bark side of the specimens as 

possible. Occurrence of reaction wood 

was visually observed in the outer 2 

growth rings and recorded for each 

quadrant and section of each tree, 

Wind Direction 

Figure 2--Orientation of Toughness 

specimens in the tree stem. 

Toughness specimens were taken from 

positions 1 and 2, except in the 

higher sections of some stems with 

smaller diameter trees where it was 

not possible to obtain both specimens 

(see Figure 2). The toughness testing 

was done on 1821 samples with a 

Wiedemann-Baldwin Impact machine. 

To test for ring shake it was necessary to stress the entire length of the 

tension perpendicular to the grain 

specimen since the location of the ring 

shake was unknown, The position and 

orientation of specimens is shown in 

Figure 3. Since the traditional 

throated tension perpendicular specimen 

described by ASTM Dl43 does not stress 

the entire length of the spechen, the 

specimen was modified by using high 

strength epoxy to bond hard maple 

blocks to the bark and pith faces of 

the tension perpendicular to the grain 

specimens. Appropriate hardware was 

bolted to the maple blocks and tested 

as per ASTM standards. Only sections 

at DBH and critical stress point were 

tested first, since there was a higher 

probability of ring separation due to 

shear stress in these specimens. The 

tension perpendicular testing was done 

on 273 specimens with a Tinius Olsen 

5000 universal testing machine, 

/--...\ 

Wind Direction $2, / 

MWm3bn removed to third gtowth inuemm 

Figure 3--Orientation of tension 

perpendicular specimens in the trea 

stem* 

EXPERImNTAL DESIGN 

This study was analyzed as a split-plot 

design where the whole-plot factor was 

the four tree-damage classes each 

represented by a sub-sample of trees. 

Whole-plot replication was by means of 

blocks defined as the three sites, The 

subplot factor was a factorial combination of the five tree sections by four 

quadrants of each tree. The design was 

unbalanced which led to a complicated 

analysis* At the whole-plot level, 

there were no trees in one damage class 

for one of the sites. This resulted in 

a missing cell and, hence, only 5 

degrees of freedom for the site by 

damage claas affect instead of the 
typical 2x3=6. In addition, the 

er of trees sub-sampled in each 

site by damage class was unequal, At 

the subplot level, there were several 

missing observations at various 

section-by-quadrant treatment combinations, Due to the unbalanced nature 

of this study, approxdte F-tests 

were performed in the typical 

split-plot design fashion using the 

whole-plot and sub-plot error terms. 

The expected mean squares obtained 

from SAS (SAS Institute Inc,, 1988) 

indicated that these tests were close 

to those in the typical balanced situation. Mean separation tests were 

performed on the main factor effects 

with Tukeyfs test. General mean 

comparisons were not performed since 

they would require synthesized error 

terms using Satterthwaitefs procedure 

which was not attempted because of the 

complexity of the design, 

RESULTS AND DISCUSSION 

Toughness and Specific Gravity 

Analysis 

Results from the analysis of variance 

on toughness and specific gravity are 

shown in Table 2, while treatment 

means and Tukeyfs multiple comparisons 

for all main effects are shown in 

Table 3. The analysis was performed 

on the position I and position 2 

specimens both separately and 

combined. 

The effect of juvenile wood is evidenced by the lower values of toughness and specific gravity of the 

position 2 specimens as compared to 

the position 1 specimens. The position 2 specimens should exhibit more 

juvenile properties of lower toughness 

and specific gravity because of their 

closer proximity to the pith* 

FIA Damaqe Class Effects 

The damage class factor was not quite 

significant for toughness (P=0.07). 

Generally, toughness decreased with 

increasing damage class (i.e. highly 

ged trees had lower toughness). 

Similarly, Tukeyfs comparison tests 

showed a trend of increasing specific 

gravity with damage classification. 

Damage class effects on specific 

gravity were significant at the 0.05 

level. This trend supports the conclusion that trees with higher 

specific gravity and hence higher 

strength were better able to survive 

the effects of the storm. Perhaps 

this trend is due to the development 

of root systms. A better root system 

provides better support for the tree 

stem and is important in resisting 

windthrow and root upheaval. It seas 

logical that they develop denser wood 

tissue, since better developed root 

systems provide more nutrient and 

moisture uptake. 

The interaction of damage class and 

quadrant also had a significant effect 

on toughness (P=8,02), Figure 4 illustrates this interaction, The highest 

toughness values are concentrated near 

the tension (T) quadrant, the lowest 

values near the compression quadrant, 

and intermediate values are predominantly associated with the left and 

right quadrants. The trend is increasing toughness from damage class 1 to 4. 

The tension quadrant at damage class 4 

caused the interaction effect by not 

having higher toughness than the other 

quadrants. This may be explained by 

the low occurrence of reaction wood and 

higher specific gravity in this conbination of damage class and quadrant. 

Figure 4--Interaction of Damage Class 

and Quadrant. 

The purpose of the toughness test was 

to detect compression failures occurring on the transverse axis of the 

wood. While a trend in toughness with 

damage class was observed, it was 

probably due to the significant trend 

in specific gravity rather than the 

detection of internal damage. Compression failures were observed in 

several samples that were tested. 

However, these compression failures 

were extremely localized and their 

effects lost in the large sample of 

specimens, 
Table 2--Results from the analysis of variance (P-values)' based on a split-plot 

design. 

Position 1 and 2 Position 1 Position 2 

Source df2 Tough- SG df Tough- SG df Tough- SG 

ness ness ness 

Site 

ge Class (De) 

Site*DG 

Tree (Site*DC) 

Sect 

Quad 

Sect *Quad 

DG*Sect 

DC*Quad 

DC*Sect*Quad 

Error (b) 

Total 

(Corrected) 

Probability that main effect or interaction has no effect on the measured 

reponse. 

Degrees of freedom. 

-- means not of interest or cannot be calculated. 

Table 3--Means for toughness and specific gravity with Tukeyrs mean separation.' 

Factor Position 1 and 2 Position 1 Position 2 

Toughness SG Toughness SG Touahness SG 

( in-lbs ) ( inllbs ) ( inllbs ) 

Damage 1 

Class 2 

3 

4 

Section A 

B 

C 

D 

E 

Quadrant T 

L 

R 

C 

Means in the same Factor for a given variable not followed by the same 

letter are signifcantly different at the a = 0.05 level using Tukeyrs test. 
Section and Quadrant Effects 

The section variable reflects tree 

height and shows significant effects 

on toughness as expected (P=O,OO), 

The lower toughness associated with 

juvenile wood is evidenced by decreasing toughness with increasing section 

height. Toughness specimens become 

closer to the pith and tree crown 

higher up the stem, These specimens 

have mod tissue with more juvenile 

characteristics. The trend is identical for specific gravity which is a 

primary measure of juvenility. 

Quadrant had a significant effect on 

toughness and specific gravity (Pa 

0.00). Quadrant indicates the location of the specimen around the tree 

stem relative to the wind direction 

during the storm, The windward side 

of the stem (T) shows the highest 

toughness while the side of the stem 

undergoing compression (C) showed the 

lowest toughness, The L and R 

quadrants were always intermediate in 

toughness and closest in actual value. 

This observation is logical since the 

L and R quadrants experienced similar 

stresses, The trends are more complex 

for specific gravity with quadrant. 

It would be logical that specific 

gravity would be constant around the 

tree stem at a specific tree height. 

Therefore, we would not expect the 

quadrant to have a significant effect 

on specific gravity. The T quadrant 

of the section was significantly lower 

in specific gravity than the other 

quadrants at position 1 and 2, This 

is contrary to accepted relationships 

between wood strength and specific 

gravity, However, the occurrence of 

reaction wood offers some explanation 

of why this trend occurs, Reaction 

wood has higher specific gravity but 

lower strength. 

Occurrence of Reaction Wood 

Low average toughness values of the 

compression side specimens may be 

attributed to the high occurrence of 

reaction wood. Figure 5 illustrates 

the frequency of reaction wood occurrence in damage class by quadrant. 

The C quadrant had highest occurrence 

of reaction wood as would be expected. 

However, extensive reaction wood was 

occurring on damage class 4 trees 

which were standing straight. 

Residual stress from the storm must 

have triggered reaction wood formation 

in the following growing season. 

Considering toughness values with 

Quadrant as a factor, compression-side 

toughneas values were considerably 

lower than all others due to partial rings of reaction wood which in many 

cases had been growing since the storm, 

In some cases reaction wood extended 

into the left and right quadrants, The 

overall effect of reaction wood in the 

left and right quadrants, however, was 

less pronounced for two reasons. There 

were fewer ocCurrences of reaction wood 

in these quadrants since the reaction 

wood bands did not always extend into 

the left and right quadrants. 

Secondly, the reaction wood bands 

generally became thinner as they 

proceeded away from the compression 

quadrant so the strength reduction due 

to the reaction wood band was diminished in the left and right quadrants, 

FIA Damage Class 

Quadrant (I 3 

Figure 5--Reaction wood frequency for 

quadrant by damage class. 

Perhaps more importantly, reaction wood 

was observed in trees of all four 

damage classes. This is significant 

since even trees appearing to have no 

wind damage (i,e. not leaning), those 

of damage class 4, have a frequency of 

reaction wood as high as damage class 

1. Stress from the wind has caused 

formation of reaction wood in the two 

growing seasons after the storm even in 

trees which are straight and have no 

visible damage. The formation of 

reaction wood in leaning stems should 

continue until harvesting, however it 

is unknown how long reaction wood will 

continue to form in damage class 4 

trees which are essentially straight. 

The formation of reaction wood occurred 

almost uniformly with tree height as 

shown in Figure 6. 

Evidence of Ring Shake 

observations of failures in tension 

perpendicular to the grain showed no 

evidence of ring shake which was 

confirmed by the test results of 

tension strength perpendicular to the 
Quadrant Section 

Figure 6--Reaction wood frequency for 

quadrant by stem section. 

section variable was significant with 

mmction A significantly higher in 

tmsile strength than section C (see 

Table 4). This trend is consistent 

with observations of decreasing toughmss with tree height. Table 5 shows 

tension strength means for d 

by quadrant. It is noted that these 

average tension strength values are 

c~nsistent with the literature (Hood 

Handbook, 1987). 

Y A11JI) CONCLUSIONS 

The results of the study offer inconclusive evidence that the FIA damage 

elasses are indicative of internal 

dunage to storm-stressed trees. It was 

expected that compression failures and 

micro-fractures would be found to have 

a varying effect on toughness and that 

ring shake would have a similar effect 

on tension perpendicular to the qrain 

in a manner consistent with the FIA grain. There were no significant damage classes; but this relationship 

differences found in tension strength was marginally significant for toughfor damage class or quadrant. The ness strength and nonexistent for 

Table 4--Mean tension strength values by stem section 

Damage Class 

Section 

A C Damage Class Means' 

Section Means6 

Damage class means were not significantly different at the 0.05 level. 

Section means were siginifcantly different at the 0.05 level. 

Table 5--Mean tension strength values by Quadrant 

Damage Class 

Class Heans 

Quadrant ~eans? 

' Quadrant means were not significantly different at the 0.05 level. 
tension strength perpendicular to the 

grain, Several interesting patterns 

did arise however. Specific gravity 

was a factor in determining the extent 

ge. The specific gravity 

measurements made on the toughness 

specimens do offer some explanation as 

to the nature of wind damage. In 

particular, with damage class as the 

whole plot factor, the specific 

gravity values of position 1 specimens 

fall into a pattern. Here again we 

consider only the position 1 specimens 

to avoid the highly variable juvenile 

wood present in most position 2 specimens. Moving from damage class 1 to 4 

specific gravity shows an increasing 

trend and significantly different 

means between damage classes 1 and 4 

at the .05 level using Tukey's test. 

The trees most resistant to wind 

damage, those classified in damage 

class 4, were found to have the 

highest average specific gravity. 

Thus there is a negative relationship 

between wind damage, as defined by the 

FIA damage class system, and wood 

density. Other studies (Foster, 1988 

and Studhohe, 1989 for instance) have 

shown this negative relationship 

between sustained wind damage and 

specific gravity. The variation of 

toughness and specific gravity could 

be explained in part by the occurrence 

and extent of reaction wood observed. 

The relatively higher specific gravity 

and lower strength of reaction wood 

will impact the utilization of these 

trees. 

In conclusion, with dwindling timber 

resources it will become more important to correctly determine the shortterm as well as long-term effects of 

catastrophic storms on our timber 

resources. While the FIA visual 

damage classification system was 

developed to predict risk of mortality, it has been shown not to be 

an indicator of internal damage as 

measured by loss of mechanical 

properties. FIA damage class was a 

good indicator of the wood quality in 

the tree as measured by specific 

gravity. 

The high occurrence of reaction wood 

as measured in this study indicates 

that residual stress from the storm 

caused reaction wood in all damage 

classes. It is likely that reaction 

wood formation will continue in 

leaning stems (damage classes 1 to 3). 

Further study is needed to determine 

if non-leaning trees will continue 

reaction wood formation. The formation of reaction wood appears to be the 

major damage to trees still standing 

after the storm. 

- ACKNOWLEDGEMENTS - 

Support for this study was provided by 

the Southeastern Forest Experiment 

Station, USDA Forest Service, 

Asheville, North Carolina, 28802, 

Gratitude is expressed to Michael 

Thompson (Forester, Forest Inventory 

and Analysis, Asheville, NC) for 

evaluation of the standing poletimber 

in the Francis Marion National Forest. 

LITERA'IZURE CITED 

American Society for Testing Materials. 

Standard D143-93, 1993. Toughness and 

Tension Perpendicular to the grain 

procedures, Philadelphia, PA. 

Ehinger, L. H. 1990. Hurricane Hugo 

Damage. Annual Conference of the 

International Society of Arboriculture 

in Toronto, Ontario, August 1990. 

Foster, D. R. 1988. Species and Stand 

Response to Catastrophic Wind In 

Central New England, USA. Journal of 

Ecology 76~135-151. 

Mayer, H. 1988. Windthrow. Philosophical Transactions of the Royal 

Society of London. Series B, Biological Sciences. 1989, 324:1223, 

267-281 

Sheffield, R. M. and Michael T. 

Thompson. 1992. Hurricane Hugo--Effects 

on South Carolina's Forest Resource, 

Southeastern Forest Experiment Station 

Research Paper SE-284. June 1992. 

Studholme, W. P. 1989. Windthrow on the 

Canterbury Plains. Workshop on Wind 

Damage in New Zealand Exotic Forests. 

FRI bulletin 146. Forest Research 

Institute, Ministry of Forestry, PV 

3020, Rotorua, New Zealand. 

SAS Institute Inc. 1988 SAS/Stat Users 

Guide, Release 6.03 Edition, Cary, NC: 

SAS Institute Inc. 1028 pp. 

Webb, S. L. 1988. Windstorm Damage and 

Microsite Colonization in Two Minnesota 

Forests. University of Minnesota, 

Department of Ecology and Behavioral 

Biology, Minneapolis, Minnesota 55455. 

Wood Handbook: Wood as an engineering 

material. Forest Products Laboratory. 

Agric. Handb. 72, Washington DC: USDA 

rev. 1987. 466 p. 
OCCURRENCE OF COMPRESSION WOOD IN 

HUMICME-STmSSED PINE POLETI-ER 

Timothy D. ~aust', Mark Fuller, and Robert H. McAlister 

Abstract--Occurrence of compression wood in hurricanestressed pine poletimber was evaluated by Forest Inventory 

Assessment (FIA) storm damage class, tree height and tree 

radius (orientation to the wind). As expected, occurrence 

of compression wood was highest on the radius of the tree 

subjected to compression stress from the wind and the lean 

of the tree. However, trees that had no visible damage 

from the wind (i.e. not leaning) had the same occurrence of 

compression wood as the most severely damaged trees (FIA 

damage class 1). This would imply that stress from the 

storm induced the tree cambium to form compression wood 

even though the main stem was not leaning. Compression 

wood occurrence was slightly higher at the base of the 

crown where strain on the stem was greatest. Stands with 

leaning poletimber will probably continue to form compression wood and should be harvested instead of allowing it to 

mature into sawtimber. 

The authors are Associate Professor (706-542-1122), Graduate Assistant, 

University of Georgia, Warnell School of Forest Resources and Forest Products 

Technologist, USDA Forest Service, Southeastern Forest Service Experiment Station, 

Athens, Georgia 30602. Support for this study was provided by the Southeastern 

Forest Experiment Station, US Forest Service, Asheville, North Carolina. Gratitude 

is expressed to Michael Thompson (Forester, USDA Forest Service) for evaluation of 

the standing poletimber in the Francis Marion National Forest. 
OF TESTING THE FULL CROSS 

TENSION PERPENDICULAR TO 

-SECTION OF 

THE GRAIN 

WOOD 

Timothy D. Pnust, Mark Fuller, and James T. ice' 

Abstract--This report describes a method of testing wood 

specimens in tension perpendicular (TP) to the grain 

whereby the entire cross-section of the wood may be 

subjected to stress. This method makes it possible to use 

tension perpendicular testing to detect internal tree 

damage such as ring separation through the entire radius of 

the tree. The testing procedure is performed on a solid 2- 

by 2-inch variable length test specimen where tensile 

stress is transferred to the test specimen through hard 

maple blocks which are glued to the pith and bark faces of 

the test specimen. The work was prompted by a study of 

storm damaged trees in the Francis Marion National s ore st'. 

As part of the study sections were removed from sixty tree 

stems. A total of 273 specimens were tested. Tensile 

strength and break location were the primary variables of 

interest. Although the results show no conclusive evidence 

of internal damage, the test may be a useful alternative to 

the standard ASTM 143-83 for full cross-section testing of 

tension perpendicular to the grain. 

INTRODUCTION 

The evaluation of storm damage to 

timber as a result of Hurricane Hugo 

has prompted work in accessing not 

only the damage in terms of felled 

timber but also damage to timber that 

is still standing and will continue to 

mature. Of particular interest to 

forest managers a r e t h e poletimbersize (5.0 to 8.9 inches DBH) trees 

that will mature into the sawtimber of 

the future. Winds in excess of 135 

miles per hour caused considerable 

stress to even poletimber-size trees. 

There is the potential for internal 

damage to these trees in the form of 

compression failure, ring shake (ring 

separation) or development of compression wood which would reduce their 

utility for higher value solid wood 

products such as stress graded lumber 

and plywood veneer. 

To test the tree stem for internal 

damage in the form of ring shake, a 

modified method of ASTM D143-83 was 

devised3. The standard method for 

testing tension perpendicular to the 

grain uses the outer material of the 

test specimen for gripping purposes 

and the material is not subject to 

tension stress (see Figure 1). Since 

the actual location of potential ring 

shake in the tree stem is unknown, it 

is desirable to subject the full crosssection of the wood to tensile stress. 

This paper describes the methods and 

equipment that were devised to 

accomplish this. 

The authors are Associate Professor, 

Graduate Research Assistant and Associate Professor, Warnell School of 

Forest Resources, University of 

Georgia, Athens, Georgia. Support was 

provided by the US Forest Service 

Southeastern Forest Experiment Station, 

Athens, Georgia under contract #12-11- 

008-876. 

Faust, T,D,, Mark Fuller, and Robert 

H. McAlister, 1992. Assessing Storm 

Damage to standing Pine Poletimber in 

the Francis Marion National Forest. 

Final Report for Cooperative agreement 

#12-11-008-876 by Southeastern Forest 

Experiment Station and University of 

Georgia Agricultural Experiment 

Station. 

ASTM D143-83, Tension perpendicular 

to the grain. Small clear specimens of 

timber. American Society for Testing 

and Materials, Philadelphia, PA. 

V04.09, pp. 55-56, 
Figure 1--ASTM D143-83 test specimen 

for tension perpendicular to the 

grain, 

OBJECTIVES 

This research was conducted to develop 

a method of testing Loblolly and longlead pine in tension perpendicular to 

the grain across the full crosssection of the wood. To accomplish 

this several objectives were defined, 

Evaluate various adhesives in 

bonding the test jig to longleaf 

and loblolly pine to exceed its 

tensile strength, 

Develop a test jig to grip a 

wood specimen to transfer uniform tension stress through the 

full cross-section and cause it 

to fail in tension perpendicular 

to the grain. 

METHODS 

Initially the test jig consisted of a 

2- by 2-inch steel tab with a grippable pin welded onto the back as 

shown in Figure 2a. These pull tabs 

were described by Knowles (1981)4. 

In this case, each TP specimen is 

prepared by bonding one tab to the 

bark side and one tab to the pith side 

of the wood specimen and tensile 

stress is applied to the test specimen 

through the pins, Several hot melt 

Rnowles, Lorence. 1981. Rapid 

method to deternine internal bond and 

density variations of particleboard. 

Forest Products Journal 31(12):51-53. 

Figure 2--A, metal tab; Be hard maple 

block; C. backing plate. 

and epoxy adhesives were used to bond 

the plates to the wood specimens. We 

found that the metal to wood interface 

did not provide sufficient adhesive 

strength. Virtually all failures of 

these TP specimens occurred at the 

adhesive-plate interface. In some 

cases a few wood fibers were removed 

from the wood specimen, but, in no 

cases did failure occur at a significant distance from the bark or pith 

side face of the specimens. The metal 

plates were abandoned in favor of a 

wood to wood interface. A method was 

designed whereby the pine specimens 

could be glued to hard maple blocks and 

with some appropriate hardware the 
blocks could then be used to transmit 

tensile stress to the pine specimens. 

Hard maple was chosen since it has a 

higher TP strength value than the pine 

species. The adhesives tested here 

were PVA, several hot melts, and a 

high-strength epoxy. Epoxy was chosen 

since it provided the needed bonding 

strength and did not require clamping 

due to its gap-filling ability. The 

test block design is shown in Figure 

2a and its construction and use are 

described below, 

Construction 

First machine eight-quarter maple 

lumber into 2- by 6-inch blocks where 

the grain runs along the 6-inch axis. 

This grain direction utilizes the 

maximum strength of the maple block 

during testing. Next machine the 2- 

inch-wide slot 'bf into the center of 

a tangential face of the block as 

shown in Figure 2a. This tangential 

face will be considered the upper 

face. The metal tab of Figure 2a 

should fit snugly into the groove and 

its top side should be flush with the 

upper face of the block as shown in 

Figure 3. Now referring again to 

Figure 2, drill the six 3/8-inch holes 

.cf. Next drill the larger holes for 

the heads of the bolts to fit into. 

These holes are drilled concentrically 

with the 3/8-inch holes but from the 

lower tangential face of the block. 

The outline of one of the holes is 

shown in Figure 2b. The drill press 

should be set so that the 3/8-inch 

holes remain intact to a depth of 

about one inch from the upper face. A 

large drill bit may be spun by hand to 

remove any loose wood material from 

the edge of the holes after drilling. 

Now the test block is ready to be 

assembled. Insert the metal tab into 

slot b and insert the six bolts from 

the lower tangential face so that the 

threads extend out of the top 

tangential face as shown in Figure 4. 

A 810-32 x 1 112-inch bolt works well. 

Place the 1/4-inch steel backing plate 

over the screws and fasten it into 

place. 

Use 

The first step is to glue the wood 

specimens onto the lower face of the 

maple blocks. The grain direction of 

the block and wood specimen should be 

parallel. In aligning the pine 

samples in the jig it was helpful to 

place pencil marks along the radial 

face of the test blocks. These marks 

are shown as lines 'a@ in Figure 2b 

and may be seen also in Figure 5. A 

Figure 3--Maple block with inset for 

metal pull tab. 

Figure #--Metal tab in position with 

backing plate. 

Figure 5--Completed ass 

testing 
holding table lnay be easily constructed with a flat piece of plywood 

or fiber board and thin pieces of wood 

on which the block can rest with its 

upper face turned downward. This 

arrangement can be seen in Figure 5, 

Eilany blocks may be prepared simultaneously using the holding table, To 

inhibit movement of the specimens 

during adhesive cure, dowels which are 

long enough to span the full length of 

the holding table may be placed on the 

lower face of the blocks and clamped 

against the end grain of the TP 

specimens, In our case, we glued the 

first block, allowed it to dry, and 

then glued the second block, Depending on the clamping assembly used, it 

may be possible, and certainly more 

desirable, to glue both blocks at 

once. An epoxy-type adhesive was used 

to attach the pine specimens to the 

blocks. The completed test specimen 

is shown in Figure 5 and is ready to 

be tested, After testing, the two 

halves of each specimen may be placed 

next to each other on the holding 

table and conveniently interpreted. 

Before a test block can be reused it 

is necessary to remove wood and 

adhesive material from the lower 

tangential face to ensure a good bond 

with the next TP specimen. This may 

be done by sanding the center of each 

block to remove most of the material 

and then jointing to ensure a flat 

surface. Care should be taken to keep 

the top and bottom faces parallel so 

the stresses induced during testing 

are in fact perpendicular to the grain 

of the test specimens. By removing 

just enough material from the lower 

face of the blocks they may be used 

thirty to forty times. Also the bolts 

may need to be tightened after each of 

the first few uses as the heads of the 

bolts become seated. 

RESULTS 

Specimens were stressed to failure and 

data was recorded for tensile strength 

and location and type of break. A 

total of 273 specimens were tested. 

The tensile strength statistics for 

the 273 test specimens are shown in 

Table 1. 

The following conventions were adopted 

in describing the type and location of 

break in Table 2. 

Any given test specimen may require 

one or more codes to be fully 

Table 1--Average tensile strength for 

all specimens, 

Tensile Strength flbsl/sq. in1 

# obs Mean Plinhm/ ST11 COV 

Table 2--Summary of codes defining 

failure mode. 

Code Break position/type 

G Fracture along growth increment 

P Break near pith-side glueline 

B Break near bark-side glueline 

M Break near mid-section of 

specimen 

R Break along radial plane 

X% *Xf% of fracture surface along 

a glue line 

PI? Fracture at pitch pocket 

described. For instance a fracture 

described by the mnemonics "P, 20%" 

would indicate that the specimen 

fractured near the pith side and that 

20% of the surface exposed by the 

fracture was along the glueline. 

Interpretation of the results could 

take one of several paths. Ideally the 

glueline should be as strong as the 

test specimen. A measure of the relative strength of the glueline to test 

specimen, and hence the success of the 

testing procedure, is the percentage of 

glueline exposed in the tested samples. 

The following table illustrates one 

possible breakdown where the percentage 

categories were arbitrarily chosen, 

Table 3--Summary of average tensile 

strength by percent glueline failure. 

% glue line 0 to >lo% >30% >60% 

failure 10% to 30% to 60% 

% of observations 53.8% 14.7% 12.8% 18.7% 

Average tensile 

strength (psi) 489.73 520.91 512.75 481.63 

Coefficient of 

Variation 0.1815 0.1456 0.1537 0.2038 
At first glance, these results may 

seem unsettling in that 18.7% of all 

specimens tested resulted in >60% 

glueline failure; however, the average 

tensile strength of these observations 

was 495.7 lbslsq. in. with a range of 

243.3 lbs/sq. in. to 727 lbs./sq. in. 

The average strength is not significantly different with reported tensile 

strength of 470 psi for both longleaf 

and loblolly pine (Wood Handbook, 

1987)5. Differences in strength 

between failure classes are also not 

significant (a = 0.05). 

CONCLUSIONS 

Although the results are open to 

interpretation, the test assembly as 

described was able to impart sufficient stress to the longleaf and 

loblolly pine specimens to reveal 

internal damage in the form of ring 

shake. This is supported by the fact 

that the average TP strength of the 

test specimens exceeded reported 

average TI? strength in the literature. 

There were some problems with glueline 

quality where failure did not occur 

through the test specimen. Glueline 

quality may restrict the use of this 

method for use as a measure of tensile 

strength but this problem is not 

insurmountable. Clamping would have 

helped to reduce variation in glueline 

quality by forcing more intimate contact between test blocks and pine 

specimens and by reducing the frequency of air bubbles. Other adhesives such as straight resorcinol could 

also be explored. 

This procedure is not intended to 

replace the present ASTM method of 

tension perpendicular testing. Its 

intent was to reveal ring-separation in 

wind damaged poletimber, and although 

no evidence of internal damage was 

found, the results seem to show that 

the test is appropriate for this 

purpose. 

WQC)~ Handbook: Wood as an 

Engineering Material, 1987. USDA Reprinted with permission from Forest 

Agricultural Handbook No. 72. Forest Products Journal 44(3):23-26, Dr. Art 

Products Laboratory, US Dept. of Brouner, Editor, 2801 Marshall Ct,, 

Agriculture. Washington, DC. 466 p. Madison, WI 53705. 
EFFECTIVENESS OF WATER SPRINKLING FOR 

LONG-TERM STORAGE: OF 

John B. Syme and Joseph R. ~aucier' 

Abstract--Loblolly pine sawlogs were stored under water 

sprinklers for a two-year period to determine the 

effectiveness of different sprinkling schedules on 

preventing infestation by insects and fungi. Onehundred-twenty freshly-harvested test logs were 

selected from the same timber tract for the project. 

One-half of the logs were placed under water sprinklers 

immediately after harvest, while the other half were 

dry-stored from one to six months and then placed in 

the sprinkled decks. The test logs were stored in four 

separate sprinkled decks, each with a different sprinkling schedule. The test logs were sampled periodically to determine moisture content, presence of fungi 

and insects, and change in mechanical properties. At 

the end of the two-year sprinkling period, the test 

logs were processed in a sawmill and veneer plant to 

determine the extent of degradation by fungi and 

insects. The continuous-heavy sprinkling schedule 

afforded the best protection to the logs of the four 

sprinkling schedules; there was no visible evidence of 

blue stain fungus, pine sawyers, or ambrosia beetles 

after two years of sprinkler storage. Logs in decks 

with other sprinkling schedules with lower water 

volumes showed various amounts of fungal and insect 

degradation, relative to the volumes of water applied. 

Some mechanical properties appeared to be affected by 

long-term sprinkling: tangential toughness was significantly lower at the end of the test period, while 

modulus of rupture, modulus of elasticity, and radial 

toughness were not reduced by a significant amount. 

The logs which were dry-stored prior to sprinkling, 

became infested with fungi and insects during the 

second month of dry-storage, and were heavily infested 

by the fourth month. 

INTRODUCTION 

The temporary surplus of sawlogs 

resulting from the large volume of 

blow-down timber by Hurricane Hugo in 

1989, has raised several important 

questions about the long-term effects 

of storing southern pine logs under 

Lecturer, Department of Forest 

Resources, Clemson University, 

Clemson, SC 29634-1003; and Project 

Leader, Southeastern Forest Experiment 

Station, USDA Forest Service, Athens, 

GA 30602-2044 

water sprinklers. Beyond general 

guidelines, inadequate information is 

available concerning the rate of 

deterioration of logs stored under 

water sprinklers for long periods of 

time. 

Previous research indicates that water 

sprinkling provides protection from 

insects and fungi if the sapwood moisture content is maintained above 100 to 

120 percent, oven-dry basis (Liese 

1984, Volleman 1966). Logs which have 

lost moisture, prior to placing them in 

sprinkler storage, are subject to 
attack by insects and fungi until the 

moisture content reaches the above 

threshold level. Information relating 

to the rate of moisture pickup by logs 

under sprinklers was not found in the 

literature. Also, some researchers 

suggest that continuous sprinkling is 

necessary to reach and maintain the 

desired moisture content (Mason and 

others 1963, Wagner 1976), while 

others believe that intermittent 

sprinkling is adequate (Miller and 

Swan 1980, Roff and Dobie 1968). 

Another important question relates to 

possible strength losses due to 

sprinkling. Anaerobic bacteria may 

invade the sapwood of logs in sprinkler storage and degrade the cell 

walls, thereby increasing the porosity 

of the sapwood. It is not clear 

whether or not the strength of the 

wood is affected, since past research 

results were controversial and 

involved relatively short periods of 

storage (Lutz and others 1966, Scheld 

and DeGroot 1971). 

The purpose of this research was to 

develop more information related to 

the effects of different sprinkling 

configurations on the long-term 

storage of southern pine sawlogs. The 

study, conducted at a sawmill in 

Cameron, South Carolina, began in 

April 1991 and ended in May 1993. 

METHODOLOGY 

The loblolly pine (Pinus taeda) test 

logs were from trees harvested in the 

upper coastal plain of South Carolina. The trees were approximately 35 

years old. A 34-foot-long butt sawlog 

was cut from each of the 120 trees 

harvested. Immediately following 

harvest, the test logs were trucked to 

the research site and prepared for the 

sprinkling experiment. Each log was 

assigned a permanent identification 

number and all test data were recorded 

on the basis of individual logs. 

Moisture content and specific gravity 

discs were taken from both log ends, . 

large- and small-end diameters were 

measured and recorded, and a threefoot section was removed from the 

large end of every fifth log for 

strength tests. 

One-half of the sawlogs were divided, 

at random, into four groups of 15 logs 

each. Each group of logs was placed 

under a different water sprinkling 

schedule : 

Group 1. Intermittent 

Sprinkling, "Heavy" Water Volume 

Group 2. Intermittent Sprinkling, 

"Light" Water Volume 

Group 3. Continuous Sprinkling, 

"Heavy" Water Volme 

Group 4. Continuous Sprinkling, 

"Light" Water Volume 

The remaining 60 logs were stored 

unsprinkled in the logyard. At onemonth intervals, over a six-month 

period, a portion of the unsprinkled 

logs was placed in each of the above 

sprinkled decks. At the end of six 

months, all of the test logs were in 

the four sprinkled decks. Prior to 

placing each monthly set of logs under 

sprinklers, the logs were sampled for 

moisture content and specific gravity 

determination and for degree of fungal 

and insect infestation. 

The sprinkling site was located at a 

sawmill, where the research sprinkling 

system was connected to the logyard 

sprinkling system. A closed-loop 

system was utilized with runoff water 

collected and recirculated. standard 

impact irrigation sprinklers were used 

with water pressure maintained at 40 

psi at the sprinkler head. A 1/8-inch 

diameter nozzle orifice, rated at 2.9 

gallons per minute, was selected for 

the "Light" sprinkling; and a 3/16-inch 

diameter nozzle orifice, rated at 6.4 

gallons per minute, was selected for 

the "Heavy" sprinkling condition. The 

intermittent sprinkling schedule, for 

both "Heavy" and "Light" conditions, 

was 60 minutes on and 120 minutes off, 

24 hours each day. The system was 

monitored closely throughout the twoyear test period to ensure that all 

sprinklers were operating properly and 

that the proper water pressure was 

maintained. Actual sprinkler output, 

in inches of water per day, was 

measured with rain gauges: 

Inches of 

Water per 

Sprinklinq Schedule 24-Hour Day 

Intermittent-Light 0.7 

Intermittent-Heavy 1.3 

Continuous-Light 2.2 

Continuous-Heavy 4.0 

At three-month intervals, moisture content discs were cut, at random, from 

both ends of one-third of the logs in 

each of the sprinkled groups. Outer 

sapwood and inner sapwood (near the 

center of the log) sections were taken 

from each large-end disc. Because of 

the smaller diameter, only outer 

sapwood sections were taken from the 

small-end discs. The sections were 
weighed, dried in an oven (105 degrees 

F,), reweighed, and the oven-dry moisture content calculated, Specific 

gravity was determined by the immersion method, The discs were also 

visually inspected for evidence of 

fungal and insect infestation. 

At the beginning and end of the twoyear test period, a three-foot-long 

section was cut from the large end of 

one-third of the logs in each sprinkled group for strength, stiffness and 

toughness testing. The green test 

specimens (four replications for each 

test) were left over-sized and dried 

to approximately 10 percent moisture 

content. They were then jointed to 

final dimensions and stored at ten 

percent ElJlC prior to testing, 

The static bending tests were conducted using 1-by 1-by 16-inch 

specimens with center loading over a 

14-inch span following the procedures 

in ASTM Dl43 pp, 245-252- Specimens 

were weighed and measured at mid-point 

prior to testing, Load deflection 

data were taken at three second intervals, the slope of the load-deflection 

line was determined using linear 

regression (minim= acceptable R~ > 

0,95), and the modulus of elasticity 

and modulus of rupture were calculated, These data were summarized for 

each storage period. Specimens were 

oven-dried after testing and moisture 

contents at time of test calculated. 

The toughness tests were conducted 

using 0.79-by 0.79-by 11-inch specimens over a 9-47-inch span following 

procedures in ASTM D-143 pp. 71-76 and 

FPL Report No. 1308 Forest Products 

labor at or^ Touqhness Testinq Machine. 

Tests were performed with the weisht 

in position-4 and an initial angl; of 

60 degrees. All specimens were 

weighed and measured in the radial and 

tangential directions at mid-point 

prior to testing, Specimens were 

tested in both the radial and tangential modes, Spechens were oven-dried 

after testing and moisture contents at 

the of test were calculated. 

At the end of the two-year sprinkling 

period, the surface of each test log 

was visually exarnined for insect and 

fungal infestation. Additionally, a 

section from each test log was processed in a veneer plant or sawmill. 

A veneer hlt, 103 inches in length, 

was taken from the large end of onehalf of the test logs for processing 

into veneer. Ths green sheets sf 

veneer from each Bolt were examined 

and the degree of blue stain 

(Ceratocystis pfni), 

f Platypus flavicornis) , and pine sawyer 

(Nonochmus titillator) infestation was 

recorded. A 12-f oot-long sawlog was 

cut from the large end of the remaining 

one-half of the test logs for processing in the sawmill. Each sawlog was 

sawed in half on a sawmill headrig, the 

exposed surface was examined, and the 

degree of fungal and insect infestation 

was recorded, 

A rating system was devised by which to 

classify the extent of fungal and 

insect infestation in the test logs, the veneer from the veneer bolts, and 

the sawlogs. This was based on the 

percent of surface area infested, 

estimated visually: 

Slight -- Less than 10 percent 

Light -- 10 to 24 percent 

Medium -- 25 to 39 percent 

Heavy -- 40 percent or higher 

RESULTS 

The initial data gathered on the 

freshly cut 34-foot-long test logs were 

in agreement with the typical moisture 

and specific gravity relationships 

which have been previously reported 

(Koch 1972)- For example, the specific 

gravity of the outer sapwood specimens 

from the large end averaged 0.59 as 

compared with the small-end average of 

0-48. Outer sapwood moisture content 

at the large end averaged 68 percent 

versus 107 percent at the small end, 

Moisture content was inversely proportional to specific gravity. Average 

moisture content and specific gravity 

determinations of samples from the test 

logs are summarized in Table 1. 

Table 1--Moisture content and specific 

gravity of samples from all 120 test 

logs at beginning of test. 

Moisture Specific 

Mean Range Mean Range 

Outer Sapwood 68% 49- 99% 0.59 0.45-0.71 

Inner Sapwood 93% 55-184% 0.50 0.37-0,64 

Small End 

Outer Sapwood 107% 76-138% 0.48 0.41-0.59 

The initial moisture content and 

specific gravity of the samples from 

the large end of the 60 test logs, by 

sprinkled dock, are s arized in %able 

2. Differences in average initial 
moisture content axtong sprinkler decks 

were small, as were differences in 

average specific gravity. 

Table 2--Initial moisture content and 

specific gravity of samples from the 

large end of 60 test logs under 

different water sprinkling schedules 

for two years. 

Moisture Specific 

Sprinkling Large End Content Gravity 

Schedule Log Dim, Inner Outer Inner Outer 

(inches) (percent) (percent) 

Average 11.9 93 71 0.50 0.59 

IH - Intermittent - Heavy 

IL - Intermittent - Light 

CH = Continuous - Heavy 

CL 5 Continuous - Light 

Results from Logs Placed Under 

Sprinklers at the Beginning of 

the Test Period 

Moisture Increase 

After the initial three months of 

sprinkling, the outer sapwood reached 

an average moisture content of 99 

percent and the inner sapwood an 

average of 111 percent. This represents a 29 percent increase in moisture content for the outer sapwood and 

an 18 percent increase for the inner 

sapwood. The average moisture content 

after three months of sprinkling 

ranged from 92 to 111 percent among 

sprinkling decks for the outer sapwood 

and 104 to 116 percent for the inner 

sapwood. Monthly moisture sampling 

during this period showed a different 

rate of moisture increase in both the 

outer and inner sapwood for each of 

the four sprinkling schedules: 

Initial wnthly 

Moisture Increase 

Outer Inner 

Sprinklinq Schedule Sapwood Sapwood 

(percent) 

Deck 1: Intermittent-Heavy sapwobd sapwood 

Deck lr Intermittent-Heavy 16 7 

Deck 2 t Intermittent-Light 9 5 

Deck 32 Continuous-Heavy 3 0 13 

Deck 4: Continuous-Light 21 9 

During the second three-month period, 

the moisture eontent of samples from 

the large end of the test logs 

increased at a much slower rate than 

the initial period, with the outer 

sapwood reaching an average of 104 

percent and the inner sapwood 120 

percent. The moisture content levels 

reached equilibrium by the end of the 

third three-month period of sprinkling 

for the outer sapwood and by the end of 

the fifth three-month period for the 

inner sapwood. No significant increase 

or decrease in moisture content was 

seen fox the raainder of the two-year 

period. Table 3 shows the beginning 

and ending moisture content and moisture gain during the two-year period 

under the different sprinkling 

schedules. 

Table 3--Beginning and ending moisture 

content and moisture gain of samples 

from the large end of 60 test logs 

under different water sprinkling 

schedules for two years. 

~eginninq Endinq 

MC MC MC Gain 

Outer Sapwood 

Intermittent - Heavy 7 2 

~ntermittent - Light 7 4 10 7 3 3 

Continuous 

- Heavy 6 9 105 3 6 

Continuous 

- Light 6 7 101 34 

Inner Sapwood 

Intermittent - Heavy 9 3 135 

~ntermittent 

- Light 9 2 126 34 

Continuoua 

- Heavy 9 0 136 4 6 

Continuous 

- Light 9 0 130 4 0 

Funqal and Insect Infestation 

Results from the visual examination of 

the test log surfaces which were under 

water sprinklers for the entire twoyear period are shown in Table 4. None 

of the test log surfaces, regardless of 

sprinkling schedule used, showed evidence of blue stain or pine sawyer 

infestation. All logs in the two decks 

with intermittent sprinkling schedules 

had heavy levels of 

damage, while there was no indication 

of ambrosia beetle damage in the logs 

in the two decks with continuous 

sprinkling schedules. 

Table 5 gives the results of the visual 

examination of the veneer from the 

veneer bolts and the sawlogs from the 

test logs which were under sprinklers 

for the entire two-year period. 
"Slight" to "light" amounts of blue 

stain were present in logs in all 

sprinkled decks except the continuousheavy deck, where none was found, 

Lags in both continuous sprinkled 

decks showed no signs of infestation 

rosia beetles, while both 

intermittent sprinkled decks had 

significant mounts of ambrosia beetle 

infestation. None of the logs in the 

four sprinkled decks showed any 

evidence of pine sawyer infestation. 

Table 4--Visual examination of the 

exterior surface of test logs which 

were under four sprinkling schedules 

for the two-year test period. 

Degree of Infestation* 

Blue Ambrosia Pine 

- Stain Beetle Sawyer 

Log Deck L 

Intermittent - Heavy None Heavy None 

Intermittent - Light None Heavy None 

Continuous - Heavy None None None 

Continuous - Light None None None 

* None, Slight, Light, Medium, or Heavy 

Table 5--Visual examination of lumber 

and veneer from test logs which were 

under four sprinkling schedules for 

the two-year test period. 

Sprinkling Type of Infestation 

Schedule Blue Ambrosia Pine 

Stain Beetle Sawyer 

Intermittent Light Medium None 

- Light 

Intermittent Slight- Light- None 

- Heavy Light Medium 

Continuous Slight None None 

- Light 

Continuous None None None 

- Heavy 

Mechanical Properties 

The results of the strensth tests, 

from samples from the same logs, at 

the beginning and end of the two-year 

test period shows that there was no 

significant change in modulus of rupture, modulus of elasticity, and 

radial toughness. Tangential toughness was significantly lower at the 

end of the sprinkling period than at 

the beginning. Data from the mechanical tests are s xized as follows: 

Beqlnnxnq Ending 

Specific Gravity 0.58 0.55 

Modulus of Rupture 

(lo3 psi) 17.4 15.0 

Modulus of Elasticity 

!lo6 psi) 1.62 1.58 

Unrt Toughness - 

Radial (psi) 40.1 30-7 

Unit Toughness - 

Tangential (psi) 63-5 39-2 

Results from Logs Which Were 

Dry-Stored Prior to Sprinkling - - Moisture Chanqe 

The test logs which were dry-stored for 

one to six months, prior to- being 

placed in the four sprinkled decks, 

showed an increasing loss in moisture 

content as the dry-storage time was 

increased. The average moisture loss 

in the outer sapwood of samples taken 

from the large end of the test logs at 

the beginning and end of the drystorage period are shown below: 

Outer Sapwood 

Dry Storaqe Time Moisture Loss 

(Months ) (Percent ) 

The gain in moisture content, after the 

dry-stored logs were placed under 

sprinklers, took place at a different 

rate for each of the four sprinkling 

conditions. Generally, the rate of 

moisture gain was directly related to 

the volume of water applied to the 

logs. The rate of moisture gain was 

highest during the initial sprinkling 

period and slowed as log moisture 

content increased, 

The average outer sapwood moisture 

gain, after the first month under 

sprinklers following dry storage, is 

summarized as follows for each 

sprinkling schedule: 

Percent Gain in 

S~rinklins schedule Moisture Content 

Intermittent - Light 13 

Intermittent - Heavy 22 

Continuous - Light 27 

Continuous - Heavy 38 
An important factor is the time 

required for the outer sapwood to 

reach the threshold moisture content 

(assumed to be 100 percent) after the 

logs have been placed under the 

sprinklers. An analysis of the rate 

of outer sapwood moisture gain among 

the four sprinkling schedules, based 

on stratified sampling of logs drystored three months and five months 

prior to placing under sprinklers, is 

shown in Figures 1 and 2. This comparison shows that logs under the 

Continuous-Heavy sprinkling schedule 

reached the threshold moisture content 

sooner than the logs under the other 

schedules, Logs under the 

Intermittent-Light schedule did not 

reach the threshold moisture level, 

Funqal and Insect Infestation 

Sections were removed from the drystored logs and taken to the laboratory for visual inspection of two 10 x 

10 centimeter areas from each log 

section. The areas were examined for 

presence of blue stain, pine sawyers, 

and ambrosia beetles, Twenty-eight 

logs were sampled after dry storage 

from one to six months and again at 

the end of the sprinkling period. 

Blue stain was found in all samples, 

at the end of one to six months of dry 

storage; however, at the end of the 

sprinkling period, the amount of blue 

stain had not increased in any of the 

samples. No evidence of pine sawyers 

was found in samples from logs drystored for one and two months; 

Intermittent-liqht i j IntermitUurt-Heavy - ..j 

Continuour-light a 1 Contimom-Heavy S : 

I 

Figure 1--Average gain in moisture 

content of outer sapwood samples from 

the large end of test logs which had 

been dry-stored and then placed in 

sprinkled decks with different 

sprinkling schedules, 

however, logs dry-stored for three to 

six months were heavily infested with a 

total of 18 entrance holes and 7 exit 

holes in the 56 sample areas ex 

At the end of the sprinkling pe 

samples from logs under the two intermittent schedules showed an increase in 

pine sawyer infestation, while samples 

from logs under the two continuous 

schedules show& no increase, rosia 

beetles were present in 25 percent of 

the samples from logs dry-stored from 

one to three months, as compared to 100 

percent for logs dry-stored three to 

six months, At the end of the sprinkling period, eight log sections showed 

no evidence of ambrosia beetle infestation, while evidence was found in the 

remaining twenty log sections; the 

eight logs not infested had been stored 

in decks with the two continuous 

sprinkling schedules, 

The mill processing of the veneer bolts 

and sawlogs from the test logs which 

were in dry storage for up to six 

months, prior to being placed under 

sprinklers, revealed increasing amounts 

sf infestation by blue stain, rosia 

beetles, and pine sawyers as dry 

storage time was increased, Generally, logs in dry storage for one month 

had light levels of infestation, while 

logs in dry storage for five and six 

months had heavy levels of infestation. 

It should be noted that the dry storage 

occurred during the summer months when 

fungal and insect activity is normally 

higher than in other seasons. 

QV 

BEGIN IST 3dD ~TH 5TM 

WARTER ENDING 

Figure 2--Average moisture content of 

outer sapwood samples from the large 

end of test logs which had been drystored and then placed in sprinkled 

decks with different sprinkling 

schedules, 
The data from the dry-stored logs 

indicate that the continuous sprinkling schdules were more effective 

than the inte ttent schedules, and 

the heavy spr ling schedules more 

effective than the light schedules. 

Apparently, logs under the higher 

sprinkler water volumes reached the 

threshold moisture level, where fungal 

and insect activity ceases, agore 

quickly than the lower water volume 

schedules. Lags which were dry-stored 

longer than two months before sprinerious levels of fungal and 

gel regardless of the 

sprinkling schedule used. 

The results show that freshlyharvested southern pine sawlogs can be 

stored under water sprinklers for a 

two-year period without serious degradation, provided an adequate volume of 

water is applied to the logs on a 

continuous basis. The combination of 

these results indicate that the degree 

of protection of the sprinkled logs 

from fungal and insect infestation is 

dirmtly related to the volume of 

water applied. The moisture content 

of logs under the heavier water volume 

sprinkling schedules reached the 

threshold moisture content more 

quickly, which prevented infestation 

by insects and fungi. The continuousheavy schedule, which had the highest 

water volume, provided the best 

protection. The intermittent-light 

schedule, which had the lowest water 

volume, provided the poorest protection. Continuous sprinkling was 

superior to intermittent sprinkling, 

but this difference appears to be more 

related to water volume than to the 

difference between continuous and 

short-cycle intermittent sprinkling 

schedules . The mechanical properties of samples 

from the sprinkled logs were lower at 

the end of the test period than at the 

beginning. Part of this difference 

can be attributed to the lower 

specific gravity of the final samples 

which were further from the original 

large ends of the logs. After 

adjustment for specific gravity 

difference, tangential toughness was 

the only property tested which was 

reduced significantly. 

The results also show that ambrosia 

beetle and pine sawyer activity and 

blue stain and brown rot fungal 

activity, in logs which have been drystored prior to sprinkler storage, can 

be arrested by water sprinkling. It 

appears that heavier water volumes stop 

the activity =re quickly than lighter 

water volumes, Moisture content of 

logs under the heavier sprinkling 

volumes increases more rapidly than 

logs under the lighter sprinkling 

volunres; thereby reaching the threshhold moisture content, where insect and 

fungal activity stops, more quickly. 

Blue stain was present in all logs 

sampled after only one month of dry 

storage. Significant presence of 

rosia beetles and pine sawyers was 

not evident during the first two months 

of dry storage, but increased rapidly 

thereafter. These results demonstrate 

the importance of placing logs under 

water sprinklers as soon as possible 

after blow-down to avoid early deterioration from fungi and insects. 

Of the four sprinkling schedules, the 

Continuous-Heavy sprinkling schedule 

produced the best results. The sprinkler output on the logs in this deck 

was four inches of water per 24-hour 

day. The deck contained 30 logs, 

stacked to an approximate height of 

five feet. Although the four inches of 

water per day was adequate to protect 

the logs in the test deck, larger-sized 

conunercial decks where logs are 

typically stacked to heights of up to 

30 feet, will require additional inches 

of water output to protect the stored 

logs. The amount of water required 

will vary with the height of the log 

deck and other conditions. 

LITEFUTURE CITED 

Koch, Peter. 1972. Utilization of 

southern pines, Vol. I. Agriculture 

Handbook No. 420. USDA Forest Service. 

Liese, W. 1984. Wet storage of windblown conifers in Gemany. New Zealand 

Journal of Forestry 29(1):119-135. 

Lutz, JOE',; Duncan, C.G.; Scheffer, 

T.C. 1966, Some effects of bacterial 

action on rotary-cut southern pine 

veneer. Forest Products Journal 

16(8):23-28. 

Mason, R-R.; Muhonen, J.M.; Swartz, 

J.N. 1963. Water sprayed storage of 

southern pine pulpwood. Tappi 

46(4):233-240. 

Miller, D.H.; Swan, Sam. 1980. Blue 

stain in sprinkled log decks and lumber 

piles of ponderosa pine. Forest 

Products Journal 30(2):42-48. 
Roff, J.W,; Wbie, J, 1968, Hater 

sprinklers check biological deterioration in stored logs. British 

ia Lumberman 52(5)* 

Scheld, H.W.; DeGroot, R,C, 1971, 

Toughness of sapwood in water-sprayed 

longleaf pine logs, Forest Products 

Journals 21(4):33-34, 

Vollmn, D. 1966, Water spray storage 

of southern pine pulpwood. Tappi 

49(7):48A-53A* 

Wagner, F.G, 1976, Experience with 

stain, decay, and insects in mid-south 

storage yards. Southern Lde 

323(2874):9-10. 
FACTURE OF SOUTHERN PIMEt: PLWOOD FROM 

HURRICANE HUGO SALVAGE LOGS STORED UNDER 

WATER SPRINKLERS' 

J. He Syme, P. N. Peralta, and Ro Ho ~c~lister~ 

ABSTRACT--The study documented and analyzed the 

activities which occurred during the water storage and 

plywood processing of Hurricane Hugo salvage logs at 

the Georgia-pacific ~orporation's Plywood Plant in 

Russellville, S.C. It was observed that in log decks 

where adequate water was properly applied, the log 

storage program was effective in preserving sound logs 

and in stopping further damage from insects and fungi 

in logs which were already infested when placed in 

storage, No major problems were encountered in 

processing the sound logs which had been properly 

sprinkled; however, severe production problems were 

experienced in processing logs which were not sprinkled 

or which were heavily infested with fungi and insects 

prior to water storage. Additionally, the incoming 

logs to the plywood plant were made up of a varying 

mixture of cull (severely infested) and sound logs. 

The extreme variation in log quality and moisture 

content created processing problems from the water vats 

to the hot press. Process and adhesive adjustments 

were made on a continuous basis in order to stay within 

process control limits. Regardless of the processing 

problems, the plant consistently produced plywood from 

the salvage logs which met industry panel glueline and 

strength specifications. 

INTRODUCTION 

On September 22, 1989, Hurricane Hugo 

struck the South Carolina coast with 

the full force of 135 mile-per-hour 

winds. Hugo swept through central 

South Carolina into North Carolina, 

creating extensive damage to timber 

and property, in a swath 50 miles wide 

from Charleston to Charlotte. The 

greatest overall economic loss was to 

A paper presented at the 72nd Annual 

Meeting of the Appalachian Society of 

American Foresters held at Greenville, 

S.C., on January 20-22, 1993. 

John H. Syme and Perry N. Peralta, 

Department of Forest Resources, 

Clemson University, Clemson, SC 

29634-1003; and Robert H. McAlister, 

U,S. Forest Service, Southeastern 

Forest Experiment Station, 320 Green 

St,, Athens, 6A 30602-2044. 

the timber resource in the p'ath of 

Hugo. Twenty-three counties in South 

Carolina reported substantial timber 

devastation (Figure 1). Trees were 

uprooted, broken off, and otherwise 

damaged. Estimates placed the total 

timber destruction in the state at 

$1.18 billion (Table l), with the 

equivalent of four years harvest of 

sawtimber destroyed, 

South Carolina (;overnor Campbell moved 

rapidly to bring the forest industry 

public and private sectors together, by 

creating a Forest Disaster Salvage 

Council on October 5, two weeks after 

Hugo struck. The Council was charged 

with coordinating activities related to 

the timber salvage efforts, Early 

action included temporary waiving of 

sprinkler and water storage penits for 

log storage, increasing the maximum 

hightray gross weights for log trucks, 
and recruiting of loggers from other 

states. A salvage goal of 625 million 

cubic feet was established, or 25 

percent of the total estimated volume 

destroyed of 2.5 billion cubic feet. 

The salvage program was hampered by a 

combination of wet weather and the 

difficult logging conditions created 

by the downed timber. Ehphasis was 

given to the salvage of pine over 

hardwoods, because pine stands were 

more easily accessible. Despite the 

establisbent of several sprinklered 

storage sites, the increased harvest 

of timber exceeded the industry's 

processing capacity. By early spring 

of 1990, the price of pine sawtimber 

had dropped to $89 per thousand board 

feet, from $175 prior to Hugo, while 

the pulpwood price dropped to $11 per 

cord from $22 previously. Saturation 

of the pine timber market slowed the 

salvage program and, as a result, many 

of the loggers from outside the area 

returned home. Conversely, hardwood 

sawmills and veneer plants experienced 

a shortage of logs, because of the 

number of loggers moving to the 

salvage area to log pine. 

By mid-March, 1990, approximately 255 

million cubic feet, or 40 percent of 

the goal of 625 million cubic feet, 

had been salvaged. Softwoods comprised 87 percent of the total. As 

the weather warmed, the quality of the 

downed timber began to deteriorate 

rapidly due to increased insect and 

fungal activity. By June, 1990, most 

pine salvage logging had ceased. 

Total estimated volume of timber 

salvaged as of November, 1990 was 383 

million cubic feet or 61 percent of 

the original goal. Softwoods, mostly 

pine, comprised 86 percent of the 

total volume. 

ary of Timber Damage by 

Hugo 

During the first half of 1990, the 

Southeastern Forest Experiment 

Station, U.S. Forest Service, conducted a special inventory of the 

forest resource in the Hugo-devastated 

areas of South Carolina. The purpose 

of this inventory was to assess the 

volume of timber damaged by the 

hurricane. A total of 2,530 permanent plots in 23 counties were 

measured. The 23 counties contained 

6.5 million acres of timberland, of 

which 4.5 million acres were damaged 

by Hugo. In six of the counties --- 

Berkeley, Clarendon, Florence, Lee, 

Sumter, and Williamsburg --- more than 

90 percent of the timberland sustained 

damage. 

The 1990 inventory included all 

merchantable trees that were alive. 

Each tree was placed in one of four 

classes : 

1. Class 1: Severe damage, high 

probability of dying in the near 

future. 

2. Class 2: Moderate damage, 

questionable probability of 

surviving. 

3. Class 3: Light damage, high 

probability of surviving. 

4. Healthy: No obvious hurricane 

damage. 

Because the future mortality rate in 

each class is unknown, the actual longterm loss of timber due to Hugo can 

only be estimated at this time. 

Based on the survey, the softwood 

growing stock inventory of 4.8 billion 

cubic feet was reduced by about 21 

percent or 1.0 billion cubic feet 

(Figure 2). One-third of the lost 

softwood volume was salvaged, twothirds was killed but not salvaged. 

Softwood sawtimber volume was reduced 

from 19 to 14 billion board feet, a 

decline of 26 percent. Large-diameter 

trees were most prone to hurricane 

losses, while reductions were more 

modest for smaller trees. Volume was 

reduced by 6 percent in the 6-inch 

diameter class, 11 percent in the 8- 

inch class, and 16 percent in the 10- 

inch class; while reductions of 22 to 

32 percent were calculated in the 12-, 

14-, 16-, 18-, and 20-inch categories. 

All yellow pine species showed severe 

damage, while cypress was least 

affected by Hugo. 

The hardwood growing stock inventory of 

5.1 billion cubic feet was reduced by 6 

percent or 319 million cubic feet 

(Figure 3). This inventory reduction 

was attributed to 270 million cubic 

feet of Hugo-related mortality and 49 

million cubic feet of timber salvage. 

About one-third of the post-Hugo hardwood inventory was damaged to some 

degree. Damage to hardwoods by Hugo 

was much more difficult to assess than 

was softwood damage. Severely damaged 

hardwoods did not die as quickly after 

the hurricane as did softwoods. The 

extent of damage to the hardwood 

resource is, therefore, understated, 
The larger trees suffered the greatest 

Hugo-related mortality. Red oaks were 

the hardest hit species with 42 percent of the inventory d 

percent in Class 1, 

ry, Hugo-related mortality 

txnue to accumulate for 

several years. According to the U.S. 

Forest Service, a reasonable est 

of long-tern ssftwad loss is about 30 

percent of the pre-Hugo inventory, or 

1.4 billion cubic feet. It 

mated that total hardwoods d 

about 20 percent of pre-Hugo volume, 

or 1.0 billion cubic feet. 

Water Storage of Hugo Logs 

One of the initial proposals by the 

Governor's Forest Disaster Salvage 

Council was the wet storage of 

harvested logs. It was assumed that 

the wet storage facilities would 

maximize the salvage of Hugo-damaged 

timber by providing a safe place for 

storing a large volume of harvested 

logs which exceeded the short-term 

capacity of processing plants. Less 

than one month after Hugo, the Council 

alerted the forest industry about the 

importance of developing wet storage 

facilities. Government disaster funds 

were requested to provide wet storage 

sites for small businesses and landowner cooperatives. The industry was 

requested to identify potential storage areas, including rock quarries, 

lakes, ponds, and dry-land sprinklered 

sites, which could be reached by truck 

or rail transport. A survey in early 

December, 1989, revealed that 30 

potential sites had been identified 

with a planned log storage capacity of 

160 million board feet, or 20 percent 

of the anticipated pine salvage volume 

of 800 million board feet. Additional 

sites were also proposed in the 

Francis Marion National Forest, 

A 1989 year-end survey indicated that 

few logs had been placed in water 

storage, Wet weather had hmpered 

logging operations, and mills were 

diately consume almost all 

of the salvage logs hamested. Further, it was reprted that the secure 

ing of government funds for log storage had been unsuccessful, Government 

agencies had also failed to respond to 

requests for approval to store logs in 

lakes and ponds. Another barrier was 

the lack of available infomation 

related to the design of log sprinkling syst-s for dry-land storage, 

although sprinkling logs is cornonly 

pra~ticed by many hardwood mill^. The 

Department of Health & Environmental 

Control (DHEC) in South Carolina 

approvd a twprary progrann to allow 

mills to sprinkle stored logs without 

going through the permit procedure, 

provided the sprinkling facility was a 

closed-loop, recirculating system with 

a 24-hour rain capacity. 

Beginning in January, 1990, the 

response to the program was positive in 

ted 140 million board 

feet of salvaged pine logs and 6 

million board feet of hardwood logs 

were stored under sprinklers over the 

following six-month period. Typically, 

logs (both tree-length and cut-tolength) were stored in long rows or 

piles, from 10 to 25 feet in height, 

Standard irrigation sprinklers were 

used to apply a continuous spray to the 

log piles. The logs were normally 

stored for several months and, in some 

cases, over one year, prior to 

processing. 

Sprinkler storage proved to be a very 

effective and low-cost method for 

storing the salvaged logs. Sprinkling 

prevented insect and fungal attack on 

freshly-harvested logs, and stopped 

further insect and fungal activity on 

logs which were infested prior to 

storage, provided adequate water was 

applied to the logs to maintain the 

required moisture levels, No serious 

problems were encountered in processing 

the sprinkled logs into lumber, veneer, 

and plywood, and no product degrade 

could be attributed to sprinkler 

storage. 

Literature Review: Wet-Storage 

of Logs 

A survey of existing literature 

revealed a large number of articles on 

the subject of water log storage, both 

softwoods and hardwoods. Although 

underwater storage in ponds or lakes 

was once a popular storage method, dryland sprinkler storage is the most 

popular current method for preserving 

stored logs, Little detailed info 

tion was found on the practical aspects 

of log sprinkling or on the design of 

sprinkling systems. Most af the 

articles are general in nature, or 

report the results of research on a 

spetcific topic, 

ry, sprinkling piles of logs 

with water is reportedly the most 

practical method of preventing or 

stopping insect and fungal attack in 

stored logs, Air in the wood is 

replaced by water, and at a certain 
moisture content (threshold level) the 

insects are drowned or driven from the 

wood and the fungi become inactive due 

to lack of oxygen, Scheffer (1969) 

hypothesized that water sprinkling 

rosia and other beetles 

because the water on the log surface 

masks the natural attractants that 

lure the insects to the log for 

reproduction. If the logs are already 

infested when placed in storage, the 

insects or fungi will remain active 

until the sapwood moisture content is 

raised to the threshold level by the 

water sprinklers, Liese (1984) and 

Miller (1979) found that a sapwood 

moisture content of 100-120 percent 

(0.D. weight basis) will reduce the 

available oxygen below the level 

required to sustain fungal growth. 

Less is known about threshold moisture 

levels required to stop insect 

activity; one reference (Mason et al. 

1963) indicated that attacks by Ips 

engraver beetles and sawyers were 

prevented as long as the log surfaces 

were kept wet. Koch (1972) reported 

that blue stain fungi become less 

active at temperatures below 50 

degrees F. A later study on ponderosa 

pine sapwood reported that blue stain 

fungi continued to be active at temperatures down to 37 degrees F. and 

the greatest amount of staining 

occurred at 45 degrees F (Miller and 

Swan 1980). 

Pine logs, properly sprinkled, apparently can be stored for long periods 

of time without degrade. According to 

Wagner (1978), successful sprinkler 

storage of up to two years for S. pine 

logs appears to be fairly common, with 

storage up to six years reported in a 

few cases, References reported on the 

storage of storm-damaged logs in 

several foreign countries. Pine logs, 

for example, have been stored under 

water sprinklers in Germany (Liese 

1984) and New Zealand (Clifton 1978) 

for as long as five years without 

measurable degrade. 

Certain types of bacteria (anaerobic) 

do not require oxygen to survive and 

will continue their activity in the 

sprinkled logs; however, the presence 

of these bacteria normally does not 

cause a problem, The 1 

from logs which have been stored 

several years may have grayish 

streaks, have an unpleasant odor 

before being dried (Clifton 1978, 

Volkmann 1966), and may exhibit 

increased permeability (Miller 1979, 

Rayner 1988). The stain can be 

eliminated by dipping the green lumber 

or veneer in a ch-ical solution. The 

odor disappears when the lumber or 

veneer is dried. Basic strength properties are not materially affected 

(Lutz et al. 1966, Shefter 1969, Liese 

1984) , 

On balance, there appears to be little 

difference in cost and problems experienced between processing sprinkled logs 

and fresh logs. The wetter bark on the 

sprinkled logs may present problems in 

immediate use for boiler fuel (Miller 

1979, Djerf 1969); additionally, much 

of the bark tends to slough off in the 

storage yard (Liese 1984). Sprinkled 

logs reportedly can be sawn and peeled 

at faster rates (Liese 1984), but the 

green veneer and lumber may require 

slightly longer drying times. 

Approach, Method, and Data 

Collection 

Although most of the activities related 

to storing and processing the sprinkled 

Hugo-logs took place at the Plywood 

Plant, several other organizations were 

deeply involved throughout the program, 

Georgia-Pacific's Timber Division 

procured and stored the salvage logs, 

The Company's Chemicals Division 

supplied the various plywood adhesive 

formulations required to obtain the 

best glue-bond results, The American 

Plywood Association provided continuous 

glue-bond evaluation, panel strength 

testing, and technical advice. The 

Southeastern Forest Experiment Station, 

U, S. Forest Service, performed periodic moisture content and specific 

gravity tests on samples from logs in 

storage and stiffness tests on the 

finished plywood panels produced from 

those logs. 

The project study team's general 

approach was to collect pertinent 

information and data from the Plywood 

Plant and from each of the other 

organizations involved. In-depth 

personal interviews were conducted with 

management and supervisory personnel in 

the Plpood Plant and with key personnel in the other organizations. 

Production, quality control, technical, 

and other reports were also obtained. 

Special reports were requested in 

instances where available data were not 

adequate. Weather data (Figures 4a, 

4b) for the Russellville area, covering 

the Hugo-log storage period, were also 

obtained from the National Climatic 

Data Center, 
Information from the personal interviews was analyzed and edited. 

Reports and other data were analyzed 

rized; graphs were prepared 

comparing results for three periods: 

prior to, during, and after the 

processing of Hugo logs. The project 

study team reached conclusions and 

developed recomendations from the 

data gathered and analyzed and from 

the literature review, 

FACT OF PLYWOOD FROM 

=I"-STORED HUGO LOGS AT 

GEORGIA-PACIFIC" 

RUSSELLVILLE PLYWOOD PLANT 

Georgia-Pacific Corporation responded 

aggressively to the Hurricane Hugo 

disaster. The company's Eastern Wood 

Products Manufacturing Division 

mounted a full-scale timber salvage 

program which resulted in the harvesting and storage of a large quantity of So pine logs for manufacture 

of plywood at its Russellville plant. 

A substantial additional volume was 

also harvested and shipped to several 

of the companyfs other plywood plants, 

A thorough review of the companyfs 

Hugo log salvage program indicates 

that it was, by and large, very 

successful. The many serious problems 

encountered were overcome through 

effective coordination within the 

company, its Building Products Group, 

and its Eastern Wood Products Manufacturing Division; and with valuable 

assistance from outside organizations 

such as the American Plywood Association, 

Unfortunately, lack of or slow action 

by government organizations created 

serious problems in implementation of 

timely salvage programs by the industry. For example, if permission had 

been granted to store logs in Lake 

Moultrie, it is estimated that more 

than twice as much timber could have 

been salvaged and stored for future 

consunnption. After the company made 

the decision to go to dry-land sprinkler storage, its salvage program was 

also impaired because permission to 

draw sprinkling water out of the 

Rediversion Canal was slow in coming, 

On the other hand, the fact that the 

Hurricane occurred late in the year 

(September 19, 1989), when cool 

weather was starting, provided more 

time to implement a salvage program 

before rapid log deterioration set in. 

In fact, little deterioration was seen 

in the Hugo logs during the first 

three months after Hugo. However, the 

at goverment's lack of 

in a much smaller 

r being salvaged than 

otherwise could have been. 

As mentioned earlier, there is a lack 

of specific info tion on how to 

design a program for harvesting 

storing large volumes of logs d 

by hurricanes or 

very little info 

relating to the manufacture of plywood 

from salvaged logs. Therefore, the 

company's salvage program, at least in 

the beginning, was largely experimental. It is difficult to look back 

and recount the number and severity of 

problems encountered (on an hour-tohour and day-to-day basis) in producing 

plywood from the wet-stored salvaged 

logs, It is obvious, however, that in 

spite of all the problems, the plywood 

plant did an outstanding job of producing a satisfactory product from the 

salvaged timber. This was accomplished 

through effective leadership and coordination, and plain hard work by everyone involved. 

The major manufacturing problems were 

created by the wide variation in 

incoming log quality and moisture 

content. This was particularly 

difficult during two periods: 

(1) during processing of logs that 

were received during the last two 

months of salvage operations (May 

& June, 1990), when the quality 

of the logs had severely deteriorated before harvesting; and 

(2) during processing of logs from 

the first decks built, where the 

initial sprinkler system design 

did not provide adequate coverage 

to protect the logs from deterioration. 

Log Receiving, Storage, and 

Sprinkling 

The suddenness of the hurricane, plus 

the huge amount of damage to the timber 

in the area, forced Georgia-Pacific's 

Eastern Wood Products Manufacturing 

Division to react quickly. The original goal was to salvage 20 million 

board feet (Doyle) of S. pine veneer 

logs, but this was later increased to 

30 and then to 40 million board feet, 

A total of about 60 million board feet 

was actually salvaged and stored for 

the Russellville plywood plant (Figure 

5), plus additional volumes were 

shipped by rail to other company 

plywood plants in North and 
South Carolina, Georgia, Florida, and logs were purchased as pulpwood and 

Virginia, The overall objective was placed in sprinkler storage mixed with 

to salvage the largest and highest- good logs. An original objective was 

er as rapidly as possible. to put the better logs in storage and 

send the worst logs directly to the 

Log ~eceiving and Storage 

Within three weeks after Hugo, the 

company began receiving salvage logs. 

This continued through June of 1990, 

when it became obvious that the logs 

contained too much rot and insect 

ge to produce plywood. Approximately 60 percent of the volume came 

from Berkeley County (mostly from the 

Francis Marion National Forest); a 

significant volume also came from 

Clarendon County, with lesser volumes 

from Sumter and Williamsburg Counties. 

As the salvage operation increased in 

volume, the company added log receiving and storage personnel and 

increased the number of receiving 

scales from one to four. At peak 

times, the company was receiving as 

many as 300 truckloads of logs per day 

and physically could not handle any 

more. Incoming loads of logs at the 

Russellville plant are normally 

weighed, unloaded, with some loads 

stick-scaled (Doyle), Deductions are 

made for defect, which normally runs 

about 3.5 percent, However, because 

of the large volume of incoming logs 

during the Hugo salvage period, the 

loads were visually inspected on the 

trucks (logs were counted and both 

ends of logs inspected) with deductions estimated. 

The company's timber personnel established salvage log specifications and 

worked closely with contract loggers 

to make sure that the log specifications were understood and followed, 

The log specifications were: 

- 8' 9" multiples in length 

(average log length was 35', 

ranging from 17 to 54') 

- small-end minimum diameter 8" 

(raised to 14" near end of 

program 

- no visible cracks, splits, or 

ring shake 

- no visible rot or insect damage 

- tight bark 

Although loggers adhered to the 

specifications fairly closely, a 

significant volme of reject logs were 

delivered to the logyard. The reject 

plywood plant for processing; but, in 

reality, the huge volume of incoming 

logs made it impractical to do any 

sorting. After unloading, the bogs 

were stacked on the ground in decks to 

a height of 27-28 feet. ApprsxiPn%tdy 

30 acres of land was required to store 

the 63 million board feet of logs. 

Log Sprinkling 

Problems with government "red tape" and 

the lack of internal knowledge about 

the parameters of log sprinkling 

created initial delays in getting the 

logs under water. Although DHEC 

(Department of Health and Environmental 

Control) temporarily waived the normal, 

long-term approval process, it still 

required that any log sprinkling 

installation be a closed-loop, recirculating system meeting certain raincapacity requirements. Also, obtaining 

permission from the Corps of Engineers 

for pumping the sprinkling water from 

the Rediversion Canal proved to be a 

time-consuming problem, The proper 

design of a log sprinkling system 

itself was not known, relating to pump 

type and volume, pressure, filtration, 

pipe sizes, sprinkler head design and 

placement, and other factors, Because 

of this lack of knowledge, the design 

of an effective sprinkled log storage 

system was essentially a trial-anderror approach. Some assistance on 

sprinkler system design was obtained 

from two sources, (W, P. Law & Company 

in Columbia, SC and Bill Gomez and 

Associates in Lakeland, FL) but neither 

firm was experienced in systems for 

sprinkling logs. 

Sprinkling actually began on the first 

decks of logs in February, 1990. The 

initial sprinkling system used very 

large agricultural sprinkler "guns" 

covering a wide area. Although the 

system sprayed an estimated 13.5 inches 

of water per day, coverage was poor, 

and the logs deteriorated significantly 

while in storage. This created severe 

problems in the plywood plant when the 

logs were finally processed. 

Subsequent sprinkling systems employed 

er of smaller sprinkler 

heads (3fl6" and lf4" orifice diameter) 

on top sf the decks at 60-foot intervals and on the ends of the decks. 

This provided considerable overlap and 

more uniform caverage with about 
one-half the volume of water. These 

were equipped with pump 

strainers and were operated continuously, except for maintenance. Each 

40 hp pump, operating at 80 psi (50 

psi at sprinklers), provided water for 

five million board feet of logs. The 

company operated 16 such pumps, plus a 

larger one for pmping makeup water. 

Total water volume pumped was about 12 

million gallons per day, with makeup 

water requirements of 2-3 percent. 

Two sources of water were used: the 

main source was from the Rediversion 

Canal out of Lake Moultrie which 

supplied over three quarters of the 

requirements; the balance came from 

wells. The pH of the water in the 

circulation ponds remained at about 

7.5. A total of approximately 10 

miles of pipe was laid during the 

program. 

Two unusual problems were encountered 

as a result of the sprinkling program. 

First, the company received many complaints from nearby residents about 

the foul odor emitted from the log decks. Chlorine tablets were introduced i n t o t h e sprinkling system, with 

no apparent improvement. The second 

problem involved an increased mosquito 

population which bred in the circulation ponds. About 100,000 mosquitoeating minnows (Gambusia affinis) were 

obtained from the Santee-Cooper 

Authority and planted in the ponds, 

which apparently solved the problem. 

As time passed following Hugo, particularly after February, 1990, when 

the weather warned, insect and fungal 

damage in incoming logs became progressively worse. Beginning in early 

April, insect infestation increased at 

a rapid rate, and Clemson University 

scientists were called in to assess 

the situation. It was recommended that 

logs be placed under sprinklers as 

soon as possible after harvest. Random inspections of the condition of 

incoming logs and their condition 

after being under sprinklers, showed 

that sprinkling appeared to be effective in preserving good logs and stopping further damage by insects and 

fungi in infected logs. 

Moisture samples, taken from logs in 

storage by the company during the 

summer of 1990, showed wide variation: 

from 9 to 126 percent (oven dry 

basis), with an average of 60 percent. 

Moisture tests on incoming logs also 

showed wide variation, from 14 to 105 

percent, also with an average of 60 

percent. The wide variation in moisture content of the logs resulted from 

harvesting trees that were (1) still 

standing, (2) blown over, but with some 

roots intact, and (3) trees that had 

been blown over or broken off with no 

source of moisture. Timber site 

(swampy or dry) also affected log 

moisture content. 

The company estimates that the additional cost of installing the sprinkler 

system and storing and sprinkling the 

Hugo logs amounted to approximately $45 

per thousand board feet (Doyle). The 

incremental direct costs for operating 

the storage and sprinkler system, once 

the installation is made, is approximately $2.00 per ME3F. 

Plywood Processing 

The plant began processing Hugo logs in 

October of 1989. Processing of 

sprinkled logs began in mid-1990 and 

continued through January of 1992. The 

salvaged logs were transferred from the 

sprinkled decks to the plywood operation on a last-idfirst-out basis. 

This was done in order to process the 

logs with the greatest amount of 

deterioration first, since the 

effectiveness of water storage in 

stopping further damage was not known. 

The result of this program was that the 

driest logs were under the sprinklers 

for the shortest length of time. Also, 

since the logs were stored as they were 

unloaded from the trucks, with no sorting, the logs from the storage decks 

were delivered to the plywood plant in 

the same random manner. From the to 

time, fresh logs were also processed 

along with the Hugo logs in order to 

produce the veneer mix needed by the 

plant . Green End 

Several problems were encountered in 

producing green veneer from the Hugo 

logs. Because of the variation in 

moisture content and extent of fungal 

and insect damage from log to log, 

constant adjustments had to be made "on 

the run", 

The blocks from the dry logs floated in 

the water vats, which required the 

water level to be dropped so the floor 

chains would pull the blocks out of the 

vats. Vat water temperature was 

reduced, block dwell time increased, 

and less caustic was required to 

maintain the proper pH (7.5-8.0). 

Blocks on the infeed chain between the 
vats and lathe had to be sprinkled to 

wet the surface so they would center 

properly in the XY charger. 

The plant's boiler fuel costs also 

increased when Hugo logs were processed, Much of the bark sloughed off 

during log handling and storage and 

could not be recovered for fuel. This 

resulted in the purchase of increased 

volumes of supplemental fuel from 

outside sources (Figure 6). 

Veneer blocks from the dry logs 

produced a very rough peel with a 

large amount of shelling, The dry 

blocks also required a different lathe 

set-up than green blocks, to obtain 

the proper veneer thickness, Veneer 

thickness from the dry blocks was 

increased slightly due to less 

"spring-back", as compared to veneer 

from green blocks. Clipping width of 

veneer from the dry blocks was reduced 

to compensate for less shrinkage in 

the dryers. Stacks of green veneer 

from the dry blocks did not produce 

mold growth when stored prior to 

drying. 

The influence of the Hugo logs on 

green veneer volume recovery is 

difficult to assess, because of the 

mixing of the cull logs with grade 

logs and the lack of accuracy (on a 

short-term basis) in determining the 

voiume of logs transferred to the 

plywood plant from the sprinkled 

decks. On the other hand, the negative effect on veneer grade recovery 

(Figures 7a, 7bI 7c) was obvious from 

the prevalence of insect holes, blue 

stain, brown rot, stress cracks, 

splits, shake and rough peel. At 

times, the production of siding and 

other higher-grade panels was substantially reduced due to lower face 

veneer yield from the Hugo logs 

(Figure 8). 

Veneer Dminq 

Variation in moisture content from log 

to log and within a log, created 

serious problems at the veneer dryers. 

Proper control of dry veneer moisture 

content was a constant problem 

throughout the Hugo program due to the 

wide fluctuation, on a short-interval 

basis, in moisture content of the 

green veneer, The dryer speeds were 

constantly adjusted to try to 

compensate for the green veneer 

moisture content variations; the 

result was the veneer from the dry 

logs was typically overdried and the 

veneer from the wetter logs was 

underdried. 

A constant problem was the abnormal 

exudation of pitch from the green 

veneer which accumulated on conveyor 

rolls, dryer rolls, etc. This also 

could be seen on the dry veneer in the 

form of black streaks and spots. A 

greater-than-normal amount of wood 

"trash" also accumulated in the bottom 

of the dryers, creating a fire hazard, 

Panel Production 

Panel layup presented the greatest 

challenge in processing because of the 

uncontrollable variables which had to 

be dealt with. Dry veneer moisture 

content, roughness, and absorptive 

properties were constantly changing. 

This required continuous modification 

of the adhesive formulation and spread 

rates to try to compensate for the 

changing conditions. For example, 

between November, 1989 and June, 1991, 

the adhesive mix was changed 17 times. 

Extenders were modified, resin solids 

was increased, the base resin changed, 

the mix "dried-up or greened," flow 

enhancer increased, etc. 

Panel thickness variation was also a 

problem, due to the variatisn in log 

moisture content. This was controlled 

by adjusting both the peel thickness 

and press schedule (single-stage), 

Product Quality 

The plant faced a myriad of severe 

processing problems which directly 

impacted product quality in manufacturing plywood from the Hugo logs. 

Most of these problems resulted from 

the wide variation in quality and 

moisture content of the incoming logs. 

The severity of the problem was 

increased by the fact that (1) log 

quality varied from hour-to-hour, and 

(2) the total production process was 

affected, from the water vats through 

the hot press. 

During the Hugo-log utilization period, 

the plant experienced an increase in 

gluing problems (Figure 9). Basic 

reasons for the glueline problems 

include (1) dried-out glueline due to 

overdried veneers, rough veneer, and 

blue stain; (2) over-penetration of 

glue due to increased porosity and 

permeability associated with blue stain 

and decay; (3) heavy, light, and spotty 

spreads attributable to glue application procedures; and (4) thick and thin 

veneer due to inconsistency in log 

moisture content and quality, block 

conditioning, and lathe setup. The 

mixing of fresh logs with Hugo logs, 

modification of the glue formulation, 

and process adjustments helped to 
alleviate these gluing problems and 

enabled the plant to produce plywood 

which consistently met product 

standards. 

Panel strengthlstiffness tests were 

carried out during the Hugo-log 

utilization period by both the 

American Plywood Association (Figure 

10) and the Southeastern Forest 

Experiment Station, U.S. Forest 

Service (Figures lla and llb). The 

test results showed that the panels 

consistently exceeded minimum product 

standards and, in most instances, were 

better than the controls. The 

increase in panel strength/stiffness 

is attributed to the larger logs 

processed from the old-growth Hugodamaged timber. Minimum small-end 

diameter specifications for the 

salvage logs was gradually increased 

from 8 to 18 inches during the period 

when Hugo logs were received. 

In summary, the plywood plant was able 

to overcome these major obstacles 

associated with the Hugo logs and, 

through effective leadership and 

teamwork, consistently produce a 

product which met or exceeded minimum 

panel standards. The company's 

Chemical Division (adhesives supplier) 

and the American Plywood Association 

worked closely with the plant 

throughout the Hugo program and 

provided valuable assistance in 

maintaining product integrity. 

WCOWNDATXONS 

Two extremely important messages 

emerged from this project. First, the 

slowness of some government agencies 

in responding to industry's needs 

delayed and sometimes prevented the 

implementation of critical programs. 

Second, the lack of experience and 

readily-available information, related 

to dealing with a timber disaster such 

as Hugo, prevented the private and 

public sectors from responding in a 

timely and effective manner. These 

obstacles delayed or prevented needed 

action and resulted in (1) much less 

timber being salvaged than should have 

been, and (2) higher costs and greater 

problems in storing and processing the 

Hugo logs. Also, the full impact of 

these problems was not experienced 

because of the timing of Hugo, which 

provided more response time than if it 

had occurred, for example, in the 

spring. 

Based on past history, it can be 

assumed that another hurricane will 

ered area in the South, 

ck and effective action by 

the private and public sector 

required to salvage as much t 

possible. At least two major 

recommended before another hurricane 

strikes. First, all available info 

tion related to harvesting, storing, 

and processing storm-damaged timber 

should be compiled and stored where it 

is readily available. The existence of 

such an information center(s) should be 

communicated to appropriate public 

agencies and the forest industry. 

(This report is an example of the kinds 

of information needed.) Second, public 

agencies and the forest industry need 

to develop a disaster plan which identifies decisions and critical actions 

which must take place and describes how 

these will be made and implemented on a 

timely basis. 

Information for Future 

Consideration 

The following suggestions are offered 

to alleviate some of the most serious 

problems experienced in harvesting, 

storing and processing the Hugo timber, if a similar situation were to 

occur in the future. 

Adequate Log Storaqe Capacity 

One of the most serious problems 

encountered with salvaging Hugo timber, 

was the lack of planned water-storage 

sites for large volumes of logs. As 

harvesting volume increased beyond the 

processing capacity of mills, the 

market became flooded with pine logs 

because of lack of alternative storage 

sites. This caused some loggers to 

leave the area and discouraged others 

from coming to the salvage area. The 

use of Lake Moultrie for temporary log 

storage would have been of great 

benefit, with minimal environmental 

problems created. Also, the U.S. 

Forest Service considered offering to 

wet-store logs from all sales on the 

Francis Marion National Forest, with 

payment to be made when the logs were 

removed from storage. This potentially 

beneficial program was never implemented. 

These are examples of actions which 

should have been taken, but were not. 

If the maximum volume of timber is to 

be salvaged, adequate storage facilities must be provided, and financial 

assistance should be available to carry 

the increased log inventories. 
Loq Specifications 

The volume of cull logs mixed with the 

grade logs, caused problems in plywood 

processing. Also the economics of 

going to the expense of hauling and 

wet-storing cull logs should be questioned, Practical and easily understood log grade rules, which will omit 

the undesirable logs, should be established, mggess should be trained to 

follow the established rules and 

monitored to make certain the rules 

are being followed and cull logs are 

not brought to the storage site or 

mill . 

Sprinklered Loq Storage 

Practices 

Sites for sprinklered log storage 

should be carefully selected to meet 

DHEC regulations for runoff collection, recirculation, and rainfall 

capacity. Adequate makeup water 

should be available, and three-phase 

electrical power is needed. Based on 

Georgia-Pacific's experience, approximately two million board feet (Doyle) 

of logs can be stored per acre. 

The large variation in log quality and 

moisture content contributed to the 

bulk of problems encountered in plywood processing. If practical, some 

sorting of incoming logs should be 

done. Cull logs which are delivered 

should be chipped, if possible; if 

chipping is not feasible, the culls 

should be marked and stored separate 

from grade logs. Dry logs should also 

be identified if possible, and stored 

separately, 

Maximum height of log decks should not 

exceed 20 feet, in order to get adequate moisture to all logs. Piling 

density should also be considered, 

since closely-piled logs require more 

water. Decks should be laid out so 

that ends of logs in adjoining decks 

are as close together as practical. 

Decks should be built directly on the 

ground. Logs will gradually pick up 

moisture in wet-storage and moisture 

content variation among logs will be 

reduced. Therefore, logs should 

remain in wet-storage as long as 

possible and removed for processing on 

a first-idfirst-out basis. 

Loq Sprinklinq System 

The critical factors in successfully 

storing logs under sprinklers are to 

(1) get water on log decks as quickly 

as possible, with a continuous spray 

which is adequate to keep log surfaces 

completely wet at all times, and (2) 

reach and maintain a sapwood moisture 

content high enough to prevent or stop 

insect and fungal infestation. Sprinklers should be placed on top of the log 

decks so there is adequate overlap to 

maintain coverage when the wind blows. 

Sprinklers should also be placed 

between decks to keep the log ends wet. 

Sprinklers should be operated continuously around the clock, 365 days per 

year. The sprinkler systera should be 

monitored on a daily basis to ensure 

that all sprinklers are operating 

properly and all log surfaces are wet. 

Provision should be made for a backup 

system in case of pump failure, Moisture sampling of the logs in sprinkler 

storage should be done periodically to 

ensure that adequate water is being 

applied. Research is being carried out 

currently by the U.S. Forest Service 

and Clemson University on the long-tern 

storage of pine logs under water 

sprinklers. This research will provide 

more specific information about the 

design and operation of log sprinkling 

systems . In most closed-loop systems, the runoff water carries a large amount of 

dirt, bark, and other debris back to 

the circulation pond, which makes it 

necessary to install an efficient 

filtering system at the pump. A 

settling pond in front of the pump pond 

is also beneficial. The pumps should 

be sized to maintain a pressure at the 

sprinklers of 40-50 psi. A typical 

system uses full-circle impact irrigation sprinklers, with 3/16- or 1/4-inch 

orifices, placed 60 feet apart, For 

example, a 3/4- or 1-inch sprinkler 

with a 3/16-inch nozzle will spray 6.4 

gallons per minute at 40 psi nozzle 

pressure. Also, prevailing winds 

affect water distribution and should be 

considered in placing the sprinklers. 

Log sprinkling produces some unusual 

"side effectsn which should be considered in designing and operating the 

system. After a few weeks under 

sprinklers, the log ends become coated 

with a layer of slime fungi, algae, and 

moss. Bark will tend to slough off the 

logs, As the sprinkling water is 

recycled, it will develop an unpleasant 

odor which may cause complaints from 

nearby residents. The circulation 

ponds may become a breeding place for 

mosquitos. If the log decks are 

located near a paved road, the windblown water may freeze in cold weather, 

creating a hazard for motorists. 

Sprinkled logs also become extremely 

slippery, which makes them more 

difficult to handle when removed for 
processing, and also creates a serious 

safety problem for personnel maintaining the sprinkler systa. Caulked 

boots are required for anyone walking 

on the decks. 

As mentioned above, logs should be 

vd from the sprinkled decks for 

processing on a first-inlfirst-out 

basis. Log input to the plant should 

be planned so that manufacturing 

variables are minimized as much as 

possible. For example, rather than 

processing sound and defective logs or 

green and dry logs together, it would 

be preferable to keep them in separate 

categories and make production runs on 

each log type. If the logs to the 

processing plant contain wide variations in moisture content and cannot 

be presorted, then it would be desirable to sort the green veneer or 

lumber (by moisture content) for 

drying purposes, to reduce moisture 

variation in the dried lumber and 

veneer. 

Proposed Forest Disaster Plan 

The South is periodically struck by a 

major storm, which causes extensive 

damage to an area's timber resource. 

Hurricanes have been the most destructive force striking the southern 

coastal states in the past, and continue to be the major threat in the 

future. A review of the timber 

salvage programs related to some of 

the past hurricanes in the South, 

including Hugo, show a similar 

scenario. Typically, a task force is 

formed to coordinate salvage activities; timber harvesting is increased 

rapidly; in a few weeks, inventories 

at using mills are filled to physical 

and financial capacity; it is discovered that government assistance is 

not available for facilitating the 

development of large wet-storage sites 

for salvage logs; sawtimber is salvaged as pulpwood; harvest rates 

decline because of the saturated 

market and reduced prices; and much of 

er is destroyed by 

gi before it can be 

harvested. Not only is th 

value of the 

danger and hampers reforestation. 

For example, Hurricane Camille damaged 

285 million cubic feet of t 

it struck the Mississippi Gulf Coast 

in August, 1969. A total of only 77 

million cubic feet, comprised of 

818,000 cords of pulpwood and 109 

million board feet of sawtimber, was 

harvested. Within two months after the 

hurricane, it was reported that mill 

inventories were filled and that 

government funds were being requested 

for wet storage of surplus logs. A 

month later, the forest industry was 

notified that government funds for 

storing logs were not available. 

er harvest rates slowed and most 

er harvested was sold for pulpwood. Almost three-fourths of the 

ged volume was lost, 

Mississippi's Forest Disaster Salvage 

Council was dissolved in July, 1970. 

In its final report, the Council made a 

number of recommendations for use after 

the occurrence of a future forest 

disaster. Nothing was recommended 

regarding planning before the next 

hurricane. 

Need for Planninq 

Based on past history and the recent 

Hugo experience, there appears to be a 

real need for the development of a 

forest disaster plan involving southern 

coastal states. Because of the rapid 

deterioration of downed timber, particularly during warmer weather, time is 

critical to a successful timber salvage 

program. The damaged timber should be 

harvested as quickly as possible, and 

the surplus logs placed immediately in 

wet storage. Most mills are not 

prepared, either physically or financially, to develop large water storage 

facilities on short notice. Therefore, 

planning before the storage facilities 

are needed is an absolute necessity. 

Most government agencies use timeconsuming decision-making processes 

and, therefore, have difficulty in 

responding to urgent requests. Since 

several government agencies perform key 

roles in timber salvage programs, preplanning is necessary to accelerate 

decision-making and enable the agencies 

to make positive, timely respanses to 

timber salvage program needs, 

er salvage activie, with many 

decisions made q kly without adequate 

planning or info tion, In situations 

where government agencies were 

involved, critical decisions were 

somethes delayed or not made at all, 

Further, most states do not have the 

resources to mount an effective timber 

salvage program without outside 

assistance. 

A consortim of southern states should 

be fomed, including the southern 
coastal states from Virginia to Texas, 

This consortium should take a 

proactive stance in developing a 

er disaster pla 

icable to any 

the next disaster occurs, The plan 

should provide a framework for effective and timely hplementation and 

decision-mking, and should identify 

the major resources that will likely 

be needed and the providers of those 

resources, States who are members of 

the consortium should pledge to 

provide assistance to one another in 

implementing the plan when a disaster 

occurs. 

A consortium regional forest disaster 

task force should be established, 

consisting of a representative from 

each consortium member state, and 

representatives from the private 

sector and from each regional government agency directly involved in 

environmental regulation, transportation, financial assistance, and other 

functions involved in timber salvage, 

The logical representative from each 

member state would be its State 

Forester, Industry would be represented by an executive from each of 

two or three firms which have operations in several of the consortium 

states. A representative from each of 

the appropriate regional government 

agencies would represent the public 

sector. The regional task force would 

be responsible for establishing a 

regional disaster plan and 

coordinating related activities among 

the member states, e 

An important objective of the regional 

disaster plan would be to eliminate 

barriers between states so that the 

resources and markets for a timber 

salvage program would be available 

beyond the state or states in which 

the disaster occurred, An example 

would be the development of an 

economic model which would establish 

fair market prices for salvage timber 

products throughout the region, and 

which would provide incentives to 

harvest, store, and process the 

maximum volume of salvage timber. 

Additionally, reciprocal agreements 

should be made between states to 

facilitate the transportation of 

timber products across state lines. 

A forest disaster task force also 

should be established in each state, 

under the umbrella of the regional 

task force, and headed by the state 

forester, Appropriate representatives 

from the private and public sectors in 

that state would be selected to serve 

on the individual state task forces, 

Each state task force would develop a 

forest disaster plan for its state, 

within the framework established by the 

regional task force, Examples of key 

areas which should be addressed in the 

state plan are: 

1, Development of a rapid method 

(satellite imagery, for example) 

for quickly assessing the extent 

and characteristics of the timber 

damaged, 

2, Creation and maintenance of a 

current listing of all timber 

producers (loggers), dealers, and 

buyers in the state, along with 

their capabilities, 

3, Pre-approval by regulatory 

agencies, related to harvesting 

the damaged timber, transportation of logs, wet-storage of 

logs, and other vital activities 

associated with the timber 

salvage program, 

4. Formulation of an emergency 

financing plan, involving both 

the public and private sectors, 

which would provide needed 

funding for harvesting, transportation, storage, and processing of the salvage timber. 

5, Development of information 

relating to the detailed design 

of log sprinkling systems and 

other methods of wet-storing 

salvaged logs. 

6. Designation of a university 

forestry school (Department of 

Forest Resources at Clemson 

University, for examples as the 

information center for timber 

salvage technical information, 

such as wet-storage of logs, 

In summary, past salvage programs for 

timber disasters have resulted in the 

recovery of a relatively small volume 

of damaged timber. A timber disaster 

plan of the type described above can 

result in the recovery of millions of 

dollars of additional valuable timber 

than typically has been salvaged in the 

past. 

LITERAWIRE CITED 

Clifton, N.C. 1978, Sprinkler storage 

of windblows proves effective and 

economic. World Wood 19(12):26-27. 
Djerf, A,C,; Vollunan, D,A, 1969, 

Experiences with water spray wood 

storage, Tappi 52(10)t1861-1864, 

Xoch, P, 1972a. Utilization of the 

Southern Pines, Vol, f - The Raw 

Material. USDA Forest Service 

Agriculture Handbook No, 420, 734 pp. 

Liese, W, 1984. Wet storage of 

windblown conifers in Ge 

Zealand Journal of Forestry 29 ( 1 ) : 119- 

135, 

Lutz, J,F,; Duncan, C.G.; Scheffer, 

T.C. 1966. Some effects of bacterial 

action on rotary-cut southern pine 

veneer, Forest Products Journal 

16(8):23-28, 

Mason, R.R.; Muhomen, J.M.; Swartz, 

JON. 1963, Water sprayed storage of 

southern pine pulpwood, Tappi 

46(4):233-240, 

Miller, D.J, 1979. Deterioration of 

logs in cold decks: A survey of 

information applying to the Pacific 

Northwest, Forest Products Journal 

29(1):34-40. 

Miller, D.J.; Swan, S. 1980. Blue 

stain in sprinkled log decks and 

lumber piles of ponderosa pine, Forest 

Products Journal 30(2):42-48, 

Rayner, A.D.M.; Boddy, L, 1988, Fungal 

Dscompsition of Wood: Its Biology and 

Ecology. Wiley, N.Y, 

Roff, J,W,; Dobie, J. 1968, Water 

sprinklers check biological 

deterioration in stored logs, British 

Scheffer, T,C, 1969, Protecting stored 

logs and pulpwood in North America, 

Material und Organismen 4(3):167-199, 

Volkmann, D, 1966, Water spray storage 

of southern pine pulpwood, Tappi 

49(7):48A-53A, 

Wagner, FOG,, Jr, 1978, Preventing 

degrade in stored southern logs. USDA 

Forest Service, Forest Products 

Utilization Bulletin, 

Reprinted with permission from 

Hurricane Hugot Recovering from 

Disaster, Proceedings 72nd Annual 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Foresters, Greenville, SC, 

Jan, 20-22, 1993, Dr. Vernon L. 

Robinson, Sec-Treas, 2557 Abbott 

Circle, Seneca, SC 29678, 
Table 1. Estates of damages, re ursements, and unreimbursed losses ($ 

million) from Hurricane Hugo, (Source: Office of Economic Research, 1991). 

Residences 

~omercial/Industrial 

Federal Flood Insurance 

Autos, Misc. 

Utilities 

Ports Authority 17 

Forest 1,181 

Agricultural Structures 294 

Agricultural Crops 87 

Charleston Naval Base 250 

Unreimbursed 

Public 

Insurance Assistance Losses 

Shaw Air Force Base 0 0 

Other Govt. Agencies 1 142 1 0 142 1 0 

Total ( 6,422 1 2,891 541 1 2,990 

* Estimated value of salvaged timber. ** Funds received by farmers from FEMA are included under 

reimbursements for residences. 

It is estimated that South Carolina sustained more than $6 billion in 

damages due to Hurricane Hugo. Hardest hit were the residential, forestry, 

and comercial/industrial sectors, which suffered damages of $2.96 billion, 

$1.18 billion, and $1.03 billion, respectively. Taking into account the 

ursements received by the different sectors, it is clear that forestry 

e big loser with only $150 million worth of timber recovered through 

the salvage operation, This recovered amount represents only 13% of the 

ges. In comparison, residences and comerciallindustrial 

businesses recovered 46% (or $1.4 billion) and 80% (or $829 million) of 

the damages, respectively, through insurance claims and public assistance. 
Counties with EXTENSIVE DAMAGE 

Counties with MODERATE DAMAGE 

a Counties with LIGHT DAMAGE 

Figure 1--Relative degree of forest 

destruction caused by Hurricane Hugo 

in South Carolina counties, (Source: 

South Carolina Forestry Commission, 

Columbia, SC) 

Twenty three counties reported 

substantial timber damage, with seven 

of the counties--Berkeley, Charleston, 

Clarendon, Sumter, Williamsburg, Lee, 

and Dorchester--accounting for 70% (or 

918 million cubic feet) of the total 

volume of timber lost in these areas. 

An additional 98 million cubic feet of 

timber were lost in Xershaw, 

Darlington, and Florence counties, 

The 23 counties contained 6.5 million 

acres of timberland, of which 4.5 

million acres (or 69%) were damaged by 

Hurricane Hugo, 

Figure 2--Softwood stock inventory in 

the 23 South Carolina counties which 

suffered substantial timber destruction 

due to Hurricane Hugo, (Source: 

Sheffield and Thompson, 1992) 

The pre-Hugo inventory of 4.8 billion 

cubic feet was reduced by about 21 

percent or 1 billion cubic feet, Onethird of this lost softwood volume was 

salvaged; while two-thirds was killed 

but not salvaged, Twenty-nine percent, 

or approximately 1.1 billion cubic 

feet, of the growing stock classified 

as live timber sustained damage to some 

extent, Roughly 245 million cubic feet 

of this damaged volume were categorized 

as having class 1 or such severe damage. 

that it was recommended they not be 

retained in the stand. Almost 330 

million cubic feet were categorized as 

having class 2 or moderate damage; 

while about 530 million cubic feet 

sustained class 3 or light damage, 
Figure 3--Hardwood stock inventory in 

the 23 South Carolina counties which 

suffered substantial timber 

destruction due to Hurricane Hugo. 

(Source: Sheffield and Thompson, 

1992) 

The pre-Hugo inventory of 5.1 billion 

cubic feet was reduced by about 6 

percent or 319 million cubic feet. 

This inventory reduction was 

attributed to 270 million cubic feet 

of Hugo-related mortality and 49 

million cubic feet of salvaged timber. 

About one-third, or 1.5 billion cubic 

feet, of the post-Hugo hardwood 

growing stock was damaged to some 

degree. Almost 610 million cubic feet 

of this damaged volume were 

categorized as class 1 (severely 

damaged); while 351 million cubic feet 

and 565 million cubic feet were 

classified as class 2 (moderately 

damaged) and class 3 (lightly 

damaged), respectively, 

I - TEMP. RANGE -M- AVE TEMP. -&- % SUNSHINE I 

I - RH. RANGE -M- AVE RH. + PREClPTTAnON I 

Figure 4b--Monthly averages of relative 

humidity (%) and precipitation (in,) 

for the Russellville, SC area during 

the Hugo-log storage period. (Source: 

National Climatic Data Center, 

Asheville, NC) 

The occurrence of Hurricane Hugo late 

in the year when cool weather was 

starting provided the company a few 

months of salvage operation before 

rapid log deterioration set in. The 

decision to extend the salvage 

operation until June 1990 is debatable 

considering that the weather conditions 

were such that the logs would have 

already deteriorated badly by then. 

Weather conditions in the area during 

the storage operation were also 

favorable to the growth and development 

of fungi and insects, Even during 

winter, the temperature was mild and 

not low enough to prevent fungal and 

insect attack, The percentage of 

sunshine was high throughout the year 

SO that moisture evaporation from the 

logs required continuous and adequate 

water sprinkling; precipitation was not 

high enough to supplement the water 

spray. 

Figure 4a--Monthly averages of 

temperature (9') and sunshine (% of 

total possible) for the Russellville, 

SC area during the Hugo-log storage 

period. (Source: National Climatic 

Data Center, Asheville, NC) 
DATE 

Figure 5--Inventory of Hugo logs (bd. 

ft.) in four sprinklered sites set up 

by the Georgia-Pacific Timber Division 

in Russellville, SC. 

A total of about 40 million board feet 

was stored in these sites. Not 

reflected in the figure are the 

additional 7 million board feet wetdecked in the plywood mill yard and 

the 13 million board feet stored in 

the GP Jamestown yard. The plateau in 

the curve between June and October 

1990 indicates that logs from the 

other sites were processed into 

plywood during this period. 

Figure 6--Cost of supplemental boiler 

fuel at the Georgia-Pacific 

Russellville plywood plant during the 

period when Hugo logs were processed 

into plywood. 

Since much of the bark normally used as 

fuel was lost due to sloughing off 

during storage and handling, the cost 

of supplemental boiler fuel went up 

during the Hugo-log utilization period, 

particularly in early 1991. The 

subsequent reduction in cost was 

probably due to better bark recovery 

when the plant started mixing fresh 

logs with the Hugo logs. 
101 I 

~t&DEC~ ~CRi\RhMAY&kMAPRMAY 

MONTH 

- FACE - BACK & INNER PUES 

Figure 7a--Percentage of face and 

back/innerply veneers produced from 

Hugo logs. 

10.. 

DATE 

Figure 7b--Grade classification of 

Hugo-log face veneers. Note: Bbs is 

a special grade of B-veneer containing 

more than 50% blue stain. 

Figure 7c--Grade classification of 

Hugo-log back/innerply veneers. Note: 

C* represents veneers of lower value 

than Cp grade due to insect boreholes. 

Figure 7a shows the percentage of face 

and back/innerply veneers produced from 

Hugo logs. The recovery of face-grade 

veneers declined, while that of back/ 

innerply-grade veneers increased during 

the period when Hugo logs were peeled. 

The negative effect on veneer grade was 

mainly due to the prevalence of insect 

holes, blue stain, brown rot, stress 

cracks, splits, shake, and rough peel. 

A breakdown of face-grade veneers in 

Figwe 7b shows that the high-quality 

A- and B-grade veneers declined 

tremendously; while the Bbs grade 

increased significantly during the 

later part of the Hugo-log utilization 

period. Bbs, a special grade, was 

created to accommodate B-grade veneer 

which has more than 50% blue stain. 

Among the four face-veneer grades, 

almost 60% were classified as Bplugged; while only about 5% were 

considered A-grade veneers. Figure 7c 

gives a breakdown of the back/innerply 

veneers into the different grades, 

Majority of the veneers (approximately 

45%) were of the D grade. C* grade 

veneers started to appear in July 1990, 

representing as much as 7% of the 

backlinnerply veneers produced. C* 

indicates veneers which are of lower 

value than the Cp grade due to insect 

boreholes . 
Figure 8--Product nix at the DeorgiaPacific ~ussellville plant during the 

period when Hugo logs were processed 

into plywood. Note: The October 1989 

increase in sheathing (SHTG) was in 

response to Hurricane Hugo protection 

and repair needs. 

The production of siding and other 

high-grade panels was reduced at times 

due to poor veneer quality. Sheathing 

panels represented approximately 55% 

of the total production, while T & G 

panels comp~ised 25%. 

Figure 9--Average percent wood failure 

during vacuum-pressure testing of 

CDX-grade panels produced from Hugo 

logs at the Georgia-Pacific 

Russellville plant. 

The best indicator of glueline quality 

is the average percentage of wood 

failure following a stringent vacuumpressure-soak cycle. Figure 9 depicts 

the glueline test performance of 

Russellville immediately prior to and 

through the processing of Bugo-downed 

timber. The Product Standard for 

Construction Grade Plywood (PS-1) sets 

a lower limit of 80% wood failure for 

conformance to the Standard. 

Remarkably, despite all the processing 

hurdles the mill had to overcome, the 

mill met or exceeded the Standard 

requirement, except for December 1990 

and January 1991. Mill management and 

the adhesive supplier monitored this 

problem closely during these critical 

winter months to insure that deficient 

panels were identified and trademarks 

indicating conformance to the Standard 

were removed from the panels. 
,. Q g iii 

Figure 10--Full-panel bending 

properties (stiffness, El; and maximum 

bending moment, F,S) along and across 

the major panel axis of Hugo plywood 

produced at the Georgia-Pacific 

Russellville plant. 

The figure presents the panel 

stiffness (EI, lb-in2/ft of panel 

width) and maximum moment (F,Sre, lbin/ft of panel width) of 15/32 , 3- 

layer Southern pine plywood produced 

from Hugo logs and tested during 

routine quarterly sampling using the 

Amerjcan Plywood Association flexure 

machine. Data for past production 

include those from 1983 to 1990. No 

apparent upward nor downward trend was 

indicated by the data, suggesting that 

the wet storage of Hugo logs had no 

negative effect on the strength 

properties of the panels produced from 

the said logs. In fact, the stiffness 

and maximum moment along and across 

the major panel axis of the Hugo 

plywood were, in general, higher than 

those of the panels from past 

productions due to the larger, oldgrowth Hugo logs processed. Note, 

however, that the average EI across 

the major panel axis of the Hugo 

plywood produced during the fourth 

quarter of 1991 was noticeably lower 

than the average from previous 

samplings. 

I 150 JrzjQl MAYbn AWQ1 ocl-a1 

DATE OFTEST 

I -w- JA~I LWS - JUNE LOGS I 

Figure lla--Dead-weight panel stiffness 

(lb-in2/ft) of plywood produced from 

Hugo logs at the Georgia-Pacific 

Russellville plant, 

i 1 '= &'so A91 MAYQl WQ1 OCT91 

DATE OF TEST 

I -n- JAN LWS + JUNE LOQS I 

Figure llb--Dead-weight modulus of 

elasticity (psi) of plywood produced 

from Hugo logs at the Georgia-Pacific 

Russellville plant. 

Figures lla and llb present the results 

of dead-weight testing conducted to 

determine the effect of the delay in 

the sprinkling of the salvaged logs on 

the quality of the panels produced. 

The tests were performed at various 

times to evaluate as well how the 
bending properties of the panels 

changed during the Hugo-log wetstorage period, The controls were 

from logs harvested from standing 

trees; the January and June logs were 

from trees domed by Hurricane Hugo, 

The January group consisted of panels 

made from logs stored in January 1990 

with water applied in April 1990; 

while the June group was from logs 

stored in June 1990 with water applied 

in July 1990. The EI and MOE of the 

June-log panels were, in general, 

lower than those of the January-log 

panels suggesting that significant 

deterioration had occurred in the logs 

which were left unprotected longer in 

the forest and were not immediately 

placed under water, The EI value of 

the January-log panels remained more 

or leas steady throughout the test 

period; while the EI of the June-log 

panels took a 19% reduction from 

185,000 lb-in2/ft in May 1991 to 

150,000 lb-in2/ft in August 1991. The 

average EI values of both the Januaryand June-log panels were above the 

minbm acceptable limit (116,000 lbin2/ft) established by the American 

Plywood Association. With regard to 

the MO&, the average for the Januarylog panels showed a steady decline from 

about 2.12 million psi to 1.8 million 

psi; while that of the June-log panels 

fluctuated between 1,75 million psi and 

1,9 million psi. All MOE averages for 

the January- and June-log panels were 

above the control-panel average of 1.68 

million psi. 
EFFECT OF LOG WET STORAGE TIME ON THE STIFFNESS OF 

SOUTHERN PINE PLYWOOD (A CASE STUDY)& 

Robert B. McAlister, Alexander Clark 111, 

and Joseph R. Saucier 

INTRODUCTION 

Hurricane HUGO, which struck the South 

Carolina coastline on September 22, 

1989, was one of the most destructive 

storms of the past 200 years. One of 

the effects of HUGO was devastation of 

standing timber in the Coastal Plain 

of South Carolina. After the storm, 

it was estimated that the downed and 

damaged timber represented over 5 

years of normal capacity for the wood 

products mills in the area. Salvage 

of the damaged pine timber began 

immediately after the storm and continued for about 9 months when it 

became unusable for most products. 

Salvage of damaged hardwood timber was 

hampered by wet logging conditions and 

limited markets, but continued on a 

limited basis for 18 months. Approximately 20 percent of the storm-damaged 

timber was salvaged. 

The major concerns which may have 

deterred more extensive salvage 

efforts were the uncertainty concerning the deterioration of logs 

stored under water sprinklers beyond 

one year and the effect of storage on 

logs which had already undergone 

considerable deterioration. 

STUDY OBJECTIVES 

We designed this study 1) to determine 

the storage time at which plywood 

produced from stored logs begins to 

lose stiffness to a measurable degree; 

and 2) to determine if increased 

storage time results in a significant 

increase in spinouts or broken veneer. 

mTERIALS AND PROCEDURES 

Logs salvaged immediately after HUGO 

(January stored logs) and logs salvaged 9 months after HUGO (June stored 

logs) were sampled at 3-month intervals beginning one year after HUGO. 

"rresnted at 46th Annual FPRS; 

Charleston, SC. June 24, 1992. 

The logs were pulled from the storage 

piles, spread on the log yard and 

measured for length and large and small 

end diameter. The logs were then 

placed on the merchandiser butt end 

first. Disks approximately 1 to 3 

inches thick were removed from the tree 

length logs at the butt and at the top 

of each 102-inch veneer block on the 

merchandiser cross-cut saw. These 

disks were placed in plastic bags and 

taken to Athens, Georgia, for moisture 

content and specific gravity determinations. Specific gravity was computed 

from green volume and ovendry weight. 

Moisture content was computed on a dry 

basis after samples were dried to 

constant weight at 21S°F. 

The study blocks were tagged on the 

ends with aluminum tags before being 

placed in hot water vats for conditioning. The two log storage groups 

(January and June) were separated in 

the vats by a marking system using both 

rope wrapping and the end tags. Blocks 

were conditioned for about 18 hours at 

170T prior to peeling. This was 

standard conditioning time for the 

mill. The blocks were peeled into 

nominal 1/6-inch veneer. Before the 

blocks from each group were peeled, the 

green chain was cleared of all veneer. 

The diameter of each dropped core was 

measured and recorded. 

The integrity of the veneer from each 

group was maintained through the 

drying, layup and pressing procedures. 

Veneer from each group was used to 

manufacture CDX (3-ply, 15/32", 

unsanded) peformance-rated panels. 

Ninety panels from each group were 

randomly selected and tested for panel 

stiffness using the American Plywood 

Association portable panel tester. 

Full size panels were supported over a 

span of 84 inches. They were preloaded 

with a 20-pound full panel width bar. 

The deflection of the panel was 
measured at the center to the nearest 

0.001 inch with a dial gauge. The 

panel was then loaded with a 20.5- 

pound full-panel width bar. The 

deflection at the center point of the 

panel was read and recorded. These 

deflection values together with the 

average thickness of the panel were 

used to calculate the panel EI or 

stiffness value. 

The stock of June stored logs was 

exhausted after the August 1991 test 

sample. A group of fresh logs of 

approximately the same diameter as the 

stored logs was substituted for the 

June stored logs in the October 1991 

study sample. These fresh logs were 

included as a comparison (control) 

group for log moisture content and 

panel properties. 

IUESULTS AND DXSCUSSION 

The timber salvaged after Hurricane 

Hugo was of very high quality. Most 

of the storm-damaged timber was oldgrowth longleaf pine (Pinus palustris 

L.) with dbh over 16 inches. This raw 

material would be expected to produce 

plywood of above average properties. 

From the start of the study, the 

difference in appearance between the 

January stored and June stored logs 

was striking. The January stored logs 

had some intact bark and appeared to 

be firm. The June stored logs had no 

bark and had obvious spongy areas on 

the surfaces and the ends. When the 

tree-length logs were bucked to 

length, the June stored logs showed 

extensive bluestain and some radial 

drying checks; the January stored logs 

showed practically no bluestain and no 

radial checking. There was little 

change in appearance over the period 

of the study, except that for the 

August 1991 sample, the June stored 

logs showed extensive decay pockets 

and zone lines. The January stored 

logs showed some light bluestain but 

otherwise remained bright and sound 

throughout the study. There were 

practically no spinouts throughout the 

study. There was no increase in core 

diameter for either the January or 

June logs. 

During the course of the study, the 

plywood mill was continually adjusting 

process variables such as veneer 

thickness, drying time, adhesive 

formulation, and pressing conditions. 

These adjustments were required to 

mintain quality in the light of subtle 

changes in veneer surface characteristics, porosity and wettability. 

These process adjustments were 

initiated primarily because of the 

characteristics of the June stored 

logs . The specific gravity and moisture cantent of the January and June logs for 

the study period are shown in Table I. 

Essentially, there was no change in 

moisture content or specific gravity 

for the study period. The 10- to 15- 

percent variation in moisture contents 

are quite common in large log piles. 

Generally, the January stored logs had 

slightly higher moisture contents than 

the June stored logs. The control logs 

had the lowest moisture content of all. 

This indicates that the sprinklers were 

maintaining acceptably high moisture 

contents in the stored logs. It also 

shows that veneer from the stored logs 

would probably require longer drying 

time than that from fresh logs. 

The average and standard deviation 

values for panel stiffness and panel 

thickness for the study material are 

show in Table 2. The minimum value 

for panel EI as established by the U.S. 

Product Standard PS-1 for Construction 

and Industrial Plywood is 116,OO lbsin2. Generally the January stored log 

group shows higher EI values than the 

June stored log group (May 1990 test is 

an exception). The January stored log 

group also had a slightly higher EI 

than the Control group tested at the 

same time. 

CONCLUSIONS 

Logs can be stored under water 

sprinklers for up to 2 years with no 

measurable degrade in panel properties. 

Changes in the process of producing 

plywood may be required. Depending on 

the time of year and the weather, 

damaged timber can be salvaged for a 

period of up to 6 months. Bluestain 

can develop very quickly in downed 

timber especially in warm weather. 

Generally bluestain affects the 

appearance but does not reduce the 

strength or stiffness of wood products. 

It is important that the salvaged logs 

be put under water sprinklers as soon 

as possible. 
Table 1--Average (standard deviation) moisture content and specific gravity for 

disks removed from test logs during the study. There were no June stored logs 

for Oct 1991 tests. 

January Stored Loqs June Stored Lass 

Test Sample MC % SG Sample MC % SG 

Date Disks Disks 

Sep 1990 169 lOl(20) 0.486(0.044) 164 96(19) 0.496(0.044) 

Jan 1991 91 104(20) 0.476(0.049) 83 105(22) 0.496(0.047) 

May 1991 62 105(26) 0.486(0.046) 67 92(24) 0.471(0.056) 

Aug 1991 99 llO(21) 0.456(0.052) 85 93(23) 0.474(0.049) 

control control control 

Oet 1991 70 104(22) 0.473(0.050) 73 83(21) 0.525(0.049) 

Table 2--Average (standard deviation) panel EI and panel thickness for the 

plywood log storage study. Each value represents 90 panels, There were no 

June stored logs for Oct 1991. 

January Stored Loqs June Stored Loqs 

Test EI Thickness EI Thickness 

Date ( lbs-in2) ( inches ) ( lbs-in2) ( inches ) 

Sep 1990 184,618(18,790) 0.404(0,010) 176,713(35,080) 0,452(0.011) 

Jan 1991 212,496(26,443) 0.464(0.009) 178,946(49,877) 0.467(0.008) 

May 1991 180,179(24,457) 0.448(0.009) 185,127(22,609) Oe460(0.O08) 

Aug 1991 183,795(27,042) 0.461(0.008) 150,967(22,061) 0.442(0.012) 

control control 

Oct 1991 199,160(19,383) 0.480(0.007) 193,056(34,116) 0.486(0,008) 

Note: the minimum EI value for Performance Rated, 15/32-inch sheathing panels 

is 116,000 lbs-in2 (U.S. Product Standard PS-1). 
Environmental Impacts 

DISTIJIRBANICE EFFECTS OF HURRICANE HUGO ON 

A PRISTIm COASTAL DSCAPE : 

NORTH INLET, SOUTH CAROLINA, USA 

LOR. ~ardner', WoKo ~ichener', TOM. ~illinms~, EoRo ~lood', 

Bo ~jerfve', LoAo smock3, D. J. ~ipscomb~ and C. Wesham2 

Abstract--Despite its intensity and landfall at high 

tide, Hurricane Hugo (22 Sept. 1989) had only a modest 

impact on the geomorphology of the undeveloped coastal 

landscape at North Inlet, South Carolina. Pre- and 

post-Hugo aerial photographs (April 1987 and October 

1989) showed no change in the salt-marsh creek network, 

nor could changes be seen in the size or shape of sand 

bars within the creeks. Several new, small washover 

fans formed on the adjacent barrier islands. These 

lobate fans extend 50 to 100 m from the dune line into 

the back barrier area and are deposited on older but 

recently formed fans in areas where the islands are 

thin and devoid of large shrubs and trees. Hugo's 

failure to have a more dramatic geomorphic effect was 

probably related to the rapid approach of the storm 

along a path perpendicular to the coast. This allowed 

minimal time for the surge to build and for wave attack 

to modify the shoreface. 

In contrast, the nearby coastal forest experienced 

extensive wind damage as well as tree mortality due to 

soil salinization by the surge. Wind damage was a 

function of tree species, diameter and soil type. The 

most severe damage occurred in mixed bottomland hardwood sites on Rutledge (sandy, silicious, thermic Typic 

Humaquepts) soils. Salt-induced foliage discoloration 

and defoliation became fully evident in the surgeinundated area by January 1990. Above-normal salt 

concentrations were found in shallow groundwater 

samples from sites up to the 3.0-m contour (MSL). Salt 

concentrations generally decreased inland from the 

forest-marsh boundary and with the passage of time. 

Trees standing along the forest-marsh boundary and in 

swales suffered the most severe salt-induced mortality. 

As of June 1991, new understory vegetation and pine 

seedlings appeared to be flourishing in the saltaffected area. Salinization also mobilized ammonium 

from soil storage as a result of ion exchange with 

seawater cations and disruption of nitrogen cycling 

processes. 

' Belle W. Baruch Institute for Marine Biology and Coastal Research, University 

of South Carolina, Columbia, SC 29208 USA ' Baruch Forest Science Institute, Clemson University, P.O. Box 596, Georgetown, 

SC 29442 USA ' Department of Biology, Virginia Commonwealth University, P.O. Box 2012, 816 

Park Ave., Richmond, VA 23284 USA 
There was a virtual absence of insects and terrestrial 

vertebrates in the surge-affected forest immediately 

following Hugo. Flying insects and birds were the 

first to return but six months after Hugo, the abundance of reptiles and amphibians remained significantly 

lower than populations observed prior to the storm, 

Scouring and high salinity had a catastrophic effect on 

benthic invertebrates in the blackwater streams of the 

forest. Population density dropped by 97% and biomass 

declined from 542 mg dry ma~s*m-~ to only 2.0 mg dry 

~I?S*LTL-~~ The cramunity recovered quickly, however, as 

density and biomass returned to pre-storm levels in 

three and six months, respectively. 

1. ImElODUCTION 

The role of disturbance in the structure, function and evolution of ecosystems has long been a topic of 

interest to ecologists (Sousa, 1984). 

Since disturbances generally lie near 

the extremes of a continuum of natural 

perturbations, the concept is difficult to define precisely. Sousa 

(1984) suggests that 'a disturbance is 

a discrete, punctuated killing, displacement or damaging of one or more 

individuals (or colonies) that 

directly or indirectly creates an 

opportunity for new individuals (or 

colonies) to become established* , 

Against this background, we report our 

obse~ations of the ecological impact 

of Hurricane Hugo on a coastal landscape. 

1.1. Hurricane Hugo 

Hugo made landfall at Charleston, SC 

at 0001 hours EDT on 22 September 1989 

(Figure 1). The hurricane, which 

started as a depression off the west 

coast of Africa on 9 September, was 

the most devastating storm to hit 

South Carolina in modern times. 

Hurricane Hugo reached its maximum 

strength several hundred kilometres 

east of the Leeward Islands on 15 

September, with a central pressure of 

918 mbar and observed surface wind 

speeds of 72 mo s'' (National Hurricane 

Center, 1989). Hugo wreaked havoc on 

the islands of Guadeloupe on 17 

September and on Puerto Rico the 

following day. The hurricane lost 

some strength as it moved away from 

Puerto Rico towards the southeastern 

United States, but gathered renewed 

energy as it crossed the Gulf Stream. 

It advanced towards the South Carolina 

coastline at a rapid 12 me s-If 

exhibited a central pressure of 935 

mbar, and had measured sustained winds 

of 39 m0s-' with gusts up to 48 mas-" 

upon landfall in Charleston (National 

Hurricane Center, 1989). 

Hugo struck South Carolina near high 

tide, which is the reason for the 

massive property damage along the 

coast. Fortunately, the hurricaneassociated rainfall was relatively low. 

Sullivans Island, just east of 

Charleston, received only 21 mm of 

rain, and Myrtle Beach, to the north of 

North Inlet, received only 6 mm. An 

unofficial rain gauge at North Inlet, 

SC registered 65 mm. Had it rained 

more, coastal flooding would have been 

far greater. 

2, METHODS 

2.1. Study Area 

North Inlet, located 90 km northeast of 

Charleston (Figure l), is one of 18 

sites in the Long-Term Ecological 

Research (LTER) network sponsored by 

the National Science Foundation. The 

site covers about 80 ?an2 and consists 

of barrier islands, intertidal salt 

marsh, and low-lying coastal forest 

(Figure 1). The site has been the 

focus of studies on coastal ecology, 

forestry and geology for over twenty 

years. At North Inlet, the storm surge 

traversed the Holocene barrier islands, 

flooded the Spartina marshes and temporarily caused ocean water to flood 

over a large area of the coastal 

forest. Fragments of Spartina caught 

in tree branches indicate that the 

maximum surge elevation was 3 to 4 m 

above mean sea level (NSL), or approximately 2 to 3 rn above mean high tide. 

The forest ecosystem at North Inlet has 

developed on sandy Pleistocene beach 

ridges and swales, which trend 

northeast-southwest (Gardner and Bohn, 

1980). The highest ridges lie about 6 

m above MSL. Approximately 30% of the 

forest ecosystem lies at elevations 

below the 3-m contour and was thus 

subject to the effects of salt-water 

inundation. The bulk of the forest 

system consists of variably-aged pine 

forest growing on the ridges. The 
Debidue 

Beach 

+::r::,j North 

I Inlet 

North 

Island 

0 t $7 KILOMETERS 2 

Figure l--Map showing path of Hurricane Hugo and geographic features of the 

North Inlet area. Barrier islands, black; marsh, shaded; Hobcaw Barony forest 

and open water, unshaded, 

swales between ridges typically contain intermittent blackwater streams, 

support stands of cypress and gum, and 

have fringes of mixed bottomland hardwoods. 

2.2. Air Photo Surveys 

Three aerial photography surveys of 

the study area were conducted in order 

to assess the effects of Hugo on the 

geomorphology and forest resources of 

the study area, Contract missions 

were flown in early October 1989, 

early February 1990 and late October 

1990, just prior to leaf-fallout of 

the deciduous trees, Photographs were 

taken with a 23 cm x 23 cm aerial 

camera suspended in a pod from a 

Cessna 150 aircraft, using Kodak 

Aerochronte 2443 infrared film, Photographs were taken in a stereoscopic 

mode with about 60% overlap and at an 

altitude that gave an approximate scale 

of 1:6000, allowing distinction of 

individual uprooted and broken trees. 

Scale-correct portions of each photograph were obtained by constructing 

overlays from a forest overstory map 

which had been rectified to 1:4800- 

scale cadastral maps produced for the 

Georgetown County Tax Assessors Office 

using ARC/INFO GIs software (Lipscomb 

and Williams, 1990), A map of discoloured and defoliated trees was then 

produced by digitizing infomation from 

the photographs to the GIs mapping 

system. These maps delineate the 

extent of salt-induced mortality in 

evergreen species. 

In early May 1990, large populations of 

pine bark beetles (Dendoctonous 

frontalis and Ips sp.) were found in 

the areas adjacent to both salt-killed 
and wind-thrown pines. Infestation 

continued throughout the summer of 

1990. The October 1990 photographs 

were used to map the mortality due to 

insect attack as well as the extent of 

salt-induced mortality in deciduous 

trees that could not be done on the 

February photos. 

For mapping geomorphic changes, the 

October 1989 photographs were compared 

with true colour aerial photos of 

1:12000 scale taken in April 1987, 

Using a GIs base map, geomorphic 

features on the two sets of photographs were digitized into GIs files 

for rectification and adjustment to a 

common scale. 

2.3. Ground Surveys 

We sampled wind damage to trees in 293 

of the 362 Hobcaw Forest stands from 

November 1989 to May 1990. Stand 

sizes range from 6 to 440*103 m2. 

Stands without 10-cm diameter-atbreast-height (DBH) trees or in which 

timber was salvaged were not sampled. 

Within each stand, we inventoried a 

randomly located 100 x 10 m2 plot by 

recording species, DBH and damage 

class of all live, woody stems greater 

than 10 cm DBH. If a stand was 

greater than 0.2 km2, two plots were 

inventoried. If a plot contained less 

than 25 trees, it was extended until 

25 'trees were inventoried. We 

visually estimated wind-related tree 

damage and assigned trees to one of 

the following damage classes : 

Undamaged: Bole not bent and 

vertical with little crown 

damage; 

Bent: Roots intact, lower bole 

vertical, upper bole not 

vertical; 

Limbs broken: Many limbs broken, 

terminal leader intact; 

Defoliated: Sparse foliage, with 

brown or dying foliage; 

Top broken: Many limbs broken, 

teminal leader broken; 

Broken: Bole broken between 

ground and crown base; 

Uprooted: Tree partially 

uprooted with bole leaning; 

Downed: Tree partially uprooted 

with bole lying on ground, 

These damage classes were grouped as 

follows for discussion purposes: 

undamaged trees (class 1); light 

damage, bole bent or limbs broken 

(classes 2 and 3); moderate damage, 

defoliated or top broken (classes 4 

and 5); heavy damage, broken, uprooted 

or downed (classes 6, 7 and 8). In 

total, we tallied 16,870 stems in 329 

plots covering 1.08% of the Hobcaw 

Forest. 

To study the effects of soil salinization on forest vegetation, ten 

sampling transects were established 

around the perimeter of the Hobcaw 

Barony (Figure 2). Each transect 

started at the boundary between forest 

and high marsh (0 m inland) and 

extended inland up to the approximate 

limit of surge penetration (-3.0-m 

contour). Most transects had one or 

more stations in the first 30 m (0, 3, 

10 and 25 m). Thereafter, stations 

were typically located at 25, 50 or 

100-m intervals. The elevations along 

each transect were surveyed with a 

transit and compass, and leveled with 

respect to known bench marks. At 

Transect 4, only the first 750 m of the 

1,6-km long transect could be surveyed 

because of the large number of downed 

trees. Sampling along transects consisted of measurements of depth-towater table at each station, chemical 

analysis of groundwater samples and 

descriptions of the type and condition 

of vegetation. Water table depths were 

obtained by augering holes at each 

station and allowing water to rise to a 

static level. Samples of groundwater 

from each hole (or standing surface 

water in some cases) were taken in 

acid-cleaned plastic bottles. The 

first transect sampling was conducted 

two weeks after Hugo, Subsequent 

samplings were conducted 4, 8, 16, 32 

and 52 weeks after the storm. During 

the first sampling, observations were 

made of the height of Spartina detritus 

in the tree branches, the location and 

thickness of detritus deposits on the 

forest floor and the extent and height 

of detritus rub marks on tree trunks. 

To investigate the effects of soil 

salinization on forest nutrient 

cycling, time series measurements of 

ammonium concentrations in soil waters 

were made at a pine forest site 

adjacent to the marsh (Figure 2). 

Detailed, long-term nutrient cycling 

studies have been conducted at this 

site since May 1983. In 1983, the 

20-year-old pine stand contained 2200 

stems per 10' m2 with a basal area of 

25.5 m2 per 10' rnZ and a mean DBW of 

14.5 cm. Sparse hardwood vegetation in 

the stand is composed mainly of wax 

myrtle (Myrica cerifera) in the understory and occasional oaks (Quercus 

spp.) and red maples (Acer rubrum) in 

the overstory. The s o i l s a r e classified as Spodosols and consist of Aeric 

Haplaquods in drier portions of the 
Marsh 

1 

- 

0 tkm 

Figure 2--Map showing extent sf salt-damaged coastal forest (shaded) and 

location of study transects on Hobcaw Barony forest including unaffected 8r-m 

(unshaded). The nutrient cycling site and Third Boundary Creek are located 

near the star on map. 

stand and Typic Haplaquods in wetter 

areas (Stuckey 1982). The spodic Bh 

horizon averages 35 cm in thickness 

and is underlain by parent material of 

weathered, quartzose sand with occasional intermixed shell, The average 

slope of the watershed is less than 

1 m per km. 

At this site, a 1000-m2 plot was 

established and subdivided into ten 

sub-plots. A groundwater well and 

lysimeters in both the A (organic) and 

Bh horizons were placed randomly in 

each sub-plot. The ten replicates 

from each well and soil horizon were 

averaged for each sample date. 

To study the effects of Hugo on the 

blackwater streams draining the 

forest, surveys were made of the preand post-storm organic matter storage 

and benthic invertebrate biomass and 

species compsition in Third Boundary 

Creek (in the northeast corner of the 

ffobcaw Barony near Transect 1, Figure 

2). Sampling was conducted during the 

three months prior to Hugo and then 

monthly beginning two weeks after Hugo. 

Depth of scour into the stream amdfaient 

was determined using the teohnhqtlst of 

Metzler and Smock (1990). Chang6~: in 

sediment organic matter storage were 

obtained from eight cores (4.8-cm 

diameter) taken during each sampling 

period. Ash-free dry mass was 

determined by ignition at 550°C for 

four hours, The benthic invertebrate 

community was quantified from eight 

samples collected with a Hess sampler 

(0.088 m2) during each sampling period. 

Samples were washed through a 0-15-mm 

pore size sieve; all organisms were 

identified, counted and measured with 

an ocular micrometer, Biomass was 

computed using regression equations 

relating dry mass to body size. 

2.4. Chemical Methods 

The concentrations of Na, R, Ca and 

Mg in water samples were measured by 

atomic absorption spectroscopy using 

a Perkin Elmer Zeeman 5100 spectrophotometer (American Public Health 

Association, 1985). Samples were 

diluted with distilled, de-ionized 
water to appropriate concentration 

ranges for analysis. Sample conductivities were measured with a 

Scientific Model 604 conductiv 

meter. Salinities were computed from 

sample conductivities and taperatures 

using the equations given in Cox and 

others (1967). nim was measured 

by automated colorimetry with a Technicon Autoanalyzer I1 or Orion Scientific Autoanalyzer System using the 

phenate method (Technicon Industrial 

Method No. 154-71W). 

3. RESULTS 

3.1. Geomorphic Effects 

Despite its intensity, Hugo had a 

modest geomorphic impact on the North 

Inlet estuarine area. Pre- and postHugo aerial photographs show no 

changes in the salt-marsh creek network, nor can changes be seen in the 

size or shape of sand bars within the 

creeks. Changes appear limited to the 

inlet and the adjacent barrier 

islands. Several small, new washover 

fans fonned on ~ebidue Beach to the 

north of the inlet and on North Island 

to the south (Figure 1). These fans 

extend 50 to 100 m from the dune line 

into the back barrier area and are 

lobate in form. The largest new fan 

(on North Island) extends as a finger 

about 500 m into the back barrier where 

it encounters a small creek. Nonetheless, no breach developed in the 

island. New fans appear to have 

developed on older, but recently formed 

fans in areas where the barrier islands 

are thin and devoid of large shrubs and 

trees. Sand for the fans probably was 

obtained by levelling and breaching of 

the pre-storm dunes. The pre- and 

post-storm configurations of North 

Island are shown in Figure 3. At North 

Inlet itself, post-storm photographs 

show that some of the former offshore 

bars are diminished or missing. This 

suggests that the large ebb-tidal delta 

experienced erosion when the large 

0 .5 1 

KILOMETLRS 

0 5 1 

KILOMETERS 

WATER 

MARSH 

ad 75 w .t^ " - SANDIDUNE 

35 NC 

sc NEW WASHOVER 

' * NORTH INLET 

* CWFSTON 

I 

h 

EBB TIDAL BAR 

SHORE FACEIBERM 

H INTERTIDAL SAND FLAT 

BACK BARRIER VEGETATED 

BACK BARRIER UNVEGETATED 

Figure 3--Pre- (a) and poet-Hugo (b) geomorphology af the north and of North 

Island. 
volume of surge water drained as sheet 

flow across the marsh on the following 

ebb tide, but became constricted and 

channelized at the inlet. 

The main effect of the storm in the 

marsh was to transport much of the 

dead Spartina stalks and leaves into 

the adjacent forest, where it was 

deposited as mats of detritus. The 

storm had no visible effect on live 

Spartina, which was neither uprooted 

nor bent. Although a thin film of mud 

coated the litter in the forest, no 

measurable erosion or deposition of 

mud could be detected in the marsh, 

3.2. Forest Wind Damage 

Wind damage to the forest was extensive and varied with tree species, 

diameter and soil type. Approximately 

73% of the trees sampled was undamaged 

(24%) or lightly damaged (49%), while 

16% was moderately damaged and 11% was 

heavily damaged. Live oak (Quercus 

virginiana) and swamp tupelo (Nyssa 

sylvatica) were the least damaged of 

the hardwoods. Longleaf pine (Pinus 

palustris) was the least damaged of 

the pines with 87.7% of the stems 

undamaged or lightly damaged. 

Approximately 84% of the bald cypress 

( Taxodium distichum) stems was 

undamaged (11.2%) or lightly damaged 

(73.0%). Laurel oak (Quercus 

laurifolia) and water oak (Quercus 

nigra) were the most heavily damaged 

hardwoods, while pond pine (Pinus 

serotina) was the most heavily damaged 

pine. In general, the trees larger in 

diameter were more heavily damaged. 

Large water oak and pond pine were 

more likely to be uprooted while large 

laurel oak and loblolly pine (Pinus 

taeda) had more bole breakage. Tops 

were also broken in the larger live 

oaks. Since tree diameter was related 

to the degree of damage, losses of 

basal area are the best indicators of 

losses due to the hurricane. When 

basal area is used as a measure of 

loss, 43% of pond pine, 35% of water 

oak, 17% of loblolly pine, 11% of 

longleaf pine and 3% of live oak were 

heavily damaged. These results agree 

with previous data on the resistance 

of these species to wind damage 

(Touliatos and Roth, 1971; 

Glitzenstein and Harcombe, 1988; 

Harcombe and Marks, 1983; Lugo and 

others, 1983; Putz and others, 1983). 

A listing of all species-damage 

estimates and statistical analyses of 

the wind damage data can be found in 

Gresham and others (1991). 

Heavy damage occurred primarily in 

mixed bottomland hardwood sites on 

Rutledge (sandy, siliceous, thermic 

Typic Humaquepts) soils (Stuckey, 

1982). Water oak, which grows on such 

soils, suffered the greatest proportion 

of uprooting, 

3.3. Surge Effects on Forest 

Vegetation 

Based on surveyed water marks, 

Schuck-Rolben (1990) estimated that the 

elevation of the Hurricane Hugo surge 

at North Inlet was about 3.3 m above 

MSL. This allowed salt water to penetrate to about the 3,O-m contour in the 

adjacent maritime forest. At this contour, the maximum distance of penetration is about 1,s km into the forest 

from the forest-marsh boundary. Penetration of the surge into the forest 

resulted in salinization of the forest 

soils, death to some trees and forest 

vertebrates, mobilization of soil 

ammonium and scour of blackwater stream 

bottoms with attendant disruption of 

the benthic invertebrate community. 

The effects of salt stress on forest 

vegetation began to appear shortly 

after the storm and were fully evident 

by December 1989. Within a few days 

after Hugo, the pine needles along the 

edge of the marsh had turned brown, 

This early browning may have been due 

to wind burn and/or salt spray during 

the storm. The most salt-sensitive 

tree species appeared to be black gum 

saplings, whose leaves turned brown 

throughout the surge-affected area 

within one week of the storm. Wind 

burn is not likely to be the cause of 

the browning for these trees since they 

were protected from wind stress by the 

taller trees. 

Two weeks after the storxn, 80 to 100% 

of the leaves and needles on trees and 

shrubs located within 10 m of the marsh 

along the eastern edge of the forest 

had turned brown or dropped as a result 

of salt andlor wind stress, At distances of 50 to 150 m from the marsh, 

10 to 50% of the pine needles showed 

signs of browning while all gum and oak 

leaves had turned brown or dropped, 

Further inland, the spatial pattern of 

salt stress became more complex, For 

example, along Transect 1 (Figure 2), 

pine needles appeared healthy at the 

station 467 m from the marsh, although 

wax myrtle (Myrica cerifera) and 

blueberry (Vaccinium spp.) leaves had 

browned or dropped. At a distance of 

626 m from the marsh, approximately 10% 
of the pine needles were brown while 

no indications of salt stress were 

observed at stations located 784, 943, 

and 1101 m from the marsh. In 

general, understory vegetation showed 

evidence of salt stress at much 

greater distances inland than large 

trees. 

Tree mortality due to intrusion of 

salt water became apparent in early 

er and was mapped using the 

February 1990 aerial photographs* 

Salt-induced mortality is distributed 

throughout the eastern side of the 

forest (Figure 4) and is about equal 

in magnitude to the wind damage. 

Mortality along the southern and 

western sides of the forest was less 

severe, probably because the surge 

there consisted of low-salinity Winyah 

Bay water. Mortality was most severe 

along swales and at the boundary 

between forest and marsh, 

3-4, Salinization of Forest 

Soils 

Space does not permit a display of a11 

soil-salinization time series data. 

Two typical transects of Na concentration, water table depth and station 

elevation are shown in Figures 5 and 6. 

Prior to Hugo, Ha concentrations in the 

forest groundwater ranged between 4 and 

30 mg* dm-' (T. Williams, unpublished 

data). Two weeks after Hugo, most 

stations in the surge-affected forest 

had Na concentrations in excess of 100 

~tg*dm-~, with many in excess of 1000 

mg* dm-'. Maximum concentrations 

approached 4000 mg* dm-3 or approximately 40% that of seawater. In 

general, Na concentrations decreased 

both inland and with the passage of 

time. By January 1990, Na had declined 

at most stations by an order of magnitude, with a few falling back into the 

pre-Hugo range. Between January and 

May 1990, concentrations of Na tended 

to rise at most stations as water table 

elevations fell during this unusually 

dry spring, By October 1990, Na concentrations were approximately or 

slightly lower than those in January. 

There is some indication that Na 

concentrations were lower in swales 

than on ridge sites, but the data are 

not consistent for all transects. Soil 

Figure 4--Map of pine and hardwood mortality due to soil salinization and bark 

beetle attack. 
600 40 

- 

- 500 

E 

5 30 - 

2 400 E 

91 

n 

300 .- - 20 2 

n $ 200 a - - Uf 

.- to 2 100 (D n 

0 0 

-100 100 300 500 700 900 1100 

Meters Inland 

Figure 5--Spatial and temporal variation of Na concentration in groundwater and water table depth (upper two 

panels) along Transect 1. For 

clarity, only data for three of the 

six sampling dates are shown. 

Profiles of ground elevation and 

thickness of detrital deposits are 

shown on bottom panel. 

salinization extended about 700 m 

inland along Transect 1 to an 

elevation of -4.0 m MSL (Figure 5). 

Along Transect 4 (Figure 6), salinization extended inland 1500 m, but 

elevation measurements are not yet 

available f o r t h e landward end of this 

transect. All other transects across 

the east side of the forest showed 

salinization along their entire 

length. Maximum elevations along 

these transects are below 4.0 m NSL. 

Although most ridge sites and some 

swale sites showed a monotonic 

decrease in Na with time, there were 

several exceptions, particularly in 

the May sampling. Most notable are 

the ridge sites between 400 and 700 m 

on Transect 1 (Figure 5) and the ridge 

site at 250 m on Transect 4 (Figure 

6) * 

-I i-Elevrtion 

+Detritus Depth 

olll.lll,, 0 

-100 $80 306 508 780 908 1160 1306 1500 1700 

Meters lnland 

Figure 6--Spatial and temporal variation of groundwater Na concentration 

and water table depth (upper two 

panels) along Transect 4. For clarity, 

only data for three of the six sampling 

dates are shown. Profiles of ground 

elevation and thickness of detrital 

deposits are shown on bottom panel. 

At the majority of stations, the water 

table elevation fell during the first 

three samplings, but rose again following the recharging rains of December 

and early January. The water table 

again fell during the dry spring of 

1990 but recovered by the final 

sampling in October. In general, water 

table fluctuations were greater on 

ridge sites than along the marsh edge 

or at swale sites, 

3,5, Mobilization of Soil 

onium 

salinization also affected the 

concentrations of ammonium. in soil 

and groundwaters (Figures 7 and 8). 

Approximately 1.5 m of salt water 

inundated the long-tern nutrientcycling study site (Figure 2) during 
1 1 Forest Floor 

Ground water 

0 20 40 60 80 100 120 

Days After Hugo 

Figure 7--The series of ammonium and 

sodium concentrations in standing, 

soil and groundwaters at the long-term 

forest nutrient cycling site. Na 

measurements are unavailable for 1990. 

Ammonium data for 1990 are shown in 

Figure 8. 

SONDJFM AMJJ AS 

1989 1990 

Figure 8--Time series of amonium 

concentrations in soil and groundwater 

at the long-term forest nutrient 

cycling site for the year following 

Hurricane Hugo. 

the storm surge. Two days after Hugo, 

water standing on the forest floor had 

an average salinity of S=21. As the 

salt water penetrated the soil, significant alteration of the soil solution occurred. Two weeks before the 

storm, soil-solution total ionic 

content (TIC) averaged 1.6 meqwdm-3 in 

A-horizon soil water and 3.4 meq*dme3 

in groundwater. Two days after the 

storm, TIC was 227 to 778 meq OK a 

salinity of S=2.3 to 12. Soil-solution 

salinities were lower than standingwater salinities due to dilution by the 

underlying fresh groundwater. Maximum 

soil-solution salinities, ranging from 

S=9.7 (Bh horizon) to 13.0 (A horizon), 

were detected one week after the storm. 

In early October, soil-solution 

salinities declined due to dilution 

from rainfall (103 m) and a rising 

water table. During the November dry 

spell, groundwater elevation declined, 

resulting in an increase in soil 

salinity. Two months after Hugo, TIC 

remained elevated by 58 to 142 times 

the pre-storm values. 

Two days after Hugo, Na concentrations 

in soil solution were 16 (A horizon) to 

122 (groundwater) times the annual 

average concentrations for 1984 to 

1987. Initially, Na concentrations 

(Figure 7) were greatest in water 

ponded on the forest floor (245 meqodm- 

' ) and in groundwater ( 107 meq* dm-') . The initially higher concentration of 

Na in the groundwater as compared to 

that in the overlying soil horizons was 

due to the fact that surge water 

flooded down and filled the open 

piezometer pipes, and then seeped into 

the surrounding aquifer after the surge 

retreated. Concentrations of Na in 

ponded surface water and groundwater 

declined for the next three weeks and 

then began to increase until midNovember (Figure 7). Maximum Na 

concentrations in the A horizon were 

detected one week after Hugo, fluctuated around 85 meq* dm-3 until midNovember and declined erratically 

thereafter. In the Bh horizon, Na 

increased almost linearly following 

Hugo and reached a maximum concentration of -122 meq-dm-' early in 1990, 

beyond which our samples have not yet 

been measured for Na. 

If the early contamination of groundwater by flow of surge water down the 

piezometer pipes is ignored, then these 

results suggest the downward movement 

of a saline front that originated in 

the ponded surge water at the surface. 

Movement of this front probably was 

driven by both advection (to replace 
losses of soil water by evapotranspiration and seepage) and diffusion. 

Two distinct phases were observed in 

the response of nium to soil 

salinization. T 

developed within two days after the 

stom and lasted for about one month. 

Prior to Hugo, average concentrations 

of nium in the A and Bh soil 

horizons were 0.34 and P .O peq* dm3, 

respectively, whereas the average in 

14 peqedm3. Two days 

nium concentrations in 

izons were 20 and 10 

times greater than their pre-storm 

averages, respectively. Groundwater 

nium concentration at this time 

was similar to the pre-storm average. 

Two days after Hugo, the highest concentration of ammonium was found in 

water standing on the forest floor (77 

peq*~h-~). It is unlikely that the 

original surge water had this level of 

ammonium because seawater at North 

Inlet typically contains only 1.0 to 

3.0 peq* dm-3 (Whiting and others, 

1987). Therefore, the excess ammonium 

observed in the standing water must 

have been derived from the forest 

floor during its two days of residence. monium concentrations in the 

standing water remained nearly constant at about 100 peqedm" during the 

month following Hugo, even though Na 

concentrations decreased due to dilution by rain and diffusion into the 

underlying, less saline soil water 

(Figure 7). About one month after 

Hugo, ammonium in the standing water 

suddenly rose to a peak concentration 

of 1800 peq*&ir3, marking the onset of 

the second phase in the ammonium 

response to salinization. During the 

month following Hugo, ammonium in the 

A and Bh horizons and in groundwater 

rose to concentrations of 50 to 100 

leq* dmm3 (Figure 7 ) , but thereafter 

showed dramatic increases similar to 

that observed in the standing water. 

Ammonium. in the A horizon reached a 

maxim- concentration of 1000 ~eq*dm-~ 

about six weeks after Hugo, and thereafter began to decrease gradually but 

erratically* In the Bh horizon and 

groundwater, the second phase in the 

monium response was not as dramatic 

as in the standing water and A 

zon, and was somewhat delayed. 

nium in the Bh horizon increased 

ptly from 50 to 250 peq*&r3 about 

one month after Hugo and then rose in 

hamony with Na until it reached a 

peak concentration of 1000 peqdm3 in 

early 1990 (Figure 8). Thereafter, 

nium in the Bh horizon decreased 

gradually in a similar fashion to the A 

horizon. Groundwater ammonium, also 

showd an abrupt increase (50 to 200 

peq*dnr3) about one month after the 

storm (Figure 7) and continued to rise 

gradually- but erratically throughout 

the year following Hugo (Figure 8)- 

One year after Hugo, nium concentrations in the A and Bh soil horizons 

and in groundwater were still several 

orders sf mgnitude greater than their 

pre-storm averages. 

The lag between the A horizon and 

groundwater in reaching their peak 

ammonium concentrations suggests the 

downward movement of a layer of 

ammonium-enriched water that formed 

suddenly a month after Hugo on the 

forest floor and/or in the A horizon. 

As in the case of the saline front 

mentioned above, movement of this layer 

probably was due to advection and 

diffusion. 

3,6, Effects on Freshwater 

Benthos 

The surge also affected the benthic 

ecology of blackwater streams in the 

Hobcaw Forest. Measurements made in 

Third Boundary Creek indicate that the 

surge scoured the sand bottom to a mean 

depth of 6 cm, about three to four 

times greater than the usual month-tomonth scour depth, This had a significant effect on detritus storage and the 

benthic invertebrate community. Detritus storage in the top 5 cm of sediment 

prior to the storm was 4.2 kg ash-free 

dry mass* m-'. Scouring suspended all 

of this detritus into the water column. 

During recession of the surge, 5 cm of 

sediment and detritus was redeposited 

in the channel, but detritus storage 

decreased to 2,4 kg-m-', a net loss of 

1.8 kg0m-'. This loss of detritus 

represents a large transfer of energy 

from the channel to the forest and/or 

marsh. Scour also transferred detritus 

from the largely anaerobic sediments of 

the channel, where decomposition and 

hence cycling rates were slow, to 

aerobic environments where decomposition and incorporation into detrital 

food webs occur more rapidly. 

The combination of scour and high 

salinity initially had a catastrophic 

effect on benthic invertebrates in the 

stream. Prior to Hugo, invertebrate 

density on the sediment was 4580 

ind* m2, whereas the density 

ately after the stom was only 165 m-', 

a 97% decrease, Biomass declined from 

542 mg dry rna~s*m-~ toonly 2 mg*m-2. 

However, the community recovered 
quickly as density and biomass 

returned to pre-storm values three and 

six months after the disturbance, 

respectively* 

Species composition was greatly 

altered in the stream. The amphipod 

arus tigrinus had been the most 

abundant species in the stream, 

composing 76% of the density and 93% 

of the biomass, Aquatic insects, 

primarily Chironomidae (Diptera), also 

were common, Immediately after Hugo, 

no amphipods and few chironomids were 

found: benthic copepods, oligochaetes 

and ostracods were the predominant 

organisms, although low in number, In 

the months following the storm, 

several species of chironomids 

(Chironomus spp,) became the dominant 

taxa, Gammarus was initially slow to 

recover. However, it began steady 

recolonization four months after the 

storm, and one year later it composed 

93% of the density and 62% of the 

biomass. 

3.7. Effects on Forest 

Vertebrates 

Surveys made of fauna in the marsh and 

forest following Hugo were marked by 

the near absence of insects, birds and 

other organisms, The surge killed or 

displaced virtually all fauna in the 

flooded portion of the forest. Numerous carcasses of rice rats (Oryzomys 

palustris), Eastern gray squirrels 

(Sciurus carolinensis), marsh rabbits 

(Syvilaqus palustris) , f era1 hogs (Sus 

scrofa) and various shore and wading 

birds were found within 100 m of the 

marsh. Habitat damage to the avian 

nesting community was severe. Nesting 

trees for red cockaded woodpeckers 

(Picoides borealis), bald eagles 

(Haliaeetus leucocephalus) and ospreys 

(Pandion haliaetus) were severely 

damaged. Flying insects and birds 

were the first organisms to return to 

the forest and marsh, Observations 

made six months after Hugo suggest 

that the abundance of reptiles and 

amphibians along the eastern edge of 

the forest remained significantly 

lower than densities observed prior to 

the storm. 

4, DISCUSSION 

In general, the geomorphic effects of 

Hugo were focused on the barrierisland portion of this coastal landscape whereas the ecological effects 

were focused on the nearby coastal 

forest. The intervening marsh displayed no obvious ecological or 

geomorphic effects, probably because 

it was protected during the surge by 3 

to 4 m of water from wind, wave action 

and currents. 

4.1. Geomorphic Effects 

Hurricane Hugo was a category-$ storm 

(Ludlum, 1989), Despite the extensive 

property damage that it caused along 

the coast, Hugo's geomorphic effect on 

the undeveloped landscape at North 

Inlet was minimal. In the absence of 

direct measurements, we hindcast wind 

and wave characteristics for Hugo at 

North Inlet as the storm approached 

landfall, using the procedures of 

Kjerfve and others (1986). The 

results, given in Gardner and others 

(1991), indicate relatively steady 40 

m* s-I winds from 30 N for more than 12 

hours preceding landfall, Hugo was a 

rapidly translating storm with a large 

radius of maximum winds, two reasons 

why the storm did not become more 

intense, The calculations yielded a 

maximum local significant wave period 

of 11.7 s at the time of landfall, a 

peak significant wave height of 10.7 m 

in deep water and a maximum deep-water 

wave length of 213 m. However, as the 

South Carolina shelf slopes gently 

seaward with the 20-m and 50-m isobaths 

located offshore at 50 km and 100 km, 

respectively, these waves initially 

would have broken very far offshore, 

and thus would have been considerably 

smaller than the calculated heights at 

the time they broke again on the 

barrier beaches at North Inlet. 

The landward distance of overwash deposition by Hugo did not exceed the mean 

distance of 130 m determined by Godfrey 

(1970) for ten years of storm activity 

at Core Banks, North Carolina. On the 

basis of this parameter, Hugo's impact 

at North Inlet appears to be similar to 

that of Hurricane Ginger in 1971 (100 

m, Dolan and Godfrey 1977), but small 

compared to that of Hurricane Carla, 

which made landfall in Texas in 1961 

(Hayes, 1978) with a wind speed and 

surge height similar to Hugo. 

Hugo's failure to have a more dramatic 

geomorphic effect on the North Inlet 

landscape may be due to several factors. The storm approached normal to 

the coast at a fast speed, The rapid 

approach did not allow much time for 

the surge to build or for wave attack 

to modify the shoreface. Had the storm 

travelled parallel to the coast just 

offshore at a slower pace, the surge 

may have been larger and the wave 

attack prolonged. In addition, if the 

storm had moved along the coast, the 

wind direction would have shifted 
suddenly from onshore ahead of the eye 

to offshore behind the eye, This 

sudden change of wind direction would 

have driven surge water out of the 

back barrier and enhanced the chance 

for bayside breaches of the barrier 

(Leatherman, 1982). Finally, the 

paucity of rainfall associated with 

Hugo added little to the volume of 

water draining from the back barrier 

following passage sf the eye, 

The lesson to be learned from Hugo is 

that while man-made structures are 

prone to catastrophic damage by such 

storms, natural barrier islands are 

well designed to cope with the wind 

and wave energy associated with 

hurricanes and tropical storms. 

4.2. Tree Mortality and Forest 

Recovery 

Damage due to Hugo to the Hobcaw 

Forest was caused directly by wind, 

subsequently by soil salinization and 

finally by insect attack of trees 

stressed by both wind and salt. Wind 

damage to Hobcaw Forest was less 

severe and showed more resistance 

differences by tree species and size 

than forests further south, which were 

in the path of the eye wall (Hook and 

others, 1991). Subsequent damage to 

the forest by salinization and bark 

beetle attack resulted in approximately the same magnitude of tree 

death as the wind. In early May 1990, 

large populations of pine bark beetles 

were found in areas adjacent to both 

salt-killed and wind-thrown trees, 

These insects continued to infest pine 

trees throughout the summer of 1990. 

The extreme heterogeneity and patchiness of tree mortality and its continuing nature have made ground-based 

study of salinization and beetlecaused mortality extremely difficult, 

In addition, determination of the 

cause of pine mortality is confounded 

by infestation of both a primary cause 

of death (Dendroctonus) and insects 

(Ips sp.) that attack trees already 

dying from another cause. Thus, were 

the trees killed by the insects or 

were the insects attracted to trees 

that were already dying from salt 

stress? 

In any case, subsequent mortality was 

most severe in hardwood swales and 

closed depressions that trapped surge 

water. Pine mortality occurred mostly 

in areas adjacent to swales. This was 

true even for beetle-infested trees in 

the surge-inundated area. This 

distribution suggests that saline soil 

either directly killed these pines or 

so severely stressed the trees that 

beetle attacks were nearly exclusive to 

these trees, Outside of the surge 

area, fatal beetle attacks were primarily by Dendroctonus, Field inspection of these sites usually revealed 

that the initial attack was in bent or 

broken loblolly pine. Although limited 

in extent, this mechanism increased the 

total mortality of loblolly pine due to 

wind damage. 

Recovery of the forest will be a longterm and uncertain process, particularly in the surge area. Extensive 

areas of hardwoods failed to produce 

leaves in March 1990 when spring growth 

normally begins, However, a few leafless hardwood and cypress trees managed 

to resprout by the summer of 1991, 

Pine seedlings also appeared in the 

surge-affected area in the summer of 

1990 but most of these turned brown and 

died shortly thereafter. A new cohort 

of pine seedlings appeared in the 

summer of 1991, and appear to be 

flourishing so far. This difference in 

survival of the two cohorts is probably 

due to progressive flushing of salt 

from the forest soil, but also could be 

due to the fact that the spring and 

summer of 1990 were very dry. It 

remains to be seen whether this year's 

cohort survives as they send their 

roots into deeper and perhaps more 

saline soil. Recovery is likely to be 

most drawn out and problematic in 

hardwood swales. Salt leached from 

ridge soils will seep down-gradient 

towards swales, thus prolonging saline 

conditions there. Swale soils are 

humus rich, water-logged most of the 

year and thus anaerobic, Sulphate 

reduction is likely to occur due to 

high concentrations of sulphate in 

seawater, In iron-deficient soils such 

as these, the resulting H,S will be 

lethal to both seedlings and surviving 

adults. Recent analyses of soil waters 

in swales indicate low levels of 

sulphide in some samples (Gresham, 

unpublished data). Should such 

conditions become more pervasive, the 

lower ends of some swales may be 

permanently transformed into Juncus 

marsh. 

4.3. Mechanisms of Soil 

Salinization 

There were probably several mechanisms 

involved in the salinization of the 

forest soil, When the surge occurred, 

the water table was near the ground 

surface along the swales, but 30 to 60 
cm below ground level along the 

ridges. Figure 9 shows the hydrographs of four continuously recording 

wells before arrival of the surge, 

along with the record of rainfall from 

a weighing rain gauge. The surge 

terminated the records of all four 

wells, but the rain gauge continued to 

operate throughout the storm. Wells 

12-5 (swale) and 21 (ridge) abruptly 

went off-scale between 2300 and 2330 

hours on 21 September, indicating that 

the surge entered the forest at about 

2300 h and had covered some of the 

ridges by 2330 h. Just prior to submergence by the surge, the water level 

in well 21 was about 12 cm below 

ground level. As one unit of infiltration usually results in a ten-unit 

rise in the water table in these sandy 

forest soils, the soil near well 21 

probably had enough unsaturated pore 

space to accommodate about 1.2 cm of 

salt-water infiltration. Well 12-5, 

on the other hand, is located in a 

swale and the water table at this site 

was nearly at ground level when the 

surge arrived; thus there was probably 

little, if any, pore space for saltwater infiltration at this site. The 

records for the other ridge wells are 

unclear because either the float 

caught or the ink smudged, However, 

using the one-to-ten infiltrationwater level response rule, we can 

estimate the quantity of salt-water 

infiltration at these sites, The rain 

gauge record indicates that approximately 41 mm of rain fell up to the 

time of arrival of the surge, implying 

a 41-cm potential rise in the groundwater level from the pre-storm base 

level. This suggests that by the time 

the surge arrived, well 44 should have 

risen to about 23 cm below ground 

level while well 12-1 should have 

risen to about 15 cm below ground 

level. This would have allowed 2.3 

and 1.5 cm of salt-water infiltration 

at wells 44 and 12-1, respectively. 

Thus, one factor controlling the 

spatial variation in salinization is 

the depth to the water table at the 

time of the surge. In turn, this was 

controlled by elevation, topographic 

slope and soil permeability. Our 

experience indicates that ridges 

underlain by coarse permeable sands 

have substantially lower average water 

table elevations than ridges underlain 

by fine to medium sand even if elevation and topography are similar. 

Along swales, very little salt water 

immediately entered the nearly 

saturated soil. When the surge 

receded, about 1.0 rn of salt water was 

Figure 9--Records of water table elevations (MSL) at four forest well sites 

up to the arrival of th surge (top 

panel). Open circle indicates time 

that float caught. Closed square indicates where ink smudged and records 

might not be accurate. The X's indicate where records went off-scale, 

which is approximately equal to ground 

elevation, The bars above the circle 

and square show elevation of ground in 

relation to the last readings. Bottom 

panel shows record of cumulative rainfall where the closed square indicates 

cumulative rainfall up to the arrival 

of the surge. 

trapped in the low gradient swales that 

were obstructed by downed timber and 

blowdown plates. The water in these 

depressions remained in the forest for 

over two weeks after the storm; saline 

water then moved into the soil to 

replace water lost by transpiration. 

Salt also diffused into the underlying 

freshwater. 

Though more salt water initially infiltrated ridge soils than swale soils, 

trees on ridge sites generally showed 

less evidence of salt stress than those 

in or near swales. No clear explanation can be given at this time for this 

paradox but several suggestions can be 

offered, During October and November, 

the water table dropped to greater 

depths beneath ridge sites than in 

swales. Several modest rain events 

during this period may have been 
sufficient to dilute andfor elute 

residual salt from ridge soils above 

the water table, This may have 

allowed trees there to transpire less 

saline water from the unsaturated soil 

zone. The water table remained closer 

to ground level along swales, entirely 

covering tree roots in saline water. 

In addition, salt water that entered 

ridges should drain down-gradient 

towards swales. Thus, saline groundwater should disappear from ridge 

sites more rapidly than from swales. 

4.4. Mechanisms and Implications of onium Mobilization 

Soil nitrogen dynamics were dramatically affected by exposure to saline 

water. In general, ammonium concentrations in all soil horizons 

increased approximately an order of 

magnitude immediately after Hugo, 

decreased slightly in the following 

several weeks and then increased 

suddenly by about another one to two 

orders of magnitude one month after 

the storm. Subsequently, ammonium 

concentrations in the A horizon began 

a gradual decline to levels that, one 

year after the storm, are still an 

order of magnitude greater than 

pre-storm values, Ammonium concentrations in the Bh horizon continued to increase until early 1991 

and have since declined very gradually 

to levels that are still two to three 

orders of magnitude above pre-storm 

values. Although erratic, groundwater 

concentrations of ammonium rose 

throughout the year following Hugo to 

levels that are now several orders 

greater than those prior to the storm. 

The initial rapid increase in ammonium 

was most probably due to ion exchange 

with seawater cations. Ammonium 

occurs as an exchangeable cation on 

clay-humus colloids and can be 

extracted by leaching with NaCl 

solutions (Armson, 1977). 

Three processes may have produced the 

dramatic second-phase increase in 

monium that occurred about a month 

after the storm: inhibition of nitrification, increased decomposition of 

storm-deposited litter and decreased 

uptake of N by stressed and dying 

vegetation. Soil solution nitrate 

concentrations in the A and Bh 

horizons exceeded ammonium concentrations by three to fourfold prior to 

Hugo. Two days after Hugo, ammonium 

exceeded nitrate by up to eightfold. 

Nitrate concentrations in soil solutions declined rapidly to undetectable 

levels one month after the storm, 

Increased monium concentrations may 

have resulted from inhibition of nitrification by chloride. McClung and 

Frankenberger (1985) observed rapid 

inhibition of nitrification when soil 

was treated with 0.1 to 0.6% NaCl. 

They measured 39 to 83% decreases in 

nitrification within 21 days. Chloride 

concentrations after Hugo were sufficient to inhibit the conversion of 

ammoniu to nitrite (Roseberg and 

others, 1986). These investigators 

also found greater inhibition at lower 

pHfS. The pH of the soil solution 

after Hugo at this site ranged between 

four and five. 

Increased ammonium concentrations may 

also have resulted from the decay of 

litter deposited by the storm. Litterfall resulting from wind damage and 

salt stress was heavy. In some areas, 

thick mats of Spartina litter were 

deposited by the surge on the forest 

floor. This large input of litter 

could have provided ammonium to the 

soil water by decomposition and leaching. Although we did not measure the 

amount of litter deposition or its 

decay rate, we have projected the 

hurricane-induced nitrogen input by 

using measured normal litterfall from a 

30-year-old loblolly pine stand similar 

to our site (Blood and others, 1991). 

Such a stand with a stem density of 

2200 stems produces -0.4 kgom-' of 

needle litter per year (Gresham, 1982). 

Loblolly pines drop -50% of their 

annual production each year, thus the 

standing leaf biomass estimate for this 

site is 0.8 kg*m-' (R. M. Allen, pers. 

corn.). Loblolly pine reabsorbs 45% of 

its leaf nitrogen prior to senescence, 

making the green needle content 1.36% 

nitrogen. The projected nitrogen input 

from hurricane-induced litterfall is 

thus 10.9 g*m-'. This is about four 

times the nitrogen input that would 

gradually occur during a normal year. 

The total annual nitrogen input to this 

site by precipitation through fall and 

stemf low is only 0.24 gem2 (Blood and 

others, 1989). The lag in the release 

of amonium from litter decomposition 

may have been due to inhibition of 

decay immediately after the storm by 

standing saline water and residual salt 

in the litter. 

Decreased vegetative uptake of nitrogen 

following Hugo also may have allowed 

the buildup of amonium in soil waters. 

Root damage by wind stress (Parrotta 

and Lodge, 1991) and increased osmotic 

pressure in soil water may have 
hindered plant uptake of N during the 

early weeks following Hugo. Biological uptake of N is normally rapid in 

undisturbed forests, and the pools of 

available monium and nitrate are 

relatively small and turn over quickly 

(Vitousek and Matson, 1985). The 

continued elevated monium concentrations months after Hugo may be partly 

due to decaying roots and depressed 

rates sf N-uptake, 

The continuing increase of ammonium. in 

the groundwater is probably due to its 

production in, and downward migration 

from, overlying soil horizons, Being 

largely below the root zone, it is not 

clear whether the great amount of 

moniunt now stored in the deeper 

groundwater will again be taken up by 

plants. 

The impact of salinization on nitrogen 

dynamics may have a longer-lived 

effect on the forest than wind damage, 

Hurricanes with soil salinization 

decrease the efficiency of nutrient 

cycling through the rapid loss of 

leaves without N reabsorption and 

decreased N-uptake by vegetation, 

Microbial inunobilization of N and 

absorption of ammonium ions on soil 

exchange sites are also reduced by 

sea-salt cations, Decomposition of 

hurricane-induced litterfall, together 

with inhibited nitrification and plant 

uptake, produces a large pool of soil 

water nitrogen which may be exported 

from the forest system by groundwater 

seepage and surface runoff. Loss of 

this nitrogen pool might limit the 

forest nitrogen and delay or prolong 

recovery. 

4.5. Implications for Landscape 

Evolution 

Variability in ecosystem patterns and 

processes observed at any given point 

in space or time is a function of 

controls operating over multiple 

spatial-temporal scales (Delcourt and 

Delcourt, 1988). The barrier island 

and marsh ecosystems at North Inlet 

have developed during Holocene time 

under a regime of slowly rising sea 

level (Gardner and Bohn, 1980). As 

sea level rises, the boundary between 

forest and marsh moves inland due to 

salinization of forest soils, It is 

not known whether this succession is 

gradual or occurs in pulses, perhaps 

triggered by surge events, Thus it 

will be of interest to observe whether 

the low-lying forest along the marsh 

and in swales recovers or is 

permanently transformed into marsh. If 

permanent transformation should occur, 

then Hugo will have been a 'disturbance' in the fullest sense envisioned 

by Sousa (1984). Only with continued 

research and data collection will it be 

possible to determine the range of 

variation in scale and intensity of 

natural disturbances (Pickett and 

White, 1985; Glitzenstein and Harcombe, 

1988), and to recognize and interpret 

community and ecosystem responses to 

short-term events, such as hurricanes, 

within the context of longer-tern 

changes such as sea-level rise 

(Delcourt and others, 1983). 

ACKNOtJZIEDGNENTS 

Funds for this study were provided by 

NSF-SGER grant BSR-9001807, NSF grant 

BSR-8514326. NOAA grant NA90AA-D-SG672 

and appropriations from the State of 

South Carolina. Technical assistance 

with sampling and laboratory analyses 

was provided by J. Jefferson, D. Spoon, 

D, Karinshak, B, Haskin, P. Anderson, 

D, Taylor, S, Service, L, Smith, J. 

Jones, M, Hooper, J. Tupacz and S. 

Hutchinson. K. Magill provided editorial assistance, This is Contribution Number 696 of the Belle W, 

Baruch Institute for Marine Biology 

and Coastal Research. 

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Reprinted with permission from 

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30:249-263, 1992, Related to the 26th 

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Dr. J.J. Beukema, Editor, P.O. 59 

1790AB, Den Burg, Texel, Netherlands, 
ABOVEGROUND 

PLAIN 

Richard K. Myers, David H. Van Lear, and F. Thomas ~loyd~ 

Abstract--This paper describes one phase of a long-term 

study on the role of fire in post-hurricane forest plant 

community dynamics. Two years after Hugo but prior to 

initiation of fire regime treatments, the biomass complex 

within the 75-ac study area on the heavily damaged Santee 

Experimental Forest in South Carolina was assessed using a 

variety of techniques to establish pre-burn data baselines. 

Overall, downed woody debris comprised the largest biomass 

component at 57.8% of the total, followed by forest floor 

(16.3%), living residual trees (15,0%), dead residual trees 

(8.l%), and regeneration layer vegetation (2.8%). Detailed 

quantitative pre-treatment descriptions characterize biomass distribution and document variation in post-hurricane 

vegetative structure and fuel characteristics, and will 

permit assessments of nutrient pool variation among treatment plots. These baselines will allow for more sensitive 

testing and evaluation of fire effects on the development 

of plant communities following devastating hurricanes. 

INTRODUCTION 

Hurricane Hugo's profound impact on 

the Francis Marion National Forest in 

South Carolina has presented the rare 

opportunity to formally study plant 

communities as they develop following 

what is arguably the most severe of 

natural disturbance factors in the 

southeastern United States: the 

combination of strong winds from 

hurricanes and subsequent wildfires in 

heavy fuels. This combination has 

almost certainly been a highly influential force in the evolution of plant 

species and community successional 

patterns, and a driving factor in the 

development of coastal plain landscapes, However, little documentation 

of the ecological processes involved 

Paper presented at the Seventh 

Biennial Southern Silvicultural 

Research Conference, Mobile, Alabama, 

er 17-18, 1992. 

* Graduate Assistant, Professor, and 

Adjunct Professor, respectively, 

Department of Forest Resources, 

College of Forest and Recreation 

Resources, Clemson University, 

Clemson, South Carolina, 

in this interaction have to date been 

reported in the literature. 

One part of a current research effort 

(Van Lear 1990, Van Lear and Myers 

1992) investigating the role of fire in 

hurricane-devastated coastal plain 

forest plant communities has involved 

the detailed description of the biomass 

complex of the study area. Measurement 

and description of post-hurricane/ 

pre-fire biomass components will allow 

for evaluation of such phenomena as 

nutrient redistribution and vegetation 

change following the implementation of 

burning treatments. One objective of 

this paper is to document post-Hugo 

stand conditions and to characterize 

biomass distribution of forest stands 

in which the fire-regime treatments are 

to be applied. 

Characterizing post-hurricane forest 

structure and biomass becomes a 

difficult sampling problem. Forests 

severely damaged by windstorms and 

abetted by two growing seasons of early 

successional vegetative development are 

chaotic and highly variable assdlages 

of both living and dead plant material. 

Empirical description of the quantity 

of biomass and nutrients in various 
biomass components has required the BI S aTEGORIES AND 

use of both standard and improvised 

techniques. Thus, a second objective ESTImTES 

of this paper is to report on methods Five distinct biomass categories were 

herein employed to describe the post- recognized which collectively comprised 

hurricane biomass complex, the vegetative complex of the 

hurricane-impacted forest two years 

STmx AREA 

This research is being conducted at 

two sites on the Santee Experimental 

Forest (SEF) within the Witherbee 

Ranger District of the Francis Marion 

National Forest (FMNF), The FPlZNF is 

located in the Lower Terraces of the 

Coastal Flatwoods Region, a part of 

the Flatlands Coastal Plain Province 

in South Carolina (Myers et ale 19861. 

Soils are mostly moderately well 

drained to somewhat poorly drained, 

and include Craven, Duplin, Lenoir, 

and Wahee soil series. These are 

soils with slow to moderately slow 

permeability and seasonally high water 

tables (Long 1980). 

Both of the two study sites on the SEF 

were natural, unevenage mature pine 

stands prior to Hurricane Hugo, with 

the oldest trees exceeding 150 yrs in 

age. Stand records indicate loblolly 

(Pznus taedil L,) and longleaf (Pinus 

palustris Mill,) pine were the predominant overstory species, comprising 

approximately 70% and 30%, respectively, of pre-Hugo stocking. Fire 

had been excluded from these stands 

for decades, except for four small 

wildfires that burned in parts of both 

sites in the 1960's (USFS Witherbee 

ROD. Fire Atlas), Various species of 

hardwoods, notably the oaks (Quercus 

spp,), sweetgum (Liquidambar 

styraciflua L,), and blackgum (Nyssa 

sylvatica Marsh.), had become wellestablished in the under- and midstories, and were beginning to 

encroach into the overstory. 

Fifteen, 5-ac burning plots, each 

surrounded by a wide (30 it) firebreak, comprise the treatment areas in 

this study. A randomized complete 

block design was utilized with three 

blocked replicates of five treatment 

plots. Four burning regimes plus an 

unburned control constitute the five 

treatments, which were assigned at 

random for each block of five plots. 

Biomass and structure of vegetation, 

living and dead, was characterized 

prior to burning for each treatment 

plot, Biomass summaries will be 

presented here on an average per ac 

basis by treatment (3 reps combined) 

rather than on a plot by plot basis* 

following £3~~0. These five biomass 

categories are: the regeneration layer 

(RL), forest floor (FF), downed woody 

debris (DWD), living residual trees 

(LRT), and dead residual trees (DRT), 

Empirical description of each of these 

components required specialized and, in 

some cases, improvised sampling 

methods. 

Regeneration Layer 

This biomass component consisted of 

living vegetation, both woody and 

herbaceous, much of which has developed 

in the two years following the 

hurricane-induced removal of the 

canopy. The regeneration layer (RL) 

was defined to include trees and shrubs 

less than 1-in dbh, woody vines, 

graminoids, forbs, and ferns, These 

six lifeform groups were arranged in a 

diverse assemblage of species associations and developing plant cornunities 

across the 75-ac study area, 

It was subjectively observed prior to 

sampling that there was considerable 

variation in quantity and vegetative 

makeup of RL biomass within the study 

area, Nutrient content per unit weight 

of biomass can also vary greatly from 

one type of vegetation to another, 

Because of this perceived variation in 

amount and form of RL biomass, stratification was considered appropriate to 

decrease sample size, given the constraints of time, manpower, and funds 

available for this phase of the study. 

A stratification procedure was developed that combined identification and 

eitimation of unit area dry weight of 

Regeneration Layer Cover Types (RLCT) 

with measurement of area occupied by 

cover types within each plot. By combining RLCT weight per unit area 

with an estimate of cover type area, RL 

biomass and its composition in terms of 

lifeform plant assemblages for each 

pre-burn plot could be estimated. 

Weight per unit area was determined for 

each RLCT from destructive (ground) 

samples, and cover type area was 

measured on low-level helicopterobtained aerial photography of each 

plot, a technique similar to that 

suggested by Helms and Shain (1981). 

This method increased sampling 

efficiency by reducing variability of 
stratified clip plots, resulting in a 

smaller sample size for obtaining 

acceptable weight est 

RLCT . Eight rectangular (6.6 ft x 9.8 ft) 

quadrates were located in each of the 

five photo-identifiable RLCTrs, and 

monmented with 5-ft conduit driven 

1.5 ft into the ground. Four samples 

of each cover type (ns28) were placed 

in dormant season burn plots while the 

other 20 samples were located in 

growing season burn plots, allowing 

regeneration layer development 

comparisons between these two levels 

of the season-of-burn main effect. 

One half (3.3 ft x 9.8 ft) of each 

clip plot was sampled prior to initial 

fire treatments in late October-early 

November of 1991, The remaining 

unclipped plot-half was reserved for 

post-burn sampling in 1992 and 1993. 

Bommnn (1953) described the advantages of using rectangular (long/ 

narrow) plot shapes in uneven, 

discontinuous, and variable 

vegetation. 

All herbaceous and woody plants less 

than 1-in dbh rooted in the plot were 

cut at or as near as possible to the 

groundline, and separated into the six 

previously-described lifeform groups. 

Vegetation was placed into separate 

paper bags by group, labeled, and 

returned to the lab for dry weight 

determination. Estimates for dry 

weight per unit area (T/ac) for each 

RLCT were obtained from the average of 

eight oven-dry sample weights, based 

on the composite weight of all plants 

clipped on each destructive sample 

plot. Thus, each RLCT pre-burn 

biomass estimate is based on 258.7 ft2 

of clipped plot area. Separation of 

RLiCT destructive biomass samples into 

plant lifeform components allowed for 

detemination and description of preburn plant cornunity composition based 

on biomass proportions (Table 1). 

Estimation of area covered by each RLCT 

for each plot was achieved by dot grid 

counts on aerial photographs. Photos 

were obtained on October 16, 1991 using 

hand-held 35-~nm cameras and color slide 

films (400 ASA) during low-level (500 

ft above land surface) helicopter 

flights over the study areas. Plots 

were framed within separate, nearlyvertical exposures using zoom lenses so 

that plot firebreaks were as close as 

possible to image borders. Accurate 

photo-interpretation of plots was 

possible with the high resolution slide 

images enlarged by projection. Corrections for photo scale distortion 

resulting from tilt were made by the 

use of rectified dot grid transparencies mounted in the same frames with 

color slide plot images. Rectified 

grids were constructed optically in the 

lab by photographing tilted dot grids 

drawn on white paper at a density of 

four dots per in2. 

For each plot, the total number of dots 

falling in each of the five RLCTrs was 

counted. That proportion of dots per 

type to total dots per plot was calculated and used as an estimate for the 

proportion of area in each plot covered 

by each cover type. Table 2 presents 

area estimates for cover types in each 

of the five treatment areas. 

As a check on this method of determining area in cover types from aerial 

photo interpretations and dot counts, 

an independent area estimate was made 

based on a set of 480 ground samples. 

Table 1--Dry weight of lifeform components comprising five regeneration layer cover 

types (RLCT), prior to burning and two growing seasons following Hurricane Hugo. 

Plant Reseneration Layer Cover Type 

Lif ef om Pine Herb, Hwd . Nixed Shaded 

..................... dry a. - tonsfacre ...................... 

Trees 1.97 

Shrubs 0 . 49 

Woody Vines 0.07 

Graminoids 0.60 

Forbs 0.40 

Ferns/Moss 0.01 

Total 3,54 2.26 3.49 2-22 0.89 
Table 2--Area in regeneration layer cover types (RLCT) estimated from aerial 

photos, summarized by treatment area, 

Treatment Reqeneration Layer Cover Type Treatment 

Area Pine Herb, Xwd , Mixed Shaded Total 

Total 6.242 7,062 21.398 23,892 16.405 75 

Thirty-two cover type ground samples 

(3.3 ft x 9.8 ft) were systematically 

located in all 15 treatment plots, 

Each sample was given one of the five 

RLCT names based on its vegetative 

makeup. That proportion of ground 

samples (X/32) in each RLCT was taken 

as an estimate for the proportion of 

area in the treatment plot occupied by 

each RLCT, in the same manner as with 

the aerial photo procedure. 

A simple correlation analysis was 

performed for the two methods of area 

estimation. While correlation was 

expectedly imperfect, the scatter 

diagram (Fig. 1) and high coefficient 

of determination (r2 = 0.7598) shows 

that there is a strong relationship 

between the estimates of the two 

methods, Since a statistically 

significant (F = 230.95; df = 73) 

relationship resulted from this 

analysis, it can be inferred that the 

two methods yield similar estimates of 

area in cover types. The aerial 

technique with its greater sampling 

intensity (n=2401) is less apt to 

exclude smaller areas of relatively 

rare cover types, while the ground 

method has obvious advantages for 

correctly identifying vegetative 

assemblages and assigning cover type 

names. Aerial photo area estimates 

were ultimately used to calculate both 

regeneration layer and forest floor 

biomass for this project, Overall, 

regeneration layer biomass averaged 

2.3 T/ac across the 75-ac study area 

(Table 3 ) . 

0 t I I , I I J 

0 1 2 3 

Ground area (acres) 

Figure l--Correlation of photo and 

ground RLGT area estimates. 
Table 3--Pre-burn regeneration layer (RL) biomass distribution, two growing seasons 

following Hurricane Hugo. 

Treatment Regeneration Layer Cover Type 

Area Pine Herb. Hwd . Hixed Shaded Total 

...................... dry wt, - tonslacre ...................... 

Mean 0.29 0.21 1 . 00 0.62 0.19 2.32 

Forest Floor 

Forest floor (FF) biomass was assessed 

by methods similar to those used in 

regeneration layer biomass description. High variation in characteristics of the forest floor across the 

study area were anticipated and 

assumed to be related in part to 

vegetation characteristics. To 

minimize sample sizes while still 

obtaining representative estimates for 

forest floor biomass and nutrient 

content, sampling was stratified by 

RLCT. One 0.672 ft2 composite (litter 

+ fermentation layer + humus) sample 

was collected from one of 48 possible 

random locations within each of the 40 

clipped regeneration layer plots 

described above. All organic material 

excluding dead woody material visible 

on the litter surface was removed, 

placed in paper bags, labeled, and 

returned to the lab for drying, 

processing in a hammer mill, determination of mineral content, and 

storage for later nutrient content 

assays. Mineral fraction of samples 

was determined by the method of Hesse 

(1974). 

Forest floor weight estimates were 

calculated for each RLCT based on the 

average of the eight samples per cover 

type. Area factors for RLCTts already 

established (Table 2) were used to 

determine dry weight biomass estimates 

for the forest floor in each of the 15 

treatment plots (Table 4). Overall, 

forest floor biomass averaged 13.7 T/ac 

across the 75-ac study area. 

Downed Woody Debris 

The planar intersect method described 

by Brown (1974) was employed to estimate pre-burn dry weight of wood and 

bark contained in down and dead trees 

and other downed woody material (DWD). 

Eight sampling planes were established 

on each 5-ac treatment plot using the 

permanent measurement points already in 

place as plane origins. A subset of 

the 16 points per plot was chosen by 

Table 4--Pre-burn forest floor (FF) biomass distribution, two growing seasons 

following Hugo. 

Treatment Reqeneration Layer Cover Type Total 

Area Pine Herb. Hwd . Mixed Shaded Biomass 

...................... dry We - tonslacre ...................... 

Mean 
random selection of either the evenor odd-numbered stations. Compass 

bearings for sampling planes were also 

randomly selected from one of the 

three remaining cardinal or semicardinal directions not already used 

for plant cover measurement. Thus, 

eight samples per plot (241treatment 

area) were established for downed 

woody material biomass assessment. 

Variable-length sampling planes were 

utilized to achieve high sampling 

efficiency. Long planes (50 it) were 

used for the larger (3+ in), lessfrequently-occurring pieces of DWD, 

while shorter transects were used for 

the numerous small pieces. Woody 

material 0-1 in diameter at the point 

of plane-intersection was measured on 

6-ft planes, while 12-ft planes were 

used for material 1-3 in diameter. 

End-points of transects were marked 

with flagging and aluminum pins placed 

in the ground to facilitate reestablishment and remeasurement of sample 

planes after burning. 

Table 5 summarizes quantities and 

variation in DWD distribution, by size 

class, for the five treatment areas. 

Given the severity of damage and the 

larse size of trees in these stands 

prior to Hugo, it is not surprising 

that DWD represented the largest of 

the five components of aboveground 

biomass in the hurricane-impacted 

forest. Overall, DWD averaged 48,7 

T/ac across the 75-ac study area. 

Variation was moderate, ranging from a 

low average of 41.8 T/ac for the three 

plots (15 ac) in treatment C to a high 

of 56.2 T/ac for treatment B. 

Residual Living and Dead Trees 

Biomass in living residual trees (LRT) 

and standing, dead residual trees (DRT) 

was quantified for each plot using tree 

measurements of dbh and total height 

obtained from fixed-radius plot 

samples. These tree data were used to 

estimate total aboveground biomass in 

living and dead residual trees in conjunction with published biomass equations for estimating wood and bark in 

the total tree (Clark and Taras 1976; 

Phillips 1981; Saucier and Clark 1985; 

Taras and Clark 1977). Each treatment 

plot was "cruised" using sixteen 1120- 

ac circular plots with centers at the 

240 monumented sampling points previously described. All trees 3.0-in 

dbh and larger, dead or alive, rooted 

within these plots were tallied for 

species, dbh, total height, and condition (vertical, leaning, downed, topbroken, etc.). In addition, 32, 11200- 

ac samples per treatment plot (n=480) 

were established at monuments and at 

monument mid-points in which the above 

measurements were taken for trees and 

large shrubs 1.0 - 2.9-in dbh. Using 

information from these inventories, 

woody biomass descriptions were compiled in tabular form for each of the 

fifteen 5-ac plots. 

The majority of trees in the hurricane 

area had abnormal form, with tops blown 

out or broken off, limbs removed from 

crowns to varying degrees, and (with 

hardwood species) two years of vigorous 

regrowth in the form of epicormic, 

limb, and basal sprouts. Equations 

generally used dbh and total height to 

predict whole-tree biomass. Trees with 

crowns completely removed (e.g. the 

Table 5--Pre-burn downed woody material (Dm) biomass distribution, two growing 

seasons following Hugo. 

Treament 

Area 

0-3" size class 

0-.25" 25-1" 1-3" 

3"+ size class 

sound rotten 

Total 

Biomass 

Mean 
numerous dead standing pine boles 

typical of the hurricane-iwpacted 

forest area) were measured for total 

height of that portion of stan remaining, and equations for dbh and merchantable height were used to estimate 

biomass of mod and bark, on a dryweight basis. 

The many published whole-tree equations are not designed to predict 

biomass in trees with wind-d 

crowns. Thus, the accuracy of the 

biomass predictions for the damaged 

residual forest stand may be in question. However, the alternative to the 

use of existing equations was to 

destructively sample many trees of 

many species, a prohibitively expensive and time-consuming task. Since 

the quantities of biomass estimated in 

this study are used primarily as a 

means for comparing effects of various 

burning treatments on the redistribution of nutrients, the method is 

defensible and valid. It is the 

repeatability of the measurements and 

estimates that is most important in 

this application, and not estimate 

accuracy. Tables 6 and 7, respectively, summarize distribution of LRT 

and DRT biomass. In Table 7, the term 

"snags" refers to dead pines whose 

crowns were completely broken out by 

strong wind, leaving only the standing 

boles. 

I>ISTRIBUTION OF BXOMASS 

Total aboveground dry biomass across 

the study area averaged 84.2 T/ac 

(Table 8). This quantity is similar 

to estimates from other studies for 

total forest biomass in natural, 60+- 

year-old southern pine and mixed pinehardwood forests (Knight and McGlure 

1981). 

Downed woody debris comprised the 

largest (57.8%) component, by weight, 

of biomass in the hurricane-devastated 

forest, This finding was expected in 

view of the severity of Hugo's impact 

and the extensive windthrow and stem 

breakage of many large trees. The 

regeneration layer represented the 

smallest (2.8%) biomass component, but 

required the most effort for valid 

quantification because sf its variability and the diversity of plant 

forms comprising it, This effort was 

considered worthwhile, since RL biomass 

is high in nutrient content relative to 

the other more woody biomass components 

(Van Lear et al. 1988), and because 

these plants represent the seed sources 

and root-stocks that will play .important roles in the colonization of the 

sites following burning treatments. 

CONCLUSIONS 

The biomass quantification phase of 

this study demonstrated that in the 

chaotic, complex structure of 

hurricane-devastated but rapidly 

regenerating forests, a combination of 

standard and improvised techniques is 

necessary for assessing forest attributes- On the Santee Experimental 

Forest after Hurricane Hugo, downed 

woody debris was the largest component 

of total biomass (57.8%)' followed by 

the forest floor, living residual 

trees, dead residual trees, and the 

regeneration layer. ~aseline data have 

been collected and summarized which 

thoroughly describe pre-treatment 

conditions of stand structure and 

biomass distribution, allowing for 

subsequent assessment of nutrient 

pools. These baselines will enable 

burning treatment effects to be 

documented and analyzed in an on-going 

study of the interactive effects of 

Table 6--Pre-burn living residual tree (LRT) biomass distribution, two growing 

seasons following Hugo. 

Treatment Species Group Total 

Area Pine Oaks Sweetgum H-Hwd S-Hwd Biomass 

....................... dry wt, - tonslacre ...................... 

Mean 
Table 7--Pre-burn dead residual tree (DRT) biomass distribution, two growing 

seasons following Hugo. 

Treatment 

Area 

Pine 

Trees Snags 

~ardwood 

Hard Soft 

Total 

Biomass 

Mean 

Table 80-Pre-burn aboveground biomass distribution for five treatment areas two 

growing seasons post-Hugo. 

Treatment RL DWM FF LRT DRT 

Area 

TOTAL 

..................... dry a. - tons/acre ....................... 

HEAN 

PERCENT 

hurricanes and fire on the development 

of forest plant communities. 

LITERATURE: CITED 

Bonnann, F.H. 1953. The statistical 

effect of plot size and shape in 

forest ecology. Ecology 34:474-487. 

Brown, J.K. 1974. Handbook for inventorying downed woody materials. USDA 

Forest Service General Technical 

Report INT-16, 24 p. Intermountain 

Forest and Range Experiment Station, 

Ogden, UT. 

Clark, A., 111; Taras, M.A. 1976. 

Comparison of aboveground biomasses of 

the four major southern pines. Forest 

Products Journal 26(10):25-29. 

Helms, J.R.; Shain, W.A. 1981. Problems 

related to the use of remote sensing 

for inventory and mapping of lower 

coastal plain forests. Proceedings 7th 

International Symposium Machine Processing of Remotely Sensed Data. Purdue 

University, West Lafayette, IN. June 

23-26, 1981, p. 540-542. 

Hesse, P.R. 1974, A textbook of soil 

chemical analysis. John Murray Ltd., 

London. 520 p. 

Knight, H.A.; McClure, J.P. 1981. 

Multiresource inventories--forest 

biomass in South Carolina. USDA Forest 

Service Research Paper SE-230. 27 p. 

Southeastern Forest Experiment Station, 

Asheville, NC. 
Long, B,M, 1980. Soil survey of 

Berkeley County, South Carolina, 

National Cooperative Soil Survey: USDA 

Soil Conservation Service and Forest 

Service, South Carolina Land Resource 

Consenation C ttee and South 

Carolina Agricultural Experiment Station, 

Myers, R.K.; Zahner, R,; Jones, S,M. 

1986, Forest habitat regions of South 

Carolina from satellite imagery, 

Department of Forestry, Clemson 

University, Forest Research Series No, 

42, 31 p. 

Phillips, D.R. 1981, Predicted totaltree biomass of understory hardwoods, 

USDA Forest Service Research Paper 

SE-223, 22 p, Southeastern Forest 

Experiment Station, Asheville, NC, 

Saucier, J.R.; Clark, A,, 111. 1985, 

Tables for estimating total-tree and 

product weight and volume of major 

southern tree species and species 

groups, USDA Forest Service, Athens, 

GA, Southwide Energy Committee, APA 

Inc., Washington, DOC. Publication No. 

85-A-11. 59 p. 

Taras, M.A.; Clark, A,, 111. 1977. 

Aboveground biomass of longleaf pine 

in a natural sawtimber stand in 

southern Alabama, USDA Forest Service 

Research Paper SE-162, 32 p. 

Southeastern Forest Experiment 

Station, Athens, GA, 

USDA Forest Service. 1930-1992, Fire 

Atlas of the Witherbee Ranger District, Francis Marion National Forest. 

Dispatch Office, Witherbee Ranger 

Station, Witherbee, SC. 

Van Lear, DOH, 1990. Coastal plain 

plant cornunities response to firehurricane interactions. Cooperative 

Research Proposal: USDA Forest Service, 

Southeastern Forest Experhent Station, 

Charleston, SC, 4 p, 

Van Lear, DOH,; Kapeluck, P.R.; Waide, 

JOB, 1988, Nitrogen pools and processes 

during natural regeneration of loblolly 

pine, pp. 234-252, In: Gessel, J,P,; 

Lacate, D,S,; Weetman, G.F.; Powers, 

R-F,: Sustained Productivity of Forest 

Soils. Proceedings 7th North American 

Forest Soils Conference, University of 

British Columbia, Vancouver, BC. 525 p, 

Van Lear, DOH.; Myers, R.K, 1993. 

Coastal plain plant communities 

response to fire-hurricane interactions. Progress Report: USDA Forest 

Service, Southeastern Forest Experiment 

Station, Charleston, SC, 46 p. 

Reprinted with permission from 

Proceedings of the Seventh Biennial 

Southern Silvicultural Research 

Conference, Mobile, AL, Nov, 17-19, 

1992, published by the USDA For. Serv, 

SFES Gen. Tech, Rep. SO-93, July 1993, PO 189-196. 
COMPZICTION RUTTING DURING G 

IAFFECT BE DIRI1INED SOILS 

POORLY DRAINED SOILS ON WET PINE FLATS 

We Michael Aust, Mark D. Tippett, James A. Burger, 

and William H. McKee, Jr.' 

Abstract--Soil compaction and rutting (puddling) are 

visually distinct types of wet-site harvesting disturbances; however, the way in which they affect soil 

physical properties and hydrology is not well documented. Three compacted and three rutted sites were 

evaluated to determine the effects of the disturbances 

on soil physical and hydrologic properties. For each 

site, primary skid trails and non-trafficked areas were 

compared. Both compaction and rutting increased bulk 

density, and reduced macropore space and saturated 

hydraulic conductivity. Water tables and reducing 

conditions were closer to the soil surface within the 

primary skid trails. For the compacted and rutted skid 

trails, changes were greatest on sites that initially 

had better drainage and aeration. Compacted sites may 

prove easier to mitigate with site preparation than 

rutted sites due to the shallower nature of the disturbances and drier site conditions that will facilitate 

mechanical mitigation, 

INTRODUCTION 

Wet flats comprise a landform on the 

southern Atlantic Coastal Plain that 

are characterized by little or no 

relief, water tables at or near the 

soil surface for a portion of the 

year, and s o i l s t h a t a r e moderately 

well to very poorly drained, Pine 

stands on these wet flats are an 

important source of fiber to the wood 

products industry; some of the most 

productive pine plantations are 

located on these sites (Allen and 

Campbell 1988). The seasonal high 

water tables associated with wet pine 

flats present a dilemma for forestry 

harvesting operations, Rubber-tired 

felling equipment and skidders may 

traffic over 50 percent of a site and 

may result in soil compaction or rutting, particularly if logging occurs 

when soils are wet (Aust and others 

1993). 

Many researchers have concluded that 

harvesting wet sites can result in soil 

compaction or rutting (puddling) 

(Dickerson 1976; Gent and others 1983, 

1984: Hatchell and others 1970; 

~atchell 1981: Incerti and others 1987; 

W, Michael Aus~, College of Forestry 

and Wildlife Resources, Virginia 

Polytechnic Institute and State 

University, Blacksburg, Virginia; 

Mark D, Tippett, Law Environmental, 

Kennesaw, Georgia; James A. Burger, 

College of Forestry and Wildlife 

Resources, Virginia Polytechnic 

Institute and State University, 

Blacksburg, Virginia; and William H, 

McKee, Jr,, USDA Forest Service, 

Southeastern Forest Experiment 

Station, Charleston, South Carolina. 

Karr and others 1991; Lockaby and 

Vidrine 1984; McKee and others 1991; 

Moehring 1970; Moehring and Rawls 1970; 

Murphy 1983; Wert and Thomas 1981). 

However, few forest-harvesting disturbance studies have differentiated 

between the effects of compaction and 

rutting on soil properties, Soil compaction and soil puddling occur under 

different soil moisture conditions and 

may have different effects. Soil compaction occurs when soil solids in a 

given soil volume increase relative to 
soil pore space. Soil compaction 

usually occurs when soils are near 

field capacity because, compared to 

drier soils, soils at this moisture 

level have lower cohesive forces and 

load-bearing capacities (Akram and 

Remper 1979). Therefore, soil moisture levels between field capacity and 

saturation are most susceptible to 

compaction, although compaction is 

also influenced by machinery weight, 

tire size and pressure, soil misture, 

soil texture, and vegetative cover 

(Greacen and Sands 1980). 

Soil rutting (puddling) generally 

occurs on sites that are harvested 

under saturated soil conditions 

(Burger and others 1989)- Soil 

puddling is "the destruction of soil 

aggregates into ultimate soil particles" (Shanna and DeDatta 1986)- 

Soils at or near saturation experience 

shear failure when a load is applied, 

resulting in the formation of a rut, 

Soil structure is altered by puddling 

because soils are at the liquid limit 

and have a liquid response to external 

forces. Soil aggregates are destroyed 

and churned into plastic mud (Beacher 

and Strickland 1955; Ghildyal 1982; 

Swanson and others 1955). 

In the fall of 1989, Hurricane Hugo 

devastated many wet-flat pine stands 

in coastal South Carolina and initiated hundreds of salvage-logging 

operations. Due to an unusually wet 

fall and winter, salvage-logging was 

conducted under moist to wet soil 

conditions. On many sites, logging 

operations severely rutted or compacted primary skid trails, Site 

disturbances due to this salvagelogging were similar to those created 

by many standard clearcut harvesting 

operations on wet soils, The objective of this study was to evaluate 

three rutted and three compacted sites 

in order to contrast compaction and 

rutting effects on soil physical and 

hydrologic properties. This information is necessary to determine if 

different strategies are needed to 

avoid and mitigate compaction versus 

rutting disturbances. 

METHODS 

The study sites were near Charleston, 

South Carolina, on the Francis Narion 

National Forest. Six wet pine flats 

that had been salvage-logged following 

Hurricane Hugo were selected for 

study. Dominant soil series in the 

study included Bethera (poorly 

drained, clayey, mixed, thermic Typic 

Paleaquults), Rains (poorly drained, 

fine-loamy, siliceous, thermic Typic 

Paleaquults), Lynchburg (somewhat 

poorly drained, fine-loamy, siliceous, 

thermic Arenic Paleaquults), and 

Goldsboro (moderately well drained, 

fine-loamy, siliceous, thermic, Aquic 

Paleudults). Topography was nearly 

level (0-1 slope) and all sites had 

water tables at or near the soil 

surface for portions of the year. Soil 

drainage classes of the sites ranged 

from moderately well drained to poorly 

drained. Soil textures included 

coarser materials in the surface 

horizon (loamy sands, sandy loams, and 

loams) overlying finer sub-soil 

materials (sandy clay loams and clays). 

Three sites were classified as being 

rutted (puddled) because soils in 

primary skid trails had obviously 

experienced liquid flaw and soil had 

been displaced into berms adjacent to 

ruts. The other three sites were 

classified as being compacted, with no 

berm formation along the primary skid 

trail. 

The compacted and rutted soil studies 

were conducted as two separate but 

parallel experiments. Each study 

consisted of a randomized complete 

block design (Steele and Torrie 1980) 

containing three blocks (sites) and two 

treatments. Treatments consisted of 

heavily-trafficked primary skid trails 

and non-trafficked areas adjacent to 

the primary skid trails (Figure 1). 

Soils within each site had the same 

texture and drainage class; therefore, 

non-trafficked areas were judged to be 

representative of site conditions prior 

to salvage operations. 

road , I primary 

skid 

trail non-?raf ficked 

measurement 

Figure 1--Generalized layout of one 

salvage-logged block (site) including 

measurement plots in primary skid 

trails and non-trafficked areas. 
Four measurement plots (25 ft, x 80 

ft.) were established within each 

block (Figure 1) and four sampling 

transects were randomly located across 

each measurement plot. At each 

sampling transect, the following 

measuraents were recorded: soil 

disturbance class, soil surface 

profiles, water table depth, soil 

depth to reducing enviroment, bulk 

density, and porosity. 

Five soil disturbance classifications 

(Burger and others 1989) were 

assigned: non-trafficked, berm 

(inside and outside), tire-track, and 

between-tire-track. Non-trafficked 

subplots contained only non-trafficked 

cate-gories. Rutted measurement plots 

contained berms, tire-track and 

between-tire-track categories, 

Compacted measurement plots contained 

tire-track and between-tire-track 

categories. 

Cross-sectional profiles of soil 

disturbance were measured in the 

trafficked plots in the following 

manner: a leveled line was stretched 

across the skid trail at each sampling 

transect. Leveled-line height corresponded to the groundline elevation on 

either side of the skid trail and 

closely corresponded to the predisturbance soil surface elevation. 

The distance from the leveled line to 

the post-disturbance soil surface was 

measured at 0.5-ft, intervals across 

the sampling transect. 

One water table well (Faulkner and 

others 1989) was established at each 

sampling transect (4 wells per 

measurement plot), Wells were located 

between the tire tracks in the trafficked measurement plots and located 

randomly in the untrafficked measurement plots, Wells were measured 

biweekly from April through September, 

1991, Elevations of all wells within 

a block (site) were determined with a 

transit so that water table values 

could be corrected for differences in 

topographic elevation. After topographic differences had been accounted 

for, the water table levels of the 

undisturbed areas were used as the 

baseline comparison value. Water 

table levels on disturbed plots were 

recorded relative to the undisturbed 

areas. 

Two iron rods (1/8 in. diameter x 40 

in. length) were inserted at each 

sampling transect to determine the 

relative depth of reduced conditions 

that occurred in the different types 

of treatments (Bridham and others 1991; 

Carnell and Anderson 1986; Hook and 

others 1987; McKee 1978). On each 

sampling transect in the primary skid 

trail treatment, one iron rod was 

installed between the tire tracks and 

another was installed in the tiretrack. Two iron rods were randomly 

located and installed on each sampling 

transect of all non-trafficked subplots. Depth of rust on the iron rods 

was measured biweekly. 

Five soil cores (2 in, diameter x 4 in. 

length) were collected from the upper 

four inches of the soil surface on each 

sampling transect (20 per measurement 

plot). The soil cores were taken from 

the tire-track (2), between-tire track 

(I), and berm (2) soil disturbances 

classes. Soil cores were subsequently 

analyzed for bulk density (Blake and 

Hartge 1986), macropore space 

(Danielson and Sutherland 1986), and 

saturated hydraulic conductivity (Klute 

and Dirksen 1986). 

RESULTS 

The average depth of ruts in the primary skid trails of the three rutted 

blocks were 14 inches below the original ground surface, while average rut 

berm heights were 9 inches above the 

original soil surface (Figure 2). 

Average percentages of each disturbance class within the rutted plots 

were: outside berm (29 percent), 

tire-track (43 percent), inside berm 

(24 percent), and between-tire-track (4 

percent). Thus, on over 90 percent of 

the rutted skid trail, characteristically denser and less fertile subsoil horizons were either exposed by 

tire tracks or deposited as berms over 

surf ace horizons. 

Soil surface chanae (inches) 

'" / I 

I - = original soil surraze I 

= campacted skid trail 

= rutted skid trail 

I -10- I 

I 

0 5 f O 15 20 25 

Primary skid trail width (feet) 

Figure 2--Average change of soil 

surface profiles in compacted and 

rutted primary skid trails. 
Compacted skid trails had tire-tracks 

6 inches below the original soil 

surface but no berms were formed. 

Between-tire-track areas also were 

approximately 3 inches below the 

original soil surface (Figure 2). The 

tire-track disturbance class comprised 

82 percent of the skid trail area and 

the between-tire-track class made up 

18 percent. No subsoils were exposed; 

overall the surface profiles of compacted sites were less severely 

affected than the rutted sites. However, the between-tire-track of the 

compacted areas were further below the 

original soil surface than the rutted 

area, indicating that dragged logs had 

removed more topsoil in the compacted 

sites (Figure 2). McKee and Hatchell 

(1987) concluded that removal of 

topsoil by dragged-logs could retard 

tree growth on skid trails. 

Rutted skid trails had average bulk 

density values that were 15 percent 

higher than non-trafficked areas 

(Table 1). Bulk densities between the 

tire tracks and on the berms were not 

significantly different from bulk 

densities in the non-trafficked areas. 

However, soil bulk density values 

averaged 1.39 Mg m-3 within the track, 

a density level that could limit root 

growth (Vepraskas 1988) depending on 

soil moisture levels. This higher 

bulk density in the track was a function of compaction as well as soil 

displacement (Figure 2). 

Table l--Average soil bulk density, 

macropore space, and saturated hydraulic conductivity for primary skid 

trails and non-trafficked treatments 

on rutted (puddled) and compacted 

sites (alpha level = 0.01). (Values 

represent area-weighted averages of 

all disturbance classes). 

Treatment 

Rutted Study 

Non-trafficked 

Skid trail 

Compacted Study 

Non-traf f icked 

Skid trail 

Hacro- Saturated 

Bulk pore Hydraulic 

Density Space Conductivity 

(Mg EI-~) ( % ) (in hr-I) 

Compacted skid trails also had higher 

average bulk density values relative 

to the non-trafficked treatment (Table 

1). The impact of skidder traffic was 

more uniformly distributed across 

compacted trails compared to rutted 

trails (Figure 2). Tire-track and 

between-tire-track bulk densities 

averaged 1 . 17 and 1.12 Mg m-', respectively, which were not significantly 

different. Bulk density values were 

higher than in the non-trafficked area, 

but did not exceed levels limiting to 

root growth. 

Macropores are pr rily responsible 

for rapid drainage of free gravitational water from within the soil 

(Greacen and Sands 1980). Reductions 

in macropore space caused by trafficking decrease soil drainage and reduce 

aeration. Rutting reduced soil macropore space to about 60 percent of that 

on non-trafficked plots, while coxnpaction reduced macropore space to approximately 80 percent of that on nontrafficked plots (Table 1). Similar 

reductions in soil macropore space due 

to trafficking have been reported by 

others (Aust and others 1993; Gent and 

others 1983; Incerti and others 1987). 

Saturated hydraulic conductivity is a 

measure of the rate that water moves 

through a saturated soil and is related 

to macropore space; water flow is 

proportional to the fourth-power of the 

pore radius (Baver and others 1932). 

That is, water moves 16 times faster in 

a soil pore that is twice the radius of 

an adjacent pore. Saturated hydraulic 

conductivity serves as a quantitative 

index of soil drainage. Rutted primary 

skid trails had an average hydraulic 

conductivity of 0.3 in hr-' compared to 

3.5 in hr-' on non-trafficked plots 

(Table l), a ten-fold decrease in the 

rate that free water is able to drain 

from soils puddled by rutting. 

Compaction resulted in a similar 

reduction in hydraulic conductivity. 

The non-trafficked plots averaged 7.4 

in hr-' versus 0.9 in hr-I in the 

compacted skid trails (Table 1). These 

low hydraulic conductivity rates in 

compacted and rutted (puddled) sites 

were similar to those reported by Aust 

and Lea (1992), Dickerson (1976), and 

Gent and others (1983) for forest sites 

that were trafficked under similar 

conditions. 

Low saturated hydraulic conductivity 

caused by rutting and compaction would 

suggest poor drainage within primary 

skid trails. Higher water tables 

confirmed that drainage was poorer in 

the somewhat poorly drained to moderately well drained soils. On poorly 

drained soils water tables were not 

significantly closer to the soil 

surface in the skid trails than in the 
non-trafficked areas (Figures 3.a, 

3.b). Two of the rutted sites were 

poorly drained; so a reduction of 

saturated hydraulic conductivity in 

the rutted skid trails did not result 

in any major hydrologic changes. 

However, one rutted site was somewhat 

poorly drained. On this site, the 

reduction in hydraulic conductivity 

within the primary skid trails 

resulted in a water table that was 25 

inches higher than in the 

non-trafficked plots (Figure 3.a). 

Water table change (in.) 

50 I 

Non-trafficked i- Poorly Drained 

* Poorly Drained 

-loL I I 8 I I 

April May June July Au61 Sept 

1991 

Water table change (in.) 

50 1 I 1 - .on-traftlcked -+ Somewhat Poorly 

40 + Moderately welt ++ Poorly Drained I 

10 

0 

- 10 

April May June July Sept 

1991 

Figure 3--Average disturbance-induced 

water table change for (a) rutted and 

(b) compacted primary skid trails by 

site drainage class. (Water table 

values are adjusted for topographic 

differences, so higher water tables 

indicate change from the 

non-trafficked condition represented 

by the zero base line.) 

The compacted sites included a moderately well drained, a somewhat poorly 

drained, and a poorly drained soil. 

The degree to which soil compaction 

treatment affected the water table was 

also related to the initial soil 

drainage class. Compaction-induced 

changes in water tables were inversely 

related to drainage class. The water 

table increased 17.0 inches in the 

moderately well drained compacted 

plots, compared to 6.9 and 3.3 inches, 

respectively, for the somewhat poorly 

drained site and poorly drained sites 

(Figure 3.b). 

Higher water tables affected soil 

aeration, as shown by depth of rust on 

iron rods. Within the primary skid 

trails of the rutted (puddled) sites, 

aerated conditions existed to an 

average soil depth of 9.6 inches, 

compared to 12.9 inches within the 

non-trafficked areas (Figure 4.a). The 

same pattern existed within the 

compacted plots: compacted primary 

skid trails were aerated to a depth of 

8.8 inches, and non-trafficked areas 

were aerated to 9.7 inches (Figure 

4.b). 

Rust depth below soil surface (in.) 

OQ 

1 

-16' I I I I I 

May June July Aug Sept 

1991 

- Non-trafficked - Skid trail 

Rust depth below soil surface (in.) 

0 1 

I 1 , 1 

- 16 I 

May June July Au9 Sept 

1991 

- Non-trafficked - Skid Tra~l 

Figure 4--Average soil depth of rust on 

iron rods for (a) rutted and (b) 

compacted primary skid trails, where 

rust indicates depth to reducing 

environment. 

DISCUSSION 

Wet pine flats are characterized by 

seasonally high water tables, many of 
these sites require bedding for the 

successful regeneration of pine plantations. om pact ion or puddling of 

soils on these wet sites will probably 

not result in soil strength increases 

that would impede root growth. Aust 

and Lea (1992) compared soil disturbance on a skidder-logged area to a 

control area in an alluvial floodplain 

and concluded that skidder-logging did 

not increase soil strength. Likewise, 

Burger and others (1989) evaluated 

soil strengths associated with 

increasing skidder traffic levels on 

wet pine flats under saturated and 

moist conditions and found that soil 

strengths actually decreased with 

increasing traffic levels because of a 

corresponding increase in volumetric 

water content. Soils in the compacted 

and rutted blocks usually retain 

enough water during the growing season 

so that increases in bulk density do 

not result in higher soil strengths. 

However, both compaction and rutting 

altered soil drainage and aeration to 

an extent that could adversely affect 

root growth. Compaction and puddling 

decreased macropore space and 

saturated hydraulic conductivity. 

Decreases in macropore space and 

hydraulic conductivity due to wet-site 

trafficking have been found by 

numerous researchers (Burger and 

others 1989, Gent and others 1983, 

Incerti and others 1987). The 

compacted and rutted sites drained 

more slowly, as shown by the higher 

water tables and more reduced conditions (lower soil oxygen). Drainage 

and aeration reductions were more 

pronounced on sites that had better 

initial drainage and aeration characteristics. The sites having poor 

drainage and aeration prior to either 

disturbance were less affected, 

implying that compaction and rutting 

can have more severe site productivity 

impacts on better drained sites. It 

will be interesting to see if the soil 

properties observed on the sites 

affect the development of the stands 

as evapotranspiration increases. 

Langdon and Trousdale (1978) showed 

that the water tables on similar sites 

were lowered about 1 ft. for each 40 

ftO2 of basal area increase. 

Both compaction and rutting can have 

deleterious impacts on soil physical 

properties. However, the compacted 

sites were on better drained areas 

that are easier to mitigate. Rutted 

sites were wetter and may have 

relatively narrower windows of 

operation when a mechanical mitigation 

treatment could be applied. 

Additionally, the rutted areas had 

deeper disturbance profiles and 

successful mitigation of these 

disturbances will probably require 

mechanical operations that operate to 

deeper soil depths. Bedding may 

successfully fill in the rutted areas, 

but may have little impact on soil 

physical properties (Gent and others 

1983, 1984). Disking may prove to be a 

successful mitigation treatment on 

shallow disturbances of the compacted 

sites. However, Hatchell (1981) 

observed that bedding improved early 

growth of loblolly pine on a similar 

poorly drained site, but disking was 

not effective for mitigation of skid 

trails. The interaction of site 

drainage and different methods of 

mitigation may change with time. 

Three mechanical (disking, bedding, 

disking and bedding) and one fertilization treatment were applied to these 

rutted and compacted treatment plots. 

Results of these mitigation treatments 

on soil properties and tree growth will 

be reported at a later time. 

ACKNOWLEDGMENTS 

This research was partially funded by 

the USDA Forest Service, Southeastern 

Forest Experiment Station. The Francis 

Marion National Forest and Experiment 

Station provided valuable logistical 

and personnel support. 

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Reprinted with permission from Southern 

Journal of Applied Forestry 19(2). 

Forthcoming. Not for further 

reproduction, 
SOIL PHYSICAL AND HYDROLOGICAL CHANGES ASSOCIATED 

WITH LOGGING A WET PINE FLAT WITH WIDE-TIRED SKIDDERS 

W. M. Aust, To W. Reisinger, J. A. Burger', 

and Bo J. stokes2 

Abstract--A wet pine flat in the coastal plain of South 

Carolina was harvested with a rubber-tired skidder 

equipped with 68-in.-wide tires. Soil physical properties were measured immediately before and after a 

salvage harvest to document changes associated with 

traffic disturbance. Paired t-tests indicate that the 

wide-tired operation significantly increased soil 

volumetric water content, bulk density, and soil 

strength, and decreased saturated hydraulic conductivity, soil porosity, and depth to the water table. 

Changes were greatest for the more disturbed areas, and 

rutting that occurred in the skid trails apparently 

interrupted subsurface drainage. 

XNTROBUCTION 

Technological modifications in harvesting equipment, such as the use of 

wide, high-flotation skidder tires, 

have made it possible to operate on 

soft, wet sites. However, there is 

continued concern over the site 

impacts associated with wet site 

operations. Most postharvest evaluations of site impacts reported in the 

literature have concentrated on soil 

damage due to trafficking of relatively well-drained soils (Reisinger 

and others 1988). 

When a poorly drained soil is trafficked, its soil strength may actually 

decrease due to an increase in volumetric water content (Burger and 

others 1989). For many wet sites, 

assuming few periods of soil drying, 

the soil strength may never approach 

levels that will actually limit root 

or seedling growth (Burger and others 

1991). The most critical changes 

associated with wet-site harvesting 

operations are those that are related 

Assistant Professors and Associate 

Professor, Dept. of Forestry, Virginia 

Polytechnic Institute and State 

University, Blacksburg, VA 24061-0324. 

Project Leader, Southern Forest 

Experiment Station, USDA Forest 

Service, Auburn, AL 36849. 

to the movement of air and water within 

the soil profile. Any decreases of 

soil aeration and drainage on already 

poorly drained soils have the potential 

to reduce overall site productivity and 

further limit management opportunities. 

The objectives of this study were to 

evaluate the impacts of a wide-tired 

grapple skidder on soil physical and 

hydrological properties of a wet forest 

site. 

mTHODS 

Site Description 

The study site is located on the 

Francis Marion National Forest in the 

Coastal Plain of South Carolina 

(Berkeley County), where Hurricane Hugo 

devastated the forests during the fall 

of 1989. The 4.0-ha study site had a 

slight slope (1-2 percent) from west to 

east (Figure 1). The soil was classified as a Bethera loam, clayey, mixed, 

thermic Typic Paleaquult (USDA Soil 

Conservation Service 1980). This soil 

series typically has a loamy surface 

layer about 10.2 to 17.8 cm thick over 

a clay layer. Drainage is poor, and 

the soil is commonly saturated from 

early winter through spring. A 60- 

year-old natural loblolly pine (Pinus 

taeda) stand covered the entire site 

prior to Hurricane Hugo. After the 

hurricane, over 50 percent of the trees 

in the stand were bent, uprooted, or 

broken due to the high winds. This 
damage prompted a tremendous effort to 

salvage downed timber on the Francis 

Marion National Forest and within the 

region. 

N Drain 

Figure 1--Map of transect lines used 

to delineate skid trails and soil 

disturbance classes: + = skid trails; 

1 = undisturbed; 2 = slightly 

disturbed; 4 = rutted. 

Salvage Operations 

The salvage operation consisted of 

chainsaw felling of large-diameter 

standing snags and bucking merchantable sawlogs from windthrown trees; 

only dead trees were removed during 

this operation. After the sawtimber 

had been felled and bucked, the logs 

were grapple-skidded to a landing 

located next to a graveled road, All 

skidding was done over a 2-day period 

(in May 1990) with a John Deere 648 

grapple skidder equipped with 68 X 68 

x 25 in. Ardco tires. 

Study Design 

An assessment of site disturbance was 

ediately prior to and immediately after the salvage harvest. Four 

transect lines, spaced 40 m apart, 

were installed to locate sampling 

stations perpendicular to the expected 

skid trail pattern. Each transect 

line measured 225 m in length, as 

determined by salvage sale boundaries 

(illustrated in Figure 1). 

Soil disturbance classes were determined and assigned continually along 

each transect line and were similar to 

the disturbance classification system 

developed by Miller and Sirois (1987). 

The classes were: 

Class 1--Undisturbed 

Class 2--Slightly disturbed 

a. litter still in place 

b. litter removed and mineral soil 

exposed 

c. mineral soil and litter mixed 

d. mineral soil deposited on top of 

litter 

Class 3--Deeply disturbed, surface soil 

ved and subsoil exposed 

Class 4--Rutted, compacted 

a. 0-15.2 cm 

b. 15.2-30.5 cm 

c. > 30.5 cm 

Class 5--Depression deposit, soil 

deposited in low spots 

Class 6--Covered by slash to depth that 

will hamper regeneration 

Class 7--Nonsoil, streambed, stump, 

etc . 

Along each transect line, on a 5 m 

spacing, cone penetrometer (Bradford 

1986) samples were taken in 2.54 cm 

intervals to a soil depth of 15.2 cm 

(at 184 stations). A standard U.S. 

Army Corps of Engineers penetrometer 

(ASAE Standards 1990), equipped with a 

30° 1.27-em2 cone was used. Soil bulk 

density (Blake and Hartge 1986) core 

samples (5.1 x 5.1 cm cylinders) were 

taken from the soil surface every 12.5 

m along the transect lines (at 76 

stations). Every other bulk density 

sample (40 stations) was kept in its 

cylinder and later analyzed to determine total pore, micropore, and macropore space (Danielson and Sutherland 

1986), and saturated hydraulic conductivity (Klute and Dirksen 1986). Water 

table wells were augered on a 40 m 

spacing (40 stations) to determine 

depth to the water table (Reeve 1986). 

All stations were marked with flagged 

stakes so that before- and afterharvest samples could be taken within 

15 cm of the same point. Sampling the 

before-and-after periods from the same 

stations allowed the data to be 

analyzed by paired t-tests (Steele and 

Torrie 1980). All preharvest stations 

were classified as undisturbed, but the 

tests paired stations based on the 

postharvest classification. 

RESULTS 

Visual inspection of the study area 

indicated no machine disturbance prior 

to salvage harvest. Immediately after 

harvest, the area was reclassified, and 

only three classes of site disturbance 

were detected. The undisturbed (Class 

I), slightly disturbed (Class 2a), and 
rutted (Class 4a), covered 52, 14, and 

34 percent of the site, respectively, 

following the harvest (Figure 1). In 

general, Class 2a represented areas 

that had received 1 or 2 skidder 

passes, while Class 4a represented an 

area that had been repeatedly trafficked (i,e,, primary or secondary 

skid trails). 

The area was harvested under conditions of relatively high soil moisture 

(Table I), as necessitated by the time 

constraints of the salvage effort, 

Volumetric water contents increased as 

the level of disturbance increased. 

Volumetric water content is influenced 

by bulk density; because bulk density 

increased on Classes 2 and 4, the 

volumetric water content also 

increased compared to the preharvest 

level. 

Postharvest bulk density values were 

higher than preharvest values and 

increased as the level of disturbance 

increased (Table 1). Although the 

increase in bulk density was significantly higher for the slightly 

disturbed and rutted classes, average 

bulk densities were still relatively 

low, being less than 1.0 Mg/m3. 

Hydraulic conductivity, an index of 

soil drainage, is proportionally 

related to macropore space. Soil 

drainage is primarily a function of 

macropore space under saturated soil 

conditions. Saturated hydraulic 

conductivity values decreased as 

traffic intensity increased, with a 

twofold reduction for slightly disturbed areas and an almost complete 

interruption of water movement for the 

rutted areas (Table I), 

Harvesting operations caused a significant decrease in total porosity in 

disturbed areas (Table I). No change 

in micropore space occurred; however, 

macropore space decreased significantly. Notable was the significant 

difference in maeropore space, even for 

the undisturbed Class 1. Areas 

visually classified as undisturbed may 

have received some level of undetected 

traffic, or the impact of felled trees 

may also have had an effect. 

Mechanical resistance values f o r t h e 

postharvest treatment were higher than 

for the pretreatment values (Table 1). 

Mechanical resistance tends to decrease 

as volumetric water content increases; 

however, volumetric water contents did 

not vary greatly (i.e., 30.9-35.28). 

Mechanical resistance, like bulk 

density, increased more on the more 

highly trafficked areas, down to the 15 

cm depth. 

Preharvest well measurements indicated 

that the water table depth was fairly 

constant across the entire site (i,e., 

50-56 cm). Postharvest measurements 

(from the same wells) revealed that 

water tables were nearer the soil surface (i.e., 32-37 cm) than before harvest. The water table was also significantly closer to the surface in the 

slightly disturbed areas (33 cm) and 

primary skid trails (32 cm) than in the 

undisturbed areas (37 cm) (Table 1). 

Table 1--Mean values of soil physical and hydrological properties for the preand postharvest sampling period separated by postharvest site disturbance class 

following a salvage harvest on the Francis Marion National Forest. 

Saturated Mechanical Depth of 

Volumetric Bulk hydraulic Porosity resistance water 

water density conductivity Total micro Macro (0-15.2 cm) table 

(0) (xg/cm3) (cm/hr ) (0) (0) (&a) (cm) 

Preharvcsst 

undisturbed 33.81a 0.71a 57.8a 74.3a 53.7a 20.6a 433a 51a 

slightly disturbedt 32.2a 0.70a 66.7a 75.la 54.2a 20.9a 359a 50a 

ruttedt 30.9a 0.72a 64.2a 71.4a 54.la 17.3b 525b 56a 

postharvest 

undisturbed 33.5a 0.75a 44.6a 72.0a 53.9a 18.1*a 425a 37 *a 

slightly disturbed 35.2b 0.89*b 20.5*b 64.6*b 52.4a 12.2*b 450*a 33*b 

rutted 34.4b 0.96*c 0.2*c 65.6*b 53.2a 11.4*b 625*b 32 *b 

* Significant difference between before and after values (alpha = 0.05). 

# Different letters denote siqnificant difference between site disturbance classes within each period (alpha = 

0.05). 

t No preharvest areas were disturbed or rutted; the classification refers to the pairing of stations following 

harvest. 
DISCUSSION 

Wide-tired skidders are the most 

comonly used machine adaptation for 

logging on wet sites, However, the 

use of wide tires does not necessarily 

reduce site disturbance, On this 

study area, the wide tires provided 

operators the necessary mobility to 

harvest the area, often operating on 

ground too wet to support a conventionally equipped skidder, In this 

case, the wide-tired skidder trafficked 48 percent of the total site 

during the harvest, 

The impact on soil physical properties 

on the untrafficked area was negligible, Mechanical resistance was the 

only soil property for which a preharvest difference was found. It is not 

coincidental that the skid trails 

occurred in areas with the highest 

soil strength. Equipment operators 

quickly find, via trial and error, the 

areas that best support the machine, 

On the trafficked areas, soil strength and bulk density were well within the 

acceptable ranges for normal plant 

growth (< 1.4 Mg/m3 and < 2500 Kpa, 

respectively), even for the most 

highly disturbed classes (Reisinger 

and others 1988). 

However, the hydrology of the area was 

significantly influenced by the network of skid trails (Figure 1, Table 

1). No rainfall occurred on the site 

between pre- and postharvest measurements, and no live trees were harvested during the salvage operation, 

Thus, the increase in water tables was 

not a function of precipitation or 

reduced evapotranspiration; rather, 

the difference was a result of 

decreased subsurface water movement, 

The rutted areas, where total porosity 

and saturated hydraulic conductivity 

were drastically reduced, impede the 

lateral flow of water through the 

porous surface soil horizons above the 

clay layer, 

The study site has a slight slope from 

the western side of the site towards 

the small drain on the eastern side. 

The skid trails intersected and 

blocked this natural flow pattern, 

resulting in a larger change in water 

table elevations on the western side 

of the study area (Figure 2). The 

clay subsoil on this site has an 

inherently low hydraulic conductivity, 

so the interruption of lateral 

subsurface flow within the surface 

horizon resulted in a higher water 

table. This higher water table will 

result in a less well-aerated condition 

on an already poorly drained site and 

may ultimately reduce site productivity. A previous study within the 

same general area indicated that the 

amelioration of similar sites through 

natural soil processes may require as 

long as 18 years (Hatchell and others 

1970). An 18-year period of less than 

optimal growing conditions represents a 

significant proportion of a pine 

stand" rotation and thus may affect 

future volume yields. 

N Drain 

1 

Figure 2--Decrease in depth (i.e,, cm 

of change) to water table following the 

logging operation. 

Skidders equipped with wide tires can 

effectively reduce site impacts when 

used on sites that are marginally 

possible to log with a conventionally 

tired skidder, When wide tires are 

used as a mechanism of gaining access 

to sites normally inoperable with 

narrow-tired skidders, negative soil 

and site impacts can occur, 

ACKNOWLEDGMENT 

The authors wish to thank those 

individuals with the Wambaw and 

Witherbee Ranger Districts of the 

Francis Marion National Forest, the 

National Forests of South Carolina, the 

USDA Forest Service Engineering Lab, 

and the Santee Forest Experiment 

Station who assisted in this project. 

LITEEU1TUm CITED 

ASAE Standards. 1990. Soil cone 

penetrometer. Am. Soc. Agric, Eng. 

Stand, ~313~2, P. 567, 
Blake, G.R.; Hartge, K.H. 1986. Bulk 

density. P. 363-376 in A. Klute (ed.), 

Methods of soil analysis, Part 1, 

Physical and mineralogical methods. 

Ed. 2. Am. Soc. Agron., Soil Sci. SOC. 

Am., Madison, WI. 1188 p. 

Bradford, J.M. 1986. Penetrability. P. 

463-478 in A. Klute (ed.), Methods of 

soil analysis, Part 1, Physical and 

mineral~gicak methods. Ed. 2, Am. Soc. 

Agron., Soil Sci. Soc. Am., Madison, 

WIo 1188 PO 

Burger, I.A.; Aus~, H.M.; Stuart, W.B. 

1991. Strength of soils compacted and 

rutted during logging operations. P. 

346 in Agron. Abstr., Annual Meeting 

of American Society of Agronomy, Soil 

Sci. Sac. of Am., For. Soils Div. Am. 

Soc. Agron., Madison, WI. 

Burger, I.A.; Wimme, K.I.; Stuart, 

W.B.; T.A. Walbridge, T.A., Jr. 1989. 

site disturbance and machine performance from tree-length skidding with a 

rubber tired machine. P. 521-525 in 

Proc. Fifth Bienn. South. Silvic. Res. 

Conf. USDA For. Sen. Gen. Tech. Rep. 

SO-74. 618 PO 

Danielson, R.E.; Sutherland, P.L. 

1986. Porosity. P, 443-462 in A, Klute 

(ed.), Methods of soil analysis, Part 

1, Physical and mineralogical methods. 

Ed. 2. Am. Soc. Agron., Soil Sci. Soc. 

Am., Madison, WI. 1188 p. 

Klute, A,; Dirksen, C. 1986. Hydraulic 

conductivity and diffusivity: Laboratory methods. P. 687-734 in A. Klute 

(ed.) Methods of soil analysis, Part 

1, Physical and mineralogical methods. 

Ed. 2. Am. SOC. Agron., Soil Sci. Soc. 

Am., Madison, WI. 1188 p. 

Hatchell, G.E.; Ralston, C.W.; Foil, 

R.R. 1970. Soil disturbances in 

logging. J. For. 68:772-775. 

Miller, J.H.; Sirois, D.L. 1986. Soil 

disturbance by skyline yarding vs. 

skidding in a loamy hill forest. Soil 

Sci. Soc. Am. J. 50(6):1579-1583. 

Reeve, R.C. 1986. Water potential: 

Piezometry. P. 545-562 in A. Klute 

(ed.), Methods of soil analysis, Part 

I, Physical and mineralogical methods. 

Ed. 2. Am. Soc. Agron., Soil Sci. Soc. 

Am., Madison. WI. 1188 p. 

Reisinger, T.W.; Simmons, G.L.; Pope, 

P.E. 1988. The impact of timber 

harvesting on soil properties and 

seedling growth in the south. South. J. 

Appl. For. 12(1):58-67. 

Steele, R.G.D.; Torrie, I.N. 1980. 

Principles and procedures of 

statistics--A biometrical approach. Ed. 

2. McGraw-Hill, New York. 633 p. 

USDA Soil Conservation Service. 1980. 

Soil Survey of Berkeley County, South 

Carolina. U.S. Gov. Print. Off. 

1980-232-406152. Washington, DC. 94 p. 

Reprinted with permission from Southern 

Journal of Applied Forestry 17(1):22-25 

published by the Society of American 

Foresters, 5400 Grosvenor Lane, 

Bethesda, MD 20814-2198. Not for 

further reproduction. 
C IN BALD CYPRESS-SWAMP TUPELO WETLAND 

CHEMISTRY CAUSED BY HURRIC HUGO 

Charles A. @reshad 

Abstract--Several soil chemical characteristics were 

measured in three bald cypress (Taxodium distichum L. 

Rich. var distichum) - swamp tupelo (Nyssa sylvatica var 

biflora (Walt.) Sarg.) swamps that were either not 

inundated, or inundated to various depths by the storm 

surge associated with Hurricane Hugo. Soil chloride 

concentrations were high 2.5 years after the storm and 

were the only soil change directly attributable to 

saltwater inundation. Many other parameters including 

soil organic matter, nitrogen and phosphorus were 

indirectly associated with saltwater inundation via 

canopy tree mortality. 

Introduction 

~urricanes frequently disturb coastal 

forests in the southeastern United 

States (Purvis 1973) with both shortterm and long-term effects. Shortterm damage is seen as saltburn 

(Gresham 1981) or wind damage (Gresham 

and others 1991) and the degree of 

damage is a function of proximity to 

the hurricane's eye and species. Forest recovery from short-term damage is 

rapid because pre-existing regeneration will be released or residual 

stems will sprout. For example, 

heavily damaged stands on the Francis 

Marion National Forest were revegetated by loblolly pine (Pinus taeda) 

and sweetgum (Liquidambar styraciflua) 

by the second growing season after the 

hurricane. Long-term hurricane damage 

to a forest results from saltwater 

inundation causing tree mortality and 

soil chemistry changes. This type of 

site alteration not only changes what 

is present in the short-term, but 

paper presented at Seventh Biennial 

Southern Silvicultural Research 

Conference, Mobile AL, Nov. 17-19, 

1992. Belle hl. Baruch Forest Science 

Institute Technical Contribution: 

93-2. 

Associate Professor, Baruch Forest 

Science Institute of Clemson 

Univereity, Georgetown. 

could also influence how fast an inundated area is revegetated and what 

species re-occupy the forest during 

recovery. Along the Atlantic Coastal 

Plain, bald cypress ( Taxodium distichum 

L. Rich. var distichum) - swamp tupelo 

(Nyssa sylvatica var biflora (Walt.) 

Sarg.) wetlands are the most vulnerable forest type to saltwater inundation because of their hydrologic connection to marshes and estuaries. 

Salinity tolerence of bald cypress has 

been investigated (Pezeshki and others 

1988) but little is known about the 

effects of saltwater inundation on 

wetland soil chemistry despite several 

hypothesized effects. 

Overstory mortality resulting from 

saltwater inundation will allow more 

direct sunlight on the wetland floor, 

thus increasing soil temperatures and 

possibly nitrogen mineralization, This 

mortality will also add coarse woody 

debris to the wetland and will decrease 

annual leaf fall. Chloride ions could 

extract monium and nitrate ions from 

the soil thus increasing the potential 

to lose nitrogen from the wetland. 

Soil microorganism metabolism could be 

reduced in the presence of saltwater, 

thus affecting the oxidation/reduction 

status of the soil, Saltwater inundation should not directly affect soil 

phosphorus concentrations. onim 

nitrogen mobilization by saltwater 
inundation has been reported in pine 

forest soil solutions (Blood and 

others 1990, 1991) and freshwater and 

marine sediments (Gardner and others 

1991). Ion pairing of ammonium with 

saltwater anions and saltwater 

cations occupying soil cation exchange 

sites would increase aonim loss. 

Alterations of several soil chemical 

characteristics due to flooding are 

driven by microorganism oxygen consumption (Gambrel1 and Patrick 1978, 

Ponnamperuma 1984, Patrick and others 

1985). Since the activity of microorganisms is affected by soil salinity (McClung and Frankenberger 1985, 

Roseberg and others 1986), several 

wetland soil physical and chemical 

characteristics could be altered by 

saltwater inundation, as compared to 

freshwater inundation. The intrusion 

of North Inlet estuarine saltwater 

into adjacent cypress wetlands associated with Hurricane Hugo on Hobcaw 

Barony (Hook and others 1991) created 

an opportunity to monitor the effects 

of saltwater inundation on cypresstupelo wetland soil chemistry. Similar wetlands that were not either 

inundated or less deeply inundated 

were also available for comparison. 

Specific objectives were to monitor 

(1) wetland kydrslogy, (2) selected 

soil chemical characteristics, and (3) 

canopy woody and foliage litterfall 

patterns. 

Methods 

Three bald cypress-swamp tupelo wetlands on Hobcaw Forest, 3 mi east of 

Georgetown, South Carolina were chosen 

for study. The most severely impacted 

stand, referred to as Marsh Road, is a 

linear inter-dune swamp approximately 

750 ft from North Inlet estuary which 

was inundated to a depth of approximately 9 ft during Hurricane Hugo's 

landfall on September 21, 1989. The 

soil is a Hobcaw soil (fine-loamy, 

siliceous, thermic, Typic, Umbraquult; 

Stuckey 1982). There was no evidence 

of saltwater intrusion since the 

hurricane. The least impacted stand 

was an isolated bald cypress-swamp 

tupelo-ash (Fraxinus (L.)) swamp 

approximately 1 mi from North Inlet 

estuary. This stand, called Crabhaul 

suffered only light wind damage and is 

also on a Hobcaw soil. The third 

stand, referred to as Boardwalk, is a 

bald cypress-swamp tupelo headwater 

swamp that drains into a brackish 

marsh and was flushed with saltwater 

during the hurricane. Soil types are 

Rutledge sand (sandy siliceous thennic 

Typic Humaquept) on the brackish marsh 

side and Johnston loam (coarse lomy, 

siliceous, acid, thermic, Cumulic 

Humaquept) on the inland side. 

Five 0.12-ac plots were installed in 

each stand in the spring of 1990, and 

two 10.7 ft2 wooden littertraps were 

placed in each plot in February, 1991. 

A soil sampling station and a shallow 

observatian well was installed in each 

plot in May, 1991. At each sampling 

station, type R thermocouples and 

platinum redox probes (Letey and Stolzy 

1964) were buried at approximately 

3 in, 7 in, and 12 in (Crabhaul and 

Boardwalk) or 12 in and 16 in (Marsh 

Road) below the top of the litter 

layer. A recording rain gauge was 

installed within a mile of each site 

and one observation well in each stand 

had a water level recorder installed. 

Soil samples were taken twenty times 

from April 1991 to April 1992 by 

extracting two 3 in by 18 in soil cores 

with a sharpened pipe from each plot in 

each stand. The soil cores were 

divided into upper and lower 6-in 

sections and samples taken by depth. 

Equal volumes of soil from both depths of the first core and DDW were mixed in 

the field and pH was measured with 

glass electrodes. Thermocouples were 

read with a hand-held meter and redox 

probes were read with a hand-held 

millivolt meter and a calomel reference 

electrode in a KC1-agar salt bridge. 

Littertraps were emptied monthly and 

the water table depth in non-recording 

observation wells was measured weekly. 

Results and Discussion 

Water table dynamics of the three study 

areas is presented in Figure 1. In the 

Crabhaul stand, the water table drops 

rapidly due to leaf emergence, rises 

with frequent rains and drops again 

when the rainfall decreases. This 

stand dries out the most because of the 

high basal area and floods the deepest 

because of its pond-like topography. 

Similar, though less pronounced patterns were noticed in the Marsh Road 

stand which had the most tree mortality. In contrast, the water table 

level in the Boardwalk stand rarely 

dropped below ground level nor flooded 

deeper than 4 in. Since we noticed 

that part of the Boardwalk stand water 

table behaved differently from the 

other, two recording wells were 

installed and this difference is seen 

in Figure 1 as deeper flooding of the 

inland plots. The hydrologic 
15 r Boardwalk inland side 

-20 L 

1s r Boardwalk marsh side 

Figure 1--Water level depths and 

rainfall for three bald cypress-s 

tupelo stands in coastal South 

Carolina that were severely impacted 

(Marsh Road), moderately impacted 

(Boardwalk), and not impacted 

(Crabhaul) by Hurricane Hugo's tidal 

surge. 

connection between the Boardwalk stand 

and brackish marsh is probably responsible for both the lack of flooding 

(rainfall quickly flows from the swamp 

to the marsh) and the lack of drying 

(water flowing from the marsh to the 

swamp if the swamp water table level 

is low). This hydrologic connection is 

supported by the presence of short 

periods of high water levels not 

closely associated with rainfall. 

These "spikesw are explained by lunar 

tides pushing marsh water into the 

sweuap. The two saltwater impacted 

stands had similar soil and water 

tetmperatures, and both were warmer than 

the control Crabhaul stand. These 

tenrgerature trends indicate that saltwater inundation indirectly affected 

soil temperature by reducing canopy 

shading of the swamp floor. The seasonal range of temperatures, within 

stand variation of temperatures, and 

yearly average temperature decreased 

along the progression of; air, water, 

upper soil, and deeper soil. During 

most of the study period all soils were 

reduced (+lo0 to -100 mv) to highly 

reduced (-100 to -300 mv) at both 

depths. However, the upper layers were 

less reduced than the lower layers. 

Reduced conditions indicate that the 

microbial populations were active in 

the impacted stands. Crabhaul soils 

did not oxidize when the water table 

dropped below the soil surface, as 

would be expected in a drained sail, 

Soils of impacted stands were less acid 

than the control stand. Two factors 

probably contribute to this: more 

decomposing litterfall in the control 

stand contributing more organic acids 

and the displacement and loss of 

hydrogen ions by saltwater cations in 

the impacted stands (Blood and others 

1991). Foliage and woody litterfall 

rates reflected saltwater-induced tree 

mortality in opposite ways. The 

unaffected control stand had a foliage 

litterfall rate of 5900 kg ha-1 yr-1 as 

opposed to 2800 kg ha-1 yr-1 for 

Boardwalk and 1110 kg ha-1 yr-1 for 

Marsh Road. Woody litterfall was 

highest for Boardwalk (10,900 kg ha-1 

yr-1) less for Marsh Road (2500 kg ha-1 

yr-1) and far less (600 kg ha-1 yr-1) 

for the Crabhaul, the control stand. 

Therefore, saltwater inundation reduced 

foliage litterfall and increased woody 

litterfall. Soil organic matter was 

highest in Crabhaul swamp, lowest in 

Marsh Road, with Boardwalk having 

slightly more than Marsh Road. Longterm heavy litterfall and cooler tanperatures of Crabhaul swamp probably 

contributed to soil organic matter 

buildup, while low litterfall rates and 

warmer soil temperatures probably 

reduced Marsh Road's soil organic 

matter. Boardwalk's intermediate soil 

organic matter may have resulted from 

different soil types and less tree 

mortality than Marsh Road. Upper soil 
layer organic matter content was 

higher than the lower layer in all 

three stands. The stand with the 

highest saltwater mortality, Marsh 

Road, had soil chloride concentrations 

tely 400 ppm and Crabhaul 

r less, Boardwalk soil 

chloride levels were 5-10 times that 

of Marsh Road. This can be explained 

by repeated brackish water inundation 

from the marsh into Boardwalk over 

many years. Tidal "spikes" were 

noticed in water table level recordings indicating that marsh water 

entered Boardwalk during high lunar 

tides. Because this has probably been 

happening for decades the stand has 

apparently accumulated chloride. Soil 

monium nitrogen levels were highest 

in Marsh Road, which may have resulted 

from mineralization of the high 

biomass input following tree 

mortality. Lower soil ammonium 

concentrations in Crabhaul may reflect 

tree uptake removing nitrogen about as 

fast as litterfall and mineralization 

replaces it. Similarly Boardwalk has 

less litterfall input and less basal 

area to remove ammonium from the soil. 

Also the high chloride levels may 

cate that ion paring may be making 

nium more mobile. 

Soil nitrate levels were low in all 

three stands which is expected in 

reduced soils where microorganisms 

reduce nitrate nitrogen to ammonium 

nitrogen. Among the low values, 

Crabhaul stand had the highest nitrate 

levels indicating that this stand had 

the least reduced soil. The water 

level in Crabhaul did drop below the 

soil twice during the study to deeper 

levels than in the other stands. Soil 

phosphorus concentration patterns were 

similar to soil ammonium concentration 

patterns; highest in Marsh Road, 

lowest in Crabhaul. Like ammonium 

nitrogen, high phosphorus levels in 

Harsh Road are likely the result of 

mineralization of mortality related 

biomass input to the swamp floor. 

Lower phosphorus in Crabhaul may 

indicate a balance between litterfall 

mineralization and tree uptake. 

Overall Saltwater Inundation 

Effects 

Soil chloride was the only soil 

chemical parameter directly affected 

by saltwater inundation. Perhaps soil 

pH differences were influenced by 

hydrogen ion displacement due to 

saltwater anions, but the data could 

not verify this, Most of the other 

soil chemical parameters measured were 

indirectly affected by saltwater 

inundation via tree mortality. Marsh 

Road, the stand with the highest tree 

mortality, had higher soil temperatures, less leaf litterfall, more woody 

litterfall, lower soil organic matter, 

and higher nium nitrogen and phosphorus. These same soil chemical 

changes would be expected if similar 

mortality were caused by another agent 

such as herbicide or insect infestation. 

Literature Cited 

Blood, E.R.; Anderson, P.; Williams, 

T.M. 1990. The impact of Hurricane Hugo 

on coastal forest soils. Bull, Ecol. 

SOC. 71:94. 

Blood, E.R.; Anderson, P.; Smith, PoAo; 

Nybro, C.; Ginsberg, K.A. 1991. Effects 

of Hurricane Hugo on coastal soil solution chemistry in South Carolina. 

Biotropica 23:348-355. 

Gafibrell, R.P.; Patrick, W.H., Jr. 

1978. Chemical and microbiological 

properties of anaerobic soils and 

sediments. pp. 375-423. In: Hook, D.D.; 

Crawford, R.M.M. (eds): Plant Life in 

Anaerobic Environments. Ann Arbor 

Science, Ann Arbor MI. 564 p. 

Gardner, W.S.; Seitzinger, S.P.; 

Malczyk, J.M. 1991. The effects of sea 

salts on the forms of nitrogen released 

from estuarine and freshwater sediments: does ion paring affect ammonium 

flux? Estuaries 14:157-166. 

Gresham, C.A. 1981. A survey of salt 

spray damage of beach vegetation along 

the northern beaches of South Carolina. 

Clemson Univ. For. Bull. #27. 

Gresham, C.A.; Williams, T.M.; 

Lipscomb, D.J. 1991. Hurricane Hugo 

wind damage to southeastern U.S. 

coastal forest tree species. Biotropica 

23~420-426. 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest. J. Coast. Res. 8~291-300. 

Letey, J.; Stolzy, L.H. 1964. 

Measurement of oxygen diffusion rates 

with the platinum microelectrode. I. 

Theory and equipment. Hilgardia 

35:545-554. 
HcClung, Go; Frankenberger, W.T., Jr. 

1985, Soil nitrogen transfo 

affected by salinity, Soil Sci, 

139:405-411, 

Patrick, W-H,, Jr,; Mikkelsen, D,S,; 

Wells, B.R. 1985, Plant nutrient 

behavior in flooded soil, pp, 197-228, 

In: Fertilizer Tsehnology and Use (3rd 

Ed,). Soil Sci, Soc, Am. Hadison WI, 

Pezeshki, S.R.; DeLaune, ROD,; 

Patrick, W,H,, Jr, 1988, Effect of 

salinity on leaf ionic content and 

photosysthesis of Taodim distichm 

L, Am. Midl, Nat. 119~185-192, 

, F,N, 1984, Effects of 

flooding on soils, pp, 9-45, In: 

Kozlowski, T.T. (ed) Flooding and 

Plant Growth, Acaddc Press, New 

York. 356 p, 

Purvis, J.C. 1973, Hurricanes. Disaster 

Prepardness Agency, Columbia, SC, 

Roseberg, R,J,; Christensen, NOW.; 

Jackson, T,L, 1986, Chloride, soil 

solution osmotic potential and soil p~ 

effects on nitrification. Soil Sci, Soc 

Ant. J, 50:941-945. 

Stuckey, B.N. 1982, Soil Survey of 

Georgetown County, South Carolina, USDA 

Soil Cons, Serv, Georgetown, SC, 

Reprinted with permission from 

Proceedings of the Seventh Biennial 

Southern Silvicultural Research 

Conference, Mobile, AL, Nov, 17-19, 

1992, Published by the USDA For. Serv. 

SFES Gen, Tech, Rep, SO-93, July 1993, 

p. 171-175, 
T WATER M NT WITHIN THE WATER TABLE AQUIFER 

FOLLOWING aURRICANE HUGO' 

Thomas Me ~illiarns~ 

Abstract--Hurricane Hugo generated a tidal surge 

approximately twenty feet high which inundated a strip 

of coastal forest from Charleston to just south of 

Myrtle Beach. On the Hobcaw Forest, east of 

Georgetown, the surge was about 10 feet above sea level 

and inundated a strip about 3500 feet wide. Salt water 

infiltrated directly into the forest soil and water 

table aquifer during the surge and from ponded areas 

for a period after the storm. Early auger hole 

measures of water table aquifer salinity reflected the 

deposition of salt within the aquifer throughout the 

surge area. Later multi-level sampling indicated that 

salt concentrations have remained high (2000 mg C1/1) 

through 1992. Higher concentrations have persisted 

deep (12 ft) in the aquifer but groundwater flow has 

also carried high concentrations into hardwood 

drainages. Forest mortality was more closely related 

to salinity determinations in multi-level samplers than 

earlier auger hole data. 

INTRODUCTXON C111) around their roots (Franscois 

Southern coastal forested wetlands are 1980). The fate of salt water within 

subject to hurricanes sometime during the water table aquifer will determine 

the lifetime of most of the tree vege- both mortality and the rate of forest 

tation (Conner In press). Tidal recovery. 

surges are associated with most hurricanes and affect coastal wetlands with 

the same frequency. The extent of 

flooding associated with a tidal surge 

depends on the tidal stage when the 

hurricane approaches the coast and the 

slope of the upland adjacent to the 

coast. Since much of the coastal 

landscape has very small relief a 

tidal surge occurring near high tide 

may cause flooding miles landward from 

the coast. Salt water carried into 

the forest will infiltrate into the 

soil and potentially move within the 

water table aquifer, Trees may be 

killed if water conductivity exceeds 5 

millimhoslcm (approximately 3000 mg 

' Paper presented at Seventh Biennial 

Southern Silvicultural Conference, 

Mobile, AL, Nov. 17-19, 1992. Belle 

W. Baruch Forest Science Institute 

Technical Contribution 93-5, 

Professor, Baruch Forest Science 

Institute of Clemson University, P,O. 

Box 596, Georgetown, SC 29442, 

Hurricane Hugo struck the coast of 

South Carolina on September 21, 1989, 

approximately 2 hours before the 

astronomical high tide (Brennen 1991). 

The eye of the storm crossed the coast 

just north of Charleston, S.C. The 

tidal surge extended northeast of the 

storm center with a maximum height of 

twenty feet above sea level near 

McClellanville, S.C., about thirty 

miles northeast of the center of the 

eye (Coch and Wolff 1991). Elevated 

tidal stages extended to Garden City 

about 75 miles northeast of the center 

of the eye. 

The Hobcaw Forest is located approximately 50 miles northeast of the storm 

center. The forest is located directly 

behind a barrier beach and salt marsh. 

Tidal surge at this location was 

between 9.5 and 10.5 feet above sea 

level (7.5 feet above mean high tide) 

and extended into the forest up to 3500 

feet landward of the salt marsh edge 

(Gardner and others 1991). Salinity 
measured in auger holes in this zone 

immediately after the storm ranged 

from >lo0 to 4000 mg Na/l. The 

maxhum was equivalent to 40% of the 

Na concentration in sea water. 

INXTIAZ1 QE 

Wind damage from Hurricane Hugo was 

moderate on Hobcaw Forest. The most 

severely damaged tall oaks experienced 

less than 30% mortality while the more 

resistant trees had less than 10% 

mortality (Gresham and others 1991). 

Initial damage due to salt stress was 

noted in November of 1989. By 

February 1990 many pines were showing 

severe stress with yellowing foliage 

and defoliation throughout the portion 

of the forest with elevations below 10 

feet above sea level. Defoliation 

continued throughout the spring of 

1990. By late spring pines with 

yellowing crowns were also heavily 

infested with southern pine beetle 

(Dendroctonus frontalis Zherman) and 

engraver beetles (Ips spp.) and the 

role of salt stress became ambiguous. 

Many deciduous trees within the same 

zone failed to produce foliage in the 

spring of 1990. Except for a few 

cypress ( Taxodium distichum (L. ) 

Rich.) that produced new sprouts in 

late 1990 and early 1991 these trees 

subsequently died. Aerial photographs 

taken in early February 1991 revealed 

the pattern of initial mortality 

within the zone of tidal surge 

flooding (Figure 1). 

Figure 1--Distribution of living 

(gray) and dead timber (black) on 

Hobcaw Forest (February 1991) as a 

result of soil salinity. 

The pattern of survivors in 1990 was 

not predictable from the auger hole 

salinity measures taken by Gardner and 

others (1991). Salinity in auger 

holes was highest near the edge of the 

marsh and generally higher on pine 

ridges. Most surviving trees were on 

ridges and there was a fringe of living trees along much of the marsh edge. 

The distribution of mortality suggested 

that salt had maved from the highest 

and best drained areas and accumulated 

in lower topographic positions. This 

suggested that a large portion of the 

tidal surge waters had moved within the 

water table aquifer. 

Salt water within the water table 

aquifer poses a threat to the present survivors and to regeneration, either 

natural or planted. This study had the 

obje~tive of determining three aspects 

of salt distribution in the aquifer: 

(1) What was the present distribution 

of salt in the aquifer? (2) What were 

the rates and direction of water 

movement and was salt moving with the 

groundwater flow? (3) What was the 

rate of salt removal from the system 

and when would salt no longer threaten 

forest health? 

METHODS 

The premise of this research was that 

sea salt movement would be most easily 

characterized by piezometric potential 

and distribution of chloride ion. 

Piezometric potential measures allow 

determination of flow directions. 

Chloride is a major constituent of sea 

salt and most closely approximates a 

conservative tracer. 

The study was conducted within a small 

watershed in conjunction with Gresham 

(this volume) and Conner (this volume). 

The watershed is located adjacent to 

the North Inlet salt marsh and is 

labeled marsh road in each paper. It 

is oriented from southwest to northeast 

with an outlet to the marsh northeast 

of the study site. A small stream 

draining the watershed to the northeast 

flows within a stand of cypress 

(Taxodium distichum (L.) Rich.) and 

swamp tupelo (Nyssa sylvatica var. 

biflora (Walt.) Sarg.). Elevations 

within the stream wetland vary from 4.5 

to 6 feet above sea level. The bottom 

of the best-defined channel slopes from 

4.8 to 4.5 feet above sea level within 

the study area. The wetland is separated from the marsh by a ridge on the 

eastern side that ranges from 7 to 8 

feet above sea level, A ridge along 

the western side separates the watershed from another stream to the west. 

The western ridge also ranges from 7 to 

8 feet above sea level. 

Groundwater was sampled from five transects along the stream section (Figure 

2). A piezometer station was placed in 

the center of each vegetation plot 
established by Conner (this volume), 

Four more piezometer stations were 

established on a line perpendicular to 

the stream forming five transects from 

the top of the eastern ridge to the 

top of the western ridge each with 

five piezometer stations, Each 

piezometer station followed a design 

which had accurately measured water 

chemistry and piezometric potential in 

a layered sandy aquifer near the study 

area (Willi- and McCarthy 1990). At 

each station, piezometric potential 

was measured at depths of 5, 7.5, 10, 

and 15 feet below the surface in 

capped 3/4 in piezometers screened 

with #10 well screen for an interval 

of 4 in at the appropriate depth, 

Water chemistry samples were collected 

from 112 in x 4 in samplers screened 

with #10 well screen and connected to 

the surface by If4 in polyethylene 

tubing, Water chemistry samplers were 

at 4, 6, 8, 10, and 12 feet below the 

soil surface. 

Figure 2--Distribution of sampling 

piezometers. 

Piezometric potential was measured 

weekly from April 1, 1991 through 

March 31, 1992. Piezometer top elevations were surveyed from a nearby 

benchmark. Water levels in each 

piezometer were measured with an 

electrical resistance probe. 

Water chemistry samples were withdrawn 

from the soil on a monthly basis 

during the same time period, Samples 

were withdrawn from the samplers with a 

peristaltic pump. Water was pumped 

from each sampler and discarded until 

three to five sampler plus tubing 

volumes were removed. Then a 60 rnl 

sample was taken in a NHCl washed 

polyethylene sample bottle which had 

been rinsed with distilled water to 

remove all traces of NHCl, Samples 

were returned to the laboratory and 

refrigerated until analysis. Chloride 

analysis was performed on a Technicon 

11 auto analyzer using the ferricyanide method (American Public Health 

Association). 

mSULTS 

Twenty-four sampling stations were 

actually installed. The western ridge 

was indistinct on transect 1 and a 

station was not installed, Piezometric potentials were collected for 52 

weeks from April 1, 1991 until March 

31, 1992, Potentials varied with 

weekly changes in rainfall and potential evapotranspiration, Large weekly 

variability is normal for shallow water 

tables (Lipscomb and Williams 1989). 

During high rainfall periods piezometric potentials within the wetland 

were relatively uniform and equal to 

the height of water standing on the 

surf ace, 

Groundwater chloride concentrations 

showed spatial as well as temporal 

variability. Individual measures 

varied from less than 50 mg/l to over 

3000 mg/l during the year, Highest 

values were found during drier summer 

months while lowest values were found 

during high water in April, 1991. 

However, any inverse relation of 

groundwater chloride concentration to 

antecedent rainfall was weak and 

obscured by spatial variability. 

Chloride distribution and groundwater 

flow directions can be summarized as 

annual averages. The study site can be 

circumscribed by a 1630 feet by 835 

feet by 20 feet thick block, Figure 2 

shows the position and orientation of 

the five piezometer transects within 

this block. Figure 3a shows five 

cross-sections of the block at each of 

the transects. Figure 3b represents 

horizontal maps of the block at each of 

the five sampling depths. Figures 3a 

and 3b each depict three aspects of the 

experiment. The maps represent a contouring of the mean chloride concentrations. At each actual sample point a 

small rectangle is shaded to indicate 

the 95% confidence interval of the mean 

value at that point. Arrows on each 
Transect 1 Transect 2 

I ransect 3 Transect 4 

CROSS SECTIONS 

Transect 5 

1 95 Bir confidence interval 

- 

Figure 3a--Cross sections of each transect showing mean chloride concentrations 

(contoured gray scales), 95% confidence limits on mean values for each sampling 

site (small rectangles with gray scales) and mean direction of groundwater flow 

( arrows ) , 
4 fi. Depth 6 ft. Depth 8 ft depth 

10 ft. Depth 12 ft. Depth 

Figure 3b--Horizontal cross sections of sampled area at each chloride sampling 

depth. Chloride concentration contours and 95% confidence rectangles use the 

same scale as Figure 3a. Groundwater flow lines are for piezometer level just 

below sampling level. 
map are a two-dimensional representa- rendition the darker the gray the less 

tion of groundwater flow direction living vegetation in the pixel. 

detemined from average piezometric 

potential gradients hick were 

significantly (95%) different from 

zero, There were only four 

piezometers per station and they were 

at depths intemdiate between 

chloride samplers. The arrows on 

Figure 3b are representations of the 

flow at depths just below the 

samplers. The 10-foot depth is the 

exception with flow directions of the 

10-foot piezometers (same as the 8- 

foot depth). 

In Figure 4 the mean concentration at 

the upper level (4 foot) is compared 

to forest mortality determined from 

February 1991 color infrared aerial 

photography. Photography was 

digitized and rectified to the Hobcaw 

Forest GIs system base map (Lipscomb 

and Williams 1990). The base map in 

its present configuration has an error 

from true ground position of 7-5 to 10 

feet. The digitized photography has a 

pixel size of 10 feet and a mean error 

of registration of 1-5 pixels or 15 

feet. In the photography living 

vegetation has a bright red or pink 

appearance while dead material is dark 

blue or Mack. In the gray scale 

Spatial Distribution of Salt in 

the Aquifer 

The contours in Figure 3 clearly indicate heterogeneity in all three dimensions. High concentrations (> 1000 

mg/E) airre found near the surface in the 

centers of transects 2, 4, and 5. 

These high values show greater temporal 

variability resulting in 95% confidence 

intervals from 100 to 2000 mg C1/1. 

Slightly lower concentrations were 

found at lower depths under both the 

east and west ridges. Values over 750 

mg/l were found beneath the east ridge 

at transect 5, An extensive area with 

concentrations over 500 mg/l was 

present under the western ridge from 

transect 2 north all the way to transect 5, High concentrations in these 

locations were consistent throughout 

the study and 95% confidence limits 

were often less than 100 mgll wide, 

Concentrations below 50 mg/l were found 

at the surface under the eastern ridge 

at transects 1, 3, and 5, and at the 

surface under the border of the western 

ridge at transect 4. Values below 108 

q/P were found at the aquifer bottom 

near the centers of all five transects. 

Figure 4--Comparison of photographic mortality (right) estimates and 4-foot 

depth salinity est tes (left). Salinity map is the same as Figure 3b and 

uses same gray scale. Mortality is gray scale of digitized February color 

infrared photograph. White box and markers are study area and well locations. 

Larger gray squares are 10 x 10 ft pixels with gray level indicating extent of 

live vegetation. Darker tones indicate greater mortality. 

276 
Groundwater Flow Direction and 

Salinity 

Groundwater flow direction combined 

with the chloride concentration distribution shows a relatively clear explanation of the data collected in 

this study. The bulk of the high 

salinity water is located under the 

west ridge, primarily beneath transects four and five. The bulk sf the 

movernent is to the southeast at most 

depths (Figure 3b). In addition, at 

transects 2 - 5, there is a strong 

upward movement from beneath the 

western ridge. The eastern ridges do 

not show much movement and the fresh 

water beneath them is most likely an 

accumulation of rainfall since the 

surge. The low salinity areas at the 

bottom of the aquifer in transects 3, 

4, and 5 are all consistent with 

artesian flow from an aquifer below 

the clay layer. At the eastern side 

of transect 4, a very strong gradient 

is moving fresh water in all directions and blocking the flow from the 

west. The saline water from the west 

is turned toward the south and the 

surface resulting in very high salinity at the surface in transects 4 and 

5. Saline water also flows towards 

transect 2. In transect 2, the same 

upward movement of saline waters from 

the west and northwest seems to be 

caused by a very small upwelling. In 

this case, relatively little water 

seems to be entering the aquifer; but 

a high pressure area caused the waters 

from the west to rise, 

In all cases, high salinity occurred 

at the surface where upwelling of 

water from the lower aquifer forced 

the normal flow in the water table 

aquifer to the surface. At each of 

these points, salinity rose rapidly 

during periods of little rainfall and 

high evaporation. In some cases the 

upwelling fresh water moved laterally 

and vertically. In transect 3, there 

is a small fresh area that may have 

resulted from upwelling water in 

transect 4 moving upward and outward 

at depths below 6 feet. Such a flow 

may have forced saline water to both 

the south and north at the edge of the 

lowland in transect 3. 

Measured Salt Concentrations 

and Mortality 

The similarity of spatial pattern of 

salt concentration in this study to 

that of tree mortality (Figure 4) is 

quite apparent. Those portions of the 

site where mean chloride concentrations were found to average over 503 

mg C1/1 also generally had dead trees. 

Likewise, the portions where concentrations were less than 100 mg C1/1 

were mostly und ged. Since the salt 

study was not begun until seven months 

after overstory death had occurred the 

measured salinity was not the cause of 

death. The measured salinity is more a 

record of groundwater flow patterns 

that may have also occurred during the 

period of overstory mortality. Also 

the mean chloride concentration of all 

samplers in March 1992 was only 5 mg/l 

less than that measured in April 1991 

indicating relatively little change in 

overall salinity over the entire year. 

CONCLUSIONS 

High concentrations of salinity were 

found up to 30 months after a tidal 

surge covered a coastal pine and wetland area. Yearly averaged chloride 

concentrations at the top of the 

aquifer were found to be above 500 mg/l 

in most of the study area which experienced overstory mortality during 1990. 

Chloride concentrations varied over two 

orders of magnitude in all three physical dimensions as well as through time. 

The spatial variability was consistent 

with measured flow paths and salinity 

patterns. With elaborate threedimensional sampling the pattern of 

overstory mortality was explained post 

priori. 

A consistent finding in this study was 

that highest salinity and overstory 

death were found in areas where groundwater flow moved deeper groundwater 

toward the surface. One might expect 

that in coastal systems highest salt 

induced mortality would be along wetland borders where one would normally 

find perennial wet spots. 

ACKNOWLEDGNENTS 

Funding was provided by the U.S. Forest 

Service and the State of South 

Carolina. Dedicated field sampling and 

preliminary data reduction on piezometric data were done by Steven 

Williams and laboratory analyses were 

conducted by Louwanda Jolley. Their 

efforts are greatly appreciated. 

LITERLATURIE CITED 

American Public Health Association. 

1985. Standard Methods for Examination 

of Water and Wastewater. ISBN 

0-87553-131-8. 

Brennen, J.W. 1991. Meteorologic 

suwnary of hurricane Hugo. J. of 

Coastal Res. SI 8:1-12, 
Coch, N.K.; Wolff, MOP, 1991. Effects 

of hurricane Hugo stom surge in 

coastal South Carolina, 3. of Coastal 

Res, SI 8~201-228, 

Conner, W,H, In Press, Impact of 

hurricanes on forests of the Atlantic 

and Gulf coasts, Coastally Restricted 

Forests, Lade n A, (ed,), Oxford 

University Press, 

Conner, W,H, (this volume). Utificial 

Regeneration of Baldcypress in three 

South Carolina forested wetland areas 

after hurricane Hugo, Seventh Biennial 

Silvicultural Sppsium Proceedings, 

Franscois, L,E, 1980. Salt injury to 

ornamental shrubs and ground covers, 

USDA Home and Garden Bull, #231 U,S. 

Goverment Printing Office Washington, 

DOC, 

Gresham, C. A. (this volume), Changes 

in Baldcypress-Swamp Tupelo wetland 

soil chemistry caused by hurricane 

Hugo induced saltwater inundation. 

Seventh Biennial Silvicultural 

Symposium Proceedings. 

Gresham, C.A.; Williams, TOM,; 

Lipscomb, D,J, 1991, Hurricane Hugo 

wind damage to southeastern U.S, 

coastal forest tree species, 

Biotropica 23:420-426, 

Gardner, LOR.; Michner, WOK,; Blood, 

E.R.; Williams, T.M.; Lipscomb, D,J,; 

Jefferson, W,H, 1991, Ecological 

impact of hurricane Hugo - salinization of a coastal forest, J, of 

Coastal Res, SI 8:301-318, 

Lipscow, D.J.; Williams, T.M. 1990, 

Developing a GI§ for forest managaent 

in the 1990Fs, pp. 551-560 In Resource 

Technology 90: Second International 

Symposiurrr on Advanced technology in 

Natural Resource Managaent, Am. Soc. 

Photo, and Remote Sensing. Bethesda, 

MD, ISBN 0-944426-45-~, 

Lipsco&, B.J,; Willi-8, T.M. 1989, 

Lower Coastal Plain Pine-hardwood 

Stands: Two distinctly different site 

types, pp. 246-250 In Waldrop, T. (ed) 

Pine-hardwod mixtures: A symposicun on 

mnagement of the type, USDA For. Ser,, 

Southeast, For. Exp, Stat., Gene Tech, 

Rep, SE-58, Asheville, N.C. 

Williams, TOM,; McCarthy, J,C, 1991. 

Field-Scale tests of ColloidFacilitated Transport. pp, 179-184 in 

1991 National Research and Development 

Conference on the Control of Hazardous 

Materials, Hazardous Materials Research 

Institute, Greenbelt, HD. 

Reprinted with permission from 

Proceedings of the Seventh Biennial 

Southern Silvicultural Research 

Conference, Mobile, AL, Nov. 17-19, 

1992. Published by the USDA For. Serv. 

SFES Gen. Tech, Rep, SO-93, July 1993, 

p. 177-183. 
Economic and Social Impacts 

THE EFFECT OF HURRICANE RUGO ON FOREST PRACTICE COSTS' 

Allan P. Marsinko, Thomas J. Straka, and Jeffrey L. ~aumann~ 

astract--Comparisons were made of forest practice costs on 

Hurricane Hugo damaged sites and on undamaged sites. In 

general, mechanical site preparation costs were higher on 

ged than on undamaged sites. Chemical site preparation 

costs tended to be the same or lower on damaged sites, 

probably due, in part, to economies of scale. Timber stand 

improvement costs tended to be about the same on damaged 

and undamaged sites. 

INTRODUCTION 

On September - 21-22, 1989, Hurricane 

Hugo, a class 4 hurricane, struck 

South Carolina causing severe damage 

to midland and coastal plain forests. 

Of immediate concern to forest managers was salvage. Later, programs to 

encourage reforestation and timber 

stand improvement became primary considerations. The severity of the 

damage resulted in inordinate amounts 

of residual vegetation which presented 

operational and economic problems to 

site preparation operations. Because 

site preparation costs occur at the 

beginning of a rotation and must bear 

the effect of compound interest 

throughout the rotation, small 

increases in these costs can have a 

large effect on net revenue. Thus, 

these costs will have a large impact 

on the lonq-term timber supply in the 

region. his paper addresses the 

effect of the hurricane on site 

preparation costs and timber stand 

improvement costs. 

 THOD DO LOGY 

The objective of this research was to 

determine the effect of Hurricane Hugo 

on site preparation costs based on 

site preparation method and amount of 

residual vegetation, and timber stand 

Presented at the Proceedings of the 

72nd Annual Meeting of the Appalachian 

Society of American Foresters held at 

Greenville, S.C., on January 20-22, 

1993. 

Allan P, Marsinko and Thomas J. 

Straka, Department of Forest 

Resources, Clemson University, 

Clemson, SC 29634, Jeffrey L, 

Baumann, South Carolina Forestry 

Commission, ~ol ia, SC 29221- 

improvement and chemical costs based on 

intensity of practice. 

Conventional site costs were obtained 

for South Carolina through the South 

Carolina Forestry Commission. Because 

of the relatively small amount of data 

available when broken down by category, 

these conventional cost estimates were 

averaqed with Southwide cost data from 

the Forest Farmer Manual 1990 and 1992 

cost of forest practices surveys. 

Post-hurricane costs were obtained from 

the South Carolina Forestry Commission 

based on data collected through reforestation programs they administered 

after the hurricane. Both sets of data 

were summarized and analyzed by category . 

F4ESULTS 

As expected, site preparation costs 

were generally higher on damaged sites 

than an conventional sites (Table 1). 

They ranged from 6% higher for shear, 

rake and pile to 59% higher for the 

shear and disk operation. In one case, 

the post hurricane cost was lower than 

the cost on a conventional site. 

This is probably partly due to the way 

Table 1 is constructed. Costs on conventional sites are based on the site 

preparation method only. Cost figures 

relating method to residual vegetation 

are not available for conventional 

sites. Thus the cost of $165.68 is 

listed twice, for the same site preparation method and different amounts of 

residual vegetation. This figure can 

be viewed as an average site preparation cost for all levels of residual 

vegetation. The post-hurricane costs 

are broken down by the amount of 

residual vegetation. These costs are 
Table 1--Site preparation costs for reforestation on Hurricane Hugo-damaged forest 

land in South Carolina, 1990-1992 

Arnount of Residue 

Vegetation 

Cost on 

Cost on Hurricane 

Site Preparation Conventional D 

Practice Forest ~ite-orest Site 

Light vegetation present 

Medium vegetation present 

Medium-heavy vegetation present 

Heavy vegetation present 

Heavy vegetation present with 

blowdowns and tree breakage 

Heavy vegetation present with 

blowdowns and tree breakage 

single disk or chop $ 42.84 $ 50.60 

shear and disk 88.00 139.94 

shear, rake, and pile 124.41 131.66 

shear, rake, pile, and 165.68 144.41 

bed or disk 

shear, rake, pile, and 165.68 182.23 

bed or disk 

V-bladed strips with 62.00 98.86 

medium herbicides 

Conventional cost is the average cost on sites not damaged by Hurricane Hugo in 

South Carolina, averaged with Southwide cost of forest practices data from the 1990 

and 1992 Forest Farmer Manual surveys (Dubois et al. 1991 and Belli et al. 1993). 

This column is based on the site preparation practice only (previous column). It 

is not related to residual vegetation. 

Power ($144.41) when there is less 

residual vegetation and higher 

($182.23) when there is more residual 

vegetation. 

The post-hurricane costs behave as 

expected. They increase as the site 

preparation method becomes more 

complex and as the site becomes more 

difficult to work. Other differences 

between pre- and post-hurricane costs 

are likely due to variability in the 

post hurricane data which was due to 

the relatively small number of observations and to differences in criteria 

(from the standpoint of residual vegetation) used to select site preparation methods. Because of the extent 

of damage, foresters from all over the 

state assisted with determining damage 

levels and site preparation practices. 

Because many of these foresters were 

not familiar with local damage criteria, it is likely that damage levels 

were overstated in some cases. This 

is supported to some extent by the 

fact that the "heavy" vegetation 

category consisted of 140 tracts 

(5,746 acres) and the "medium heavy" 

category consisted of only 30 tracts 

(1,711 acres). 

The final entry in Table 1, V-bladed 

strips with medium herbicides, was a 

method devised as a result of Hurricane 

Hugo. All cost data for this method 

were supplied by the S.C. Forestry 

Commission. This is an atypical site 

preparation method devised specifically 

for the hurricane salvage area. Both 

the conventional and post hurricane 

data for this method were supplied by 

the S.C. Forestry Commission. 

The first five entries in Table 1 

increase in difficulty and, in general, 

in cost. These were used along with 

the number of acres per tract in an 

attempt to define an explanatory 

equation relating these variables to 

site preparation cost per acre. The 

resulting regression equation is: 

Site prep. = $78.12 - $,I5 Acres + 

cost per (3.5) 

acre $24.80 Practice Level 

(9.0) R~ = .30 

where 

Acres = number of acres on site being 

prepared. 

Practice level = difficulty level of 

practice (1-5, from Table 1). 
The model behaves as expected. Costs 

increase as the practice level 

increases and they decrease as larger 

tracts undergo site preparation. The 

regression coefficient R' was .30 

which is reasonable for this type of 

data. The equation says that costs 

per acre will be reduced by $.I5 for 

each additional acre in the tract due 

to economies of scale and will 

increase by $24.80 for each increase 

in complexity (difficulty) of the site 

preparation practices. Because the 

cost decreases as the number of acres 

increase, this equation gives feasible 

results only within a limited range of 

acres. At practice level 1, for 

example, the equation becomes negative 

if acres increases beyond 686.13. The 

data analyzed for this regression 

includes several tracts in the 300-400 

acre range and one tract in excess of 

500 acres. The equation cannot be 

used with reliability over about 350 

acres. Likewise, practice levels must 

be in the range 1-5 as they have no 

meaning beyond this range. The value 

of this equation is explanatory, not 

predictive. It does explain the 

quantitative nature of the relationship. 

There is little difference in chemical 

site preparation costs between damaged 

and conventional sites (Table 2). 

This is to be expected as helicopters 

were used for this method and the 

application costs should not vary much 

on different sites. The quantity of 

chemicals used would be expected to be 

greater on hurricane damaged sites and 

this could be why costs on the light 

and medium sites (Table 2) were higher 

on the damaged areas. However, the 

large number of tracts being treated 

helped contain the costs on these 

sites, On the "Heavyw sites, the 

costs on damaged lands were lower than 

on conventional sites. This is likely 

due to the fact that a large number of 

tracts were set up for this practice 

in Smter and Clarendon counties, thus 

permitting a contractor to complete 

many sites in a concentrated area. 

This would be expected to result in 

significant economies of scale. 

Timber stand improvement costs on 

hurricane damaged sites were nearly 

the same as costs on conventional 

sites for medium and heavy levels of 

timber stand improvement (Table 3), 

The cost was higher on damaged sites 

for light levels of timber stand 

improvement. However, this cost 

resulted from treatment of only one 

Table 2--Chemical control costs for 

reforestation on Hurricane Hugo-damaged 

forest land in South Carolina, 1990- 

1992 

Level of cost on Cost on 

Site Conventional Hurricanepreparation Site damaged Site 

Light $ 563,OO $ 64.75 

Medim 88.00 91.53 

Heavy 128.00 106.27 

Table 3--Timber stand improvement costs 

for reforestation on Hurricane Hugodamaged forest land in South Carolina, 

1990-1992 

Cost on 

Level of Cost on HurricaneTimber Stand Conventional damaged 

Improvement Site Site 

Light $30.00 $41.52' 

Medium 66.00 70.37 

Heavy 90,OQ 88.02 

' This cost is for one tract of land. 

Generalizations should not be made 

based on this figure. 

tract. Therefore, no general conclusions can be made. 

s-Y 

In general, mechanical site preparation 

costs were higher on Hurricane Hugodamaged lands and they increased with 

increasing levels of residual vegetation. This is to be expected because 

the residual vegetation affects the 

site preparation activity through 

direct contact with the site preparation equipment, resulting in slowing 

the activity and increasing equipment 

wear and the propensity for equipment 

malfunction* 

Chemical site preparation costs tended 

to be the same or lower on Hurricane 

Hugo-damaged lands although these costs 

also increased with increasing levels 

of residual vegetation. Chemical 

application was by helicopter so the 

effect of residual vegetation was 

primarily to slow application somewhat 

as greater quantities of chemicals were 
applied. Costs reflect the effect of 

residual vegetation but economies of 

scale probably counteracted the effect 

of the hurricane. 

er stand hprovment costs did not 

ar to be affected much by the 

hurricane. This was probably due 

largely to the fact that the lessged stands underwent timber stand 

hprovement . Finally, local market conditions would 

be expected to influence these costs, 

The demand for these services 

increased. If the increase was sufficient to create a shortage of services, prices (in this case costs on 

hurricane damaged sites) would be 

expected to increase. The exact 

magnitude of the change that is due to 

this market situation cannot be 

determined. However, some effect 

should be expected as a result of a 

disaster of this magnitude. 

LXTERiRTURE CITED 

Belli, M.L.; Straka, T.J.; Dubois, 

P9.R.; Watson, W.F. 1993, Costs and cost 

trends for forestry practices in the 

South. Forest Farmer (29th Manual 

Edition) 52(3):25-31. 

Dubois, M.R.; Watson, W.F.; Straka, 

T.J.; Belli, R.L. 1991. Costs and cost 

trends for forestry practices in the 

South. Forest Farmer (28th Manual 

Edition) 50(3):26-32. 

Reprinted with permission from 

Hurricane Hugo: Recovering from 

Disaster, Proceedings 72nd Annual 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Foresters, Greenville, SC, 

Jan. 20-22, 1993. Dr. Vernon L. 

Robinson, Sec-Treas, 2557 Abbott 

Circle, Seneca, SC 29678, 
A FINMCIAL ASSESSMENT OF CAPITAL-EXTENSIVE 

GEMENT ALTERNATIVES FOR STORM- GED T*MB~R1 

Thomas J. Straka and James B. ~akerl 

Abstract--An analysis of the investment costs of three 

management alternatives for storm-damaged pine stands 

is presented: (1) selection management, with 25-30% 

initial stocking, (2) natural even-aged management 

resulting from chemical release of suppressed pine 

seedlings, and (3) a standard pine plantation, with and 

without increased site preparation costs due to storm 

damage. Selection management and natural even-aged 

management were shown to provide a low-capital alternative with reasonable rates of return for stand rehabilitation. The landowner's management objective and 

treatment of land cost will determine the optimal 

alternative. 

INTRODUCTION 

Catastrophic loss of timber is not 

common in forestry investments. 

Wildfire or beetles may cause an 

occasional sudden loss, but the risk 

is minimal. The average southern 

forested acre also has little chance 

of being damaged by a hurricane. 

However, averages mean little to a 

forest landowner after a hurricane has 

passed over his personal forested 

tract. In September 1989, Hurricane 

Hugo damaged over one-third of South 

Carolina's total timberland base. 

Dalnaged timber volume exceeded three 

times the normal annual timber harvest 

in the state. 

Storm-damaged timber, especially for 

disasters of this magnitude, means a 

equipment, tree planting equipment, 

seedlings, and contractors to plant the 

seedlings. The only way to produce an 

"economical" timber sale may be to 

allow both down and standing green 

timber to be jointly harvested. This 

poses a dilemma for the timberland 

owners. Some landowners can get just 

the damaged timber harvested. But for 

those who can't, is it better to sell 

both the damaged and standing timber at 

"current" depressed prices, or to 

forego salvage to sell the standing 

timber at later higher prices. Will 

the unsalvaged down timber affect the 

cost of regenerating the tract? Can 

natural regeneration methods be used, 

and, if so, how important is it to 

retain the standing timber for seed 

trees or growing stock? 

"timber glut" and short-term depressed 

timber prices. It can also mean a This article (1) discusses management 

shortage of loggers, timber harvesting alternatives available to forest 

landowners after such a disaster as 

 his article is based on "Financial 

Assessment of Management Alternatives 

for Storm-Damaged Timber" presented at 

the Management Alternatives for StormDamaged Timber Workshop, February 8- 

10, 1990, Sumter, SC. 

Thomas J. Straka, Department of 

Forest Resources, Clemson University, 

Clemson, S.C. 29634-1003; and James B. 

Baker, USDA Forest Service, Southern 

Forest Experiment Station, Monticello, 

AR 71655. 

Hurricane Hugo, particularly alternatives that require minimal capital 

outlays by the forest owner and (2) 

addresses the financial efficiency of 

the management alternatives for stormdamaged timber. Several methods that 

require low levels of initial capital 

investment are described. The 

importance of the residual stand to 

management alternatives is stressed. 

When capital, loggers and contractors 

are limited, the residual stand may 

provide the basis for economically 
regenerating a damaged stand. The 

many small-acreage nonindustrial 

private forest landowners with limited 

capital resources my find these 

management alternatives to be more 

cost-effective than the more traditional site preparation and plant 

alternative. 

mTHOI)S 

This discussisn is based on yield 

tables developed from case studies 

conducted on or near the Crossett 

Experimental Forest in southeastern 

Arkansas. These results apply to 

loblolly pine (Pinus taeda L.), but 

the economic comparison can be applied 

to any tree species, 

Three alternatives were evaluated for 

a 50-year management period: (1) 

selection management, starting with an 

understocked residual stand (30% 

stocking and 10 ft2 of basal area/ac), 

(2) natural even-aged management, 

resulting from a chemical release of 

suppressed pine seedlings, and (3), a 

standard pine plantation, requiring 

site preparation and planting. 

Average cost data are primarily from 

Straka and others 1989 and Baker 1987. 

All alternatives incur a $3/ac annual 

management cost. 

The selection management alternative 

assumes a stand that was initially 30% 

stocked, on site index 90 (base age 

50) land, and a 7-year cutting cycle 

beginning at year 18. Competing 

hardwoods were controlled initially 

with herbicide at a cost of $45/ac. A 

supplemental management cost of $13/ac 

(for inventory and marking) was 

incurred every 7 years prior to the 

harvest cut. Timber stand improvement 

was done every 10 years at a cost of 

$45/ac. 

The natural even-aged management 

alternative incurred an initial cost 

of $45/ac to chemically release a 

stand originating from natural reproduction (at least 100% stocked) using 

herbicide. Timber stand improvement 

was done at age 5 at a cost of $45/ac, 

Prescribed burning was done every 5 

years, beginning at age 15, at a cost 

of $5/ac. A supplemental management 

cost of $13/ac (for inventory and 

marking) was incurred every 5 years 

prior to harvest. 

Plantation management normally may 

require an initial outlay of $150/ac 

for site preparation and planting. 

After storm damage approximating 

Hurricane Hugo this initial outlay may 

be $250 or higher. Both of these 

initial costs were considered. Thus, 

the plantation management alternative 

has two wsubalternatives"t a normal 

site preparation/planting cost of 

$150/ac and a post-stom-d 

preparationlplanting cost of $250/ac. 

Pine release was done at age 5 at a 

cost of $45/ac. Prescribed burning was 

done every 5 years, beginning at age 

15, at a cost of $5/ac. A supplemental 

management cost of $12/ac (for inventory and marking) was incurred every 5 

years prior to harvest. 

Pulpwood stumpage was valued at 

$15/cord and sawtimber stumpage at 

$150/mbf (Doyle). These were treated 

as real prices (i.e., net of inflation), and no price appreciation is 

assumed. The analysis was on a beforetax basis. Also, cost-sharing was not 

considered. Tax savings and costsharing would improve the economic 

performance of these alternatives. 

However, different owners may have 

vastly different tax treatments (e.g., 

many nonindustrial landowners may 

amortize their investment over 7 years 

and take an investment tax credit, 

while industrial owners effectively 

will not have this option or access to 

cost-sharing). 

All the alternatives were considered 

with and without a $400/ac land cost. 

Land cost is an opportunity cost. 

Almost all forest landowners have the 

option of selling the forestland and 

investing the proceeds elsewhere. But 

not all forest landowners actually feel 

they can exercise this option. Perhaps 

the land is an integral part of a faming operation, or the land has been in 

the family a number of years, or the 

land is held in a trust that does not 

allow its sale. If the option to sell 

the land does not exist, then land cost 

need not be included (many small 

acreage nonindustrial private forest 

tracts may fall into this category). 

Industrial forest owners would need to 

include land cost, as they do have the 

opportunity to sell the land, 

Stand characteristics, harvests, and 

timber production data for the three 

alternatives are presented in Tables 1 

to 3. The yield data used to describe 

the recovery and development of understocked loblolly-shortleaf pine stands 

are from Baker (1990). Data for the 

even-aged natural stand and plantation 

are from Baker (1987). All three 

alternatives were evaluated over a 
Table 1--Growth, yield, and harvest cuts over a 50-year managaent period for 

an uneven-aged loblolly pine stand that was initially 30% stocked (site index 

90, base age 50). 

Merchantable Sawlog 

cubic foot volume 

Basal area vo luma (Doyle) 

Year (ft2/ac ) (per acre) (per acre) 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

Af tar harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Total production 152 4,542 17,594 

Table 2--Growth, yield, and harvest cuts over a 50-year management period for an even-aged natural loblolly pine stand after chemical release over a 50-year 

management period (site index 90, base age 50). 

Merchantable Sawlog 

cubic foot volume 

Basal area volume ( D~Y le 

Year ( f t2/ac ) (per acre) (per acre) 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

After harvest 

Before harvest 

Harvest 

Af ter harvest 

Total production 281 7,807 16,414 
Table 3-Growth, yield, and harvest cuts over a 50-year mnagegent period for a loblolly pine plantation (site index 90, base age 50). 

Herchantable Sawlog 

cubic foot volume 

Basal area volume (Doyle ) 

Year ( f t'lac ) (per acre) (per acre) 

Before harvest 15 

Barvest 

After harvest 

Before harvest 20 

Harveat 

After harvest 

Before harvest 25 

Harvest 

After harvest 

Before harvest 30 

Harvest 

After harvest 

Before harvest 35 

Harvest 

After harvest 

Before harvest 4 0 

Harvest 

Af tar harvest 

Before harvest 45 

Harvest 

After harvest 

Before harvest 50 100 3,456 12,818 

Harvest 100 3,456 12,818 After harvest --- --- --- 

Total production 293 8,488 20,956 

Table 4--Net present values and internal rates of return of timberland 

investment alternatives, with and without land cost, on a per acre basis. 

Internal 

Net present value rate of 

Alternative 4 % 7 % 10% return (%) 

Without Land Cost 

Selection management 

Chdcal release 

Plantation (est. cost $150) 

Plantation (eat. cost $250) 

With Land Cost 

Selection management 

Chemical release 

Plantation (eat. cost $150) 

Plantation (est. cost $250) 

50-year management period, This may 

bias the results slightly toward the 

selection managaent system. Timberland investors utilizing the more 

capital-intensive alternatives often 

would use much shorter rotation 

lengths. For example, land owned by a 

pulp mill might be on a 25-year 

rotation, However, the advantage of 

comparing equal length investments, 

all managed for high quality sawtimber, outweighs this potential bias. 

FZNANGI- RESULTS 

All three alternatives were analyzed 

in terns of net present value at 4, 7, 

and 10% and in terms of internal rate 

of return. Recall this analysis is 

before-tax and in real terms (interest 

rates are net of inflation). This 

accounts for the seemingly low internal 

rates of return. If one assumes an 

inflation rate of 4%, for example, a 

4.5% real rate of return equates to a 

current interest rate (like on a 

certificate of deposit j of 8.68%. 

Analysis results are presented in 

Table 4. 
When land cost is not considered, the 

low capital alternatives produce the 

highest rates of return. Since land is 

"free," it makes sense that modest 

er output, coupled with low initial 

costs, will produce high rates of 

return. At the low discount rates that 

are most likely appropriate for 

nonindustrial private forest 

landowners, the selection management 

also is "competitive," With no land 

cost, selection management produces a 

higher net present value than site 

preparation and planting a stormdamaged site (at the $250/ac cost) at 

all interest rates. Indeed, at a 5% 

interest rate the net present values 

of the first three alternatives (i.e., 

selection management, even-aged 

natural stand management, and the 

plantation having the $150 establishment cost) are within $10.75 of one 

another. This suggests nonindustrial 

private forest landowners with limited 

capital and no land cost could rehabilitate storm-damaged loblollyshortleaf pine stands with at least 

30% initial stocking and earn rates of 

return competitive with large industrial site prepared and planted 

stands, 

However, land is not "Free" for many 

landowners. Over 50 years the net 

present value of holding $400/ac land 

is significant. At the three interest 

rates discussed above, the net present 

values of land cost would be 

Interest Net present value 

rate (%) of land cost 

4 $343.71 

The results in Table 4 show lower net 

present values and internal rates of 

return when land cost is considered. 

The alternatives are ranked identically with the "no land cost" 

analysis. Even when land cost is 

considered, rates of return are 

attractive on a real interest rate 

basis. 

WE3(Y GROW PLANTATION WOO13 AT 

ALL3 

One may ask, why grow plantation wood 

at all? Pine plantations have an 

economic advantage over selection 

management when land cost is considered. But the advantage hardly 

seems great enough to justify the large 

establishment cost. The advantage of 

pine plantations over natural regeneration is based on the fixed cost of land 

being spread among many more units of 

volume in the pine plantation (Holley 

1976). While land represents an opportunity cost to many forest landowners, 

especially forest industry, pine plantations produce an opportunity return 

for industrial forest landowners. 

Consider the three managment alternatives, Each produces a different total 

cubic foot output over 50 years: 

cubic 

Management foot 

alternative output 

Selection management 4,542 

Even-aged natural 

stand management 7,807 

Plantation management 8,488 

Plantation management produces 87% more 

cubic feet of wood (primarily pulpwood) 

than the selection system. The nonindustrial private forest landowner, 

concerned only with overall rate of 

return, would not have a need for the 

extra wood, For the industrial forest 

landowner, however, site preparation 

and regeneration can be "traded" for a 

smaller required land base (Straka and 

Hotvedt 1984). A pulp and paper 

company requiring 32 million ft2 of 

pulpwood annually from company-owed 

timberlands would be required to own 

352,268 acres using selection management (a management system that concentrates tree growth on sawlog rather 

than pulpwood production) and 188,501 

ac under plantation management. If 

land is worth $400/ac, the extra 

163,767 ac required under selection 

management represents $65,506,800 of 

capital. At a 5% interest rate this 

is an annual opportunity cost of 

$3,275,340. 

Thus, it makes perfect sense for the 

industrial landowner to invest in high 

establishment costs; just as it makes 

perfect sense for nonindustrial 

private forest landowners to use a 

selection system to maximize rate of 

return. The simple example above does 

not consider the higher valued 

products that longer rotations and 

selection management produce; but it 

does illustrate the effects of land 

cost on pulpwood oriented industries, 

Porterfield and others (1979) 

described other reasons the extra 

investment in plantation management 

might be acceptable to a timber 

company, Plantations produce 

uniformity. This can translate to 

lower harvesting costs or lower 

sorting and manufacturing costs. 
Thus, delivered cost of wood to a mill 

or rail concentration point could be 

reduced. Plantations produce higher 

yields and increase timber availability near a mill. The extra wood 

might be costly to the timber company, 

but marginal wood purchased on the 

open market would not have to be "bid 

up" because of the extra availability. 

This serves to keep the overall cost 

of timber lower. Plantations also 

offer the chance to reap the benefits 

from growing genetically improved 

trees. 

The advantage of pine plantations is 

that they produce more wood in a 

shorter rotation. The disadvantage is 

that they cost more. Whether natural 

stand management or plantation management is preferrable depends on the 

landownerfs objectives and financial 

expectations. 

CONCLUSION 

Selection management and natural evenaged management provide a low-capital 

investment alternative for nonindustrial private forest landowners to 

regenerate storm-damaged forest 

stands. If land cost is not considered, these alternatives can produce 

higher rates of return than plantation 

management. For forest landowners 

facing large-scale catastrophic storm 

damage, such as the 4.4 million ac of 

timberland damaged by Hurricane Hugo, 

the low-capital requirements of 

selection management may make it the 

best available means of rehabilitating 

a damaged stand. 

Not all stands are suitable for this 

selection system. Baker (1989) suggests that a manageable and biologically and economically feasible stocking threshold is in the range of 15 to 

25%, or 5 to 10 ft2, of basal area/ac. 

If the trees are uniformly distributed, 

of good form, and vigorous, then the 

stand could probably be rehabilitated 

and managed at a lower cost than 

starting over with a pine plantation. 

Foresters should make nonindustrial 

private landowners with storm-damaged 

timber aware of this management 

alternative. 

LITERATURIE: CITED 

Baker, J.B. 1987. Production and 

financial comparisons of uneven-aged 

and evenaged management of loblolly 

pine. P. 267-273 in Proc. Fourth Bienn, 

South. Silvic. Res. Conf., USDA For. 

Serv. Gen. Tech. Rep. SE-42. 

Baker, J.B. 1989. Recovery and development of understocked loblolly-shortleaf 

pine stands. South. J. Appl. For. 

13(3):132-139. 

Baker, J.B. 1990. Development of intermediate and suppressed loblolly pine 

following release. Paper presented at 

Management Alternatives for StormDamaged Timber Workshop, February 8-10, 

1990, Sumter, SC. 4 p. 

Holley, D.L. 1976. Some economic considerations in comparing hardwood 

plantations with natural stands. P. 

111-122 in Hardwood Short Course, Sch. 

For. Resour., North Carolina State 

Univ., Raleigh. 

Porterfield, R.; Utz, K.; Balmer, W. 

1979. Analyzing alternative hardwood 

management strategies. South. J. Appl. 

For. 31(1):7-19. 

Straka, T.J.; Hotvedt, J.E. 1984. 

Timberland ownership by southern 

companies. South. Pulp Paper 

47(12):17-19. 

Straka, T.J.; Watson, W.F.; Dubois, 

M.R. 1989. Costs and cost trends for 

forestry practices in the South. For. 

Farm. (Manual Ed.) 48(5):8-14. 

Reprinted with permission from Southern 

Journal of Applied Forestry 15(4):208- 

212 published by the Society of 

American Foresters, 5400 Grosvenor 

Lane, Bethesda, PID 20814-2198. Not for 

further reproduction. 
SITE PREPAMTION AND TREE PLANITlNG COSTS 

ON HURRICANE-D GED LWDS IN SOUTH CAROLINA 

Thomas J. Stmka, Allan P. Marsinko, 

Jeffrey L. Baumann, and Robert G. ~aight' 

Hurricane Hugo damaged 4.5 million 

acres of South Carolina forest land in 

1989; 1.2 million of these acres 

required reforestation. Much of this 

acreage required site preparation. 

This article presents the major types 

of site preparation utilized after a 

natural disaster like Hurricane Hugo 

and contrasts the costs of these 

operations with those on conventional 

sites. 

Standard site preparation techniques 

were used on the hurricane-damaged 

sites. The amount of residual vegetation was rated as light, medium, 

medim-heavy, and heavy with blowdowns 

and tree breakage. Site preparation 

techniques varied from a single disk 

or chop for light damage to shear, 

rake, pile, and bed or disk for heavy 

blowdowns and tree breakage (Table 1). 

A cheaper alternative used in areas 

with heavy vegetation present with 

blowdowns and tree breakage was to 

push V-bladed strips through the 

debris, plant in the strips, and use 

an application of herbicide to control 

vegetation. 

As expected, site preparation costs 

were generally higher on damaged sites 

than on conventional sites (Table 1). 

They ranged from 6 percent higher for 

shear, rake, pile and bed or disk to 

54 percent higher for the shear and 

disk operation. In one case, the 

post-hurricane cost was lower than the 

cost on a conventional site. This is 

probably partly due to the way Table 1 

'Thomas 3, Straka and Allan P. 

Marsinko, Department of Forest 

Resources, Clemson University, 

Clemson, SC 29634-1003; Jeffrey L. 

Baumann, South Carolina Forestry 

Comission, Box 21707, Columbia, SC 

29221; and Robert G. Haight, USDA 

Forest Service, North Central Forest 

Experiment Station, 1992 Folwell Ave., 

St. Paul, MN 55108. 

is constructed. Costs on conventional 

sites are based on the site preparation 

method only. Cost figures relating 

method to residual vegetation are not 

available for conventional sites. Thus 

the cost of $165.68 is listed twice, 

for the same site preparation method 

and different amounts of residual 

vegetation. This figure can be viewed 

as an average site preparation cost for 

all levels of residual vegetation. The 

post-hurricane costs are broken down by 

the amount of residual vegetation. 

These costs are lower ($162.75) when 

there is less residual vegetation and 

higher ($176.33) when there is more 

residual vegetation. 

The post-hurricane costs behave as 

expected. They increase as the site 

preparation method becomes more complex 

and as the site becomes more difficult 

to work, other differences between 

pre- and post-hurricane costs are 

likely due to variability in the posthurricane data which was due to the 

relatively small number of observations 

and to differences in criteria (from 

the standpoint of residual vegetation) 

used to select site preparation 

methods. Because of the extent of 

damage, foresters from all over the 

state assisted with determining damage 

levels and site preparation practices. 

As many of these foresters were not 

familiar with local damage criteria, it 

is likely that damage levels were overstated in some cases. This is supported to some extent by the fact that 

the "heavy" vegetation category consisted of 140 tracts (5,746 acres) and 

the "medium heavy" category consisted 

of only 30 tracts (1,711 acres). 

The final entry in Table 1, V-bladed 

strips with medium herbicides, was a 

method devised as a result of Hurricane 

Hugo, V-bladed strips were placed 

every 25 to 40 feet within the forest 

stand, using a 0-8 equivalent-sized 

tractor. Seedlings were planted using 

a 5 foot by 8 foot spacing within the 
Table l--Site prkparation and tree planting costs per acre for reforestation on 

undamaged and Hurricane Hugo-damaged forest land in South Carolina, 1990-1992. 

Cost Per 

Acre for 

Tree 

Cost Per Acre Cost Per Acre Planting 

Arnount of Site on Conven- on Hurricane with 

Residue Preparation tional Damaged Percentage Loblolly 

Vegetation Practice Forest Site Forest Site Difference Pine 

Light singledisk $ 42.84 $ 51.60 + 20.4% $31.10 

vegetation or chop 

present 

Medium shear and disk 88.00 135.47 + 53,9% 61.36 

vegetation 

present 

Medium-heavy shear, rake, 124.41 133.99 + 7,7% 50.35 

vegetation and pile 

present 

Heavy shear, rake, 165.68 

vegetation pile, and bed 

present or disk 

Heavy shear, rake, 165.68 

vegetation pile, and bed 

present with or disk 

blowdowns and 

tree breakage 

Heavy V-bladed strips 62.00 

vegetation with medium 

present with herbicides 

blowdowns and 

tree breakage 

strips. All cost data for this method Five representative photographs of site 

were supplied by the S.C. Forestry preparation activities on hurricaneCommission. This is an atypical site damaged lands appear at the end of this 

preparation method devised specifi- paper + 

cally for the Hurricane salvage area. 

Tree planting costs per acre on the 

site prepared stands are also 

presented in Table 1. No consistent 

pattern is evident as amount of 

residue vegetation and intensity of 

site preparation practice seem to 

interact to create different quality 

levels of planting sites* All 

practices, except the V-bladed strips, 

required 350 well-spaced seedlings per 

acre after the first growing season as 

minimum acceptable seedling survival. 

The V-bladed strips required 250 

seedlings per acre. Average tree 

planting cost per acre was $50.13 for 

loblolly pine. Ten tracts were 

planted with longleaf pine at an 

average cost of $79.89 per acre. 

s-Y 

In general, mechanical site preparation 

costs were higher on Hurricane Hugodamaged lands and they increased with 

increasing levels of residual vegetation. This is to be expected because 

the residual vegetation affects the 

site preparation activity through 

direct contact with the site preparation equipment, resulting in slowing 

the activity and increasing equipment 

wear and the propensity for equipment 

malfunction. 

Chemical site preparation costs tended 

to be the same or lower on Hurricane 

Hugo-damaged lands although these costs 

also increased with increasing levels 

of residual vegetation. Chemical 
application was by helicopter so the 

effect of residual vegetation was 

primarily to slow application somewhat 

as greater quantities of chemicals 

were applied. Costs reflect the 

effect of residual vegetation but 

econcranies of scale probably counteracted the effect of the hurricane, 

er stand improvement costs did not 

appear to be affected much by the 

hurricane. This was probably due 

largely to the fact that the lessdamaged stands underwent timber stand 

improvement. 

Finally, local market conditions would 

be expected to influence these costs. 

The demand for these services 

increased. If the increase was 

sufficient to create a shortage of 

services, prices ( i n t h i s case costs on 

hurricane damaged sites) would be 

expected to increase. The exact 

magnitude af the change that is due to 

this market situation cannot be 

determined, However, some effect 

sh~uld be expected as a result of a 

disaster of this magnitude* 

1, Exampleofmoderatedamage. 

2. Single chop site preparation on light damage. 

29 1 
3. A tractor equipped with a V-blade 4. A tractor operating i.n a site 

in a site preparation area. preparation area. 

5. Tractor pushing windrows. 
THE ECONOMICS OF LOBLOLLY PINE PLANTATIONS 

UNDER RISK OF HURRICANE D 

Robert G. Hnight, William D. Smith, and Thomas J. ~traka' 

Abstract--Hurricanes have the potential to instantly 

destroy or damage loblolly pine plantations in the southern 

United States, and the risk of hurricane damage 

substantially reduces the expected economic yield. With a 

6 percent annual probability of hurri-cane damage, which is 

the same as the historical frequency of hurricanes reaching 

the coastal plain of South Carolina, the expected present 

value of intensive plantation management is less than zero 

using 1992 prices and costs and a 4-percent discount rate. 

If trees are salvagable and young stands are less vulnerable, expected present value is positive but still much less 

than the economic yield computed with no risk. Government 

assistance with planting cost results in a moderate 

improvement. The economic effect of tree damage depends on 

the type of damage. Stem sweep causes negligible 

reductions in the expected present value; tree mortality 

results in substantial reduc-tions. These results should 

caution decision makers to make a thorough economic 

accounting of the risk of hurricane damage. 

INTROI>UCTION 

Hurricane Hugo, which passed over 

South Carolina in September 1989, 

demonstrated the destructive potential 

of intense hurricanes. Hugo instantly 

damaged or destroyed 4.5 million acres 

of pine and hardwood forest (Sheffield 

and Thompson 1992). Although several 

authors document the economics of 

loblolly pine (Pinus taeda L.) management (Arthaud and Klemperer 1988, 

Broderick and others 1982, Roise and 

others 1988), none account for the 

risk of hurricane damage possibly 

because intense hurricanes have been 

relatively infrequent during the last 

two decades. During the period of 

The authors are Principal Economist, 

USDA Forest service, North Central 

Forest Experiment Station, 1992 

Folwell Ave, St. Paul, MN 55108; 

Assistant Professor, Department of 

Forestry, North Carolina State 

University, Raleigh, NC; and Associate 

Professor, Department of Forest 

Resources, Clemson University, 

Clemson, SC. 

1970 to 1987, only one Saffir-Simpson 

category 3 hurricane (maximum sustained 

wind speed of greater than 110 miles 

per hour) made landfall along the U.S. 

east coast. In constrast, during the 

period of 1947 to 1969, 13 category 3 

or greater hurricanes made landfall 

(Gray 1990). A review of data linking 

the occurrence of intense hurricanes 

with weather patterns in western Africa 

suggests that hurricane landfall will 

be more frequent in the 1990s and 2000s 

(Gray 1990). 

The damage caused by Hurricane Hugo and 

the prediction of increased hurricane 

frequency raise two immediate questions: (i) What is the effect of the 

risk of hurricane damage on the long 

term economic yield of forestry? (ii) What is the effect of hurricane-induced 

tree damage on the economic yield of an 

existing stand? We address these questions using case studies for loblolly 

pine plantations located in the coastal 

plain of South Carolina. Yields are 

predicted with a version of the North 

Carolina State University Plantation 

Management simulator (Hafley and Buford 
1985, Smith and Bafley 1986) that 

includes the effects of tree d 

the farm of stem sweep (Smith 

stand value is computed using 1992 

prices and costs, These parameters 

are included in formulas for the 

expected present values of income 

under hurricane risk for two 

management situations: (i) the land 

expectation value (LEV) of an infinite 

series sf plantations starting with 

bare ground, and (ii) the expected 

present value (EPV) of a damaged stand 

that may be regenerated in the future, 

In each case, the effect of hurricane 

risk is determined by varying its 

level within the range of historical 

hurricane frequency. 

Most work on the economics of stand 

damage addresses the effect of the 

risk of catastrophe on the long term 

economic yield of plantation management (see Caulfield 1988 for review). 

In a pioneering study, Reed (1984) 

shows that expected LEV can be determined with a simple modification of 

the Faustmann formula rather than with 

more complicated stochastic optimization methods. For the case of fire 

risk, Reed (1984) assumes that fires 

occur in a time-independent Poisson 

process and result in total destruction, and he extends the fomulas to 

include salvagable yield following 

fire and fire risk that depends on 

stand age. Because the assumptions 

about stochastic fire damage apply 

reasonably well to the case of hurricane damage, we use Reed's (1984) 

formulas to estimate the effect of the 

risk of hurricane damage on the 

economics of loblolly pine plantation 

management. 

There is evidence that even moderate 

levels of risk quickly dissipate 

expected LW, Using data for white 

spruce (Picea glauca (Moench) Voss) in 

the northern interior region of 

ia, Reed and Erric~ 

(1985) show that expected LEV is 

negative for all possible rotation 

ages when the risk of fire damage is, 

on average, 1 fire per 100 years, 

Based on this evidence, ~113 hypothesix 

that the level of risk associated witk 

the historical rate of hurricane 

occurrence substantially reduces the 

expected LEV associated with loblolly 

pine management. 

TMo studies analyze the effects af 

risk on the economics of loblolly pine 

plantation managment for risk-averse 

decision makers who account for both 

expected economic yield and its variation (Caulfield 1988, Taylor and 

Fortson 1991). We limit the formulation to risk-neutral decision makers 

who maximize expected present value and 

leave the problem of risk aversion for 

future work. 

There is one study on the economics of 

managing stom-damaged loblolly pine 

stands. Straka and Baker (1991) evaluate alternative reforestation systems 

for damaged stands that have either 

abundant natural regeneration or enough 

vigorous seed trees. They find that 

low-cost treatments that utilize 

natural regeneration have present 

values close to or greater than those 

of high-cost planting alternatives. 

In our analysis of storm-damaged 

stands, we focus on management alternatives for young plantations less than 

20 years old. Storm damage consists of 

stem sweep in live trees and mortality, 

Because young stands have growth potential even with damage, we hypothesize 

that higher economic yield is obtained 

by postponing regeneration. Yield 

predictions explicitly account for the 

effects of stem sweep on product value. 

Further, the fornula for EPV accounts 

for the risk of further hurricane 

damage. Because the growth model is 

developed to predict plantation yield, 

we limit the reforestation option to 

planting, 

mTWODS 

Predicting Plantation Yield and 

Value 

The Plantation Management Simulator 

includes growth models that predict a 

frequency distribution of trees by stem 

diameter and sweep class in one-year 

intervals, Predictions are based on 

parameters describing the initial 

stand: site index, age, density, and 

sweep distribution* The predicted tree 

distribution is the basis for computing 

the value of the yield from a thinning 

or final harvest. 

The value of stand yield on the stmp 

(dollars per acre) is computed witk a 

residual value approach (e,g,, Motvedt 

and Straka 19871, The fipst step is to 

compute the value of the yield at the 

mill* Each tree is utilized as sawtimber or pulpwood depending on value. 

Sawti~er value is computed using a 

bucking program (Faaland and Briggs 

1984) that splits the tree into sawlogs 

based on stm size and sweep and on 

er value (from Random Lengths) and 

milling cost (Deal 1986). Sawlogs are 
cut with a minFmum 4-inch top, Pulpwood value is the product of tree 

volume and pulpwood price. Volume is 

computed using the stem dimensions 

(Smith 1988). From Timber Mart-South, 

pulpwood price (at the mill) is $50 

per cord, 

The second step is to compute the 

value of the yield on the stump by 

subtracting logging and transportation 

costs from the mill value. Logging 

and transportation costs are a function of the diameter distribution of 

tree-length logs (Deal 1986). The 

transportation cost assumes a 50-mile 

haul distance, 

The residual value approach allows us 

to account for the effect of stem 

sweep on tree value, Stem sweep 

affects log length, Because the 

bucking program attempts to produce 

straight logs, as sweep increases, log 

length decreases. Because shorter 

logs have lower values (per unit 

volume), trees with stem sweep have 

lower values than straight trees 

(Smith 1988). 

The residual value approach results in 

stumpage values that increase with 

stand age. For stands without stem 

sweep, sawtimber values (Scribner) 

increase from $111 per thousand board 

feet (Mbf) for a 20-year-old plantation to $232 per Mbf for a 45-year-old 

plantation, Pulpwood values increase 

from $23 per cord to $37 per cord, 

For comparison, quarterly 1992 

southern pine sawtimber and pulpwood 

stumpage prices in Timber Mart-South 

vary around $180 per Mbf and $22 per 

cord, respectively. 

Determining Land Expectation 

Value Under Risk of Storm 

Damage 

The Faustmann equation for LEV is used 

to measure the economic impact of the 

risk of storm damage, According to 

the Faustmann equation, LEV is the 

present value of an infinite series of 

plantations starting with bare land 

and using a fixed reforestation 

strategy and rotation age, Let cr be 

the cost of reforestation and T be the 

rotation age, Associated with the 

reforestation strategy is a value 

function V(T) representing the value 

of the plantation (dollars per acre) 

at rotation age. Letting r be the 

instantaneous, risk-free discount 

rate, LEV (represented by the term 

L(T)) is 

The instantaneous discount rate r is 

related to the annual discount rate i 

by the formula er=l+i, LEVs are computed with an annual discount rate of 4 

percent (r-0.03922). With some manipulation, equation 1 is equivalent to the 

more familiar LEV formula: 

We assume that management takes place 

on site index 70 (ft in 25 years) land 

in the lower coastal plain of South 

Carolina. The planting spacing is 8x8 

(680 trees per acre) with 90 percent 

survival, Stand value is predicted 

assuming no sweep for rotation ages 

between 15 and 45 years in annual 

intervals. In the formulas for LEV, 

the impacts of storms are determined by 

accounting for the probability of storm 

damage, 

We start with three assumptions about 

storm occurrence and damage: (i) 

Storms occur independently of one 

another and randomly in time with some 

average annual probability. (ii) The 

probability of storm damage is independent of stand age, (iii) A storm 

totally destroys the stand. Under 

these assumptions, storm damage is a 

time-independent Poisson process, If 

the management policy is to cut when 

the stand reaches age T and to reforest immediately following harvest or 

storm, then the management regime 

involves a sequence of plantations that 

may or may not reach rotation age 

depending on when storms occur. 

Because storms occur in random intervals, LEV is a random variable with an 

expected value. Let c, and c, be costs 

of reforestation following harvest and 

storm, respectively, and let h be the 

hazard rate (mean annual probability of 

a damaging storm). The risk-adjusted 

Faustmann equation for the expected LEV 

is (Reed 1984) 

[h+r] [ V(T) -c, ~e-'~'")~ h 

LIZ') = 1 -,=-Ih+rfT 

1 - TG2 -C2* 

(21 

Note that, apart from constant terms, 

equation 2 is the same as equation 1 

with a risk premium h added to the 

discount rate r. Thus, the impact of 

storm risk on the optimal rotation age 

can be determined simply by adding a 
premium to the discount rate in the 

marginal conditions f o r t h e optimal 

rotation age (Reed 1984). The effect 

of adding a premium to the discount 

rate is to decrease the optimal 

rotation age and expected LEV. 

Reforestation cost depends on storm 

ge. Because of unusable debris, 

the cost of reforestation following a 

damaging storm is greater than the 

cost of regenerating an undamaged 

stand. Based on average reforestation 

costs recorded in the South in 1992, 

the cost of regenerating an undamaged 

stand is $200 per acre (Belli and 

others 1993). Based on a finding that 

the costs of mechanical site preparation in storm-damaged stands are up 

to 54 percent greater than sitepreparation costs in undamaged stands 

(Straka and others 1993), t h e t o t a l 

cost of reforestation following storm 

damage is $250 per acre. 

To set the hazard rate for a locale, 

it is useful to look at both the 

historical frequency of hurricanes and 

the results of hurricane prediction models. We use the Francis Marion 

National Forest (FMNF) located in the 

coastal plain of South Carolina as an 

example, Hooper and others (1990) 

estimate that 18 hurricanes have 

affected the FMNF over the last three 

centuries. With this frequency, the 

average return time is 16 years and 

the hazard rate is 6 percent. Using a 

hurricane prediction model developed 

at the National Hurricane Center in 

Florida, Hooper and McAdie (In press) 

estimate that the average return time 

for hurricane-induced winds (exceeding 

75 miles per hour) t h a t s t r i k e t h e 

FNNF is 14 years producing a hazard 

rate of 7 percent. Because of its 

location near the Atlantic coast, the 

FMNF is more likely to receive 

hurricane winds than inland forests 

which have lower hazard rates. To 

determine the impact of the hazard 

rate on LEV, we compute LEVs using 

hazard rates of 0 percent, 3 percent, 

and 6 percent, 

The next formula for LEV relaxes the 

assumption that a storm totally 

destroys the stand. Instead, hediately following a damaging storm, some 

of the timber may be salvaged prior to 

reforestation. In the area affected 

by Hurricane Hugo, about 25 percent of 

the damaged softwood timber was 

salvaged (Marsinko and others 1993). 

In most damaged stands, only a portion of the timber was salvaged because of 

stem breakage and limited accessability. Further, the value of 

er was reduced because of 

costs. To account for 

salvage, the risk-adjusted Faustmann 

equation (2) is modified to include an 

age-dependent salvage rate s(t) 

enting the proportion of the 

ged value of a stand age t that 

is salvaged immediately following a 

storm. We assume that 25 percent of 

the value of stands aged 15 and older 

is salvagable: 

The formula for the expected LEV of a 

plantation regime with rotation age T 

and salvage following storm damage is 

(Reed 1984) 

where 

o(T)= /3s (t) ~(t)e-(~+~)~dt. 

Equation 4 includes the term 0(T) 

representing the c 

counted salvage value weighted by the 

hazard rate. The integral for 0(T) is 

approximated using a finite summation 

over annual intervals. In equation 4, 

the risk of storm damage with salvage 

not only adds a premium to the discount rate but also increases the 

effective stumpage value (Reed 1984). 

Storm salvage increases the expected 

LEV, but its effect on the optimal 

rotation age depends on the form of the 

salvage function. A salvage r a t e t h a t 

increases with stand age (e.g., 

equation 3) increases the optimal 

rotation age. To determine the 

economic effect of the salvage function 

defined by equation 3, we compute the 

relationship between LEV and rotation 

age with a hazard rate of 6 percent. 

The final formula for LEV relaxes the 

assumption that the risk of storm 

damage is independent of stand age. 

Instead, the hazard rate is age 

dependent. In the area affected by 

Hurricane Hugo, stands less than 20 

years old sustained much less damage 

than older stands (Gresham and others 

1991, Hooper and McAdie 1993, Hooper 

and others 1990, Sheffield and Thompson 

1992). Further, as we find later, even 

if storm damage in the form of stem 

sweep is widespread in a young stand, 

the damage does not greatly reduce the 

expected economic yield. Thus, we 
assume that young stands (<lo years 

old) are not subject to risk of storm 

damage and teenage stands (10 to 20 

years old) are subject to half the 

risk affecting older stands, Letting 

h(t) be the risk of storm damage in a 

stand of age t, the piecewise hazard 

function is: 

Following Reed (1984), we modify 

equation 4 for the expected LEV with 

salvage to incorporate the hazard 

f ction h(t). Letting m(T)= P h(t)dt be the cumnulative hazard 

rate for a plantation with rotation 

age TI the expected LEV of the 

plantation regime with salvage 

following storm damage and 

age-dependent damage risk is 

where 

The integrals are approximated using 

finite smations over annual intervals. 

In equation 6, the effect of the risk 

of storm damage is more complicated 

than changing the effective discount 

rate and value function as in equations 2 and 4 (Reed 1984). The 

optimal rotation age depends on c,, 

the cost of reforestation after storm 

damage. With an age-dependent hazard 

rate, the rotation age affects the 

probability of storm damage and thus 

the frequency of more costly 

reforestation efforts. 

The reforestation cost is an important 

variable in the computation of 

expected LEV because, as the hazard 

rate increases, the number of reforestation occurrences is likely to 

increase. If the reforestation cost 

is high, the economic impact of an 

increase in the hazard rate is greater 

than if the reforestation cost is low. 

Government assistance can reduce 

reforestation cost following a damaging storm. For example, the Federally 

funded Hugo Incentive Program (over 6 

million dollars) paid about 75 percent 

of the total reforestation cost to 

over 900 qualified applicants (Straka 

and others 1993). To determine the 

impact of assistance with reforestation cost on expected LEV, we compute 

LEVs using equation 6 with reforestation costs for damaged stands ranging 

between $0 and $250 per acre. 

Evaluating Management Regimes 

for Damaged Stands 

Sheffield and Thompson (1992) estimate 

that 62 percent of the area of pine 

plantations within a 23-county area af 

South Carolina sustained some form of 

damage. The storm left broken, dead 

trees and live trees with damaged 

crowns, boles, or roots. The degree of 

plantation damage increased with stand 

age. More than 80 percent of the young 

plantations (<lo years old) sustained 

little or no damage, and damage was 

limited to crown reduction and stem 

sweep. In contrast, about 40 percent 

of the teenage plantations suffered 

moderate to heavy damage in which 

stocking was substantially reduced 

because of tree mortality. 

The presence of damaged trees affects 

the economic yield. Trees with stem 

sweep in young plantations have lower 

value at rotation age because logs are 

bucked into shorter lengths and some 

logs are merchandized as pulpwood 

rather than more valuable sawtimber. 

Trees with stem sweep in teenage 

plantations have even less value at 

rotation age because the degree of 

sweep limits their use to pulpwood. 

The presence of damaged trees raises 

the question of the best management 

strategy. When should the damaged 

stand be clearcut and replanted? 

Should the stand be thinned to remove 

crooked trees? We address these questions for a set of representative 

stands (Table 1). The stand descriptions are based on plot information 

collected following Hurricane Hugo 

(Shef field and ~hom~son 1992 ) . The 

first two stands are 5 years old. Stand 

1 has no damage. Fifty percent of the 

trees in stand 2 are leaning more than 

30 percent from vertical and will 

develop significant stem sweep. Stands 

3 and 4 are 15 years old. Stand 3 has 

no damage, Forty percent of the trees 

in stand 4 are leaning more than 30 

percent from vertical. To simulate 

hurricane-induced mortality, the yields 

in stand 4 are multiplied by a percent 

representing stand stocking. Stocking 

percentages range between 100 percent 

and 10 percent in intervals of 5 

percent. 

The management variables for each stand 

are the timing and intensity of a 

commercial thinning and the rotation 
Table 1. Initial conditions for 

representative loblolly pine stands 

Percent trees 

Density 

Age (treesf (ftT r (years) acre) acre) 

age. The rotation age varies between 

15 and 45 years in 5-year intervals. 

The thinning age varies between 15 and 

39 years in 2-year intervals. The 

percent of the trees thinned may be 

20, 40, or 60 percent. Damaged trees 

are cut first. 

Expected present value is the criterion for determining the best 

management strategy for each stand, 

The EPV is computed assuming that 

damaging storms may occur in the 

future. For simplicity, future storm 

damage is modeled as a timeindependent Poisson process using 

the three basic assumptions in the 

LEV analysis. Although the assumptions that a storm totally destroys 

the stand and that the probability of 

storm damage is independent of stand 

age over-state the potential economic 

impact of storm damage, these impacts 

are reduced by lowering the hazard 

rate. 

Following Reed (1984), we let X be a 

random variable representing the time 

until either the first destructive 

storm or the rotation age T. By definition of the Poisson process, the 

distribution function for X is 

The economic yield Y associated with X 

depends on whether the stand is 

destroyed. If so, the economic yield 

at the time of destruction is the LEV 

(represented by the term L) minus the 

cost of clearing c, For simplicity, 

we assume that the value of the 

thinning is lost if the stand is 

destroyed. Although this assumption 

is unrealistic if a storm occurs 

between thinning and rotation age, the 

effect on EPV is probably small 

because thinning values are small. If 

the stand reaches rotation age, the 

economic yield is the sum of two 

components: the compounded value of 

the thinning and the value of the trees 

present at rotation age (v(T)) and the 

LEV, Thus 

The pair of random variables (X,Y) is 

used to determine EPV (represented by 

J) where J=E(e-rXY). Using the distribution function for X (equation 7), 

J= /:[L-C ] e-mhe-hTdt +e-"[ v ( T) +L ] e-". 

The first term represents the expected 

yield if the stand is destroyed; the 

second term is the expected yield if 

the stand reaches rotation age. After 

integrating and combining terms, the 

formula for EPV is: 

Management regimes for damaged stands 

are evaluated using hazard rates of 0 

percent, 3 percent, and 6 percent. The 

annual discount rate is 4 percent. The 

cost of clearing the land after a storm 

and prior to site preparation and 

planting is $50 per acre. 

RESULTS 

Effects of Risk on Land 

Expectation Value 

To begin the assessment of the economic 

impact of the risk of storm damage, we 

use equation 2 for expected LEV assuming that the hazard rate is independent 

of plantation age and each storm 

destroys the plantation. The relationships between expected LEV and rotation 

age are plotted in figure 1 for hazard 

rates of 0 percent, 3 percent, and 6 

percent. The outstanding feature of 

Figure 1 is how rapidly the expected 

LEVs decrease with increasing hazard 

rate, With no risk of storm damage, 

the maxhum LEV is $1,076 per acre with 

a 31-year rotation. With a 3 percent 

hazard rate, the maximum expected LEV 

($343 per acre) is 68 percent less than 

the maximum LEV with no risk of storm 

damage. With a 6 percent hazard rate, 

which is equivalent to the historical 

average annual probability of a damaging storm reaching the Francis Marion 

National Forest, the maximum expected 

LEV is $-I53 per acre. In fact, for 

hazard rates greater than about 5 

percent, this plantation investment 

earns less than the annual discount 

rate of 4 percent. As expected, the 

optimal rotation age decreases with 

increasing hazard rate. 
Expected LEV (doflars per acre) 1500 I 

In the case with an age-dependent 

hazard rate, the maximum expected LEV 

($461 per acre) is 57 percent less than 

the maximum LEV with no risk. 

, 1s 

75 20 25 30 35 40 45 

Rotarton age jyeafsj 1 

Hazard rate 

GO 03 + 05 I 

Figure 1--Expected LEV versus rotation 

age for loblolly pine plantations 

under alternative levels of hurricane 

risk. 

The next step in the assessment of the 

economic impact of the risk of storm 

damage is the computation of an 

expected LEV that includes an agedependent salvage rate (equation 4). 

Compared to the relationship between 

expected LEV and rotation age for the 

case with a 6 percent hazard rate and 

no salvage, including a 25 percent 

salvage rate for stands greater than 

15 years old (equation 3) produces a 

minor increase in expected LEV (Figure 

1). The maximum expected LEV ($-86 

per acre) provides a $67 per acre 

increase over the maximum expected LEV 

in the case with no salvage. The 

optimal rotation age (27 years) is 

slightly longer than the case with no 

salvage (26 years) because salvage 

increases the stand's expected value 

growth rate. 

Finally, the economic impact of the 

risk of storm damage is assessed using 

the formula for expected LEV that 

includes an age-dependent hazard rate 

in addition to an age-dependent salvage rate (equation 6). When the 

hazard is less than 6 percent for 

stands less than 20 years old (equation 5), the expected LEVs are substantially greater than the expected 

LEVs of plantation regimes computed 

with a 6 percent hazard rate that is 

independent of stand age (Figure 2). 

I 

Hazara rats 

00 4- 06 -+ :?+ salvage I 

Figure 2--The effect of an agedependent salvage rate on the relationship between expected LEV and 

rotation age for loblolly pine plantations under a 6% annual risk of 

hurricane damage. 

In Figure 3, we find that, for hazard 

rates greater than about 5 percent, 

plantation management has a negative 

expected LEV. One way to mitigate the 

negative effect of the storm hazard is 

to reduce the cost of regenerating a 

damaged stand (e.g., government costsharing). Figure 4 shows maximum 

expected LEVs for alternative costs of 

regenerating damaged stands. The LEVs 

are computed using equation (6) with an 

age-dependent hazard rate and salvage. 

For comparison, the horizontal line 

represents the LEV of plantation 

management without hazard ($1,076 per 

acre). Although the expected LEV with 

hazard increases with reduced cost, a 

full cost subsidy produces a maximum 

expected LEV ($574 per acre) that is 

still 46 percent less than the maximum 

LEV without risk. This expected loss 

in value emphasizes the economic 

importance of hurricane damage that 

reduces and postpones harvest revenue. 

The Economics of Managing 

Damaged Stands 

Management regimes for damaged stands 

are evaluated according to their EPV 
(equation 8) under alternative hazard 

rates. From the analysis above, the 

expected LEV (L in equation 8) is $461 

per acre, which is the maxhum LEV 

obtained using equation (6) with a 25 

percent salvage rate in stands greater 

than 15 years old (equation 3) and 

with the age-dependent hazard rates 

(equation 5). 

Expected LEV (doliars per acrej 1500 

Rotation age (years) 

Hazard rate 

00 + 06 -4- var~abie + salvage 

Figure 3--The effect of an agedependent salvage rate and an agedependent risk of hurricane damage on 

the relationship between expected LEV 

and rotation age for loblolly pine 

plantations. 

In the first case, we compare EPVs and 

optimal management strategies for 

young plantations (5 years old) with 

and without damage. The damaged stand 

includes stem sweep in 50 percent of 

the trees. The relationships between 

EPV and rotation age for 3 percent and 

6 percent hazard rates are presented 

in Figure 5. The outstanding feature 

is the negligible impact of stem sweep 

on the EPV of the young plantation. 

For the 3 percent hazard rate, the 

maximum EPV of the undamaged stand 

($585 per acre) is only 7 percent 

greater than the maximum EPV of the 

damaged stand ($544 per acre), For a 

6 percent hazard rate, the difference 

between maximum EPVs is even less. In 

addition, the presence of stem sweep 

has only a slight effect on the 

optimal management strategy. Damage 

does not affect the optimal rotation 

age (30 years for a 3 percent hazard 

Expected LEV {dollars per acre) 

1200, 

Refcres tation cost (dollars per acre) I 

Hazara rate 

+ Var~able + salvage 

Figure 4--The effect of reducing reforestation cost following hurricane 

damage on the maximum expected LEV of 

loblolly pine plantations. LEVs are 

computed with age-dependent salvage and 

hazard rates. 

rate and 25 years for a 6 percent 

hazard rate); however, damage does call 

for an earlier commercial thinning. 

For example, for a 3 percent hazard 

rate, 40 percent of the trees should be 

removed from the damaged stand in year 

21 compared to year 23 for an undamaged 

stand. 

We attribute the small economic effect 

of hurricane-induced stem sweep to the 

relationship between log size and 

value. Price premiums are given to 

long logs that are sawn into wide 

boards. However, for rotation ages 

less than 35 years, which provide the 

highest present values in the above 

cases, few premium logs are produced 

even in stands without stem sweep. 

There is no premium for long logs that 

are sawn into small dimension lumber. 

Thus, although stands with stem sweep 

produce shorter logs, the value 

reduction is not great. 

We have assumed that lumber cut from 

trees with stem sweep does not affect 

lumber grade. However, the compression wood found in logs with sweep can 

cause lumber to warp, which in turn 

reduces lumber grade and value (Smith 

1988). Because we do not know the 
Expected present value ($/acre) 

600 11 

0 1 1 I I 1 - I 

I5 20 25 30 35 40 45 

R~tation aGe (years) I 

Hazard rate--Damage 

- 08--None -B- 06--None 

* 03--rfeavy -9- 06--Heavy I 

Figure 5--Expected present value 

versus rotation age for a 5-year-old 

loblolly pine plantation with 

alternative levels of stem sweep under 

3% and 6% hazard rates. 

degree of this problem, we may 

underestimate the effects of stem 

sweep on the EPVs of damaged stands. 

In contrast to the small effect of 

stem sweep on EPV, increasing the 

hazard rate substantially reduces the 

EPVs of young stands. The maximum 

present value of an undamaged stand 

under no hazard ($1,051 per acre) is 

44 percent and 60 percent greater than 

the maximum EPVs of the same stand 

under 3 percent and 6 percent hazard 

rates ($585 per acre and $421 per 

acre, respectively), Similar results 

are obtained for damaged stands. 

These expected reductions in present 

value result from the assumption that 

another storm totally destroys the 

stand regardless of its age. This 

assumption is reasonable for older 

stands (>$20 years old), but younger 

stands are less susceptible to damage. 

Although an age-dependent hazard rate 

similar to equation 5 would give a 

more accurate estimate of the effect 

of storm hazard on EPV, using an 

average hazard rate across all age 

classes (e.g., 3 percent) is a reasonable approximation. 

damaged stand, about 40 percent of the 

trees have severe stem sweep and must 

be utilized entirely as pulpwood. The 

relationships between EPV and rotation 

age for 3 percent and 6 percent hazard 

rates appear in Figure 6. Stem sweep 

in a teenage stand reduces EPV slightly 

more than does stem sweep in a young 

stand. The maxhum EPVs of the 

undamaged stand are up to 11 percent 

greater than the maximum EPVs of the 

damaged stand for hazard rates between 

3 percent and 6 percent, Compared to 

the optimal strategy for an undamaged 

stand, the optimal thinning age and 

rotation age for a damaged stand are up 

to 5 years earlier. 

Expected present value ($lac) 1600 1 1 

Roration age (years) 

Hazard rate--0amage 

- 03--None * .O6--None 

.03--Heavy * .O6--Heavv 

Figure 6--Expected present value versus 

rotation age for a 15-year-old loblolly 

pine plantation with alternative levels 

of stem sweep under 3% and 6% hazard 

rates. 

Stem sweep has a greater economic 

impact in teenage stands because we 

assume that teenage trees with stem 

sweep cannot be cut into merchantable 

sawlogs. Instead, damaged trees must 

be utilized entirely as pulpwood. 

Nevertheless, the economic impacts are 

mitigated by removing damaged trees 

during commercial thinning, By 

concentrating growth on undamaged 

sawtimber, the effects of storm damage 

are reduced. 

In the second case, we compare EPVs Increasing the hazard rate substanand optimal management strategies for tially reduces EPVs of both damaged and 

teen-age plantations (15 years old) undamaged teenage stands. The maximum 

with and without damage. In the present values of an undamaged teenage 

301 
stand under no hazard ($2,161 per 

acre) are 36 percent and 53 percent 

greater than the maxhum EPVs of the 

same stand under 3 percent and 6 

percent hazard rates ($1,380 per acre 

and $1,141 per acre, respectively). 

Similar results are obtained for 

damaged stands. 

Hurricane-induced stocking reduction 

affects EPV much more than stem sweep. 

The relationships between EPV and 

rotation age for damaged teenage 

stands with alternative stocking 

levels are shown in Figure 7. The 

hazard rate is 3 percent. Each 25 

percent reduction in stand stocking 

reduces the maximum EPV by $240 per 

acre. As stocking drops below 25 

percent, the maximum EPV approaches 

the expected LEV associated with 

immediate reforestation. 

Ex pected present value (Wac) 

1400 '@O0 I 

Rotation age (years) 

r 1 

Stocking percent I - 

I 1.00 ++ 0.75 * 3.56 - 0.25 I 

Figure 7--Expected present value 

versus rotation age for a 15-year-old 

loblolly pine plantation with stem 

sweep and alternative levels of 

mortality (expressed as stand 

stocking) under a 3% hazard rate. 

Moderate reductions in stand stocking 

do not affect the optimal management 

strategy. For stocking levels above 

50 percent, the optimal thinning age 

(21 years) and rotation age (30 years) 

are unchanged. The surprising result 

is that a stand with as little as 25 

percent stocking should be allowed to 

grow for 10 years before clearcut. 

The EPV of this strategy ($508 per 

acre) is 10 percent greater than the 

EPV of immediately clearcutting and 

replanting ($476 per acre). 

DISCUSSION 

The outstanding result is the negative 

effect of the risk of hurricane damage 

on the expected economic yield of 

plantation management. With a 6 percent hazard rate, which is consistent 

with the historical frequency of 

hurricanes affecting a locale in the 

coastal plain of South Carolina, 

intensive plantation management is not 

profitable using 1992 prices and a 4 

percent real discount rate. Assuming 

that young stands are immune to damage 

and that a small portion of damaged 

stands may be salvagable makes plantation management profitable, but the 

expected economic yield is substantially less than the yield computed 

with no risk. These results should 

caution decision makers to adjust their 

estimates of the economic yields from 

forestry taking into account the risk 

of hurricane damage. 

There are ways to mitigate the economic 

effect of hurricane risk. Our results 

show that government payment of regeneration cost following storm damage 

moderately increases expected economic 

yield. Using low-cost management 

options would have a similar effect. 

Indeed, Straka and Baker (1991) show 

that low-cost reforestation methods for 

damaged stands with adequate sources of 

natural regeneration can have present 

values that are superior to those of 

more intensive reforestation methods. 

The potential economic benefits of 

practicing low-cost forestry in areas 

subject to high hurricane risk are an 

incentive to investigate the efficacy 

of these practices. 

The results in this paper apply to 

risk-neutral decision makers who want 

to maximize the EPV of the stream of 

future stand yields. The best harvest 

policy and EPV may change for riskaverse decision makers (Caulfield 1988, 

Taylor and Fortson 1991). Because the 

actual yield stream depends on the 

particular sequence of destructive 

storms, actual present value may be 

above or below the EPV. Taking into 

account the variability in EPV, a 

risk-averse decision maker may not want 

a management policy that maximizes EPV. 

Instead the manager may want to minimize the probability of obtaining a low 

total discounted yield or to maximize 

the minimum periodic yield. These 

problems are left for further work. 
The LEV results are based on a singlestand model that can be extended to a 

whole forest only under restrictive 

assmptions. The expected LEV of a 

single plantation can be viewed as the 

average LEV obtainable from many similar sites that are managed independently under similar, although independent, hazard rates (Reed and Errico 

1985). These assmptions are not 

realistic when the decision maker 

imposes harvest flow constraints and 

when stands are grouped geographically 

so that hazard rates are not independent. A whole-forest model similar to 

those developed by Reed and Errico 

(1986) and Gassmann (1989) is needed 

to address the harvest scheduling 

problem under hurricane risk. 

ACKN0ULEDGME:NT 

Financial support was provided by the 

Economics of Forest Protection and 

Management project of the USDA Forest 

Service, Southeastern Forest 

Experiment Station, Research Triangle 

Park, North Carolina. 

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prediction. Forest Science 31:237-247. 

Hooper, R.G.; McAdie, C,J. In press. 

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In: Kulhavy, D.L.; Costa, R.; Hooper, 

R.G., eds. Proceedings of the third 

red-cockaded woodpecker symposium; Jan. 

25 to 28, 1993; Charleston, SC. 

Hooper, R.G.; Watson, J.C.; Escano, 

R.E.F. 1990. Hurricane Hugors initial 

effects on red-cockaded woodpeckers in 

the Francis Marion National Forest. 

North American Wildlife and Natural 

Resources Conference 55:220-224. 

Hotvedt, J.E.; Straka, T.J. 1987. Using 

residual values to analyze the economics of southern pine thinnings. 

Southern Journal of Applied Forestry 

11:99-106. 

Marsinko, A.P.; Straka, T.J.; Baumann, 

J.L. 1993. Hurricane Hugo: a South 

Carolina update. Journal of Forestry 

91(9):9-17. 

Reed, W.J. 1984. The effects of the 

risk of fire on the optimal rotation of 

a forest. Journal of Environmental 

Economics and Management 11:180-190. 

Reed, W.J.; Errico, D, 1985. Assessing 

the long-run yield of a forest stand 

subject to the risk of fire. Canadian 

Journal of Forest Research 15:680-687. 

Reed, W.J.; Errico, D. 1986, Optimal 

harvest scheduling at the forest level 

in the presence of the risk of fire. 

Canadian Journal of Forest Research 

16:266-278. 

dynamic programming. Management 

Science 30:245-257. 
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1988. Stand level sensitivity analysis 

on the effect of markets on optimal 

management regimes. In: Kent, B.M.; 

Davis, L.S., eds. Proceedings of the 

1988 symposium on systems analysis in 

forest resources; March 29 to April 1, 

1988; Pacific Grove, CA, Gen. Tech, 

Rep. RM-161. Fort Collins, GO: U,S, 

Department of Agriculture, Forest 

Service, Rocky Mountain Forest and 

Range Experiment Station: 145-153. 

Sheffield, R-M,; Thompson, M.T, 1992. 

Hurricane Hugo: effects on South 

Carolina's forest resource. Res. Pap, 

83-284, Asheville, NC: U.S, Department 

of Agriculture, Forest Service, Southeastern Forest Experiment Station: 

51 p. 

Smith, W.D. 1988. Modeling sweep in 

loblolly pine. Ph.D. thesis, Department of Forestry, North Carolina State 

University, Raleigh, NC. 94 p. 

Smith, W.D.; Hafley, W.L. 1986. Evaluation of a loblolly pine plantation 

thinning model. Southern Journal of 

Applied Forestry 10:52-63, 

Straka, T.J.; Baker, J.B. 1991. A 

financial assessment of capitalextensive management alternatives for 

stom-damaged timber, Southern Journal 

of Applied Forestry 15:208-212. 

Straka, T.J.; Marsinko, A.P.; Bamnn, 

J.L.; Haight, R.G, 1993, Site preparation and tree planting costs on 

hurricane-damaged lands in South 

Carolina. Southern Journal of Applied 

Forestry (submitted). 

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Optimum plantation planting density and 

rotation age based on financial risk 

and return. Forest Science 37:886-902. 
TEIE IMPACT OF HURRICANE HUGO ON 

SOUTH CAROLINA'S TIMBER SUPPLY' 

Robert Abt, John Burch, and Gerardo ~ncheco~ 

ABSTRACT--The immediate impact of Hurricane Hugo on 

timber inventory has been documented by the Forest 

Inventory and Analysis (FIA) unit of the Forest Service's Southeastern Forest Experiment Station, The 

impact on South Carolina's timber economy, however, 

will be felt long after the salvage operation is over, 

The approach in this research project is to model the 

impact of Hugo on inventory, supply, and price over the 

next thirty years. This will be accomplished by building three inventory models that correspond to the FIA 

categories of heavy, light, and undamaged regions. 

Yield models will be used to model the growth response 

of the damaged stands, These inventory models are 

being built using the Forest Service's ATLAS modeling 

system that has been configured to include five 

management-types (plantation, natural pine, mixed-pine, 

upland hardwood, lowland hardwood) and two ownerships 

(industry, non-industrial private). These models will 

be Pinked by a stupage market model (SRTS) which will 

project aggregate stumpage price changes and allow 

hasvest to shift among damage regions and ownerships in 

response to inventory levels. The economic model 

allows simulation of different harvest projections and 

sensitivity analysis to economic assumptions. The 

model will also be used to evaluate the welfare effects 

by estimating consuer and producer surplus implicit in 

each projection. The basis for the comparison will be 

a "without Hugo" projection based on historical trends. 

Entployment impacts will be modeled by linking harvest 

simulations to IMPUN input-output multipliers for the 

forest products sector. If you are interested in 

receiving a copy of our final report, please send your 

request to Bob Abt, Department of Forestry, North 

Carolina State University, Box 8008, Raleigh, NC 

27695-8008. The report should be available by July 1, 

1993. 

A pawr presented at the 72nd Annual ~eeting of the Appalachian Society of 

merican Foresters held at Greenville, S,C., on January 20-22, 1993, 

Robert Abt, John Burch, and Gerardo Pacheco, North Carolina State University, 

Raleigh, NC 27695-8008. 

Reprinted with pemission from Hurricane Hugo: Recovering from Disaster, 

Proceedings 72nd Annual Meeting and Regional Technical Conference, Appalachian 

Society of American Foresters, Greenville, SC, Jan. 26-22, 1993, Br, Vernon L, 

Robinson, See-Treas, 2557 Abbott Circle, Seneca, SC 29678. 
mMICME mwt TImER I NTORY, PRICE 

AND WELFARE EFFECTS FOR SOUTH CAROLINA 

John R. Burch, Robert C. Abt, Oerardo Pncheco, 

T. Barton Lander, and Raymond M. ~heffield' 

Abstract--Economic implications of decreased timber 

supply in South Carolina due to hurricane Hugo are 

examined using estimates of changes in consumer and 

producer surplus. The approach used is a "with" and 

"without" Hugo comparison. The baseline, "without" 

scenario, simulates South Carolina inventory without 

the occurrence of Hugo. This is compared to a projection based on the Forest Service's Hugo survey. Timber 

inventory is projected using the ATLAS model. Regional 

supply and demand shifts are estimated using the SubRegional Timber Supply (SRTS) model. Together they 

produce compatible inventory and stumpage price projections. Comparison of producer and consumer surplus are 

made and aggregate welfare impacts are estimated. Note 

that these results are prelhinary and subject to revision. The focus in this paper is on the modeling 

approach, not the price or inventory levels. 

INTRODUCTION 

Hurricane Hugo swept through the 

coastal plain and piedmont of South 

~arolina on September 21, 1989 damaging over one-third of the state's 

timberland. The inventory reduction 

was estimated to be 1.3 billion cubic 

feet of which one billion was in softwood management types. The immediate 

destruction wrought by Hurricane Hugo 

will have long-run impacts on the 

future of South Carolina's timber 

economy. The objective of this study 

is to estimate long-run inventory, 

price, and welfare impacts which 

result from the loss of private timber 

inventory. 

In this study we project statewide 

inventory using two different 

scenarios, The baseline projection 

The authors are: Former Graduate 

Research Assistant, Currently Forest 

Analyst, Georgia-Pacific Corp., 

Atlanta, GA; Associate Professor of 

Forest Economics and Graduate Research 

Assistants, respectively, North 

Carolina State University, Raleigh, 

NC; and Resource Analyst, Forest 

Inventory & Analysis, Asheville, NC. 

estimates state inventory levels that 

would have been likely if Hurricane 

Hugo had not occurred. The second, 

with-Hugo, projection models inventory 

trends based on what was left after the 

Hurricane. 

The long-run difference in inventory 

projections is a result of the different starting inventories, the resulting 

change in age-class distribution, and 

the price and harvest consequences of 

the shift in supply. It is doubtful 

that South Carolina's demand for growing stock will be unaffected by Hugo. 

In this paper, however, we model the 

inventory effect given the same demand 

scenario. 

The change in welfare for producers and 

consumers was calculated by integrating 

the appropriate areas of the estimated 

supply and demand relationships resulting from the economic analysis. 

MODELING APPROACH 

The period of analysis for this study 

is from the year 1990 to 2025, This 

will allow for at least one rotation of 

inventory recovery. For the purpose of 

this study South Carolina is considered 

to be an autonomous trade region. The 
ameliorating effect of stumpage flows 

between South Carolina and the coastal 

plain of Georgia or North Carolina are 

ignored. Within the state of South 

Carolina, the inventory is subdivided 

into damage regions which reflect the 

various degrees of damage sustained 

from the hurricane. The damage 

regions are heavy, light, and no 

ge as defined by the USDA Forest 

Service. Private and industrial 

ownerships are modeled separately 

within each category. The exclusion 

of publicly owned forest inventory was 

due to the small number of FIA plots 

available to support an extensive 

modeling effort (3 damage classes x 3 

management types x age class) and its 

uncertain prospects for contributing 

to future timber supply. 

Within ownerships, inventory is 

divided into three types, 1) planted 

pine, 2) natural pine/oak-pine, and 3) 

bottomland/upland hardwood management 

types. 

Data 

These models are currently structured 

to allow for the projection of only a 

single product (growing stock) and a 

single market price. SRTS models 

price as an index. In this case, 

initial price was calculated as an 

average of the pulpwood and sawtimber 

prices weighted by their proportion of 

total state removals as reported in 

the industry sununary of 1988 

(Davenport and Tansey 1990). The 

starting price for the baseline projection is calculated from third 

quarter 1989 Timber Mart-South data 

(Timber Mart South 1989). The third 

quarter of 1989 was the last data 

period prior to Hurricane Hugo. The 

weighted price for the with-Hugo 

simulation is calculated using the 

fourth quarter 1990 data. It is 

assumed that the interim fifteen 

months gives a more stable starting 

point for the price series. 

Starting inventory information was 

provided by the Forest Inventory and 

Analysis (FIA) survey. The 1977 

(Snyder 1978; Craver 1979; Sheffield 

and Hutchison 1979) and 1986 (Tansey 

1986, 1987, 1987a) South Carolina 

state FIA surveys are used to establish accurate growth and yield information. The 1986 survey inventory 

level was used as the baseline starting inventory. It was adjusted, using 

average annual rates of change, to 

represent 1985 levels primarily for 

reporting purposes and the five-year 

increment used in the model. An additional special FIA survey of post-Hugo 

inventory was completed in 1990 and 

provided the starting inventory for the 

with-Hugo projection (Sheffield and 

Thompson 1992). 

The Econoanic Model: SRTS 

The SubRegional Timber Supply (SRTS) 

market model is used to model the 

economic effect of the inventory 

changes through time. SRTS models 

demand as function of price and an 

unspecified shifter. It models supply 

as a function of price and beginning of 

period inventory assuming a constant 

elasticity (logarithmic) functional 

form. SRTS uses projected harvest and 

aggregate supply to determine price and 

reallocate harvests between regionowner units (Abt and others 1993). 

It is assumed that demand increases as 

projected in the South's Fourth Forest 

study (USDA Forest Service 1988). The 

harvest trend was used in the baseline 

case to determine the implicit demand 

shift through time (Abt and others 

1993). These period-specific demand 

shifts were then applied to the postHugo projection. 

Table P shows the demand and supply 

elasticities used for the results 

reported here. These correspond 

generally to the elasticities for the 

Southeast in Haynes and Adams(1985). 

Table 1--Elasticities assumptions. 

Elasticity Owner Estimate 

Inventory-Supply Owner ~stimate 

supply-price FI .47 

NIP . 30 

Demand-Price ALL 015 

Inventory-Supply ALL 1.0 

The Inventory Model: ATLAS 

The Forest Service model ATLAS (Aggregate TimberLand Assessment System; 

Mills and Kincaid 1991) was used to 

project timber inventories for the two 

scenarios. ATLAS is an age-class based 

model that moves acres through time 

based on user specified management 

assumptions and yields. Timber inventory was modeled by damage region, 

ownership, and management type (3 

damage regions x 2 ownerships x 3 

management types). Each was projected 

separately to determine aggregate 
inventory. Table 2 illustrates the 

ATLAS configuration that is specific 

to the Hurricane Hugo study. 

Table 2--ATLAS configuration for Hugo 

study. 

Damage Management 

Region Ownership Type 

None Industrial Planted Pine 

Private 

Light Non-Industrial Natural Pinel 

Private Oak Pine Mix 

Heavy Hardwood 

The acreage shifts, or conversion 

rates, used in the inventory projection are consistent with published 

trends for South Carolina (Alig 1985). 

We assumed that acreage allocation 

among management types and initial age 

classes was not shifted by the hurricane though it is possible that some 

rapid one time conversion will take 

place. The only accelerated conversion accounted for in this projection 

is that which occurred after Hurricane 

Hugo but before the completion of the 

1990 FIA post-Hurricane Hugo survey. 

some consequences of these assumptions 

are discussed later. 

The yield tables are constructed differently for the baseline and withHugo scenarios. For the baseline 

projection, "growthw yield tables are 

developed using the FIA survey data. 

It assumed that cumulative average 

growth by age class most accurately 

describes stand yield in each fiveyear age class. 

For the with-Hugo scenario, yield 

tables for dmaged stands were constructed using a planted pine growth 

model and a natural pine model to 

reflect changes in growth and yield 

patterns due to tree loss at different 

ages. Damaged hardwood yield tables 

are constructed from estimated growth 

reductions, The yield tables for 

undamaged stands are the same in both 

scenarios, 

Market-Inventory Model Linkage 

ATLAS projects individual inventories 

for the region-owner-type units for a 

five-year period. This inventory is 

passed to the SRTS market model. The 

percentage change in aggregate 

inventory is used as a shifter for the 

aggregate supply curve. Supply curve 

shifts and assumed harvest level determines a new price. The new price is 

applied to the supply curves of the six 

individual region-owner units to determine the new harvest allocation for 

each region-owner. The allocation of 

harvest across mnagernent types within 

a region-owner unit is not modeled 

economically. It is determined by a 

cornbination of initial hameat propartions, current inventory proportions, 

andlor current growth proportions. 

The harvest request for the next period 

is then passed back to ATLAS, and the 

sequence is repeated for the next fiveyear period to the end of the projection horizon. Figure 1 shows the 

conceptual relationships between the 

inventory model and the economic model. 

ECONOMIC MODEL 

INVENTORY MODELS 

Figure 1--Relationship between 

inventory and economic model. 

The sequencing of this link is different in the baseline projection and the 

with-Hugo projection. The difference 

is due to the need to hold demand 

rather than harvest constant between 

the two projections. The baseline 

simulation is projected first using the 

harvest trends from the South" Fourth 

Forest. Along with supply shifts due 

to inventory, SRTS uses these harvest 

levels to determine price and the 

implicit demand shift for the period. 

The with-Hugo run takes the more traditional economic approach to use demand 

(as estimated above) and supply to 

determine harvest. Though the demand 

curve is assumed to be the same, harvest declines due to the decrease in 

supply 

Figure 2 illustrates the modeling 

approach. The line labeled "Baselinew 

is the baseline supply curve for any 

period and the "With Hugow is the 

corresponding supply curve for the 
with-Hugo run. In the base run, 

harvest level for each period is known 

and the supply curwe is detemined as 

inventory is passed from ATLAS. The 

price is determined at the point where 

the supply curve and harvest levels 

intersect and the d 

implied through this point, In the 

with-Hugo run, the inventory is passed 

to SRTS as before and the aggregate 

supply curve *With Hugo" is determined, Since the deinand curve is the 

same as in the baseline projection, 

the resulting equilibrium harvest 

level and price can be determined, 

Figure 2--Modeling approach. 

WELFARE MEASUREMENT 

Welfare effects were measured as 

changes in consumer and producer 

surplus, Producer surplus is the area 

left-bounded by the y axis, upperbounded by the price line and lowerbounded by the supply curve, Similarly, consumer surplus is that area 

left-bounded by the y axis, lowerbounded by the price line and upperbounded by the demand curve, For this 

study the welfare estimates are 

calculated as changes rather than as 

absolutes, 

In the stumpage market, producers are 

the forest landowners, and consumers 

are users of stumpage or primary 

owners of processing facilities. The 

producers of stumpage lose potential 

income associated with volume loss, 

Those who have a residual forest after 

the hurricane, however, will realize 

gains from the higher prices. The 

consumers who face more competition 

for reduced supply lose due to both 

reduced production and higher input 

prices, In this project no attempt 

was made to separate welfare effects 

for fully integrated industries that 

operate as both producers and 

consumers in this market. 

Figures 3 and 4 illustrate changes in 

consumer and producer surplus from a 

shift in supply, Figure 3 shows in 

area a the loss in consumer surplus 

from an increase in price and a 

decrease in quantity, In Figure 4 area 

a represents gains to producers due to 

the increased price, Area b represents 

the loss to producers from decreased 

harvest, The difference between area a 

and b is the net gain to producers, 

Figure 3--Consumer surplus change. 

Figure 4--Producer surplus change. 

RIESULTS 

Inventory 

Initial inventory reduction in softwood for the ownerships in this model 

was about 700 million cubic feet or 

about 8 percent of aggregate volume. 

About 6 percent of aggregate hardwood 

inventory was destroyed by Hugo or 

roughly 300 million cubic feet. The 

impact of this initial reduction in 

aggregate inventory levels is evident 

in the with-Hugo projections of both 

management types. 

Initial reductions in softwood inventory seem to be the basis for the gap 

between baseline and with-Hugo softwood projection (Figure 5). The baseline projection for softwoods shows an 

increase from 8 billion cubic feet to 
12 billion cubic feet. The Hugo 

scenario projected slightly less than 

11 billion cubic feet. The with-Hugo 

projection flattens after 2020 as a 

result of relatively higher dernand 

pressure on younger age classes, In 

2030 the aggregate inventory differes are approx tely 13 percent for 

wLtwoods. 

Figure 5--Softwood inventory 

projection, 

The initial inventory reduction in 

hardwood types seems to be a large 

factor in the projected inventory 

differences as well (Figure 61, However, the growth/drain ratio also 

plays an important role in determining 

the future hardwood inventory. From 

1995 to 2005 in baseline run the 

inventory increases indicating balanced growth and removals, After this 

period, removals surpass growth and 

inventory flattens and then declines 

to the end of the projection, The 

first 10 years of the with-Hugo 

simulation indicates the initial 

effect of the hurricane on the 

growth/removals balance. An 

increasing trend up to 2010 indicates 

acme recovery of the growth/removal 

-- ---- 

4----------- ---- 2------- 

I 

ieOO 1- 204JO 2005 Mi0 MlS MXI XIW ZIXID 

- Beullne - Hugo -A 

Figure 6--Hardwood inventory 

projection. 

ratio, However, the inability of 

inventory to recover fully in the withHugo projection ultimately results in 

suppressed growth and an approximate 

20 percent lower inventory at the end 

of the projection period. 

If a more elastic demand curve were 

used to reflect substitution of wood in 

neighboring states, the harvest would 

decrease more and the with-Hugo inventory projection would likely show 

better aggregate inventory recovery, 

Price 

Since supply and demand are inelastic, 

the decrease in inventory leads to a 

relatively small decrease in harvest, 

but relatively a greater increase in 

price, Price trends follow shilar 

paths but the effect of timber supply 

rduction is to magnify the price 

effects (Figures 7 and 8). For 

example, increasing price trends in the 

baseline are also increasing trends in 

the with-Hugo but at a faster rate, 

When the price decreases for softwoods, 

the trends decrease more slowly than in 

the baseline. 

IpriOOnrR Baseline v. Hugo 

1W r 

I i 

Figure 7--Softwood price projection. 

Baseline v. Hugo 1 

la IWJ IQW 1995 2W iW 2010 :atS ,m ms 

Figure 8--Hardwood price projection. 
Welfare 

The welfare results indicate that as 

producers wait until the price effects 

peak, they can maximize welfare gains 

by realizing the highest prices. The 

consumers will realize maximum losses 

when forced to compete for less wood 

offered at the price peaks. Stumpage 

consumers will be relatively worse off 

until sufficient inventory recovery 

restores the market to pre-hurricane 

conditions. 

Consumers are expected to have 

increasingly negative welfare effects 

throughout the projected period. 

Conversely, producers are estimated to 

have positive welfare effects. Furthermore, the projected losses to 

consumers will exceed the gains to 

producers over the 35 years, The 

relative distribution of gains and 

losses over time for producers and 

consumers is shown in Tables 3 and 4. 

The net value of producer surplus and 

consumer surplus or total social 

welfare loss for all markets is 

displayed in Table 5. The present 

value of net welfare loss to the 

timber economy is discounted at 

several rates to indicate relative 

severity in 1998 dollars. 

The welfare effects reported in this 

paper are aggregate impacts and could 

be different for producers and consumers under alternative assumptions 

or model specifications. The following section discusses some conditions 

that could alter the results. 

Table 3--Softwood Consumer and 

Producer Surplus Change and Net 

Welfare , 

Period PS Change CS Change Net Welfare 

Impact 

Total 1,705,677,657 -2,720,429,043 -1,014,751,386 

Table 4--Hardwood Consumer and Producer 

Surplus Change and Net Welfare. 

Period CS Change PS Change Net Welfare 

Impact 

1990 

99,864,119 -1671231,329 -67,367,210 

1995 

136,833,814 -232,474,459 -95 , 640,645 2000 220,610,930 -369,559,277 -148,948,347 2005 

329,140,690 -548,110,713 -218,970,022 2010 534,344,735 -862,897,251 -328,552,515 20 15 

845,051,195 -1,378,763,763 -533,712,568 2020 1,332,330,328 -2,188,895,667 -856,565,338 2025 2,181,141,587 -3,616,743,567 -1,435,601, 979 2030 

Total 5,679,317,398 -9,364,676,026 -3,685,358,628 

Table 5--Net Present Value of Welfare 

Effects. 

Discount Rate Net Present Value 

1)ISCUSSXON 

These projections are sensitive to some 

of the input parameters and economic 

assumptions. Alternative assumption on 

several parameters would likely create 

different inventory and economic 

results, Sensitivity should be conducted on ATLAS, SRTS and the link 

between the two models for the following components: acreage assumptions, 

stocking adjustment coefficients, harvest trend (i.e., demand assumptions), 

regional definition and product 

differentiation. A discussion of 

sensitivity on several of these 

variables is presented for TRIM by 

Alexander (1991). 

Acreage Shifts 

In ATLAS, acreage by age class is an 

important determinant of aggregate 

inventory so projections are sensitive 

to these specifications. Acreage 

trends reflecting alternative conversion rates in response to Hugo may 

alter the results. It is likely that 

stand conversion to planted pine or 

younger age classes of natural pine 
will proceed more rapidly than anticipated in the Alig study as a result of 

Hurricane Hugo. Data from the 1992 

statewide remeasurement indeed show 

that replanting may be minimal but 

natural regeneration has increased 

significantly. This one-time rapid 

conversion could have a significant 

impact on the long-run inventory 

recovery and therefore on the resulting price trends and welfare effects. 

Potential consequences will be 

explored in future models. 

stocking Adjustment 

The density change (approach-tonormal) coefficients in ATLAS are used 

to adjust stocking ratios through time 

to what would be considered "normal" 

stocking. The process to estimate the 

density change coefficients involves 

regressing current stocking on previous period stocking (Mills 1989). It 

was found that small changes in coefficient specification may lead to 

large changes in inventory projections. It should be noted that this 

is primarily an accepted theory at the 

stand level but evidence that regional 

inventories exhibit this behavior has 

not been documented empirically. 

Harvest Assumptions 

Harvest requests have important implications for supply shifts and price 

projections for the baseline projection. The assignment of regional 

starting harvests was based on historic regional harvesting activity. 

Basing initial harvests on historical 

information caused some regions with 

little inventory after the hurricane 

to be over harvested because they had 

the highest requests due to heavier 

historic cutting. The resource in 

some of the regions was being cut out 

before the economic model could shift 

harvests to other regions. The 

problem was solved by moving harvests 

to regions with higher inventories for 

the first period. This assumes that 

regional harvests are better predicted 

by current inventory than past harvest 

levels. 

Related to harvest assumptions is the 

hplied increasing derived demand for 

stumpage. The reduction of inventory 

by Hugo will likely affect the demand 

in both the end use and stumpage 

markets. The harvests may remain 

constant or even decline in response 

to supply shifts and market pressure, 

To capture this effect, demand should 

be allowed to change in the with-Hugo 

simulation or at least shift to 

outside regions (i-e., North Carolina 

andlor Georgia). 

Regional Definition 

Restricting stumpage trade between 

South Carolina and Georgia or North 

Carolina imposes unrealistic restrictions on the stumpage market. It 

furthermore elevates the est 

price and welfare effects by not 

allowing some capacity to shift out of 

the state. The mitigating effects of 

allowing trade between these regions 

should be investigated to obtain more 

realistic impact assessment. One 

method of accommodating other regions 

is to define additional management 

units for bordering regions. Another 

method may be to adjust elasticities to 

reflect more quantity harvest adjustments in response to price movements, 

Product Differentiation 

Product differentiation is not accommodated in this research. If welfare 

impacts could be distributed among 

consumers by products, the producers 

and consumers would likely have very 

different results. For example, the 

welfare impacts to the consumers of 

pulpwood would be different from those 

experienced by sawmills since degrade 

may create an overabundance of 

pulpwood. 

CONCLUSION 

Hurricane Hugo affected the short- and 

long-run timber economy of South 

Carolina. Though the net social 

welfare loss was substantial, the 

distribution of the loss is also 

important* These welfare impacts show 

the potential size of the impact and 

its distribution among consumers and 

producers of timber. 

Only the long-term welfare effects were 

estimated by this research. The shortterm welfare impacts were very different from the long run. Producers had 

short-term losses from depressed market 

prices and unsalvaged timber. Consumers however had gains from salvage 

wood and the ability to stock salvaged 

timber* From a broader perspective, 

some of the losses to the timber sector 

may have been offset by gains in other 

parts of the state economy, e.g., home 

construction. 

ACKNO'tdZEDGmNTS 

The authors wish to thank Bill Smith, 

North Carolina State University; David 

Kelly, Florida Division of Forestry; 

and John Mills, USW Pacific Northwest 
Forest Experiment Station, for their 

support on ATLAS modeling, 

Abt, ROC.; Pacheco, Go; 

1993, The subregional t 

model. Unpublished manuscript. North 

Carolina State Univ. 

Abt, ROC, 1989. A "top-down" approach 

to modeling state forest growth, 

removals, and inventory, For. Prod. J. 

39(1):71-76. 

Adams, Darius M.; Haynes, Richard W.; 

Darr, David Ro 1977. A Welfare Analysis of Long Term Forest Products Price 

Stabilization. Amer, J. Agric. Econ. 

NOV. 1977. pp. 662-673. 

Alexander, Susan J, 1991, Sensitivity 

of TRIM Projections to Management, 

Harvest, Yield, and Stocking Adjustment Assumptions, USDA For. Serv., 

Pacific Northwest Res. Sta., Res. Note 

PNW-RN-502. 

Alig, Ralph J.; Lewis, Bernard J.; 

Morris, Paul A, 1984. Aggregate timber 

supply analysis. USDA For. Serv., 

Rocky Mountain For. and Range Exp. 

Sta., Gen. Tech. Report RM-106. 

Alig, R,J. 1985. Modeling acreage 

changes in forest ownerships and cover 

types in the Southeast. Res. Pap, 

RM-260, USDA For. Serv. Rocky Mountain 

For. and Range Exp. Sta. 

Brooks, David Je 1987. SPATS: A model 

for projecting softwood timber inventories in the Southern United States. 

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Res. Sta., Res. Paper PNW-RP-385, 

Graver, G,C. 1979, Forest statistics 

for the northern coastal plain of 

South Carolina, 1978, USDA For, Serv., 

Southeastern For. Exp. Sta,, Res. 

Bull* SE-47, 

Cubbage, Fred; Harris, Thomas; Alig, 

Ralph; and others, Projecting State 

and Substate T nventories: The 

Georgia Region er Supply Model. 

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of Georgia Agricultural Experiment 

Station, Athens, GA. 

Davenport, E.Le; Tansey, J-B, 1990. 

Changes in South Carolina" industrial 

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Far, Serve, Southeastern For, Exp, 

Sta., Res. Bull. SE-115, 

Holmes, Thomas P, 1991a. Price and 

Welfare Effects of Catastrophic Forest 

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Forests in the Southern United States 

(draft ) . 

Just, Richard El; Hueth, Darrefl L,; 

Schmitz, A. 1982, Applied Welfare 

Economics and Public Policy. PrenticeHall, Englewood Cliffs, NJ. 491 pp. 

Marshall, Alfred. 1930. Principles of 

Economics. ~cNillan Press, London. 

Mills, J.R. 1989. TRIM Timber Projections: An Evaluation Based on Forest 

Inventory Measurements, USDA For. 

Serv,, Pacific Northwest Res. Sta., 

Res. Pap, PNW-RP-408. 

Mills, J.R.; Kincaid, J.C. 1991, The 

aggregate timberland assessment system 

--ATLAS: A comprehensive timber projection model. USDA For. Serv., Pacific 

Northwest Res, Sta., Gen. Tech. Rep. 

PNW-GTR-281. 

Montgomery, Albert A,; Robinson, Vernon 

Lo 1988. Georgia's future timber 

supply: an economic outlook. Ga. For, 

Corn., Res, Div,, For. Res. Paper 75. 

Robinson, Vernon L,; Montgomery, Albert 

A, 1978. GASPLU: A Computer model for 

Georgia's future forest. Ga, For, 

Corn., Res, Div,, Report No, 36A. 

Sheffield, R.R.; Hutchison, J. 1979. 

Forest statistics for the southern 

coastal plain of South Carolina, 1978. 

USDA For. Serve, Southeastern For. Exp. 

Sta,, Res, Bull. SE-49. 

Sheffield, R.M.; Thompson, M.T. 1992. 

Hurricane Hugo: Effects on South 

Carolina" forest resource. USDA Fora 

Serv,, Southeastern For. Ewp, Sta., 

Res. Pap, SE-284, 

Snyder, N,L. 1978. Forest statistics 

for the piedgnont of South Carolina, 

1978, USDA For. Serv., Southeastern 

For. Exp. Sta,, Res. Bull. SE-$5, 

Tansey, JIB. 1986. Forest statistics 

for the piedmont of South Carolina, 

1986, USDA For. Ser,, Southeastern For. 

Exp. Sta., Res, Bull. SE-89. 
Tansey, J.B. 1987a. Forest statistics 

for the northern coastal plain of 

South Carolina, 1986. USDA For. Sew., 

South-eastern For. Exp. Sta., Res. 

Bull. SE-91. 

Tansey, J.B. 1987b. Forest statistics 

for the southern coastal plain of 

South Carolina, 1986. USDA For. Sew., 

Southeastern For. Exp. Sta., Res. 

Bull, SE-92* 

Tansey, J.B.; Hutchins, C.C., Jr. 

1988. South CarolinaPs forests. USDA 

For. Sen., Southeastern For. Exp. 

Sta., Res. Bull. SE-103. 

Timber Mart-South, Inc. 1989. Timber 

Mart-South. Highlands, NC: Timber MartSouth, Xnc. 

Timber Hart-South, Inc. 1990. Timber 

Mart-South. Highlands, NC: Timber HartSouth, Inc. 

USDA Forest Service. 1988. The South's 

fourth forest: Alternatives for the 

future. USDA For. Sen., For. Res, Rep. 

24. 

Willig, Robert D. "Consumer Surplus 

Without Apology". American Economic 

Review 66(4):589-97. September 1976, 
THE EFFECT OF HURRICANE HUGO ON TIMBER SUPPLY 

Allan P. Marsinko, Thomas J. Strakn, and Robert G. ~aight' 

XNTRODUCTXON 

Timber damage caused by Hurricane Hugo 

was over $1 billion. Many trees were 

downed and many others suffered in 

terms of quality. A total of 10.3 

billion board feet of sawtimber and 

13.2 million cords of pulpwood were 

damaged, representing a tremendous 

impact on the state's timber supply. 

This article examines the short-term 

effects of this large scale natural 

disaster on the timber supply in the 

state. 

TYPES OF SUPPLY 

Supply is the amounts of a product 

that will be offered to the market at 

various prices. It is the entire 

curve, S, shown in Figure 1. Quantity 

supplied is a specific quantity 

offered to the market at a specific 

price (e.g., Point A, B or C in Figure 

1). The quantity supplied would be 

expected to change as a result of a 

change in price. For example, it 

might move from point A to point B. A 

change in the quantity supplied by 

moving along the curve (from A to B) 

is not a change in supply. Because 

supply is the entire curve S, a change 

in supply is a change in the entire 

curve, such as a shift in location 

from S to Sf. The term "supply 

response" refers to a change in the 

quantity supplied. This can occur as 

a movement along a supply curve (e.g., 

from A to B in Figure l), or it can 

occur along with a shift of the supply 

curve (e.g., from A to C in Figure 1). 

Three types of supply are usually 

identified. The first goes by several 

names that imply a brief time span: 

e.g. very short run (Nicholson 1972), 

Department of Forest Resources, 

Clemson University, Clemson, SC 

29634-1003, USA; USDA Forest Service, 

North Central, Forest Experiment 

Station, St. Paul, MN 55108. 

Price 

0 200 500 800 1100 1400 

Quantity (MMCF) 

Figure 1--Hypothetical pre- and posthurricane supply curves for pine 

timber. 

momentary run (Samuelson 1989), market 

(Worrell 1959)' or stock supply (Duerr 

1993). It consists of the supply of 

stocks on hand, available for more or 

less immediate offering to the market. 

It is the amount of stock in a warehouse or, as in this case, the timber 

ready for market. The second is short 

run supply. This is based on the rate 

of output going into stocks, the rate 

controlled by changing the variable 

inputs in the short run (e.g. increasing the intensity of management). In 

the short run, factory size and technology do not vary. Last is long run 

supply. It is based on changing the 

rate of output by changing most or all 

inputs. In this case, factories, technology, and the number of producers can 

change. This paper focuses on the very 

short run supply, the effects of which 

are now apparent. This paper has been 

extracted and condensed from a detailed 

discussion of the three types of supply 

which has been submitted to a journal. 
Hurricane Hugo's Effect on the 

Very Short Run Supply of South 

Carolina Tiarl>er 

Although there are some indications 

that Hurricane Hugo caused a situation 

which illustrates "textbook economics," there are several factors 

which do not fit the standard models. 

Generally, a perfect market is assumed 

in which buyers and sellers have 

complete knowledge of the market. 

But, after a disaster such as this, 

knowledge of the pre-disaster market 

is no longer valid and confusion 

reigns. In a perfect market, market 

price adjusts instantaneously. Immediately after Hurricane Hugo, it 

was hoped that prices would remain 

near their pre-hurricane levels, and, 

in the days immediately following the 

hurricane some landowners received 

higher prices for their wood than did 

those who sold later. A few others, 

however, panicked and gave their 

timber to loggers in order to get 

their land cleared. Both buyers and 

sellers found themselves in a unique 

situation, never before having 

witnessed this type of loss. 

Uncertainty was heightened by 

conflicting reports about the time 

available to salvage the wood, which 

has the effect of temporarily dividing 

the market into relatively small local 

entities, each with its own set of 

"knowledge." 

Supply responses are generally considered to be the results of decisions 

made by producers based on their predictions of future market conditions. 

A producer will make a positive supply 

response (offer more standing timber 

to the market) if he believes that he 

can get a higher price now than in the 

not-too-distant future. He acts in 

such a way as to take advantage of 

what he believes to be temporarily 

higher prices. This type of supply decision is usually a decision of 

whether or not to cut. The decision 

is tempered by longer term market 

perceptions because it takes a long 

time to replenish the stock of standing timber. In this case, Hurricane 

Hugo made the decision or, at least, 

changed the decision framework. By 

virtue of damaging the timber and 

making it potentially worthless in the 

future, Hurricane Hugo increased the 

tirnber available to the market a t a l l 

prices. The result is a positive 

supply response; not the type that 

moves from A to B in Figure 1; but the 

type that moves from B to C. It 

shifted the supply curve to the 

right.' The quantity of pine timber 

normally available to the market from 

the hurricane d 

216,339,000 cubic feet (Tansey 1987). 

After Hurricane Hugo, the quantity 

available was increased to about 1.4 

billion cubic feet, 6.5 times the 

normal harvest in the affected 

counties. Figure 1 approximates the 

magnitude of the supply response for 

pine. The pre-hurricane curve i% ahom 

by S and the post-hurricane curve is 

shown by SF. Although the actual 

shapes and slopes of the supply curves 

are not known, the post-hurricane curve 

is probably less responsive to price 

(less elastic) and is drawn to reflect 

this assumption. 

When the supply curve shifts to the 

right as has occurred here and the 

shift is not accompanied by a corresponding shift of the demand curve (an 

increase in demand), prices can be 

expected to fall. This is what happened after Hurricane Hugo. Prices 

were higher just after the hurricane 

than later probably because of the lack 

of knowledge in the market. The market 

did adjust prices, however, to posthurricane averages 20 to 50 percent of 

their pre-hurricane levels. Although 

the exact shape and slope of the demand 

curve is not known, it is probably 

reasonably close to the curve (D) shown 

in Figure 2. It is possible that 

demand decreased which means the demand 

curve also shifted (to the left in this 

case). However, most mills were back 

in operation soon after the hurricane. 

If the demand curve did shift, then the 

true demand curve is not as steep as 

the one drawn in Figure 2. 

The preceding example grouped pine 

pulpwood and sawtimber into a single 

product, pine timber. Table I breaks 

down the sawtimber and pulpwood and 

compares average annual removals to 

quantities damaged by Hurricane Hugo. 

Although it would be better to analyze 

the supply of pulpwood or sawtimber 

individually, the nature of the damage precludes this. Table I indicates that 

* An argument can be made that 

Hurricane Hugo changed the product from 

standing timber to cut timber. 

However, since the very short run 

supply decision is whether or not to 

cut, the analysis should still be 

valid. The difference is that, under 

normal circumstances, the decision 

maker can rescind if the market becomes 

unfavorable; in this case, he can't. 
Price 

P 

.4P 

Quantity (MMCF) 

Figure 2--Hypothetical pre- and posthurricane stock supply curves for pine 

with demand curve. 

Table I--Comparison of average annual 

removals in the hurricane damaged area 

to hurricane damaged volumes of pine 

sawtimber and pulpwood. 

Average Change 

Annual Hurricane ( Damaqed 

Removals' ~amaged' Removals ) l- I 

Sawtimber 842,215 6,318,892 7.5 

( MBF 

PU~~WOO~ 90,635 459,796 5.1 

f MCF) 

Based on forest survey (Tansey 1987) and S.C. 

Forestry Cormnission conversion factor of 6.7 BF 

international rule/cubic foot. 

Classified before Hurricane Hugo. After 

Hurricane Hugo, much sawtimber was not usable as sawtimber. 

6,318,892 MBF or 7.5 times the normal 

annual removals of sawtimber was 

damaged. This timber was sawtimber 

before the hurricane struck. After 

the hurricane, much of this wood could 

not be used as sawtimber. Instead, it 

became pulpwood. Exactly how much was 

no longer sawtimber is not known. 

Therefore, all that can be said is 

that a supply response occurred and 

the quantity of pine sawtimber available to the market increased by a 

factor less than 7.5 and that the 

quantity of pine pulpwood available to 

the market increased by a factor 

greater than 5.1. The exact magnitudes of these supply responses are 

not known. 

Stumpage prices before and shortly 

after the hurricane are shown in 

Table 11. These prices are taken from 

r Mart South (1989) and reflect 

1 fluctuations, prices for undamand prices for hurricane 

r. Therefore, the postces shown are probably 

ged timber. They are near 

the upper end of the 20 to 50 percent 

range discussed earlier. Stumpage 

prices also reflect increased logging 

costs. Delivered product prices after 

the hurricane were over 80 percent of 

pre-hurricane prices. 

TABLE 11--Comparison of average pine 

stumpage prices in the hurricane 

damaged area before and after Hurricane 

Hugo. ' 

Average Average 

* Price Price Change 

Before After 

Hurricane ~urricane' [ '- ] 

Sawtimber $175.00 $89.00 

($/MBF) 

Pulpwood 21.50 11.00 

($/Cord) 

'source: Timber Mart South, South Carolina, 

Area 3. 

This "almost textbook* example shows 

that the very short run supply curve 

shifted, the market was flooded, and 

the price fell. Pressure to sell 

before the wood deteriorated lowered 

reservation prices and made the posthurricane supply curve relatively 

unresponsive to price. Not all of the 

wood was salvaged because logging and 

mill capacity were not sufficient and 

because most loggers were forced to 

take a technological step backward to 

chain saws in order to harvest fallen 

trees. 

LITERATURE CITED 

Duerr, W.A. 1993. Forestry Economics as 

Problem Solving. McGraw-Hill. New York. 

485 p. 

Nicholson, W. 1972. Microeconomic 

theory-basic principles and extensions. 

The Dryden Press, Incorporation. 

Hinsdale, Ill. 557 p. 

Samuelson, P.A.; Nordhaus, W.D. 1989. 

Economics. McGraw Hill. New York. 

1013 p. 
Tansey, JOB. 1987, Forest statistics Worrell, A,C, 1959, Economics of 

for South Carolina, 1986. USDA Forest American forestry, John Uiley & Sons, 

Service Resource Bulletin SE-93, 53 p, Incorporation, New York, 441 p, 

Timber Mart-South, 1989, T 

South, 4th Quarter 1989, Highlands, 

N,C, Val. 14, No, 4. 
THE TIMBER SITUATION IN SOUTH CAROLINA'S NORTHERN 

COASTAL PLAIN THREE YEARS AFTER HUGO' 

Berbert A. Knight and Stephen K. ~odine' 

Abstract--A new forest survey of the Northern Coastal Plain 

(Forest Survey Unit 2) of South Carolina, conducted in 

1992, measured a 27-percent reduction in pine growing 

stock, a 16-percent reduction in cypress, and a 13-percent 

reduction in hardwood, Most of these reductions are 

attributed to Hurricane Hugo, which demolished much of the 

Region's forests on the night of September 21, 1989. A 

more significant dimension of the inventory reductions was 

the loss of large trees, particularly pine sawtimber. 

Inventory of pine sawtimber was down by 1/3. There is 

evidence a recovery is underway. The new survey measured 

more than 1.0 million acres of pine stands 10 years and 

younger. Many of these young pine stands had already been 

established prior to the storm, through the Conservation 

Reserve Program and other regeneration efforts. These 

young pine stands were not seriously affected by Hugo. 

They will provide thinning opportunities for pulpwood 

within the next PO to 15 years, but it will be 30 years or 

longer before they can replace the pine sawtimber stands 

destroyed. In the meantime, mills producing solid-wood 

products will be drawing supplies from a greatly diminished 

resource. 

INTRODUCTION survey conducted in 1992, about three 

Today, we meet to assess the timber years after Hurricane Hugo demolished 

situation in the Northern Coastal much of the Region's forests on the 

Plain (Forest Survey Unit 2) of South night of September 21, 1989. This 

Carolina. This assessment is based on storm was perhaps the greatest forest 

statistics developed in a new forest disaster in South Carolina's history 

(Sheffield and Thompson 1992). 

Presented at a forestry conference 

in Columbia, South Carolina on April 

28, 1993. This conference was jointly 

sponsored by the south Carolina 

Forestry Commission and the U,S. 

Forest Service's Southeastern Forest 

Experiment Station. 

Herbert A. Knight, formerly the 

principal forest resource analyst in 

the Southeast with the USDA, Forest 

Service, is a forestry consultant in 

Asheville, N.C., specializing in 

timber resource analysis, He wrote 

and presented this paper. Stephen K. 

Nodine is Instructor and Extension 

Forester, Clemson University 

Department of Forest Resources, 

Clemson, See. He edited the text and 

figures for this publication. 

While our attention will focus on 

damage to the forests and evidence of 

their recovery, we should not forget 

the loss of life and property associated with this storm outside the 

forests. Overall losses and damages 

were severe and extended well beyond 

the area we are going to be looking at 

in this meeting. 

The greatest destruction of forests did 

occur in this Unit, where the storm 

damaged more than 90 percent of the 

timberland in some counties. The new 

survey measured a 27-percent reduction 

in pine growing stock, a 16-percent 

reduction in cypress and a 13-percent 

reduction in hardwood. Most of these 

reductions are attributed to Hugo. 
A more significant dimension of the 

inventory reductions was the loss of 

large trees, particularly pine sawthis Unit, inventory of 

er was down by one third. 

Hugo could not have chosen another 

area in the Southeast where it could 

have done more d ge to pine sawtimber. For example, in conducting 

the periodic forest surveys, the U.S. 

Forest Service divides the five southeastern states into 21 Survey Units. 

Prior to this storm, Unit 2 contained 

the largest concentration of pine 

sawtimber, in terms of volume per acre 

of timberland, in these 21 Units. The 

Unit now ranks 20th. 

Prior to the storm, Berkeley County, 

South Carolina, alone contained more 

than two billion board feet of pine 

sawtimber, the largest inventory of 

the 472 counties in the Southeast. 

This latest survey shows 2/3 of the 

pine sawtimber that was in Berkeley 

County is gone, 

Finally, prior to the storm, the 

Francis Marion National Forest in Unit 

2 contained almost 15 percent of all 

the pine sawtimber on national forests 

in the Southeast. This latest survey 

shows 3/4 of this pine sawtimber is 

gone. The Francis Marion now contains 

less than 5 percent of the pine sawtimber on national forests in the 

Southeast. 

Fortunately, all the statistics are 

not negative, and there is evidence 

the recovery is already well underway. 

For example, the new stand-age distributions show more than one million 

acres of pine stands 10 years and 

younger (Table 1). This measure is 

almost double the acreage of pine in 

this age class in the 1986 survey. 

As I will confim with statistics 

later in this presentation, many of 

these young pine stands had already 

been established prior to the stom 

through the Conservation Reserve 

Program (CRP) and other regeneration 

efforts. These young pine stands were 

not seriously affected by Hugo, 

Because of the big increase in pine 

sapling stands, n er of 2-inch pine 

trees almost doubled over the 6-year 

rmeasurement period (Table 2). 

Fortunately, this large concentration 

of young pine stands will provide 

thinning opportunities for pulpwood 

within the next 10 to 15 years. The 

big problem is it will be another 30 

years or longer before these young 

stands can replace the pine sawt 

stands destroyed by Wugo. 

In the meantbe, mills producing 

and other solid-wood products in this 

region are going to be drawing t 

supplies from a greatly diminished 

resource. 

After this lengthy introduction, I will 

move on to a more orderly assessment of 

the timber resources. I would like to 

(1) call attention to some of the longterm trends, (2) measure the impact of 

Wugo on these trends, and (3) conclude 

with a few remarks about the prospective outlook for timber supplies from 

this region over the next several 

decades, 

RESOURCE T-NDS 

Seven regularly-scheduled surveys of 

the forest resources in the Northern 

Coastal Plain of South Carolina have 

been conducted since 1936. Results 

from these seven surveys document 56 

years of the Region's forestry history. 

In addition, there was an interim 

survey following Hugo, and perhaps 

other partial surveys of the Unit over 

the years, 

Timberland 

About 65 percent of all land in Unit 2 

is forest land, and 98 percent of this 

forest land qualifies as timberland. 

In contrast to many other areas of the 

Southeast, area of timberland in Unit 2 

has remained relatively stable at 

around 4.7 million acres over the past 

50 years. 

Seemingly, the CRP reversed a slight 

downward trend in timberland in the mid 

1980's. Because of the establishment 

of pine trees on land previously used 

for agriculture, area of timberland 

increased by more than 140,000 acres 

between 1986 and 1992. Over this same 

period, area in cropland and pasture 

declined by more than 230,000 acres. 

Between 1978 and 1986, the annual rate 

of pine regeneration on nonforest land 

averaged only 7,000 acres. Between 

1986 and 1992, this rate jmped to 

23,000 acres. Hugo did not affect the 

total amount of timberland. 

Forest Type 

In our discussions of forest type, pine 

forest type includes all stands where 

pines account for 25 percent or more of 

the live-tree stocking. The oak-pine 

stands are included with the pine. 
Table P--Area of t errand, by stand-age and broad management elasses, all 

ownerships, Northern Coastal Plain of South Carolina, 1992, 

Stand-age class 

(years 1 

abz 

classes plantation pine oak-pine hardwood hardwood 

0-10 

11-20 

2 1-38 

3 1-4 0 

4 1-50 

51-50 

61-70 

71-80 

81+ 

No manageable stand 

.................................... Acres .................................... 

NCYTEI From Table 13, page 22 of Shedfield and Thompson, 1992, 

er sf live trees on tiderland, by species and diameter class, 

Northern Coastal Plain of South Carolina, 1992, 

WII 8~36@ies aiesess 2.9 4.9 6.9 8.9 10.9 12.9 14.9 16,8 18-9 20.9 18.8 Larger 

............................................. Thousand trees ................................................. 

Soft 

Wag Be sf pine Slash pine Sharkleaf pins 

ZsbloLLy pins Bond pins 

Sprwe pine Bsldcwrersa 

Pondcmress 

Cedar ta 

37,530 12,208 

35,146 9,039 

7,600 2,820 731,309 393,297 

36,090 14,465 

1,184 1,088 

19,429 5,861 

PO, 894 3,801 

9,178 5,066 

Total soft 888,360 447,625 186,836 110,203 62,578 93,555 20,834 12,178 7,004 3,876 1,839 1,580 96 

Select xed sakm Ot\er whit* oaks Other red oaks 

Hickory 

Hard maple soft maple Beech 

sweew 

YaLlw-pplm 

Bay and magnolia Black cherry B%sek walnut. Sycamore 

Black Locust Kb 

Other eaetatn hardwi 

-- 

Ail spaeeirm 3,250,361 2,894,113 563,983 257,985 144,566 78,602 47,969 31,958 11,296 9,860 5,357 5,256 609 

NOTI: From Table %2# pages 33 of Sheffield and Thompson, 1492, 
Between 1940 and 1960, area in pine 

type declined about 14 percent as 

hardwoods replaced pines on about 

400,000 acres. Between 1960 and 1985, 

area in pine type r 

stable at around 2.5 million acres. 

Since 1985, area of pine has increased 

about 5 percent. Again, most of this 

recent increase can probably be 

attributed to pine planting under the 

CRP . 

Within the pine type, the big change 

has been the shift from natural to 

planted stands. Since 1940, area in 

natural pine has decreased from 2.9 to 

1.7 million acres, or by 40 percent. 

Wer this same period, almost one 

million acres of pine plantations have 

accumulated. Plantations now account 

for about 1/2 of all pine stands 30 

years and younger. Between 1978 and 

1986, pine plantations were estabished at an average annual rate of 

33,000 acres. Between 1986 and 1992, 

pine plantations were established at 

the rate of 59,000 acres per year. 

Both the CRP and Hugo contributed to 

this recent increase. 

Total area in hardwood forest type has 

remained fairly stable at around 2.1 

million acres, with the only variations being an increase back in the 

1940s and some decline since 1980. 

Ownership 

Figure 1 shows the trends in timberland, by ownership. Currently, 

nonindustrial private forest (NIPF) 

owners control 21'3 of the timberland, 

forest industry 23 percent, and public 

agencies 10 percent. 

Over the past 30 years, the most 

significant changes have been in the 

amount of timberland in industry 

ownership. Between 1958 and 1986, 

timberland in industry ownership 

increased by 63 percent to 1.3 million 

acres. Between 1986 and 1992, the 

trend reversed as timberland in 

industry ownership decreased by 15 

percent, down to 1.1 million acres, 

This recent decline in industry 

ownership in Unit 2 seems to be part 

of a regionwide decline across the 

Southeast. This recent decline 

follows several decades of increase. 

Inventory Volume 

Figure 2 shows the trend in softwood 

growing stock. Pines account for 

about 90 percent of this softwood. 

Year 

I I 

0 1 3 4 6 

Million acres 

Figure f--Timberland ownership in the 

northern coastal plain forest survey 

unit in South Carolina, 1950-1992. 

Year 

I T I I I 7 

0 Ob 1 1.6 2 26 3 3.6 4 

Billion cubic feet 

Figure 2--Softwood growing stock in the 

northern coastal plain forest survey 

unit in South Carolina, 1940-1992. 
Most of the remainder is cypress, and 

there is a small amount of cedar, 

Between 1940 and 1960, inventory of 

softwood remained fairly stable at 

about 2,4 billion cubic feet, Between 

1960 and the occurrence of Hugo, the 

inventory increased more than 40 

percent, up to 3.4 billion cubic feet. 

The new survey measured a 26-percent 

drop in softwood inventory, all the 

way down to 2.5 billion cubic feet. 

So three years after Hugo, the inventory of softwood is the smallest it 

has been in 30 years. Without Hugo, 

there would have been little or no 

reduction in softwood inventory, 

Another way to measure the impact of 

the storm is to relate inventory to 

average annual rates of cutting. 

Prior to the storm, the inventory 

contained a 21-year supply of softwood, without any additional growth, 

based on the 1986 rate of cutting, 

The new survey measured a 16-year 

supply based on the 1986 cutting rate, 

and only a 14-year supply based on the 

1992 cutting rate. 

Although you can expect a sharp upturn 

in softwood growth to follow the 

storm, mills within this region will 

be drawing softwood supplies from a 

greatly diminished softwood inventory 

at least through the 1990's. The 

storm's impact on softwood sawtimber 

supplies will extend over a much 

longer period. 

Figure 3 shows the trend in hardwood 

growing stock. For several decades, 

inventory of growing stock in Unit 2 

had been fairly equally divided 

between softwood and hardwood. 

Although its impact was much smaller 

than it was on the softwoods, Hugo 

also took a heavy toll out of the 

hardwood inventory. 

Between 1945 and 1960, inventory of 

hardwood declined about 13 percent, 

down to 2.6 billion cubic feet. 

Between 1960 and Hugo, hardwood 

increased 40 percent, up to 3.6 

billion cubic feet. The new survey 

measured a 13-percent reduction, down 

to 3.1 billion cubic feet. Again, 

without Hugo there would have been 

little or no reduction in hardwood. 

One interesting aspect of the stomfs 

impact on the hardwoods was a significant difference between species 

groups. Gums and other soft-textured 

Year i 

0 0.6 1 1.6 2 2.6 3 3.6 4 

Billion cubic feet 

Figure 3--Hardwood growing stock in the 

northern coastal plain forest survey 

unit in South Carolina, 1940-1992, 

species dominate the hardwood inventory. These soft-textured species 

fared much better than the oaks and 

other hard-textured species. Inventory 

of soft-textured species was down less 

than 10 percent, while inventory of 

hard-textured species was down more 

than 20 percent. Again, this is not 

good news for the producers of solidwood products. 

One reason the hard-textured species 

suffered a greater loss was a difference in tree-size distribution, A 

higher percentage of the hard-textured 

species was in trees over 20 inches in 

diameter. These large trees were 

harder hit than smaller trees. 

Prior to the storm, the inventory contained about a 50-year supply of hardwood, without any additional growth, 

based on the 1986 cutting rate. The 

new survey measured a 42-year supply 

based on the 1986 cutting rate, and a 

36-year supply based on the 1992 

cutting rate. 

While there was less loss of hardwood 

than softwood, the recovery of hardwoods will take longer. First of all, 
it takes more the to grow a new stand 

of hardwoods up to merchantable size. 

Secondly, in contrast to the pine 

situation, the Unit does not have a 

million acres of well-stocked hardwood 

stands already established in the O to 

10-year age class. The cowarable 

figure for hardwood stands is 355,000 

acres. 

Over the past 25 years, periodic 

raeasurements of pe 

plots have provided 

reliable estbates o 

he earlier sunre 

er gro-h were developed from 

incrment borings, 

Figure 4 shows the trend in softwood 

growth since 1940. Between 1940 and 

1978, net annual growth of softwood 

just about doubled, increasing from 96 

to 196 million cubic feet. Between 

1978 and 1986, softwood growth turned 

dow slightly and averaged about 177 

million cubic feet per year. Between 

1986 and 1992, net annual growth of 

softwood averaged only 28 million 

cubic feet because of the high martality associated with Hugo. In fact, 

some counties in this Unit even 

experienced negative net growth over 

this period. 

In the absence of another natural 

catastrophe, softwood growth should 

quickly recover to the pre-Hugo level 

or higher over the next 10 years. As 

mentioned earlier, there are more than 

one million acres of pine seedling and 

sapling stands already established. 

Figure 5 shows the trend in hardwood 

growth, Between 1940 and 1960, net 

annual growth of hardwood remained 

fairly stable in a range between 54 

and 62 million cubic feet. Between 

1960 and 1978, hardwood growth more 

than doubled, reaching 134 million 

cubic feet. Between 1978 and 1986, 

hardwood growth dropped back off to 98 

million cubic feet, Between 1986 and 

1992, hardwood groeh averaged 23 

million cubic feet, because of the 

high moPtality associated with Hugo. 

Because so much of the t 

ment effort in this Unit has been 

directed toward pine, the recovery in 

hardwood growth will be somewhat 

slower than that for softwood. 

Tiasr Removals 

Over the past 25 years, periodic 

rmeasuraents of permanent sample 

0 W) 1QO $643 900 

Million cubic feet 

Figure 4--Net annual groak of softwood growing stock in the northern 

coastal plain forest survey unit in 

South Carolina, 1940-1992. 

Year 

Figure 5--Net annual growth of hardwood 

growing stock in the northern coastal 

plain forest survey unit in South 

Carolina, 1940-1992, 
plots have provided consistent and 

were developed from 

d measurements. In 

this analysis, the rmoval est 

include all man-caused reimoval of 

growing stock from the inventory, not 

just comercia1 logging, 

Figure 6 shows the trend in softwood 

raovals since 1940, Between 1940 and 

1960, softwood raovals averaged 

around 95 to 100 million cubic feet 

per year. Between 1960 and 1986, 

rmovals increased to 160 million 

cubic feet. 

I f I 

0 60 100 1W 200 

Million cubic feet 

Figure 6--Annual rernovals of softwood 

er in the northern coastal plain 

forest survey unit in South Carolina, 

1940-1992. 

Between 1986 and 1992, annual softwood 

remiovals averaged 175 million cubic 

feet, Roughly, 35 percent of the 

softwood destroyed by Hugo was salvaged over about a 9-month period 

following the storm, By mid 1990, 

most of the pine killed by Hugo was no 

longer merchantable for conventional 

products. 

Now 1 would like to make clear that 

the estisnate of softwood removals 

ahom in this chart for 1992 excludea 

the salvage of dead trees, In this 

survey, the salvage of dead trees was 

included with the mortality rather than 

with the removals. Generally, field 

crews are unable to determine whether a 

tree was dead or alive when it was cut. 

Because of the interim survey conducted 

shortly after the storm, crews were 

able to make this determination i n t h i s 

latest survey. 

If the salvaged dead trees had been 

included in the removals rather than in 

the mortality, annual removals of softwood between 1986 and 1992 would have 

averaged 233 million cubic feet rather 

than the 175 million shown in this 

chart. 

Timber products output (TPO) data collected from the mills each year provide 

some insight on how the softwood 

removals fluctuated during the period. 

Keep in mind the salvage operations 

extended over parts of two calendar 

years, 1989 and 1990. The TPO statistics suggest the high was 195 million 

cubic feet, reached in 1989. By 1991, 

softwood output had dropped back to 147 

million, which was almost 20 percent 

below the pre-Hugo level. 

Figure 7 shows the trend in hardwood 

removals since 1940. Between 1945 and 

Year 

Million cubic feet 

Figure 7--Annual removals of hardwood 

timber in the northern coastal plain 

foreat aurvey unit in South Carolina, 

1940-1992. 
1960, there was about a 20-percent 

reduction in the average annual 

reraovals of hardwoods, down to about 

50 million cubic feet, Hardwood 

vals then increased up to about 64 

ion cubic feet, a level it maintained between 1965 and 1980 

1986, annual rernovals had cl 

74 million cubic feet, 

Between 1986 and 1992, annual hardwood 

removals averaged 89 million cubic 

feet. Only an estimated 10 percent of 

the hardwood destroyed by Hugo was 

salvaged, although the salvage period 

was somewhat longer than that for 

pine. 

Again, the est te of hardwood 

removals shown in this chart for 1992 

excludes the salvage of dead trees. 

If the salvaged dead trees had been 

included in the removals rather than 

in the mortality annual removals of 

hardwood between 1986 and 1992 would 

have averaged 94 million cubic feet 

rather than the 87 million shown in 

this chart, 

The hardwood TPO data are well below 

the survey removal measure over the 

period. This kind of difference has 

n across the S~utheast, 

Generally, the TPO data exclude a lot 

of hardwood chipped for export, a lot 

of hardwood fuelwood, and a lot of 

hardwood logging residue. The hardwood TPO data confirm there was a low 

rate of hardwood salvage, but still 

there was a significant reduction in 

hardwood output in 1991 compared to 

the pre-Hugo level. 

CURRENT IWENTORX 

Now that we have looked at some of the 

Unit trends, let us look more closely 

at the current timber inventory. 

Again, we will look at the recent 

changes in some of the key distributions. 

Pine Growing Stock 

Currently, the inventory of pine growing stock totals 2,3 billion cubic 

feet, Sonre 57 percent is on NIPP 

lands, 29 percent is on forest industry holdings, and 14 percent is on 

erland (Table 3). 

A net reduction of 27 percent in pine 

growing stock occurred between 1986 

and 1992. The largest reduction was 

on public land, where the pine inventory was don 40 percent. The largest 

er was on public land, and the 

Francis Marion National Forest took a 

direct hit from Hugo, The next largest change was on NIPF, where the pine 

inventory was down 32 percent, There 

was only a 5-percent reduction on 

industry land, because so much of the 

inventory is in small trees in pine 

plantations. 

Again, the storm d ge was heavily 

sensitive to tree size. Only 28 

percent of pine growing stock is in 

trees 16 inches and larger (Table 4). 

Prior to the stom, 35 percent was in 

trees 16 inches and larger, Figure 8 

ehows the percentage changes by d.b.h, 

between 1986 and 1992. The reductions 

ranged from 3 percent in the 6-inch 

class up to 50 percent for trees 22 

inches and larger. 

Percent change 

Figure 8--Percent change in pine growing stock in the northern coastal plain 

forest survey unit in South Carolina, 

1986-1992, 

Finally, looking at the current distribution of pine by species, loblolly 

pine accounts for more than 314 of the 

total, longleaf pine 10 percent, slash 

pine 6 percent; and pond pine accounts 

for most of the rentainder, 

Hardwood Growing Stock 

Currently, the inventory of hardwood 

growing stock totals 3,1 billion eubie 

feet, which is almost 48 percent 
Table 3--Merchantable volume of live trees and growing stock on timberland, by 

ownership class and species group, Northern Coastal Plain of South Carolina, 1992, 

Live trees Growing stock AIL Other Sof t Hard All. Other Sof t Bard Ownership class species Pine softwood har har species Pine sof har 

---------------------------------------- Thousand cubic feet ............................................. 

rational forest 260,416 91,791 36,740 99,476 32,409 239,079 91,040 35,114 86,519 26,406 

Other public 338,826 221,679 21,337 47,420 48,390 315,866 220,890 21,337 39,290 34,349 

Forest industry 1,536,694 636,640 78,825 601,798 219,431 1,426,111 631,334 76,263 531,930 186,584 

Forest in-try-leased 31,340 20,539 1,417 4,716 4,668 29,913 20,539 1,417 4,352 3,605 

Other private 3,969,335 1,304,667 130,104 1,652,244 882,320 3,639,482 1,293,828 123,771 1,468,449 753,434 

All mershipe 6,136,611 2,275,316 268,423 2,405,654 1,187,218 5,650,451 2,257,631 257,902 2,130,540 1,004,378 

llOTE: Fraa Table 27, page 31 of Sheffield and 

Table 4--Merchantable volume of live trees on timberland, by species and diameter 

class, Northern Coastal Plain of South Carolina, 1992. 

All 

Spaaies classes 6.9 8.9 10.9 12.9 14.9 16.9 18.9 20.9 28.9 larger 

S0f twood 

Longleaf pine 

Slash pine 

Short leaf pine 

Loblolly pine 

Pond pind 

Spruce pine Ba ldc ypr e ss Pondcypress 

Cedars 

.------------------------ Thousand trees 

Total softwoods 2,543,739 267,877 371,727 388,003 394,095 340,291 275,176 210,224 123,408 157,108 15,830 

xudwood Select whito oaks Select red oaks Other white oaks Other red oaks niakory 

Bard naple Soft maple Beech 

Swoetgtma 

Tupelo and black- Aah 

Cottonwood 

Basclwaxi 

Ye llov-poplar 

Bay and magnolia Black cherry Blwk walnut Sycamore 

Klrs 

Other eastern hardwoods 

Total hardwoods 3,592,872 394,084 483,675 496,469 470,713 506,772 367,987 267,796 208,972 313,244 83,160 

All species 6,136,611 661,961 855,402 884,472 864,808 847,063 643,163 478,020 332,380 470,352 98,990 

llm: From Table 34, page 35 of Sheffield and Thompeon, 1992. 
greater than the inventory of pine. 

Before the storm, inventory of 

hardwood exceeded the inventory of 

pine by only 16 percent. Almost 71 

percent is on NIPF, 23 percent is on 

industry, and only 6 percent is on 

public holdings, 

Hardwood growing stock showed an overall 13 percent reduction between 1986 

and 1992. Again, the largest reduction, 19 percent, was on public land* 

Both NIPF and industry suffered 

13-percent reductions. 

Table 4 shows the current distribution 

of hardwood growing stock, by d.b.h. 

class. The largest mount is in the 

14-inch elass, More than 35 percent 

is in trees I6 inches and larger. 

Figure 9 shows the percentage change 

by d,b.h, between 1986 and 1992, As 

with the pines, the larger trees 

suffered the greatest reductions. 

Reductions ranged from I percent for 

LO-inch trees up to 36 percent for 

trees 22 inches and larger. 

Figure 9--Percent change in hardwood 

growing stock in the northern coastal 

plain forest sumey unit in South 

Carolina, 1386-1992, 

When considering the current distributian of hardwoad by species groups, 

dodnate and account for ahost 

112 of the total. Oaks account for 114 

of the dotal, Before the stom, oaks 

accounted for ahosL 30 percent. 

STmIS-AGE DISTRZBUllffONS 

Distributions of er stands, by age 

class, by forest , probably provxde 

some of the best uses of current 

and prospective t r supplies in the 

Unit, Stand-age ributions reflect 

past rates 02' harvesting and 

regeneration, and identify pr 

deficiencies in the flow of t 

supplies. As you will see, Hugo significantly altered the age distribut ion, 

Pine Stanads 

Figure 18 shows the age distribution of 

the 2.5 million acres in pine and oakpine type as of 1986, divided into 

planted and natural stands. Keep in 

mind, this distribution was prisr ta 

Hugo, Some 304,080 acres included with 

these pine stands were so poorly 

stocked, a manageable stand did not 

exist. These acres show up in the 

0-0-age class, Some 0% those were 

recently hamested acres not regenerated. 

Figure 10--Age distribution sf pine 

stands in the northern coastal plain 

forest survey unit in South Carolina, 

by stand type, 1986, 
This distribution shows a large concentration of pine stands 10 years and 

younger, and then a fairly even distribution of age classes up through 

age 50. About 30 percent of the 

manageable stands were more than 40 

years old, tjhich was slightly above 

the Southeast average, Most of the 

700,000 acres of pine plantations were 

under 30 years of age. 

Figure 11 shows the age distribution 

of the 2.7 million aeres of pine 

stands in 1992, some 3 years after 

Hugo. We still have about 290,000 

poorly-stocked acres in the 0-0-age 

class, but the manageable stands are 

now heavily skewed toward the younger 

age elasses. 

Figure 11--Age distribution of pine 

stands in the northern coastal plain 

forest survey unit in South Carolina, 

by stand type, 1992, 

Because of the GRP, other regeneration 

efforts, and Hugo mre than one million aeres have accmulated in the 

0-10-year age c%a%s, There have been 

significant reductions in stands over 

20 years old, Less than 20 percent of 

the manageable stands are mre than 40 

years old, which is well below &Ae 

Southeast average, 

As promised earlier, I would like to 

confim that many of the pine stands in 

the youngest age class, 0-10, had 

already been established prior to the 

stonn. Figure 12 shows breakdowns of 

pine stands 12 years and younger into 

3-year classes as of 1986, and as of 

1992, The chart shows 213 of the pine 

stands in the 0-10-year class in 1992 

were established between 1983 and 1988, 

or prior to the stom. 

Figure 13 shows the changes in the age 

distribution of pine stands in this 

Unit between 1986 and 2992, As you can 

see, Hurricane Hugo really took a heavy 

toll out of the 20-to-60-year old 

stands. Over this 6-year period, these 

age classes supplied more than 3/4 of 

the pine harvest* 

Tbe current age distributions promise 

no significant recovery in these age 

classes over the next 10 years* In 

fact, it will be at least 20 years 

before there is any significant 

recovery in pine stands older than 30 

years. In the meantime, mills 

producing solid-wood pine products are 

going to be drawing timber supplies 

from a greatly diminished resource in 

this unitB 

Hardwoad Stands 

Figure 14 shows the age distribution of 

the 2,l million acres in hardwood type 

as of 1986, Again, this distribution 

was prior to Hugo. Some 513,000 acres, 

or 1/44 sf the total, were poorly 

stocked and show up in the 0-0-age 

class. This distribution indicates 

deficiencies in well-stocked hardwood 

stands between II and 40 years sf age. 

These deficiencies can be traced back 

to low rates of hardwood harvesting and 

regeneration between 1945 and 1975. 

Ahut 68 percent of the manageabbe 

stands were more than 40 years old, 

Figure 14 also shows &he age 

distribution of the 2,P million acres 

in hardmod type as of 1992, We now 

have almost 550,008 acres that are 

poorly stocked, There was a 45-percent 

increase in hardwood stands 10 years 

and younger, and a smaller increase in 

ll-to-26-year stands, The deficiency 

in bl-do-40-year stands in I986 has now 

extended into the 41-to-50-year class, 

About 54 percent sf the manageable 

stands are over 40 years old, 

Figure 15 shows the changes in the age 

distribution sf hardwood stands between 

1986 and 1992e 
=

Thousand acres 

Stand-age class Stand-age class 

1- t]Ndl*l 

Figure 12--Age distribution of pine stands 12 years of age and younger in the 

northern coastal plain forest survey unit in South Carolina, by stand type, 1986 

and 1992. 

Thousand acres 

508 

Age class 

Figure 13--Changes in the age distribution in pine stands in the northern coastal 

plain forest survey unit in South Carolina, by stand type, from 1986 to 1992. 
nousand acres 

do0 

-. 

0.10 21-30 41-60 61-70 81 + 

Age class 

Thousand acres 

606 

0.10 21- 41-60 61-70 81+ 

Age class 

Figure 14--Age distribution of hardwood stands in the northern coastal plain forest 

survey unit in South Carolina, 1986 and 1992. 

Thousand acres 

150 

Age class 

Figure 15--Changes in the age distribution in hardwood stands in the northern 

coastal plain forest survey unit in South Carolina, from 1986 to 1992. 
PROSPIECTZVIE OUm001C 

I would like to conclude with a few 

about the prospective outlook 

er supplies in Unit 2. First, 

I would like to focus on the outlook 

for pine, and then look at the prospective hardwood future, 

Pine Outlook 

I do not envision any serious deficiencies in pine pulpwood supplies in 

Unit 2, The large concentration of 

some 1.0 million acres of pine stands 

10 years and younger will greatly 

boost thinning opportunities within 

the next 10 to 15 years. In the 

meantime, an additional 1.0 million 

acres of pine stands over 20 years 

old, in the current inventory, can 

supply the recent rates of pine 

harvest, 

The main concern in this Unit, and for 

the Southeast as a whole, is the prospective outlook for pine sawtimber. 

Because of uncertainty surrounding 

prospective supplies of softwood 

sawtimber in the western US, some 

resource analysts believe the South 

will have to supply a greater share of 

the solid-wood demand in the near 

future. 

While the overall inventory of pine 

growing stock across the Southeast 

declined slightly between the 5th and 

6th forest surveys, inventory of pine 

sawtimber showed little change. 

Increases in North Carolina and 

Virginia offset small decreases in 

Florida and Georgia, while the inventory of pine sawtimber in South 

Carolina remained about the same 

between 1978 and 1986. Hurricane Hugo 

alone reduced the inventory of pine 

sawtimber in the Southeast by 3 

percent or more in just a matter of 

hours. 

Unit 2 provides the earliest results 

from the 7th survey of the forests in 

the Southeast. As stated earlier, 

inventory of pine sawtimber is down by 

113, primarily because of the storm. 

Unit 2 still contains 1.5 billion 

cubic feet of pine sawt 

great potential for recovery, 

In my opinion, it will require at 

least 40-year rotations of pine stands 

to replenish the size and quality of 

shed in the 

stormo Although er growth potential varies by site, and management 

objectives vary by ownership, let us 

assume these 2.7 million acres of pine 

in Unit 2 are going to be mnaged on 

40-year rotations, on the average. 

Some will be shorter; others will be 

longer This asswed raanagement 

strategy would call for 66,500 acres to 

be harvested and regenerated each year, 

Bettseen 1978 and 1986, pine stands were 

harvested in Unit 2 at an average rate 

of 67,900 acres per year (Figure 16). 

Between 1986 and 1992, pine stands were 

harvested at a rate of 84,200 acres, 

but this rate was inflated by the Hugo 

harvest. These recent rates of pine 

harvest confim that the assumed cutting rate is a reasonable estimate for 

supplying recant d 

Period (vears) 

Thousand acreslyear 

Figure 16--Measured and projected 

sustainable annual rate of harvest of 

pine stands in the northern coastal 

plain forest survey unit in South 

Carolina, 1978-2032, 

At the assumed cutting rate of 66,500 

acres per year, Unit 2 had a 7-year 

supply of pine stands 40 years and 

older, as of 1992. These remaining 

older stands would satisfy the harvest 

assumption out through year 1999. The 

1992 age distribution also contained 

the large concentration of 0-10-year 

old pine stands that would start to 

feed into the harvest age in 2022. We 

have now confined any pine supply 

deficiencies into a 22-year period 

between 2000 and 2021. 
The 1992 age distribution indicates 

Unit 2 would only be able to sustain a 

hamest rate of 41,000 acres per year 

of 40-year old pine stands over this 

22-year period, By shortening the 

rotation on some 350,000 surplus acres 

now in the 0-10-year class, the annual 

harvesting rate could be pushed up to 

about 57,000 acres. 

Without some increase in average 

yield, these statistics suggest a 

15-percent shortfall in pine sawt 

supplies each year over this period 

between 2000 and 2022. While all of 

this prospective shortfall cannot be 

attributed to Hugo, the storm certainly hastened the shortfall's onset 

and extended its duration. 

Because of a backlog of some 300,000 

acres of pine regeneration need, the 

annual rate of pine regeneration over 

the next 40 years would need to 

average about 74,000 acres. Figure 17 

compares this rate with recent past 

rates. Between 1978 and 1986, pine 

regeneration in Unit 2 averaged 64,500 

acres per year. Between 1986 and 

1992, the average was about l26,OOO 

acres. This latter rate included more 

than 23,000 acres per year on 

nonforest, 

Hardwood Outlook 

Finally, let us try and assess the 

prospective outlook for hardwood 

timber supplies. While the Southeast 

is often perceived as primarily a pine 

timber region, hardwoods account for 

57 percent of the growing stock across 

the 5-State Region. Here in Unit 2, 

hardwoods account for 55 percent of 

total growing stock. 

After several decades of custodial 

management, low usage, and increasing 

inventories of hardwood timber across 

the Southeast, recent forest surveys 

are measuring some significant changes 

in this resource. Between the 5th and 

6th surveys inventory of hardwood 

growing stock in the Southeast 

increased about 6 percent, which was a 

significant slowdown from the earlier 

trend, Most all of this recent 

increase was in large trees. Inventory of hardwood pulpwood actually 

declined about 5 percent. Indications 

are that the longtime buildup in 

hardwood inventory in the Southeast is 

coming to an end. 

Between the 5th and 6th surveys, 

annual cut of hardwoods increased 

about 30 percent while hardwood growth 

0 20 410 0 80 100 120 140 

Thousand acreslyear 

Figure 17--Measured and projected pine 

regeneration rates in the northern 

coastal plain forest survey unit in 

South Carolina, 1978-2032. 

declined about 12 percent. Much of 

this recent increase in hardwood cut 

can be attributed to increased chip 

production. Much of the recent decline 

in hardwood growth can be attributed to 

an aging resource with high mortality. 

After several decades of low harvesting 

and regeneration, there is a deficiency 

in well-stocked hardwood stands between 

10 and 40 years old, and a large accumulation of mediocre hardwood stands 50 

years and older. One of the problems 

with this resource is that many of the 

older stands are on wet sites, steep 

slopes, or public holdings and may not 

be readily available for timber production. 

Now, let us focus on the prospective 

outlook for hardwood supplies from Unit 

2. As with the pine, I would like to 

start with a theoretical management 

strategy for the 2.1 million acres of 

hardwood type in the 1992 inventory. 

Here, I would like to assume an average 

rotation of 60 years. Again, some will 

be shorter; others will be longer. 

This assumed management strategy would 

call for 34,300 acres to be harvested 

and regenerated each year (Figure 18). 
Period (years) 

Figure 18--Measured and projected 

sustainable annual rate of harvest of 

hardwood stands in the northern 

coastal plain forest survey unit in 

South Carolina, 1978-2032. 

Between 1978 and 1986, hardwood stands 

were harvested in Unit 2 at an average 

rate of 28,300 acres per year. 

Between 1986 and 1992, hardwood stands 

were harvested at a rate of 32,200 

acres, a rate not significantly 

inflated by Hugo, Again, the assumed 

cutting rate of 34,300 seems reasonable and in line with the recent 

trend , 

If all hardwood stands were available, 

the 1992 age distribution suggests 

they could supply an annual harvest of 

34,300 acres of 60-year and older 

stands for about 28 years, or through 

2020, A fairly large concentration of 

stands in the O-10-year class would 

start to feed the harvest age in 2042. 

We have now confined any hardwood 

supply deficiencies into a 21-year 

period between 2021 and 2041, 

The 1992 age distribution indicates 

Unit 2 would only be able to sustain a 

hasvest rate of 6,000 acres per year 

of 60-year old hardwood stands over 

this 21-year period. Without some 

increase in average yield, a 

significant reduction in poorly-stocked 

stands, or shortened rotations, these 

statistics suggest an 80 percent shortf a l l i n hardwood sawtimber supplies 

over this 21-year period. Most of this 

prospec-tive shortfall is attributed to 

inade-quate hardwood managment practices in the past rather than to Hugo. 

Because of the backlog of nearly 

550,000 acres of hardwood regeneration 

need, the annual rate of hardwood 

regeneration over the next 60 years 

would need to average about 43,500 

acres. Figure 19 compares this rate 

with recent past rates. Between 1978 

and 1986, hardwood regeneration in Unit 

2 averaged 28,800 acres, Between 1986 

and 1992, the average was 50,400 acres. 

Period ( 

Figure 19--Measured and projected 

hardwood regeneration rates in the 

northern coastal plain forest survey 

unit in S~uth Carolina, 1978-2032. 

In this hardwood analysis, we did not 

discount the gross hardwood acreage 

because of adverse sites nor public 

ownership. If we exclude the wet sites 

and public holdings, the prospective 

deficiency could occur as early as 

2012. 

The conclusion is that the prospective 

deficiency in hardwood sawtimber, while 

further out in the future, will be 
considerably greater than the prospec- REFEmMCES 

tive deficiency in pine sawtimber Sheffield, R.M.; Thompson, M.T. 1992. 

supplies. This conclusion is under- Hurricane Hugo: effects on South 

standable, considering the greater Carolina's forest resource. Res. Pap. investment made in pine management SE-284. Asheville, NC, U.S. Department 

over the years. of Agriculture, Forest Service, Southeastern Forest Experiment Station. 

51 PP* 
William E. IQa itt, Robert D. Bixxer, and Theresa A. ~errick' 

astract--Hurricane Hugo struck the central coast of 

South Carolina and the and area with 140 

mph winds on the night er 1989, Over onethird of South Carolina" forest land was devastated, 

Ten counties suffered extensive or moderate forest 

resource damage and 13 counties lesser, bud significant, 

levels of forest damage. Forest-based recreation sites 

and facilities, habitats and settings, and participation 

opportunities were impacted to various degrees on these 

same forest/park lands, The purpose of this report was 

to assess the forest-based recreational impacts in south 

Carolina sf Hurricane Hugo, The hpact assessment was 

limited to the 10=county area most heavily damaged by 

Hugo. Impacts assessed included the type and extent of 

damage to the physical (i,e, structures and facilities), 

biological (i.e. habitat and natural resources), social 

(i-e. accessibility and visitation), and economic (i.e. 

fee receipts and revenue) Sorest recreation resources 

within the study area. Resource managers and ather 

agency personnel of forested lands within the study area 

were surveyed by telephone and letter to inventory the 

impacts and obtain empirical data, when available, 

~N"flfEtOE)UCaC1EO]N 

Hurricane Hugo, which swept through 

South Carolina on SepL 

was the single greatest natural 

disaster ever to strike the state, 

aver one-third of South Ca~alina@s 

forest Land was devastated. Ten 

counties suffered extensive or 

moderate forest damage and thirteen 

counties lesser, but significant, 

levels of forest damage, Loss or 

er was estimated to have 

illion acres of tianSr-lerillion cubic feet sf 

at $1-2 billion (Smith 

Professor, College of Forest and 

Recreation Resources; Graduate 

Research Assistant, Department of 

Parks, Recreation and Tourism 

Managmeat, respectively, 61emssn 

University, Glmson, SC; and Assistant 

Professor, Department of Recreation 

and Park Ahinistsation, Arkansas Tech 

University, Russelville, AR, 

and Smith 19891, The Francis Marion 

National Forest, a 256,000-acre 

multiple-use resource with abundant 

wildlife recreation opportunities, 

hiking trails, and cmping areas, was 

heavily hpacted by Hugo, An estimated 70 percent of the trees above 10 

inches DBH were blom dom or broken 

off in the forest, 

Associated with severe ti~er hpacts 

of Hurricane Hugs were other multipleuse forest resource impacts, particularly forest-based recreation, Hunting, hiking, cmpkng, and picnicking 

often depend on a natural, forested 

setting for a quaLity recreation 

experience, The 1985 South Carolina 

Statewide Comprehensive Outdoor Recreation Plan indicates that 16,3, 15,1, 

14,9, and 65,2 percent of residents 

participate in the four activities, 

respectively- Wrnong state park 

visitors interviewed in the 1985 study, 

the majority reported staying in public 

campgrounds (85-6 percent)- Several sf 
the state parks and their facilities 

ged by Hugo. The same is 

true for the Francis Marion National 

Forest and other agency areas. Forest 

interpretive progrms on Hugo's 

effmts, as well as rehabilitation of 

forest trails, cmpground, and other 

recreational facilities occurred after 

the hurricane on the Francis Marion. 

However, the full extent and type of 

impacts to forest-based recreation 

resources of all agencies is not well 

understood. 

mile the general bpacts of Hugo 

affected many resources and uses of 

Sauth Carslinars forests, the direct 

hpacts are no more obvious and 

visible to the general public than 

during on-site recreation visits to 

these forests. Therefore, the full 

range of Mugo" bpact on forest 

resources can not be evaluated without 

also understanding the forest 

recreation hpacts of Hugo, 

Purpose 

The grhary purpose of this research 

was to assess the fsrest-based 

recreational hpaets in South Carolina 

of Hurricane Hugo, The assessment 

focused on recreational settings, 

facilities, and opportunities directly 

dependent upn forest enviromenls for 

their existence. Impact assessments 

included type and extent sf damage to 

the physical (i.e, structures), 

biological (i.e, resource setting), 

social (i,e. activity participation) 

and economic (i.e, fee receipts) 

forest recreation resources for the 

10-county study area mst affected by 

Hugo. Specific objectives addressed 

in the paper include: (1) the type 

and extent sf dmage caused by 

Hurricane Hugo to forest-based 

recreational facilities, structures, 

habitat settings, and access routes; 

(2) the influence sf Hugo an forestbased reereation activity participation, visitation, and fee receipts in 

special use areas; and (3) the influence sf Hugo on the natural characteristics and quality of forest recreation opportunity settings, 

mTHODS 

Study ArPea 

The hpact assessment was Ihited to 

the 10 South Carolina counties that 

suffered the most extensive or 

moderate levels of forest damage 

(Figure 1). The specific counties 

were Charleston, Berkeley, Dsrchestenr, 

Williamsburg, Clarendon, Smler, Lee, 

Darlington, Florence, and Georgetom. 

Within these counties, forest-based 

reereation agencies (both public and 

private) were surveyed for Hugo related 

hpacts . 

Data Sources 

Se~ondary data provided by foresl-based 

recreation agency personnel served as 

the major source of impact data. An 

inventory of the type of recreational 

bpacts and their extent was genercated 

from the secondary data collected, 

This inventory included physical 

hpacts ta structures and facilflies, 

biological hgacts to recreational 

habitats and settings, social hpacts 

on activity participation and visitation, and economic impacts on fee 

receipts to parks and special use areas 

(i.e campgrounds), Visitation records 

and fee receipts were obtained from 

agencies, when available, 

The influence of Hugo on the natural 

characteristics and related quality of 

forest recreation opportunity settings 

ns delemined by asking recreation 

resource managers to estimate the 

degree of disturbances to various 

natural settings. 

Data Cslleetion Pr~~edure 

An initial list was compiled for 

Porest-based recreation resources in 

the 10-county study area by first 

exmining a South Carolina state map 

and identifying agencies managing 

forest-based recreation resources 

within the identified area, These 

agencies were then contacted by telephone to determine who was responsible 

for compiling statistics on Hurricane 

Hugo dmage, In some of the agencies 

one individual was the main contact* 

In others several agency aployees were 

responsible for tracking hurricane 

gee Sme statistics were reported 

through telephone conversations, Other 

agencies wanted a written letter of 

reques& for infomation with background 

infamation ab~ut the purpose and 

objectives of the study. AIL agencies 

contacted were asked to supply infomation in the following categories: (I) 

attendance and use figures for the site 

12 months to Hurricane Hugo and 

12 months Hurricane Hugo; (2) 

descriptions and snonetary vahe of 

darnage to recreational structures, 

roads and trails used by visitors; (3) 

percentage of tree cover last on the 

forest-based recreation resource due Lo 

the hurricane, including total acres of 

forest cover and percent type of forest 
South Carolina FORESTRY Commission 

Figure 1--Distribution of the counties of South Carolina with forests damaged by 

Hurricane Hugo, 1989. Source: South Carolina Forestry Commission. 
cover lost; (4) changes in wildlife 

species due to the storm, as well as 

any significant changes in habitat; 

and (5) some coments about how long 

the site was inaccessible to visitors 

because of the hurricane and steps 

taken to ameliorate the damage, 

Several comerciah t 

that lease land for hunting in the 

10-county study area were also contacted. A list of these timber 

companies and the individuals who 

supervise hunting leases was provided 

by the South Carolina Forestry Association. Other agencies contacted 

because of their ownership or management of forest-based recreation 

resources in the study area included: 

Francis Beidler Forest (Audubon 

Society) and the South Carolina Public 

Service Authority which leases recreation resources along the lake fronts 

in the 10-county study area. Again, 

information about damage from 

Hurricane Hugo was pro-vided by 

telephone contact or through written 

letter of request following the same 

format as the one used for state and 

federal agencies. In total, 26 

agencies and management areas were 

contacted (Hammitt 1993). 

Data Analysis 

Because of considerable variation, and 

even absence in the type, amount, and 

format of data recorded and provided 

by the various agencies, a comparative 

analysis among the sources was impossible. Therefore, compilation and 

descriptive analysis of the impact 

data furnished by agencies was the 

main means of analysis. The data was 

analyzed and is reported by the four 

impact categories of physical, 

biological, social, and economic 

impacts for the major different types 

of agencies and land units contacted. 

WSn'ICS AND DISCUSSION 

Results indicated that damage to 

physical structures and facilities 

were extensive for the Francis Marion 

National Forest, State Parks and 

National Wildlife Refuges. Damage 

assessments to Forest Service developed sites by Hugo totaled $920,000. 

All developed recreation sites 

received some damage, all trails were 

blocked by down timber, wilderness 

area signs and boundary markings were 

damaged and needed re-establishment, 

and several archeological sites were 

damaged (Table l), Total damage was 

estimated at $2,676,000, State Park 

facilities at the major parks in the 

study area suffered structural and 

debris removal damages totaling 

$390,276. Damage was greatest at 

Givhans Ferry and ~oinsett parks (Table 

2). Cape Romain National Wildlife 

Refuge experienced the most physical 

impact, where t h e v i s i t o r center and 

support office buildings were destroyed 

(estimated at $2,100,000 to rebuild), 

nature trails and bridges extensively 

damaged ($20,000+), and water-retaining 

dikes required repair ($650,000). 

Industrial Forest Lands and State 

Forests contained few to no recreation 

structures, except for some structures 

constructed and maintained by hunting 

clubs . Biological impacts were extensive to 

the forest and wildlife resource/ 

habitats that support wildlife 

recreation opportunities. The U.S. 

Forest Service established that 70 

percent of the sawtimber was down or 

broken by Hugo, and some State Wildlife 

Management Areas lost up to 80 percent 

of the forest cover. The interior of 

Bulls Island (US Fish & Wildlife 

Service) was closed for 1.5 years after 

Hugo. Biological impacts to fish/ 

wildlife habitat and species reduced 

fishing and hunting opportunities for 

recreationists, All hunting was 

canceled at Cape Romain for the 1989 

fall season, Rail hunting re-opened 

for the fall of 1990 and a limited deer 

hunt was planned for 1991, Freshwater 

fishing at Cape Romain had not reopened by fall 1991, but saltwater 

fishing was not affected. At Santee 

Refuge, deer, squirrel, dove, raccoon, 

and opossum hunting was canceled in 

1989. However, the post-Hugo 1990 deer 

harvest on Santee was one of the best, 

showing a 95 percent increase over the 

number of deer taken during the last 

hunts held pre-Hugo in 1988. The U.S, 

Fish & Wildlife Service reported that 

"the cancellation of the 1989 hunts had 

a definite impact on the Santee 

Refuge's deer population" (U.S.D.I. 

1990:34). Several of the State Wildlife Management Areas also reported 

positive impact related to Hugo, with 

increases in certain types of habitats 

and species after Hugo, The Francis 

Beidler National Audubon Forest also 

reported mixed results from Hugo, with 

some songbirds more abundant after 

Hugo, and an increase in open pond habitat for alligator viewing by the 

public. 

Lack of accessibility and damage to 

physical facilities impacted the 
ge Assessment Report for Structure and Facility Impacts Related to 

Hurricane Hugo on the Francis Marion National Forest. 

Initial Actual 

1. Developed Sites 

Buck Hall Campground 

Huger Cmpground 

Canal Day Use Area 

Tarpit Day Use Area 

Guilliard Lake Campground 

Boggy Head Rifle Range 

Honey Hill Hunt Camp 

Elmwood Campground 

McDonnellps Landing 

Twin Ponds Rifle Range 

Half-Way Creek Campground 

Wambaw Trail Head 

Preconstruction/Construction 

Engineering Overhead 

Recreation Planning 

$ 450,000 

70,000 

60,000 

Eliminated 

5,000 

4,000 

11,000 

11,000 

3,500 

1,500 

11,000 

11,000 

80,000 

60,000 

60,000 

Total Developed Sites 

2. Trails (Clearing, Trailheads, 

Signing, and Blazing) 

Swamp Fox Trail 

Wambaw Motorcycle Trail 

Hellhole Bay Canoe Trail 

Wambaw Creek Canoe Trail 

Total Trails 

3. Wilderness (Re-establish 

Boundaries and Signing 

Hellhole Bay 

Wambaw Swamp 

Little Wambaw Swamp 

Wambaw Creek 

N.D. 

N.D. 

N.D. 

N.D. 

Total Wilderness 

4. Special Areas 

Guilliard Lake Scenic Area 

(Re-establish Boundary Markings) 

Sewee Shell Meddon 

Total Special Areas 

5. Cultural/Archeological Resources 

Cultural Resource Inventory 

Cultural Resource Evaluations 

Cultural Resource Treatment 

N.D. 

N.D. 

N.D. 

Total Cultural Resources 
Table 1 (continued) 

Initial 

Estimate 

Actual 

Estimate 

6. Landscape and Aesthetic Planning 

for Timber Salvage Areas 

Landscape Architect for Six 

Months 

Total LandscapefAesthetic 

Planning 

Total Cost for Recreation !j1,354,000 $2,676.000 

N.D. = No Data 
Table 2--Monetary D ge Estimate to State Park Structures and Facilities Within 

the 10-County, Hurricane Hugo Study Area." 

Park 

Disaster Survey Structure/Facility 

Description 

Givhans Ferry 

Hampton Plantation 

Lee 

Lynches River 

Old Dorchester 

Poinsett 

Woods Bay 

TOTAL 

Picnic area facilities 

Debris 

Damaged building 

Destroyed building 

Damaged building 

Damaged building 

Damaged building 

Damaged building 

Destroyed building 

Damaged building 

Campsite 

Chainlink fence 

Climbing facilities 

Debris 

Damaged building 

Damaged well pump 

Picnic tables 

Damaged building 

Debris 

Debris 

Parking lot lights 

Interpretive kiosk 

Picnic area/facilities 

Debris 

Electrical distribution lines 

Recreation equipment 

Debris 

Damaged building 

Water heater equipment 

Building contents equipment 

Damaged building 

Damaged shed 

Table and shelter 

Chainlink fence 

Chainlink fence 

Electrical distribution lines 

Debris 

" Source: South Carolina State Park Disaster Survey Report 
activity participation and visitation 

on the Francis Marion National Forest 

after Hugo. However, the Forest 

Service reported that pre-Hugo and 

post-Hugo visitor use figures are only 

estimates, not based on sound data, 

since most of their effort and funds 

were devoted to keeping up facilities 

and not toward recording recreational 

use, Reprts of "Recreation Visitor 

Days" (RVD) of use prior-to and after 

Hugo reveal an estimated decrease in 

total use of 73,000 RVD or -60 percent 

(Table 3). Recreational use decreased 

for a11 the activities, except sightseeing (view South Carolina) and 

tours. In terms of decreased use, 

camping (-91 percent), picnicking (-89 

percent), and hiking (-87 percent) 

were the forest-based activities 

showing some of the largest decreases 

in post-Hugo participation. 

Although Hurricane Hugo hit the State 

Parks after the busy use season and 

the park system had the off-season 

period to repair facilities before the 

spring use season of 1990, there was 

still a 49.8 percent decrease in 

attendance between FY 1988-89 and FY 

1989-90 for the 8 study parks (Table 

4). The greatest decreases were for 

Givhans Ferry (-75 percent), Old 

Dorchester (-72 percent), and N.R. 

Goodale (-37 percent). All 8 parks 

registered decreases in visitor 

attendance between the 2 years. 

Decreases in visitation were noticeable in every activity group of state 

park visitors: picnickers (-59 

percent), cabin users (-45.5 percent), 

fishermen (-38.4 percent), campers (- 

36.2 percent), and swimmers (-16.7 

percent ) . The National Wildlife Refuges reported 

a drop in visitation ranging from 23 

percent for Cape Romain to 26 percent 

for Santee, The biggest decreases 

took place during the 4 months 

directly after the September 1989 

hurricane. State Wildlife Management 

Areas and Industrial Forest Lands did 

not have accurate, or any records, of 

visitor use. 

Economic impacts related to reduced 

recreational revenues and fee receipts 

were greatest for State Parks, since 

they rent cabins, have developed 

campsites and charge for swimming and 

other special uses, However, total 

revenues were reduced only 3,4 percent 

for the 8 state parks as a result of 

Hugo (Table 5), The lack of economic 

impacts at State Parks can be partially 

explained by the fact that Hugo 

occurred in the off-use season 

er 21) and time was available 

for repair of damaged facilities before 

the 1990 heavy use, s 

Economic impacts related to the 

physical damage of structuresf 

facilities have already been reported. 

CONCLUSXONS 

Impacts of Hurricane Hugo on recreational use seemed to be greatest for 

hunting, particularly since Hugo struck 

South Carolina at the beginning of the 

1989 fall hunting season. Several of 

the National Wildlife Refuges and State 

Wildlife Nanagement Areas had to cancel 

the 1989-1990 hunting season. Most 

areas were re-opened in 1990, and some 

showed increased harvests for deer and 

certain other species. In the case of 

summer use activities, agencies had 

enough time between Hugo (21 September 

1989) and the following summer use 

season to repair cabins, campgrounds 

and other facilities accompanying 

recreational use, Forest-based 

recreation impacts would have been 

greater if the hurricane had occurred 

during the heavy visitor use, summer 

season. 

The overall impacts (physical, biological, social, and economic) of Hurricane 

Hugo on forest-based recreation in 

South Carolina were extensive; as were 

the impacts to the forest resource that 

support wildland recreation opportunities, It is important to realize that 

many forest recreation opportunities 

are heavily dependent upon forest 

resources and habitats, and those 

opportunities will recover only as fast 

as the forest resource-base recovers. 

However, some impacts to forest-based 

recreation were much shorter-term that 

those to South Carolina's timber 

resource. While it will take decades 

for the timber resource to recover to 

pre-Hugo status, much of the recreation 

resource, in terns of facilities, 

settings, and visitation opportunities, 

had recovered within 2 years after 

Hugo. Certainly by 1995, little impact 

related to recreational opportunities 

will be evident other than habitat 

damage, Even with habitat, the 

recreational impacts of Hugo were not 

all negative. Some forms of wildlife 

habitat and hunting opportunities were 

improved as a result of Hugo. Yet, the 

interior of Bulls Island was so devastated that it probably will never be 

the same, 
Table 3--Recreation Visitor Days (RVD) of Use on the Francis Marion National 

Forest, Before and After Hurricane Hugo, 

Activity 

Camping 

Picnic 

Swim 

Water Ski 

View South Carolina 

Auto Travel 

Motorcycle 

Nature Study 

Hiking 

Horse Riding 

Canoe 

Hunting 

Forest Products 

Tours 

Interpretation 

Total 

a Units are 1,000'9 of Recreation Visitor Days (RVD). One RVD = 12 hours, thus 

1.0 - 12,000 hours, 

Table 4--Total Visitation to Forest-Based State Parks in the LO-County, 

Hurricane Hugo Study Area, for the Fiscal Years of 1987-88, 1988-89, 1989-90 

(Fiscal Year July 1 to June 30)," 

Total Park Visitation 

Park FY 1987-88 1988---89 1989-90 

Givhans Ferry 

Warnpton Plantation 

Lee 

Lynches River 

N.R. Goodale 

Old Dorchester 

Poinsett 

Woods Bay 

Ar%nual Difference -3,s "pcd"" -49*8 "pet"" 

" Urban and historical parks within study area not included in data set, 
Table 5--Total Revenue to Forest-Based State Parks in the 10-County, Hurricane 

Hugo Study Area, for the Fiscal Years of 1987-88, 1988-89, 1989-90 

Park 

Total Visitor Revenue 

FY 1987-88 1988-89 1989-90 

( Timber ( Timber 

Salvage ) Salvage ) 

Givhans Ferry 

Hazlipton Plantation 

Lee 

Lynches River 

N.R. Goodale 

Old Dorchester 

Poinsett 

Woods Bay 

Totals 

% Annual Difference 

'NOD. = No Data 
The aesthetics of forest environments 

and sightseeing opportunitieslbenefits 

to recreationists will be affected by 

Hugo for 30 plus years. These impacts 

a r e d i f f i c u l t to document empirically, 

but are know to be important, as 

sightseeing in natural environments is 

the dominant outdoor recreational 

activity in the U.S. 

There were obvious limitations to the 

type and extent of recreation data 

available from the various agencies 

managing forest reereation lands. 

Accurate records of visitor use were 

particularly lacking and affected our 

determination of Hugo on activity 

related, visitation impacts. Better 

records of total visitor use, and 

individual activity use, would have 

been beneficial . 

The authors thank Frederick W. 

Cubbage, Southeastern Forest 

Experiment Station, U,S. Forest 

Service, for his cooperative efforts in 

sponsoring this research. Financial 

support for the study was provided 

under U*S*D,Ao Forest Service cooperative agreement No, 18-409, supplment 

No. 130. 

LXTEMlllfTIE CITED 

itt, William E, 1993, Assessing the 

Forest-Based Recreational Impacts in 

South Carolina of Hurricane Hugo, Final 

project report on file: Asheville, 

NoC,: Southeastern Forest Experiment 

Station. 43 pp. (plus appendices), 

Smith, Jack D.; Smith, Jane K. 1989. 

Hurricane Hugo: Aftermath in South 

Carolina. The Logger and Lumberman. 

38(12):7-16. 

U.S. Department of Interior, Fish and 

Wildlife Service. 1990. Santee National 

Wildlife Refuge: Annual Narrative 

Report. Santee, S.C. pp. 15, 20, 21, 

32-35 
IMPACTS OF' HURRIC 

ATTITUDES AND PERCEPTIONS' 

Abstract--Nonindustrial private forest (NIPF) landowners 

from the area in South Carolina hardest hit by Hurricane 

Hugo were surveyed to examine their responses to the 

storm's damage and to determine their needs and attitudes 

toward reestablishing their forest stands, More than 51 

percent of the landowners had discussed their damages with 

a forester, and 62 percent of the landowners tried to 

salvage timber. Only 19 percent indicated that they had 

made plans to regenerate their forest by either natural or 

artificial means, Landownersc expectations for the future 

of their land were mixed for the first two years, but they 

became more positive when considering a longer time frame. 

Landowners offered a wide variety of suggestions to encourage recovery of damaged forest land, including many forms 

of financial and technical assistance, The importance of 

cost-share assistance is noted, but direct contacts with 

landowners by foresters is recommended as essential to 

achieving post-hurricane reforestation. 

INTRODUCTION 

The events surrounding Hurricane Hugo 

provided an open window into the minds 

of NIPF landowners, This storm 

brought their worst fears to reality, 

forced them to face forest management 

decisions that many had managed to 

avoid before, and exaggerated their 

latent tendencies - both those that 

are positive and those that are negative, By surveying those landowners 

we have tried to peer through that 

window to give some direction to postHugo assistance programs and to better 

understand the nature of the enigma we 

call NIPF landowners. 

This project was funded and supported 

by the South Carolina Forestry 

Comission as a part of its post-Hugo 

reforestation education and technical 

A paper presented at the 72nd Annual 

Meeting of the Appalachian Society of 

American Foresters held at Greenville, 

S.C,, on January 20-22, 1993. 

Stephen K. Nodine, Clemson University Department of Forest Resources, 

Box 341003, Clemson, S.C. 29634-1003, 

assistance initiative. The Commission 

had the responsibility for designing 

and delivering the most effective and 

useful programs of assistance for 

landowners. In addition, it is important to understand the factors that 

influence landowners following disaster 

situations. 

The study consists of two mail surveys. 

The first was conducted during the 

summer of 1990, and the second is to be 

completed in the spring of 1993. 

THE FIRST SURVEY 

The primary objective of the first 

survey was to gauge the responses and 

needs of the affected landowners so 

that reforestation assistance could be 

directed most effectively. To understand the implications on long-term 

forest management decisions and priorities, we also needed to assess any 

changes in landownersc attitudes. It 

was important to understand both what 

landowners were up against as they 

contemplated possible recovery of their 

forest land and what the assistance 

agencies would be up against as they 

tried to encourage reforestation, 
The survey and its conclusions were 

built upon two foundation stones. 

First, a landowner's decisions are 

part of a decision strategy based upon 

the interaction of motivations, objectives, and constraints (Kurtz and 

Lewis 1981). Second, landowners 

follow different patterns of adopting 

new ideas (Fraser 1981, Duolittle and 

Straka 1987, Hapond 1888), 

The area studied included 14 counties 

covering the full range of moderate 

and severe damage from Hugo, Landowners were sampled at random from 

tax rolls, A total of 434 landowners 

who had experienced hurricane damage 

responded to a mail survey, Questions 

dealt with the landownersf background 

in forest management activities, the 

damage they incurred from the hurricane, their responses to date, and 

their perceptions as to the future 

prospects for their forest land's 

health and its role in their financial 

futures. 

Description of Sampled 

Landou11ers 

Landowners who were affected by the 

hurricane were fairly typical of 

landowners in South Carolina (Nodine 

1992). They had a tendency more 

towards being retired, as well as a 

slightly stronger connection to farming backgrounds than the statewide 

average (Marsinko and others 1987), 

They also tended more to live close to 

or on their forest land (60 percent 

compared to 40 percent), although 

their personal concepts of how close 

is close enough was somewhat clouded. 

They were more likely to have acquired 

their land through inheritance than 

purchase, and their average size of 

ownership was slightly larger than the 

statewide average. 

These landowners had slightly more 

experience than average in past 

reforestation work, but they were 

somewhat less experienced in terms of 

past harvesting, This may have 

hindered their potential salvage 

opportunities, but was anticipated to 

increase their propensity toward 

reforestation. Typically, they were 

relatively unfamiliar with various 

forms of assistance already available 

to them, with only one-fourth being 

familiar with cost-share programs and 

less than 17 percent familiar with 

various income tax benefits, More 

than half of the sampled landowners 

had some previous contact with 

professional foresters. Consulting 

foresters had provided information or 

assistance to the most landowners, 

followed by state agency foresters and 

industry foresters, 

landowner incurred seemed to transcend 

income, social status, age, and other 

normally distinctive characteristics 

which can influence attitudes and 

actions. The newspaper publisher, the 

real estate agent, and the low-income 

farmer were all joined together in a 

common experience. Their responses 

eventually have varied based in part on 

available resources, but the usual 

patterns have not always been followed, 

In spite of their varied reactions to 

common experiences, most landowners 

were set back both in their financial 

condition and their confidence. Their 

general characteristics and tendencies 

were exaggerated by their experiences. 

Most of the sampled landowners had 

taken some actions to assess the 

damages they incurred and to make some 

responses to those damages. Ninetyfive percent of the landowners had 

visited their land, and 51 percent had 

discussed the damages with a forester. 

Sixty-two percent tried to salvage 

damaged timber, and nearly two-thirds 

of them had completed a salvage 

harvest. Almost 55 percent of the 

landowners indicated they would use 

part of any salvage receipts for 

reforesting their land. This is a 

positive sign among those who have 

recovered some value from their damaged 

stands, but it leaves many who apparently are not yet ready to reinvest 

some of those earnings. 

Only 19 percent of the landowners had 

made plans for reforesting their land. 

Of these landowners nearly 60 percent 

planned to request cost-share assistance, Of those who indicated no 

reforestation plans, nearly two-thirds 

said they want to reforest their land, 

but barriers such as cost and a lack of 

information stood in their way. Fewer 

than one-fourth of these landowners had 

discussed reforestation with a forester, and nearly 54 percent said they 

needed more information. Fifty-eight 

percent said the availability of costshare assistance might change their 

plans, 

Landowners* Outlook 

In general, landowners had become less 

dependent on their land for income, 
with less of a focus on growing timber 

as a main objective* While they had 

higher than average expectations for 

income before Hugo, their expectations 

shifted further into the future or 

disappeared altogether after the 

stom. Only a few landowners actually 

moved their income expectations more 

toward the present. Similarly, 

although these landowners indicated a 

higher-than-average priority for 

timber production before Hugo, the 

number with timber as their top land 

ownership priority dropped by almost 

one-third after Hugo. Some of those 

who comented on such a change shifted 

their priority from timber production 

to investment, while others were 

uncertain about their top priority. 

Even though landowners anticipated 

many problems in the recovery of their 

forest land, there was a general 

acceptance of the need for reforestation and forest recovery, The 

majority agreed that reforestation is 

necessary to restore forest productivity (74 percent) and to improve the 

environment (62 percent), When asked 

if they would reforest their land if 

all financial and technical constraints were removed, 82 percent said 

yes, 15 percent said no, and 3 percent 

were unsure. 

Generally landownersf expectations for 

their land within the first two years 

began on less than a positive note, 

but they became more positive when 

looking ahead five years, This seems 

to reflect a belief in the intrinsic 

regenerative power of the forest, 

only 34 percent of those responding 

predicted a positive condition for 

their land in two years, while 58 

percent had a positive prediction 

after five years, At the same the, 

negative predictions dropped from 20 

percent to 16 percent and uncertain 

responses dropped from 42 percent to 

26 percent. Non-qualitative responses 

dropped from three percent to one 

percent, and were primarily related to 

changing land use away from timber 

production. Most of the shifting 

attitudes were among those who were 

uncertain after only two years, but 

who anticipated more positive conditions after a longer interval after 

the storm, 

Landowners' Weeds and 

Suggestions 

When asked what needs to be done to 

encourage the recovery of damaged forest lands and who should do it, 60 

percent of the landowners offered suggestions* Various forms of financial 

assistance dominated the suggestions, 

led by cost sharing (40 percent) and 

tax assistance (16 percent), Eighteen 

percent suggested technical assistance 

to landowners, reflecting the sense of 

landowners that perhaps the tried-andtrue management practices of the past 

might not quite fit the needs of postHugo forest stands. All segments of 

the forestry comunity were recognized 

as having certain responsibilities for 

accomplishing the recovery. 

OUR RECOMMENDATIONS 

This first survey provided us with a 

good cross-section of landowners in the 

affected area. From their actions and 

responses we can draw several conclusions abut the types of reforestation 

assistance efforts that should yield 

the greatest results, Landowners 

expressed concerns about the prospects 

of their forests providing the same 

financial returns that they had previously expected, and their confidence 

in their abilities to manage an effective reforestation program had been 

shaken, They expressed guarded optimism about the future, but many were 

unsure as to how a favorable outcome 

could be achieved. Their reservations, 

coupled with the long time required for 

those stands which are reforested to 

reach maturity, indicate that supplies 

of timber in this region will be 

affected for many years, Future market 

conditions in the area may be positive 

for forestry investments, but their 

impact on reforestation decisions is 

uncertain at this the. 

The extent of damage received and a 

landownerfs economic position will have 

an impact on his or her response to the 

storm. Neither of these, however, can 

serve as a reliable predictor of reforestation intentions or accomplishments~ 

Each landowner is responding to Hugo in 

a very personalized manner, each based 

on a sometimes complex set of circumstances. Therefore it is necessary to 

approach each landowner with a personalized and flexible set of incentives 

and assistance. 

Nearly 70 percent of the sampled landowners have conducted some type of 

natural or artificial reforestation 

work on their land in the past, Sixtytwo percent have conducted some type of 

thinning or final harvest. This familiarity with two basic forest management 

activities should provide a good 

framework for planning recovery 
regeneration. However, many forest 

landowners deal with these activities 

only infrequently, and they tend to 

become less confident in their own 

abilities as time passes, 

Regarding progr which might be 

targeted toward ndowners, most 

the traditional assistance progr 

have a lower recognition and utilization rate than foresters might expect, 

This opens the door for several opportunities in providing the most help 

possible to landowners. Educational 

programs describing the availability 

and conditions of reforestation tax 

incentives may provide significant 

motivation to many landowners who 

realize the opportunity for quick 

deductions for their expenses. Such 

incentives are available now to all 

landowners and should be emphasized in 

any contacts with landowners. 

Cost-share programs are very helpful 

to those landowners who use them, but 

as shown above many landowners do not 

know about them. Because of the 

limited funding which is available for 

these programs and the uncertainty 

about future funding, these programs 

should not be expected to carry the 

burden of financial assistance to 

landowners. For those who need the 

funding to be able to accomplish any 

work, however, such programs may be 

vital. And, based on a recent study, 

those who wait for such funds will not 

likely suffer financially due to the 

delay (Nodine 1990). 

The fact that two thirds of the 

landowners have had contact with a 

forester is very encouraging in 

planning a reforestation campaign. In 

a regeneration study, Royer and Kaiser 

(1985) found "the presence of a professional forester was positively 

associated with, and likely the reason 

for, much of the pine management 

activity both during and following 

hamesting in the South." Although 

they report that the optimal time for 

landowner contacts with foresters is 

before or during harvest, the main 

advantage to be gained by early 

contacts is the opportunity to coordinate harvesting and subsequent 

reforestation work. The opportunity 

for such preplanning is obviously 

precluded by a sudden event such as 

Hugo, but contacts after the atom can 

still have significant effects on 

reforestation plans, 

Royer and Kaiser recommended that 

public foresters might become more 

effective if their emphasis was shifted 

from being technical assistants to 

being facilitators. As such they could 

serve to promote forest management, 

discuss factors which affect the landowner's situation and decisions, and 

encourage contacts with consulting 

foresters. 

Birch (1986) suggested an approach of 

targeting segments of the NIPF owners 

who have similar conditions and 

customizing informational programs to 

each group. He recommended the use of 

multi-media contacts which multiply the 

communication potential of each forester. Examples included the use of 

articles on forest management in nontraditional publications which are read 

by forest landowners, correspondence 

courses, and computerized information 

systems and decision-making software. 

Doolittle and Straka (1987) reported 

that although mass media are the most 

efficient method for diffusion of 

awareness information, direct contacts 

by a forester may be necessary to 

translate awareness into reforestation 

actions. They recornend special 

training for foresters to improve 

communications with reluctant 

landowners. 

Given the importance of landowner contacts with foresters and the unique 

circumstances resulting from Hugo, the 

effective use of public and private 

foresters cannot be overemphasized. 

With the support and funding which is 

available from the federal Dire 

Emergency Supplemental Appropriations 

Act, and the broad interest and 

commitment on the part of all seqments 

of the forestry co~unity, priority 

should be given to enabling all 

available foresters to advise and 

assist landowners in their recovery 

efforts. Training on both communications skills and technical aspects of 

post-hurricane reforestation should be 

undertaken to maximize the impacts of 

the reforestation efforts. 

Not surprisingly, there are significant 

difficulties to be overcome in the 

quest for encouraging and implementing 

the massive reforestation needs of this 

region. Traditional programs and practices have a place in the response of 

the forestry community to the damage, 

Additional resources surely are needed, 

but shply "more of the same" will not 
be sufficient. A reallocation of 

n resources following the suggestions of Royer and Kaiser, with an 

emphasis on personal contacts between 

foresters and landowners, is essential 

to meet the challenge. The destruction of Hurricane Hugo is indelibly 

marked in the minds and hearts of all 

landowners who felt its impact, and 

the repercussions will be present for 

many years, 

THE: FOUOW-UP SUIiVEY 

It has been found that forest landownersf eventual actions do not always 

exactly correspond to their original 

intentions (Turner and others 1977). 

It is also true that there still 

existed a great deal of uncertainty in 

the minds of sampled landowners as to 

how certain reforestation techniques 

would work out and how financial 

assistance programs would develop. 

For these reasons a second survey is 

currently underway. This survey will 

revisit those who responded to the 

first survey to evaluate their ability 

to accomplish their stated intentions, 

It will also survey a new random 

sample of landowners in the area. The 

objective of these contacts will be to 

study in greater detail reforestation 

behavior under the extreme circumstances created by Hurricane Hugo. We 

will be testing predictions of landowner behavior based on current behavioral research, We will also try to 

assess the effectiveness of current 

post-Hugo landowner assistance efforts 

in encouraging reforestation, In 

testing the conventional wisdom as to 

what will explain or predict landowners' reforestation behavior, we 

will focus on several key factors that 

can be readily isolated. We will also 

be working with the U.S, Forest Service and faculty from Duke University's Institute of Policy Sciences 

and Public Affairs to analyze landowner assistance policy decisions and 

the effectiveness of various efforts 

in motivating reforestation, 

Specifically, we will be trying to 

address the following questions: 

1, Did wildfire protection help 

reassure landowners and reduce 

their anxiety? 

2. Did success or failure with 

salvage harvesting provide 

support (source of capital, 

reduced costs, reduced wildfire 

threat, etc.) for reforestation? 

3, Did regeneration inspections 

provide landowners with guidance 

and confidence? 

4. Did HIP cost sharing provide the 

necessary capital? 

5, Was there any interactive effect 

from these programslactivities? 

6. Can we characterize reforestation 

tendencies of those who received 

(and responded to) certain types 

of assistance, as well as those 

who did not? 

7 , Based on the above, were 

resources allocated in an optimal 

manner? 

We will also try to determine the 

current constraints that are being 

faced or perceived by landowners. 

LITERATURE CITED 

Birch, TOW. 1986. Communicating with 

nonindustrial private forestland 

owners. Journal of Forestry 84(12):25- 

33 , 

Doolittle, L.; Straka, T.J. 1987. 

Regeneration following harvest on 

nonindustrial private pine sites in the 

South: a diffusion of innovations 

perspective, Southern Journal of 

Applied Forestry 11(1):37-41. 

Fraser, E.C., 111, 1981, Motivating the 

non-industrial timber landowner to grow 

more trees. P. 94-99 in Increasing 

forest productivity, Proceedings of the 

1981 convention of the Society of 

American Foresters. 

Haymond, J.L. 1988. Adoption of 

silvicultural practices by opinion 

leaders who own nonindustrial private 

forestland. Southern Journal of Applied 

Forestry 12(1):20-23, 

Kurtz, W.B.; Lewis, Bernard. 1981. 

Decision-making Framework For 

Nonindustrial Private Forest Owners: 

An Application in the Missouri Ozarks. 

Journal of Forestry, May 1981, pages 

285-288 , 

Marsinko, A,; Stevens, R,; Nodine, S. 

1987. Nonindustrial private forest 

lands and landowners in South Carolina. 

Clemson University Department of Forest 

Resources, Forest Research Series No. 

43, 36 pages. 

Nodine, S.K. 1990. Benefits and costs 

of reforestation delays under the 

Forestry Incentives Program in South 

Carolina. Ph.D. dissertation, Clemson 

University, Clemson, SC. 
Nodine, SoKO 1992. Forest landowners' 

responses to Hurricane Hugo. 61 

University Department of Forest 

Resources, Forest Research Series No. 

47, 37 pages, 

Rsyer, J.P.; Kaiser, H.F. 1985, 

Influence of professional foresters on 

pine regeneration in the south, 

Southern Journilf of Applied Forestry 

9(1):48-52, 

Turner, B.J.; Finley, J.C.; Kingsley, 

N.P. 1977, How reliable are woodland 

ownersr intentions? Journal of 

Forestry 75(8):498-499, 

~eprintd with permission from 

Hurricane Hugo: Recovering from 

Disaster, Proceedings 72nd Annual 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Foresters, Greenville, SC, 

Jan, 20-22, 1993, Dr, Vernon L, 

Robinson, See-Treas, 2557 Abbott 

Circle, Seneca, SC 29678, 
IMPACTS OF HUGO TIMBER D E 

Y WOOD MANUFACTURERS 

IN SOUTH CAROLINA 

John H. S and Joseph R. saucier' 

PREZ'ACE 

This report describes a three-part study of the economic impact of 

Hurricane Hugo on primary wood 

manufacturers in South Carolina. 

Obviously, the State's third largest 

manufacturing industry--wood products 

--has been severely damaged by Hugo. 

This study indicates that there is 

simply not enough suitable remaining 

timber to support the industry in its 

past configuration. Significant 

changes have already taken place and 

more will follow. 

Operations that cannot compete in the 

new environment must recognize that 

their survival depends on changing 

their business strategies. They must 

increase their operating margins to be 

able to pay rising prices for timber, 

or they must reduce their dependence 

on scarce forms of timber. 

Relatively small firms appear to be 

hardest hit by Hugo. Unfortunately, 

these firms typically do not have the 

resources to make strategic changes to 

better secure their futures. The 

results from this project provide a 

potential opportunity to assist highly 

vulnerable firms in making the changes 

that would reduce their dependence on 

timber raw material that is in short 

supply * 

John H, Syme is Lecturer, Department 

of Forest Resources, Clanson University, Clemson, SC, and Joseph R. 

Saucier is Project Leader with the 

U.S. Department of Agriculture, Forest 

Service, Southeastern Forest Experiment Station, Athens, GA. 

EXECZrrIVE SmY 

To assess impacts of Hurricane Hugo on 

forestry industry, primary woodproducts manufacturers in South 

Carolina that sustained timber damage 

were contacted. The storm-damaged area 

was divided into primary and peripheral 

regions, and two counties outside the 

damaged area were selected to serve as 

a control region, Eighty-three pr 

manufacturing plants were identified xn 

the three regions. A questionnaire was 

mailed to each plant, and 83 percent of 

the firms responded. In addition, 41 

plant managers were personally interviewed. 

In total, nonpaper wood-products plants reported a considerable drop in timber 

raw-material consumption since Hugo. 

They forecasted additional declines in 

future consumption in the primary 

region but foresaw slight increases in 

the peripheral region. Consumption 

volumes in the control region remained 

the same as before Hugo, and no changes 

were predicted for the next 3 years. 

Timber procurement has become a severe 

problem for most plants in all three 

regions. Competition is intense, 

timber and log prices have risen 

dramatically, procurement areas have 

been enlarged resulting in much longer 

log-hauls, and quality of available 

timber is lower, The effect of Hugo on 

timber procurement has extended far 

beyond the damaged area, as plants 

reach out farther to satisfy their 

needs. Most plants expect the 

situation to worsen in the future, 

Major concerns expressed most often by 

the respondents were increasing competition for timber, higher timber 

prices, lower available t 

inadequate timber supply, reduced 
profitability, increasing competition 

from large corporate firms, and 

inability to survive in the future. 

Twenty percent of the 69 respondent 

plants indicated they had experienced 

some type of curtailment or closure 

due to Hugo. Infomation from both 

the mail survey and personal interviews showed that three plants have 

been closed penmanently, twelve more 

appear to have short-term survival 

problems, and five additional plants 

have longer-tern survival problems. 

The few plants that have not been 

seriously impacted by Hugo appear to 

have strengths that enable them to 

better cope with major threats. 

Based on the information gathered in 

this project, it appears that there is 

not enough available timber to meet 

the projected needs of the primary 

wood-products Ilaanufacturers in the 

study area. Most of the vulnerable 

plants are located in small rural 

communities and are important contributors to their economies. Further 

curtailment or closure will seriously 

impact the economies of the rural 

areas in which the plants are located. 

Theref ore, it is extremely important 

that appropriate assistance be identified and provided to the threatened 

plants so they can continue to operate. Preliminary investigations 

conducted during this study indicate 

that these firms need several different kinds of assistance in order to 

become less dependent on timber raw 

materials that are in short supply or 

to increase their operating margins to 

be able to pay higher prices for the 

raw materials. 

INTRODUCTION 

On September 22, 1989, Hurricane Hugo 

struck the South Carolina coast with 

the full force of 135 mile-per-hour 

winds. Hugo swept through central 

South Carolina into North Carolina, 

creating extensive damage to timber 

and property, in a swath 50 miles 

wide. Severe damage to timber 

occurred in 23 counties. In six of 

these counties, more than 90 percent 

of the timberland sustained damage. 

Estimates placed the total timber 

destruction at $1.18 billion, with the 

equivalent of 4 yearsF harvest of 

sawtimber destroyed. Large-diameter 

trees were most prone to hurricane 

losses. 

Forest industry is extremely important 

to the economy of South Carolina. 

Timber is the State's leading cash 

crop, forest products manufacturing is 

the third largest industry, and forest 

products make up the largest volume 

export product. Forest industry is a 

particularly important economic factor 

in the counties that sustained the 

er destruction. Woodproducts manufacturers believe that too 

timber was destroyed for the 

ining timber resources to sustain 

$Re existing level and type of timberprocessing industries. Curtailment or 

closure of a number of harvesting, 

raanufacturing, and related operations 

is likely. Severe negative effects on 

the countiesF economies will include 

both direct and indirect loss of jobs 

and reduced income and tax revenues. 

The first objective of the research 

described here was to accurately assess 

the impact of Hurricane Hugo on-primary 

timber-processing firms in the affected 

area. The second objective was to 

identify establishments whose survival 

is threatened as a result of Hugo and 

to suggest strategies for reducing 

their dependence on local timber 

resources that are in short supply. 

METHOD 

Twenty-eight South Carolina counties 

were selected for the study. These 

counties were in three regions: (1) 10 

primary counties (Berkeley, Clarendon, 

Dorchester, Florence, Georgetown, 

Kershaw, Lancaster, Lee, Sumter, and 

Williamsburg) that sustained major Hugo 

timber damage, (2) 16 peripheral 

counties (Bamberg, Calhoun, Charleston, 

Chester, Chesterfield, Colleton, 

Darlington, Dillon, Fairfield, Horry, 

Lexington, Marion, Marlboro, 

Orangeburg, Richland, and York) that 

were adjacent to the primary counties 

and sustained moderate timber damage, 

and (3) 2 control counties (Allendale 

and Newberry) that sustained no timber 

damage (Figure 1). Eighty-three 

establishments were identified as 

producers of primary wood products in 

the study area. Primary wood products 

are defined as those produced directly 

from the timber raw material. Examples 

include pulp chips, pulp & paper, 

lumber, veneer, plywood, and poles. 

The project was divided into three 

phases. In Phase I, a questionnaire 

was mailed to the 83 primary 

wood-processing plants in the study 

area. In Phase 11, personal followup 

interviews were conducted with selected 

establishments. In Phase 111, firms 

with serious survival problems were 

studied, and the reeourcee needed to 
Primary Region 

rmj Peripheral Region 

Control Region 

Figure 1--The three study regions. 

improve their ability to continue in 

business were identified. 

Phase I: Mailed Questionnaire 

The information required from the 

identified processing establishments 

was determined. A questionnaire was 

then developed, pretested, and mailed 

to each processor in the study area, 

The questionnaire was designed to 

gather information about current and 

long-term changes in processors' 

operations, resulting from Hugo. In 

June 1991, a letter sent to each firm 

explained the purpose of the study, 

assured confidentiality of replies, 

and stated the importance of returning 

the completed questionnaire which they 

would receive in a few days. Questionnaires were then mailed to the 83 

wood-processing plants. Two weeks 

later, a followup letter was mailed to 

firms that had not responded. A 

second letter was mailed 3 weeks after 

the initial followup letter to the 

nonrespondents. The information 

gathered from the questionnaires was 

analyzed with a computer spreadsheet 

program. 

Phase 11: Personal Interview 

Personal followup interviews were conducted with 41 of the respondents to 

the mailed questionnaire. Respondents 

who indicated an interest in participating in Phase 11, or who stated they 

had serious business problems related 

to Hugo, were selected for personal 

interviews. The manager or owner of 

each firm, along with its timber 

procurement supervisor, were interviewed at their locations over a 

2-month period in early 1992. The 

interviews focused on major changes and 

problems in the current situation and 

in forecasts for the future brought 

about by Hugo. Three major topics 

provided guidelines for the interviews: 
Major Impact on Timber Raw Material 

Changes in competition 

Prices 

Procurement area 

* Quality of available timber 

Major Impact on Processing Operations - Curtailed or closed operations 

* Programs to increase efficiency or 

expand current operations, or 

to diversify or expand into 

new areas such as secondary 

manufacturing 

Long-Term Major Concerns 

Open-ended question that permitted 

respondents to name areas of greatest 

concern about current and future 

business operations 

Responses were recorded and tabulated. 

 he‘ resulting data were analyzed ( 1 ) 

for all operations combined, (2) by 

size of operation, (3) by'type of 

operation, and (4) by regron (prunary, 

peripheral, and control). 

Phase 111: Identification of 

Firms With Serious Problems 

Firms with serious survival problems 

resulting from Hugo were initially 

identified from infomation in 

returned questionnaires. The final 

list of firms was verified from 

information gathered during the 

followup interviews. Critical needs 

of the threatened firms were sought in 

the personal interviews. 

RESULTS 

The results from Phases I, 11, and I11 

are described in separate sections. 

Table 1 (Appendix) shows the composition of the respondent plants to the 

mailed questionnaire and the personal 

interviews. 

Phase I 

A total of 69 valid responses to the 

questionnaire was received. The 

overall response rate was 83 percent. 

Responses by region and type of mill 

were : 

Plants sent Response 

questionnaire rate 

r Percent 

33 79 

Peripheral 39 85 

Control 11 91 

Mill type 

Sawmil 1 46 

Plywwd/veneer 14 

Chip mill 8 

Pole plant 5 

Paper 6 

Basket 3 

Fiberboard I 

The data gathered from the questionnaire are presented on a question-byquestion basis. In most cases, data 

from paper mills are separated from 

data from other mills. Paper mills use 

larger volumes of wood and procure 

their wood from a larger geographic 

area and from a wider variety of 

sources than do most sawmills and 

veneer mills. Paper-mill procurement 

is more regional than local. Separating out paper mills permitted more 

sensitive analyses for small geographic areas, 

For purposes of the study, the nsnpaper mills were divided into the 

following size groups, based on their 

annual consumption of timber: 

Small Less than 20,000 tons 

Medium-small 20,000-79,000 tons 

Medium 80,000-200,000 tons 

Large More than 200,000 tons 

Raw Materials Used 

Question: Please show the annual 

volumes of timber raw material used by 

your mill by species and type of timber 

(veneer logs, saw logs, pole timber, 

and pulpwood) for the period prior to 

Hugo, currently, and your projected 

volumes 3 years from now. 

Responses are summarized as follows: 
Nonpaper 

Paper 

Changes in 

total annual 

volume used 

1991 1994 

Changes in annual 

volume used, by 

timber type (nonpaper) 

1991 1994 

---Percent--- 

softwood 

Veneer logsf 

saw logs -5 -6 

PU~~WOO~ -5 -2 

Hardwood 

Veneer logsf 

saw logs -13 -3 

PU~~WOO~ -25 -14 

Poletimber -11 -18 

The reduction in current usage for 

nonpaper plants is probably not 

entirely attributable to Hugo. Market 

demand for lumber, plywood, and most 

other wood products was depressed at 

the time this census was taken, and 

these data partially reflect the 

market's influence on timber consumption, The forecast for usage 3 years 

from now (1994) is probably more 

representative of Hugo's influence on 

timber consumption. 

Overall, the 7-percent drop in projected 1994 consumption appears to be 

modest. However, the data show that 

the decrease is more severe in certain 

groups. For example, the primary 

region shows a projected decline of 17 

percent, as compared with a small 

change in the peripheral and control 

regions, Further, the 38-percent 

projected decline for small mills is 

much greater than for larger mills; 

however, the overall effect is not as 

significant, due to the comparatively 

minor volume consumed by the smallmill group. Certain types of mills, 

such as pole plants and veneer mills, 

predict a much greater decline in 

raw-material consumption than do other 

mill types. Table 2 (Appendix) 

provides the response data in greater 

detail, 

Sources of Raw Materials 

Question: Please list the sources of 

the timber raw material used by your 

mill for the period prior to Hugo, 

currently and your projected sources 3 

years from now. 

Sources of timber include purchased 

logs (PL), purchased government 

stumpage (PGS), purchased private 

stumpage (PPS), and company t 

(CT). Overall, the responses show (1) 

an increase in the proportion of raw 

material from PL, both currently and in 

the future; (2) a current increase in 

raw material from CT, followed by a 

slight reduction in the future; and (3) 

decreases in the proportion of both PGS 

and PPS, currently and in the future. 

The results are summarized in the 

following tabulation. Tables 3, 4, and 

5 (Appendix) provide more detail. 

Raw-material mix 

PL PGS PPS CT 

------Percent------ 

Before Hugo 50 5 39 6 

Currently(1991) 56 2 34 8 

Future (1994) 54 3 33 5 

Chanqes in the TimberProcurement Environment 

Question: Indicate the degree to which 

each of the following factors has 

changed in your operation as a direct 

result of Hugo. 

Change factors listed in the questionnaire related primarily to the availability, quality, cost, and competition 

for logs and stumpage; the procurement 

area covered; and the average log-haul 

distance. Changes in all raw-materialrelated factors were moderately or 

highly negative. The greatest reported 

increase was in competition for timber 

and logs, followed by cost of stumpage 

and delivered logs, log-hauling distance, and size of procurement area. 

Availability and size of timber and 

logs decreased moderately. This 

pattern was consistent for each of the 

groups analyzed (Table 6, Appendix). 

Effects on Support Services 

Question: Briefly describe any 

changes, including employment level sf 

which have taken place in your area 

related to timber suppliers, logging 

contractors, and other businesses which 

supply forest industry support 

services, as a direct result of Hugo. 

Responses to this open-ended question 

were grouped into the 10 categories 

shown in Table 7 (Appendix). Sixteen 

mills did not respond to this question, 

and 12 mills gave an invalid response. 

Of the total responses received, the 

one named the most was "decrease in 

available loggers," followed by "no 

change. " 
Chanaes in Raw Material 

Availability 

Question: Briefly describe b~rtant 

 change^, related to t 

material availability in your area, 

which you believe will take place 

during the next 3 years. 

Responses to this open-ended question 

were grouped into 18 general categories. "Increasing levels of 

competition" was named mast often, 

followed by "decreasing timber 

quality," "increasing stumpage costs," 

"fewer or no timber sales in area," 

and "additional mill closures." Table 

8 (~ppendix) shows how responses 

varied among the groups analyzed. 

Effect of Huso on Business 

Question: From an overall viewpoint, 

how will the above Hugo-related 

changes affect your business? 

Short-term? Zong-term? 

A choice of five responses ranging 

from "very detrimental" (1) to "very beneficial" (10) was provided separately for the short-term impact (first 

3 years) and the long-term impact 

(5-10 years). In both the short and 

long term, respondents saw Hugo as 

being "somewhat detrimental" to their 

businesses, with an average response 

value of 3.7. 

Chanses in Business O~erations 

Question: How much have you chanqed, - - or are you willing to change, your 

business operations in each of the 

following areas, as a direct result of 

Hugo? 

Response factors listed in the questionnaire covered major business 

activities, including raw-material 

procurement, manufacturing, products, 

markets, sales progr 

curtailment of existing operations, 

and additions of new operations. In 

total, respondents indicated that they 

had made minor to moderate changes for 

each factor listed. The analysis of 

the individual groups followed a 

similar pattern, except for fiberboard 

and pole plants, which showed major 

changes in raw material used and in 

procurment progr . Respondents 

tended to give the same response for 

both the operational changes they have 

made and for the changes they are 

willing to naake. Therefore, only 

responses related to changes that have 

already been made are shown in Table 9 

(Appendix). 

Curtailment and Closure of 

Operations - 

Question: Have you closed or curtailed 

permanently, or exgect to close or 

curtail, any operations as a direct 

result of Hugo? 

Responses to this open-ended question 

were grouped into nine general categories. They show that there have been 

some closures and curtailments of 

operations due to Hugo, but the 

majority of plants indicated that no 

change has been made or is contemplated. "No change" was reported by 47 

respondents. Closure or curtailment 

was reported by 15. Of the 15 reports 

of change, 5 related to closure of part 

of the operation and 6 to temporary 

layoffs, temporary reduction in production, or postponement of growth plans. 

Only one respondent indicated a 

pemanent plant closure. Table 10 

(Appendix) provides a detailed listing 

of the responses. 

Interest in Follorwup Proqram 

Question: As a second phase of this 

project, we are offering assistance in 

developing a1 ternative business 

strategies for companies which are 

experiencing raw-material-related 

problems as a result of Hugo. What is 

your interest in having your company 

participate in this follow-up program? 

In total, only 5 respondents expressed 

unqualified interest in participating, 

33 respondents indicated they were 

interested in participating but wanted 

more information. Twenty-five "not 

interested" responses were received. 

The response patterns were similar for 

all groupings. All responses are 

listed in Table 11 (Appendix). 

Phase 11 

Responses from the personal interviews 

were separated into three major topics: 

(1) impact on timber raw-material 

procurement, (2) impact on operations, 

and (3) long-term major concerns. 

Responses were placed in three groups 

for analysis: (1) region [pr-ry, 

peripheral, control]; (2) mill size 

[small (< 20,000 tonslyear), 

medium-small (20,000-79,000 tonsf 

year), medium (80,000-200,000 tons/ 

year), and large (> 200,000 tons/ 

year)]; and (3) mill type [pine sawmill, hardwood sawmill, pole plant, and 

other]. Table 12 (Appendix) provides a 

ry of the results from 

Phase 11. 
Hafor Impact on Timber 

RawMaterial Procurement 

Overall, 34 of the 41 mills indicated 

that nugo has had, and will continue 

to have, a major negative impact on 

er procurment. The 

seven plants reported that 

some areas of procurement had been 

affected, but they were not experiencing an overall major impact. 

Thirty-eight of the 41 plants indicated they were experiencing increased 

competition for timber raw material, 

and they expected increasing competition in the future, Thirty-six plants 

were impacted by higher stumpage or 

log prices, 32 plants have expanded 

their procurement areas, and 31 are 

experiencing a decline in quality of 

available material, 

The responses revealed little difference between primary, peripheral, and 

control regions except for the decline 

in quality of raw material (Table 13, 

Appendix). A decline in raw-material 

quality was reported by 4 out of the 9 

plants in the control region, 12 out 

of 13 in the primary region, and 14 

out of 19 in the peripheral region, 

The responses by mill size (Table 13, 

Appendix) indicated that the medium 

category was impacted the most, followed by the medium-small and large 

categories, with the small category 

reporting the least impact, Within 

the medium-size category, the plants 

in the primary, peripheral, and 

control regions all showed maximum 

impact. Within the large category, 

the impact on the control plants is 

somewhat less than on those in the 

primary and peripheral regions. In 

the medium-small category, plants in 

the primary region exhibit greater 

impact than those in the two other 

regions. 

Responses reveal little difference in 

overall impact among pine sawmills, 

pole plants, and hardwood sawmills 

(Table 13, Appendix). Plants in the 

"other" category, which includes 

veneer, plywood, and basket plants, 

reported less impact than those in the 

three specific categories. Pine 

sawmills reported greater impact in 

the primary region than in the 

peripheral or control regions. There 

were no pole plants in the control 

region, but pole plants in the primary 

region exhibited greater impact than 

those in the peripheral region. 

Responses from the hardwood sawmill 

category indicate that mills in the 

peripheral region were impacted more 

severely than those in the primary 

region; the response from the one mill 

in the control region indicated severe 

effect, In the "other" mill-type 

category, the responses disclosed that 

mills in the primary region experienced 

the greatest impact, while those in the 

control region experienced the least 

impact. 

Major Irnpaet on Operations 

Table 14 (Appendix) summarizes the 

responses related to curtailment and 

closure of operations, improvements and 

expansion to increase processing 

efficiency, and diversifying processing 

or adding secondary manufacturing. 

This table gives the percentages of 

mills that responded affirmatively in 

each of the above categories. 

Ten mills indicated they had curtailed 

or closed their operations as a result 

of Hugo. This total included five pine 

and three hardwood sawmills, Six of 

the mills were medium-size, two were 

large, and one was in each of the small 

and medium classes. Five mills were in 

the peripheral region, three in the 

primary, and two in the control region, 

Ten mills said they were improving or 

expanding their current operations to 

increase production efficiency. This 

group included nine sawmills (five pine 

and four hardwood). Four mills were in 

the medium-small size class, three were 

medium size, and three were large. 

Four mills were in the primary region, 

four in the peripheral, and two in the 

control region, 

Seven mills said they were adding 

secondary manufacturing or diversifying 

their operations into products that 

utilized lower cost or more available 

timber raw material, Six were sawmills 

(four pine and two hardwood). Three 

operations each were in the mediumsmall and large classes, and one was in 

the medium class. Four were in the 

primary region, two were in the control, and one was in the peripheral 

region. 

Maj or Lonq-Term Concerns 

Overall, the four areas of greatest 

concern to mill managers include 

reduced profitability, inadequate 

timber supply, increasing competition 

from larger firms, and future survival. 

Responses in these four areas are given 

in more detail in Table 15 (Appendix). 
Of 41 managers interviewed, 24 

indicated that reduced profitability 

was their major concern and that this 

concern was primarily related to 

er raw-material costs. 

Twenty believe the existing tigtber 

resource is n adequate to provide 

for current d nd, Thirteen plants 

considered increasing competition from 

large, integrated corporate firms to 

be a major concern, Twelve plants 

were concerned about their ability to 

continue in business at their current 

locations, 

Nine plants considered environmental 

constraints, such as those associated 

with wetlands, to be a major area of 

concern. Hardwood plants (four 

sawmills, two veneer plants) provided 

six responses; the remainder came from 

two pole plants and one pine sawmill, 

Nine plants (seven hardwood samiills 

and two hardwood veneer plants) are 

deeply concerned about the increased 

demand for hardwood pulpwood by paper 

firms. They specifically mentioned 

chipping saw logs and clearcutting 

young, vigorous hardwood stands as 

problems. Seven plants named their 

ability to obtain low-cost financing 

as being critical to survival, Five 

were pine sawmills, one was a hardwood 

sawmill, and one was classed as 

"other," Four hardwood sawmills were 

concerned about their inability to 

profitably process sweetgum and other 

less-desirable hardwoods because of 

poor market demand for products made 

from these species, 

Combined Res~onses Related to 

Major Impacts and Concerns 

Responses related to the nine concerns 

most frequently mentioned in personal 

interviews were combined to estimate 

effects of mill size, mill type, and 

location on Hugo impacts. Concerns 

included the four raw-material 

procurement factors, plus those 

relating to curtailed or closed 

operations, adequacy of the timber 

resource, profitability, increasing 

competition from larger finns, and 

ability to survive, 

Table 16 (Appendix) summarizes the 

results. The response rate is the 

number of affirmative responses as a 

percentage of the total possible 

affirmative responses, Expressions of 

concern were slightly less frequent 

for the control region than for the 

other two regions, Medium-small and 

medium size plants appear to have 

experienced more injury from Hugo than 

have small and large size plants, 

Among plant types, hardwood sa 

had the highest affirmative response 

rate and "other* plants the lowest, 

Phase 111 

Personal interview verified that three 

plants and the main part of one other 

plant closed as a result of Hugo. All 

the closed plants were samills, The 

reason given for the closures was lack 

of suitable t r at an economically 

feasible cost, The research also 

revealed that the survival of 12 

additional plants is in jeopardy, 

unless they receive near-term external 

assistance, Furthermore, at least five 

other plants have major problems which, 

if not corrected, may threaten their 

long-term survival. 

The 12 plants whose survival is 

threatened are important economic 

entities in the rural communities where 

they are located. Four plants are in 

the primary region, five in the 

peripheral region, and three in the 

control region, Most are in the 

medium-small and medium size classes, 

Seven plants are pine sawmills, but at 

least one is in each of the other plant 

type categories, The near-term 

assistance needed by the 12 plants 

includes a number of different kinds of 

programs. Examples are: 

Identification of alternative sources 

of working capital. 

Determination of feasibility of 

changing to a more specialized product 

line or diversifying into secondary 

manufacturing; identification of 

funding sources for implementing the 

new programs. 

Location of potential new plant sites 

near suitable timber resources; 

identification of funding sources for 

relocating the plant. 

Assistance in carrying out feasibility studies to justify installation 

of new equipnent to enable the plant to 

process a more-available type of raw 

material; identification of funding 

sources for purchasing and installing 

the new equipment, 

Development of a plan for identifying potential buyers of a plant and 

identification of funding sources for 

purchase of the plant, 

* Assistance in carrying out marketing 

research projects that will identify 
market niches in which the company can 

be competitive and that are compatible 

with the company's resources and 

capabilities. 

A few important inferences about the 

impacts of Hugo on pr 

products manufacturers in South 

Carolina can be drawn from our data. 

Although some definite patterns are 

developing, there are exceptions in 

many areas. A few plants in the 

regions studied have experienced 

little impact from Hugo, while other 

plants are fighting for survival. 

Much seems to depend on each firm's 

situation--its location in relation to 

Hugo; its relationships with rawmaterial suppliers; its management, 

financial, and timber resources; its 

processing efficiency; the type of 

timber raw material it requires; and 

its ability and desire to change. 

Volume and Type of Timber Raw 

Material Consumed 

Overall, nonpaper processing plants 

project a reduction in volume of 

timber consumed. The projected 

reductions are largest in the primary 

region, smaller in the peripheral 

region, and insignificant in the 

control region. On the other hand, 

paper mills are projecting a substantial increase in consumption, 

particularly for hardwood pulpwood. 

For nonpaper plants, the purchase of 

government and private stumpage is 

expected to increase. The portion of 

the raw material from company land is 

projected to remain about the same as 

before Hugo. 

Competition for Timber 

The responses from both the mailed 

questionnaire and the personal interviews confirm that competition for 

timber has increased greatly since 

Hugo. As a result, prices for logs 

and stumpage have increased substantially. Competition appears to have 

increased uniformly in the three 

regions and for the different types of 

plants. As mills in the primary 

region expanded their procurement 

areas into the peripheral and control 

regions, plants in these outer 

regions, in turn, expanded beyond 

their normal procurement areas, with 

several going into Georgia and North 

Carolina. 

The economic effects of Hugo, therefore, have spread over a much larger 

area than that which experienced 

damage. Many of the plants in this 

study describe timber procurement as a 

"war" or "battle for survival." 

Quality and size of available raw 

material have declined. This decline 

in quality appears to be more prevalent 

ry region than in either 

a1 or control regions. 

This conclusion is congruent with the 

fact that large t er suffered the 

ge from Hugo. 

Changes in Operations 

Hugo has precipitated many changes in 

operation of the affected plants. The 

biggest change has been in raw-material 

procurement. In addition, a few plants 

are improving or planning to improve 

production efficiency and volume 

through installation of new equipment 

or other process changes. Some plants 

are diversifying their operations by 

integrating forward into value-added 

processing, with the purpose of either 

obtaining a higher margin from the more 

costly raw material or reducing demand 

for timber by buying lumber and other 

primary products for remanufacture. 

Most plant operators, however, seem 

reluctant to change their strategies to 

reduce their vulnerability to the 

effects of Hugo. A few plants would 

like to make changes but lack the 

resources to do so. Other plants are 

not willing to risk major changes in 

their operations, apparently believing 

it is less risky to stay as they have 

been. 

Maj or Concerns 

Responses revealed that many firms 

share similar major concerns about the 

future of their businesses. Obviously, 

the major concerns relate to rawmaterial costs rising faster than 

selling prices for the products 

manufactured. Many plants believe the 

full effect of Hugo has not yet been 

felt. The depressed demand for wood 

products during the past few years has 

reduced demand for timber. As demand 

for wood products increases, the demand 

for timber will also increase, creating 

more severe competition than currently 

exists. 

Reduced profitability currently, and 

fears of continuing low future margins, 

are of great concern to more than 

one-half of the plant managers 

surveyed. Plants located in the 

control region and large plants appear 

to be less concerned than those in 

other regions and size categories, 
Increasing competition from large 

corporations is a major concern of 

several plants in all size categories, 

Smaller companies do not believe they 

have the resources to continue to 

compete with the large integrated 

r, especially as 

competition becomes more intense. 

Plant Curtailment and Closures 

One of the objectives of this research 

was to identify operations whose 

survival is threatened by the effects 

of Hurricane Hugo. Approximately 20 

percent of the 69 plants responding to 

the mailed survey indicated they had 

closed or curtailed operations temporarily or permanently, as a 

direct result of Hugo. Twenty-five 

percent of the 41 plant managers that 

were interviewed reported some 

curtailment or closure. 

Based on the information gathered, 

three plants have closed permanently. 

An additional 12 plants face serious 

near-tenn survival problems. Most of 

the threatened plants are of mediumsmall and medium size. They are in 

each of the regions and plant type 

groups. During personal interviews, 

changes that would make each plant 

more competitive were identified. 

These changes involved strengthening 

marketing, improving plant efficiency 

and processing capabilities, changing 

to a more specialized product line, 

adding secondary manufacturing, 

relocating the plant, strengthening 

management capabilities, and locating 

new sources of working and investment 

capital. 

Plants Mot Seriously Impacted 

by Hugo 

A few plants reported that Hugo had 

not seriously impacted their 

operations. Three of these plants are 

in the primary region, three in the 

peripheral region, and one in the 

control region. Each of these plants 

appears to have some unique capabilities that enables it to better cope 

with major problems such as Hugo. 

These include important visible 

strengths in marketing, company-owned 

timber resources, specialty products, 

close relationship and good reputation 

with local timber owners, adequate 

financial resources, and operating 

efficiency. 

GENEFULL OBSERVATIONS 

A large amount of information was 

gathered during this project. As we 

liatened to people and analyzed our 

data, we were able to make some general 

observations, Not all these observations are fully supportable with collected data, but we believe they are of 

interest t 

* The impact of Hugo extends well 

beyond the area where the storm damage 

actually occurred, Timber shortages in 

the area damaged by Hugo caused processors to expand their procurement 

activities into other areas in the 

state and into North Carolina and 

Georgia. The result is increasing 

competition for timber over a wide 

area, coupled with regional increases 

in prices. 

Because of the greatly increased 

competition for timber, it appears that 

there is not enough remaining timber 

for all processors of timber to continue operating at their anticipated 

levels of timber consumption. Therefore, the primary wood-processing 

sector's demand for timber will have to 

be reduced to reach a closer balance 

with supply. Plants using smaller and 

lower grade logs will be affected less 

than those using higher grade logs, 

such as saw logs and veneer logs. 

Processing plants within the study 

area are affected differently by Hugo, 

depending on each firm's resources and 

capabilities. Management skills, 

strong relationships with timber 

suppliers, niche marketing, efficient 

plants, and financial resources appear 

to be critical strengths. Plants 

possessing some or all of these 

attributes are less affected by Hugo 

than those which do not have them. 

Small and large plants tended to be 

affected less by Hugo than medium-size 

plants. Most small plants occupy 

specific market niches and require a 

relatively small volume of timber. 

Large plants tend to have more of the 

critical resources needed to survive 

during highly competitive periods, 

Two major threats were expressed by 

several plants. First, operators of 

small, medium-small, and medium size 

plants feel they cannot compete with 

the large firms during such highly 

competitive times as the aftermath of 

Hugo. Second, processors of hardwood 

veneer and lumber are deeply concerned 

about the rapid increase in consumption of hardwood pulpwood and the 

current practices of paper companies 

related to the chipping of hardwood saw 

logs and the clearcutting of young, 

vigorous hardwood stands for pulpwood. 
Managers of threatened companies 

seem reluctant to consider new business strategies that would reduce 

their dependence on timber raw 

material, Most appear to be willing 

to see their current business operations fail, rather than consider major 

changes in direction. A different 

business strategy, such as moving to 

mare specialized products or secondary 

~nufacturing, appears to be worth 

considering in view of the timber 

supply situation. Also, South Carolina 

lags behind most other southern states 

in value-added wood processing, which 

indicates that opportunities may exist 

in this area. 

Reprinted from Impacts of Hugo timber 

damage on primary wood manufacturers in 

South Carolina, USDA Forest Service, 

Southeastern Forest Experiment Station, 

Gen. Tech, Rep. SE-80. 28 p. 

APPENDIX 

Table 1--Composition of respondent mills to mailed questionnaires and personal 

interviews 

Mailed questionnaire Personal interview 

Type of mill Primary Peripheral Control Total Primary Peripheral Control Total 

Pine sad11 

Hardwood sawmill 

Hardwood veneer/plywood 

Softwood plywood 

Chip mill 

Paper mill 

Pole/piling 

Basket 

Fiberboard 

Total 2 5 3 5 9 6 9 13 19 9 4 1 
Table 2--Changes in timber raw material usage by mill size, by region, and mill 

type (nonpaper mills) 

Change 

Mill size, by region, Number Pre-Hugo through Projected change 

and mill type of mills volume 1991 from Hugo to 1994 

Thousand 

tonslyear ----------percent---------- 

Mill size: 

Small (<20,000 tons) 16 

Primary 76 -34 -27 

Peripheral 82 -68 -56 

Control 17 0 0 

Total 175 -4 7 -38 

Medium-small 

(20,000-79,000 tons) 

Primary 

Peripheral 

Control 

Total 

Medium 

(80,000-200,000 tons) 

Primary 

Peripheral 

Control 

Total 

Large (>200,000 tons) 

Primary 

Peripheral 

Control 

Total 

Mill type: 

Chip mill 

Hardwood sawmill 

Hardwood veneer-plywood 

Pole 

Softwood sawmill 

Softwood plywood 

Fiberboard 

All regions: 

Primary 

Peripheral 

Control 

Total 
Table 3--Sources of raw materials by region 

Region and material source 

Raw-material mix 

Before Hugo 1991 1994 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Peripheral region: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Control region: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 
Table 4--Sources of raw materials for all paper and nonpaper mills, by mill 

type 

Raw-material mix 

Mill type and material source Before Hugo 1991 1994 

Nonpaper mills: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Paper mills: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Softwood sawmills: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Softwood plywood: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

chip mills: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Hardwood sawmills: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Hardwood veneerlplywood: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Pole plants: 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 
Table 5--Sources of raw materials by mill size (nonpaper) 

Raw-material mix 

Mill size and material source Before Hugo 1991 1994 

Small (<20,000 tons per year): 

Purchased logs 

Purchased logs 

Purchased government stumpage 

Purchased private stumpage 

Company timber 

Medium-small (20,000-79,000 tons per year): 

Purchased logs 53 

Purchased government stumpage 8 

Purchased private stumpage 37 

Company timber 2 

Medium (80,000-200,000 tons per year): 

Purchased logs 38 

Purchased government stumpage 7 

Purchased private stumpage 43 

Company timber 12 

Large (>200,000 tons per year): 

Purchased logs 

Purchased government stumpage 

Purchased private timber 

Company timber 
Table 6--Changes in the timber procurement environment as a direct result of Hurricane Hugo 

Change factor 

Hill site 

All responding Resion Small rn r9* 

nonpaper wills Prisuary Peripheral Control (<20,000 tons) (20,000-79,000 tons) (80,000-200,000 tar) (>200,000 tons) 

(63 mills) (23 mills) (31 mills) (9 mills) (16 mills) (18 mills) (15 mills) (14 millr) 

Availability of suitable timber/logs 3.8 3.4 4.2 4.0 4.0 

Diammter of timber/logs 4.5 4.0 4.6 5.2 4.8 

Cost of stumpage 8.3 8.2 8.2 8.4 7.6 

Cost of delivered logs 8.2 8.0 8.2 8.0 7.6 

Procurement area covered 7.6 7.4 7.8 7.6 7.6 

Average diatance to haul logs 7.8 8.2 7.8 7.2 7.8 

tition for timber and logs 8.6 8.6 8.8 8.6 7.8 

Change factor 

Hi 11 tyDe 

Hardwood Hardwood Pole Soft- Softwcmd 

Chip mill sawmill veneer/plywpod plants sawmil 1 P~YW-~ Papar mill 

(8 mills) (13 mills) (11 mills) (4 mills) (23 mills) (3 mills) (6 mills) 

Availability of suitable timber/logs 4.0 

Diamater of timber/logs available 4.6 

Cost of stumpage 8.8 

Cost of delivered logs 8.6 

Procuremant area covered 6.8 

Average distance to haul logs 7.2 

tition for timber and logs 9.2 

Scale: 0-2 Decreased greatly 

2-4 - Lbcraased moderately 

4-6 = No change 

6-8 = Increased moderately 

8-10 = Increased greatly 
Table 7--Effects on support services as a result of Hurricane Hugo 

Change factor 

Hill sire 

All responding Reqion Small Medium-small Werd5.m brge 

nonpaper mills Primary Peripheral Control (<20,000 tons) (20,000-79,000 tons) (80,000-200,000 tons) (>200,000 tons) 

(63 mills) (23 mills) (31 mills) (9 mills) (16 mills) (18 mills) (15 laFll8) (14 mills) 

........................................ of responses--------------------------------------------------- 

Decrease in available loggers 15 8 4 3 0 3 5 7 

Increase in available loggers 3 1 2 0 0 0 2 1 

Type of loggers changing 6 4 1 1 1 1 3 1 

Equipment dealers out of business 2 1 1 0 0 1 1 0 

Dealers changing product line 2 1 1 0 0 1 1 0 

Decreased number of t-r sales 2 1 1 0 0 2 0 0 

No change 10 1 8 1 2 7 0 1 

No response 16 7 7 2 8 2 3 3 

Unrelated response 12 3 7 2 4 4 2 2 

Too early to tell 3 1 2 0 1 0 2 0 

Change factor 

Mill type 

Hardwood Hardwood Pole $of twood Wf twood 

Chip mill sawmill veneer/plyvood plants sawmill P~wO~ Paper mill 

(8 mills) (13 mills) (11 mills) (4 mills) (23 mills) (3 mills) (6 mills) 

Decrease in available loggers 

Increase in available loggers 

Type of loggers changing Equipment dealers out of business 

Dealers changing product line 

Decreased number of timber sales 

No change 

No response 

Unrelated response 

Too early to tell 
Table 8--Anticipated changes in raw material availability 

Change factor 

Mill site 

All reaponding Small Medium-all Medium Large 

(<20,000 tons) (20,000-79,000 tons) (80,000-200,000 tons) (>200,000 tons) 

(63 mills) (23 mills) (31 mills) (9 mills) (16 mills) ( 18 mills) (15 arflln) (14 mills) 

....................................... of responsen---------------------------------------------------- 

Increaae in logging costs 0 0 0 0 0 0 0 0 

Increase in stumpage costs 13 1 8 4 4 5 2 2 

Increase in levsls of c 15 4 9 2 2 3 5 5 

Decreaae in quality of timber 14 4 9 1 4 4 5 1 

Decrease in sixe of timber 7 2 4 1 0 2 3 2 

Mill closures expected 9 7 2 0 1 3 2 3 

Fermr/no timber sales in area 11 7 4 0 0 5 3 3 

No change 7 1 4 2 1 3 0 

No response 

3 

11 7 3 1 6 1 3 1 Too early to tell 0 0 0 0 0 0 0 0 

Change factor 

Increane in logging coats 

Increase in stumpage costs 

Increase in levels of ccmpetition 

Decrease in quality of t Decrease in size of timber 

Mill closures expected Fewer/no timber sales in area No change 

No response Too early to tell 
Table 9--Changes in business operations as a direct result of Hurricane Hugo 

Change factor 

Mill site 

All responding Resion ' Small Medium-small Medium Large 

nonpaper mills Primary Peripheral Control (<20,000 tons) (20,000-79,000 tons) (80,000-200,000 tons) (3200,000 tons) 

(63 mills) (23 mills) (31 mills) (9 mills) (16 mills) (18 mills) (15 mills) (14 mills) 

........................................ of responses--------------------------------------------------- 

Raw material used 4 4 4 3 4 5 3 3 

Procurement program 4 4 4 4 3 5 5 4 

Manufacturing process 2 1 2 2 2 2 2 2 1 

Products produced 1 2 2 2 2 Markets served 2 2 2 1 

1 1 3 2 1 1 

Sales program 2 1 2 1 3 2 2 1 Closure/curtailment of 

existing operations 2 2 2 2 3 2 1 1 1 Addition of new operations 1 2 0 1 1 1 1 

Change factor 

Mill type 

Hardwood Hardwood Pole Sof two4 So f twood 

Chip mill sawmill veneer/plywood plants sawmil 1 ~ly~ad Paper mill 

(8 mills) ( 13 mills) (11 mills) (4 mills) (23 mills) (3 mills) (6 mills) 

Raw material used 

Procurement program 

Manufacturing process 

Products produced 

Markets served 

Sales program Closure/curtailment of 

existing operations 

Addition of new operations 

Scale: 0 = No change 

1-3 = Minor change 

4-6 = Moderate change 

7-10 = Major change 
Table 10--Curtailment or closure of operations due to Hurricane Hugo 

Mill sixe 

All responding Recrion Small Medium-small ~sd$um 

nonpaper mills Pr- PO I+arg"' ripheral Control (<20,000 tons) (20,000-79,000 tons) (80,000-200,000 tons) (>200,000 ton.) Change factor (63 d.lls) (23 mills) (31 mills) (9 mills) (16 mills) ( 18 mills) (15 dlls) (14 mills) 

........................................ of msponses------------------------------*-------------------- 

0 0 0 0 0 0 0 0 

Plant closed perwmently 1 0 1 0 1 0 0 0 

Temporary layoffs 2 1 0 1 1 1 0 0 

Temporary reduction in production 2 2 0 0 0 1 1 0 

Permanent reduction in production 2 2 0 0 0 1 0 1 

Portion of operation closed 5 3 1 1 1 1 2 1 

Postponement of growth plans 2 1 0 1 1 1 0 0 

Change in raw material source 1 0 1 0 1 0 0 0 

W No change 47 13 2 8 7 11 14 12 12 4 

Change factor 

Plant closed temporarily Plant closed permanently 

Temporary layoffs 

rary reduction in production Permanent reduction in production Portion of operation closed Postponement of growth plans Change in raw material source No change 
Table 11--Interest in followup program for alternative business strategies 

(nonpaper) 

Change factor 

Interested, 

Region, mill size, Number Want to but want more Not 

and mill type of mills participate information interested 

Region : 

Primary 

Peripheral 

Control 

Mill size: 

Small (<20,000 tons) 

Medium-sazall (20,000-79,000 tons) 

Medium (80,000-200,000 tons) 

Large (>200,000 tons) 

Mill type: 

Chip 

Hardwood sawnil1 

Hardwood veneer/plywood 

Pole 

Softwood sawmill 

Softwood plywood 

Fiberboard 

All responding nonpaper mills 63 5 33 25 

Table 12--Summary of affirmative responses from personal interviews of selected 

mills 

Number of responses, by reqion 

Primary Peripheral Control Total 

Impacts and concerns (13 mills) (19 mills) (9 mills) (41 mills) 

Major impact on timber raw-material 

procurement: 

Increased competition 

Increased stumpage/log prices 

Expanded procurement area 

Declining quality of available timber 

Little or no major impact 

Major impact on operationst 

Curtailed or closed operations 

Improving or expanding to increase 

efficiency 

Diversifying processing or adding 

secondary manufacturing 

Long-term major concerns: 

Ability to obtain low-cost financing 

Timber resource inadequate for 

current demand 

Reduced profitability 

Environmental constraints 

Rapid increase in hardwood 

demand by paper firms 

Increasing competition from 

larger firms 

Utilization of sweetgum and other 

less-desirable hardwoods 

Future survival questionable 
Table 13--Major business impacts and concerns as a result of Hurricane Hugo, by dl1 type and size, by region 

Mill type and 

size, by region 

Hill type: 

Pine sawmill-- 

Primary 

Peripheral 

Control 

Total 

Hardwood sawmill-- 

Primary 

Peripheral 

Control 

Total 

Pole plant-- 

Primary 

Peripheral 

Control 

Total 

Other-- 

Primary 

Peripheral 

Control 

Total 

Hill size: 

Small-- 

Primary 

Peripheral 

Control 

Total 

Medium-small-- 

Primary 

Peripheral 

Control 

Total 

Medium-- 

Primary 

Peripheral 

Control 

Total 

Large-- 

Primary 

Peripheral 

Control 

Total 

All regions: 

Primary 13 12 10 11 12 45 87 

Peripheral 19 17 17 14 15 63 83 

Control 9 9 9 7 4 29 81 

Total 41 38 36 32 31 137 8 4 
Table 14--Major business impacts and concerns on operations as a result of 

Hurricane Hugo, by region, mill size, and mill type 

Impacts on operations 

Region, anill size, NWer Closure or Increasing Diversifying 

and mill type of mills curtailment efficiency processing 

Region : 

Primary 

Peripheral 

Control 

Mill size: 

SInall 

Medium-small 

Medium 

Large 

Mill type: 

Pine sawmill 20 

Hardwood sawmill 11 

Pole plant 4 

Other 6 
Table 15--long-term major concerns as a result of Hurricane Hugo, by mill type 

and size, by region 

Mill type and 

size, by region of mills timber profits firms survival Total responses 

Mill type: 

Pine sawmill-- 

Primary 

Peripheral 

Control 

Total 

Hardwood sawmill-- 

Primary 

Peripheral 

Control 

Total 

Pole plant-- 

Primary 

Peripheral 

Control 

Total 

Other-- 

Primary 

Peripheral 

Control 

Total 

Mill size: 

Small-- 

Primary 

Peripheral 

Control 

Total 

Medium-small-- 

Primary 

Peripheral 

Control 

Total 

Medium-- 

Primary 

Peripheral 

Control 

Total 

Large-- 

Primary 

PeripheralControl 

Total 

tive responses------ --Percent-- 

All regionst 

Primary 

Peripheral 

Control 

Total 
Table 16--Response rate for combined negative factors as a result of Hurricane 

Hugo, by region, mill size, and mill type 

Affirmative response rate, 

by reqion 

Wegative factors Combined mills Prilnary Periphery Control Mean 

Increased competition for timber raw material 

Increased stmpage/log prices 

Expanded procur 

Declining quality of available 

timber raw material 

Curtailed or closed operations 

Timber resource inadequate for 

demand 

Reduced profitability 

Increasing competition from 

large firms 

All responses 61 61 Sf 59 

Mill size: 

Slnall 48 50 (.--.I 49 

Medium-small 72 58 64 61 

Medium 75 67 89 71 

Large 50 78 31 48 

Mill typer 

Pine sawmill 63 65 22 52 

Hardwood sawmill 56 83 56 71 

Pole plant 67 50 -. 58 

Other 56 41 28 39 

Future survival questionable 
FOREST RESTORATION 
Protection 

POST-HURRIC ST PEST POPU~TIONS AND 

( IMPACT0 IONES DE INSECTOS FOmST 

POSTERIOR AL HURACAN HUGO)' 

Harry 0. Pates XI1 and Thomas &filler2 

Abstract--On 21 September of 1989, Hurricane Hugo slammed 

into the coast of South Carolina just north of the city of 

Charleston. Winds of 135 miles per hour and tidal surges 

of 12 to 18 feet caused damage without precedent to personal property and forest areas, It is estimated that the 

volume of broken or uprooted trees represented approximately 6.7 billion board feet. Since this natural 

disaster, a great deal of time has been spent studying 

forest insects and their ability to damage the surviving 

trees. 

During the period 1990-1991, we maintained traps to determine the population levels of the reproduction weevils 

Hylobius pales (Herbst) and Pachylobius picivorus (Germar), 

Monochamus titillator (F.), the bark beetles Dendroctonus 

terebrans (Olivier), Ips spp. and Dendroctonus frontalis 

Zh. The populations of Ips were reduced significantly 

during 1991. Very few individuals of D. frontalis were 

captured during the two years. No tree damage or mortality 

was observed to the trees in the area affected by the 

hurricane. Collections and observations were made of 

pathogens that can affect the trees; however, no significant damage was observed. 

INTRODUCTION 

Mexico and the United States share the 

coast-line rimming the Gulf of Mexico 

from the Yucatan northward and easterly to Key West, FL. This coastline 

shares the common threat of hurricanes 

each year during the period June to 

November. These storms are spawned in 

the tropical regions of the North 

Atlantic Ocean and frequently move 

northerly and westerly into the Gulf 

of Mexico where they eventually strike 

land. The unpredictable nature of 

hurricanes makes it virtually impossible to predict with any certainty 

In Press, Proceedings of VI Simposio 

Nacional sobre Parasitologia Forestal 

October 8-9, 1991, Montecillos, Edo. 

de Mexico, Mexico 

Research Entomologist, Southeastern 

Forest Experiment Station, USDA Forest 

Service, Athens, GA; Research Plant 

Pathologist (Retired), Southeastern 

Forest Experiment Station, USDA Forest 

Service, Olustee, FL, USA 

their point of landfall any sooner than 

24 hours in advance. In addition to 

winds blowing in excess of 120 kilometers per hour, associated cloud masses 

produce exceedingly heavy rains and are 

apt to spawn numerous destructive 

tornados. The northeastern coast of 

Mexico most recently experienced the 

ravages of a hurricane in the fall of 

1988. This storm caused considerable 

destruction as far inland as the city 

of Monterrey. 

During the late evening of September 

21, 1989, an extremely dangerous 

hurricane with winds in excess of 215 

kilometers per hour slammed into the 

Atlantic coast of the United States. 

This hurricane was named "Hurricane 

Hugo," Hurricane Hugo's eye crossed 

the coast of the state of South 

Carolina just north of the city of 

Charleston. 

Hugo caused unprecedented property 

losses along the coastal areas with the 

complete destruction of entire housing 
developments. Adding to the windcaused destruction the 4-6 meter storm 

surge washed many fishing and pleasure 

boats inland along the coast. The 

most destruction was to the timber 

resource throughout the area, Those 

trees not blown over or broken by the 

force of the winds sustained varying 

degrees of root disturbance andlor 

loss of branches or photosynthetic 

leaf surface. This left the residual 

stands in a stressed condition that 

predisposed them to attack by insects 

and disease organisms. It is estimated that the timber losses caused by 

Hurricane Hugo was equal to the combined losses of Hurricanes Camille and 

Frederick, the Mt. St. Helen's eruption, and the Yellowstone fires of 

1988. Over 6.7 billion board feet of 

timber was destroyed. 

An immediate priority was to salvage 

as much of this timber as possible. 

This included the use of helicopters 

to remove logs from areas inaccessible 

by vehicle. Even with the tremendous 

harvesting effort that continued 

throughout the year following the 

hurricane, it is estdted that only 

25 percent of the damaged timber was 

harvested. In areas harvested or 

those too inaccessible to harvest, a 

tremendous quantity of broken trees 

and limbs covered the ground and soon 

became dry. This dry material created 

a serious fire hazard to the remaining 

forest trees and personal property 

within the forest. In order to reduce 

the threat of fire, a ban was imposed 

on all outdoor burning. Fire crews 

and equipment were also flown into the 

area from throughout the United States 

and Canada to combat fire. 

These forest conditions were particularly favorable for the buildup of 

some potentially damaging forest 

insects and diseases. Therefore, in 

the spring of 1990 studies were begun 

to monitor pest populations and 

damage. 

OBJECTIVES 

Research was begun in the Francis 

Marion National Forest in March 1990. 

The objectives were to study the population dynamics and successional 

development by species over time of 10 

primary and secondary forest insects 

(Table 1) and to identify and study 

the pathogens that attack damaged 

trees and their development and spread 

to adjacent damaged or healthy trees. 

MATERIALS AND mTHODS 

Adult insect populations were monitored 

using bounce traps (Fatzinger 1985). 

The trap consists of a 1 m diameter 

plastic wading pool approximately 25 cm 

deep. Placed vertically in the center 

of the pool is a 1 m tall black stove 

pipe about 30 cm in diameter. A plastic bottle containing a bait is secured 

at the top of the stove pipe. A wick 

slowly releases the contents of the 

bottle to the atmosphere. The bait 

consists of a 50~50 mixture of freshly 

distilled turpentine and 95 percent 

ethyl alcohol. Insects attracted to 

the trap generally fly to and bounce 

off the upright stove pipe known as the 

"bounce column" and fall into the pool 

or "catch basin," The catch basin is 

half-filled with water to which is 

added about 15 ml of household detergent to reduce surface tension and 

cause trapped insects to sink. 

During 1990, 35 bounce traps were 

located throughout the hurricaneravaged forest area. Traps were 

visited weekly throughout the summer 

and collections were returned to the 

laboratory for separation and identification of trapped insects. 

The extensive damage to trees provided 

a unique opportunity to evaluate the 

development of tree diseases. In 

particular, we wanted to look at the 

fungi attacking trees with seriously 

disturbed root systems. Efforts were 

concentrated within three general 

areas: (1) the hazard for the occurrence of the pitch canker disease, 

caused by Fusarium subglutinans 

(Wollenw. & Reinking) Nelson, Toussoun 

and Marasas, (2) the damage to lateral 

roots of Pinus sp. caused by the wind 

stresses and any resultant attacks by 

root pathogens, and (3) assessment of 

possible interactions between pine 

seedling damage by reproduction weevils 

and the pitch canker disease. 

Petri plates containing a medim 

selective for the pitch canker fungus 

(Nash and Snyder 1962) were exposed for 

approximately 24 hours in March 1990. 

Twenty-five plates were placed at ca. 

100-meter intervals around the 

periphery of an ca, 100 hectare stand 

of severely damaged pines and 

hardwoods. Another 23 plates were 

exposed in two areas; one planted two 

months earlier and the other planted in 

January 1989. 
Table 1--Coleoptera species monitored from bounce traps in the Francis Marion 

National Forest in South Carolina 

Family Scolytidae 

Ips avulsus (Eichhoff) 

I-. calliqraphus (Ge 

I. grandicollis (Eichhoff) 

Dendroctonus frontalis Zimmermann 

Do terebrans (Olivier) 

Family Curculionidae 

Hylobius pales (Herbst) 

Pachylobius picivorus (Germar) 

Pissodes nemorensis Germar 

Family Cerambycidae 

Monochamus titillator (F.) 

M. carolinensis (Olivier) 

Small southern pine engraver 

Sixspined Ips 

Eastern fivespined Ips 

Southern pine beetle 

Black turpentine beetle 

Pales weevil 

Pitch-eating weevil 

Eastern pine weevil 

Southern pine sawyer 

Carolina pine sawyer 

In March 1990, the root systems of 

Pinus taeda L. and P. palustris Mill. 

trees, ranging in d.b,h, from 11.5 to 

30.5 cm and in height from about 10 to 

16 m were examined by excavation. 

These trees were selected on the basis 

of wind-induced lean from the vertical 

and ranged from 0 (no lean) to about 

40". Samples of lateral roots were 

examined from the direction of lean 

and at 90° and 180" f rorn the lean. 

In August 1990, roots were excavated 

from 11 moribund P. taeda and P. 

palustris trees ranging in d.b.h. from 

10 to 41 cm and from 10 to 18 m in 

height. Emphasis was placed on roots 

with damage or symptoms that might 

indicate disease. Roots were returned 

to the laboratory for isolation procedures onto the Nash-Snyder medium and 

acidified malt extract agar. 

Also, in August 1990, P. taeda seedlings with damage caused by reproduction weevils, Hylobius spp. and 

Pachylobius spp., were collected for 

isolation procedures. 

RESULTS AND DISCUSSION 

Insects 

Five species of the family Scolytidae 

were monitored. These included three 

engraver beetles: Ips awlsus 

(Eichhof f ) , I. qrandicollis 

(Eichhoff), and I. calligraphus 

(Germar), and the bark beetles 

Dendroctonus frontalis (Zimmemann) 

and D. terebrans (Olivier). Within 

species of weevils were monitored: 

Hylobius pales (Herbst), Pachylobius 

picivorus (Germar), and Pissodes 

nemorensis (Germar). In the family 

Cerambycidae trap catches were monitored for the pine sawyers, Monochmus 

titillator (F.) and M. earslinensis 

(OPivier). 

The presence of severely weakened and 

stressed pines were a source for infestation by engraver beetles. Likewise, 

the large volume of fresh logs on the 

ground provided ideal conditions for 

the buildup of beetle populations. 

This beetle buildup is reflected in the 

high populations of engraver beetle 

trap captures in May and June following 

the hurricane (Figure 1). The dramatic 

drop in adult captors beginning in July 

coincides with the deterioration of the 

host material when it was no longer 

susceptible to attack. Adult captures 

during 1991 were extremely low. No 

significant buildup of engraver beetleattacked trees has been observed in the 

surviving forest stands, 

The black turpentine beetle breeds and 

feeds in fresh stumps or the trunks of 

weakened or damaged trees. Adult 

captures increased throughout the 1990 

summer to a peak in August (Figure 2). 

As with the engraver beetles, very low 

populations were recorded during 1991. 

This dramatic drop in population also 

reflects the deterioration of host 

material suitable for feeding and 

breeding, 

the family curculionidae, . three 
Mat 

Figure 1--WecrLly trap catches of Ips 

rpp. during 1990. 

... 

Mat Apt Jun Jul 

fg$) Trap Catches 

Figure 2--Wnkly trap catches of 

&ndrocrtolnu* ter~brmr during 1990. 

The southern pine sawyer attacks logs 

with the bark still intact. This 

secondary insect feeds and breeds in 

logs that have become dry. During 

1990 trap captures remained high 

(Figure 3). These high populations of 

adults continued throughout 1991 as 

well. This insect does not create a 

problem to the surviving trees or 

adjacent pine stands. 

The reproduction weevils, Hylobius 

pales and Pachylobius picivorus, pose 

a serious threat to natural pine 

reproduction or artificial regeneration (Nord and others 1982). 

Adults are attracted to areas where 

pines have recently been cutover or 

killed. Here they feed nocturnally on 

the inner bark of freshly cut slash 

and stumps. After this host material 

dries out, they feed on the inner bark 

of small twigs and stems of pine seedlings. Such feeding may result in 

seedling death. 

Mar &r Hay Jun Jul 

19% tlliIlator Trap Catches 

Figure 3--Weekly trap catches of 

Monoclhuaus titillator during 1990. 

Weevil populations built up through the 

1990 season (Figure 4). This build-up 

was anticipated since ample breeding 

material was available in the field. 

However, continued trapping of high 

weevil populations during the 1991 

season was not anticipated. With high 

weevil populations, we expected to find 

significant damage to recently planted 

meedlings and natural reproduction. mile some weevil-caused mortality has 

occurred the incidence has been 

extremely low--less than 3 percent-- 

compared to the adult weevil population. trapped. 

Jua Jul 

1990 Trap Catches 

Figure 4--Weekly trap catches of 

Hylobius pales during 1990. 

It remains a mystery on what these high 

weevil populations are feeding and 

where they are breeding. Furthermore, 

they do not appear to be causing significant seedling mortality. We plan to 

continue monitoring insect populations 

through 1992 in an attempt to answer 

some of these questions. Observations 
of and isolations from pine roots will 

also continue. 

Pathogens 

Roots of trees leaning at about 30° or 

less had no obvious damage. Roots of 

trees at >30° typically had roots 

broken and pulled apart from the 180° 

sample and either broken or severely 

bent in the 90" samples. Roots from 

the direction of the lean exhibited no 

apparent damage. Broken roots collected and taken to the laboratory for 

cultural isolations produced only some 

expected soil-inhabiting fungi. No 

potentially pathogenic organisms were 

isolated. Two Fusarium spp. and 

several isolates of a fungus with 

black, fluffy hyphae were obtained; 

however, they have not yet been 

identified. Identified species of 

Fusariuar recovered from the area 

include Fusarium anthophilm (A. 

Braun) Wollenw., F. oxysporum (Schl.) 

en. Snyd. & Hans, P. proliferaturn 

(Matsushha) Nirenberg, F. semiteeturn 

Berk. & Rav., and F. sulglutinans. 

S P 

The bark beetle explosion that was 

anticipated following Hurricane Hugo 

failed to materialize. Furthermore 

there was no indication of root disease 

development or significant pitch canker 

syntptoms observed over the period of 

observation. The will tell if 

reproduction weevils or root pathogens 

will become a serious threat to the 

residual pine forests and regeneration. 

LITERAW- CITED 

Fatzinger, C.H. 1985. Attraction of the 

black turpentine beetle (Coleoptera: 

Scolytidae) and other forest Coleoptera 

to turpentine-baited traps. Environmental Entomology 142768-775, 

Nash, S.M.; Snyder, W.C. 1962. Quantitative estimations by plate counts of 

propagules of the bean rot Fusarium in 

field soils. Phytopathology 52~567-572. 

Nord, J.C.; Ghent, J.H.; Thomas, H.A. 

[and others]. 1982. Control of pales 

and pitch-eating weevils in the south. 

U.S. Department of Agriculture, Forest 

Service, For. Rep. SE-FR-21. 24 p. 
REC NWIONS FOR SAILfllAGE AND ES 

RAPIDITY OF ImASION BY 'VARI 

ORGANISMS OF BURRIC RESOURCES 

Patrick J. ~arry' 

The area of immediate concern should 

be the severely damaged trees in the 

counties classed as having extensive 

and moderate timber damage. 

Salvage should be concentrated in 

stands with uprooted trees, root 

sprung (leaning) trees and trees with 

main stem breakage. 

If not salvaged promptly uprooted 

trees will probably be degraded by 

stains, decay, and secondary insects, 

such as bark beetles, borers, powder 

post and ambrosia beetles. The longer 

salvage is delayed, the greater the 

amount of degrade and weight loss from 

rapid drying. 

Root sprung trees will not die 

immediately, but will show decline 

symptoms over a period of several 

years. However, these trees may be 

invaded by root rot organisms, and 

subjected to drought stress and insect 

attack immediately. Root sprung pines 

may be invaded by bark beetles and 

blue stain fungi. These pines can 

serve as prime habitat for the 

southern pine beetle and if conditions 

become favorable, an outbreak could 

occur. They can also harbor high 

populations of turpentine beetles. 

Hardwood trees with major root damage 

should be salvaged as soon as possible 

to avoid a value loss from degrade. 

Trees with main stem breakage will be 

invaded by a variety of insects and 

disease-causing organisms. Hardwoods 

may not die but will be severely 

degraded by stain and decay fungi, 

Pines often will be infested and 

killed by bark beetles and infected 

with blue stain fungi. They can 

Entomologist, USDA, U.S. Forest 

Service, Forest Health Unit, 

Asheville, N.C. 

support high southern pine beetle 

populations immediately after breakage, 

but soon become unsuitable hosts, due 

to rapid drying and deterioration of 

the thin inner bark. Turpentine and 

bark beetles also commonly attack pines 

and can build to damaging populations 

in trees with main stem breakage. 

Other areas of concern but with a 

longer planning and salvage operational 

period a r e t h e moderate to lightly 

damaged timber stands. Stands with 

trees having broken tops or branches, 

major wounds and bent trees. 

Trees with broken branches that have 

exposed heartwood will be infected by 

stain and decay fungi at the point of 

injury. Stains will move vertically 

from the point of injury at a rate of 6 

to 18 inches per year, depending on 

tree species and decay organisms. 

Decay fungi will follow the stain fungi 

in about 8 to 10 months. Breaks 

smaller than 3 inches in diameter, with 

no heartwood exposed, may be infected 

by sapwood decay fungi with no serious 

economic losses. Some broken branches 

in the tops of pine species may be 

attacked by bark beetles and infected 

with blue stain fungi. Trees with 

broken terminals and major limb damage 

(breaks, 3 inches or larger) should be 

removed during the next scheduled 

harvest, 

Many trees sustain wounds caused by 

falling tops, adjacent uprooted trees, 

and major breakage. In hardwoods, 

wounds that do not penetrate more than 

2 inches into the sapwood and have less 

than 144 square inches of surface area 

will have only localized stain, but no 

decay. Larger wounds will have stains 

and decay that will move at the rate 

described for broken branches. Pine 

trees with major wounds to the lower 

bole and roots may be attacked by bark 

beetles . 
These trees should be removed during 

the next scheduled harvest. 

Bent hardwoods usually are not 

attacked by insects or disease because 

they are not severely stressed. Pine 

trees that are bent to the extent that 

cracks and resin flow occur may be 

invaded by bark beetles and diseasecausing organisms. 

Severely bent hardwoods should be 

salvaged during the next scheduled 

harvest. Inspect large pine timber 

for pitch flow, Many large, green 

standing pines may not be usable for 

veneer, poles, or lumber because of 

internal ring shake, splintering, and 

separation of wood fibers. Often the 

only external incidence of such damage 

is pitch flow. The characteristics 

are often overlooked, and considerable 

losses are incurred during a later 

harvest. 

Another problem which could occur over 

the long-term period is some damage to 

pine reproduction planted in the next 

two years. 

Reproduction weevils can build up in 

the stumps and heavy slash lying on 

the ground at the current time and in 

stressed trees that will be dying over 

time during the next two to three 

years. 

High value trees, such as those in 

recreation areas, camp grounds, and 

seed orchards should receive special 

management considerations as follows: 

(1) Properly prune broken branches to 

promote rapid healing, 

(2) Spray residual pine trees with an 

insecticide to protect them from 

bark beetle attack. 

(3) Complete a sanitation salvage 

operation of trees previously 

described above as severely 

damaged (uprooted, severely root 

sprung trees and trees with main 

stem breakage) . 

(4) Make sure the salvaged material 

is disposed of properly or 

removed from the area as soon as 

possible. 

(5) Treat stumps in the seed orchard 

with insecticide to prevent black 

turpentine beetle build up. 

The area affected by Hurricane Hugo 

could have insect activity through mid 

November, particularly bark beethe 

activity 

Date: October 9, 1989. 
Red-Cockaded Woodpecker 

HURRICALJE HUGO'S INITIAL EFFECTS ON 

=I)-COCWEI) WOODPECKERS IN 

ION NATION= FOREST 

Robert G. Hoopet, J. Craig Watson, and Ronald E. P. ~scano' 

The Francis Marion National Forest 

(FMNF) in coastal South Carolina had 

the premier population of red-cockaded 

woodpeckers (Picoides borealis), a 

federally-listed endangered species. 

The population was the densest, the 

second largest and the only one known 

to have been increasing (Costa and 

Escano 1989). On the evening of 21 

September 1989, Hurricane Hugo scored 

a direct hit on the FMNF. Immediate 

damage to the forest in the form of 

broken and wind-thrown trees was 

severe. Most of the cavity trees 

essential for woodpecker nesting and 

roosting, as well as mek sf its 

foraging habitat were destroyed. Many 

of the woodpeckers were probably 

killed. 

This paper documents the initial 

impact of Hugo on red-cockaded woodpeckers in the FMNF, describes the 

immediate restoration effort and puts 

Hugo in historical perspective. Given 

that hurricanes are not rare events, 

we discuss possible strategies for 

lessening their impacts on this endangered species. 

IMPACT ON THE RED-COCKADED 

WOODPECKER 

Red-cockaded woodpeckers depend on the 

cavities they excavate in living pines 

for nesting and roosting. Excavation 

typically requires several years. 

Completed cavities are generally used 

for several years and sometimes for as 

long as 20 years. Cavity trees are 

critical to the woodpecker, and the 

lack of potential trees for cavity 

excavation is a primary reason the 

species is endangered (USFWS 1985). 

After Hugo, Forest Service biologists 

attempted to visit all known colony 

sites (clusters of cavity trees) to 

assess damage and prescribe emergency 

management. The damage estimates that 

follow are based on these visits. 

Ninety-nine percent of all known colony 

sites were visited and 91 percent were 

censused for surviving woodpeckers, 

Hugo destroyed 87 percent of the estimated 1765 cavities that were active 

prior to Hugo (ones with evidence of 

recent use by the bird). At 47 percent 

of colony sites that were occupied by 

red-cockaded woodpeckers before the 

storm, all the trees with active, 

inactive and incomplete cavities were 

destroyed. At 57 percent of colony 

sites with woodpeckers prior to Hugo, 

all trees with active cavities were 

destroyed. 

In the 205 colony sites that had at 

least one active- cavity remaining af t 

the hurricane, the average number of 

active cavities was only 1.9. In 198 

the number of active cavities per 

colony averaged 3.7 in 100 randomly 

selected colony sites. Thus, the 

quality of surviving colony sites was 

less than prior to Hugo. 

Onlv 10 dead red-cockaded woodpeckers 

Robert G. Hooper, USDA Forest 

Service, Southeastern Forest 

Experiment station, Charleston, South 

Carolina; J. Craig Watson, USDA Forest 

Service, Francis Marion National 

Forest, Moncks Corner, South Carolina; 

Ronald E.F. Escano, USDA Forest 

Service, Southern Region, Atlanta, 

Georgia. 

wer; found. However, based on- the mean 

number of surviving birds per colony 

(1.5) and the mean number of birds per colony determined in prior years for 

October (4.0), we estimate that 63 

percent of the woodpeckers in FMNF were 

killed or missing. Seventy-seven 

percent of all colony sites, 89 percent 

of sites with surviving cavity trees, 
and 52 percent of those with no 

surviving cavity trees still had 

woodpeckers after the hurricane, 

In 1987-88 there was an estimated 477 

family groups of from 2-9 red-cockaded 

wodpeckers (clan) in the FMNF, After 

the hurricane there were 240 colony 

sites with some surviving cavity trees 

(active, inactive or incomplete 

cavity) that still had 1 or more 

woodpeckers. Another 128 former 

colony sites without any surviving 

cavity trees still had 1 or more 

birds, Thus, the most optimistic 

estimate for the post-Hugo population 

is 368 clans, However, only 67 

percent of these had the 2 or more 

birds necessary for a potentially 

functional clan, Even under the best 

of conditions it is unlikely that all 

of these will survive for more than 1 

year following the hurricane, We 

expect a continued loss of clans 

before the population stabilizes, 

When this occurs and where the population will be at the time depends on 

survival of birds over-winter without 

cavities, the success of single birds 

in finding mates, survival of the 

remaining cavity trees, survival of 

foraging habitat in the face of wildfire and beetle attacks, the juxtaposition of remaining foraging habitat 

to colony sites, reproductive success 

in the next few years, the rate of new 

cavity excavation, interspecific 

competition for cavities, and the 

success of restoration efforts. 

IMPACT ON THE FORElST 

The destruction of pines that were not 

cavity trees was also severe. Quantitative data are not yet available, 

but it is thought that at least 50-60 

percent of the pine sawtimber trees on 

the FMNF were destroyed. These trees 

served as foraging habitat and 

replacment cavity trees, Not all 

pine stands were affected equally by 

winds of the same force. Damage to 

the forest appeared to be a function 

of both tree age and number of trees 

per acre, Sapling and young pole 

stands were frequently heavily 

damaged, but many of these may still 

be manageable without regeneration, 

Many stands in the 30-40 year age 

class escaped with moderate damage. 

Mature pine stands (more than 80 years 

old) with low to moderate basal areas 

(about 70 square feet per acre or less 

[16,1 m2/ha]) typically had less than 

10 square feet per acre (2.3 m2/ha) in 

standing trees after the hurricane, 

Unfortunately, such stands are the 

most valuable to the red-cockaded 

woodpecker as both existing and potential new colony sites. Mature pine 

stands with high basal areas (more than 

90 square feet per acre 120.7 m2/ha]) 

escaped some of the strongest winds 

with moderate damage. 

Hugo set the stage for a continuing 

process of destruction to the forest. 

Pines that survived the hurricane are 

subject to attack from engraver beetles 

(Ips spp.) and turpentine beetles 

(Dendroctonus terebrans), Additional 

trees will die from these attacks, 

Many of the pines that appear to have 

survived suffered root, bole and crown 

damage that will contribute to additional mortality, Also, with the 

enormous fuel loads the chance of a 

catastrophic wildfire is great. Only 

time will determine the final loss to 

the forest from Hurricane Hugo, 

HUGO IN PERSPECTIVE 

Hugo is called a "Cape Verde hurricane" 

because of its origin near Africa 

(Lawrence 1989). Only a small percentage of such hurricanes make landfall 

in the United States, but of the 13 

that have since 1906, 9 were major 

hurricanes (category 111-IV) (USACE 

1986). 

Hugo was a powerful category IV hurricane with maximum sustained winds 

estimated at 135 mph (217 km/hr) at 

Bulls Bay 20 miles (32 km) north of 

Charleston, S,C. (Lawrence 1989). Near 

the coast, hurricane force winds (more 

than 74 mph [I19 km/hr]) appeared to 

have occurred in a band at least 55 

miles (86 km) wide, The eye was about 

24 miles (39 krn) wide (J,V, Purvis, 

pers. comm,). Sustained winds of 

hurricane force occurred at least 90 

miles (145 km) inland and gusts of 80 

mph (129 km/hr) were reported at 

Hickory, N,C., 220 miles (354 km) 

inland (Lawrence 1989). 

Approximately 14 other hurricanes 

approaching or exceeding Hugo's 

strength have made landfall within the 

range of the red-cockaded woodpecker 

(Texas to Virginia) since 1899 (NOAA 

1977, USACE 1986). Thus, such a storm 

occurs in the birds range about every 

six years. Over 100 lesser hurricanes 

have made landfall during the same 

period (Neumann and others 1987). 

In South Carolina, the periodicity of 

hurricane landfall is about every six 

years (about 34 between 1786-1985) 

(Langley and Marter 1973, USACE 1986). 

A probable category IV hurricane landed 

in South Carolina in 1893 and another 
in 1954 (USACE 1986). Including Hugo, 

South Carolina has had three category 

IV hurricanes in the past 96 years. 

Experts consider Hugo to be a 1 in 100 

year event in South Carolina (J. C. 

Punis, pers. coma.). 

Since 1700, there appear to have been 

about 18 hurricanes that probably affsted the FNNF (Langley and Marter 

1973, Calhoun 1983, USACE 1986, 

Neumann and others 1987). These data 

suggest the FHNF is subjected to 

hurricane-force winds about every 16 

years, This estimate may be inflated 

because it is impossible to get 

specific information about the early 

hurricanes. However, the mean elapsed 

time between hurricanes is fairly 

stable across centuries (1700s = 16.7, 

1800s = 14.3, and the 1900s = 17.8). 

Clearly, not all these hurricanes had 

the same effect as Hugo, but cavity 

trees are at risk relatively frequent ly , 

RESTORATION EFFORTS 

Cavity excavation typically takes more 

than one year, and most clans without 

cavities probably would not survive. 

Artificial cavities are being constructed in colony sites where there 

are less than two natural cavities in 

good condition and at least a minimal 

amount of foraging habitat remains. 

Several experimental techniques are 

being used. The first involves 

drilling two intersecting holes and 

then plugging one to create a cavity. 

An abbreviation of this procedure 

involving one drilled hole to form a 

partially completed cavity is also 

being used. These two techniques were 

developed by Carole Copeyon, a graduate student at North Carolina State 

University. A third technique, 

developed by David Allen, a Forest 

Service biologist, involves inserting 

a preconstructed cavity into a rectangular hole cut into a pine tree 

with a modified chainsaw. 

At this writing (15 March), 470 artificial cavities have been installed in 

154 colony sites in most irnrnediate 

need of cavities. These sites require 

additional artificial cavities as do 

nearly 100 other sites with inadequate 

or unsuitable cavity trees surviving. 

At least 40 percent of the artificial 

cavities are in use. In time we think 

nearly all will be used. Copeyon 

(pers. coxnm.) has had red-cockaded 

woodpeckers nest successfully in the 

drill cavities, Thus far, birds have 

not had an opportunity to nest in the 

preconstructed cavities (Allen, pers. 

corn.). Hopefully, the mn-made 

cavities will sustain the population 

long enough for the birds to excavate 

their own cavities. 

Effort is being made to salvage as much 

of the approximately 1 billion board 

feet of destroyed t er as pssible. 

Salvage benefits the red-cockaded 

woodpecker by reducing both fire and 

beetle hazard, and offers a better 

chance to control adverse midstory 

conditions that would be severely 

detrimental to the red-cockaded woodpecker. Unfortunately, less than 25 

percent of the salvageable timber will 

probably be removed before it deteriorates. To benefit the woodpecker, all 

standing live pines, unless leaning 

more than 45 degrees (and thus most 

likely to have sustained fatal root 

damage) are being retained during the 

salvage. 

Fire suppression efforts are intense. 

They are aimed at preventing fires 

through construction of about 100 miles 

(160 km) of fuel breaks and through 

public education, and at the rapid 

detection and suppression of fires. 

Thus far since the hurricane, 49 wildfires have been suppressed before they 

could develop into a major fire. 

DISCUSSION 

The red-cockaded woodpecker and the 

coastal plain forest evolved with 

hurricanes. A review of hurricane 

periodicity shows that hurricanes are 

not rare events in the southern coastal 

plain. Even major hurricanes such as 

Hugo should not be considered rare in 

the context of providing habitat for a 

viable population of red-cockaded 

woodpeckers in perpetuity. The question is not if a hurricane will hit, 

but when. Given that truism, a more 

important question is how then to 

protect the red-cockaded woodpecker in 

the face of continuing disasters. 

The best biological answer is appealing 

but impractical: revert back to preColumbian conditions. In that era, 

hurricanes no doubt destroyed large 

areas of red-cockaded woodpecker habitat and killed large numbers of the 

birds, but had relatively little impact 

on the species as a whole. NOW, with 

the bird existing in habitat islands, 

hurricanes are a menace to the species. 

The next best answer is to have as many 

geographically large populations as 
possible. An extensive population is 

desirable because a single hurricane 

is less likely to destroy the entire 

population beyond the point that it 

can recover. Cooperative managment 

agreements with owners of private land 

adjacent to public land with redcockaded woodpeckers may be the most 

practical way to increase the geographic extent of a population. 

More study is needed, but we are 

intrigued by the apparent direct 

relationship between stand density 

(trees per acre) and tree survival. 

Others have observed a similar 

relationship following hurricanes 

(Trousdell 1955, Trousdell and others 

1965). It might be possible to 

"hurricane proof" a forest by having 

more densely stocked stands of pine 

than is currently practiced. Survival 

of pine stands appears to be age 

related also. Thus a balance of age 

classes and a spatially uniform 

distribution of stands within age 

classes seems beneficial. Cavity 

trees appear to be two to four times 

more vulnerable than trees without 

cavities and we doubt that many could 

survive hurricane force winds. However, the more foraging habitat and 

potential cavity trees that survive a 

hurricane, the more probable the 

recovery of a population. 

The damaging effects of hurricanes are 

well delineated geographically and 

damage lessens as one moves out from 

the area of most intense winds. For 

example, with Hugo, cavity trees were 

destroyed in a band 52 miles (84 km) 

wide, but loss of cavity trees varied 

from more than 90 percent to less than 

40 percent within this band. Thus, 

having colony sites uniformly dispersed within the geographic limit of 

a population (as opposed to having 

most of the colony sites clumped in 

one area) would lessen the chance of 

losing an entire population. 

mFERENCES CITED 

Calhoun, J.A. 1983. The scourging 

wrath of God: early hurricanes in 

Charleston, 1700-1804. Leaflet 29. 

Charleston Museum, Charleston, S.C. 

Costa, R.; Escano, R.E.F. 1989. 

Red-cockaded woodpecker status and 

managment in the southern national 

forests. USDA For. Serv., Southern 

Region, Atlanta, Ga, Tech. Pub. 

R8-TP 12. 

Langley, T.M.; Marter, W.L. 1971. The 

Savannah River plant site. DP-1323. 

U.S, Atomic Energy Comm. 

Lawrence, M. 1989. Preliminary report 

Hurricane Hugo. National Hurricane 

Center. Coral Gables, Fla. 

Neumann, C.J.; Jarvin, B.R.; Pike, A.C. 

1987. Tropical cyclones of the North 

Atlantic Ocean, 1871-1986. Historical 

Climatology Series 6-2. National 

Climatic Data Center, Asheville, N.C. 

NOAA 1977. Some devastating North 

Atlantic hurricanes of the 20th 

century. Nat. Oceanic and Atmospheric 

Admin., Washington, D.C. 

Trousdell, K.B. 1955. Hurricane damage 

to loblolly pine on Bigwoods Experimental Forest. Southern Lumberman 

191:35-17. 

Trousdell, K.B.; Williams, W,C.; 

Nelson, T.C. 1965. Damage to recently 

thinned loblolly pine stands from 

Hurricane Donna. J. Forestry 63:96-100. 

USACE 1986. South Carolina hurricane 

evacuation study. U.S. Army Corps of 

Eng., Charleston, S.C. 

USFWS. 1985. Red-cockaded woodpecker 

recovery plan. U.S. Fish and Wildl. 

Serv., Atlanta, Ga. 

Reprinted with permission from 

Transactions 55th North American 

Wildl ife and Natural Resources 

Conference, Denver, CO. 1990. p, 220- 

224. Richard E. McGabe, Editor, 

Wildlife Management Institute, 1101 

14th St., NW, Suite 725, Washington, 

DC . 
ECONOMIC VALUATION OF THE RED-COCRADED 

WOODPECKER AND ITS HlABITAT 

Dixie Watts Reaves, Randall A. Kramer, Thomas P. ~olmes' 

Abstract--The issue of how to assign economic values to 

goods which are not traded in the marketplace is a controversial one. When goods have no proxy in an established 

market, a non-market valuation technique can be used. 

Natural and environmental resources generally fall into 

this category, and the endangered red-cockaded woodpecker 

(Picoides borealis) (RCW) is one such example. The 

red-cockaded woodpecker population and its habitat in the 

Francis Marion National Forest (near Charleston, South 

Carolina) suffered damages from Hurricane Hugo. The economic value of these losses was assessed using the contingent valuation method (CVM). A hypothetical market was 

developed for the good to be valued, and individuals were 

asked how much they would be willing to pay for the good, 

contingent on the described setting. Individuals were 

asked to value different population restoration levels of 

the RCW in Francis Marion National Forest, to value 

restoration of the Francis Marion National Forest if the 

endangered RCW did not exist there, and to value more 

intensive management of all RCW populations in the United 

States. Data were collected by mail survey from a randomly 

drawn national sample. Results indicated that individuals 

were willing to pay between 8 and 14 dollars, on average, 

for restoration activities. 

BACKGROUND AND JUSTIFICATION Since the U.S. Forest Service is 

With the renewed interest in environ- mandated to manage for multiple uses, 

mental quality, recent research has there is a specific need for the 

focused on improving methods to value valuation of these non-market goods: 

environmental- amenities. In order to 

value the commercial components of an 

environmental good, one merely uses 

market prices. However, there is 

often a need to value non-market 

components, and that was the focus of 

this research: to use the contingent 

valuation method (CVM) to determine 

the social value of protectinq and 

The Forest Service, U.S. Department of Agriculture, is dedicated to the principle of multiple use management of the 

Nation's forest resources for 

sustained yields of wood, water, 

forage, wildlife, and recreation 

(USDA Forest Service). 

restoring the endangkred red-cockaded 

woodpecker (RCW) and its habitat, the The Forest Service, given this multiold-growth longleaf pine (Pinus ple use mandate, needs to know how to 

palustris) ecosystem. allocate limited budgets among competina needs. In an economic sense, the 

Department of Economies, Duke University, Durham, NC; School of the 

Environment, Duke University, Durham, 

NC; USDA Forest Service, Southeastern 

Forest Experiment Station, Research 

Triangle Park, NC 

~osest Service needs to know the 

appropriate weights to use in a 

multiple use objective function. 

Market prices can be used as the 

weights for commercial outputs of a 

National Forest, but non-market 

techniques must be used to estimate 

weights for the non-commercial 

outputs. 
The Longleaf Pine Ecosystem 

The longleaf pine ecosystem, ranging 

naturally from Virginia to Florida and 

west to Texas, is one of the most 

unique and diverse ecosystms in the 

temperate zone. It serves as habitat 

for nmerous species including deer, 

quail, turkey, and squirrel, as well 

as providing forage for cattle, It is 

also home to the RCW, a federallylisted endangered species. The 

longleaf pine forest, when regularly 

burned, has an open, park-like 

appearance, and provides numerous 

recreation opportunities. The longleaf 

pine is an excellent timber tree, 

offering a wide range of forest 

products. Given its characteristics, 

the longleaf timber type is well 

adapted to multiple-use management 

because of the many forest products it 

supplies, the forage it produces, the 

wildlife it supports, and the recreation it affords (Boyer and Peterson 

1983). 

Only the forest product component of 

the longleaf pine ecosystem is valued 

in the marketplace. One objective of 

this research was to provide the U.S, 

Forest Service with an estimate of 

value for some of the non-commercial 

components. Valuation focused on one 

particular geographic component of the 

overall ecosystem (the Francis Marion 

National Forest), as well as one 

particular species (the RCW) which 

uses the old-growth longleaf pine 

forest as habitat. 

Hurricane Hugo 

On the evening of September 21, 1989, 

Hurricane Hugo scored a direct hit on 

the Francis Marion National Forest 

(FMNF), located in coastal South 

Carolina. The FMNF contained a 

significant remnant of old-growth 

longleaf pine forest, and served as 

the home to the RCW. The RCW population in the FMNF was the densest, 

the second largest, and the only known 

naturally increasing population. Most 

of the RCW cavity trees for nesting 

and roosting were destroyed (87%), 

much of its foraging habitat was 

damaged (50-60%), and many of the 

birds were killed (63%) [Hooper and 

others 19901. The Forest Service is 

mandated by the Endangered Species Act 

to take steps to recover the species, 

and much restoration work has already 

been carried out, including the drilling of artificial cavities (Watson and 

others 1994). For future management 

decisions, the Forest Service needs to 

assess the benefits and costs of 

further restoration, and of potential 

prevention of similar destruction. 

Thus, they need estimates of the value 

of the endangered species, its 

habitat, and the unique ecosystem in 

which it lives. This valuation can be 

extended beyond the damages to FMNF to 

include the overall valuation of the 

unique and diverse old-growth longleaf 

pine ecosystem which serves as habitat 

for the RCW. 

STUDY OBJIECTIVES 

Since these environmental goods are 

not typically valued in the marketplace, non-market valuation can be 

employed to estimate values f o r t h e 

goods, The contingent valuation 

method (CVM) was used to determine 

dollar values for the following: 

(i) restoration of the RCW population to two different population 

levels in the Francis Marion 

National Forest in South 

Carolina, 

(ii) preservation of all RCW populations in the United States, and 

(iii) restoration of the Francis 

Marion National Forest if the 

RCW did not exist there. 

A second objective of this research 

was to make contributions to the nonmarket valuation literature by testing 

hypotheses about the values obtained 

when using the contingent valuation 

method. 

THE VALUATION OF NON-MARKET 

GOODS 

Non-market goods are goods for which 

markets are nonexistent, incomplete, 

or institutionally restrained from 

reflecting the free interplay of 

supply and demand (Peterson and 

Randall 1984)- Two common characteristics of non-market goods are 

nonrivalry, where consumption by one 

individual does not decrease the 

amount of the good available to other 

individuals (up to the point of 

congestion), and nonexclusiveness, 

which results from incomplete property 

rights. One public good that fits 

this category is the nation's highway 

and bridge system. Less common 

examples of this type of good are 

ecological diversity and stability, 

and the continued existence of endangered species. These environmental 

amenities can be enjoyed by many 

people simultaneously, either through 

sight-seeing, reading about them, 

looking at photographs, or just 

appreciating the fact that they exist 
in an undisturbed state, This represents the non-rivalry characteristic 

of the goods, The fact that these 

amenities can be enjoyed by people who 

do not pay directly for the preservation of the goods represents the 

nonexclusiveness of the goods. 

When prices do not exist for goods in 

the market place, or when prices are 

institutionally set and do not truly 

reflect consumer preferences, such as 

in park entrance fees, some method of 

valuation is needed, Economists often 

turn to Hicksian measures (Mitchell 

and Carlson 1989)- An equivalent 

measure is the amount of compensation, 

paid or received, which would bring 

the consumer to his subsequent welfare 

level if the change did not take 

place, For example, if environmental 

quality increases from Q to Qf, an 

individual's utility increases from U 

to Uf. If quality did not increase, 

willingness to accept (WTA) indicates 

the amount that the individual would 

have to be paid to attain utility 

level U'. Another Hicksian measure 

is the compensating measure and is the 

amount of compensation, paid or 

received, which would keep the consumer at his initial welfare level if 

change did occur, As an example, 

consider the case described above 

where an increase in quality from Q to 

Q' leads to an increase in utility 

from U to Uf. Now, assume the change 

does take place, Willingness to pay 

(WP) indicates the amount of money 

that one could take from the consumer 

and leave him or her at the initial 

utility level, U. 

There are 4 Hicksian measures. In the 

compensated case, WTPC refers to the 

willingness to pay for an increase in 

Q and is a measure of individual 

benefit. For example, an individual 

might be willing to pay to ensure a 

higher population level of the RCW* 

WAC refers to the willingness to 

accept a decrease in Q and measures 

individual costs or negative benefits. 

On the other hand, the equivalent 

measure, WTPe, is the willingness to 

pay to avoid a threatened decrease in 

Q (for example, a decrease in RCW 

population size), and WTA" is the 

willingness to accept compensation in 

lieu of a promised increase in Q. In 

this study, both types of willingness 

to pay measures were estimated. 

Benefit-Cost Analysis (BCA) is one 

empirical test for potential Paretoimprovements (PPIfs). A PPI is one 

where those who would gain from a 

proposed change could compensate those 

who would lose, to the full extent of 

their perceived losses, If this were 

the case, i,e, if the sum of the 

money-valued gains as judged by the 

gainers exceeded the sum of the moneyvalued losses as judged by the losers, 

then the change would be acceptable, 

In order to make use of the benefitcost criterion in public policy decisions concerning environmental goods, 

one must have monetary measures of 

benefits and costs, Shaw (1984) 

raises 3 key questions that are 

relevant for the valuation of 

environmental resources: 

(i) What are the environmental 

products that are being valued 

(recreational, aesthetic, educational, biological, social, 

andlor commercial uses)? 

(ii) Who is benefitting from the 

resource (direct consumptive 

users, direct nonconsumptive 

users, and indirect or vicarious 

users ) ? 

(iii) How well can the resource value 

be assessed in quantitative 

terms (i-e,, how precise and 

valid are the valuation 

approaches, and how much of the 

total resource is being valued)? 

This research addressed these 3 questions as they related to the valuation of restoration of Hurricane Hugo 

damages to the FMNF and the valuation 

of the unique ecosystem, the oldgrowth longleaf pine forest, 

EMPIRICAL APPLICATION OF THE 

CONTINGENT VALUATION METHOD 

The CVM is based on utility theory 

where an individual derives utility 

from market goods, X, and non-market 

environmental goods, Q, and maximizes 

that utility subject to a budget 

constraint, Borrowing from Bergstrom 

and Stoll (1987), let a multidimensional non-market good be denoted as 

where, in this case, Q is the forest 

ecosystem and each ai is a component 

the ecosystem (e.g., the RCW), The 

components of Q are assumed to be 

provided in quantities exogenously 

determined by policy. An individual 

consumer's utility function can be 

defined as 
where S is a vector of attributes of 

the individual that may affect preferences (e.gl, age, sex, and 

participation in outdoor activities), 

Each component of Q is assumed to have 

positive marginal utility: 

Simply stated, an increase in the RCW 

population increases the individual's 

utility. 

Suppose a policy change will increase 

all components of Q from the original 

level, Q0 = Q (a,,, a,,, . . . a,,) , to some 

higher level, Q' = Q (a,, , a,, , . . . a,, ) . To 

determine willingness to pay for this 

increase in p, one needs to specify 

the indirect utility function, which 

is derived by maximizing utility with 

respect to the budget constraint, and 

substituting the resulting demand 

equations into the utility function. 

This yields the indirect utility 

function, 

V=V[P, P(al, a,, . . . ,a,) , M; Sl , 

where P is the price vector for market 

goods and M is money income, The 

expenditure function is the inverse of 

the indirect utility function, 

which is derived by minimizing expenditures subject to attaining a given 

level of utility, U*. 

The derivative of the expenditure 

function, with respect to Q, yields 

the inverse Hicksian demand function 

for changes in all components of the 

non-market good, Q: 

where g is the marginal willingness to 

pay (WTP) for a change in Q, the 

vector of ecosystem outputs, Total 

WTP for a non-marginal change in Q 

from Q0 to Q1 is calculated as 

one may also be interested in calculating the willingness to pay for an 

increase in one component of Q, say a,, 

the RCW population, This can be done 

by differentiating the expenditure 

function with respect to a, while 

holding all other components constant. 

The resulting Hicksian demand function 

for a, is denoted by 

Z represents the marginal WTP for a 

marginal change in a,. Total WTP for a 

change in a, from a,, (the current RCW 

population size) to a,, (the desired 

RCW population size) can be calculated 

by integrating the Z function from a,, 

to a,,, This is one value that was 

estimated in this research project 

using the contingent valuation method. 

WTP for other components can be 

derived theoretically in the same 

manner. 

For the environmental commodities of 

interest in this study (an endangered 

species, its habitat, and associated 

ecosystem), the primary sources of 

value are off-site use (e,g., viewing 

photographs and watching television 

specials) and the knowledge of their 

existence. Randall, Hoehn, and 

Swanson (1990) state that current 

methodology suggests the measurement 

of off-site values concurrently with 

existence values in a contingent 

valuation framework, Willingness to 

pay for an improvement in the commodity can be denoted EV (as in existence 

value), where EV is calculated as the 

decrease in income that the consumer 

is willing to accept in order to 

achieve an increase in Q. Initial 

utility is equal for initial levels, Q* 

and M, and subsequent levels, Q1 and MEV: 

The preference shifter, S, will be 

suppressed in future discussion. For 

the purposes of this study, the vector 

Q can be thought of as representing 

the unique and diverse old-growth 

longleaf pine ecosystem. Components 

of the ecosys-tem include numerous 

plant and animal species, including 

the endangered RCW. Individuals were 

asked to value the specific species, 

the speciesf habitat, and the ecosystem in and of itself. 
A NATZONA*L SUEZlllEY: 

DXSCUSSXOH AM3 RESULTS 

To elicit individual consumers* values 

for the goods in question, DillIran's 

(1978) Total Design Method (TDM) was 

used in a mail survey, In a pretest, the survey was sent to 200 individuals: 50 in South Carolina, 50 in 

Mississippi, 50 in Indiana, and 50 in 

Montana, A griori, it is expected 

that those people in the states where 

RCW exists ( i n t h e pretest, South 

Carolina and Mississippi) were more 

likely to be aware of the good, to 

have a positive value for the good, 

and to respond to the survey to 

indicate that value. 

The goals of the pretest were to test 

the survey instrument, to determine 

appropriate dollar value ranges to use 

in the full survey, and to obtain some 

preliminary estimates of value for RCW 

population restoration, The overall 

response rate for the pretest was 21%. 

This level of response is to be 

expected for a mail survey which 

included only a reminder postcard 

follow-up. As expected, individuals 

in South Carolina seemed more concerned dos the good in question, as 

proxied by their higher response rate 

to the survey (26%). Since the longleaf pine ecosystem and the RCW are 

also found in Mississippi, but not in 

Indiana or Montana, it was expected 

that Mississippi, too, would have a 

higher interest in the good and, 

therefore, a higher response rate. 

This was not true, however, as both 

Mississippi and Indiana had a response 

rate of 20%. Seventeen percent of the 

individuals surveyed in Montana 

responded to the survey. 

In terms of the valuation questions, 

the pretest was not meant to reveal 

final valuations, but rather to give 

an idea of the range of expected 

values, The valuation questions were 

prefaced with a discussion of the 

contingent setting: first, individuals were asked to assume that the 

Endangered Species Act would not be 

reauthorized by Congress this year. 

Therefore, there would no longer be a 

federal mandate for the protection of 

endangered species, and there would be 

no provision for further federal 

funding for their protection. They 

were then informed of the hurricane 

damage to the RCW population in the 

Francis Marion National Forest. The 

probability of population survival was 

stated for different population sizes: 

at the post-hurricane population size, 

the population had a 50% chance of 

survival if minimal restoration 

activities were undertaken; if no 

restoration activities were undertaken, the population had a 0% chance 

of survival; and if intensive restoration activities were undertaken and 

the population was returned to its 

pre-hurricane size, it had a 99% 

chance of survival, These probabilities of survival were chosen so as to 

be able to estimate how individuals 

value the reduced risk of losing the 

population, 

Given the contingent setting, individuals were asked how much they would 

be willing to pay into an independent 

foundation whose sole purpose would be 

the protection and restoration of the 

RCW, Four separate valuation questions were asked: 

(i) How much would you be willing to 

pay into the preservation fund 

each year to keep the population 

chance of survival at 50% and to 

prevent it from dropping to O%? 

(ii) How much would you be willing to 

pay every year, over and above 

the amount already stated, to 

improve the population's chance 

of survival from 50% to 99%? 

(iii) Rather than paying into a fund 

to restore and protect one 

single population, how much 

would you be willing to pay each 

year into a preservation fund to 

give all remaining RCW populations in the United States a 99% 

chance of survival? 

(iv) Suppose the RCW did not exist in 

FMNFo How much would you be 

willing to pay to restore that 

ecosystem to its pre-hurricane 

condition? 

The average willingness to pay for 

each of the 4 valuation questions fell 

in the 8- to 13-dollar range. Individuals in South Carolina had the highest valuations as expected, followed 

by Indiana, Montana, and ~ississippi. 

Individuals were willing to pay twice 

as much, or more, for the higher 

probability of survival, indicating 

the higher value people place on 

reduced risk. However, they were not 

willing to pay substantially more for 

the restoration and protection of all 

U.S. populations versus a single 

population. This may indicate that a 

large component of the value that 

people place on endangered species is 

existence value: they are concerned 

primarily with the knowledge that the 
species exists and not so much with 

er of remaining populations, 

However, this result may also be due 

to the small sample size used in the 

pretest. Recall that the primary goal 

of the pretest was to refine the 

survey in preparation for the full 

survey. 

After making modifications to the survey instrument based on results and 

coments in the pre-test, the survey 

was sent to 1,500 individuals with 750 

people randomly chosen in South Carolina, where the primary good being 

valued is located, and with 750 people 

randomly chosen throughout the other 

states of the U.S. This stratification was undertaken in keeping with 

suggestions in the literature to 

sample more heavily in areas where a 

rare trait (here, a positive valuation 

for the good in question) is most 

likely to occur (Kish 1965). The 

response rate2 for the South Carolina 

subsample (58.6%) was higher than for 

the remainder of the United States 

(50.70%), although not significantly 

so. Average willingness to pay values 

for the 4 restoration activities for 

the two subsamples were as follows. 

For the 50% chance of survival of the 

RCW in the FMNF, South Carolina had an 

average willingness to pay $9.52 on 

average. For the 99% chance of 

survival of the RCW in the FMNF, the 

values were $13.18 and $8.74 for South 

Carolina and the U.S., respectively. 

To give all RCW populations in the 

U.S., a 99% chance of survival, South 

Carolina residents were willing to pay 

$8.56. Finally, willingness to pay to 

restore the FMNF if the RCW did not 

live there was $13.81 for South 

Carolina residents and $7.89 for the 

remainder of the U.S, These average 

willingness to pay values are significantly different from zero. However, 

it should be noted that 56% of all 

citizens surveyed indicated that they 

would be willing to pay $0' for 

restoration activities for the RCW. 

In the full survey, the contingent 

valuation question was asked using 

three different elicitation 

techniques: open-ended, payment card, 

and dichotomous choice. Results 

presented here are for the open-ended 

elicitation technique only. 

These zero valuations are included in 

the calculation of average willingness 

to pay. 

As was expected, average values were 

higher for South Carolina than for the 

remainder of the U,S. However, since 

the U.S. subsample (many of whom may 

never expect to see an RCW o r v i s i t 

the FMNF) reported a positive average 

value as well, it can be concluded 

that a primary portion of the value 

that individuals place on the endangered RCW is existence value. Individuals all across the United States 

valued the restoration of the endangered RCW, Not only were U.S. citizens concerned about endangered 

species, but they expressed concern 

about ecosystems as well as reflected 

in the positive valuation for restoration of the FMNF even if the endangered RCW did not live there. This 

survey has indicated support for 

continued efforts for the RCW and its 

habitat. 

This paper has provided a discussion 

of the theory underlying the valuation 

of non-market goods, an outline of an 

empirical model for determining the 

value of a particular enviromental 

good, and the results from a contingent valuation survey. These preliminary results suggest that individuals 

did hold some positive value for the 

endangered RCW and that they would be 

willing to forego part of their income 

to improve its chance of survival. 

Full survey results and a more 

detailed discussion of policy implications will be presented following 

the final analysis of the survey data, 

REFERENCES 

Bergstrom, John C.; Stoll, John R. 

1987. A test of contingent market bid 

elicitation procedures for piecewise 

valuation. Western Journal of Agricultural Economics 12(2):104-108. 

Boyer, William; Peterson, Donald. 

1983. Longleaf pine. In: Burns, 

Russell Mef tech, comp. Silvicultural 

systems for the major forest types of 

the United States. Agric. Handb. 445, 

Washington, DC: U.S. Department of 

Agriculture, Forest Service: 153-156. 

Dillman, Don A. 1978. Mail and Telephone Surveys: The Total Design 

Method. New York: John Wiley and Sons, 

Inc. 
Rooper, Robert G.; Watson, J. Craig; 

Escano, Ronald E. F, 1990. Hurricane 

Hugo's initial effects on red-cockaded 

woodpeckers in the Francis Marion 

National Forest. Transactions of the 

Fifty-fifth North American Wildlife 

and Natural Resource Conference 

55:220-224. 

Kish, Leslie. 1965. Survey sampling, 

New York: John Wiley and Sons, Inc. 

Mitchell, R,M,; Carson, R.T. 1989. 

Using surveys to value public goods. 

Resources for the Future, Washington, 

D.C. 

Peterson, G. L,; Randall A,, eds. 

1984. Valuation of wildlife resource 

benefits. Boulder, CO: Westview Press. 

Randall, Alan; Hoehn, John P.; 

Swanson, Cindy Sorg. 1990, Estimating 

the recreational, visual, habitat, and 

quality of life benefits of Tongass 

National Forest. U.S. Forest Service 

General Technical Report RM-192. 

Shaw, William W. 1984. Problems in 

wildlife valuation in natural resource 

management. In: Peterson, George L.; 

Randall, Alan, eds. Valuation of 

wildland resource benefits. Boulder, 

CO: Westview Press. 

U.S. Department of Agriculture, Forest 

Service. Statement of Policy, In: 

Sheffield, Rapond M.; Thompson, 

Michael T. 1992. Hurricane Hugo: 

effects on South Carolina's forest 

resource, U.S, Forest Service Research 

Paper SE-284. 

Reprinted with permission. 

Proceedings of Red-cockaded Woodpecker 

Symposium 111: Species Recovery, 

Ecology and Management, January 25-28, 

Charleston, SC. To be published by 

College of Forestry, Stephen F. Austin 

State University, Nacogdoches, TX. 
EFFECTImNESS OF NEST BOXES FOR RIEDUCING USE OF 

ED WODPECICER CAVITIES BY OTHER VlElRTEBmTES 

Susan C. Loeb and Robert G. looper' 

Abstract--The red-cockaded woodpecker (RCW; Picoides 

borealis) is highly dependent on the cavities it 

excavates in living pine trees, In September 1989 

Hurricane Hugo destroyed 87 percent of the active 

red-cockaded woodpecker cavities on the Francis Marion 

National Forest (FMHF) in coastal South Carolina, 

Although over 1,000 artificial cavities have been 

constructed to replace some of the natural cavities 

that were destroyed, the number of cdvities per colony 

site is still greatly reduced from pre-Hugo levels. As 

a result of the reduced number of cavities, interactions with other species appear to have increased. It 

is estimated that use of cavities by other species 

reduced the reproductive potential of RCWfs during the 

nesting season following Hurricane Hugo by approximately 20 percent. One method suggested to reduce 

interspecific competition for RCW cavities is the provisioning of nest boxes in colony sites. The objectives of this study were to determine whether nest 

boxes in RCW colony sites effectively decrease use of 

RCW cavities by other species, and if so, whether lower 

use of cavities by other species increases the survival 

and reproductive success of the RCWfs. 

The study was conducted in 1991 and 1992 on the Francis 

Marion National Forest and included 116 colonies (61 Control colonies and 55 Experimental colonies) in 1991, 

and 121 colonies (63 Control colonies and 58 Experimental colonies) in 1992. Three blue bird nest boxes 

(NBfs) were placed within each Experimental colony 

site. All NBfs and cavities in Control and Experimental colonies were checked at least twice during the 

RCW breeding season. 

NBfs and cavities were used by a variety of vertebrate 

species but blue birds (BBfs) and southern flying 

squirrels (SFSfs) were the most common species. Both 

species showed a preference for NBfs over cavities. 

Use of Control colonies by all species other than RCWfs 

tended to be greater than those with NBfs but this 

difference was not significant. However, in 1992 there 

were significantly fewer BBfs and SFSfs in Experimental 

colonies than in Control colonies, The presence of 

NBfs had no effect on the reproductive success of the 

RCWfs, Thus, although NBfs can reduce the number of 

potential competitors in RCW cavities, this reduction 

is small and has little impact on the RCWfs. 

' USDA Forest Service, Southeastern Forest Experiment Station, Clemson, SC and 

Charleston, SC, 
C TERISTICS OF TIMBER STANDS CONTAINING 

SUFFICIEm FOR CAVITY TION BY 

WOODPECKER 

Alexander Clark, 111' 

Abstract--The relationship of heartwood development in 

loblolly (Pinus taeda L.) and longleaf (P. palustris Mill.) 

pine stands with site quality, stocking, stand age and 

average dbh of dominant and codominant trees is presented. 

This information is important to forest managers and 

biologists managing the recovery of the endangered 

red-cockaded woodpecker (Picoides borealis) (RCW). 

Twenty-nine loblolly and 22 longleaf pine stands 

representing a range of age classes (30 to 100 years) and 

site indexes (50 to 120 feet) were sampled in the Southeast 

for heartwood and sapwood content at 22 feet above the 

ground. Regression equations are presented for estimating 

average heartwood diameter and sapwood thickness at 22 feet 

using stand age and site index as independent variables. 

Results indicate that fast-growing loblolly and longleaf 

pine stands on the better sites will have the highest 

probability of developing sufficient heartwood for RCW 

cavity excavation at the earliest age. 

INTRODUCTION 

Infonnation is available on foraging 

habitat and trees selected for cavity 

excavation by RCW clans (Lennartz and 

Henery, 1985) but little information is 

available on what timber stands have 

the highest potential for developing 

acceptable cavity trees at the earliest 

age. 

sapwood but it is rarely done. The RCW 

normally excavates cavities totally in 

heartwood and prefers redheart 

(Phellinus pini) heartwood infected 

trees for easier cavity excavation 

(Jackson 1977, Conner and Locke 1982, 

Hooper and others 1991). 

Many of the changes that occur when 

sa~wood converts to heartwood are known 

The RCW requires a cross-section of at (~kamer and Kozlowski, 1979). Basileast 5 inches of heartwood at cavity cally, extractives resulting from 

height to envelope its nesting cavity. differentiation, respiration, syn- 

~av thesis, and degradation of starch are 

or translocated along ray parenchyma cells 

toward the pith where they accumulate. 

With restricted respiration because of 

Qaper presented at the Seventh 

Biennial Southern Silvicultural 

Research Conference, Mobile, AL, 

November 17-19, 1992. This study was 

partially supported with funding from 

the U.S. Dept. of Interior, Fish and 

Wildlife Service, Atlanta, GA and USDA 

Forest Service, Southern Region, 

Fisheries, wildlife and Range, Atlanta, 

aspirated pits, sta;ch grains hydrolize and disappear, phenols oxidize and 

polymerize to form pigments in cell 

voids and the ray parenchyma cells die 

in the transition zone between sapwood 

and heartwood to form heartwood. Thus, 

heartwood forms an irregular cylinder 

at the center of the bole and generally 

decreases with tree height. 

GA . * Research Wood Technologist, Little research has been conducted on 

Southeaetern Forest Experiment Station, southern pine heartwood formation as 

Athens, GA. influenced by environmental factors 
since the 1930,s. The relative proportion of heartwood has been reported to 

vary directly with tree age and negatively with rate of growth (MacKinney 

and Chaiken 1935). Lublolly and 

longleaf pines with large crowns and 

rapid gro*h on good, moist sites are 

reported to contain a smaller proportion of heartwood than trees with small 

crowns from closely stocked stands on 

poor drier sites (Paul 1932, Bray and 

Paul 1934). 

This paper discusses the relationship 

of site quality, stocking, stand age, 

tree dbh and total height with heartwood formation at 22 feet in loblolly 

and longleaf pine sampled in the 

Southeast. Linear equations are 

presented for predicting diameter of 

heartwood and sapwood thickness at 22 

feet using stand characteristics as 

independent variables. 

MATERIALS AND METHODS 

A series of stands representing a range 

of age classes (30 to 100 years) and 

site indexes (50 to 120 feet) were 

sampled for heartwood and sapwood 

content. A total of 29 loblolly pine 

stands and 22 longleaf pine stands were 

sampled* Loblslly stands sampled were 

located on the Oconee National Forest 

in Georgia, the Francis Marion National 

Forest, and Belle W. Baruch Forest 

Science Institute Hobcaw Forest in 

South Carolina. Longleaf stands 

sampled were located on the Francis 

Marion NF and Hobcaw Forest in South 

Carolina and the Talladega and Conecuh 

National Forests in Alabama. Four to 

five dominant or codominant trees were 

randomly selected within each stand. 

Dbh, total height, height-to-base of 

full live crowns were recorded for each 

tree. A competitive index or point 

density measurement (ft2/acre) was 

determined for each tree using a 10 BAF 

prism (Spurr 1962). A 12-mm increment 

core was extracted from each tree at 

breast height and a 5-mm increment core 

was removed from each tree at 22 feet. 

Each increment core was dried, glued to 

a core holder, and sanded before staining with a benzidine-sodium nitrite 

solution to distinguish heartwood and 

sapwood (Kutscha and Sacks 1962). The 

age and length of heartwood and sapwood 

was recorded for each core. Age at 4.5 

feet was converted to tree age at stump 

by adding 3 years for loblolly pine and 

6 years for longleaf pine. The age and 

measurements collected for each tree 

within a stand were averaged to obtain 

average stand characteristics. Site 

index was determined using curves 

developed by the USDA Forest Service 

(1976). 

Correlation coefficients (r) were 

developed to evaluate the relationship 

of heartwood diameter and sapwood 

thickness at 22 feet with site index, 

stand age, basal area, average dbh and 

total height of dominant and codominant 

trees, crown ratio, and growth rates, 

Linear equations were developed for 

each species to predict average 

diameter of heartwood and sapwood 

thickness at 22 feet. The following 

models were used: 

Y = a + b (AGE) 

Y = a + b (AGE) + c (SI) 

Y = a + b (AGE) + c (THT) 

Y = a + b (AGE) + c (DBH) 

where : 

Y = average diameter of heartwood or 

sapwood thickness at 22 feet in inches; 

AGE = stand age in years; 

SI = site index in feet; 

THT = average total height of dominant 

and codominant trees in feet; 

DBH = average dbh of dominant and 

codominant trees in inches, 

MSULTS AND DISCUSSION 

Average stand age of the two species 

sampled was 64 years for loblolly and 

63 years for longleaf. Average site 

index of the longleaf stands was 76 

feet compared to 86 feet for the loblolly stands (Table 1). The loblolly 

stands were growing at an average rate 

of 0.24 inches per year compared to 

0.20 inches for the longleaf. The 

sampled loblolly pine averaged 15.7 

inches dbh compared to 13.3 inches for 

the longleaf pine. There was little 

difference in the average diameter of 

heartwood between the two species; 

loblolly averaged 4.4 inches of heartwood compared to 4.3 inches for longleaf, but loblolly contained an average 

of 0.8 inches more sapwood at 22 feet 

than the longleaf. 

Heartwood diameter at 22 feet was 

significantly correlated with stand age 

and dbh of dominant and codominant 

trees (Table 2). Diameter of heartwood 

was not significantly correlated with 

basal area of either species. Site 

index was not significantly related 

with heartwood diameter in the loblolly 

stands but was significantly correlated 

with heartwood diameter in the longleaf 

stands. This significant negative 

relationship occurred because no ofd 

longleaf stands on good sites were 
Table 1--Average stand characteristics of the 29 loblolly and 22 longleaf pine 

stands sampled for heartwood content at 22 feet," 

Stand Characteristic Loblolly Pine Longleaf Pine 

Age (Yr) Site index (ft) 

Basal area (ft2) 

DBH (in) 

Total height (ft) 

Crown ratio (%) 

Growth rate (inlyr) 

Diameter heartwood at 22 feet (in) 

Thickness of sapwood at 22 feet (in) 

' Dominant and codominant trees. 

Table 2--Correlation coefficients for diameter of heartwood and sapwood thickness 

at 22 feet with stand characteristics for loblolly and longleaf pine stands.182 

Stand 

Characteristic 

Diameter of heartwood 

Loblolly Long leaf - 

Pine pine 

Sapwood thickness 

Loblolly Longleaf 

Pine Pine 

Age 

Site index 

Basal area 

DBH 

Total height 

Crown ratio 

Growth rate 

Dominant and codominant trees 

Significant at P = -01 = ** 

Significant at P = .05 = * 

Not significant = NS 

sampled and the longleaf stands with 

the most heartwood were old stands 

growing on the poorest sites* Average 

annual diameter growth at dbh was 

negatively correlated with heartwood 

diameter at 22 feet because the sample 

trees with the most heartwood were the 

oldest and growing the slowest, 

Sapwood thickness at 22 feet in the 

longleaf stands was not correlated with 

any of the stand characteristics 

measured (Table 2), However sapwood 

thickness was positively correlated 

with site index, negatively correlated 

with stand age and highly correlated 

with rate of growth in the loblolly 

stands, This indicates, as expected, 

that young, fast-growing stands contain 

more sapwood than older slow-growing 

stands. 

A series of linear regression equations 

was developed to estimate diameter of 

heartwood at 22 feet using stand 

characteristics as independent variables (Table 3). Stand age and site 

index as independent variables 

accounted for 78 to 79 percent of the 

variation in heartwood diameter at 22 

feet. The equation based on stand age 

and average dbh of dominant and codominant trees was the best predictor of 

heartwood diameter, accounting for 85 

percent of the variation in loblolly 

pine and 93 percent in longleaf pine. 

Average predicted diameter of heartwood 

at 22 feet increased with dbh and stand 

age (Table 4) and with increasing site 

index and stand age (Table 5). Thus, 

the youngest trees that contain sufficient heartwood for normal RCW cavity 
Table 3--Regression coefficients for estimating average diameter of heartwood at 22 

feet using stand age and age in combination with site index, average dbh and 

average total height of dominant and codominant trees as independent variables for 

loblolly and longleaf pine stands sampled in the So~theast.~~~ 

Standard 

Regression parameters and coefficients error of Coefficient of Coefficient of 

Equation/ Site Total estimate determination variation 

Species Intercept Age Index DBH Betight Sy.z R2 C.V. 

(Inch) ( Percent ) 

-0.823?Sm 0.08150** 1.1 0.75 24.4 

Longleaf -0.99334= 0.08408** 1.0 0.77 22.6 

-3.56019* 0.08533** 0.02895* 

Longleaf -4,2666eW 0.10046** 0.02989- 

E ation 4 

-3.42810** 0.05684** 

Longleaf -3.71733* 0.07402** 

Dominant and codominant trees 

Significant at P = .O1 = ** 

Significant at P 1 .05 = * 

Not significant = NS 

Table 4--Average predicted diameter of heartwood at 22 feet by stand age and 

average dbh , 

Average 

dbh 

Stand ase (years) 

50 60 70 80 90 100 

( inches ) --------------(inches)-------------- 

Loblolly pine 

14 3.0 3.6 4.1 4.7 5.3 5 . 9 

16 3.7 4.3 4.8 5.4 6.0 6.6 

18 4.4 4 . 9 5.5 6.1 6.7 7.2 

20 5.1 5.6 6.2 6.8 7.4 7 . 9 

22 5.8 6.3 6.9 7.5 8.1 8.6 

Longleaf pine 

4.2 4.6 4.9 5.3 5.7 6.1 

5.6 6.0 6.4 6.8 7.2 

6.7 7.1 7.5 7 . 9 8.3 

8.2 8.6 9.0 9 . 3 

Dominant and codominant trees 
Table 5--Average predicted diameter of heartwood at 22 feet1 by stand age and 

site index. 

Site Stand aqe (years) 

index 50 60 70 80 90 100 

(feet) ------------- (inches)-------------- 

Loblolly pine 

90 2.7 3.6 4.4 5 . 3 6,l 7,0 

80 3.0 3 . 9 4.7 5.6 6.4 7.3 

90 3.3 4.2 5.0 5.9 6.7 7.6 

100 3.6 4.5 5 . 3 6.2 7.0 7 . 9 

110 3.9 4.7 5.6 6.4 7.3 8.2 

Longleaf pine 

2.3 3.2 4.2 5.3 6.3 7 • 3 

2.5 3.6 4.6 5.6 6.6 7.6 

2.8 3.9 4.9 5.9 6.9 7.9 

3.1 4.2 5.2 6.2 7.2 8.2 

3.4 4.4 5 • 5 6.5 7.5 8.5 

Dominant and codominant trees 

excavation (25 inches) were the fastest 

growing trees on the best sites. Based 

on the values shown in Table 4, sufficient heartwood for RCW cavity activity 

does not occur in the average dominant 

on codominant tree until age 50 in 

loblolly pine and age 60 in longleaf 

pine and then only in the larger diameter trees. When diameter of heartwood 

is predicted using site index and stand 

age the equations show 70-year-old 

loblolly stands with a site index 290 

and 70-year-old longleaf stand with a 

site index 280 will contain sufficient 

heartwood for RCW cavity activity. 

The same stand characteristics used to 

estimate heartwood diameter were used 

to estimate sapwood thickness at 22 

feet. However, the only variable 

combination which accounted for more 

than 36 percent of the variation in 

sapwood thickness was equation (4) 

which is shown below for each species: 

LOBLOLLY PINE 

SAP 1.74006 - 0.02776 (AGE) 

+ 0.23516 (DBH) (5) 

SAP = 1.40648 - 0,02487 (AGE) 

+ 0.23290 (DBH) (6) 

where 

SAP = sapwood thickness at 22 feet in 

inches. 

The sapwood thickness equation 

accounted for 79 percent of the 

variation in sapwood in loblolly pine 

and 73 percent of the variation in 

sapwood in longleaf pine. Predicted 

thickness of sapwood decreased with 

increasing stand age and increased with 

dbh . 

CONCLUSIONS 

Diameter of heartwood at 22 feet 

increases significantly with stand age 

and tree dbh. Fast-growing loblolly 

and longleaf pine stands on the better 

sites will have the highest probability 

of developing sufficient heartwood for 

RCW cavity excavation at the earliest 

age. At age 70, the average dominant 

or codominant tree in a loblolly stand 

with a site index 290 and in a longleaf 

stand with a site index 280 will contain sufficient heartwood (25 inches at 

22 feet) for RCW cavity activity. 

LITERATURE CITED 

Bray, M.W.; Paul, B.H. 1934. Evaluation 

of southern pines for pulp production 

shortleaf pine (Pinus echinata). 

Popular Trade Journal 99(5):38-41. 

Conner, R.N.; Locke, B.A. 1982. Fungi 

and red-cockaded woodpecker cavity 

trees. Wilson Bull. 94:64-70. 

Hooper, R,G.; Lennartz, M.R.; Muse, 

H.D. 1991. Heart rot and cavity tree 

selection by red-cockaded woodpeckers. 

J. Wildllife Management. 55:323-327. 

Jackson, J.A. 1977, Red-cockaded 

woodpecker and pine redheart disease. 

Auk 94:160-163. 
Kraaaer, P.J.; ]Rozlowski, T.T. 1979. 

Physiology of woody plants, Academic 

Press, Inc., New York, NY. 811 p. 

Rutscha, N,P,; Sacks, I.B. 1962, Color 

tests for differentiating heartwood and 

sapwood in certain softwood tree 

species. Rep. No. 2246. Madison, Wf: 

USDA Forest Service, Forest Products 

Ulxrratory, 13 p. 

Lennartz, H,R.; Henery, G,B. 1985. 

Endangered species recovery plan for 

red-cockaded woodpecker (Picoides 

borealis), U.S. Fish and Wildlife 

Service R-4, Atlanta, GA. 88 p. 

EaacKinney, A.L.; Chaiken, L.E. 1935, 

Heartwood in second-growth loblolly 

pine. Tech. Note 18. U,S. Department of 

Agriculture, Forest Service, Appalachian Forest Experiment Station. 3 p. 

Paul, B.X. 1932. The relation of 

certain forest conditions to the 

quality and value of second-growth 

loblolly pine lumber. Journal of 

Forestry 30:4-21, 

Spurr, S,H. 1962. A measure of point 

density. Forest Science 8:85-96. 

Reprinted with permission from 

Proceedings of the Seventh Biennial 

Southern Silvicultural Research 

Conference, Mobile, AL, Nov, 17-19, 

1992, Published by the USDA For, Serv. 

SFES Gen. Tech, Rep. SO-93, July 1993, 

p. 621-626. 
RESTORATION OF THE RED-COCKADED WOODPECKER 

POPUmTION ON THE F 

FOREST: THREE YEARS POST HUGO 

J. Craig Watson, Robert G. Hooper, Danny L. Cnrlson, 

William E. Taylor, and Timothy E. &tilling1 

Abstract--The Francis Marion National Forest (FMNF) once 

supported the second largest and only documented naturally 

increasing population of red-cockaded woodpeckers (RCW). 

Prior to Hurricane Hugo, an estimated 477 RCW groups 

existed on the FMNF. Hugo destroyed 87% of the active 

red-cockaded woodpecker cavity trees on the Forest and 

killed 63% of the woodpeckers. In addition, 59% of the 

birdsr foraging habitat, nesting habitat, and potential 

cavity trees were destroyed. By the nesting season of 

1990, 537 artificial cavities had been installed and there 

were 249 groups. Forty-five percent of RCW nests were in 

artificial cavities and 302 young were fledged. In the 

1991 breeding season, there were 306 groups, 483 young were 

fledged and 60% of the nests were in artificial cavities. 

In 1992, there were 332 groups, 500 young were fledged, and 

61% of the nests were in artificial cavities. Following 

the catastrophic loss of woodpeckers and their habitat in 

1989 from Hugo, the number of adult RCWs and the number of 

groups had increased 33% by 1992. This remarkable 

increase, despite the severe losses of nesting and foraging 

habitat, cavity trees, and individual birds, resulted 

primarily from installation of artificial cavities. 

INTRODUCTION 

The Francis Marion National Forest 

(FMNF) is unique in several respects 

in regard to the red-cockaded woodpecker (Picoides borealis). The RCW 

population on the FMNF was the second 

it was one of the few populations near 

a recovered level. It was also the 

first population, following classification of the bird as endangered, to have 

been impacted by a major hurricane 

(Hooper et al., in press). - - largest, one of the densest, and the 

only population known to be naturally Hurricane Hugo, a Category IV hurricane 

increasing (Hooper et al. 1990); and at landfall, hit the FMNF on 21-22 

September, 1989 (Townsend 1990). The 

center of the eye passed within 5 miles 

J. Craig Watson, USDA Forest 

Service, Francis Marion National 

Forest, Moncks Comer, SC 29461; Robert 

G. Hooper, USDA Forest, Service 

Charleston, Southeastern Forest 

Experiment Station SC 29414; Danny L. 

Carlson, USDA Forest Service, Francis 

Marion National Forest, 

McClellanville, SC 29458; William E. 

Taylor, USDA Forest Service, Francis 

Marion National Forest, Moncks Comer, 

SC 29461; Timothy E. Milling, USDA 

Forest Service, Southeastern Forest 

Experiment Station Charleston, SC 

29414 

of the FMNF and-the track of the hurricane was such that the FMNF received 

the strongest winds generated by the 

hurricane. Hurricane force winds 

occurred in a band greater than 50 

miles wide and affected the entire FMNF 

(Hooper and McAdie 1994). As a result, 

catastrophic loss to RCW cavity trees, 

RCWs, and RCW foraging habitat 

occurred. 

Hurricanes will be a continual threat 

to most recovery areas. Hooper and 

McAdie (1994) estimated there will be 4 

recovery areas hit by major hurricanes 
every 100 years on average with 39 

less intense hurricanes hitting the 11 

most vulnerable recovery areas. The 

FMNF, recently impacted by a major 

hurricane, is one of these recovery 

areas. Clearly managers will be dealing with restoration efforts in the 

future because of the periodicity of 

hurricanes impacting RCW populations, 

Our experience following Hugo should 

be of value to managers because our 

efforts have led to a remarkable and 

unprecedented increase in an RCW 

population following a catastrophic 

event. 

XHPI?LGTS OF HURRX- HUGO 

Impacts to the Forest 

Extensive damage to timber resources 

from hurricanes is not an unusual 

ocurrence (Van Hooser and Hedlund 

1969, Hook et al. 1991, Hosper and 

McAdie 1994). In South Carolina, 

approximately 10.8 billion board feet 

(bf) of sawtimber on 4 million acres 

of forested lands were destroyed by 

Hurricane Hugo (Sheffield and Thompson 

1992). 

Destruction of pine trees on the FMNF 

that represented RCW habitat was 

catastrophic. Initial estimates sf 

destroyed pine sawtimber on the FMNF 

were between 700 million and 1 billion 

bf or about 50060% of pine sawtimber 

(Hooper et al. 1990). Data from the 

Forest Inventory and Analysis (FIA) 

Research Work Unit of the Forest 

Service's Southeastern Forest Experiment Station indicated a 56% loss of 

pine trees greater than or equal to 

10" dbh with about 2.44 million stems 

surviving (Table 1). CISC (Continuous 

Inventory of Stand Condition) database 

information indicated a slightly 

higher loss of pine sawtimber with 

approximately 2.28 million pine trees 

greater than or equal to 10" dbh 

surviving Hugo (Table 1). This 

represents a 59% loss of pine sawtimber on the Forest. 

Not all pine stands were equally 

damaged by winds of the same force 

(Hooper et al. 1990). Damage appeared 

to be a function of both tree age and 

basal area (ba), Sapling and young 

pole stands survived well with varying 

degrees of damage. Stands in the 30- 

to 40-year age class generally escaped 

with moderate damage (Figure 1). Most 

of these younger stands can be managed 

without regeneration, Mature pine 

stands with low to moderate basal 

areas (70 sq/ft ba) typically had less 

than 10 sq/ft ba after the hurricane. 

Table 1--Number of pine stems in 

Francis Marion National Forest (x 1000) 

Pre- PostHugo Hugo Survival 

Size 1936' 1986' 19903 (%) 

5-9" 3,102 ----- 6,681 44 

dbh 

>lo" 2,960 5,539 2,280 4 12 

dbh (2,442)2 

Gruxnbine, A.A. 1936. 

Data are from inventories conducted 

in 1986 and 1990 by the Forest Inventory and Analysis Research Work Unit, 

Southeastern Forest Experiment Station, 

Asheville, NC . Data are from updated Continuous 

Inventory of Stand Condition (CISC) 

database from the Wambaw and Witherbee 

Ranger Districts of the FMNF after 

Hurricane Hugo. 

AGE CLASS 

Figure 1--Percent survival of pine on 

the Francis Marion National Forest 

after Hurricane Hugo. 

Most of the killed pine trees broke off 

at about 1/3 the height of the tree and 

the remaining were uprooted. Mature 

pine stands with high basal areas (90 sq/ft ba) escaped some of the strongest 

winds with moderate damage. 

Hugo not only inflicted massive 

destruction to RCW nesting and foraging 

habitat in the form of broken and 

wind-thrown trees, but also created 

conditions for a continuing process of 

short-term habitat loss. Many pine 

trees that initially survived suffered 

root, bole, and crown damage that 

contributed to additional mortality. 

Remaining trees were subject to attack 

from engraver beetles (Ips spp.), 

turpentine beetles (Dendroctonus 

terebrans), and southern pine beetles 

(Dendroctonus frontalis). 
Insect populations, suspected to be 

SPB, reached outbreak status within 9 

months of Hugo's landfall and lasted 

through the s r of 1990. Through 

October 1990 e were 343 distinct 

infestations, mostly from Ips 

in pine sapling stands on the 

Long periods of hot dry weathe 

r of 1990 are thought to have 

considerably slowed down further 

spread of Ips infestations by making 

host material unsuitable to attack (P. 

Barry, pers. comma.). Basal area in 

sawtimber stands was so reduced from 

the storm that SPB outbreaks were 

limited and confined. Not all acres 

infested required control, but a total 

of 526 acres of potential and current 

RCW habitat was lost to insect infestations. Although not as dramatic as 

the loss of habitat from Hugo, the 

attrition of pine stems from these 

cumulative impacts is continuing to 

contribute to loss of RCW habitat. 

Impacts to the Red-cockaded 

Woodpecker Cavity Trees 

Impacts to the RCW from Hurricane Hugo 

were also catastrophic. Ligon (1971) 

suggests that the cavity tree is the 

single most hprtawt feature in the 

life of the RCW, and the lack of 

potential cavity trees for excavation 

was one reason cited for the species 

decline (USFWS 1985). 

Hugo destroyed 87% of the estimated 

1765 active cavity trees on the FMNF; 

only 229 RCW cavity trees remained 

standing after the storm. Most of the 

destroyed RCW cavity trees were broken 

at the cavity (52.8%) while loss of 

cavity trees from the tree being 

uprooted or being broken between the 

cavity entrance and stump was about 

equal (Table 2). A small percentage 

(9.9%) of RCW cavity trees died as a 

result of varying degrees of crown 

damage. Fifty percent (269/538) of 

all RCW clusters on the FMNF lost all 

cavity trees. Forty-six percent 

(2181477) of the active clusters lost 

all cavity trees (this included 

active, inactive, and incomplete 

cavities), and 57% (2721477) lost all 

active cavity trees. Only in 2% 

(121538) of the clusters did all 

cavity trees survive. The average 

number of active cavities per cluster 

in a sample of 205 clusters surviving 

Hugo was 1.9 compared to 3.7 active 

cavities in 100 randomly selected 

clusters in 1988. Thus, the quality 

of the surviving clusters was greatly 

reduced. 

Table 2--Type of damage to RCW cavity 

trees on the Francis Marion National 

Forest from Hurricane Hugo (n=1028). 

Percent 

# cavity damage 

trees by Type of damage damaged category 

Crown gonelcavity 102 9.9 

present 

Broken at cavity 543 52.8 

Broken below 194 18.9 

cavity 

Cavity tree 189 18.4 

uprooted 

Total 

Initially, non-lethal damage from Hugo 

was expected to cause continuing tree 

mortality (Sheffield and Thompson 

1992). A stratified random sample of 

clusters indicated a net post-Hugo loss 

of cavity trees prior to the 1991 

nesting season of 4.9% and 10.7% prior 

to the 1992 nesting season (Table 3). 

These losses included cavity trees that 

had natural or artificial cavities. 

Sixteen percent of the loss was attributable to lightning strikes and 14% was 

the result of Hugo-induced wind damage, 

Causes for the remainder of the losses 

were difficult to determine although 

most such trees showed signs of Ips 

beetle attack. Mortality was most 

likely a combination of crown and bole 

damage from Hugo and secondary attack 

by insects. Estimated mortality of 

cavity trees on the FMNF in 1991 was 65 

trees and 137 in 1992. 

Table 3--Percent mortality of RCW 

cavity trees by type of cavity on the 

FMNF after Hurricane Hugo. 

t natural t t drilled 8 drilled t overall 

cavities ineerts cavitiee etarte mortality 

20 of 409 cavity tree8 ssapled died. 

43 of 406 cavity trees ssapled did. 

Mortality of RCW cavity trees in 1991 

was highest for natural cavity trees 

and cavity trees with drilled starts, 

while cavity trees with inserts and 

drilled cavities experienced the least 
mortality (Table 3). Mortality of 

cavitv trees with drilled starts and 

drill& cavities was about equal in 

1992, while mortality of natural 

cavity trees was highest. Mortality 

of trees with inserts increased 

slightly (Table 3). Mortality for all 

types of cavity trees increased from 

1991 to 1992, but it was apparent that 

natural cavity tree mortality exceeded 

that of trees with artificial 

cavities. 

RC!Ws 

When Hugo hit there were an estimated 

1908 RCWs on the FMW (Hooper et al. 

1991). The mean number of RCWs per 

cluster on the FMNF in Septder prior 

to Hugo making landfall was 4.0 birds. 

Although only 12 dead red-cockaded 

woodpeckers were found in post-Hugo 

inventory efforts, the mean number of 

birds per cluster surviving Hurricane 

Hugo was 1.5 birds. Seven hundred six 

(706) RCWs were accounted for after 

Hugo which indicated a loss of 63% of 

individual RCWs on the FMNF (Hooper et 

al. 1990). 

Seventy-two percent (344/477) of all 

formerly active clusters, 91% 

(227/248) of clusters with surviving 

cavity trees, and 47% (117/248) of 

those with no surviving cavity trees 

still supported one or more RCWs after 

the hurricane. Thus, there were 344 

sites that still had one or more RCWs; 

117 of these had no cavity trees and 

227 had severely reduced numbers of 

cavity trees. Only 68% (233/344) of 

these had two or more RCWs, and thus a 

potential breeding group. 

Further significant losses of RCWs 

most likely occurred from severe 

winter weather. Most RCWs that 

survived Hugo were roosting in the 

open. Temperature dropped to an 

average of 15.3"F during a 4-day 

period from 22-24 December 1991 with a 

low of 11T on 24 December (NOAA 1989, 

temperature data obtained from the 

Santee Experimental Forest headquarters on the Witherbee Ranger District). A stratified random sample 

indicated that 579 individual RCWs 

existed prior to the 1990 nesting 

season, representing a further loss of 

18% of individual RCWs after Hugo hit. 

Thus, a 70% loss of RCWs occurred on 

the FMNF after Hurricane Hugo. 

RECOVERY EFFORTS 

Colony Damage Assessment and 

Prescriptions 

Damage assessment was evaluated and 

mnagement prescriptions were developed 

for each cluster. Biologists visited 

all known clusters within 4 months 

after Hugo. The number of surviving 

RCWs and cavity trees were determined 

and an account was made of the trees 

suitable for natural and artificial 

cavities. The extent of foraging 

habitat for each cluster was also 

determined. This data provided a basis 

for our prescription of each cluster's 

potential for restoration. Prescriptions provided information for the 

priority of artificial cavity installation, placement of restrictors, removal 

of slash and debris from around cavity 

trees, needed midstory treatments, and 

silvicultural and timber management 

needs. 

Priority for rehabilitation of RCW 

clusters with artificial cavities 

(given adequate foraging habitat being 

available) was where: 

1) 2 or more birds survived with no 

suniving cavity trees, 

2) 1 bird survived with no surviving cavity trees, 

3) 2 or more birds survived with one 

functional cavity present, and 

4 1 bird survived with one 

functional cavity. Care was 

taken not to force the process of 

recovery by rehabilitating 

colonies where suitable habitat 

did not exist. 

Artificial Cavity Program 

Prior to Hugo, three experimental 

techniques for constructing artificial 

RCW cavities had been introduced 

(Copeyon 1990, Allen 1991). These 

techniques were a major technological 

breakthrough in RCW management. 

Copeyon's techniques (drilled cavities 

and drilled starts) had been tested in 

North Carolina and were successful in 

providing cavities that were used for 

nesting by RCWs (Copeyon 1991). 

Allen's technique (inserts) had not 

been tested during an RCW nesting 

season prior to Hugo. Copeyon and 

Allen came to the FMNF after Hugo to 

teach us how to construct artificial 

cavities for RCWs. 
Our immediate goal prior to the 1990 

nesting season was to ensure at least 

2 functional cavities per cluster 

where at least 1 RCW survived and 

where minimal or adequate foraging 

habitat existed. The long-term goal 

is to have at least 4 functional 

cavities (natural or artificial) per 

cluster. These actions should contribute to the overall survival of 

RCWs, provide functional cavities 

necessary for nesting, and provide 

sufficient cavities for dispersing 

RCWs . As of this writing, 989 artificial 

cavities of the three types have been 

constructed in 328 clusters. A major 

effort prior to the 1990 nesting 

season resulted in the installation of 

537 artificial cavities in 246 clusters, of which 117 clusters did not 

have any surviving cavity trees. A 

total of 428 inserts, 319 drilled 

cavities, and 242 drilled starts have 

been installed since Hugo, with the 

number of artificial cavities 

installed being about equal each of 

the following nesting years after 1990 

(Table 4). The average number of 

potential roosting cavities per 

cluster, as of the 1992 nesting season 

(including natural and artificial 

cavities), is now 3.6 and essentially 

the same as the number of active 

cavities per cluster (3.7) before Hugo 

hit . 

Table 4--Number of artificial RCW 

cavities installed on the Francis 

Marion National Forest since Hurricane 

Hugo prior to each nesting season 

(nesting season year here is defined 

as occurring from April 1 of each year 

to March 31 of the following year). 

1990 1991 1992 1993' Total 

Inserts 277 52 27 72 428 

Drilled 126 65 89 39 319 

cavities 

Start 134 34 24 50 242 

cavities 

Total 537 151 140 161 98g2 

Number of artificial cavities 

installed from April 1, 1992, to 

September 30, 1992. 

An additional 70 artificial cavities 

are projected to be installed prior to 

the 1993 nesting season for a total of 

1,059. 

Initial monitoring of artificial 

cavities to determine use was intensive. At this writing, greater than 

90% of all artificial cavities were 

to be used to some extent by 

ntenance of resin wells, 

chipping of the entrance tunnel or 

cavity, roosting, or nesting). As the 

utilization rate of artificial cavities 

and the average n er of cavities per 

cluster increased, mnitoring activities were reduced. The elapsed time 

for cavities to be used varied, dependent upon the number of available 

cavities in the cluster and the number 

of birds in the group. Some cavities 

were utilized the same day of construction and approximately 30 are not 

being used three years after installation. Those not utilized may not have 

sufficient habitat in those sites to 

support RCWs. We expect nearly all 

artificial cavities installed in suitable habitat to be utilized eventually. 

Time till first use of an artificial 

cavity also appeared to be related to 

the degree of simulation of a natural 

cavity tree. Trees with artificial 

cavities that simulated the copious 

resin flow of natural cavity trees were 

utilized quicker than trees with artificial cavities that were not treated 

with artificial resin wells (Taylor and 

Hooper 1991, Copeyon 1990, Allen 1991). 

Some artificial cavity trees that are 

now active have enough resin flow 

developed to be indistinguishable from 

natural cavity trees. Many of the 

drilled starts were excavated to 

complete cavities within 2 months. 

Approximately 540 artificial cavities 

were constructed prior to the 1990 

nesting season by Copeyon's and Allen's 

technique. A modification of Copeyon's 

technique by Taylor and Hooper (1991) 

has reduced training time, safety 

hazards, and improved mobility of work 

crews. Allen's technique was modified 

by increasing the depth of the cavity, 

primarily to reduce competition from 

secondary cavity nesters. Artificial 

cavities constructed after the 1990 RCW 

nesting season utilized the modified 

techniques. These changes improved 

already successful techniques, allowed 

increased efficiency of construction, 

and resulted in higher utilization of 

artificial cavities. 

Restrictors 

Since Hugo, 306 cavity restrictors have 

been installed. Traditional restrictors recommended by Carter et al. 

(1989) were installed where cavity 

enlargement was observed. Full plate 
restrictors similar to Type A restrictors described by Carter et al. (1989) 

were placed on inserts when enlargement occurred. Approximately half of 

the inserts installed have been outfitted with restrictors, The width of 

the restrictor entrance was increased 

to 1.75" to allow easy entry and exit 

by RCWs, and to reduce monitoring 

efforts, Although no quantitative 

data are available, we feel that 

restrictors have most likely contributed to the successful nesting efforts 

of RCWs since Hugo. Data from the 

stratified random sample indicates 

that 25%, 21%, and 20% of RCW nests 

were in cavities with restrictors in 

1990, 1991, and 1992, respectively. 

~eproductive Attainment and 

Population Trend 

For the first three nesting seasons 

following Hugo a stratified random 

sample of RCW clusters (n=90) was used 

to estimate reproductive attainment 

and population trend. The sample was 

stratified by the level of damage to 

the clusters: high, medium, and low 

(this is the same stratified random 

sample mentioned throughout t h e t e x t 

to estimate other parameters of 

population condition). Clutch size, 

number of eggs hatching, and the 

number of nestlings reaching fledgling 

age was determined. An additional 30 

clusters were examined throughout the 

nesting season f o r t h e same nesting 

activity. Data on competition was 

also collected in these 120 clusters, 

60 of which had 3 bluebird boxes 

erected in the cluster, The purpose 

of the bluebird boxes was in part to 

reduce competition from secondary 

cavity nesters. Although data on 

competition has yet to be analyzed, 

juvenile RCWfs were observed using 

bluebird boxes for roosting in 

clusters where the number of RCWs in a 

group was greater than the number of 

available cavities. 

Three years after Hurricane Hugo, all 

evidence supports the conclusion of a 

continued improvement in the FMNF RCW 

population size. An estimated 250 

groups with two or more adults were 

present in the 1990 nesting season 

(Table 5). The number of groups with 

2 or more adults increased each of the 

first three years since Hugo. Between 

1990-91, the number of 2-bird groups 

increased 23,0%, from 249 to 306, The 

rate of increase between 1991-92 

Table 5--Estimated values for RCW 

population in the Francis Marion 

National Forest after Hurricane Hugo, 

based on a stratified random sample of 

90 clusters. 

# of elusters 384 384 3 9 1 

# of adults 607 729 806 

Clusters with 249 306 332 

2+ birds 

Clusters with 83 30 27 

1 bird 

Clusters with 52 48 31 

no birds 

The increase in the number of 

clusters from 1991 to 1992 is due to 

artificial cavities being installed in 

seven recruitment stands and being 

managed as clusters, 

slowed, but was still 8.5%. Overall, 

increase in 2-bird groups from 1990 to 

1992 was 33.0%, from 249 to 332. 

The increase came mostly from either 

single birds that successfully 

attracted a mate or from colonization 

of vacant clusters (Table 5). The 

number of clusters with 1 bird 

decreased by 67% from 1990-92, while 

the number of clusters with 0 birds 

decreased by 40% for the same period 

(Table 5). Relatively large numbers 

of dispersing RCWs (302, 483, and 500 

RCWs fledged in 1990, 1991, and 1992 

respectively, Table 6) and the presence of suitable cavities (mostly 

artificial cavities) has resulted in 

the occupation of clusters that 

formerly had 0-1 birds. Additional 

population increases resulted from an 

increase in the mean number of birds 

per group for the three-year period 

since Hugo. The mean number of adult 

birds per group during the nesting 

season has increased each year from 1.5 

in 1990, and to 1,9 and 2.1 birds in 

1991 and 1992, respectively. 

In 1990, 1991, and 1992, respectively, 

45,60, and 61% of RCW nests were in 

artificial cavities (Table 6). Without the use of artificial cavities by 

RCWs, the current population would most 

likely be 100-125 groups. 
Table 6--Estimated nesting attainment 

of RCW population on the Francis 

Marion National Forest after Hurricane 

Hugo, based on a stratified random 

sample of 90 clusters. 

#of youngfledged 302 483 500 

Mean young 1.21 1.58 1.50 

fledgedlgroup 

with 2+ birds 

% of groups with 72 81 81 

2+ birds nesting 

successfully 

% of nesting 45 60 61 

artificial cavities 

Recruitment Stands 

Further evidence of the excellent 

nesting attainment, dispersal of RCWs, 

and the utility of artificial cavities, has been the colonization of 

recruitment stands provisioned with 

artificial cavities. Two kinds of 

recruitment stands were designated. 

The first was the traditional recruitment stand with no history of occupation by RCWs (USFS 1985). The second 

type of recruitment stand designated 

were clusters totally destroyed by 

Hugo having suitable habitat available 

to support a group and not having 

birds two years after Hugo, Utilizing 

CISC database information and Geographical Information System (GIs) 

maps displaying RCW habitat elements, 

the most likely locations for recruitment stands were determined. Criteria 

used to delineate recruitment stands 

were: 

1) stands with greater than 40 

sqlft basal area (preferably 

higher) , 2) pine trees> 14" dbh and, 

3) the presence of suitable 

foraging habitat within .5 mile 

of the proposed site. 

The value of this criteria was 

verified as one recruitment stand, 

identified through use of GIs, was 

found to have an active cluster (not 

previously known) when the stand was 

visited. Since the 1991 nesting season artificial cavities were installed 

in 9 recruitment stands; six were in 

previously unoccupied habitat and two 

were formerly active, but now 

destroyed cluster sites. The remaining recruitment stand was a shift of a 

formerly inactive cluster where all 

cavity trees had died. The new 

cluster, approximately .2 mile away 

from the original site, contained 

larger trees suitable for artificial 

cavity excavation. Seven of the 9 

recruitment stands were created prior 

to the 1992 nesting season. Of these 

7, 5 successfully fledged young in 1992 

(including the inactive cluster we 

shift&). of the r ining 2, one is 

inactive and the other had 1 RCW in 

1992. The cluster with 1 bird 

attracted a second bird after the 1992 

nesting season. Two recruitment stands 

were created after the 1992 nesting 

season; both are active, with 1 bird at 

one cluster and 2 birds at the other. 

The mean period for colonization was 49 

days, and all recruitment stands outfitted with artificial cavities are 

expected to be occupied by functional 

groups in time. All recruitment stands 

were located within .75 mile of an 

active cluster except one that was 

located 1.25 miles from an active 

cluster; it became active in 30 days. 

Augmentation 

Due to the excellent dispersal of RCWs 

into unoccupied and single bird 

clusters since Hugo, augmentation 

efforts were minimal. Three female 

RCWs were moved from the FMNF to the 

Savannah River S i t e a f t e r Hugo because 

these solitary birds had little chance 

of surviving. Four translocations were 

conducted within the FMNF similar to 

those described by DeFazio et al. 

(1987); two resulted in group formation and successful nests. Because 

natural RCW dispersal appears to be 

contributing to the overall growth and 

health of the population, intensive 

augmentation efforts within the FMNF 

are not anticipated. 

HABITAT NANAGEmMT 

As critical as the artificial cavity 

program has been in the stabilization 

and recovery of the RCW on the FMNF, 

other successful management efforts 

have played an important role. Salvage of downed timber, fire suppression, and prescribed burning, have been 

an integral part of the short-term 

recovery of the RCW. Habitat restoration and timber management efforts will 

no doubt play an integral role in the 

long-term recovery of the RCW by 

establishing much needed RCW habitat, 

Salvage Efforts 

Post-Hugo, the greatest risks to the 

remaining pine resource on the FMNF 

were fire and insect attack. Normal 
fuel loads in coastal plain forests 

prior to Hugo were between 1.7-7,l 

tonslacre (Hook et al. 1991), Fuel 

loads after Hugo were in excess of 60 

tonslacre, increasing the chances of 

catastrophic wildfires (and difficulty 

of suppression) and insect attacks, 

Salvage guidelines were designed to 

protect the RCW and facilitate removal 

r. Guidelines included 

sd salvage areas for 

RCW clusters before salvage, leaving 

trees that were leaning less than 45" 

for RCW foraging, leaving 5 snagslacre 

for secondary cavity nesters, restrictions on salvage activities during the 

RCW nesting season, and penalties for 

ging cavity trees and potential 

cavity trees during salvage operations. Following these guidelines 

resulted in the protection of RCW 

habitat, reduced fuel loads, and 

reduced dead and dying wood that 

attracted insects. 

Efforts to salvage the estimated 1 

billion bf of downed timber began 

immediately, and by the end of 1992 

approximately 290 million bf of timber 

had been salvaged, representing about 

30% of the downed volume (Table 7). 

The largest effort was in 1990 with 

250 million bf salvaged. In addition, 

debris was removed and scattered from 

within 50 feet of existing cavity 

trees to further reduce the threat of 

insect attack and damaging wildfires. 

Table 7--Timber salvage and thinning 

volumes in MBF on the Francis Marion 

National Forest since Hurricane Hugo 

(MBF=thousand board feet). 

Net salvage volume 249,235 37,805 11,850 298,980 

Green volume cut 13,149 ------ ------ 13,149 

Thinning volume 2,786' 793 1,663 5,242 

Total volume cut 265,170 38,598 13,513 317,281 

Volume cut before Hurricane Hugo struck the FMNF. 

Fire Suppression 

Efforts for fire suppression after 

Hugo included an intensive fire 

prevention program by the South 

Carolina Forestry Commission and the 

Forest Service, and the rapid detection and suppression of wildfires. 

One hundred ninety miles of fuel 

breaks were constructed between 

private lands and Forest Service lands 

to minimize wildfire hazards to all 

landholders. Prior to January 1993, 

212 wildfires had started on the FNNF. 

They were rapidly suppressed and only 

3,308 acres were burned. No wildfires 

have resulted in the mortality of 

cavity trees or RCWs. Many of the 

wildfires suppressed were determined to 

be roadside arson, thus salvage efforts 

played a major role in prevention of 

catastrophic wildfires by reducing fuel 

loads near roadsides. 

Prescribed Burning 

The importance of prescribed fire to 

the RCW can not be over stated. The 

RCW does not tolerate hardwood 

encroachment into the colony site 

(Val Balen and Doerr 1978, Locke et al. 

1983, Loeb et al. 1991, Hooper et al. 

1991). Prescribed fire is the most 

cost effective and ecologically sound 

method of controlling unwanted hardwoods. No prescribed burning was 

conducted on the FMNF the first year 

after Hugo. However, prescribed 

burning resumed the second year after 

Hugo with 21,000 acres burned in 1991 

and 31,000 acres burned in 1992. In a 

five-year period (1985-1989) prior to 

Hugo, an average of 37,600 acres were 

burned annually on the FMNF, and this 

level of burning is expected to resume 

in the near future. Growing season 

burns, thought to be more efficient in 

controlling encroachment of hardwoods 

into clusters, were conducted on 

approximately 4000 acres in 1992. To 

further control encroaching hardwoods 

in clusters after Hugo, 1900 acres were 

treated with a combination of chainsaws 

and herbicide. 

Reforestation Efforts 

Prescribed burning is also playing a 

key role in reforestation efforts 

necessary to reestablish suitable RCW 

habitat, particularly in the recovery 

of longleaf pine (Pinus palustris) 

stands. Approximately 9,000 acres of 

longleaf stands have been burned for 

seedbed preparation andlor brown spot 

needle blight (Scirrhia acicola) 

control. An additional 6,000 acres 

have been site prepared and planted to 

longleaf pine since Hugo. 

Efforts to manage loblolly pine (Pinus 

taeda) have also been intensive with 

13,700 acres of loblolly pine seedlings fertilized. An additional 12,500 

acres of naturally regenerating 

loblolly pine stands were site prepared by injecting hardwoods with 

herbicide. Approximately 32,000 acres 

on the FMNF have regenerated naturally 

to loblolly pine without any post-Hugo 

silvicultural treatments (J. Dupre, A, 

Kiser, pers. comm.). 
Timber Management 

er management practices that promote the growth of pine stands will 

also have a profound positive effect 

on future RCW habitat, Hooper et al. 

(1991) reported that 36% of the pine 

stands on the FmF were regenerated 

from 1957-1987. These stands are now 

6-36 years old. Although only 2,224 

acres have been pre-commercially 

thinned since Hugo, the potential for 

these thinnings is enormous, as is the 

potential to thin loblolly pine stands 

naturally regenerating after Hugo. 

Thinned stands should be suitable as 

foraging habitat sooner than unthinned 

stands (Hooper and Harlow 1986). 

Except for salvage, all timber harvested since Hugo has been from firsttime thinning operations (Table 7). 

Projected thinning volume for the next 

three years is 38.3 million bf (Table 

8), all in pine poletimber 20-30 years 

old. These young stands suffered 

little damage and because of the 

amount of pine stands in younger age 

classes present when Hugo hit, a 

relatively large number of young pine 

stands are available for management. 

Table 8--Projected salvage and 

thinning volumes for the Francis 

Marion National Forest in MBF for 

1993-1995 (MBF=thousand board feet) 

1993 1994 1995 Total 

Salvage volume 3,211 ---- 1 ---- I 3,211' 

Thinning 18,939 16,022 3,408 38,36g2 vo lume 

Total 22,150 16,022 3,408 41,580 

No projected salvage volume although salvage 

volume will most likely occur. 

* Additional volume is being proposed on the 

Wambaw Ranger District in this three-year 

period . 

DISCUSSION 

Three years after Hurricane Hugo 

destroyed 87% of the active cavity 

trees and 63% of the RCWs on the FMNF, 

the RCW population has recovered 

remarkably, Popular opinion and current literature would have suggested 

that a continued and severe decline of 

the RCW population could be expected. 

Losses from Hugo were thought to be 

insurmountable: loss of birds, disruption of group composition, loss of 

cavity trees, the tremendous loss of 

foraging habitat, and fragmentation of 

the forest. Instead, the population 

is at 333 groups, instead of perhaps 

100-125 groups or less had there been 

no restoration efforts, This recovery 

is primarily due to the implementation 

of an artificial cavity program and the 

efficacy of artificial cavities. 

Forty-five, 60, and 61% of RCW nests 

were in artificial cavities in 1990, 

1991, and 1992, respectively. 

Excellent reproductive attainment 

(Table 6) and dispersal of RCWs produced during the past three nesting 

seasons has led to this increase, New 

groups are being formed by RCWs occupying recruitment clusters or by single 

birds attracting mates. We estimate 

1285 RCWs successfuLly fledged in the 

three years since Hugo, and these birds 

have taken advantage of the opportunities provided by single-bird clusters 

and vacant recruitment clusters. 

Although no quantitative data on the 

number of floaters in the population 

exists, they are present and likely 

responsible for the quick occupation of 

recruitment stands with artificial 

cavities. The number of 2-bird groups 

has increased annually, but has slowed 

(8.5% increase in 1992 as compared to 

23.0% in 1991). It is unlikely that 

future increases will be this high 

because not enough suitable habitat 

exists at this time to sustain this 

continued rate of growth. 

Currently we see the biggest threats to 

the population to be: 

1) the desire by some individuals, 

agencies, and organizations for 

more hardwoods throughout the 

FMNF ; 

2) encroachment of both pine and 

hardwood midstory into RCW 

clusters ; 

3) the general lack of potential 

cavity trees and increased cavity 

tree mortality; 

4) another hurricane. 

If successfully implemented, management programs designed to grow more 

hardwoods throughout the FMNF would 

have a negative effect on the RCW. 

Significant increases of hardwood in 

RCW habitat and potentially suitable 

habitat would not only most likely 

cause a loss of groups, but also 

decrease the potential for growth and 

expansion of the existing population. 

Midstory problems on the FMNF are 

compounded by the flush of new growth 

in clusters, in the wake of Hugo 

opening the forest canopy and 
stimulating growth of shade intolerant 

species. It is hoped that an aggressive prescribed burning program combined with mechanical treatments and 

the application of herbicide can 

control most of this growth, 

Another managment challenge includes 

controlling loblolly pine regeneration 

in clusters with low basal areas. Our 

goal is to reestablish foraging and 

nesting habitat as quickly as possible 

for long-term recovery of the RCW. 

However, with loblolly pine regenerating in clusters, fire may be 

excluded to protect the seedlings and 

saplings, creating a pine midstory in 

clusters. Pine encroachment will also 

cause abandonment of clusters if not 

controlled (Loeb et al. 1991). 

No doubt we will have to develop a 

strategy that both controls pine midstory and encroaching hardwoods, and 

facilitates pine regeneration for 

improvement of RCW habitat. 

An important factor that became apparent during the last two years was the 

increasing mortality of cavity trees. 

RCWs are making cavities on their own, 

but the general lack of potential 

cavity trees and increased mortality 

of cavity trees may affect some 

groups, It is likely that some groups 

can not locate or construct enough 

cavity trees to offset the mortality 

of existing cavity trees. A shortage 

of trees suitable for artificial 

cavities is anticipated, but the 

extent of this shortage is unknown. 

Hopefully, in most cases it will be 

possible to shift the cluster to 

another stand. There is no doubt that 

the current RCW population would be a 

fraction of what it is now without the 

use of artificial cavities, and we 

doubt that the current population can 

maintain its current level without the 

continued construction of artificial 

cavities. However, the rapid development of nesting habitat and the potential for provisioning recruitment 

stands with artificial cavities will 

hopefully provide suitable habitat and 

clusters necessary to recover the 

population, 

Ironically, the amount of sawtimber 

surviving Hugo is similar to the 

amount of pine sawtimber that existed 

when the FMNF was acquired, and the 

number of pine stems 5-9" dbh on the 

FMNF now is twice what it was in 1936 

(Table 1) (Grumbine 1936). Pine 

stands 40 years old and younger survived well (Figure 1). Stands that 

survived Hugo with less than 30 sq. ft. 

ba were considered sparse or destroyed 

and were placed into the 0-10 year age 

class, although some stands categorized 

as such support RCW clusters and 

residual trees that represent potential 

RCW cavity trees. In addition, the 

number of pine stems r 10" dbh is only 

slightly less than what was present in 

1936 (Table 1) (Grumbine 1936). The 

F&fNFrs RCW population recovered largely 

on its own from the conditions that 

existed in 1936, despite the fact that 

the first 30 years of management 

included cutting of cavity trees and 

entire clusters in thinnings and regeneration harvests (Hooper et al. in 

press). By 1989 the population was 

essentially recovered. Presently, 

conditions are similar to those in 

1936. The number of potential cavity 

trees surviving Hugo, the potential for 

developing foraging and nesting habitat 

quickly, and the amount of pine in 

regeneration will contribute greatly to 

the long-term recovery of the RCW on 

the FMNF, The more foraging habitat 

and potential cavity trees, the more 

probable the recovery of the populat ion. 

Considering the potential for managing 

future RCW habitat, it is likely that 

the RCW population on the FMNF can 

reach a recovered level (500 active 

groups or 250 effective groups) in 

time, assuming another hurricane causing catastrophic losses does not impact 

the FMNF. Hurricanes hitting the FMNF 

within the next 50 years would be 

capable of destroying most of the trees 

with artificial cavities and many of 

the trees without cavities that were 

injured by Hugo. In the next 100 

years, 45 hurricanes are expected to 

make direct hits on the 11 most vulnerable recovery areas (Hooper and McAdie 

1994). Four of these hurricanes will 

bring category 111 winds to 4 of the 

recovery areas, 2 of the 4 getting hit 

twice by such winds. Perhaps the most 

vulnerable recovery area is the FMHF 

(Hooper and McAdie 1994). Fortunately, 

not all of the RCW population and 

habitat was destroyed, although 3 of 4 

major concentrations of RCWs on the 

FMNF were severely impacted by Hugo, A 

more uniform spatial distribution of 

clusters on the FMNF would have 

resulted in less impacts to the entire 

population and would be desirable so 

that concentrations of RCWs would not 

be severely impacted. 
The big lesson from Hurricane Hugo is 

that an RCW population suffering 

catastrophic losses can be stabilized 

and increased, at least over the short 

term, given that integrated managment 

efforts strive for common goals. This 

is important considering the expected 

er of hurricanes to hit recovery 

areas in the next 100 years (Hooper 

and McAdie 1994). A myriad of management efforts led to an increase of the 

RCW population on the FMNF before 

Hugo, and the continuation of these 

efforts will no doubt contribute to 

the eventual recovery of the RCW on 

the FHHF after Hurricane Hugo. In 

only three years, the population of 

RCWs on the FMHF has increased 

greatly; breeding groups fledged 1285 

young, much of this recruitment coming from artificial cavities, Given the 

enormous impacts to the RCW population 

on the FMNF in 1989 and its apparent 

subsequent recovery, it is highly 

probable and technologically possible 

that similar results could be achieved 

on other recovery areas not impacted 

by hurricanes. 

ACKNOWLEDGMENTS 

We would like to express thanks to the 

many persons that have contributed to 

the success of RCW recovery on the 

FMNF. District Rangers Jim Brotherton 

and Glen Stapleton, their immediate 

staff, support personnel, and District 

employees, all gave full support and 

cooperation for this effort. The 

Southeastern Forest Experiment Station 

(SEFES) was primarily responsible for 

the initiation of the artificial 

cavity program, providing initial and 

continued support for the project. 

The Supervisorfs Office of the FMNF, 

the Southern Region Office, and the 

Washington Office of the Forest 

Service are to be commended for the 

quick response for funding and 

support. Jerry Henderson, Oscar M. 

Stewart, Ronald E.F. Escano, Michael 

Lennartz, Charles C. Vansickle, and 

Eldon W. Ross were instrumental in 

these efforts. Wildlife biologists 

and technicians from Region 8 detailed 

to the FMNF after Hurricane Hugo spent 

many months collecting the data 

necessary to plan and build a program 

of recovery for the RCW. Carol 

Copeyon, Jay Carter, John Hanunond, 

Dave Allen, and Sheryl Sanders taught 

us the original techniques for making 

artificial cavities. Fort Bragg and 

Camp Lejeune provided personnel and 

vehicles necessary to initiate the 

recovery work. This remarkable 

recovery could not have been accomplished without the personnel that have 

to date installed approximately 1000 

artificial cavities for the RCW on the 

FMHF, These people are Carolyn Short, 

Doug Short, Anne Ripley, Joseph Zisa, 

John Young, Richard Lama, Michael 

Weeks, Bradley Morris, Roger Dennis, 

Michael Leslie, Michael Ayers, Brian 

Grant, Chuck Kinsey, Susanne Shipper, 

Will Howard, and Hal White, Thanks to 

the Pine Knot Job Corps Center, KY, for 

supplying inserts. Finally, thanks to 

Jean Reiher of the SEFES for continuing 

to monitor, collect, and compile data 

necessary to our successful program. 

LITEWWRIE: CITED 

Allen, D.H. 1991, An insert method for 

constructing artificial cavities for 

red-cockaded woodpeckers, Gen. Tech. 

Rep. SE-73, Asheville, NC: U.S. 

Department of Agriculture, Forest 

Service, Southeastern Forest Experiment Station. 19 pp. 

Carter, J.H. 111, J.R, Walters, S,E. 

Everhart, and POD. Doerr. 1989. 

Restrictors for red-cockaded woodpecker cavities. Wildl. Soc, Bull. 

17~68-72. 

Copeyon, C.K. 1990. A technique for 

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18:303-311. 

Copeyon, C.K., J.R. Walters, and J.H. 

Carter. 1991. Induction of red-cockaded 

woodpecker group formation by 

artificial cavity construction. J. 

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DeFazio Jr, J.T., M.A. Hunnicutt, M.R. 

Lennartz, G.L. Chapman, and J.A. 

Jackson. 1989. Results of red-cockaded 

woodpecker translocation experiments in 

South Carolina. Proc. Annu. Conf. 

Southeast Assoc. Fish and Wildl. 

Agencies 41:311-317. 

Grumbine, A,A. 1936, Management plan. 

Francis Marion National Forest. 

Unpublished report. 45 pp. 

Hook, D.H., M.A. Buford, and T,M. 

Williams. 1991. Impact of Hurricane 

Hugo on the South Carolina coastal 

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Hooper, R.G., D.L. Carlson, and J.C. 

Watson. In press. The red-cockaded 

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Hugo. In Proceedings of the Nat. 

Council of the Paper Ind. for Air and 

Stream Imp., Southern Regional Meeting, Charleston, SC. 

Hooper, R.G. and R.F. Harlow. 1986. 

Forest stands selected by foraging 

red-cockaded woodpeckers. USDA Forest 

Service, Research Paper SE-259. 

Hooper, R.G., J.C. Watson, and R.E.F. 

Escano. 1990. Hurricane Hugo's initial 

effects on red-cockaded woodpeckers in 

Francis Marion National Forest. North 

Amer. Wildl. and Natur. Resour. Conf. 

55:220-224. 

Hooper, R.G., D.L. Krusac, and D.L. 

Carlson. 1991. An increase in a population of red-cockaded woodpeckers. 

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woodpecker. Proc. of Red-cockaded 

Woodpecker Symposium 111: Species 

Recovery, Ecology and Managment, 

January 25-28, Charleston, SC. In 

press. 

Ligon, J.D. 1971. Some factors 

influencing numbers of the redcockaded woodpeckers. Pages 30-43. In 

R.L. Thompson, ed. The ecology and 

management of the red-cockaded 

woodpecker. U.S. Bur. Sport Fish. and 

Wildl., and Tall Timbers Res. Stn., 

Tallahassee, Florida. 

Locke, B.A., R.N. Conner, and J.C. 

Kroll. 1983. Factors influencing 

colony site selection by red-cockaded 

woodpeckers. Pages 46-50. In D.A. 

Wood, ed. Red-cockaded Woodpecker 

Sympssiurn 11. Fla. Game and Fresh 

Water Fish Corn., Tallahassee, FL. 

Loeb, S.C., W.D. Pepper, and A.T. 

Doyle. 1991. Habitat characteristics 

of active and abandoned red-cockaded 

woodpecker colonies. So. Jour* Applied 

For. 16:120-125. 

Sheffield, R.M. and M.T. Thompson. 

1992. Hurricane Hugo: effects on South 

Carolinafs forest resource. Res. Pap. 

SE-284. Asheville, NC: U.S. Department 

of Agriculture, Forest Service, Southeastern Forest Experiment Station. 

51 PP* 

Taylor, W.E. and R.G. Hooper. 1991. A 

modification of Copeyonfs drilling 

technique for making artificial redcockaded woodpecker cavities. Gen. 

Tech. Rep. SE-72. Asheville, NC: U.S. 

Department of Agriculture, Forest 

Service, Southeastern Forest Experiment 

Station. 31 pp. 

Townsend, J.F. 1990. Preliminary data 

report, Hurricane Hugo in the 

Charleston area. National Weather 

Service, Charleston, SC. 

U.S. Department of Agriculture, Forest 

Service, Southern Region. 1985. Wildlife habitat management handbook, 

chapter 420, red-cockaded woodpecker. 

Forest Service Handbook 2609.23Re 

Atlanta, GA. 

U.S. Department of the Interior, Fish 

and Wildlife Service, Region 4. 1985. 

Red-cockaded woodpecker recovery plan. 

Atlanta, GA. 88 pp. 

Van Hooser, D.W. and A. Hedlund. 1969. 

Timber damaged by Hurricane Camille in 

Mississippi. U.S. Forest Service 

Resources Note 50-96. New Orleans, LA. 

5 PP* 

Van Balen, J.B. and P.D. Doerr. 1978. 

The relationship of understory to 

red-cockaded woodpecker activity. Proc. 

Southeast. Assoc. Fish and Wildl. 

Agencies 32182-92. 

Reprinted with permission. Proceedings 

of Red-cockaded Woodpecker Symposium 

111: Species Recovery, Ecology and 

Management, January 25-28, Charleston, 

SC. To be published by College of 

Forestry, Stephen F. Austin State 

University, Nacogdoches, TX. 

National Oceanic and Atmospheric 

Administration. 1989. Climatological 

Data, South Carolina, Dec. 1989, Vol. 

92, No. 12. National Climatic Data 

Center, Asheville, NC. 
mMICWES THE LONG-TEm 

THE IUEII3-COC ED WOODPECKER 

Robert G. Hooper and Colin J. ~c~die' 

Abstract--Hurricanes will play a major role in the longterm management of the red-cockaded woodpecker (Picoides 

borealis) [RCH], Historical evidence indicates that 

hurricanes can destroy extensive areas of forests. Forests 

are helpless in the face of catastrophic winds, but such 

winds are limited in extent in hurricanes. Most damage is 

caused by lesser winds interacting with tree and site 

factors, It may be possible to enhance tree survival 

silviculturally by modifying tree factors. The vulnerability of RCW recovery areas to hurricanes is largely 

determined by their distance from the coast. The 4 most 

inland of the 15 recovery areas are essentially immune from 

severe hurricane-induced winds. The mean time between 

category I and 1x1 force winds occurring over 1 or more of 

the 11 most vulnerable recovery areas is 2 and 16 years, 

respectively. On average in 100 years, 45 hurricanes are 

expected to deliver at least category I force winds to 10 

of the 11 most vulnerable recovery areas. Six of these 

hurricanes are expected to bring very destructive winds of 

at least category 111 force to 4 of the recovery areas. 

Repeated hits to the same areas could extirpate their RCW 

populations. It seems certain that at least 1 recovery 

area will always be in the process of restoration from 

hurricane damage, Currently, at least 2 recovery areas are 

in that process, 

INTROI>UCTION 

Hurricanes have the potential to 

instantly destroy the habitat of 

red-cockaded woodpecker [RCW] over 

large areas. A hurricane's effects 

can be long lasting, and some 

probability exists that an area will 

get hit again before it has had time 

to recover from its last hurricane. 

From 1970 when the RCW was listed as 

endangered, through 1991, there had 

been only 0.68 hurricanes per year 

making landfall within the range of 

Robert G. Hooper, U.S.D.A., Forest 

Service, Southeastern Forest Experiment Station, Charleston, SC 29414; 

Colin J. P.lcAdie, U,S.D.C,, NORA, 

National Weather Service, National 

Hurricane Center, Coral Gables, FL 

33146 

the RCW (from Galveston, TX to the 

NC-VA border), This is the lowest 

frequency of hurricanes for any period 

of similar length since 1899, and is 

half the frequency from 1899 through 

1969 (Nemann et al. 1987). Thus, the 

first 2 decades of recovery of the RCW 

were conducted during a lull in hurricane occurrence. During this lull, 5 

recovery areas were impacted by hurricanes, and the populations on 2 of 

these areas suffered significantly. We 

can probably expect an increase in 

frequency of hurricanes in the coming 

decades (Gray 1990). In addition, 

there is some concern that global 

climate changes may significantly 

increase the frequency and intensity of 

future hurricanes (Walker et al. 1991). 

It seems evident that hurricanes will 

have some role in the long-term management of RCW recovery areas (Figure I). 

Our paper explores this role, 
Figure 1--Location of red-cockaded woodpecker recovery sites: (1) Sam Houston 

National Forest [NF); (2) Ft. Polk-Vernon District, Kisatchie NF; (3) Bienville 

NF; (4) DeSsto NF; (5) Oahulge District, Talladega NF; (6) Talladega-Shoal Creek 

Districts, Talladega NF; (7) Eglin Air Force Base-Blackwater State Forest-Conecuh 

NF; (8) Apalachicola NF; (9) Osceola NF; (10) Piedmont National Wildlife 

Refuge-Oconee NF; (11) Ft, Stewart; (12) Francis Marion NF; (13) Carolina Sandhills 

National Wildlife Refuge-Sandhills State Forest; (14) Ft. Bragg; (15) Croatan NF 

(from Lennartz and Henry 1985). 

THE HISTORICAL RECORD 

Damage to the southern pine 

forest 

In assessing the risk to RCW recovery 

areas from future hurricanes, it is 

important to understand the damage 

these storms can cause to pine 

forests. One approach is to examine 

the damage inflicted by past hurricanes a able 1). ~iven the human 

tragedy associated with hurricanes, we 

suspect that forest damage has frequently gone unreported. Some evidence exists for hurricane damage to 

forests prior to 1875 (Ludlum 1963), 

but it is not quantitative either in 

the extent or degree of damage. Nonetheless, it appears that earlier 

hurricanes were very destructive to 

the virgin forests of the time. 

By 1900, there was increased economic 

interest in forest resources in the 

South (Walker 1991:97-101), and 

foresters and lumbermen were making 

quantitative reference to hurricane 

damage. But we suspect that hurricanes that hit after the old-growth 

forests had been cut (1885-1930 

depending upon region) had relatively 

little to destroy until fairly recent 

(say after 1960). Thus, it is difficult to get a clear picture of potential hurricane damage to forests from 

the historical record alone. 

The hurricanes of 1875 and 1900 in 

Texas did impressive damage to large 

areas of forests, as did the 1906 

hurricane in Mississippi (Table 1). 

The 1906 hurricane may have done more 

damage than Hugo. There seems to be a 

pattern of increasing damage over time 

beginning with Hazel in 1954 and continuing with Audrey in 1957, Gracie in 

1959, Camille in 1969, Federick in 1979 

and Hugo in 1989. This trend may be due 

in part to the increasing age of the 

southern forest. Hugo was 5 times more 

destructive to forests in the South 

than any previous hurricane in the past 

4 decades. There can be little doubt 
Table 1--Hurricanes that occurred within the range of the red-cockaded woodpecker 

since 1875 for which forest damage was reported. 

Year State Damage Reference 

TX Almost completely destroyed old-growth loblolly in 

20x100 mile area. 

FL Enormous d ge to pine in 50-mile-wide strip. 

TX 50% of oak and pine timber in 2000-square-mile area 

blown down. Nearly 100% of trees down on thousands 

of acres. 

30-90% of timber in 50x150-mile area blown down. 

10% of timber in 2 parishes lost. 65% of virgin 

longleaf blown down. 

Extensive areas of even-aged longleaf established 

following hurricane, 

10% of turpentine trees killed. 

50-75 million board feet of pine blown over in 30-mile 

wide strip. 

Many pines and hardwoods in 50x50-mile area were 

destroyed. 

Hazel: widespread but unquantified damage. 

LA Audrey: 212 million board feet of merchantable timber 

killed. 90 miles inland 10 million board feet of virgin 

loblolly killed. 

SC Gracie: 580 million board feet of timber damaged. 

LA Hilda: about 4 million board feet expected to be 

salvaged. 

LA Betsy: 200 million board feet of timber killed. 

MS, Camille: 1.2 billion board feet of sawtimber and 1.3 

LA million cords of pulpwood on 115-mile strip 20-60 

miles wide damaged. 

FL Eloise: 400,000 cords of pine and 270,000 cords of 

hardwood damaged. 

MS, Frederick: 3.4 billion board feet of sawtimber (68% 

AL pine), plus 881,000 cords of pulpwood damaged. 

TX Alicia: 56 million board feet damaged in Sam Houston 

National Forest. 

FL Kate: 80,000 mostly older longleaf pines destroyed on 

Apalachicola NF, 100 miles inland, 10% of old-growth 

longleaf killed, 

SC, Hugo: In SC 10.8 billion board feet killed, plus 9.6 

NC billion in critical condition. In NC, 1 billion board 

feet destroyed. 

Bray 1901 

Henry 1896 

Bray 1901 

Dunston 1910 

Foster 1912 

Boyer 1991 

Annon. 1928 

Annon. 1935 

Bradwell 

1947 

Camey and 

Hardy 1962 

Seamon 1954 

Derr and 

Enghardt 

1957 

Flory 1960 

Hurst 1965 

Robinson 1965 

Annon. 1965 

Van Sickle 

and Hedlund 

1969; 

Touliatos and 

Roth 1971 

Wilkinson 

et al. 1978 

MFC 1979 

L. J. 

Carmical, 

pers. commun. 

Bodie 1985; 

Platt et al. 

1988 

Sheffield and 

Thompson 

1992; 

Doggett 1989 
that much of the dmge resulted from 

the extensive areas of pine sawtimber 

in Hugo's path (Sheffield and Thompson 

1992). Bray (1901), Foster (1912), 

and Derr and Enghardt (1957) made 

special note of hurricane destruction 

to the old-growth pine forest (Table 

1) 

ge to RCw Cavity Trees and 

Recovery Areas 

Note that the references to hurricane 

strength in the following section are 

hourly interpolations of mximum sustained winds (1-minute average) near 

the storm center using estimates of 

such winds that had previously been 

made at 6-hour intervals. These data 

were obtained as part of the printout 

from the HURISK model (Neumann 1987) 

we used to estimate average time 

between hurricane occurrences. The 

threshold maximum sustained winds for 

Saffir-Simpson category I, 11, 111, 

IV, and V hurricanes are 74,96, 111, 

131, 155 mph, respectively (Saffir 

1977). 

Hurricane Hugo. The Francis Marion 

National Forest (NF) (Figure 1) 

suffered catastrophic loss to its RCW 

population, cavity trees and foraging 

habitat from Hugo. The storm 

destroyed 87% of the cavity trees, 

killed 63% of the birds, and destroyed 

70% of the foraging habitat (Hooper et 

al. 1990). Overnight, the population 

was reduced from 477 groups down to 

239 groups. The 239 groups reflected 

a response to installation of 537 

artificial cavities prior to the first 

nesting season following Hugo. 

Without the artificial cavities the 

number of groups may have been as low 

as 100 (Watson et al. 1994). 

Hugo was a category IV hurricane at 

landfall, and a category 111 and then 

11 as it passed over the Francis 

Marion. The Carolina Sandhills 

National Wildife Refuge (Figure 1) 

lost 10% of its cavity trees from Hugo 

(David H. Robinson, pers. comun.). 

Had Hugo turned more northerly, loss 

of cavity trees on the refuge could 

have been substantial. Severe loss of 

cavity trees occurred over an area >50 

miles wide 15 miles from the coast, to 

at least 10 miles wide 110 miles 

inland (Figure 2). 

Hooper et al. (1990) thought RCW 

cavity trees were 2-4 times more 

vulnerable to wind than trees without 

cavities. Lipscomb and Williams 

(1994) found that cavity trees 45 

miles from the center of Hugofs storm 

track were 4 times more vulnerable to 

ge than trees without 

cavities. Eighty-six percent of the 

heavily damaged cavity trees broke at 

the cavity (Lipscoh and Williams 

1994). 

thesis that RCW cavities weaken 

trees is support& by Watson et ax. 

(1994), who found 53% of the cavity 

trees lost in Francis Marion NF broke 

at the cavity; 10% broke above the 

cavity and 19% below the cavity, and 

the remaining 18% were uprooted. 

Engstrom and Evans (1990) reported 6 of 

8 wind-killed cavity trees broke at the 

cavity and 2 snapped below the cavity. 

Other hurricanes. Kate passed over the 

western edge of the Apalachicola NF 

(Figure 1) in 1985 with category I 

force winds. About 80,000 trees, 

mostly older longleaf pines, were blown 

down or broken (Bodie 1985). Balboni 

(1985) estimated more than 80 cavity 

trees were killed. This number was 

only about 4% of the cavity trees on 

the western half of the Apalachicola 

(Susan M. Fitzgerald, pers. commun.). 

Alicia, damaged about 56 million bard 

feet of timber in the Sam Houston NF 

(Figure 1) in 1983 (L.J. Carmical, 

pers. commun.). The storm did not have 

maximum sustained winds of hurricane 

force by the time it was abreast of the 

center of the Sam Houston. Wind damage 

exacerbated a southern pine beetle 

(Dendroctonus frontalis) epidemic which 

eventually destroyed more timber than 

Alicia. Conner et al. (1991) reported 

about 3% of the RCW cavity trees were 

killed outright by Alicia, but that 

during the 5 years after Alicia 26% of 

the cavity trees were lost. 

Eloise passed over Eglin Air Force Base 

(Figure 1) in 1975 as a category I11 

and I1 hurricane. Significant forest 

damage occurred on 55-60% of the 

400,000-acre area (Hilkinson et al. 

1978). Most of this damage was to sand 

pine (Pinus clausa) (Stephen M. Seiber, 

pers. comun.), a species of little or 

no value to RCW. Seiber stated that 

little damage was done to RCW cavity 

trees because most were west of the 

storm track. 

The DeSoto NF (Figure 1) suffered 

significant damage from 3 hurricanes 

starting with Camille in 1969 (Wayne H. 

Stone, pers. comun.). Camille was a 

category V hurricane at landfall but 

had decayed to a category I1 when 
DISTANCE FROM WIND CENTER (MILES) 

Figure 2--Percentages of red-cockaded 

woodpecker cavity trees in 6 by 6 mila 

areas that were destroyed by Hurricane 

Hugo, relative to the distances from 

the wind center tract and the coast. 

Data are from Cely (1991); Lipscomb 

and Williams (1994); D.L. Carlson, 

J.E. Cely, C.J. Townsend, D.H. 

Robinson, J.C. Watson (pers. 

co~unications). 

abreast of the west side of the 

DeSoto. Ninety million board feet of 

timber were salvaged from the DeSoto 

and it was estimated that at least 12 

clusters of RCW cavity trees were 

destroyed by Camille, In 1975, 

Frederick passed on the east side of 

the DeSoto as a category I1 hurricane 

when abreast of the DeSoto, After 

Frederick, 110 million board feet were 

salvaged from the DeSoto and 9 clusters of RCW cavity trees were 

destroyed or heavily damaged. 

In 1985, Elena passed to the southwest 

of the DeSoto as a category I1 hurricane. After Elena, 8 million board 

feet of timber were salvaged from the 

DeSoto, and 4 RCW clusters were 

destroyed or heavily impacted, The 

DeSoto had only 18 active clusters in 

1989 (Dennis L. Krusac, pers. comun,). 

RS AFFECTXWGC FOREST 

a1 forest 1 

forests var thin 

of a hurricane. A better 

understanding of this variation might 

help in derivation of a strategy for 

dealing with future hurricanes. We can 

think of the total d ge from a hurricane as simply the sum of the damage to 

individual stands of trees. Stand 

damage is a function of the hurricane 

wind field parameters, the position of 

the stand in the wind field, rainfall, 

tree factors, and site factors (Figure 

3) 

Hurricane wind field parameters affecting the potential for forest damage are 

maximum sustained winds, horizontal 

wind profile, forward speed of the 

storm, decay rate as the hurricane 

progresses inland, associated rainfall, 

and the frequency, intensity and aerial 

extent of down bursts, The damage 

potential of a hurricane is filtered 

through site and tree factors, which 

either exacerbate or ameliorate the 

actual damage that occurs. With catastrophic winds (probably category V 

force winds), site and tree factors are 

overridden; any stand subjected to such 

winds will be destroyed (Hook et al. 

1991). However, such winds over land 

usually occur over a relatively small 

portion of the area affected by most 

hurricanes. Thus, most forest damage 

occurs from an interaction of wind 

field parameters, tree factors and site 

factors (Figure 3). 

Wind Field Parameters 

Horizontal wind profiles. In the 

northern hemisphere the highest maximum 

sustained winds usually occur on the 

right side (facing the direction of 

forward motion) of hurricanes. The 

high velocity of wind near the eyewall 

is supplemented by the hurricane's 

forward speed (Simpson and Riehl 1981). 

Thus, forest damage tends to be more 

severe on the right than on the left 

side of hurricane tracks. This skewed 

effect was prominent in Hugo (Sheffield 

and Thompson 1992, Doggett 1989) and 

was seen to a lesser extent in Camille 

(Touliatos and Roth 1971). An exception to this rule occurred with Hazel. 

More forest damage occurred on the left 

side of the track because the heaviest 

rainfall occurred there (Trousdell 

1955). 
I STAND DAMAGE 1 

I WIND 'JELOGITY 

I EXTREME / 

MAXIMUM SUSTAINED 

WINOS I:-MIN1 

Figure 3--Major factors that affect 

hurricane damage to an individual 

forest stand. The total damage to a 

region from a hurricane is the sum of 

the damages to individual stands. 

Because of the relationships shown 

here, forest damage tends to be 

patchy. 

The radius of maximum winds (RMW) is 

the "radial distance outward from the 

center of the eye where the winds 

reach a maximum value. This typically 

occurs a few miles radially outward 

from the eyewall" (Neumann 1987). On 

average, the RNW varies directly with 

latitude and inversely with storm 

intensity, with latitude having the 

greatest effect. The difference in 

latitude between the southern-most and 

northern-most recovery areas is about 

5 degrees, resulting in an average 

increase in RNW of 5 miles (Neumann 

1987). Beyond the RMH, wind velocity 

decreases with distance from the 

center of circulation. Wind damage 

follows this same pattern: damage is 

greatest near the RMW and decreases as 

one moves away from the hurricane 

center. 

Gusts. Much of the damage to forests 

may be caused by short-duration gusts 

(2-4 seconds) resulting from turbulence (Savill 1983); and from extreme 

gusts associated with extremely convective rainbands, both within and 

external to the eyewall (Hook et al. 

1991, Powell et al. 1991). These gusts 

may partially explain the patchy 

occurrence of damage to forests from 

hurricanes (Bray 1901, Curtis 1943, 

Derr and Enghardt 1957, Flory 1960, 

Robinson 1965, Burst 1965, Wilkinson 

et al. 1978, Doggett 1989, Hook et al. 

1991, Sheffield and Thompson 1992). 

Damage caused by extreme gusts is 

probably mistaken for tornadic damage. 

Tornadoes are associated with about 25% 

of the hurricanes making landfall in 

the United States. Typically, when 

they do occur, tornadoes are found in 

the right front quadrant of large 

hurricanes (Anthes 1982:62). 

Decay rate, Barometric pressure 

increases and wind velocity decreases 

after hurricanes make landfall. The 

decay rate strongly affects potential 

damage from a hurricane. Three major 

physical effects are responsible for 

the decay of hurricanes over land 

(Anthes 1982:62). The most important 

factor may be the sudden reduction in 

evaporation as the storm leaves the 

ocean. A second factor is that during 

the hurricane season, the land is 

cooler than the ocean and the low-level 

air is cooled rather than heated by the 

underlying surface. Lastly, the 

rougher surface of the land causes more 

friction than the ocean. 

Rainfall 

The amount of rain prior to and during 

hurricanes interacts with soils to 

greatly increase damage to forests, 

especially damage from less intense 

storms. Saturated soils can behave as 

a liquid, greatly reducing the holding 

ability of tree roots (Day 1950, Derr 

and Enghardt 1957, Trousdell et al. 

1965). 

Damage from Hurricane Hazel was probably lessened considerably by a dry 

summer and by the rainfall distribution resulting from the hurricane 

(Trousdell 1955). Heavy rainfall for 

the 9 months preceding the 1900 

Galveston Hurricane was credited with 

contributing to the enormous forest 

damage from that storm (Bray 1901). 

Others have also implicated rainfall as 

a major factor in wind-related forest 

damage (Curtis 1943, Grano 1953, Croker 
1958, Hurst 1965, Trousdell et al. 

1965), 

Influence of Tree Factors on 

Species. Derr and Enghard (1957) 

thought slash pine (Pinua elliottii) 

plantations on wet, shallow soils, 

were more susceptible to windthrow 

during Hurricane Audrey than loblolly 

(P. taeda) plantations on similar 

soils. Grano (1953) found loblolly to 

be many times more wind resistant than 

shortleaf pine (P. echinata) on soils 

with poor internal drainage. From 

their experience with Hurricane 

Camille, Touliatos and Roth (1971) 

ranked longleaf (P. palustris) , slash, 

and loblolly in that decreasing order 

of resistance to breakage, uprooting, 

insects and disease. 

Hook et al. (1991) found no difference 

in the loss of longleaf (89%) and 

loblolly (91%) pines that were subjected to eyewall winds during Hugo. 

However, in an area 45 miles to the 

right of the storm track, only 27% of 

the longleaf was damaged, compared to 

52% of the loblolly. In the same 

area, there was little difference in 

the percentages of longleaf and 

loblolly that suffered fatal damage 

(7.8 vs 9.0%, respectively) (Gresham 

et ale 1991). Loblolly, however, was 

much more susceptible to defoliation 

and top breakage than longleaf (17.5 

vs 4.5%, respectively), Some 26.7 

percent of the pond pine (P. serotina) 

suffered fatal damage. 

Sheffield and Thompson (1992) saw no 

difference in resistance to wind damage among loblolly, longleaf, slash 

and pond pine throughout South 

Carolina from Hugo, But in the 

Francis Marion NF, where some of the 

strongest winds occurred, 56% of the 

longleaf r 10 inches DBH survived, 

compared to 40% of the loblolly 

(comparison based on inventories made 

in 1986 and 1990 by the Forest 

Inventory and Analysis Work Unit, 

Southeastern Forest Experiment 

Station, Asheville, NC). 

Pond pine seems highly vulnerable to 

wind damage. Pond pines often have 

heartrot and grow on unstable soils 

(Bramlett 1990). These factors 

probably account for its vulnerability. Among the other pine species, 

none seems to have a major advantage 

over the others in the ability to 

survive hurricanes. Loblolly may be 

more windfirm than slash on wetter 

sites. Longleaf sea to be more 

resistant to fatal wind damage than 

loblolly. But, because site and tree 

factors have not been accounted for in 

the assessment of vulnerability among 

species, we are not certain these 

apparent advantages are real. Comparisons mong species are also confounded by the patchy distribution of 

hurricane damage caused by extreme 

gusts and down burst^^ 

Tres age and size, Age and size affect 

tree survivability in strong winds. 

Typically, the older and larger trees 

are more susceptible to fatal wind 

damage than younger and smaller trees, 

In what is now the Francis Marion NF, 

n (1905) reported that windfalls 

were common in over-mature loblolly 

(some of the windfall was due to 

earlier fire damage). In Louisiana, 

the major causes of tree loss over a 

5-year period in a virgin longleaf 

stand with trees 175-240 years old were 

windthrow (not of hurricane origin) and 

bark beetles (Chapman 1923). Windthrow 

usually occurred after heavy rains 

(implicating soils) and usually 

involved the larger, older trees. The 

major sources of mortality among 

longleaf > 11 inches DBM in a virgin 

stand in Georgia over a 4-year period 

were lightning and wind (54 and 31% of 

the mortality, respectively) (Platt 

et al. 1988). Later, Hurricane Kate 

killed 10% of the larger trees in the 

stand, about 2.5 times the mortality 

observed during the 4 years of study. 

Chapman (1923) stated that hurricanes 

(as evidenced by the orientation of 

windthrow mounds) had created even-aged 

stands in former old-growth longleaf. 

This statement suggests that the vast 

majority of canopy trees had been 

destroyed. 

Trousdell (1955) reported that young 

stands suffered minor damage while 

older stands, especially those that 

were recently thinned or had low stocking, sustained significant damage 

during Hazel. In a 1,365-acre area 50 

miles east of the storm track and 70 

miles after landfall, Hazel destroyed 

6.1% of the pines > 10 inches DBH, 

Derr and Enghardt (1957) found that 

Audrey damaged older stands more than 

younger ones. Stands below merchantable size and 30- to 40-year-old longleaf were not seriously damaged. 

Managed stands of intermediate age were 

damaged to varying degrees, and virgin 

stands of loblolly were heavily damaged. Much of the bole breakage in 

large loblolly pines was thought to be 

associated with heartrot. 
Pulpwood-sized stands suffered less 

ge from Betsy than sawt 

ds (Robinson 1965). To 

Roth (1971) report hat older stands 

suffered the most ge from Camille. 

Bodie (1985) stated that the majority 

of longleaf pines uprooted and broken 

during Rate were older trees. 

In an area 45 miles to the right of 

Hugo's track, mean DBH's of undamaged 

longleaf, loblolly and pond pine were 

11, 7, and 6 inches, respectively; 

means for trees with fatal damage were 

15, 11, and 13 inches, respectively 

(Gresham et al. 1991). In the Francis 

Marion NF, loss of pines from Hugo 

increased as DBH increased (Figure 4). 

Hooper et al. (1990) reported that 

sapling and pole stands were frequently heavily damaged but that 

enough trees survived to make a 

manageable stand. Many 30- to 40- 

year-old pine stands in the Francis 

Marion were moderately damaged and 

many mature stands suffered very heavy 

damage. In Congaree Swamp, 90 miles 

inland, Hugo killed 71% of the 

loblolly pines 24-30 inches DBH, 45% 

of those 32-38 inches DBH, and 24% of 

those more than 40 inches DBH (Putz 

and Sharitz 1991). It is not clear 

why those results are contrary to the 

other studies cited in this section. 

0 LONGLEAF 

LOBLOLLY 

DIAMETER CLASS (INCHES) 

Figure 4--Reduction in the number of 

longleaf and loblolly pines by 

diameter classes in Francis Marion 

National Forest as a result of 

Hurricane Hugo. Under normal 

conditions, the percentage change in 

any diameter class would have been 

< 5%. Data are from inventories 

conducted in 1986 and 1990 by the 

Forest Inventory and Analysis Research 

Unit, Southeastern Forest Experiment 

Station, Asheville, NC. 

Stand density. Stand damage is 

inversely related to stand density 

(stocking), with denser stands surviving better than more sparsely 

stocked ones. Closed canopies tend to 

keep wind out of stands (Curtis 1943, 

Alexander 1964, Garden 1973, Wilson 

1984, Foster 1988). Trees also gain 

mutual support from adjacent crowns. 

Recently thinned stands are especially 

vulnerable to winds if the individual 

trees have not had sufficient time to 

develop strong roots and boles, but 

such trees gradually become less 

vulnerable as they respond to the 

increased exposure to wind and the 

temporary reduction in competition 

(Mergen 1954, Savill 1983, Kozlowski 

et al. 1991:491). Hooper et al. (1990) 

observed that 100-year-old longleaf 

stands with 110 square feet of basal 

area were reduced to about 70 square 

feet of basal area by Hugo. Similar 

stands thinned to 70 square feet 3 

years before Hugo were reduced to less 

than 10 square feet of basal area. 

Seed tree and shelterwood stands are 

vulnerable to windthrow for a long time 

(Trousdell 1955, Robinson 1965, Savill 

1983). 

The effect of stand density may be 

misleading in that trees grown in 

stands where competition is less 

intense throughout their life, tend to 

develop superior wind resistance. 

Thus, we do not mean to imply here that 

growing trees in dense stands would 

necessarily be the best long-term 

approach to reducing hurricane damage. 

Taper. Open-grown conifers with 

pronounced stem taper are much more 

resistant to wind breakage from wind 

than trees grown in dense stands 

(Curtis 1943, Mergen 1954, Gratkowski 

1956, Larson 1963, Assmann 1970:60, 

Savill 1983, Smith 1986:398). 

Increased tree taper may be partially a 

response to swaying caused by the wind; 

this effect is inhibited in stands with 

closed canopies (Mergen 1954, Savill 

1983, Burton and Smith 1972, Wilson and 

Archer 1979). 

Curtis (1943) found a direct relationohip between crown development and 

resistance to windthrow and breakage. 

He thought the longer crowns had their 

geometric centers lower down the bole, 

which reduced the leverage affect of 

the wind on the bole. More likely, the 

trees with longer crowns had more taper 

and stronger boles (Assmann 1970:60, 

Smith 1986:100, Farrar and Murphy 1987, 

Oliver and Larson 1990:83, Nix and 

Ruckelshaus 1990). 
at. Mergen (1954) 

thought that windthrow resulted from 

compression failure of roots on the 

leeward side of trees and that roots 

could be strengthened by exposure to 

wind during their development. Resistance to uprooting increases as the 

overall size of the root system 

increases (Frazer 1962, Coutts 1983). 

It is generally thought that opengrown trees or at least trees with 

well developed crowns, have stronger 

root systems than trees grown in dense 

stands, and that thinning of stands 

can improve root development, especially if done when the stands are 

young, and continued into older age (Mergen 1954, Zahner and Whitmore 

1960, Larson 1963, Smith 1986:399, 

Oliver and Larson 1990, Kuiper and 

eoutts 1992). 

Influence of Site Factors on 

Stand Damage 

Soil, Hardpans and other restrictive 

layers can halt the development of a 

taproot in the pines important to the 

RCW (Boyer 1990, Baker and Langdon 

1990, Lohrey and Kossuth 1990, Lawson 

1990). Pulling studies have shown 

that relatively small reductions in 

root development result in significant 

loss of wind firmness (Frazer 1962). 

Thus, it is not surprising that soils 

have frequently been cited as a 

primary factor in wind damage to 

stands, especially when the storms 

were accompanied by heavy rainfall 

(Bray 1901, Foster 1912, Pessin 1933, 

Grano 1953, Croker 1958, Trousdell et 

al. 1965, Foster 1988). The same 

restrictive layers that retard root 

development can also inhibit internal 

soil drainage. Water-logged soils 

behave essentially as a fluid with 

greatly reduced root holding properties (Day 1950, Derr and Enghardt 

1957, Trousdell et ale 1965). 

Soil texture can also affect wind 

firmness (Mergen 1954). Trousdell 

will be at great risk from even a 

category I hurricane and category 111 

force winds would cause catastrophic 

Topography. Topography strongly 

influences wind d ge to trees (Curtis 

1943, Gratkowski 1956, Alexander 1964, 

DeWalle 1983, Foster 1988, Bellingham 

1991). Ridges and valleys accelerate 

winds in sow areas and create protected zones in others. On the lower 

coastal plain, where hurricane-induced 

winds are strongest, however, topography is not very pronounced. Topographic influences on hurricane d 

to forests, are probably greater in the 

more inland recovery areas. 

Adjacent stands, The more uniform a 

canopy, the less the damage from wind 

(Curtis 1943). Gaps in the canopy 

allow wind to enter the stand and cause 

damage (Curtis 1943, Gratkowski 1956). 

In addition, an uneven canopy causes 

turbulence, a principal factor in 

gusting. The rougher the canopy and 

the faster the wind velocity, the 

greater the turbulence (Savill 1983). 

In some areas, partial cuts that 

created small gaps, have led to more 

wind damage than clearcuts that created 

large gaps (Alexander 1964). Several 

studies outside the range of the RCW 

suggested that overall wind loss 

decreases as gap size increases 

(Alexander 1964, Neustein 1965, Gorden 

1973). 

Two additional studies found no relationship between gap size and damage to 

adjacent stands (Ruth and Yoder 1953, 

Gratkowski 1956). The shape of adjacent stand boundaries can funnel and 

accelerate winds, multiplying damage 

(Gratkowski 1956 Alexander 1964, Gorden 

1973, DeWalle 1983, Conner et al. 

1991). The effect of gaps on wind 

damage decreases if residual trees have 

time-to respond to increased growing 

space and become more windfirm. 

et al. (1965) observed that stands on 

moderately coarse-textured soils lost EXPECTED FREQUENCY OF FUTURE 

30% of their trees, compared to 5% frluRRIm]Es 

loss in stands on medium- and finetextured soils, and 51% loss on soils The HURISR Model 

No one can predict when a hurricane with restrictive layers. will hit a recovery area, however, 

The effects of soils on root development and wind firmness are important 

because relatively low velocity winds 

can cause major forest damage to 

stands on shallow, coarse or restrictive soils (Bray 1901, Foster 1912, 

Trousdell 1955, Foster 1988). Thus, 

if a recovery area has such soils it 

it is possible to estimate the mean 

elapsed time between hurricanes 

(return period). Neuxnann (1987) 

developed a model, HURISR, for estimating return periods for tropical 

cyclones with sustained winds of at 

least some threshold strength at 

specified locations within the Atlantic 

tropical cyclone basin. HURISK fits 
site-specific historical information 

for tropical cyclones to probability 

distributions or functions. The 

primary parameters in the model are 

storm distance from the site, maximum 

winds, radius of naaximum winds, 

effects of latitude, horizontal wind 

profile, and frictional effects. The 

model uses a Monte Carlo simulation to 

select sequentially from the distributions of 10,000 tropical cyclones 

within a 150-nautical mile radius of a 

site. The number of years that it 

would take for the 10,000 storms to 

occur is based on the observed frequency of tropical cyclones within the 

150-mile radius. For example, with 

2.00 storms per year, it would take 

5,000 years to have 10,000 cyclones. 

Return periods (mean time between 

events) are then calculated from the 

simulated frequencies for specified 

winds occurring at the site (e.9. the 

center of each recovery area, based on 

the number of years it would take to 

have 10,000 storms. For example, out 

of the 10,000 simulated storms, 25 

might have caused category 111 force 

winds to occur over the site. Thus, 

5,000 years divided by 25 equals a 

return period of 200 years for 

category 111 force winds over the 

site, 

HURISK uses a Weibull distribution of 

maximum wind velocities associated 

with tropical cyclones within 75 

nautical miles of a site and a storm 

count-distance function, to create a 

family of lines representing return 

periods for specified winds at different distances from the site. The 

combination of the site and areal 

return periods allows one to determine 

the return periods for winds having at 

least the specified strength occurring 

anywhere over an area of specified 

size and stated location within the 

Atlantic tropical cyclone basin. The 

data in Tables 2 and 3 were derived 

with these procedures. 

Based on comparisons to actual events, 

the estimated return periods generated 

by HURISK are considered to be reasonably valid for periods up to 100 

years. While the validity of the 

estimates beyond 100 years are less 

certain, they are still the best 

available (Neumann 1987). 

Relative Vulnerability of 

Recovery Areas 

We used HURISK to estimate return 

periods for hurricane-induced winds of 

a specified or greater force (category 

I-IV, Saffir 1977) occurring within the 

boundaries of a specified RCW recovery 

area (Figure 1, Table 2). For application in HURISK, we defined the recovery 

area boundary as the area of a circle 

equal to the area of the irregular 

convex polygon that enclosed the 

recovery area, The area of any private 

lands enclosed by the polygon was 

included as part of the circle. 

The threshold maximum sustained wind 

(1-minute average) expected to occur 

within the boundary of each recovery 

area on average in 100 years as a 

result of tropical cyclones (Table 3)' 

was used as an index of the relative 

vulnerability of each recovery area to 

hurricanes. The 100-year expected 

winds were regressed against distance 

from the center of the recovery areas 

to the coast. Distance from the coast 

accounted for most of the variation in 

the relative vulnerability among the 15 

recovery areas (Figure 5). The closer 

a recovery area is to the coast, the 

more frequently it will experience 

hurricane-induced winds and the more 

intense those winds are 

likely to be. 

The least vulnerable. Least vulnerable to hurricanes a r e t h e Bienville NF, 

Piedmont National Wildlife Refuge 

--Oconee NF, and the Oakmulgee and 

Talladega Ranger Districts of the 

Talladega NF. For these areas, 

estimated return periods for hurricaneinduced winds of at least category I 

strength were r 170 years (Table 2). 

HURISK output indicates the return 

periods for hurricane-induced maximum 

sustained winds of at least category 

111 force are more than 5,000 years for 

these 4 recovery areas. These values 

greatly exceed the model in several 

respects, but do suggest that the 4 

most inland recovery areas may be 

essentially immune to the more 

destructive category 111 force winds, 

The 2 least likely recovery areas to be 

subjected to hurricane force winds are 

the Oakmulgee and Talladega Ranger 

Districts with return periods of 350 

and more than 500 years, respectively, 

for winds of category I force or 

greater (Table 2). Because of the 

paucity of observed hurricanes near 

these two areas, and the fact that 

HURISK does not take into account the 

physical constraints imposed by sites 

located well inland, our estimated 

return periods for the 2 areas are 

questionable, Nonetheless, tropical 
Table 2--Return periods for hurricane-induced winds of at least the specified force 

(Saffir-Simpson Category I-Iv1) occurring within the boundaries of red-cockaded 

woodpecker recovery areas, Return periods were estimated by HURISR. 

Recovery Area 

Miles Category of wind1 

From 

Coast2 I I I: I11 IV 

-------------Return periods (years)------------- 

Francis Marion HF 15 14 43 90 260 

Croatan NF 15 15 55 130 400 

Apalachicola NF 20 16 50 100 325 

~glin- lackw water-Conecuh" 25 20 52 99 250 

DeSoto NF 50 21 55 105 260 

Ft, Stewart 35 25 110 280 >500 

Osceola NF 60 27 140 240 >500 

Ft. Bragg 105 38 120 270 >500 

Sam Houston NF 90 48 290 >500 >500 

Carolina Sandhills NWR-SF 105 50 210 >500 >500 

Ft, Polk-Vernon RD' 90 90 420 >500 >500 

Bienville NF 140 170 >500 >500 >500 

Piedmont NWR-Oconee NF 180 200 >500 >500 >500 

Oakulgee RD' 175 350 >500 >500 >500 

Talladega-Shoal Cr, RD' 200 >500 >500 >500 >500 

Maximum sustained winds (1-minute average) Saffir-Simpson Category I: 74-95 mph. 

Category 11: 96-110 mph, Category 111: 111-130 mph. Category IV: 131-155 mph. 

Miles from center of recovery areas to the coast. 

~glin Air Force Base - Blackwater State Forest - Conecuh NF. 

Ft. Polk and Vernon Ranger District of the Kisatchie NF. 

Talladega NF, 

Table 3--Threshold maximum sustained winds1 expected to occur within the borders of 

red-cockaded woodpecker recovery areas in N-years, on average, as a result of 

tropical cyclones. Expected values were estimated by HURISK. 

N-Year Event 

Recovery Area 10 25 50 100 200 

--------we Maximum Sustained Winds (mph)l---------- 

Francis Marion NF 68 86 101 116 131 

Croatan NF 

Apalachicola NF 

~glin-Blackwater-Conecuh2 

DeSota NF 

Ft. Stewart 

Osceola NF 

Ft. Bragg 

Sam Houston NF 

Carolina Sandhills NWR-SF 

Ft. Polk-Vernon RD' 

Bienville NF 

Piedmont NWR-Oconee NF 

Oahulgee RD~ 

Talladega-Shoal Cr, RD' 

Haxhum sustained winds averaged over 1 minute. 

Eglin Air Force Base - Blackwater State Forest - Conecuh NF. 

Ft, Polk and Vernon Ranger District of the Kisatchie NF. 

"alladega NF . 
Distance From Coast (miies) 

Figure 5--Relationship between 

tropical cyclone-induced 100-year wind 

events that are expected to occur 

within the borders of red-cockaded 

woodpecker recovery areas, and the 

distance from the center of recovery 

areas to the coast, The 100-year wind 

events a r e t h e average threshold 

maximum sustained winds (1-minute 

average) expected in 100 years. 

Expected values were estimated by 

HURISK. 

cyclones can still have hurricane 

force winds that far inland in the 

southern United States, and given the 

uncertainties involved, the Oakmulgee 

and Talladega Ranger Districts should 

not be thought of as being totally 

immune to minimum hurricane force 

winds, 

The most vulnerable, The 11 most 

vulnerable recovery areas represent a 

wide range of return periods: 14 to 

90 years for category I force winds, 

and 90 to more than 500 for category 

I11 force winds of hurricane origin 

(Table 2). Compared to say the 

Francis Marion NF, Ft. Polk-Vernon 

Ranger District is not very vulnerable 

to hurricanes. HURISK indicates the 

return period for category 111 force 

winds occurring over Ft, Polk - Vernon 

RD and Sam Houston NF may be more than 

1,000 years, Nonetheless, those 2 

recovery areas are relatively 

vulnerable to category I force winds. 

The 5 most vulnerable recovery areas 

are Francis Marion, Croatan, 

Apalachicola NF, DeSoto NF, and Eglin 

AFB--Blackwater SF--Conecuh NF (Table 

2). These areas have return periods 

of s 130 years for category I11 force 

winds of hurricane origin, and s 55 

years for category I1 force winds, 

Osceola NF, Ft. Stewart and Ft, Bragg 

have relatively short return periods 

for category I hurricanes 38 years), 

but relatively long ones (2 240 years) 

for category 111 force winds. 

The shorter the return period, the more 

Likely a recovery area will be hit by 

another hurricane before its forests 

can recover from previous hurricane 

damage, For example, it may take the 

 ranc cis Marion NF more than 50 years to 

recovery to its pre-Hugo condition 

(Hooper et al. 1990, Watson et al. 

1994), 

The return time for hurricane-induced 

winds of at least category I force for 

the Francis Marion is only 14 years 

(Table 2)- Such a storm would be 

capable of destroying most of the trees 

with artificial cavities and many of 

the trees without cavities that were 

injured by Hugo, Thus, RCW populations 

on the 5 most vulnerable recovery areas 

are at considerably greater risk of 

extirpation from hurricanes than any of 

the other recovery areas. 

N-year Events 

A useful question to ask for a given 

recovery area is what intensity of wind 

on average, can be expected in a 

specified number of years? N-year 

events for each recovery area were 

determined from the same HURISK output 

as return periods (Table 3). The 

threshold maximum sustained wind that 

the Francis Marion NF, Croatan NF, 

Apalachicola NF, Eglin AFB--Black-water 

SF--Conecuh NF, and DeSoto NF will 

experience on average in 25 years as 

the result of tropical cyclones is r 82 

xnph, sufficient to destroy a signiflcant number of cavity trees. The 

seven most vulnerable recovery areas 

can expect at least 95 mph maximum 

sustained winds every 100 years on 

average. Winds of that velocity can be 

expected to cause serious loss of both 

cavity trees and foraging habitat. In 

comparison, the four least vulnerable 

recovery areas would expect to experience winds of 76 mph in 200 years on 

average. 

N-year events and return periods are 

averages from a distribution of events. 

Therefore, a 100-year event will not 

happen every 100-years, nor will a 

25-year event happen every 25 years, 

etc. The frequency of N-year events 

occurring through time can be described 

by the binomial distribution, from 

which one can determine the probability 

of an event of any N-years occurring 

one or more times in any number of 
years (Formula 4, Appendix I). The 

relationship of the probabilities of 

several N-year events to elapsed time 

is shown in Figure 6. This figure 

essentially describes the recurrence 

of hurricanes over a recovery area. 

For example, to be nearly certain that 

a 100-year event will occur at least 

once, one would have to wait 500 

years. Stated another way, every time 

a 100-year event occurs, it will 

almost certainly have been less than 

500 years since the last such event 

occurred and it will almost certainly 

be less than 500 years before such an 

event occurs again. But six out of 

ten times a 100-year event will occur, 

on average, within 100 years of the 

last such event. And two times out of 

ten, a 100-year event will occur 

within 22 years of the last event. 

There are numerous examples of several 

hurricanes making landfall near the 

same location in a relatively few 

years, but then many years elapsing 

before the same location is again 

visited (Neumann et al. 1987). 

Likelihood of Hurricanes Among 

Recoveq Meas 

There are 15 recovery areas (Figure 1) 

with varying degrees of risk from 

hurricanes (Figure 5). The 4 most 

inland recovery areas have such a low 

probability of hurricane force winds 

occurring over them, we excluded them 

from the following analyses. The 

chance of any one or more of the 11 

most vulnerable recovery areas experiencing hurricane force winds is much 

greater than for a specified recovery 

area. For example, the probability of 

the Francis Marion NF experiencing 

hurricane-induced winds of category I 

and 111 or greater, in a year is 0.069 

and 0.011, respectively (Formula 1, 

Appendix I). In contrast, the probability of at least 1 of the 11 most 

vulnerable recovery areas experiencing 

hurricane-induced winds of category I 

and 111 force in a year, is 0.319 and 

0.060, respectively (Formula 2, 

Appendix I). 

Similarly, the return period for any 1 

or more of the 11 most vulnerable 

recovery areas experiencing hurricaneinduced winds of at least a specified 

intensity, is much less than for a 

given recovery area. The return 

period for category 111 force winds 

occurring over any 1 or more of the 11 

recovery areas is only 16 years 

(Formula 3, Appendix I), compared to a 

return period of 90 years for the 

Francis Marion NF (Table 2). The 

I I 

10 1 00 1 000 

ELAPSED TIME (years) 

Figure 6--Probabilities of N-year 

events occurring over time. Values are 

calculated from the binomial distribution using Formula 4, Appendix I. 

return period for category I force 

winds occurring over any 1 or more of 

the 11 most vulnerable recovery 

populations is only 2 years. Again 

this is much shorter than the 14-year 

return period for category I force 

winds occurring over the Francis 

Marion. 

Expected Number of Hurricanes 

We used the Poisson distribution 

(Formula 5, Appendix I) to estimate the 

total number of recovery areas that can 

be expected to be affected by at least 

1 hurricane-induced wind event of 

designated intensity over t-years 

(Figure 7). For example, it will on 

average take about 500 years for all 11 

of the most vulnerable recovery areas 

to experience at least category 1 force 

winds within their boundaries. However, 8 recovery areas will on average 

experience at least 1 such event in 

only 50 years, and 10 of the 11 areas 

will do so in 80 years (Figure 7). 

Shilarly, 4 of the recovery areas are 

expected to have at least category 111 

force winds occur over them in 100 

years on average (Figure 7). 

While we wait for all 11 of the most 

vulnerable recovery areas to experience hurricane-induced winds of a given 

intensity, some of the 11 areas will 

have numerous such events. In other 

words, more than 11 hurricanes will 

occur among the 11 recovery areas 

before all 11 areas experience winds of 

specified intensity at least once. 

This relationship (Figure 8) was 

estimated by Formula 6, Appendix I. 

For example, in the 500-year period 
YEARS 

Figure 7--Expected number of redcockaded woodpecker recovery areas 

from among the 11 most vulnerable, 

that will experience at least once 

over time, a hurricane-induced wind 

event within their respective boundaries of at least the specified 

Saffir-Simpson category (I, 11, or 

111). Expected numbers of areas were 

calculated by Formula 5, Appendix I, 

using return periods estimated by 

HURISK (Table 1). 

that it takes for all 11 recovery 

areas to experience at least 1 event 

with category I force winds (Figure 

7), 226 such events are expected among the 11 recovery areas (Figure 8). 

Obviously, some of the 11 areas will 

experience many hurricanes before all 

the areas have experienced at least 1. 

Similarly, while category 111 or 

greater winds are expected to occur 

over 4 recovery areas in 100 years on 

average (Figure 7), 2 of those 4 areas 

are expected to have 2 such events in 

that time (Figure 8). 

DISCUSSION 

Uncertainty 

The stochastic nature of tropical 

cyclones adds considerable uncertainty 

to the long-term recovery and management of the RCW. We presented estimated average return times (Tables 2, 

3) and average numbers of recovery 

areas expected to be hit by hurricanes 

(Figures 7, 8). Because our estimates 

are averages, recovery areas could be 

impacted fewer times by hurricanes in 

say the next 100 years than our data 

suggest, or just as likely, they could 

be impacted more times than we estimate. However, the longer the period 

of time that we define as "long-term", 

the less effect stochasticity has and 

in that sense, the more closely our 

estimates may predict the future, 

YEARS 

Figure 8--Expected number of events in 

which hurricane-induced winds of at 

least the specified Saffir-Simpson 

category (I, 11 or 111), will occur 

within the boundaries of any of the 11 

most vulnerable red-cockaded woodpecker 

recovery areas. Expected numbers of 

events were calculated by Formula 6, 

Appendix I, using return periods that 

were estimated by HURISK (Table 1). 

The Average Worst Case Scenario 

~urricane-induced maximum sustained 

winds of category I force can destroy a 

significant number of cavity trees. 

Most recovery populations have demographic problems and suffer from a 

paucity of trees suitable for cavities 

(Costa and Escano 1989). A significant loss of cavity trees can have 

major impact on these floundering 

populations. Category I force winds 

can have a devastating effect on a 

recovery area that has recently been 

hit by a major hurricane. Trees with 

artificial cavities are probably more 

susceptible to breakage from winds than 

trees with natural RCW cavities (Allen 

1991, Taylor and Hooper 1991). Also, 

trees that have survived major winds 

frequently have compression and root 

damage that render them more susceptible to breakage in future winds 

(Mergen 1954, Trousdell 1955, Watson 

et al. 1994). Recovery areas with soil 

limitations can suffer major damage 

from category I force winds, Finally, 

catastrophic loss of trees can occur 

when soils are waterlogged. 

We expect that hurricane-induced maximum sustained winds of category 111 or 

greater force occurring over a recovery 

area will cause tremendous damage to 

cavity trees, potential cavity trees 

and foraging habitat, Such an event in 

1 of the floundering populations can 

cause extirpation, Major hurricanes 
passing over large and relatively 

healthy populations can greatly reduce 

the population and create isolated 

sub-populations. 

In 100 years, on average, we expect 4 

recovery areas to suffer the effects 

of maxim- sustained winds of category 

I11 or greater force (Figure 7). 

of those areas will probably be 

affected twice (Figure 8). In addition, 39 instances of category I or I1 

force winds are expected to occur 

among the 11 most vulnerable recovery 

areas. Some of those could as likely 

hit a recovery area following a 

category 111 hurricane as anywhere 

else, Thus, even in 100 years we can 

expect major hurricane-induced 

problems in recovery populations, 

Clearly, future managers of 1 or more 

RCW recovery areas will be dealing 

with the effects of hurricanes on a 

continuing basis. Currently, at least 

2 recovery areas are suffering from 

past hurricanes. Hugo devastated the 

Francis Marion NF. The RCW population on the DeSoto NF is small and has 

suffered a decline, partially at 

least, as a result of Camille, 

Frederick and Elena. 

What Can We Do3 

The inclusion of inland populations as 

part of the recovery of the species 

was wise (Lennartz and Henry 1985). 

The 4 most inland recovery areas are 

essentially immune from major hurricanes and are at low risk from minor 

ones. These inland areas should 

receive renewed emphasis. Establishment of additional inland recovery 

areas has considerable merit; several 

opportunities exist for doing that on 

public lands. 

Catastrophic hurricane damage is 

fairly limited geographically and 

overall damage is typically patchy. 

Thus, anflhing that can be done to 

increase the geographic extent of a 

population associated with a recovery 

area will enhance its potential for 

surviving hurricanes and its ability 

to recover from them, Probably the 

worst management decision that could 

be made would be to concentrate a 

population into a portion of a 

recovery area. In our opinion, it is 

better to have a given number of 

groups at a lower density on a larger 

area, than to have the same number of 

groups concentrated at a higher 

density in a smaller area, 

Recovery areas under even-aged management have an advantage of having stands 

of different age classes spatially 

distributed. In general, the younger 

age classes survive better than the 

older ones. Recovery from hurricanes 

is enhanced by having stands surviving 

that are 10-50 years old (Watson et al. 

1994). Some reasons to think that net 

tree survival may not be as great under 

uneven-aged mnagaent are the extended 

periods of growth suppression for 

younger trees (Farrar and Boyer 1990) 

and the increased turbulence from. an 

uneven canopy (Curtis 1943, Savill 

1983) . There is general agreement that nothing 

can be done to protect trees from 

catastrophic winds. However, much of 

the damage from hurricanes comes from 

lesser winds interacting with tree 

characteristics (Figure 3). Considerable interest has been shown in windsilvicultural relationships in other 

regions, but almost none has been shown 

within the range of the RCW. One 

reason for this lack of interest has 

been the typically short rotations (ca. 

30 years) used to grow the southern 

pines. Given that recovery of the RCW 

will require extended rotations (ca. 

80-120 years) in order to provide old 

trees for cavities, we think an 

analysis of the best way to grow 

stronger and more windfirm trees would 

be worthwhile. There is much literature that suggests it is possible to 

grow more wind-resistant trees. 

Basically trees need to be grown 

throughout their lives in stands that 

are not overcrowded in order to enhance 

crown development, root development, 

taper, and bole strength. This 

approach to growing trees in recovery 

areas would also reduce the threat of 

southern pine beetle epidemics 

(Thatcher et al. 1986, Belanger et al. 

1988), another very serious threat to 

long-term management of the RCW 

(Rudolph and Conner 1994). 

The importance of recent technological 

advances that can now be used to 

counter the effects of hurricanes can 

not be overstated. The artificial 

cavities developed by Copeyon (1990) 

and Allen (1991) have provided an 

effective response to the loss of RCW 

cavity trees. The use of artificial 

cavities, along with augmentation of 

populations (Allen et al. 1993) when 

necessary, can reduce the effects of 

hurricanes on healthy RCW populations. 
This prediction assumes: 

(1) the responsible agency can 

respond to the crisis, 

(2) enough trees for foraging and 

artificial cavities survive to 

support a population, and 

(3) that the recovery area is not 

soon hit by other hurricanes. 

We may very well lose some 

populations from repeated hits 

by hurricanes. Also at great 

risk are smaller populations 

that are already struggling. 

LITERATURE CITED 

Alexander, R.R. 1964. Minimizing 

windfall around clear cuttings in 

spruce-fir forests. Forest Science 

10:130-142. 

Allen, D.H. 1991. An insert technique 

for constructing artificial redcockaded woodpecker cavities. Gen. 

Tech. Report SE-73. USDA, Forest 

Service, Southeastern Forest 

Experiment Station, Asheville, NC. 

Allen, D.H., K.E. Franzreb, and R.E.F. 

Escano. 1993. Efficacy of translocation strategies for red-cockaded 

woodpeckers. Wildlife Society Bull. 

21:155-159. 

Anonymous. 1928. Third storm of the 

season sweeps over the turpentine 

country. Savannah Weekly Naval Stores 

Review and Jour. of Trade. 

38(25):3,30. 

Anonymous. 1935. Severe losses in 

Perry, Fla. section result of storm. 

Savannah Weekly Naval Stores Review 

and Jour. of Trade. 45(26):15. 

Anonymous. 1965. Coordinated campaign 

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Anthes, R.A. 1982. Tropical cyclones: 

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effects. Meteorological Monogr. 19. 

Assmann, E. 1970. The principles of 

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Ox£ ord . 

Baker, J.B. and O.G. Langdon. 1990. 

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of North America. Vol. 1, Conifers. 

Agri. Handb. 654. USDA, Forest 

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red-cockaded woodpecker colonies. 

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AE)PEHDIX 1 

Fomulae used to calculate the probabilities and expected values for 

hurricanes that were used in the text 

and figures. 

Our basic data were the return periods for category I-V hurricanes passing 

near the center of the 15 red-cockaded 

woodpecker recovery areas (Table 1). 

Those return periods were generated by 

HUaISK (Newnn 1987). A brief 

description of HtJRISR is provided in 

the text. 

The mean number of hurricanes of a 

given category per year, mi, is the 

reciprocal of the return periods in 

Table 1. 

The yearly probability of 1 or more 

hurricanes of a specified intensity 

passing over the center of a specified 

recovery area is equal to, 

The yearly probability of 1 or more 

hurricanes of a specified intensity 

passing over the center of any 1 or 

more of the 15 recovery areas is equal 

to, 

The return period for 1 or more 

hurricanes of specified intensity 

passing near the center of any 1 or 

more of the 15 recovery areas is equal 

to, 

The probability of having 1 or more 

N-year events in t years is equal to, 

The expected n er of recovery areas, 

from among the 8 most vulnerable, that 

will be hit by 1 or more hurricanes of 

specified intensity over t years is 

equal to, 

The expected number of hurricanes of 

specified intensity passing near the 

center of any of the 8 most vulnerable 

recovery areas over t years is equal 

to, 

Reprinted with permission from 

Proceedings of Red-cockaded Woodpecker 

Symposium 111: Species Recovery, 

Ecology and Management, January 25-28, 

Charleston, SC. To be published by 

College of Forestry, Stephen F. Austin 

State University, Nacogdoches, TX. 
IMPACT OF HURRICANE HUGO ON CAVITY TREES OF 

A RED-COC ]ED WOODPECKER 

RE:COVERY AFTER llWO 

Donald Jo Lipscomb and Thomas Mo ~illiams' 

Abstract-The impact of hurricane Hugo on a relatively 

isolated population of red-cockaded woodpeckers (Picoides 

borealis) was evaluated by the loss of cavity trees to 

wind, saltwater, and bark beetles. The population is 

located 90 km northeast of Charleston, South Carolina, on a 

peninsula between Winyah Bay and the Atlantic Ocean. Damage to red-cockaded woodpecker cavity trees was significantly more severe than damage to the surrounding forest 

and 45 of 127 active cavity trees were destroyed. New 

cavities were begun in 47 trees and 38 cavities completed 

two and a half years after the storm. However, additional 

cavity tree mortality from salt intrusion and bark beetles 

resulted in an eighteen-month delay before a net gain in 

active cavity trees occurred. Dynamics of cavity activation, deactivation, and tree mortality show the complexity 

of cavity tree replacement in a red-cockaded woodpecker 

population after a catastrophic event. 

INTRODUCTION 

Hobcaw Barony is located on the South 

Carolina coast approximately 90 

kilometers northeast of Charleston and 

4 km east of Georgetown. Hobcaw 

forest is approximately 3077 hectares 

surrounded by 3800 hectares of nonforested marshes and islands between 

Winyah Bay and the Atlantic Ocean. 

The forest is 80 percent pine and 

pine-hardwood types. Age class 

distribution of the pine types was 

skewed heavily toward the over 100- 

year class before Hurricane Hugo 

(Figure 1). Less than four percent of 

the longleaf area was under 80 years 

old. Hobcaw forest was prescribe 

burned regularly since the mid 1970's. 

Thus there was an abundance of open 

old pine stands on the forest. Redcockaded woodpeckers (RCW) have been 

reported on Hobcaw for more than 20 

years. Dennis (1971) reported 138 

cavity trees (active and inactive 

combined) on Hobcaw in the early 

1970's. Grimes (1977) studied 77 

active cavity trees in the late 1970's. 

A geographic information system (GIs) 

red-cockaded woodpecker data base, 

initiated in 1988 and completed before 

August 1989, recorded 194 active and 

inactive cavity trees. The cutting on 

Hobcaw between 1955 and 1965 (Williams 

and Lipscomb 1983) combined with the 

burning program of the 1970's and 

1980's resulted in a density of 

approximately 1 cavity tree per 13 

hectares of pine type. 

On September 22, 1989, Hurricane Hugo 

crossed the South Carolina coast 20 

kilometers east of Charleston with 

maximum sustained winds of 222 km/hr 

(Purvis and others 1990). However, 

winds at Georgetown were lower at 87 

km/h and gusts to 138 km/h. Hobcaw 

forest was still significantly impacted 

by the wind with 27 percent of the 

trees receiving moderate to heavy 

damage resh sham and others 1991). In 

Belle W. Baruch Forest Science 

Institute Technical Contribution: 

93-01, 

The Baruch Forest Science Institute, 

Clemson University, Georgetown, SC 

29442 * 

addition, the storm surge inundated 

roughly 600 hectares on the east and 

south portions of the forest. The 

combination of salt water in the soil 

and bark beetles killed more trees than 

were killed by wind. Latter mortality 
vegetation included basal area of pines 

10 inches dbh and larger and basal area 

of mid-story pine and hardwoods. 

Figure 1--Age-class distribution of 

pine types on Hobcaw Forest, South 

Carolina, before Hurricane Hugo, 

occurred primarily during 1990 but has 

continued until 1993. These combined 

forces killed trees accounting for 40 

percent of the merchantable volume on 

the forest. 

We observed the effect of Hurricane 

Hugo on RCW cavity trees and the. 

dynamics of cavity tree replacement by 

the surviving RCW population on 

Hobcaw. Our objective was to observe 

the interaction of forest condition, 

storm impact, and nesting recovery 

with a goal of defining forest conditions that allow recovery of RCW 

cavity trees without resorting to 

artificial cavities. We chose this 

goal rather than artificial cavity 

construction because the area studied 

had a surviving woodpecker population 

and extensive nesting habitat remaining after the storm. 

Maps of RCW cavity trees were created 

by RCW research in the early 1970's. 

Annual inventories of Hobcaw Forest 

were conducted in 1976 and 1986. In 

each inventory all stands in the 

forest were surveyed. RCW cavities 

found during these surveys were also 

added to the maps. In 1988 and the 

early part of 1989 all known redcockaded woodpecker cavity trees were 

visited and evaluated. Information 

recorded included the height and 

activity of the cavity or cavities; 

the species of the cavity tree and its 

dbh, total height, and crown class. 

Information about the surrounding 

This data and mapped locations were put 

in the Hobcaw GIs (Williams and 

Lipscomb 1988) which was established in 

1986, The RCW data layer could then be 

overlain on existing stand, soil, and 

other information already in the data 

base (Lipscomb and Williams 1990). All 

known RCW cavity trees were entered 

into the data base before Hurricane 

Hugo. 

A 1.08 percent sample of the forest was 

taken during the winter of 1989-90 to 

evaluate damage to all species on the 

forest. Over 16,000 trees were 

measured and placed into one of eight 

wind-damage categories (Gresham and 

others 1991). All 194 cavity trees 

were visited, examined for cavity 

activity, and placed into one of the 

same damage categories immediately 

after Hugo in November 1989. 

We re-evaluated the surviving trees in 

April 1991 and again in April 1992. 

Areas likely to have new cavities 

(based on either distance from a known 

active or inactive colony or stand 

characteristics) were searched for new 

cavities from December through March 

prior to each evaluation. The same 

parameters were measured on new trees 

as on previously known cavity trees and 

the new trees were added to the permanent record. 

RESULTS 

RCW cavities occurred in three pine 

species on Hobcaw: loblolly pine 

(Pinus taeda L.), pond pine (Pinus 

serotina Michx.) and longleaf pine 

(Pinus palustris Mill.). For each 

species three data sets were prepared; 

one containing the cavity trees, one 

containing all trees in the damage 

survey, and one from the damage survey 

with tree diameter distributions 

matched to the cavity trees. The eight 

damage classes of Gresham and others 

(1991) were grouped into light (undamaged, bent, branches broken), medium 

(defoliated, top broken), and heavy 

(bole broken, uprooted, downed) and the 

three data sets compared. Heavy damage 

in cavity trees was four times the 

damage of all trees of the same 

species, and at least twice as high as 

in trees matched by diameter (Figure 

2). RCW excavate cavities in old, 

large pines (Conner and OrHalloran 

1987, Jackson and others 1979). Larger 

trees were subject to greater wind 
Loiigleaf Firie 

Survey 

Matching Trees 

toblolly Pii~e I 

a. 80 Pond Pine 

60 

40 

20 

0 

Light Moderate Heavy 

Damage Damage Damage 

Figure 2--Wind damage to pines on 

Hobcaw Forest following Hurricane 

Hugo. Survey was a 1.08 percent 

sample of the entire forest. Matching 

was a subset of the survey with the 

same diameter distribution as the 

cavity trees. Light damage: none, 

bent, or broken branches; Moderate 

damage: defoliated or top broken; 

Heavy damage: bole broken, or uprooted 

and leaning, or uprooted and down. 

stress and were more heavily damaged 

as shown by the matched data set in 

Figure 2. Note that there is little 

difference in longleaf pine since 96 

percent of the longleaf on the forest 

was over 80 years old. In addition, 

69 of the 80 cavity trees heavily 

damaged by the wind, broke at the 

cavity. For the general forest trees 

matched by diameter the greatest 

damage was by uprooting. Not only 

were the cavities in large trees which 

were likely to be uprooted but apparently the cavity weakened the tree to 

the point that it broke at the cavity. 

While 80 of the 194 cavity trees were 

severely damaged by wind, six were 

still alive in Novder 1989. Of the 

120 surviving cavity trees 83 were 

active. Since wind mortality in the 

forest in general was less than 20 

percent and more than 87 percent of 

the longleaf pine survived (Gresham 

and others 1991), there was an 

abundant supply of potential cavity 

trees available. 

Forty-five active cavity trees were 

lost during Hurricane Hugo, 20 new 

cavity trees (including starts) were 

found by April 1991, and 27 more during 

the following year for a total of 47 by 

April 1992. Of these 47 new cavity 

trees 38 had completed cavities 30 

months after the hurricane. However, 

the number of active cavity trees did 

not reach pre-hurricane level since 

1 mortality, saltwater intrusion, 

and bark beetles continued to take a 

toll (Figure 3). 

Apr . 

Aug. Aug. Nov. 1991 

1989 1989 1989 to 

to 

Nov. 

1989 

'E CAVIl 

to 

Apr. 

199 1 

"Y TREE 

Apr. 

1992 

.S 

Active (no chonqe) a Become 

Inactive (no change) 

0 New Cavities 

Died 

' INACTIVE CAVITY TREES 

Figure 3--Net changes in red-cockaded 

woodpecker cavity trees on Hobcaw 

Forest from August 1989 to April 1992. 

Active cavities includes 6 starts in 

April 1991 and 9 starts in April 1992. 

Between November 1989 and April 1991,20 

new cavity trees were found (14 completed cavities) and 16 active cavity 

trees died. Fifteen active cavity 

trees became inactive while 6 previously inactive cavity trees (some 

having been inactive for more than 

three years) were reactivated. These 

changes in activity affected more than 

one third of the total remaining active 

cavity trees. However, the number of 

active cavity trees declined by five. 

Between April 1991 and April 1992, 27 

new cavities (for a total of 47 new 

cavities with 38 completed) were found 
and seven active cavity trees died, 

Again six previotlsly inactive cavities 

became active, but only three previously active trees became inactive, 

Less than thirteen percent of active 

cavities was subject to change during 

1991-1992. One might surmise that the 

large number of trees becoming inactive in the first time period compared 

with the second, were a result of bird 

mortality during the storm, The combination of lower mortality and lower 

deactivation allowed a 29 percent net 

increase of active cavity trees during 

this time period, By April 1991 the 

woodpeckers had completed 38 new 

cavities and had nine starts, If this 

rate were to continue the number of 

active cavity trees would reach 

pre-hurricane levels in a few years, 

However, by 1991 the hurricane effects 

killed 40 percent of the pine foraging 

habitat as well as 97 active cavity 

trees. 

CONCLUSIONS 

There was significant damage to RCW 

cavity trees on Hobcaw forest located 

70 kilometers from the center of the 

path of Hurricane Hugo's eye, Damage 

to the RCW cavity trees was significantly greater than the damage to 

similar trees in the surrounding 

forest, Within two and a half years 

the birds had constructed more new 

active cavity trees (and had 38 of 47 

new cavities completed) than were 

initially lost to hurricane winds, 

However, additional losses of cavity 

trees occurred after Hugo from salt 

intrusion and bark beetles. Thus, 

thirty months after the hurricane 

there were still 21 percent fewer 

active cavity trees than before the 

hurricane. 

Hurricanes are a frequent episodic 

event throughout the red-cockaded 

range (Hooper and McAdie 1994). We 

found RCW cavity trees are especially 

vulnerable to wind damage. Over 40 

percent of the cavities were lost 70 

km from the eye with wind gusts under 

140 kmlh. Old, large pines are both 

preferred for cavities and subject to 

strong wind stress, Cavity trees are 

more likely to break at the cavity 

probably due to weakness caused by 

either the cavity itself or red heart 

fungus often associated with the 

cavity, 

The RCW population on Hobcaw forest 

was able to establish new active 

cavity trees in a relatively short 

time period because there were abundant 

old pines that survived. With sufficient nesting habitat the birds were 

able to complete a large number of 

cavities in a short period of time, 

Artificial cavity placement (Copeyon 

1990, Allen 1991) is an important 

strategy, but it was unnecessary for 

this population, The criteria we used 

to choose natural recovery was presence 

sf a surviving cavity tree in each 

colony and survival of 87 percent of 

the longleaf which was over 80 years 

old 

LITER~TURE CITED 

Allen, DOH. 1991, An Insert Technique 

for Constructing Artificial RedCockaded Woodpecker Cavities, USDA 

Forest Service General Technical Report 

SE-73. 19 pp. 

Conner, R,N.; OrHalloran, K.A, 1987, 

Cavity tree selection by red-cockaded 

woodpeckers as related to growth 

dynamics of southern pines, Wilson 

Bull. 99:392-412. 

Copeyon, C.K. 1990, A technique for 

constructing cavities for the redcockaded woodpecker. Wildlife Society 

Bulletin 18:303-311. 

Dennis, J.W, 1971. Map on file at The 

Belle W. Baruch Forest Science Institute, Georgetown, S,C, 

Gresham, C.A.; Williams, T.M.; 

Lipscomb, D.J. 1991. Hurricane Hugo 

Wind Damage to Southeastern U.S. 

Coastal Forest Tree Species, Biotropica 

23(4a):420-426, 

Grimes, T.L. 1977. Relationship of 

Red-Cockaded Woodpecker (Picoides 

borealis) Productivity to Colony Area 

Characteristics. Master's Thesis, Dep. 

For, Res, Clemson Univ. 

Hooper, R.G.; McAdie, C.J. 1994. 

Hurricanes and the long-term management 

of the red-cockaded woodpecker. This 

publication, 

Jackson, J.A.; Lennartz, M.R.; Hooper, 

R.G. 1979, Tree age and cavity initiation by red-cockaded woodpeckers, 

Journ, Forestry 77:102-103, 

Lipscomb, D.J.; Williams, T.M. 1988. 

Micro-Computer Map Based Data Retrieval 

System for Forest Managers. USDA Forest 

Service General Technical Report SO-74: 

p. 219-224. 
Lipscomb, D.J.; Williams, T.M. 1990. 

Developing a GIs for forest management 

in the 1990@s. p. 551-560 In Resource 

Technology 90: Second International 

Smpsim on Advanced Technology in 

Natural Resource mnagement. Am, Soc. 

Phot. and Renote Sensing. Bethesda, 

MI). ISBN 0-944426-45-X. 

Purvis, J.C.; Sidlow, S.F.; Smith, 

D.3,; Tyler, We; Turner, I, 1990, 

Hurricane Hugo. C1 te Report G-37, 

South Carolina Water Res. Corn., 

Williams, T.M.; Lipscomb, D.J. 1983. A 

Logging History of Bobcaw Barony, 

Clemson Dept, of Forestry Research 

Series, No. 38. 12 pp. 

Reprinted with permission. Proceedings 

of Red-cockaded Woodpecker Symposiunr 

111: Species Recovery, Ecology and 

Managenrent, January 25-28, Charleston, 

SC- To be published by College of 

Forestry, Stephen F, Austin State 

University, Nacogdoches, TX. 
TECHNOLOGY AND INNOVATION...KEY TO HUGO RECOVERY' 

D. W. t3erhardt2 

A)BSTfZACT--Westvaco forest managers utilized advanced 

logging methods, technology, and research to recover from 

forest damage done by Hurricane Hugo. Hugo affected more 

than 175,000 acres of Westvaco woodland and 21,000 acres of 

private woodland in the companyfs Cooperative Forest 

Management program. Westvaco used a computer-based Forest 

Resources Information System (FRIS), the National Aerial 

Photography Program (NAPP), and aerial reconnaissance to 

assess the damage and plan the salvage operation. A 

variety of logging methods, including horse logging, 

helicopter logging, and logging crews from Oregon and 

Sweden, allowed Westvaco and its CFM participantsf salvage 

success rate to be almost double the statewide rate. 

Intensive site preparation techniques helped reestablish 

pine plantations with little or no loss of production. 

Westvaco Forest Research established a long-term study to 

determine response of plantation loblolly to hurricane 

damage. 

What Ifd like to do is explain the 

damage done to Westvaco lands, the 

planning for recovery, recovery 

methods and technology employed, and 

our forest research results since 

Hugo. 

Unlike many others, I had the pleasure 

of not being here when Hugo actually 

hit. My wife and family will tell you 

that I fled inland, not to the safety 

of Charlotte, but clear to the west 

coast. In some ways this qualifies me 

as an expert--I was out of state when 

Hugo hit! 

When I returned, I was faced with the 

prospect of salvaging storm-damaged 

timber from Westvacofs forest land. 

Recovery from Hugo occupied our work 

lives, personal lives, and impacted 

our community for over one year, I'm 

only one of many Westvaco foresters 

who could share this learning experience with you. 

A paper presented at the 72nd Annual 

Meeting of the Appalachian Society of 

American Foresters held at Greenville, 

S.C., on January 20-22, 1993. 

David W. Gerhardt, Westvaco Corporation, P. 0. Box 1950, Summerville, SC 

29484. 

For those who may not be familiar with 

Westvaco, let me give you a brief 

description of our South Carolina 

operations. Westvaco is South 

Carolina's largest private landowner, 

with over 500,000 acres of forest land, 

most of it located in the Coastal Plain 

or Low country. Through our Cooperative Forest Management, or CFM program, 

we assist private landowners in managing another 420,000 acres of forest 

land in the state. Our management 

objective is to provide a stable supply 

of wood fiber to our paper mill in 

North Charleston. About 2,200 Westvaco 

employees in South Carolina are 

involved in a range of activities from 

forest management to paper, chemical, 

and lumber production. 

Much of Westvaco*~ forest land was in 

the direct path of the hurricane. More 

than 175,000 acres of company land were 

affected; roughly 50,000 acres were 

severely damaged. Another 21,000 acres 

of CFM properties were also severely 

damaged, 

A "team spirit" grew quickly at 

Westvaco among our Kraft, Chemical, 

Lumber, Real Estate, and Timberlands 

units, plus private landowners in our 

CFM program. In the days immediately 

following the storm, the state forestry 
c 'ssion, U.S. Forest Service, 

Westvaco, and o r landowners began 

to assess the d ge to our state's 

forests. 

Westvaco's initial efforts following 

Hurricane Hugo focused on identifying 

and assessing the extent of damage and 

prioritizing salvage efforts based on 

potential loss and loggability for 

company and CFM lands. Our Forest 

Resources Information System (FRIS) 

was invaluable in providing pre-storm 

stand statistics and provided much of 

the information needed to prioritize 

salvage efforts. The National Aerial 

Photography Program (NAPP), a comonly 

used tool in the forest industry, 

provided accurate aerial information 

for forest planning purposes. Coincidently, the last NAPP photos were 

flown in 1989 just prior to Hugo. 

Westvaco management wanted as quick an 

assessment of damages as possible. 

Aerial reconnaissance, using contract 

aircraft, provided information on 

overall woodlands damage and was 

essential for setting initial salvage 

priorities. We contracted a special 

aerial photography flight using NAPP 

specifications to obtain new pictures 

corresponding exactly to pre-hurricane 

images. Using color infrared photog- 

~aphy, Westvaco employees were able to 

ldentify the areas and extent of 

damage, differentiate forest types, 

and note areas of saturated soils. 

This information, combined with the 

information from our FRIS system, 

provided a complete overview of 

damage, including timber stand 

descriptions, soil types, and soil 

moisture necessary to plan the most 

effective and efficient salvage 

operation across the woodlands. 

Our recovery goals were to maximize 

salvage volume, protect the damaged 

woodlands from debris-fed wildfire, 

and to clear salvage areas for reforestation where feasible, We set out 

to develop a salvage plan for recovering lnillions of board feet of 

sawtimber and millions more tons of 

pulpwood. There were two major 

challenges. The first was time 

(estimated six months salvage for 

sawtimber, 18 months for pulpwood) and 

the second was ground conditions, 

which were extremely wet (10" of 

rainfall and broken/fallen trees). 

Conventional shears and skidders could 

not work in these conditions and we 

did not have the luxury to wait for 

dryer times to salvage our higher value 

products. 

In the first six months after the 

stom, every conceivable approach to 

logging was considered and, over the 

course of the salvage period, most were 

tried--big tires, crawlers, shovels, 

cable systems, and horses--all of which 

required new thinking. Based on these 

and our salvage goals, we made an early 

comitment to helicopter logging for 

salvaging our highest grade sawtimber. 

Finding no local contractors, we began 

to assemble our own. We contracted 

with Heli-Jet out of Eugene, OR, which 

provided the flying and choker setters, 

and matched the helicopter with one of 

the best local loggers. 

In our highly mechanized area of the 

world, a man with a chain saw became a 

valuable commodity, We had to look 

outside the local area for well-trained 

and experienced chain saw operators, 

We brought in a cutting contractor out 

of Eugene, OR; a typical western 

logging crew (with the tin hard hats, 

suspenders, and long saw bars). 

At the same time, we called a long-time 

Westvaco advisor and friend, Soren 

Erikkson, a world class chain saw 

expert and instructor. Within two 

weeks, we had professional Swedish 

chain saw cutters, all decked out in 

the latest safety gear, running high 

performance saws. Most importantly, 

they had the knowledge and training to 

safely cut the wood to stringent specifications at remarkably high production 

rates. 

It was a precise operation, with the 

helicopter removing one or more logs 

every 1 1/2 minutes. On the average, 

we ran about 40 turns/hour, 6-8 hours/ 

day, 15 loads/day, 6 days/week. We 

completed the project in four months. 

Our venture into helicopter logging was 

very successful. We even added a 

second helicopter to accelerate completion on our own land. By March 1, we 

had met all expectations, salvaging 

several million board feet of high 

quality sawtimber. 

Let me take a few minutes to put some 

of our salvage results in perspective, 

First, don't allow my enthusiasm for 

the helicopter salvage operation to 

cloud the fact that helicopters, 

horses, and other specialized systems 

were but a part of the overall salvage 

effort, albeit a strategic part. Once 
the wet ground conditions improved, 

the majority of the salvage on 

Westvaco land (and other private land) 

was accomplished by the hard work of 

the local conventional loggers, 

primarily the independent loggers who 

had been cutting and hauling to 

industry mills before the storm. 

One factor in the salvage success was 

water storage. Hore than 150,000 tons 

of recovered wood were stored under 

sprinklers during the summer of 1990. 

We stored this wood at two locations 

and metered it into our mill's wood 

flow over an 18-month period. 

Through almost a year of round-theclock teamwork, Westvaco salvaged more 

than 600,000 tons of hurricane-damaged 

timber from company lands. Another 

500,000 tons of downed timber was 

recovered from CFH lands. At 

Westvacofs Southern Woodlands, we set 

a salvage goal of 50 percent of the 

severely damaged timber volume. We 

reached 25 percent in the first six 

months, and late in 1990, we met the 

50 percent goal. Thus, the salvage 

success rate for Westvaco and its CFM 

participants was approximately double 

the statewide rate. 

Concurrent with our efforts to salvage 

damaged timber, we started looking at 

the short and long-term impacts on 

Westvacofs fiber supply. Our harvesting plans include a steady increase in 

pine pulpwood production to our 

Charleston mill. Hugo gave us a surge 

of pulpwood, as damaged trees were fed 

into the system. By mid-1994, however, the impact of Hugo on Westvacofs 

pine pulpwood production will disappear. This is largely due to improved 

practices and technology that have 

occurred over the last decade. 

Genetics, site preparation, fertilization, and competition control are just 

some of these practices. Combined, 

they effectively increase our plantation growth to replace the volume lost 

to Hugo. The advantages of genetics 

and fertilization were unaffected by 

Hugo. However, site prep prescriptions in Hugo areas involved several 

considerations. 

1. Was the broken timber salvaged? 

2. How much debris is on the 

ground? 

3. Quantity of standing snags 

(volume, size) and uprooted 

stumps. 

On any given site there could be a wide 

range of salvage (from 0 to 100 percent) and an equally wide range of site 

conditions. There are a few key factors about site preparation that helped 

us maintain production with little or 

no loss of long-term productivity. 

Traditionally, our intensive site prep 

in the Lowcountry has used a cornbination of shearing, raking, brush drumming, burning, bedding, and herbicides. 

Following Hugo, we combined these more 

effectively, plus took advantage of 

some recent technology improvements. 

Time and patience became our best 

tools. On many post-Hugo sites we 

sheared the sites and let the debris 

decompose from one to two and even 

three years. This minimized the amount 

of land occupied by piles and windrows, 

thus more of our land base is in production. In a two-year layout scenario, we can grow more volume in 23 

years with 10 percent windrows than in 

25 years with 20 percent windrows. 

There have been some equipment and 

herbicide innovations that assisted us 

in site preparation. One is the relief 

or "stump-jump" plow used to construct 

beds. The advantage of the relief plow 

is that each disk works independently of the others, This allows an individual blade to ride over a stump or 

debris while the other blades continue 

to form the bed. We have also used 

herbicides to our advantage in postHugo site prep. Some additional items 

we found useful in site preparation and 

planting were hoedads. We also used a 

machine called a slashbuster. 

You now have a good overview of how we 

prioritized our salvage operations 

using the most up-to-date technology, 

and how we tackled the additional 

twists Hugo threw us on site preparation. But what about the stands that 

were too young to salvage? One of the 

big questions confronting our operations people was what to do with young 

stands that were only marginally merchantable or really young plantations. 

Do we plow them under and start over? 

Do we let them go? If we do, will the 

trees survive, and if they survive, 

what will they look like at rotation? 

The published literature wasn't much 

help. The vast majority of hurricanerelated articles dealt with damage 

assessment rather than recovery. We 

could find only one research note 

dealing with plantation-pine recovery, 

and the results were limited, 
Looking for the silver lining, our 

Research Director pushed for the 

establishent of a long-term study to 

determine response of plantation 

loblolly to hurricane d 

decided to concentrate 

ged stands of ed-rotation age and 

younger. Older stands would be salvaged, either diately or in due 

the extent of the 

We installed the study in the early 

spring of 1990 at nine locations, 

using existing research plots to give 

us an accurate history and pre-storm 

measurements, Most of the locations 

are in the age 2- to 5-year range, We 

are following three older stands, 

primarily for survival information, 

In addition to the traditional forestry measurements, we are collecting 

several other objective and subjective 

measures, Because most of the damage 

in the young stands was stem lean, we 

want to quantify the degree of 

recovery. On all trees we are measuring the vertical and horizontal 

distances to eight feet of stem 

length, base of live crown, and the 

tip. 

We need to get a handle on where in 

the stem the recovery occurs, so on a 

10 percent subsample of the trees ages 

2 to 4, we are also measuring the 

vertical and horizontal distances to 

dbh, to one-half the original stem 

length, and to the original tip. 

These three points are permanently 

marked on the stem with paint, After 

one year we think we have a viable 

stem-angle measuring system. 

One of our subjective measures 

involves tree form. Some of these may 

not be applicable immediately but can 

be used later. Other subjective 

measures include root damage, percent 

foliage and branch loss, and stemdamage codes, In addition, we are 

also documenting recovery at each 

location by photographing subject 

trees at each remeasurement. 

Now I want to briefly go over some 

preliminary first-year results, Even 

with a rather severe drought the 

summer following Hugo, mortality was 

rather light, Only about six percent 

of the trees leaning at study installations died. The average angle of 

the dead trees was approximately 60 

degrees from vertical. There is a 

small negative correlation between 

initial age and the one-year change in 

stem lean, For example, this tree, age 

two in 1990 at study establisbent, had 

an average stem lean of 65 degrees, 

One year later, at age three, it grew 

0,lN in diameter, 1.2' in stem length, 

and improved 28 degrees. 

In 1990, the tree with the orange paint 

was five years old and had an average 

lean sf 26 degrees, After one year, 

the tree grew 0.6" in diameter, 3.2' in 

stern length, and had an average lean of 

5.6 degrees, The first-year results 

indicate that severely leaning trees 

got worse the following year. There is 

also a positive correlation between age 

and mortality, with younger trees exhibiting better recovery from storm 

damage. We will continue this study 

through the eleventh year following the 

storm. 

We hope this study, which will be 

published, will assist other forest 

managers in recovery planning from 

future disasters. Of course, we hope 

they never have occasion to use it1 

To say that Hugo presented us with some 

management opportunities would be to 

liken it to a s r squall. Th 

were Pbitiess inations of d 

severity, site conditions, accessibility factors, safety concerns, and 

subjective value judgements which 

challenged us beyond our normal duties. 

Hugo recovery was to a forester what 

war is to a soldier. 

We had numerous tools at our disposal, 

from heavy machinery to horse logging 

to herbicides, Technology and innovation provided the edge, NAPP aerial 

photos gave us a quick overview of 

damage severity, and FRIS provided 

instant information on volumes, site 

characteristics, and loggability. 

Combined, they enabled us to make 

effective, informed decisions. Our 

recent experience with site preparation 

studies and techniques also gave us 

some insight on how to approach our 

recovery goals, Without these tools, 

we would have lost much of our efficiency in salvage efforts and resource 

renewal and recovery. But, the most 

important factor was the individual 

efforts put forth by many dedicated 

people, 

I've mentioned very little about the 

impacts on families, homes, and communities. As resource managers, we 

were concerned about the resource, but 

our first overriding concerns were for 
the safety and well-being of our 

employees and neighbors where we live. 

In the first crucial weeks following 

the storm, Hestvaco resources and 

personnel were actively engaged in 

assisting others. For example, 

portable generators were loaned to 

local eomunities and refrigerated 

seedling vans were provided for food 

storage. 

One of the most crucial lessons 

learned from Hugo was the need for 

teamwork, compassion, and support 

among all groups. State, local, and 

federal government worked hand-in-hand 

with individuals, corporations, 

community, and church efforts. The 

result was a feeling of camaraderie, 

belonging, and cooperation, which 

allowed the completion of an enormous 

amount of work in a relatively short 

the period. 

Reprinted with permission from 

Hurricane Hugo: Recovering from 

Disaster, Proceedings 72nd Unuaf 

Meeting and Regional Technical 

Conference, Appalachian Society of 

American Foresters, Greenville, SC, 

Jan. 20-22, 1993. Dr. Vernon L. 

Robinson, Sec-Treas, 2557 Abbott 

Circle, Seneca, SC 29678. 
EASING THE TRANSITION: REDUCING THE COST OF 

REFORESTING LANDS 

Stephen K. Plodinel 

In September of 1989, many forest 

landowners in South Carolina learned 

first-hand how vulnerable forests are 

to storm damage, In a few short 

hours, Hurricane Hugo ripped a path of 

destruction across the state, It left 

in its wake more than four million 

acres of devastated forest land, No 

one's land was immune, and some of the 

best and most beautiful stands were 

hit hardest, 

If you are a landowner affected by 

Hurricane Hugo, you probably still 

remember the shock of seeing what 

happened to your trees, Even now, you 

may still be trying to decide if your 

forests can ever recover, Hell, the 

good news is "Yes, there is life for a 

forest after Hugo," The bad news is 

that it takes some careful planning to 

rebuild the forests in a way that is 

effective and efficient for you. But 

maybe this need for planning is not 

all bad news, because the effect of a 

good plan is a good outcome, 

There have been many questions for 

both landowners and foresters about 

how to best recover the damaged 

forests. Some of the techniques we 

have relied on just don't seem 

adequate to meet the needs, And, 

frankly, we have never really faced a 

situation with so many unknowns. 

This brochure can't address all the 

questions that have been raised by 

Hugo. It does try to answer the 

Extension Forester, Clemson University, Clemson, SC. Reprinted from a 

brochure (EC677) produced by the 

Clemson Cooperative Extension Service, 

Department of Forest Resources in 

cooperation with the South Carolina 

Forestry Commission. This work was 

supported by a grant under the Dire 

Emergency Supplemental Appropriations 

Act, providing federal funds through 

the Forestry Commission, 

question "How can I get the best forest 

regeneration in a way that I can 

afford?" There are several costsharing programs that can help reduce 

your out-of-pocket costs. Income tax 

incentives also are available to help 

recover some of those investment 

dollars within a few years, And there 

are several reforestation techniques 

that may accomplish the task without 

the high cost of some traditional 

high-intensity methods. 

START WITH A PLAN 

Under normal circumstances, it is helpful to have a plan before undertaking 

forest management activities, Under 

the conditions created by Hurricane 

Hugo, planning is essential! Without 

careful planning, at best you may end 

up paying more to reforest your land 

than might have been necessary. At 

worst, you might end up spending a lot 

of money and still have a forest that 

is not much better off than it was 

right after the hurricane. 

A professional forester can help you 

develop a plan that will meet your 

objectives on your land, Each forest 

and each landowner is different, so no 

one plan will work for everyone, 

While planning with a forester, you can 

consider: 

the condition of your land, 

possible methods of reforesting 

your land, 

your ability to afford the possible 

actions, and 

your short and long-term goals. 

If you talk about these factors with a 

professional forester, you can find a 

plan of action that is suited to you 

and your land. And remember, a management plan is required if you plan to 

apply for federal and state costsharing assistance. 

Foresters from the S.C. Forestry 

Commission, private consulting 
foresters, and landowner assistance 

foresters from some forest products 

firms are available to help you, For 

a list of names of foresters offering 

mnagement plan assistance in your 

area, contact one of the offices 

listed on the back of this brochure, 

IMG ASSISTANCE 

Sometimes a landowner cannot afford to 

pay the full cost of reforesting his 

land, For such cases, there are 

several programs in which the government will share the costs, You can 

receive 50 to 75 percent of the average costs of reforesting if you apply 

for assistance, You will need to 

carry out the work under an approved 

forest management plan, 

There are several requirements that 

are basic to most cost-share programs, 

A private, non-industrial landowner 

must own less than 1,000 acres of 

woodland to qualify for federal funds, 

State programs do not include a limit 

on total acreage owned, but a 100-acre 

limit is placed on the amount of land 

that can be cost-shared with a landowner each year, The land to be 

reforested must be able to produce at 

least 50 cubic feet of wood per acre 

per year, 

The Forestry Incentives Program (FIP) 

has helped to plant trees on more than 

235,000 acres in South Carolina since 

1975, FIP pays 50 percent of the 

costs of reforesting cut-over land, 

planting open land, and improving your 

woodlands. Reforestation practices 

include various combinations of 

mechanical, chemical, and prescribed 

burning site preparation and tree 

planting. Assistance with woodland 

improvement activities is also 

available, 

Designed to promote conservation of 

soil and water, the Agricultural 

Conservation Program (ACP) also can 

help reforest your land. ACP supports 

the same practices and cost schedules 

as FIP. Both FIP and ACP are administered by the Agricultural Stabilization and Conservation Service (ASCS) 

in cooperation with the S.C. Forestry 

Commission. 

The Forest Renewal Program (FRP) is 

sponsored by the state of South 

Carolina and is administered directly 

by the Forestry Commission, FRP 

supports reforestation practices 

similar to those funded by FIP except 

timber stand improvement, 

The newest cost-share program is the 

Stewardship Incentives Program (SIP), 

This program is designed to support 

reforestation and management practices 

that are a part of a landowner's 

stewardship forest managment plan. 

SIP includes the basic activities of 

reforestation and stand improvement, 

but also helps manage for wildlife, 

recreation, and soil and water conservation. 

A special cost-share program was 

created following Hurricane Hugo. The 

Hugo Incentives Program (HIP) can pay 

75 percent of reforestation costs. HIP 

is restricted to land that was forested 

before Hurricane Hugo and was damaged 

by the storm, Funds for HIP are provided annually by the federal government, so it is unknown how long this 

program will be available, 

Because of the wide-ranging damage 

caused by Hugo, all these programs are 

in great demand, Some delays are 

likely in receiving cost-share funds, 

but these programs can make a critical 

difference for many landowners, Remember that you need a forest management 

plan under these programs, And try to 

identify (with the help of a forester) 

the lowest-cost practices that can get 

the job done, This can help speed your 

approval under most programs. 

REFORESTATION TAX INCENTIVES 

To encourage reforestation, the federal 

government offers two significant 

income tax incentives, The first of 

these is a tax credit that you subtract 

from your income taxes paid during the 

year you reforest your land. You can 

subtract ten percent of your reforestation costs, up to a maximum credit of 

$1,000. Second, you can amortize 

(deduct) 95 percent of your reforestation costs over a seven-year period, 

rather than waiting to deduct them from 

timber harvest revenues, For example, 

if you spent $4,000 to reforest 25 

acres of land, you could receive a 

credit of $400 when you file your 

income taxes the next spring. In 

addition, you could claim deductions 

totaling $3,800 over seven yearsf tax 

returns. This would effectively reduce 

your reforestation costs from $160 per 

acre to $115. If you received 50 percent cost sharing, you would further 

reduce your effective cost to $57 per 

acre, 

Most landowners don't realize they are 

eligible for these helpful tax incentives, and as a result don't claim 
them. But there is no waiting line, 

and most private landowners can 

qualify. So be sure to claim this 

important benefit. (Incidentally, these tax incentives are available for 

all land, not just that d 

Hugo 1) 

WW-COST REFORESTATION 

mTHODS 

As a part of developing your reforestation plan with your forester, make 

sure that you have found the lowestcost method for reforesting your woodland. Many times we do things the way 

we always have, but if you do you may 

be missing out on the benefits of 

newly-developed reforestation techniques. Each site has its own special 

set of conditions that may make it 

well-suited to one method, while ruling out others all together. With the 

tangle of debris that Hugo left in 

most forests, you may need all the 

help you can get to reduce the total 

cost of preparing and regenerating the 

site. Briefly, here are several techniques that may work especially well 

on Hugo-damaged sites. 

NATTY mGENEIURT"lCN 

If there was a bright side to forestry 

after Hurricane Hugo, it was that the 

storm hit after seeds in pine cones 

had ripened. This provided many sites 

with a new potential crop of trees 

already in place. You will need to 

have a forester check your land to see 

if such natural restocking took place. 

If so, and if there are enough seedlings, the major part of your work may 

be complete. You do need to see if 

there needs to be any control of competing vegetation, any need for thinning seedlings that are too closely 

spaced, and any spot planting that may 

be needed in areas which did not 

receive a good seed fall. 

VEGETATION CONTROL WZTH 

HERBXCX DES 

If your site does appear to have a 

good crop of natural seedlings, you 

may be able to improve their growth by 

controlling competing vegetation while 

the seedlings are getting started. 

You also may need to do this if you 

planted seedlings without heavy 

mechanical clearing of the site. 

Chemical control is the only practical 

method of releasing pines. Chemical 

control combined with careful prescribed fires can also be a very 

effective yet very economical site 

preparation system. 

acceptable stocking levels, you my be 

able to manage the remaining trees 

until they are mature. In the meanthe, you may be able to develop 

natural regeneration of your next 

stand, This allows you to both delay 

and reduce the eventual costs of 

artificially reforesting the area. 

STRIP CLEARING 

Many stands of trees that could not be 

salvage harvested still contain so many 

downed trees and brush that it is 

difficult to even enter the area. 

Clearing the entire area with heavy 

machinery may be too expensive to be 

justifiable. A method called strip 

clearing pushes corridors through the 

tangle. Seedlings then are planted 

along the sides of these corridors. 

Although the trees may not be perfectly 

spaced across the entire area, an 

acceptable stand of trees can be 

established at much less expense. 

OTHER IDEAS--THE ART OF 

FORESTRY 

These are just a few of the possible 

ways that your forest stands could be 

reforested at reasonable costs. Since 

each site is different, not every 

method will work for you. But by 

working with a forester, you can draw 

upon his experience to find other 

possibilities. It may be that only 

hrute force will work, but you owe it 

to yourself to investigate all possibilities before opening your checkbook. 

IN CONCLUSION,.. 

Even though the prospects for the 

restoration of our forests seemed bleak 

after Hurricane Hugo, the ability of 

the forest to adapt and recover is one 

of its great strengths. In many cases 

the potential for starting a new forest 

stand lies just below the surface, 

waiting for a nudge to break through. 

As a forest landowner, you can be an 

important part of the recovery. And 

even if the task is large and your 

financial resources are limited, there 

are some things that you can do. Talk 

with a forester, develop a plan that 

will work for both you and your land, 

and start the healing process on your 

land. 
GIEMENT ALTERNATImS COSTS FOR 

GED TImER IN 

THE SOUTHERN UNITED STATES' 

C. D. Egbert, T. J. Straka, and A. P. ~arsinko' 

Abstract--Hurricane Hugo devastated over one-third of 

South Carolina's forest land. Much of the damage was 

so severe that site preparation is necessary for 

adequate forest regeneration. This paper describes the 

standard site preparation treatments and contrasts the 

costs in South Carolina for storm-damaged and nondamaged areas. Low-cost management alternatives are 

also described. 

INTRODUCTION 

On September 21, 1989, Hurricane Hugo 

devastated over one-third of South 

Carolina's forest land. Eleven 

counties suffered extensive or 

moderate forest damage and thirteen 

counties lesser, but significant, 

levels sf forest damage. More than 4 

million acres of trees, about 36 

percent of the state's forest area, 

suffered severe damage, (meaning that 

50 percent or more of the tree stems 

per acre are either broken or blown 

down). An estimated 1,331,785 acres 

of forest land require reforestation 

following Hurricane Hugo. In many 

cases the damage was so severe that 

management alternatives are quite 

limited. However, fortunately, wideranging management alternatives exist 

for most of the damaged area. 

SITE PREPARATION TREATMEN1CS 

Four site preparation treatments are 

in comon use. The first can be 

described as standard heavy mechanical 

site preparation, consisting of shearing, raking, piling, and bedding or 

dlsking. The remaining three alternatives consist of V-bladed strips with 

light, medium, or heavy herbicide 

A paper presented at the SAF 

National Convention poster session 

held at San Francisco, CA, on August 

4-7, 1991. 

Charles D. Egbert, Thomas J. Straka, 

and Allan P. Marsinko, Department of 

Forest Resources, Clemson University, 

Clemson, SC 29634-1003. 

application. As might be expected the 

treatments in the hurricane-damaged 

area are more costly than those in the 

non-damaged area (Table 1). Even with 

an extensive salvage effort that 

removed much of the timber, site 

preparation costs Mere roughly 20 to 

40 percent more costly in the stormdamaged area. 

Table 1--Preliminary cost trends for 

site preparation in the Hurricane Hugo 

damage area, compared to normal site 

preparation costs in South Carolina. 

Site Preparation Cost Per Acre 

Treatment Non-Hugo Area Hugo Area 

Straight three-pass 

practice (Shear, 

rake, pile, and bed or disk) $168 

V-bladed strips with 

light herbicides 8 6 

V-bladed strips with 

medium herbicides 116 

V-bladed strips with 

heavy herbicides 156 

In both the Hurricane Hugo area and the 

non-Hugo area the costs of tree planting are identical. This is expected 

because the site preparation operations 

create nearly identical planting sites. 

Total regeneration costs can be 

obtained by adding planting costs to 

site preparation costs (planting costs 

are $52 per acre for loblolly pine and 

$66 per acre for longleaf pine). 
Low-Cost Alternative 

Over half the acres damaged by Wurricane ~ugo are owned by nonindustrial 

private forest (NIPF) landowners, 

those landowners who often do not have 

the capital to finance regeneration 

efforts. Note that total regeneration 

costs ranged from $174 to $260 per 

acre in the storm-damaged area. Even 

with federal assistance many NIPF 

landowners will require Pow-cost 

mnagement alternatives. 

Straka and Baker (1991) identified two 

low-cost alternatives: (1) selection 

management, with 25-30 percent initial 

stocking and (2) natural even-aged 

-nag-ent resulting from chemical 

release of suppressed pine seedlings. 

These two alternatives were contrasted 

with a standard loblolly pine plantation management regime with a $250 per 

acre establishment cost. 

The selection management alternative 

assumes a stand that was initially 30 

percent stocked, on site index 90 

(base age 50) land, and a seven-year 

cutting cycle beginning at year 18. 

Competing hardwoods were controlled 

initially with herbicide at a cost of 

$45.00 per acre. A supplemental 

management cost of $13.00 per acre 

(for inventory and marking) was 

incurred every seven years prior to 

the harvest cut. Timber stand 

improvement was done every 10 years at 

a cost of $45.00 per acre. 

The natural even-aged management 

alternative incurred an initial cost 

of $45.00 per acre to chemically 

release a stand originating from 

natural reproduction (at least 100 

percent stocked) using herbicide. 

Timber stand improvement was done at 

age 5 at a cost of $45.00 per acre. 

Prescribed burning was done every 5 

years, beginning at age 15, at a cost 

of $5.00 per acre. A supplemental 

mnagement cost of $13.00 per acre (for 

inventory and mrking) was incurred 

every 5 years prior to harvest. 

The two low-~~st alternatives were 

compared to the loblolly pine plantation alternative. Ignoring land cost 

the selection management alternative 

earned an internal rate of return (IRR) 

of 9.9 percent, the chemical release 

8.6 percent, and the plantation 6.2 

percent. When land cost is considered, 

all the alternatives earn roughly the 

same IRR (between 4.0 to 4.5 percent). 

The landowner's management objective 

and treatment of land cost will determine the optimal alternative. Availability of federal assistance will also 

be a determining factor. 

LITERATURE: CITED 

Straka, ToJ.; Baker, J.B. 1991. A 

financial assessment of capitalextensive management alternatives for 

storm-damaged timber. Southern J. Appl. 

For. (In press). 

Reprinted with permission from the 

Proceedings of the 1991 Society of 

American Foresters National Convention, 

published by the Society of American 

Foresters, 5400 Grosvenor Lane, 

Bethesda, MD 20814-2198. Not for 

further reproduction. 
PROBLEMS WITH NIATU REGENEMTION 

ON HUGOJoe Hamilton, Jim Adkins, Jaime Teel, 

David Nagel and Patrick ~ee' 

After the initial shock over the 

extensive devastation of Hurricane 

Hugo in 1989, questions surfaced about 

how the damaged forest lands would he 

restored to a productive state. Many 

professional foresters speculated over 

the possibilities of natural regeneration due to an abundant loblolly pine 

cone crop present when Hugo hit. 

Stone Container, one of the forest 

products companies operating in the 

Hugo-damaged area, undertook a study 

on nonindustrial private landowner 

tracts in their Landowner Assistance 

Program (LOA) to determine if pine 

reproduction was sufficient to restore 

ged stands, This undertaking was 

done on behalf of the LOA clients to 

assist in determining natural regeneration results and was not intended 

to be a statistical research project. 

In the fall of the year following 

Hugo, the study was conducted in a 

ten-county area which was some of the 

hardest hit. The study area involved 

77 LOA clients and consisted of 5,477 

acres. All timber types were sampled 

to determine the success of natural 

pine and hardwood reproduction. 

Individual LOA tracts were randomly 

sampled in the study area. Due to the 

natural regeneration ability of hardwood stands more emphasis was placed 

on sampling of pine stands. Stands 

that were only slightly damaged were 

not sampled because a manageable 

residual stand existed. The sampling 

procedure first consisted of a cursory 

inspection to determine if there was 

evidence of natural regeneration. If 

a significant amount of regeneration 

was found, then a systematic sample 

was taken using mil-acre plots to 

obtain total coverage of the stand on 

Woodlands Foresters, Stone Container 

Corporation, 

a grid spacing. A minimum of 50 plots 

were taken per stand. Regardless of 

the total number of pine seedlings 

found within the plot, only a maximm 

of two seedlings four feet apart were 

counted. These two seedlings would 

express dominance over the remaining 

pine seedlings within the plot. Pine 

seedlings were also evaluated based on 

hardwood competition which could affect 

their growth. If a hardwood sapling 

overtopped the pine seedling, then the 

pine seedling was considered as not 

free-to-grow. 

All hardwood stands were evaluated 

based on a cursory observation to 

determine the number, quality and 

species of natural regeneration. 

RESULTS 

Based on the field study, the majority 

of the sampled acreage contained very 

little pine regeneration approximately 

one year after Hugo. 

Stocking categories were selected based 

on the number of trees per acre. The 

data listed in Table 1 is based on 

total pine regeneration per acre. 

Understocked stands (0-300 trees/acre) 

totaled 3,374 acres or approximately 75 

percent of the sampled area. Well 

stocked stands (300-1000 trees/acre) 

consisted of 1,068 acres or 24 percent 

of the sampled area. The balance of 

the sampled area consisted of 43 acres 

or 1 percent of overstocked regeneration (1000+ treeslacre). 

Stocking categories which contain freeto-grow (FTG) seedlings per acre can be 

found in Table 2. Well stocked stands, 

when considering only free-to-grow 

trees per acre, actually consist of 551 

acres or 12 percent of the sampled 

area. 

The cursory examination of the hardwood 

stands revealed.that these areas were 

regenerating back to hardwood. 
Table %--Acres of Total Natural Pine 

Regeneration by Stock Levels. 

0 to 300 to TOT#& 

COUNTY 300 1000 1000+ ACRES 

Berkeley 699 577 

Charleston 50 0 

Dorchester 282 115 

Orangeburg 71 73 

Clarendon 319 45 

Williamsburg 74 88 

Kershaw 490 66 

Lancaster 130 0 

Lee 5 15 38 

Sumt er -- 744 66 

3,374 1,068 

Table 2--Acres of Natural Pine Regeneration Categorized as Free-to-Grow by 

Stocking Levels. 

COUNTY 

TOTAL 

ACRES 

Berkeley 

Charleston 

Dorchester 

orangeburg 

C larendon 

Williamsburg 

Kershaw 

Lancaster 

Lee 

sumter 

Based on these results, the conclusion 

can be drawn that very little pine 

acreage (12 percent) was classified as 

adequately stocked with free-to-grow 

seedlings. This poor natural regeneration is believed to be attributable 

to the following factors: 

Evidence indicated that the 

majority of the pine cones did not 

release their pine seeds. 

Dense litter layers prevented 

available pine seed from contacting 

mineral soil. 

Dry conditions in the spring and 

summer of 1990 contributed to the poor 

survival of the pine seedlings on well 

drained to upland sites. 

It is also clear that adequate natural 

pine regeneration is not guaranteed in 

the aftermath of a major hurricane 

simply because an abundant loblolly 

pine cone crop exists. Successful 

regeneration is dependent on many 

factors such as proper seed dispersal, 

contact with mineral soil, adequate 

misture conditions and competition. 

NDATIONS TO MIX)W*NERS 

I[M f3UW MEA 

If you are a landowner whose timberlands were damaged by Hurricane Hugo, 

the following steps should be taken to 

ensure adequate restocking of your 

timberlands : 

Natural regeneration on damaged 

forest land should be checked to 

determine stocking level, species 

composition and growth potential. Acceptability of natural regeneration should be determined on a standby-stand basis, thereby avoiding fragmentation into unmanageable units. 

Consider pine-release utilizing 

forestry chemicals if adequate regeneration is present but stagnated by 

hardwood competition. Both chemical and mechanical site 

preparation methods should be considered as alternatives if inadequate 

stocking is found. 

Inquire about cost-share possibilities from state, federal and private 

sources for stand restoration if 

stocking is found to be inadequate. Based on individual goals and 

objectives, seek professional advice to 

restore timberlands to a productive 

state. 

Always remember that properly ' 

managed lands offer the landowner the 

most options under normal conditions as 

well as when catastrophy strikes. 

This study in the aftermath of Hugo 

will hopefully serve as useful reference material on natural pine regeneration when another hurricane strikes, ' The success of natural regeneration 

will vary with all of the many conditions present at the time of the 

hurricane. These pine regeneration 

results will not necessarily be the 

same with future hurricanes but do 

serve as realistic documentation with 

Hugo, 

Reprinted with permission from Forest 

Farmer, January 1992, p, 15,16,18. 

Published by Forest Farmers Association, Inc., P.O. Box 95385, Atlanta, 

GA 30347. 
CYPRESS 

(SOUTH CAROLINA) 

William 8. Conner and George ~sked 

There are over 1.2 million hectares 

(2.7 million acres) of forested 

wetland in South Carolina (Dahl, 

1990), including extensive swamps 

along the lower coastal plain. Unlike 

the coastal forests of Louisiana 

(Allen, 1992), South Carolina's 

forests are not subject to rapid water 

level rise (Stevenson and others, 

1986) or nutria predation (Platt and 

Brantley, 1990; Allen and Boykin, 

1991). Tropical cyclones, however, 

seriously affect the coastal forests 

of South Carolina. For instance, when 

Hurricane Hugo struck the South 

Carolina coast in September 1989, 

Hobcaw Forest was hit with a threemeter tidal surge, which flooded and 

killed the poorly drained bottomland 

forests and baldcypress (Taxodium 

distichum) with its saline waters 

(Hook and others, 1991). 

Our preliminary plantings of locallyobtained baldcypress seedlings at 

Hobcaw Forest show that problems due 

to high salinity remain three years 

after the storm (Conner, in press; 

Williams, in press). As a result, we 

now want to determine whether some 

populations of baldcypress may be more 

tolerant to saline water than others. 

Our experiment is being coordinated 

with James Allen at the USFWS National 

Wetlands Research Center, who is 

working on the same subject using 

seedlings he germinated from locallycollected baldcypress growing in highsalinity areas in Louisiana (see R&MN 

10(2):155). If we are successful in 

finding and reproducing a salttolerant strain of baldcypress then we 

can restore areas damaged by rising 

sea levels or storms. 

Assistant Professor and Director/ 

Professor, Baruch Forest Science 

Institute of Clemson University 

Box 596, Georgetown, SC 29442. 

During November 1992, we collected 

baldcypress seed from 5 trees from each 

of 9 tidal areas in South Carolina, 

Georgia, Alabama, and Louisiana. 

Salinity during collection averaged 2 

parts per thousand (ppt), although 

locals said levels were higher during 

other parts of the year. We moiststratified the seed for 90 days at 4-8 

degrees C (39-46 degrees F) and then 

planted 44 seeds from each of the 45 

parent trees. After the first growing 

season, we plan to measure the diameter 

and height of the nursery-grom seedlings prior to outplanting them for 

further testing at Hobcaw Forest and 

the Savannah River National Wildlife 

Refuge. 

We also planted seed from each source 

in 5 cm by 25 cm Deepots, which we will 

expose to one of the following treatments: 0, 2, 4, 6, 8, or 10 ppt saltwater. After one growing season, we 

will measure the weight of stems, 

leaves and roots to determine if there 

are differences in growth among 

sources. We have plans for a second 

test that will use a single seed source 

to produce seedlings that will be subjected to 5 ppt saltwater. We will 

harvest these seedlings every three 

days throughout the growing season in 

order to analyze the leaves, stems, and 

roots for chloride content. In the 

third part of the experiment, we will 

perform electrophoresis on all the seed 

sources to examine patterns of genetic 

diversity across the coastal portion of 

the species range using the phosphoglucose isomerase enzyme (PGI). 

References 

Allen, J.A. 1992. Cypress-tupelo swamp 

restoration in southern Louisiana. 

Restoration and Management Notes 

10(2):188-189. 
Allen, J,A,; Boykin, R. 1991. Tree 

shelters help protect seedlings from 

nutria (rnuisiana), Restoration and 

Managaent Notes 9(2):184. 

Conner, W.H. In press, Artificial 

regeneration of baldcypress in three 

South Carolina forested wetland areas 

after Hurricane Hugo, Proceedings of 

the Seventh Biennial Southern 

Silvicultural Research Conference. 

Dahl, TIE. 1990, Wetlands losses in 

the United States 1780- to 198Oes, 

U.S, Department of the Interior, Fish 

and Wildlife Service, Washington, D.C. 

21 PP* 

Hook, D.D.; Buford, M.A.; Williams, 

TOM. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest, Journal of Coastal Research 

SI8t291-300. 

Stevenson, J.C.; Ward, LOG,; Kearney, 

M.S, 1986. Vertical accretion in 

marshes with varying rates of sea level 

rise. In Estuarine Variability, ed, 

D.A, Wolfe, pp. 241-259. Orlando and 

London: Academic Press, 

Willia~ns, T.M. In press. Salt water 

movement within the water table aquifer 

following Hurricane Hugo. Proceedings 

of the Seventh Biennial Southern 

Silvicultural Research Conference. 

Reprinted with permission from 

Restoration and Management Notes 

11(2):156, Dr, William Jordon, Editor, 

University of Wisconsin-Madison 

Arboretum, 1207 Seminole Highway, 

Madison, WI 53711, published by the 

University of Wisconsin Press, 

Platt, S.G.; Brantley, COG. 1990, 

Baldcypress swamp forest restoration 

depends on control of nutria, vine 

mats, salinization (Louisiana). 

Restoration and Management Notes 

8(1) 848. 
Impact of Saltwater Flooding on Red Maple, Redbay, 

and Chinese Tallow Seedlings 

William H. Conner and George R. skew' 

Abstract--Potted seedlings of red maple (Acer rubrum L.), 

redbay (Persea borbonia (L.) Spreng.), and Chinese tallow 

(Sapium sebiferum (L,) Roxb*) were subjected to flooding 

with saltwater for 0 to 5 days. Red maple and redbay 

seedlings were very susceptible to saltwater flooding and 

were unable to tolerate more than 1 day of flooding. 

Chinese tallow seedlings, on the other hand, were able to 

tolerate saltwater well (60% survival after 5 days of 

flooding). Height growth of red maple and redbay seedlings was low (0.6 and 3.4 cm, respectively) during the 

eight-week study even for those seedlings not exposed to 

saltwater. Unflooded Chinese tallow seedlings, however, 

grew 20.7 cm during the eight-week observation period. 

Diameter growth of flooded seedlings along with biomass 

of shoot, leaf, and root components in all three species 

was significantly reduced by saltwater flooding. Biomass 

partitioning of surviving seedlings was not appreciably 

affected by saltwater flooding. Chinese tallow seems to 

be able to tolerate salinity fairly well and may become a 

dominant species of southern coastal forests. 

INTRODUCTION 

Forested wetlands in the lower coastal 

plain region of the southern United 

States are subjected to saltwater 

flooding by hurricane storm surges and 

extreme high tide events, Global 

warming and resulting rising sea level 

of 0-25 to 2.0 m by the year 2100 

(Smith and Tirpak 1989, Houghton and 

others 1990) indicate that these 

forests will be subjected to increased 

flooding and salinity in the future. 

While some research has been conducted 

on the response of major canopy 

species to salinity (see Pezeshki and 

others 1990 for a review), there are 

no published studies which describe 

the response of the understory species 

to saltwater intrusion. 

Red maple (Acer rubrum L.) and redbay 

(Persea borbonia [L.] Spreng.) are 

Assistant Professor and Director/ 

Professor, Baruch Forest Science 

Institute of Clemson University 

Box 596, Georgetown, SC 29442. 

both common species in lowland forests 

of the Atlantic coastal plain (Jones 

and Gresham 1985). Chinese tallow 

(Sapium sebiferum [L.] Roxb,) has 

successfully invaded some forested 

wetland areas of the southern United 

States (Jones and McLeod 1990). All of 

these species are shade tolerant 

(Walters and Yawney 1990, Brendemuehl 

1990, Jones and McLeod 1989). Redbay 

is commonly found growing on the 

borders of swampy areas, while red 

maple and Chinese tallow can grow in 

areas ranging from very dry to very 

wet. Both of the latter species can 

form pure to nearly pure stands in 

poorly drained areas (Helm and others 

1991, Walters and Yawney 1990). 

Because Chinese tallow can tolerate 

some salt (Huoran and Pengxin 1991) as 

well as flooding and shade (Jones and 

McLeod 1989, 1990), it may become more 

common in coastal forests in the 

future. 

The scarcity of information on the 

impact of saltwater flooding on understory components of coastal forests led 
to the development of this project. 

Although it is not a large-scale 

experiment, it can provide us with 

preliminary data as to what to expect 

when these species are flooded with 

saltwater and point us in the proper 

direction for future studies. The 

specific objective of this study was 

to determine survival, stem diameter 

and height growth, and biomass accumulation of seedling plants of the three 

species when subjected to saltwater 

flooding such as would occur during 

passage of a hurricane or an extreme 

high tide event. 

METHODS 

Red maple, redbay, and Chinese tallow 

seeds were collected from Hobcaw 

Barony near Georgetown, South 

Carolina, Chinese tallow and redbay 

seeds were collected from a variety of 

trees in the fall of 1990 and stratified according to Schopmeyer (1974). 

Red maple seeds were collected in the 

spring of 1991. All seeds were 

planted in seed beds at the Baruch 

Forest Science nursery in the spring 

of 1991, After the production of 

several fully expanded leaves, 

seedlings were transferred to Beepotsm 

(2.54 cm diameter and 25 cm deep) 

filled with a commercial potting mix 

and a slow release fertilizer 

(Osmocote 14-14-14). Potted seedlings 

were placed in an outdoor facility and 

allowed to grow for four months before 

treatment, Seedlings were irrigated 

daily and fertilized weekly with a 

water soluble fertilizer (Miracle Gro 

15-30-15). 

In July 1991, ten seedlings of each 

species were randomly assigned to 0, 

1, 2, 3, 4, or 5 days of saltwater 

flooding. After recording height and 

basal diameter, all of the seedlings 

were placed in a plastic pool (1.5 m 

diameter, 0.3 m deep) filled with 

water collected from a tidal creek (27 

ppt), One treatment was removed from 

the pool each day. Flooding was maintained at approximately 5 cm above the 

soil surface by adding salt water as 

needed. The pool was under shade 

cloth (50% reduction) to prevent the 

water from becoming too hot, Water 

temperature varied from 27-30°C and 

tracked air temperature by 1°C. 

Salinity in the pool declined from 27 

ppt to 20 ppt by day 5. 

Seedlings were flushed with fresh 

water after they were removed from the 

pool and then placed in the outdoor 

facility, watered daily with freshwater, and fertilized weekly (Miracle 

Gro 15-30-15). Flushing with fresh 

water simulated rainfall that occurred 

after passage of the hurricane. Seedlings were allowed to grow for 8 weeks 

after the flooding treatment, and their 

status was recorded weekly. After 

eight weeks, all seedlings were harvested and separated into root, stem, 

and foliage (if still alive) components, dried to a constant weight at 

65*C, and weighed, 

FiEStRTS 

Red maple and redbay seedlings were 

extremely susceptible to saltwater 

flooding (Figure 1). Within 2 weeks of 

flooding, 80% of the red maple seedlings were dead, Redbay seedlings 

seemed to be more tolerant than red 

maple seedlings at first, but after 3 

weeks they began to die rapidly. None 

of the red maple and redbay seedlings 

were capable of withstanding more than 

1 day of flooding. Chinese tallow 

seedlings were very tolerant of saltwater, with 60% surviving 5 days of 

flooding (Figure 1). Up to 2 days of 

flooding had very little impact upon 

rurvival, and mortality of seedlings 

flooded for more than 2 days did not 

occur until 3 weeks after flooding. 

figure 1--Percent survival for red 

maple, redbay, and Chinese tallow 

seedlings flooded for 0 to 5 days with 

saltwater, 

Height growth of red maple and redbay 

seedlings was low (0.6 and 3.4 cm, 

respectively) during the eight-week 

study even for those seedlings not 

exposed to saltwater, Final height of 

red maple (6.5 cm) and redbay (28.0 cm) 

seedlings surviving saltwater flooding 

was less than the average height at the 

beginning of the experiment because the 

stems tended to die and new growth 
merged from the base of the seedling. Biomass partitioning of surviving seedUnflooded Chinese tallow seedlings lings was not appreciably affected by 

grew 20.7 cm during the 8-week obser- saltwater flooding. 

vation period. Average height of 

flooded seedlings declined with 7 

increasing exposure to saltwater 6 I0 a3 

(Table 1) with a sharp decrease after I 14 

3 days of flooding. Interestingly, 5 a2 05 

average height of the 5-day flooded 

seedlings was greater than the 4-day 

!s 

flooded seedlings. 3 

2 

Average diameter growth of unflooded I 

seedlings was 1.2, 1.6, and 2.4 cm for 

redbay, red maple, and Chinese tallow E 

3 O 

seedlings, respectively. After 1 day "i Chinese trilaw Red trwpk Ruibay 

of flooding, the surviving redbay r 

seedling only increased 0.5 cm during E! PP 

the 8-week post flood period while red 

maple seedling diameter only increased I 

0.2 em. Diameter growth of Chinese 

tallow decreased with each additional 

day of flooding until there was no 2 

positive change in diameter at 3 days 

and beyond (Table 1). 3 

Just 1 day of saltwater flooding 

significantly reduced the biomass of 

shoot, leaf, and root components in 

all three species (Figure 2). Red 

maple and redbay biomass values tended 

to stabilize after 1 day sf flooding, 

but Chinese tallow biomass values 

continued to decline with up to 4 days 

of flooding. Both Chinese tallow and 

redbay root and stem biomass showed a 

slight increase in dry weight for 

seedlings flooded for 5 days. Root: 

shoot (stem + leaves) ratios of 

unflooded seedlings were fairly consistent (0.45-0.49) for all three 

species. Although the Chinese tallow 

root:shoot ratio declined to 0.34 with 

3 days of flooding, the ratio for 5- 

day flooded seedlings was nearly 

identical to unflooded seedlings. 

J 

Figure 2--Biomass partitioned into 

shoot (stem + leaf) and root dry 

weights (DW) for seedlings flooded for 

0 to 5 days with saltwater. 

DISCUSSION 

Although there have been no previous 

studies detailing the response of these 

understory species to salinity, there 

have been a limited number of studies 

describing the effects of freshwater 

flooding on red maple (Day 1987, Jones 

and others 1989) and Chinese tallow 

(Jones and Sharitz 1990) and the 

effects of light intensity on Chinese 

tallow growth (Jones and McLeod 1989, 

1990). Day (1987) and Jones and others 

(1989) both reported that red maple 

Table 1--Height and diameter data for Chinese tallow seedlings flooded with 

saltwater. Standard deviation is in parentheses. Numbers in the same column 

followed by identical letters are not statistically different (alpha = 0.05, 

Fisher PLSD). 

Days Initial ht. Initial dia. Final ht, Final dia. 

flooded (cm) (cm) (cm) (cm) 
seedlings survive flooded conditions 

but total dry weight, height, and 

diameter were reduced. Day (1987) 

hypothesized that lower root:shoot 

ratios are probably the result of root 

die-off and is similar to flooding 

results of other forested wetland 

species (Dickson and Broyer 1972, 

Keeley 1979, Sena Gomes and Kozlowski 

1980, Kane 1981). Chinese tallow has 

a high shade tolerance (Jones and 

McLeod 1989, 1990) and high flood 

tolerance (Jones and Sharitz 1990). 

In the present study, all three of the 

species exhibited greatly reduced 

growth and vigor as a result of 

increased flooding with saltwater. 

Chinese tallow seedlings were the most 

tolerant and were able to survive up 

to 5 days of flooding. Red maple and 

redbay seedlings were very susceptible 

to saltwater flooding, with significant mortality and growth reductions 

after 1 day of flooding. These 

results are consistent with field 

observations of areas on Hobcaw that 

were flooded by Hurricane Hugo's storm 

surge. More study is needed to determine successional patterns in coastal 

forested wetlands that are, or will be 

in the future, subject to saltwater 

intrusion. Chinese tallow seems to be 

able to tolerate shade (Jones and 

HcLeod 1989), flooding (Jones and 

others 1989), and salinity (this 

study) fairly well and may become a 

dominant species of southern coastal 

forests. Because of Chinese tallow's 

tolerance to a wide range of environmental conditions, it is successfully 

becoming established and thriving in 

coastal wetlands of the southeastern 

United States. It has the potential 

to outcompete native vegetation and 

may become a serious pest species in 

the future. 

ACKNOWLEDGMENTS 

This research was supported in part by 

a grant from the U.S. Forest Service 

with additional funding from the 

Depastment of Forest Resources, 

Clemson university. We wish to thank 

Wayne Inabinette and Jeffery Vernon 

for their technical assistance. Belle 

W. Baruch Forest Science Institute 

Technical Contribution: 93-11. 

LITERATURE CITED 

Brendemuehl, R.H. 1990. Persea borbonia 

(L.) Spreng. Redbay. p. 503-506. a: 

Burns, R.M. and B.H. Honkala (tech. 

coords,). Silvics of North America, 

Vol. 2, Hardwoods. Agriculture Handbook 

654, USDA Forest Service, Washington, 

DOC. 

Day, F.P., Jr. 1987. Effects of flooding and nutrient enrichment on biomass 

allocation in Acer rubrum seedlings. 

Amer. J. Bot. 74:1541-1554. 

Dickson, R.E.; Broyer, T.C. 1972. 

Effects of aeration, water supply, and 

nitrogen source on growth and development of tupelo gum and bald cypress. 

Ecology 53:626-634. 

Helm, A.C.; Nicholas, N.S.; Zedaker, 

S.M.; Young, S.T. 1991. Maritime 

forests on Bull Island, Cape Romain, 

South ~arolina. Bull. Torrey Bot. Club 

118:170-175. 

Houghton, J.; Jenkins, G.; Ephraums, J. 

(eds.). 1990. Climate change: the IPCC 

scientific assessment. Cambridge University Press, Cambridge, NY. 

Huoran, W.; Pengxin, L. 1991. spotlight 

on species: Sapium sebiferum - a cash 

tree crop. Farm Forestry News 4:10. 

Jones, R.H.; Gresham, C.A. 1985. Analysis of composition, environmental gradients, and structure in the coastal 

plain lowland forests of South 

Carolina. Castanea 50:207-227. 

Jones, R.H.; McLeod, K.W. 1989. Shade 

tolerance in seedlings of Chinese 

tallow tree, American sycamore, and 

cherrybark oak. Bull. Torrey Bot. Club. 

116:371-377. 

Jones, R.H.; McLeod, K.W. 1990. Growth 

and photosynthetic responses to a range 

of light environments in ~hinese tallow 

tree and Carolina ash seedlings. For. 

Sci. 36:851-862. 

Jones, R.H.; Sharitz, R.R. 1990. 

Effects of root competition and 

flooding on growth of Chinese tallow 

tree seedlings. Can. J. For. Res. 

20:573-578. 
Jones, ROB.; Sharitz, R.R.; McLeod, ROW. 1989. Effects of flooding and 

root competition on growth of shaded 

bottomland hardwood seedlings. Amex. 

Midl. Hat. 121:165-175. 

Rane, B.S. 1981. Swamp forest root : biomass distribution, 

nutrient content, and aspects of 

growth and mortality. M.S. thesis. 

East Carolina University, Greenville, 

N.C. 

Keeley, J.E. 1979. Population 

differentiation along a flood 

frequency gradient: physiological 

adaptations to flooding in Nyssa 

sylvatica. Ecol. Monogr. 49:89-108. 

Pezeshki, S.R.; Delaune, R.D.; 

Patrick, W.H., Jr. 1990. Flooding and 

saltwater intrusion: potential effects 

on survival and productivity of wetland forests along the U.S, Gulf 

Coast. For. Ec01. Manage. 33/34: 287- 

301. 

Schoprneyer, C.S. (tech. coord.). 1974. 

Seeds of woody plants in the United 

States. Agricultural Handbook No. 450. 

USDA Forest Service, Washington, D.C. 

Sena Gomes, A.R.; Kozlowski, TIT. 1980. 

Growth responses and adaptations of 

Fraxinus pennsylvanica seedlings to 

flooding. Pl. Physiol. 66:267-271, 

Smith, J.B.; Tirpak, D. 1989, The 

potential effects of global climate 

change on the United States. Report to 

Congress. EPA-230-05-89-850, U.S. 

Enviromental Protection Agency, Office 

of Policy, Planning, and Evaluation. 

Washington, D.C. 

Walters, R.S.; Yawney, HOW. 1990. Acer 

rubrm L. Red maple. p. 60-69. In: 

Burns, R.M. and B.H. Wonkala (tech. 

coords.). Silvics of North America, 

Vol. 2, Hardwoods. Agriculture Handbook 

654. USDA Forest Service, Washington, 

D.C. 

Reprinted with permission from Castanea 

58(3):214-219. Published by Southern 

Appalachian Botanical Society, Dr. 

Audrey Nellichamp, Managing Editor, 

Dept. of Biology, Univ, of NC at 

Charlotte, NC 28223. 
ARTIFICIAL REGENERATION OF BALDCYPRESS IN 

THREE SOUTH CAROLINA FORESTED WET 

AFTER HURRICANE HUGO' 

William H. ~onner' 

Abstract--Permanent plots were established in three 

forested wetlands on Hobcaw Barony, South Carolina, 

during the spring of 1990 to monitor recovery of the 

wetlands following Hurricane Hugo. Plots were located in 

(1) an area that retained saltwater for several days 

following the hurricane storm surge, (2) an area flushed 

with saltwater, and (3) an area that received no saltwater. Because of the lack of natural regeneration 

occurring in the three areas, baldcypress seedlings were 

planted to help restock the stands. Tubex treeshelters 

were placed on one-half of the seedlings to determine if 

they improved survival and height growth. After two 

growing seasons, survival was greatest in the area that 

xeceived no saltwater, The treeshelters seemed to 

increase survival of seedlings in the two stom surge 

areas. Height growth was greatest in the area that 

retained saltwater, and seedlings averaged over 10 inches 

taller than seedlings in the other two areas. Whereas 

the treeshelters seemed to have a beneficial effect on 

height growth during the first growing season, growth 

differences were not as pronounced during year two. 

Available light and salinity levels may be the two most 

important factors controlling survival and growth in the 

stands. More detailed research needs to be conducted to 

develop sound silvicultural plans. 

INTRODUCTION 

Hurricanes are an episodic, but normal, part of the clhatic regime of 

the southeastern United States. Current evidence indicates that between 

160,000 and 320,000 hurricanes have 

occurred in the Florida Keys during the past 2 million years (Ball and 

others 1967). What coastal ecosystems 

would be like without hurricanes is 

unknown, but they would probably be 

different, both morphologically and 

ecologically (Conner and others 1989). 

Hurricane disturbance can result from 

Paper presented at Seventh Biennial 

Southern Silvicultural Conference, 

Mobile, AL, NOv. 17-19, 1992. 

Assistant Professor, Baruch Forest 

Science Institute of Clemson University Box 596, Georgetown, SC 29442. 

both wind and flooding effects. High 

winds can defoliate, break, or topple 

trees, with the severity of damage 

related to storm intensity, forest 

structure, species, and soil conditions (Weaver 1989, Gresham and others 

1991). Little attention has been given 

to storm surge effects since heavy 

rains accompanying the hurricane 

usually saturate soils to protect them 

from saltwater intrusion (Gardner and 

others 1991, Hook and others 1991). 

Hurricane Hugo struck the South 

Carolina coast in September 1989 

causing timber damage on nearly 4.5 

million acres (Hook and-others 1991). 

Hobcaw Forest, 4 miles east of 

Georgetown and 56 miles northeast of 

where the eye of the hurricane came 

ashore, was hit with winds estimated to 

be 54 mi/hr gusting to 86 mi/hr (Purvis 
and others 1990), Although heavy 

damage was sustained in pine forests 

and poorly drained bottomland forests, 

baldcypress ( Taxodium distichurn (L, ) 

Rich.) forests suffered little wind 

damage (Gresham and others 1991, Hook 

and others 1991). The greatest damage 

to forested wetlands on Hobcaw was 

caused by saltwater flooding from the 

10-foot stom surge. 

OB-CTIVES 

The objectives of this research were 

to initially document the effects of 

Hurricane Hugo on Hobcaw forested 

wetlands and natural recovery of the 

forest. However, the lack of natural 

regeneration during the first growing 

season after Hugo necessitated the 

establishment of long-term study plots 

to monitor regeneration patterns and 

to examine the feasibility of planting 

seedlings in the affected stands. 

This paper describes the damage done 

to three forested wetland stands, the 

lack of natural regeneration, and the 

initial success of underplanting 

baldcypress seedlings. 

NETHODS 

Study plots were established during 

March 1991, 18 months after Hurricane 

Hugo, in three forested wetland stands 

on Hobcaw Forest. The first stand 

(hereafter referred to as Marsh Road) 

was a baldcypresslswamp blackgum 

(Nyssa sylvatica var. biflora (Walt. ) 

Sarg.) forest that lies between two 

old beach ridges on the eastern edge 

of Hobcaw Forest. Saltwater from the 

storm surge was retained in the forest 

for several days. The second area 

(Boardwalk) was flushed by saltwater, 

and the third area (Crabhaul) received 

no saltwater but did receive minor 

wind damage. 

Within each stand, five 0.12 acre 

plots were installed during the spring 

of 1990 to inventory trees larger than 

4.0 inches diameter at breast height 

(dbh). Each tree was tagged, dbh 

measured, and condition or cause of 

death recorded. Natural regeneration 

was monitored in ten 3.3 ft X 3,3 ft 

subplots within each of the larger 

plots. Regeneration was inventoried 

in June and September 1990 and in 

January and May 1991. Seed banks were 

sampled by randomly collecting twenty 

12 in X 12 in X 2 in sections of 

forest floor from each stand in July 

1990. The soil samples were mixed, 

placed in trays, put in a greenhouse, 

kept moist, and inventoried weekly for 

three months. After three months, tree 

seeds were collected by sieving and 

tested for viability using Tetrazolium 

(Shuel 1948). 

When it became evident that little 

natural regeneration was occurring in 

the stands, 80 one-year-old baldcypress 

seedlings (obtained from the South 

Carolina Forestry Comission) were 

planted adjacent to each tree measurement plot in March 1991. The planting 

design consisted of 20 equally spaced 

planting spokes radiating from a center 

point. Four seedlings were planted on 

each spoke at a 6.6 ft spacing. Twofoot tall Tubex treeshelters were used 

on seedlings in every other row to 

determine if they increased survival 

and growth of newly planted seedlings 

in wetland conditions. 

RESULTS AND DISCUSSION 

Tree Damage 

Very few tops were broken out of trees 

in the wetland stands (Table l), 

although 84% of baldcypress trees and 

88% of swamp blackgum trees did suffer 

some limb breakage (Gresham and others 

1991). Major damage was caused by the 

10-foot storm surge that struck the 

eastern edge of the forest. Runoff was 

impeded in the Marsh Road stand by old 

logging roads at each end of the lowlying area that the forest is in. 

Saltwater was retained for several days 

until water levels stabilized at prestorm heights. Salinity levels of 2 

ppt were still being measured two years 

after the hurricane. Over one-half of 

the canopy trees were killed during the 

first few weeks following flooding. 

Saltwater also flooded the Boardwalk 

area, killing the mainly waxmyrtle 

(Myrica cerifera L.) understory. Only 

28% of the canopy trees died immediately after the saltwater surge. Additional mortality occurred, however, 

during the summer following the storm 

surge. It is unknown why this delay in 

mortality occurred in the Boardwalk 

area. Canopy trees are still dying in 

the two saltwater areas, indicating 

that there are still residual effects 

of the salt. 

Natural Regeneration 

There was very little natural 

regeneration of woody species during 

the two growing seasons following 

Hurricane Hugo. The greatest number of 

baldcypress and water tupelo seedlings 

came up in the Crabhaul stand, but they 

failed to grow tall enough to survive 

subsequent flooding. In the Marsh Road 
Table 1--Variation in Hurricane Hugo 

ge to three forested wetland 

stands in South Carolina, All values 

are given as percentages, 

TOP Dead 

Area Breakage 1990 1991 

Crabhaul 2.7 0 0 

Boardwalk 3.8 28.0 40.8 

Marsh Road 1.8 57.1 65.5 

and Boardwalk stands, some redbay 

(Persea borbonia (1,) Spreng,), waxmyrtle, fetterbush (Lyonia lucida 

(Lam.) Koch), and red maple (Acer 

rubrum Lo) became established on old 

stumps, cypress knees and buttresses, 

and other raised areas that kept them 

out of the water, Overall, only 3 

water tupelo seedlings survived in the 

Crabhaul stand, along with 5 baldcypress in the Boardwalk stand and 2 

baldcypress in the Marsh Road stand. 

The soil seed banks were surprisingly 

devoid of seeds from the canopy 

species. A total sf 7 baldcypress and 

13 swamp blackgum seeds germinated 

from the soil sections taken from 

Crabhaul, This was much better than 

the Boardwalk stand (no germination) 

or the Marsh Road stand (3 baldcypress). Although a number of seeds 

were sieved from the soil samples at 

the end of three months, none tested 

viable with Tetrazolium, This pool of 

dead seeds is similar to that observed 

by Schneider and Sharitz (1986) for 

another forested wetland site in South 

Carolina, They suggested that too 

much flooding may result in nonviable 

seeds, Saltwater may have also had an 

impact in this study. Additional work 

needs to be done exmining the seed 

longevity and viability in relation to 

flooding and salinity. 

Planted Seedlings 

Survival of baldcypress seedlings 

during the first growing season was 

greatest in the Crabhaul stand and 

least in the Boardwalk stand (Table 

2). Tubex treeshelters seemed to 

greatly increase survival in the 

Boardwalk area, while there were no 

differences in survival of Tubex and 

non-Tubex seedlings in the Crabhaul 

stand, Survival was greater with 

treeshelters in the Marsh Road stand, 

but not significantly, Survival 

percentages after two growing seasons 

Table 2--Survival of planted baldcypress seedlings in three South 

Carolina wetland stands, 

First-year Second-year 

survival survival 

Area Tubx non-Tubex Tubex non-Tubex 

Crabhaul 100 100 100 9 9 

Boardwalk 7 9 48 7 2 38 

Marsh Road 94 82 9 2 8 0 

were similar to first year survival in 

the Crabhaul and Marsh Road stands, but 

the Boardwalk stand continued to lose 

seedlings. Saltwater in the Marsh Road 

and Boardwalk areas may still be 

affecting survival. Examination of Cllevels in seedling leaves revealed 71 

ppm in the Boardwalk area and 57 ppm in 

the Marsh Road area compared to 17 ppm 

in the Marsh Road area, Whereas 

chloride is an essential micronutrient, 

excess chloride can be detrimental 

(Ghosh and Drew 1991). Pezeshki and 

others (1988) found that salinity 

causes accumulation of several ions in 

baldcypress leaf tissue significantly 

decreasing photosynthesis levels. 

Height growth was best in the Marsh 

Road area during both growing seasons 

(Table 3). Average height of seedlings 

in the Marsh Road stand were 3 inches 

greater than seedlings in the other two 

areas after one growing season and 10 

inches greater after two growing 

seasons, The Tubex treeshelters seemed 

to have a beneficial effect on height 

growth during the first growing season 

but not as clear an effect during the 

second year. Non-Tubex seedlings grew 

slightly more than Tubex seedlings in 

Crabhaul during the second growing 

season and slightly less than Tubex 

seedlings in Marsh Road. The Boardwalk 

was the only area that exhibited 

significantly greater height growth of 

Tubex seedlings during the second 

growing season. Most of the seedlings 

grew out of the 2-foot treeshelters 

during the first year, Therefore, the 

treeshelters did not offer much of an 

advantage over non-Tubex seedlings 

during the second year. Taller 

treeshelters should be tested to see if 

they remain beneficial for longer than 

one growing season, 

One factor that probably influenced 

growth rates at the Crabhaul and 

Boardwalk stands was the amount of 

sunlight reaching the forest floor. 

Only 4% of available light reached the 
Table 3--Average height growth 

(inches) of planted baldcypress 

seedlings in three South Carolina 

wetland stands. 

Firs t-year Second-year 

growth 

Area Tubex non-Tubex 

Crabhaul 3.5 3.0 4.6 5.0 

Boardwalk 3.4 1.3 5.0 0.9 

HarshRoad 7.0 4.2 11.6 10.7 

Crabhaul forest floor during the 

summer months. Even though 38% of 

available light reached the floor at 

Boardwalk, this may not have been 

sufficient for maximum growth. Baldcypress tends to be intermediately 

tolerant to shade and grows best in 

full sunlight conditions (Wenger 1984, 

Wilhite and Toliver 1990). The Marsh 

Road stand has the most open canopy 

and 58% of available light reached the 

forest floor. Conner and Flynn (1989) 

found similar results in a Louisiana 

wetland forest where baldcypress 

seedlings planted in more open areas 

grew better than those planted in 

shaded areas (9 inches versus 3 

inches ) . 

CONCLUSIONS 

Natural regeneration in hurricane 

impacted forested wetland stands is 

very erratic. To ensure adequate 

stocking of the stand after disturbance, planting may be necessary. 

However, there is much to learn before 

we can recommend large-scale reforestation of baldcypress stands. More 

detailed, long-term studies need to be 

conducted to ensure that sound silvicultural practices be formulated. 

ACKN0WLEDGME:mS 

Funding was provided by the U.S. 

Forest Service and by the McIntireStennis Cooperative Forestry Research 

Program. Comments by Chuck Gresham 

helped improve the manuscript. Belle 

W. Baruch Forest Science Institute 

Technical Contribution: 93-3. 

LITERATlfRE CITED 

Ball, M.M.; Shinn, E.A.; Stockman, 

R.W. 1967. The geologic effects of 

Hurricane Donna in south Florida. J. 

Geol. 75:583-597. 

Conner, W.H.; Flynn, R. 1989. Growth 

and survival of baldcypress (Taxodium 

distich- (L.) Rich.) planted across a 

flooding gradient in a Louisiana 

bottomland forest. Wetlands 9~207-217. 

Conner, W.H.; Day, Jr., J.W.; Baumann, 

R.N.; Randall, J.M. 1989. Influence of 

hurricanes on coastal ecosystems along 

the northern Gulf of Mexico. Wetlands 

Ecol. Manage. 1:45-56. 

Gardner, L.R.; Michener, W.K.; Blood, 

E.R.; Williams, T.M.; Lipscomb, D.J.; 

Jefferson, W.H. 1991. Ecological impact 

of Hurricane Hugo--salinization of a 

coastal forest. J. Coastal. Res. 

SI-8:301-318. 

Ghosh, G.; Drew, M.C. 1991. Comparison 

of analytical methods for extraction 

of chloride from plant tissue using 

36~1 as tracer. Plant and Soil 136:265- 

268. 

Gresham, C.A.; Williams, T.M.; 

Lipscomb, D.J. 1991. Hurricane wind 

damage to southeastern U.S. coastal 

forest tree species, Biotropica 

23(4a):420-426. 

Hook, D.D.; Buford, M.A.; Williams, 

T.M. 1991. Impact of Hurricane Hugo on 

the South Carolina coastal plain 

forest. J. Coastal Res. SI-8:291-300. 

Purvis, J.C.; Sidlow, S.F.; Smith, 

D.J.; Tyler, W.; Turner, I. 1990. 

Hurricane Hugo. Climate Report G-37, 

South Carolina Water Resources 

Commission, Columbia, SC. 

Pezeshki, S.R.; DeLaune, R.D.; Patrick, 

Jr., W.H. 1988. Effect of salinity on 

leaf ionic content and photosynthesis 

of Taxodium distichurn L. Amer. Midl. 

Mat. 119:185-192. 

Schneider, R.L.; Sharitz, R.R. 1986. 

seed bank dynamics in a southeastern 

riverine swamp, kner. J. Bot. 73:1022- 

1030. 

Shuel, R.W. 1948. Seed geminability 

tests with 2,3,5-triphenyltetrazolium 

chloride. Sci. Agric. 28:34-38. 

Weaver, P.L. 1989. Forest changes after 

hurricanes in Puerto Rico's Luquillo 

mountains. Interciencia 14:181-192. 
Wenger, K.P. fed:): 1984. Forestry Reprinted with ps 

Handbook, 2nd edition. John Wilsy d Proceedings of the Seventh Biennial 

Sons, Hew York. 1335 pp. southern Silviculturnl Re~searcb 

Conference, Mobile, AL, Nov. 17-19, 

Wilhite, L.P.; Toliver, J.R. 1990. 1992, Publishd by the USDA For. Serv. 

Taxdim diatichm (La) Rich. Bald- SFES Gen, Tech. Rep. SO-93, July 1993, 

cypress. pp. 563-572. In% Burns, R.M. p. 185-188. 

and aonkala (tech. coord,), Silvics of 

North America, Volme 1, Conifers. 

USDA Forest Service, Agriculture 

Handbook 654. 
THIRD-YEAR RESULTS FROM A TEST OF 

LONGLEAF PINE (Pinus palustris Mill.) SEED SOURCES ON 

THE F CIS ION NATIONAL]~ FOREST 

Earl R. Sluderl 

Abstract--Containerized longleaf pine seedlings from 

eight geographic sources from eastern North Carolina to 

southern Mississippi were planted at three locations on 

the Francis Marion National Forest in South Carolina 

and one location in central Georgia. Seedlings were 

started in the greenhouse in January and field-planted 

in May 1991. At age 3 years from seed, survival was 

high and most seedlings had begun height growth. 

Variation among seed sources was nonsignificant for 

survival, significant for height (P<0.05) in two 

locations, and significant for within-plot coefficient 

of variation in height (P<0.05) in the Georgia planting. Neither height nor survival varied significantly 

among seed sources when averaged over the four planting~. Differences among plantation averages were 

significant (P<0.01 or 0.001) for all three traits. 

Height growth was best in the Georgia plantation. 

INTRODUCTION 

Hurricane Hugo in 1989 destroyed much 

of the timber on Francis Marion 

National Forest (FMNF) near 

Charleston, South Carolina. Forest 

managers plan to plant longleaf pine 

on as many suitable sites as possible 

in the storm-damaged area. Unfortunately, the longleaf pine seed orchard 

also was destroyed. Until the seed 

orchard is re-established and producing, it will be necessary to use seeds 

from other sources, but some of those 

sources may not be genetically 

well-adapted to conditions on the 

FMNF. Conversely, some sources may do 

better than the local source. In 

1991, a study was installed on the 

FMNF to evaluate relative performance 

of eight prospective seed sources. 

Data from the study will provide a 

basis for deciding whether to use 

natural methods such as shelterwood 

for reproducing stands established 

from nonlocal sources, and whether 

some sources perform well enough on 

'~esearch Geneticist, Southeastern 

Forest Experiment Station, Forest 

Service, U.S. Department of 

Agriculture, Asheville, NC. 

the FMNF to be used even after local 

seeds are available. 

LITERATURE: REVIEW 

Early European settlers found most of 

the land in what is now the Southeastern United States to be covered by 

park-like stands of old-growth longleaf 

pine. The range of the species 

extended from southeastern Virginia to 

eastern Texas and from south-central 

Florida to north-central Alabama and 

Georgia (Figure 1). Over this range, 

it originally occupied approximately 60 

million acres. Longleaf stands have 

been reduced to approximately 4 million 

acres by land clearing for agriculture 

or harvesting without provision for 

reproduction (Coker 1987). 

Longleaf pine has always been much 

prized for its fire, insect, and 

disease resistance, its deep root 

system, and its rapid growth through 

middle age, The very demanding planting requirements for longleaf pine, 

however, have led to planting failures 

that discouraged management of the 

species. Stands with adequate numbers 

of seed-producing trees can be regenerated with shelterwood techniques that 

include prescribed burning, and 
MILFigure 1--Natural range of longleaf pine. 

direct-seeding has had some success 

(Derr and Mann 1971, Croker 1987). 

In part because satisfactory techniques have been developed for planting it, interest in planting and growing longleaf pine has increased a 

great deal (Croker 1987). These 

techniques include production of large 

seedlings, careful handling and storage (including refrigeration), correct 

planting depth, and control of competition and brownspot needle blight 

(caused by Hycosphaerella dearnsii 

Barr) (Brissette and others 1990, 

Croker 1987, Hatchell and Muse 1990, 

Simon 1990, Snow and others 1990, 

Wakeley 1954). 

Successful artificial regeneration 

techniques bring the ability to use 

nonlocal seed and the need to know the 

geographic limits within which seed 

can safely be moved. The Southwide 

Pine Seed Source Study has provided 

information on the broad pattern of 

genetic variation in longleaf pine 

associated with seed source. Significant variation in survival, growth, 

and resistance to brownspot needle 

blight occurred among the widely 

spaced sources in the study (Henry and 

Wells 1967, Schmidtling and White 

1990, Wells and Wakeley 1970). Variation patterns permit wide movement of 

seeds within certain specified climatic 

limits with low risk of failure. Other 

studies have indicated that local variation is greater than that amociated 

with broad geographic patterns (Kraus 

and Sluder 1990, Snyder and Derr 1972). 

Successful artificial regeneration 

techniques also permit breeding prorams for improving the genetic quality 

of planting stock. Longleaf pine areas 

on the Region 8 National Forests have 

been divided into breeding populations, 

selections have been made, and progeny 

tests and clonal seed orchards established (Schmidtling and White 1990, 

Wells and McConnell 1984). 

METHODS 

Longleaf pine seeds from eight georaphic sources were included in my 

study. The sources were distributed in 

six states within or near a zone with 

240-270 freeze-free days. This zone 

includes the Francis Marion National 

Forest (Table 1; Figure 2). The North 

Carolina source (Bladen County) is a 

few days north of the 240-day isobar. 

Seeds from the various sources were 

obtained in 1990 from cooperators as 

indicated in Table 1. Seeds collected 
Table 1--Description of seed sources used in the study. 

Lot Source Description Cooperator 

S, Alab 

N, Florida 

S. Georgia 

S. Mississippi 

S. Mississippi 

E, North Car, 

South Carolina 

South Carolina 

Seed orchard, 1988" 

Forest, 1987 

Seedling S. O., 1990 

Seed orchard, 1987 

Forest, 1987 

Seed orchard, 1988 

Seed orchard, 1987 

Forest (sandhills), 1990 

Region 8, Ashe Nursery 

Region 8, Ashe Nursery 

Georgia Forestry Corn. 

Region 8, Ashe Nursery 

Region 8, Ashe Nursery 

Federal Paper Company 

Region 8, Ashe Nursery 

South Car. Forestry Corn, 

a Year of seed collection. Lot 1 differed from lot 2 only in year of seed 

collection; it was dropped to facilitate field layout. 

Days between Iast 32' (F. i temperature in spring and hnt 32' temperature in autumn Splmg freezes are assumed to occur between January I 

and June 30; autumn freezes between July 1 and December 31. Table 

and map excerpted fhm pages 31 and 32, "Clinauric Atlas of the United 

States," Enuirmmenrni Same Sdu Adminismiion, U, S. Depmrment of Commetcc 

Figure 2--Mean length of freeze-free period, SE U.S., with approximate location 

of seed sources. 
before 1990 had been stored at 

subfreezing temperatures. 

Seeds were planted in the greenhouse 

in January 1991, in 10-cubic-inch 

plastic tubes filled with a medium of 

peat, perlite, and vermiculite to 

which a slow-release fertilizer had 

been added. When crowding of the 

seedlings became evident, tubes were 

rearranged within the racks to occupy 

alternate spaces. In April, seedlings 

were moved from the greenhouse to a 

shadehouse, then a week later to full 

sun. A Benlate drench was used 

periodically to prevent fungal 

infection. 

Three complete installations of the 

study were planted May 14-16, 1991, 

and designated as plantations 154-156, 

on the Francis Marion National Forest. 

Each installation included a 16-tree 

square plot of each source in each of 

four randomized-block replications, 

Spacing was 10 X 10 feet in plantation 

154 and 8 X 8 feet in the other two. 

Another installation was planted in 

Peach County in central Georgia in 

cooperation with Fort Valley State 

College (plantation 157). This plantation has six replications, 16-tree 

plots, and 10 X 10-foot spacing; 

planting dates were May 24 (reps 1-4) 

and June 14 (reps 5-6). Two border 

rows of the local source were planted 

around each plantation. Planting 

sites were cleared forest on the 

Francis Marion and old field in 

Georgia. Each site was disc-harrowed 

before planting. 

competition control since planting has 

included burning at the end of the 

second season in plantation 154; 

herbicides in plantation 155; and 

herbicides, mowing, and hand-hoeing in 

plantation 157. Herbicides caused 

some mortality in plantation 157 and 

excess water caused some in plantation 

155 during the first growing season, 

The dead trees were replanted with 

tubelings from the same sources which 

earlier had been transferred to larger 

containers and kept for that purpose. 

The study was assessed at the end of 

the 1993 growing season, when the 

seedlings were in their third year 

from seed. Survival was recorded and 

heights measured to the nearest em. 

Data analyzed were survival,,plot mean 

height and within-plot coefficient of 

variation (CV) in height. Percentage 

data (survival and CV) were transformed to the arcsines of their square 

roots for analysis. 

REXiULTS 

Survival was high and did not vary significantly ng f3eed WSlrces within 

any of the plantations (Tables 3 and 

4). Plantation mean survival ranged 

from 83 percent in plantation 154 to 96 

percent in plantation 157. This difference in survival across plantations 

was significant (P<0.01), whether or 

not the Georgia plantation (157) was 

included in the combined analysis 

(Table 5). No plantation-by-seedsource interaction in survival was 

evident. 

Mean heights at age 3 years varied 

significantly among sources (P<0.05) 

only in plantations 156 and 157 (Table 

4). In 156, the Alabama source (lot 2) 

was tallest and the Florida source (lot 

3) was shortest. In 157, the South 

Carolina sandhills source (lot 9) was 

tallest and the Mississippi forest 

source (lot 6) was shortest (Table 3). 

Combined analyses, however, showed that 

heights averaged over plantations did 

not differ significantly among sources 

(Table 5). Neither was there any significant interaction of seed source 

with plantation location. Plantation 

mean heights varied from 10.3 to 14.2 

csn for the three in South Carolina 

(nonsignificant), but the mean for the 

Georgia plantation of 62.5 cm in height 

was significantly greater than the 

others (P<0.001) (Table 5). 

Within-plot CV in height generally was 

quite high, as might be expected when 

longleaf pine seedlings are emerging 

from the grass stage. Variation among 

seed sources in this trait, however, 

was significant only in plantation 157 

(P<0.05) (Table 4). In combined 

analyses, variation was significant 

only among plantations (P<0.001) (Table 

5). Within-plot height CV was greatest in plantations 155 and 156 at 84 and 74 

percent, respectively (Table 3). 

DISCUSSION 

The influence of vegetative competition 

and microsite variability on height 

growth initiation and growth rate is 

quite evident in these early results. 

The high water table on the Francis 

Marion likely is the factor most 

responsible for the large difference 

between mean height there and on the 

Georgia site, where drainage is good 

but not excessive, The strong effect 

of drainage could be seen in the South 

Carolina plantations, where discing 

left some planting spots noticeably 

lower than others. After rains, 

seedlings planted in low spots stayed 
Table 2--Analysis of variance design, 

Source O, f. Expectation mean square 

Individual plantations 

Rep (R) r-1 Vrs + sV, 

Ssurce (S) S-l vrs + rv8 

RXS (r-I)(s-1) Vrs 

Plantations combined 

Plantation (P) p-1 Vr(p)s + rVsp + sV,,,, + rsVp 

Rep (R) in P (r-UP vt(P)8 + SVE(Pt 

Source (s) s-1 Vr(p)s + rVsp f PrV, 

PXS (P-l)(s-1) Vr(p)s + rVsp 

RinPXS P -1 Vr(p,a 
Table 3--Means data at age 3 years from seed. 

Seed 

lot 

Plantation 

154 155 156 157' Mean 

Survival, percent 

93.75 95.31 

93 . 75 85,94 

92.19 92.19 

89.06 96.87 

92.19 100 . 00 

87.50 93 . 75 

85.94 93 75 

89.06 90.62 

2 fiso 

3 F"w 

4 GASO 

5 MSSO 

6 MSF 

7 NCSO 

8 SCSO 

9 SCF 

Mean 

Heiqht, cm 

2 ALSO 13.72 12.75 

3 FLF 

4 GAS0 

5 MSSO 

6 MSF 

7 NCSO 

8 SCSO 

9 SCF 

Mean 

Within-plot CV, percent 

84.93 91.00 

71.11 55.69 

94.46 92.13 

82.91 60.29 

97.31 83.13 

73.18 78.25 

93.47 66.15 

76.36 66.84 

2 ALSO 

3 FLF 

4 GASO 

5 MSSO 

6 MSF 

7 NCSO 

8 SCSO 

9 SCF 

Mean 

' Plantation 157 means include only reps 1-4. 
Table 4--Mean squares from analyses of variance of third-year data, by trait 

and plantation ." 

Trait 

Variance Plantation 

source D.f . 154 155 156 157(4) 157(6) 

Survival ---------- Arcsine square root percent---------- 

Rep 3 159.55 170.85 112.90 39.46 31,37 

Seed source 7 19.05 41.79 144.81 119.00 61.78 

Error 21 88.43 102.21 104.55 78.68 85.31 

EIeight ------------------ centbeters------------------ 

Rep 3 33.84*** 189.63*** 4.92 107.06 317.86** 

Seed source 7 10.13 31.55 16.60* 141.53 262.50* 

Error 21 4.18 21.53 6.64 80.87 85.45 

Within-plot eoef. var. _-____-____ Arcsine square root percent---------- 

Rep 3 30.68 300.69 2.26 13.99 68-93 

Seed source 7 15.69 303.66 377.10 44.36 72.90* 

Error 21 52.31 600.80 435.97 33.78 31.55 

Two analyses are shown for plantation 157, for 4 and 6 reps. * P<0.05; ** P<0.01; *** P<0.001 

Table 5--Mean squares from combined analyses, age 3 years, 3 or 4 plantations. 

Variance 

source 

Trait 

D.f. Survival Height Coef . var. 

Arc sq rt pet cm Arc sq rt pct 

Plantation (P) 

Plantations 154, 155, and 156 

2 1203.15** 143.49 

Rep in P 9 147.77 

Seed source (S) 7 77.51 

PXS 14 64.07 

Rep in P X S 63 98.40 

Plantation (P) 

Plantations 154, 155, 156, and 157" 

3 1398.82** 20,660.42*** 

Rep in P 12 120.69 

Seed source (S) 7 84.03 

PXS 21 80.21 

Rep in P X S 84 93.47 

" Only reps 1-4 from plantation 147 were used in these analyses. 

** P<0.01; *** P<0.001 
under water longer, had higher mortality, and grew less than those in 

better drained spots. 

Competition from weeds and grasses 

would have been severe on the Georgia 

old-field site had not intensive 

vegetation control measures been used. 

Because of the vegetation control and 

good site, a majority of the seedlings 

there initiated height growth during 

the second season, and several of them 

were more than 1.5 m tall by the end 

of the third season. 

The brownspot needle blight disease 

has been no problem in this study. A 

few seedlings were noticeably infected 

during the second year in the Georgia 

plantation, but little or no infection 

was evident at the end of the third 

season. 

The study plantings are well established now and should provide the seed 

source information needed for management of longleaf pine on the Francis 

Marion National Forest. The next 

assessments will be at ages 5 and 10 

years. BY age 10, any effects of the 

grass stage and early competition in 

masking seed source differences should 

have become relatively small. Variation patterns evident by then should 

be reliable bases for management 

decisions. 

ACKNOWLEDGMENTS 

The author thanks the cooperators 

listed in Table 1 for seeds. In 

addition, he thanks personnel from the 

Santee Experimental Forest for site 

preparation work; personnel from the 

Witherbee and Wambaw Ranger Districts 

for planting sites and maintenance; 

Fort Valley State College for a planting site, site preparation, and site 

maintenance; and the Environmental 

Testing Center at Macon for greenhouse 

space, 

LITERATURE CITED 

Brissette, John C.; Elliott, Mark; 

Barnett, James P. 1990. Producing 

container longleaf pine seedlings. In: 

Farrar, Robert Me, Jr., ed. Proceedings of the symposium on the management of longleaf pine; 1989 April 4-6; 

Long Beach MS. Tech. Rep. SO-75. New 

Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern 

Forest Experiment Station: 52-78. 

Croker, Thomas Caldwell, Jr. 1987. 

Longleaf pine. A history of man and a 

forest. Forestry Rep. R8-FR7. Atlanta, 

GA: U.S. Department of Agriculture, 

Forest Service. 37 pp. 

Derr, Harold J.; Hann, Willim F., Jr. 

1971, Direct-seeding pines in the 

south. Agric. Handb. 391. Washington, 

DC: U.S. Department of Agriculture, 

Forest Service. 68 pp. 

Hatchell, Glyndon E.; Muse, H. David. 

1990. Nursery cultural practices and 

morphological attributes of longleaf 

pine bare-root stock as indicators of 

early field performance. Res. Pap. 

SE-277. Asheville, NC: U.S. Department 

of Agriculture, Forest Service, Southeastern Forest Esperhent Station. 

34 PP* 

Henry, B. W.; Wells, Osborn 0. 1967. 

Variation in brown-spot infection of 

longleaf pine from several geographic 

sources. Res. Note SO-52. New Orleans, 

LA: U.S. Department of Agriculture, 

Forest Service, Southern Forest 

Experiment Station. 4 pp. 

Kraus, John F.; Sluder, Earl R. 1990. 

Genecology of longleaf pine in Georgia 

and Florida. Res. Pap. SE-278. 

Asheville, NC: U.S. Department of 

Agriculture, Forest Service, Southeastern Forest Experiment Station. 

31 PP* 

Schmidtling, R. C.; White, To L. 1990. 

Genetics and improvement of longleaf 

pine. In: Farrar, Robert M., Jr., ed. 

Proceedings of the symposium on the 

management of longleaf pine; 1989 April 

4-6; Long Beach, MS. Gen. Tech. Rep. 

SO-75. New Orleans, LA: U.S. Department 

of Agriculture, Forest Service, 

Southern Forest Experiment Station: 

114-127. 

Simon, Gene A. 1990. A prescription 

for successful management of longleaf 

pine. In: Farrar, Robert M., Jr., ed. 

Proceedings of the symposium on the 

management of longleaf pine; 1989 April 

4-6; Long Beach, MS. Gen, Tech. Rep. 

SO-75. New Orleans, LA: U.S. Department 

of Agriculture, Forest Service, 

Southern Forest Experiment Station: 

247-257 . 
Snow, Go A*; Hoffard, W. H.; Cordell, 

C. E. [and others]. 1990, Pest management in longleaf pine stands. In: 

Farrar, Robert Me, Jr., ed. Proceedings of the symposium on the management of longleaf pine; 1989 April 4-6; 

Long Beach, &IS1 Gen. Tech. Rep, SO-75, 

New Orleans, LA: U.S. Department of 

Agriculture, Forest Service, Southern 

Forest Experiment Station: 128-134, 

Snyder, E. Bayne; Derr, Harold J, 

1972. Breeding longleaf pines for 

resistance to brown spot needle 

blight, Phytopathology 62(3):325-329, 

Wakeley, Philip C, 1954. Planting the 

southern pines. Agric. Monogr, 18. 

Washington, DC: U.S. Department of 

Agriculture, Forest Service. 233 pp. 

Wells, Osborn 0.; Wakeley, Philip C. 

1970, Variation in longleaf pine from 

several geographic sources. Forest 

Science 16(1):28-42. 

Hells, 6. 8.; McConneP1, J. L. 1984. 

Breeding populations in the R-8 tree 

improvment programs. In: Hiller, Dick, 

ed, Progeny testing. Proceedings of a 

servicewide genetics workshop; 1983 

Dec. 5-9; Charleston, SC. Washington, 

DC: U.S. Department of Agriculture, 

Forest Service: 61-67, 
NOTEt RESPONSE OF BALDCYPRESS LOBLOLLY PINE 

SEEDLINGS TO SHORT-TE SamATER FLOODING 

William H. Conner and George R. skew' 

Abstract--Six-month-ofd and eighteen-month-old baldcypress and loblolly pine seedlings were subjected to a 

simulated saltwater surge (salinity = 30 parts per 

thousand) for O to 5 days followed by flushing and daily 

watering with fresh water. Growth, biomass, and survival 

were monitored for 9 weeks following inundation, Sixmonth-old seedlings of both species were extremely susceptible to saltwater flooding, and survival percentages 

declined rapidly beyond 1 day of saltwater flooding. 

Eighteen-month-old seedlings were better able to survive 

saltwater flooding, with some pine seedlings surviving up 

to 3 days of flooding and some baldcypress up to 4 days 

of flooding, The general response of surviving baldcypress seedlings to saltwater flooding was to die back 

and then resprout. For loblolly pine, growth was slowed 

until a threshold level was reached, at which point the 

seedlings died. There was a direct correlation between 

duration of saltwater flooding and diameter growth with 

six-month-old seedlings but not with the eighteen-monthold seedlings. There was a steady decline in diameter 

with increasing days of saltwater flooding in surviving 

eighteen-month-old baldcypress, whereas eighteen-monthold loblolly seedlings showed some diameter growth even 

after 3 days of saltwater flooding. Root:shoot biomass 

partitioning in surviving seedlings was not appreciably 

affected .by treatments. 

INTRODUCTION 

The lower coastal plain region of the 

southern United States tends to be 

flat and poorly drained, Permanent 

swamps have developed in the most 

poorly drained sites, with baldcypress 

( Taxodium distichum (L. ) Rich, ) as a 

dominant tree species, Flatwood areas 

contain loblolly pine ( Pinus taeda 

L,), which is a broadly adapted pine 

species capable of growing equally 

well under flooded or drained conditions (Hook and Scholtens 1978), Both 

baldcypregss and loblolly pine can be 

found growing side-by-side along the 

edges of the swamps, The general 

response of these two species to 

waterlogging has been fairly well 

Assistant Professor and Director/ 

Professor, Baruch Forest Science 

Institute of Clemson University 

Box 596, Georgetown, SC 29442. 

documented (Mattoon 1916, Hunt 1951, 

Dickson and Broyer 1972, Hook and 

others 1983, DeBell and others 1984, 

Topa and McLeod 1986, Donovan and 

others 1988), Among tree species, 

baldcypress is highly tolerant to 

waterlogging while loblolly pine is 

moderately tolerant (Hook 1984). 

In contrast to the amount of work that 

has been conducted on waterlogging 

response, salt tolerance has received 

little attention, Most of the available literature comes from studies on 

the effects of salt spray on trees 

(Wall 1933, Wells and Shunk 1938, 

Wallace and Moss 1939, Moss 1940, 

Little and others 1958). With the 

increased interest in global warming 

and sea-level rise in recent years, 

more emphasis has been placed on 

determining the response of coastal 

plant species to increased flooding and 

salinity, Some research has been 
conducted on the physiological 

response of baldcypress to salinity 

(Pezeshki and others 1986, 1988), but 

only one study was found describing 

the chloride content of pine needles 

in response to short-term saltwater 

flooding (Land 1974)- 

In addition to the long-term slow rise 

of sea level, coastal forests are also 

subjected to saltwater periodically as 

a result of hurricanes or other severe 

storms. Hurricane Hazel's storm surge 

in 1954 killed thousands of hectares 

of forests in North Carolina and 

Virginia (Little and others 1958). A 

3 m storm surge resulting from Hurricane Hugo in 1989 caused major damage 

to the Hobcaw Forest in South Carolina 

(Nook and others 1991), In both 

cases, mortality was greatest in areas 

where water drainage was impeded, 

Because of the scarcity of information 

on the salt response of these two 

dominant coastal plain tree species, 

we designed a project to determine the 

impact of short-term saltwater flooding on their survival, stem diameter 

and height growth, and biomass accumulation. To simulate a hurricane 

surge, seedlings were flooded with 

seawater and then flushed with freshwater after varying days of inundation 

with the seawater. This regime was 

chosen as being typical of what happened to many well-drained sites on 

the Hobcaw Forest as a result of 

Hurricane Hugo and subsequent rains. 

METHODS * 

Seeds of baldcypress and loblolly pine 

from local sources were stratified 

according to Schopmeyer (1974) and 

sown in seed beds in the Baruch Forest 

Science Nursery, Georgetown, SC. 

After the production of several fully 

expanded leaves or needles, seedlings 

(designated CYPRESS 1 and PINE 1) were 

transferred to Deepotsw (6 cm diameter 

by 25 cm deep) filled with a comercia1 potting mix composed of peat 

moss, perlite, vermiculite, composted 

bark (Sunshine All Purpose Plus potting mix, Fisons Western Corporation, 

Canada), and a slow release fertilizer 

(Osmocote 14-14-14), One-year-old 

seedlings of both species (designated 

CYPRESS 2 and PINE 2) were obtained 

from the South Carolina Forestry 

Commission and planted in the same 

manner. Potted seedlings were placed 

in an outdoor facility where they were 

allowed to grow for 4 months. The 

seedlings were irrigated daily and 

fertilized with a water-soluble 

fertilizer (Miracle Gro, 15-30-15) once 

a week. 

In ~uly, ten seedlings of each group 

were randomly selected and assigned to 

0, 1, 2, 3, 4, or 5 days of saltwater 

flooding. Because of mortality, only 4 

seedlings per treatment were available 

for PINE 2, All seedlings were placed 

in a plastic pool (1.5 m diameter, 0.3 

m deep) filled with seawater [salinity = 30 parts per thousand (ppt)] collected from North Inlet on July 5, 

1991, and one treatment was removed 

each day. Flooding was maintained 

throughout the study at approximately 5 

cm above the soil surface of the pots 

by the addition of tap water as needed, 

Salinity was monitored daily using a 

meter. Salinity in the pool dropped 

from 30 ppt to 23 ppt by day 5. The 

pool was placed under a shade cloth 

(50% reduction in sunlight) to prevent 

the water from becoming too hot, Water 

temperature remained fairly constant 

throughout the five day flooding 

period, varying from 26-27.S°C, and 

tracked air temperature within lo. 

These temperatures are consistent with 

those occurring during the summer in 

shallow, nonflowing swamps on Hobcaw 

Barony. After removal from the pool, 

the seedlings were flushed with fresh 

water and placed in the outdoor facility where they were watered daily with 

freshwater and fertilized weekly with 

water-soluble fertilizer (Miracle Gro, 

15-30-15). All seedlings were allowed 

to grow for 9 weeks after flooding 

ceased, and their status was recorded 

weekly. 

Basal diameter and height of each seedling were recorded at the initiation of 

flooding and at the end of the experiment. As seedlings died (did not 

resprout within three weeks after loss 

of foliage), they were harvested and 

separated into root and stem parts, 

dried to a constant weight at 65OC, and 

weighed. After 9 weeks, all surviving 

seedlings were harvested and processed 

in a like manner, except that foliage 

was also included as a component. 

REISU1;TS 

Survival 

Both PINE 1 and CYPRESS 1 seedlings 

were extremely susceptible to saltwater 

flooding. One week after flooding at 

all levels, survival of CYPRESS 1 

seedlings was loo%, but survival 

percentages declined rapidly beginning 

in week 2 for seedlings flooded more 

than 1 day, Thirty percent of the 

CYPRESS 1 seedlings subjected to one 
day of flooding were able to survive 

to the end of the study, and none 

survived flooding for z 2 days. PINE 

1 seedlings were more tolerant than 

CYPRESS 1 seedlings of 1-2 days of 

saltwater flooding, Ninety percent of 

the 1-day-flooded and 10% of the 2- 

day-flooded PINE 1 seedlings survived 

to the end of the study. Beyond 2 

days, however, there were no PINE 1 

survivors , 

Eighteen-month-old seedlings of both 

species were more tolerant of saltwater flooding than the six-month-old 

seedlings, Ninety percent of CYPRESS 

2 seedlings survived up to 2 days of 

flooding, and 30% survived up to 4 

days of flooding. Eighteen-month-old 

loblolly pine were able to survive 3 

days of flooding (SO%), but none 

survived 4 or 5 days of flooding. 

Height and Diameter Growth 

Height growth of CYPRESS 1 and 2 and 

PINE 1 was negative because of dieback of the main stem and resprouting 

of the seedlings. CYPRESS 2 seedlings 

had increasing die-back with increasing days of saltwater floodingl PINE 

2 seedlings that survived saltwater 

flooding had positive height growth 

with 1 day of flooding and no growth 

after 2 or 3 days of flooding. The 

overall response of the baldcypress 

seedlings to saltwater flooding was to 

die back and resprout, whereas the 

loblolly pine seedlings showed slow 

growth or death in response to 

flooding. 

Diameter growth patterns were the same 

for CYPRESS 1 and PINE 1 seedlings. 

Both species had reduced growth with 

increasing days of flooding. After 3 

days of flooding, PINE 1 seedling 

diameters shrank. Diameter growth of 

CYPRESS 2 and PINE 2 seedlings differed in their responses to flooding. 

A steady decrease in diameter growth 

occurred with increasing days of 

flooding in CYPRESS 2, with shrinkage 

after 3 days of flooding, PINE 2 

seedlings had positive growth for 1 

and 2 days of flooding and small, but 

positive, growth for 3 days of 

flooding. 

Biomass 

One day of saltwater flooding reduced 

the biomass of shoot, leaf, and root 

components in CYPRESS 1 seedlings but 

not in CYPRESS 2 seedlings. The dry 

weight of the three components after 2 

or more days of flooding declined but 

seemed to stabilize with 4 days of 

flooding. Very little growth occurred 

in PINE 1 sedlings, even in the 

unflooded treatment. Even so, there 

was a slight reduction in biomass of 

the three components after 1 day of 

flooding, PINE 2 seedlings showed a 

slight increase in biomass of all 

components with 1 day of flooding. 

and 3 days of flooding resulted in only 

slightly rducecf biomss of a11 3 components. Loblolly pine is apparently 

not a die-back species; it halts growth 

when a threshold level of salt is 

reached and then dies beyond that 

point. Root:shoot+leaf ratios are 

fairly consistent for each species 

regardless of age or treatment. Baldcypress ratios are in the 0.6-0.7 

range, and loblolly pine ratios are in 

the 0.4-0.5 range. Biomass partitioning in surviving trees was not appreciably affected by the treatments. 

DISCUSSION 

In the present study, six-month-old 

seedling growth of baldcypress and 

loblolly pine was very susceptible to 

short-term flooding with saltwater. 

Neither species could withstand more 

than one day of flooding, which is 

consistent with our field observations 

following Hurricane Hugo, Although 

eighteen-month-old seedlings were 

better able to tolerate saltwater 

flooding, surviving up to four days of 

saltwater, there was no appreciable 

difference in root:shoot+leaf ratios, 

Ratios of 0.4-0.5 for saltwater-flooded 

loblolly pine are consistent with the 

results obtained by McXee and others 

(1984), Hook and Denslow (1987), and 

Shear and others (unpublished data) for 

loblolly pine seedlings grown in soil 

tanks for 1.0-2.5 years with continuous 

freshwater flooding during the growing 

season. More study is needed to determine if salinity tolerance increases 

with age and size, as waterlogging 

tolerance does (Gill 1970), or if 

tolerance is related to environmental 

or genetic factors. 

In other studies with baldcypress 

and loblolly pine, it has been noted 

that stomata1 conductance and net 

photosynthesis were reduced when 

salinity levels exceeded 3 ppt 

(Pezeshki and others 1987, Pezeshki 

1990, Pezeshki 1992). Over the longterm, Pezeshki and others (1988) 

speculated that ion accumulation, such 

as Na, in baldcypress leaves would 

continue until leaf death occurred. 

Leaf injury in the present study was 

evident within three days of flooding, 

but new buds appeared along the stem or 
at the base of the seedling by the end 

of the first week after renaoval from 

saltwater . Baldcypress and loblolly pine are 

limited in their distribution in 

coastal regions by salinity. Tolerance levels of these species, however, 

is unknown. Salinity tolerance of 

baldcypress has been reported variously to be 0.002 ppt (Beal 1977), 2 

ppt (Chabreck 1972, Wicker and others 

1981), or 8.9 ppt (Penfound and 

Hathaway 1938). toblolly pine is 

susceptible to saltwater flooding, 

especially in areas where drainage is 

impeded (Little and others 1958, Land 

1974, Gardner and others 1991, Hook 

and others 1991). Little and others 

(1958) hypothesize that hardwoods are 

more susceptible to saltwater flooding, and this might account for the 

fact that few hardwoods are found in 

pine stands near the Chesapeake Bay. 

As sea level continues to rise in 

coastal areas and storm surges occur 

with future storms, it will be 

interesting to observe and document 

the response of coastal forests to 

these stresses. 

Research was supported in part by a 

grant from the U.S. Forest Service. 

Additional funding was provided by the 

Department of Forest Resources, 

Clemson University. The authors wish 

to recognize the significant technical 

contributions of Wayne Inabinette and 

Jeffrey Vernon. 

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Jr.; Askew, J.L. 1984. Growth and 

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serotina, and Pinus taeda seedlings to 

anaerobic solution culture, I. Changes 

in growth and root morphology. 

Physiologia Plantarum 68:523-531. 

Wallace, R.H.; Moss, A.E. 1939. Salt 

spray damage from recent New England 

hurricane. Proceedings of the Annual 

National Shade Tree Conference 15~112- 

119. 

Wells, B.W.; Shunk, I.V. 1938. Salt 

spray: an important factor in coastal 

ecology. Bulletin of the Torrey 

Botanical Club 65:485-492. 

Wicker, K.M.; Davis, D.; DeRouen, M.; 

Roberts, D. 1981. Assessment of extent 

and impact of saltwater intrusion into 

the wetlands of Tangipahoa Parish, 

Louisiana. Report to Tangipahoa Parish 

by Coastal Environments, Inc., Baton 

Rouge, LA, USA. 

Reprinted with permission from Wetlands 

12(3):230-233. Dr. Douglas A. Wilcox, 

Editor. US Fish and Wildlife Service, 

National Fisheries Center - Great 

Lakes, 1451 Green Rd., Ann Arbor, MI 

48105. 
LONG-TERM RECOVERY OF PLANTATION-CRO 

LOBLOLLY PINE: FROM HURRIC E' 

P. H. Dunham and D. H. I3ourgeoisZ 

Abstract--A study established in nine plantations to 

quantify the long-term recovery of plantation-grown 

loblolly pine from damage by Hurricane Hugo was installed 

in early 1990. After three years, mortality of storm 

damaged trees was 8.1%, with 2% of the trees being 

non-leaners, 8% had an initial lean between 0 an 25', 15% 

were leaning between 25' and 50°, 40% were leaning between 

50' and 75' and 35% of the dead trees were leaning at least 

7S0 initially. The initial average angle of mortality 

trees was 61'. Three-year diameter growth gradually 

decreased as initial average angle increased. On average, 

height growth increased as initial angle increased, up to a 

given angle, then decreased below the growth of the 

non-leaners. Initial angle significantly influenced 

diameter growth for the three-year period for all initial 

ages, but was a significant contributor to three-year 

height growth for initial ages 2 and 5 only. For all 

leaning trees, the average positive change in stem angle 

generally decreased as the age of the stand increased, 

particularly for those stands initially older than age 5. 

Recovery, however, did occur along all measured points on 

the stem, with the greatest improvement occurring during 

the first year. 

INTRODUCTION 

Tropical storms and hurricanes strike 

the Gulf and Atlantic Coasts almost 

annually (Touliatos and Roth 1971). 

On September 21, 1989, Hurricane Hugo 

struck the Coastal Plain of South 

Carolina with sustained winds of 

approximately 135 mph (estimated) and 

gusts up to 160 mph (Powell 1990). 

Based on aerial and ground surveys, 23 

counties were judged to have substantial forest damage (Sheffield and 

Thompson 1992). Monetary loss, if the 

timber could have been salvaged for 

its highest product use, was estimated 

at $10 billion (Spell 1990). 

Westvaco Corporation, a major pulp, 

paper and packaging manufacturer, 

suffered timber damage on 150,000 

acres. While the salvage of marketable 

timber received the most immediate 

attention, relatively young loblolly 

plantations also had extensive damage, 

generally in the form of stem lean. A 

review of the literature showed most of 

the published storm-related material 

dealt with either damage assessment 

(for example, Van Hooser and Hedlund 

1969 or Trousdell and others 1965) or 

changes in e~ological succession (see 

Foster 1988). There was little in the 

literature on the recovery of existing 

trees and stands from any storm damage, 

much less hurricanes. 

A paper presented at the IUFRO Conference on Inventory and Management in McRellar (1942) reported on the shortthe Context of Catastrophic Events, tern recovery of six- and seven-yearUniversity Park, PA, on June 21-24, old plantation-grown loblolly, slash 

1993. and longleaf pines from ice damage in 

Biometrics Center Leader and Bio- the Piedmont of Georgia. More 

metry Project Assistant, respectively. recently, an unpublished Westvaco 

Westvaco Corporation, P.O. Box 1950, 

Summerville, SC 29484. 
Forest Research Report3 covered the 

eight-year response of ice damaged 

ten-year-old plantation-grown loblolly 

nt of Virginia. In both 

cases, individual pines showed partial 

covery, depending on the 

ge and the response 

variable measured. 

Brewer and Linnartz (1973) conducted a 

one-year recovery study of twenty-six, 

eleven-year-old, plantation-grown 

loblolly pine trees damaged by Hurricane Camille. Trees leaning less 

than 45O from vertical recovered to 

some extent while trees leaning lSO to 

25' straightened to the point where 

the lower portion of the bole had 

returned to vertical. The authors 

recommended salvaging any trees 

leaning more than 45' as these trees 

are not likely to recover substantially, 

Their results indicate that at least 

for one age class, plantation-grown 

loblolly pine will recover to some 

extent, depending on the initial lean 

after the storm, Long-term responses 

to hurricane damage over a range of 

ages are unknown, Guidelines are 

needed to determine which plantations 

will recover and which to salvage or 

replant. Growth and yield of damaged 

plantations need to be quantified to 

determine if and how our models should 

be modified to reflect these conditions. 

The study has three specific objectives: (i) to quantify individual 

loblolly tree and stand responses to 

hurricane damage; (ii) to develop 

operational guidelines for determining 

the future status of damaged loblolly 

plantations; and (iii) to publish the 

results in the forestry literature. 

This paper reports the recovery and 

growth responses three years after 

Hurricane Hugo, 

Field Location 

Nine existing Westvaco Forest Research 

study sites, all on the coastal plain, 

were selected on the range and degree 

of storm damage present. The majority 

of the studies were age 5 or younger 

Bell, R, D, and P, H. Dunham, 1987. 

Response of ten-year-old plantationgrown loblolly pine subjected to ice 

damage, Westvaco Forest Science 

Laboratory - Biometries Group, Res, 

Report No. 65, 17 pp. (Unpublished) 

based on the assmption that stands 

much older than five could be salvaged, 

Three older stands (ages 8, 10 and 20) 

are being followed, primarily for 

survival info 

The original objectives of the studies 

ran the gamut of applied forestry 

research, Three locations were 

genetics studies, three locations 

teeted various site-preparation 

treatments, and three locations were 

fertilizer trials with one trial also 

having a thinning treatment, In 

addition to the degree of damage, the 

plots for the recovery study were those 

treatments which would most likely be 

used in the future by operations, Due 

to the vagaries of the storm, no 

attempt was made to link the original 

treatments with the frequency or 

severity of storm damage. 

The study was installed in late 

February and early March of 1990, 

approximately five months after Hugo, 

At seven of the locations, all or 

portions of the original measurement 

plots were used. The size of the 

measur-nt plots varied but generally 

centered around 0.05 acre, At two 

locations the recovery plots were 

established in the buffer areas 

surrounding the original plots due to 

study salvage efforts. 

Response Variables 

Several objective and subjective attributes were measured, These included 

traditional variables such as dbh and 

crown class, They also included angle 

measurements for quantifying initial 

stem lean and subsequent recovery by 

stem position, Three sets of horizontal and vertical distances were 

measured on all study trees, The 

vertical distances are the height to 

eight feet of stem length, crown base, 

and the tip of the tree, The horizontal distances were measured from the 

stem base to the point perpendicular to 

each of the vertical distances. A 

carpenter's level was used periodically 

to insure both measures were true. The 

horizontal distance defaults to zero 

for non-leaning trees. A subjective 

adjustraent factor to account for badly 

bending stems of leaning trees was 

ocularly esthted to "correct" the 

calculated total stem length and length 

to crown base, 

Because crown base and terminal 

distances on surviving trees will 

change irrespective of recovery, on a 

subset of the trees ages 2 through 5, 
horizontal and vertical distances to 

4.5 feet, one half of original stem 

length and the original tip were also 

measured and marked on the stem 

(Figure 1). The number of trees 

selected varied by plot but was the 

greater of 10% or six trees. 

Figure l--Stem measurement locations. 

Several subjective codes were used to 

describe stem form, stem damage, crown 

damage and root dmage. The seven 

stem damage codes reflect the most 

severe stem damage inflicted by the 

hurricane and may be used later in the 

study to help select trees for wood 

quality analyses. The eight stem form 

codes include lean, forking, bole 

sweep, butt sweep and short crook, 

These codes are expected to change 

over time as trees recover. Crown 

damage reflects the amount of foliage 

and or branches lost in 25% increments. Root damage differentiates 

between visible, broken roots and 

"wallowing" (the formation of a hole 

in the soil at the root collar). 

At every location, selected trees and 

vistas are being photographed during 

each measurement to visually document 

change. 

Aaalyses 

The data were analyzed using graphic, 

correlation, and regression analysis 

to determine the relationship between 

post-storm and pre-storm tree size and 

the influence of initial lean on 

three-year growth and angle recovery. 

For presentation purposes the data are 

grouped into five lean categories, no 

lean (0°), 0°<x250, 25°sx<500, 50°sx 

<75O, and r75O, loosely based on 

Brewer and Linnartz (1973). Statistical significance is based on an a 

priori alpha level of 0.05. In most 

cases, however, the actual probability 

values are presented. 

RESULTS 

Some variables could not be measured 

over the or were dropped for these 

analyses due to confounding. The 

original tip could not be located after 

even one year and was dropped. The 

angle at the base of live crown was 

also dropped from the analyses due to 

ambiguous changes in angle. 

Initial Damage 

At establishment there were 1534 living 

trees across the nine locations. Initial hurricane mortality found during 

establishment was 2.7%. On a percentage basis, 61.5% of the live trees were 

classified as leaning. The average 

stem angle (leaning trees only) was 

almost 36'. Table 1 presents these 

data according to age class, along with 

the occurrence of other damage. 

Across the study, initial average angle 

(average of all angles collected for a 

given tree) was significantly negatively correlated with initial dbh, 

plantation age and stem length (analogous to total height prior to the stom 

- measured or calcudated from horizontal and vertical measurements). 

Through initial age 5, dbh and stem 

length were significantly correlated 

with initial angle although the sign of 

the coefficients varied by age. For 

the three older stands the correlations 

were generally not statistically 

significant (Table 2). 

Post-Storm Mortality 

First-year mortality overall was 4.4%. 

Mortality of trees judged to be damaged 

by the hurricane was 5.7% or 61 trees. 

By year three, total mortality had 

increased to 6.5% with storm-damaged 

mortality rising to 8.1% (Table 3). By 

lean category, the d ge mortality was 

2% (2 trees) for non-leaners, 8% (7 

trees) for trees initially leaning 

between 0' and 25', 15% (13 trees) 

leaning between 25' and 50°, 40% (35 

trees) leaning between 50' and 75' 

initially and 35% (30 trees) leaned at 

least 75'- Initial average angle of 

the mortality trees was 61°. Approximately 70% of the mortality of storm 

damaged trees to date occurred in the 

first year. 

Root damage and blowdown were also 

factors in the mortality. By the end 

of the third year, almost 45% of the 

root damaged trees had died. This 
Table 1--Initial stand conditions by age for the nine study locations 

~vgl stem2 Hurricane Average4 Total Trees With 

r of DBH Length Mortality Angle 

Age Sites (plots) (in) (ft) (percent) (degrees) 

- - 

Mean (M) or Total (T) 2.7 M 1534 T 1069 T 943 T 35.8 M 287 T 33 T 

For trees > 4.5' in height. 

Vertical height from groundline to terminal - all trees. 

NO. of living trees visually daaaaged by the hurricane. ' Average based on all angle measurements per stem, degrees from vertical - leaning trees only. 

Visible root damage - all trees. 

NO. of living trees with one e n t i r e s i d e touching the ground. Average angle of 90'. 

Table 2--Linear correlations with initially as blowdown. Not surprisaverage stem angle at study ingly, 67% of the "blowdown" trees also 

establishment across ages and by age. had visible root damage. 

NO 

Variable Trees Correlation Probability 

--------------Across Locations-------------- 

Age 1534 -0.2425 0.0001 

DBH 1423 -0.2988 0.0001 

Stem Length 1534 -0.2583 0.0001 

_-------------- Initial Age 2---------------- 

DBH 297 0.1918 0.0009 

Stem Length 407 0.3662 0.0001 

--------------- Initial Age 4---------------- 

DBB 509 -0.3280 0.0001 

Stes Length 510 -0.2871 0.0001 

---------------Initial Age 5---------------- 

DBH 285 -0.2231 0.0001 

Stem Length 285 -0.1308 0.0272 

---------------Initial Age 8---------------- 

Ilf3H 102 0.0211 0.4824 

Stem Length 102 0.2123 8.0322 

---------------Initial Age lo--------------- 

DBH 68 -0.1321 0.2830 

St- Length 68 -0 1882 0.1244 

--------------- Initial Age 20--------------- 

DBH 162 -0.1035 0.1900 

Stern Length 162 -0.0921 0.2439 

compares with the study population of 

approximately 19% of the living trees 

in- 1990 with- root damage. Twenty-one 

percent of the third-year damage 

mortality occurred in trees marked as 

"blowdown" (where the one entire side 

of the crown touched the ground). This 

is over one-half of the trees coded 

Proportionally, mortality of damaged 

trees was least in the youngest stands, 

increased with age through age 5, then 

decreased slightly through age 10 with 

a slight increase at age 20. Three 

years after the storm, mortality ranged 

from 0.3% for the initial age-2 stands 

to 14.7% for the initial age-4 stands. 

The decrease in mortality for the 

age-10 stand is probably due to the low 

number and severity of leaners (Table 

1). Except for the initial age-2 

locations, weighted average mortality 

over the three-year period for hurricane damaged trees was 11.3% (combined 

information from Tables 1 and 3). 

Qrawth 

After three years, the tips of most of 

the surviving leaners had essentially 

returned to vertical. No horizontal 

measure was required, thus stem length 

was not estimated. To keep height 

values compatible across measurement 

periods, height growth refers to 

changes in vertical height rather than 

stem length. 

Because initial average angle was 

significantly correlated with initial 

diameter and stem length, linear 

regression was used to examine the 

relationship of three-year growth to 

initial average angle after accounting 
Table 3--Three-year growth and mortality by five categories of stem lean and 

initial age. 

Lean1 

Category 

DBW 

inches 

Percent 

Hurricane2 ROO^^ 

Height Related Blowdown3 Damage 

( feet ) Mortality Mortality Mortalit

0.9* 6.1 0.1 

1.3 9.5 0 

0.9 7.2 0-2 

0.4 7.0 0.2 

All died in 1991 0.4 

- 

0.1 3.0 0.3 

None recorded at establishment 

None recorded at establishment 

O0 20 0.5* 1.8 0.1 0 

0 O<-<25 O 0.5 1.7 0.6 

25O~-<50° 0 8.0 0.1 0 0 

50°s-<75O All died in 1991 0.2 0 

275' All died in 1991 0.7 21.2 

Based on initial average angle at establishment. 

* Initial average angle was statistically significant at the a=0.05 level 

model growth = a + fil initial size + fi, initial angle. 

Based on 1069 hurricane-damaged trees recorded at establishment. 

Based on total number of trees in 1990 classified as blowdown or having 

root damage (Table 1). 

in the 

visual 
for initial size. Residuals from the 

simple linear regression of growth on 

"initial" size were plotted over 

initial angle. The residuals showed a 

distinct deereasing trend as average 

angle increased, at least for the 

younger ages (Figure 2a). Including 

average angle in the regression 

removed the trend in the residuals 

(Figure 2b). For three-year growth, 

initial average angle was a significant addition to the diameter-growth 

regressions for all initial ages but 

only contributed significantly for 

ages 2 and 5 in the three-year 

height-growth regressing. Average 

angle did not significantly improve the regressions on height growth for 

ages 4, 8, 10, and 20. 

Initial Average Angle 

Figure 2a--Residuals from regression 

of three-year diameter growth on 

initial dbh at establishment over 

initial average angle at estab1iuh;lraarnt 

for age-2 stands. 

Initial Average Angle 

Figure Zb--Residuals from regreauion 

of three-year growth on initial dbh 

and initial average angle at establishment over initial angle for age-2 stands. 

Based on the sign of the regression 

coefficient for initial average angle, 

three-year diameter growth by initial 

age shows a gradual, though significant, decrease as average angle 

increases. While not total agreement, 

this trend in decreased growth as 

angle increases is evident in Table 3. 

The sign of initial angle for threeyear height growth, however, ia not 

consistent across ages. Ifthere initial 

average angle was significant (ages 2 

and 5), the aign is positive, indicating increasing vertical growth as 

initial angle increases. Otherwise, 

the sign of the coefficient is generally negative, and the coefficient is 

not statistically significant. The 

raean height-growth values by age in 

Table 3 (and scatter plots of the data) 

indicate a parabolic relationship with 

growth increasing as initial average 

angle increases, then decreasing after 

the angle reaches some "critical 

level," Including a quadratic tern in 

the mdel did not change the results 

dramatically. 

Recovery of Lean 

The greatest improvement in average 

angle (Anglego - Angle,, ) (Anglego ) x 

1001 always occurred m the 0°+-<25' 

category while the least improvement 

occurred on those trees leaning at 

least 75O initially, irrespective of 

age. This is true for both the oneand three-year changes. The largest 

percent recovery toward vertical 

occurred after the first year for the 

two initial lean categories less than 

50' but this varied somewhat by age 

(Table 4 ) . Three years after the storm, the 

leaning trees on the initial age-2 

locations had at least a 90% recovery, 

regardless of initial angle. For 

initial ages 4 and 5, the recovery was 

80% or better for the trees leaning 

less than 7S0 at establishment. Trees 

leaning at least 75' at establishment 

improved less than 50%. As the initial 

age increases, the percent recovery 

decreases, particularly for trees 

leaning more than 25' initially. 

Simple linear regressions of percent 

change to initial average angle were 

significant for all ages, for both oneand three-year recovery. The sign of 

the angle coefficient was consistently 

negative, indicating a decreasing 

percent recovery with increasing 

initial lean (Table 4). 

By stan position, the greatest change 

in angle occurred at the tip of the 

tree. Three years after the stom the 

average hprovement at the tip was 97%. 

The least recovery occurred at the 

8-foot position, which showed a threeyear change of 77%. While proportionally a small number, several leaning 

trees showed a negative change in angle 
Table 4--First- and third-year changes in average angle by five categories of stem 

lean and initial age. 

1990, 1991' 1993' 

Average Average Change Average Change 

~ean' Angle Angle in Angle Angle in Angle 

Category ( degrees f (degrees ) (%I ( degrees ) ($1 

----------------I-------------.---- Initial Age 2-------------.--------------------- 

00 ---- 

0°<-<25 a 16 . 9 2.7 85. O* 0 loo* 

25°~-<500 36.1 6.9 80.5 0.2 99.6 

50°s-<75O 60.4 17.1 71.5 0.2 99.7 

275' 83.5 35 . 9 57.2 8.8 90.3 ................................... Initial Age 4------------------.---------------- 

o0 ---- 

0°<-<25O 15.3 2.4 85.4* 0.1 99.4* 

25°s-<500 36.0 10.3 71.2 0.8 98.3 

50°~-<750 60.2 34.6 43 • 5 12.5 80.3 

275 79.6 69.2 13.0 43.8 45.0 

.---------------------------------Initial Age s---.------------------------------- 

oO ---- 

0 O<-<25 a 14.4 2.1 87.2* 0.5 96.8* 

25O~-<50" 37.7 14.1 63.7 4.7 88.2 

50's-<75O 60.1 37.7 37.6 11.6 81.1 

275O 78.5 69.6 13.0 46.2 40.5 

-------------------------------.-Initial Age 8----------------------------------- 

oO ---- 

0°<-<2S0 9.5 2eO 87*3* 0.6 96.2* 

25'~-<50' 36.3 25.5 29.6 17.4 55.6 

50's-<75O 58.3 42.0 23.0 37.1 

r75O 

31.1 

88.8 All died in 1991 ................................... Initial Age lo---------------------------------- 

oO ---- 

oO<-<25 a 11.3 6.7 56.3* 3.5 78.8* 

2S0s-<50° 33.8 31.1 2.6 28.7 14.0 

50's;-<75O None recorded at establishment 

r75O None recorded at establishment 

-----------------------------------Initial Age 20---------------------------------- 

o0 ---- 

0°<250 10.7 9.3 26.6* 3.2 74 . 7* 

25O~-<50O 39.1 28.4 9 . 3 29.6 9.3 

50°s-<75O 55.4 All died 1991 

27S0 89.6 All died 1991 

Based on initial average angle at establishment. 

ALL live trees in 1990 by initial lean category. 

Based on all live trees by category in 1991. 

Based on all live trees by category in 1993. 

* Initial average angle was statistically significant at the a=0.05 level in the 

model % change = a + p, initial angle. The "zero-leann category was dropped for 

this analysis. 
at the El-foot position one and three 

years after the storm ( 19 and 11 

trees, respectively). Overall, the 

initial average lean improved by 92% 

after three years although this varied 

consliderably by age (Table 5). 

Leaning trees will return towards 

vertical over time, especially the 

younger trees. 

While the xesulte do show a dramatic 

inprovament in initial angle by stem 

position, that does not necessarily 

mean the trees have returned to 

pre-storm straightness. Three years 

after Hugo, 808 of the 855 surviving 

leaning trees had shifted from 

"leaners" to sowe other stem form 

condition. Of the 808, 31% were 

classified as straight, 21% had bole 

sweep, 27% had butt sweep and 14% were 

recorded as having some other stem 

form condition. Five percent of the 

surviving leaning trees were still 

considered leaning (Table 6). 

DI SCUSSION 

These results apply only to the initial conditions of this study. The 

study areas were selected to represent 

a xange in damage conditions and may 

or may not apply to the storm path as 

a whole. Similarfy, while several 

existing research studies were utilized to take possible advantage of 

past stand history, no attempt was 

made to link the severity or types of 

damage with study treatments. The 

vagaries of the stonn preclude such an 

exercise. 

 he correlations between initial tree 

size and initial average angle are 

interesting. Preliminary observations 

immediately following the storm indiated the tallest, largest trees took 

he brunt of the damage. Across all 

tudy locations this appears to be 

ue with negative correlations 

tween tree size, age and initial 

gle. By-age, however, initial angle 

s signifzcantly positively coxreted with tree size for the age-2 

ands, negatively correlated with 

tree size for ages 4 and 5 and generally not significantly correlated for 

trees age 8 and older. 

Reasons for the change for the younger 

stands from a positive to a negative 

correlation between tree size and 

initial angle are not obvious and 

probably involve factors such as soil 

rooting depth which were not part of 

the sample-selection criteria. As 

conjecture, however, the positive 

correlation for the age-2 locations may 

be related to a possible sheltering 

effect of the smaller trees by the 

taller trees and slight competition on 

the sites. By age 4 the sheltering 

effect becomes negligible while the 

larger trees, because they are better 

established, are better able to withstand the wind. 

The lack of correlation for trees in 

the older stands is in part due to the 

relatively low initial average angle. This, in turn is partially due to st= 

length and stocking. Many of the leaning trees were caught in their neighbors, artificially limiting the initial 

angle. Almost 11% of the trees in the 

ages 8-, 10- and 20-year stands contained trees leaning into them. This 

compares with 2.3% for ages 4 and 5 and 

0% for age 2. 

The growing season following the storm 

was relatively dry4. Yet first-year 

mortality of those trees noted as 

visibly damaged at establishment was 

fairly light. Only 5.7% of the damaged 

trees died during the first year. Of 

the 5.7%, 77% were leaning at least 50" 

immediately following the storm. 

Forty-four percent of the trees that 

died the first year had visible root 

ge. 

For ages 8 and 20, all trees 

initially leaning at least 75" died 

during the first year (no trees in that 

category at the age-10 location). 

These results would suggest that 

salvage efforts should concentrate 

first in stands where a majority of the 

trees are leaning at least 50" and have 

a strong occurrence of root darnage. 

This roughly agrees with recommendations by Brewer and Linnartz (1973). 

Three years after the storm, cumulative 

mortality to visibly damaged trees 

increased to 8.1% with 75% of the 

mortality again occurring in the two 

most severe-lean categories. By age, 

the greatest mortality for the two-year 

period 1991-1993 occurred for ages 4 

and 5 (22 trees). This represents 

aWst 85% of the increase from the 

first-year ~portality and is due to the 

vast majority of the most severely 

leaning trees in the older ages having 

died during the first year. 

' Based on the average total precipitation and departure from normal (period 

1951-1980) for all recording stations 

in the five counties where the study is 

located (Anonymous 1991). 
After three years, recovery in angle 

towards vertical was noted at all 

points on the stern. The greatest 

recovery occurred at the tip. The 

least recovery occurred at the lower 

stem positions, dbh and 8 feet. 

Almost 66% of the recovery noted after 

three years occurred after the first 

year. Still, average stem angle 

returned to within 92% of vertical for 

all initially leaning study trees 

surviving after three years. As 

expected, angle recovery varied by 

age. 

Approximately 94% of the initially 

leaning trees surviving after three 

years had changed their subjective 

stem form code from leaning to some 

other condition such as bole sweep or 

butt sweep. These codes will continue 

to be applied f o r t h e duration of the 

study and are expected to change 

further as the trees mature and 

possible additional recovery occurs. 

They will also be used later as part 

of the selection process for determining which trees to destructively 

sample for wood quality analysis. 

LXTEFtATtfRE2 CXTEI) 

Anonymous. 1991. Climatological data 

South Carolina summary. National 

Oceanic and Atmospheric Administration 

South Carolina Vol. 93, 13:l-7. 

Brewer, C.W. and N.E. Linnartz. 1973. 

The recovery of hurricane-bent loblolly pine. LSU Forestry Note #104. 

Louisiana State Univ., Baton Rouge, 

1A. 2 pp. 

Foster, D.R. 1988. Species and stand 

responses to catastrophic wind in 

Central New England, USA. Journal of 

Ecology 76~135-151. 

Powell, Mark D. 1990. Meteorological 

aspects of Hurricane Hugo. In: Hurricane Hugo One Year Later. Benjamin J. 

Sill and Peter R. Sparks, eds. Proceedings of a Symposium and Public 

Forum in Charleston, South Carolina, 

September 13-15, 1990. Sponsored by the 

American Society of Civil Engineers. 

p. 11-40. 

McRelfar, B.P. 1942. Ice d 

slash pine, longleaf pine, and loblolly 

pine plantations in the Piedmont section of Georgia. Journal of Forestry, 

Vol. 40, 10~794-797, 

Sheffield, Raymond M. and Michael T. 

Thompson. 1992. Hurricane Hugo effects 

on South Carolina's forest resource. 

Research Paper SE-284. Asheville, NC: 

USDA Forest Service Southeastern Forest 

Experiment Station. 51 pp. 

Spell, N.E., Jr. 1990. Hurricane Hugo 

one year later. Forest Farmer, 

September 1990. p. 23-25. 

Touliatos, P. and E. Roth. 1971. 

Hurricane and trees ten lessons from 

Camille. Journal of Forestry, Vol. 69, 

5:285-289. 

Trousdell, K.B., W.C. Williams, and 

T.C. Nelson. 1965. Damage to recently 

thinned loblolly pine stands. Journal 

of Forestry, Vol. 63, 2:96-100. 

Van Hooser, D.D. and A. Hedlund. 1969. 

Timber damaged by Hurricane Camille in 

Mississippi. Res. Note 50-96. New 

Orleans, LA: USDA Forest Service 

Southern Forest Experiment Station. 

5 PP* 

Kennedy, R.W. and J.L. Farrar. 1964. 

Tracheid development in tilted seedlings. In: Cellular Ultrastructure of 

Woody Plants. H.A. Cote, Jr. ed. 

Proceedings of the Advanced Science 

Seminar Pinebrook Conference Center 

Upper Saranac Lake, NY. Syracuse 

University Press 1965. p. 419-451. 
ECONOMICS OF LOW DENSITY STAND AGEMENT' 

Stephen K. &Iodine2 

I want to congratulate each of you for 

being here today. Your presence distinguishes you from other foresters by 

your willingness to accept a challenge. The recovery of forest land 

damaged by Hurricane Hugo offers each 

of you the challenge to apply the art 

of forestry in addition to the science 

of forest management. If I may generalize a bit, any forester with half 

his senses can prescribe the old 

tried-and-true treatments for a site. 

The forester who goes beyond the 

cookbook solutions to match the site, 

the landowner and the possibilities is 

the true artist of our profession-an 

individual who has both the courage, 

insight and foresight to respond to 

the challenge. 

In the aftermath of Hurricane Hugo and 

in the context of today's workshop, 

what is the challenge facing you? It 

is to efficiently restore forest land 

to a productive state. This new level 

and type of productivity may or may 

not resemble that which was present 

before the hurricane. It will vary, 

depending on the conditions of the 

land, the landowner's objectives and 

resources, and the resourcefulness 

which you can bring to bear on the 

situation. Since some of you work for 

government agencies, some for forest 

industry, and others as private consultants for nonindustrial private 

forest (NIPF) landowners, each of you 

will face a unique set of circumstances in each tract of land that you 

consider. Your options may range from 

"let it ridem-in other words let 

Nature take its course with whatever 

remains on the site, to pushing 

Presented at the workshop "Vegetation management on storm-damaged 

landsu in Summerville, S.C. on October 

22, 1991. This workshop was sponsored 

by Clemson University Extension Forest 

Resources. 

Stephen K. Nodine is Instructor and 

Extension Forester, Clemson University, Department of Forest Resources. 

everything over, regardless of cost or 

complexity, and starting over from 

scratch . In my discussion, I want to set the 

backdrop for the technical discussions 

and demonstrations that are to come 

later in this workshop. We will 

consider how to look at the various 

alternatives that may be available, and 

how to evaluate their relative merits. 

WHAT ARE THE FACTS? 

A question which seems obvious but 

which must be addressed at the outset 

is "Why should we worry about new and 

different methods or approaches for 

doing things that we've been doing for 

years?" The first reason is that a lot 

of land is now understocked-now that's 

an understatement if there ever was 

onel This creates specific situations 

of land producing at less than its 

biological and economical potential. 

If the landowner's objectives include 

achieving that potential, then there is 

a problem (or opportunity) that needs 

to be addressed. 

Second, landowners possess limited 

capital resources to support forest 

regeneration and management activities. 

This is always the case with NIPF 

landowners, but was never more true 

than after Hugo. In addition to having 

many other expenses facing them in 

their personal recovery from the storm, 

those who have been successful in 

having some timber salvaged have seen 

the prices they received for post-Hugo 

timber drop to as low as 10-25 percent 

of its pre-Hugo value. Cost-sharing 

assistance is available through various 

programs, but it is insufficient to 

cover the breadth of the need. Corporate landowners also face limited 

capital available for massive restoration. Even though they may have 

greater resources from which they can 

draw, they still must justify their 

actions as economically efficient, 

Third, all landowners in general, and 

NIPF landowners in particular, have 
limited knowledge of the options 

available to them, Residual debris is 

present in quantities never before 

seen or imagined. The profile of the 

forest site, the accessibility, and 

special environmental concerns pose 

that have never been 

addressed at such a scale. 

Fourth, NIPF landowners have expressed 

in surveys a profound and deep-seated 

conviction and expectation of the 

natural regenerative powers of the 

forest. Although they may not express 

it directly, their past experiences 

tell them, that the forest can do 

remarkably well at rebuilding itself, 

Although they recognize that Nature 

may not work as fast on its own 

without human intervention, they find 

themselves less willing to invest 

large amounts of money and energy in 

reforestation and stand rehabilitation. 

Fifth, several factors are more 

limited than usual* Since everyone 

needs help at the same time, foresters 

and service vendors are in short 

supply, Also, seedlings to replant 

all the acres that need replanting 

simply aren't available at present* 

The sixth reason is based in the 

context framed by the previous five 

reasons* Because landowners of all 

types are more dependent now than ever 

on foresters for advice and encouragement, it is important for us to look 

for all the best ways available to 

help stretch the vastly insufficient 

resources across a field of need that 

vastly exceeds anything we have ever 

faced up until now. 

NHAT ARE OUR OPTIONS? 

Without trying to justify any of the 

alternative stand treatments that have 

been suggested, and without getting 

into their technical requirements, I'd 

like to make note of four options and 

a few pros and cons of each. 

If a stand is still adequately 

stocked, meaning that there is still 

at least 60 percent stocking on the 

site, you may choose to do nothing 

other than routine maintenance and 

protection activities* Because of a 

stand's ability to draw upon the 

resources of a site with whatever 

number of trees are available, you may 

expect to receive near-normal returns. 

There would be little additional cost 

above that which would have normally 

occurred, It will not be a perfect 

stand of trees-there will likely 

be some unevenness in the stem distribution, and undesirable species may 

begin to encroach more readily into the 

stand, Internal damage to the residual 

stems may result in some degradation of 

product quality that can't be predicted, but the high level of stocking 

should reflect lower degrees of damage 

and minimize value loss. 

Several methods of rehabilitating 

stands have been discussed recently 

which move some of the debris, rather 

than removing it, followed by planting 

a few additional trees to achieve a 

mixed-age stand, This avoids the high 

cost of more drastic treatments, and 

allows some revenue to be received 

sooner by harvesting the residual stems 

before the new seedlings would ordinarily reach a first thinning size. 

Again, the landowner is left with a 

less-than-ideal stand, but that is the 

trade-off. Because this is an unfamiliar treatment to most foresters and 

landowners, with more uncertainty about 

the results, adopting this type of 

approach represents a step of faith for 

both the landowner and forester. 

Natural regeneration is a more familiar 

option to many of us, but practicing it 

here adds a few new twists. As with 

any natural regeneration option, you 

trade off less guaranteed success for 

lower up-front costs. A fully-stocked 

stand is assumed, but you can't take 

advantage of genetically-improved 

seedling stock. The available seed 

trees may be more dispersed than usual 

and if they have suffered significant 

damage, they may not be alive for 

several years in case the first seed 

crop doesn't take. One other factor 

that can influence natural regeneration 

practices-the use of prescribed fire 

is more risky under the heavy fuel 

loads that remain in this area. This 

practice would likely be more expensive, if it is even an option on some 

sites. 

Finally, artificial reforestation is an 

available option. This approach traditionally achieves a greater degree of 

success and allows more control over 

the resulting stand* However, few of 

us have tried debris removal in site 

preparation that comes close to what 

some damaged stands will require. If 

the damaged trees were salvaged, this 

may not be a problem, but in most cases 

there will be greater hurdles to clear, 

and higher costs associated with them. 
WftAT ARE THE PAXOFFS? 

This brings us to the bottom-line 

questions we always face-*Can this be 

done?" and "Is this profitable for 

me?" Research by Baker (1989) 

indicates that these approaches can 

result in successful restocking of a 

damaged stand. The key to success is 

evaluating the residual stocking 

levels. Those stands with greater 

than 60 percent stocking have found to 

approach near-norxnal growth and 

returns. Stands with lower stocking 

levels have been successfully managed 

using rehabilitation techniques. In 

one example, stands with less than 60 

percent stocking were cut back to 

levels of 10 to 50 percent stocking, 

primarily by removing trees greater 

than 12 inches dbh. They anticipate 

that such stands will reach acceptable 

stocking levels within 15 years at low 

investment costs ($45-$50 per acre). 

In analyzing the results of this study 

after ten years, Straka and Baker 

(1990) evaluated three alternatives: 

selection management of an understocked stand, natural even-aged 

regeneration, and artificial regeneration to a plantation. In calculating 

the profitability of each alternative, 

they considered situations that would 

include and exclude the cost of land. 

For a landowner whose options include 

selling the land, land costs should be 

considered. For the landowner who 

will continue to own the land regardless of its condition, land costs can 

be excluded. 

Highlights of the four options considered are smarized in Table 1. 

When land costs were excluded from the 

analysis, lower-cost alternatives 

provided higher rates of return on the 

investments, and had higher net present 

values a t a l l but the lowest discount 

rates. Including land costs changed 

the perspective, requiring higher 

levels of timber production to cover 

the additional costs, Were, however, 

all options were profitable only at a 

low four percent discount rate. 

WHAT AREJ THE WIM)mERS 

THXNKXNG? 

Those of you who work with NIPF landowners have already heard from them, 

and could share many "war stories" from 

their experiences. In designing 

programs and other forms of assistance 

for landowners, we conducted a survey 

to gather and analyze their attitudes 

and concerns (Nodine, 1992). We found 

that most landowners still have many of 

the same priorities for their land, but 

fewer cited timber production as their 

highest priority after Hugo (Figure 1). 

Their dependence on timber production 

as a source of income declined sharply, 

with many no longer expecting timber 

income and others shifting their expectations farther into the future (Figure 

2). Given these lowered income expectations, we can assume that they will 

be more reluctant to invest significantly in timber stand recovery. 

Table 1--Net present values (by discount rate) and internal rates of return of 

timberland investment alternatives, including and excluding land cost, on a per 

acre basis (Straka and Baker 1990). 

Internal Rate 

Alternative Net Present Value of Return 

4% 7% 10% (percent ) 

Excluding Land Cost 

Selection management 

Chemical release 

Plantation (est. cost $150) 

Plantation (est, cost $250) 

Including Land Cost 

Selection management 

Chemical release 

Plantation (est. cost $150) 

Plantation (est. cost $250) 
Figure 1--Top forest land use 

priorities of landowners before and 

after Hurricane Hugo. 

We did find, however, that as they look 

forward in time, their general expectations for their land become more positive (Figure 3)- One-third of the 

landowners expressed positive expectations for their land two years from 

now, while more than half expect their 

land to be improved five years from 

now. This result poses the possibility 

of the proverbial two-edged sword, 

Cutting in a positive way, these generally positive feelings about their 

land, coupled with a land ethic which 

i8 generally strong among NIPFs, may 

help overcome some of their reluctance 

to act. Cutting against the grain, 

however, is the likelihood that some 

landowners will not be swayed to 

actually spend much money on the 

process, leaving it instead to Nature 

to achieve the restoration. 

Positive 57.7% 

Other 1.2% 

ncertain 25.5% 

In five years 

Figure 3--Forest landownersr expectations for their forest land following 

Hurricane Hugo. 

When asked about the effect of costsharing on their plans, many did indicate that this would influence their 

decisions. Many others, however, indicated that cost was not their onlv 

eignif icant concern. Their own lick of 

Figure 2--Forest landownersr familiarity with traditional forest 

dependence on their forest land for practices is compounded by the extreme 

income, before and after Hurricane damage they experienced and the lack of 

Hugo. technical information and advice that 
they have received so far. If there 

ever was a time for forester contacts 

with landowners, this is it1 

mERE DOES THIS LEAVE US? 

We can conclude that there are costeffective ways to approach these 

damaged stands, but I think you 

already know that there are no simple 

blanket prescriptions that can be 

applied profitably in a blanket 

approach. You will see during the 

inder of this workshop some of the 

technical aspects of forest restoration and recovery. I think that you 

should view those within the context 

of the landowners that you will be 

facing after the workshop. Obviously, 

it is in the best interest of the 

landowner to make his investment best 

for his situation. If he can earn a 

reasonable profit under natural stand 

management with a low initial investment, why should you recommend a 

system that may earn a little more but 

which is much more expensive up front 

and which may not provide as many 

other benefits which serve his other 

ownership objectives? 

Landowners are hungry for technical 

information and advice, especially in 

the area affected by Hugo and in the 

subject of natural regeneration and 

management. In fact, the landowner is 

the first resource to be managed by 

the forester. The forest resource 

must come second. You as foresters 

need to be facilitators for landowners, providing them with options 

and general recommendations, and then 

either helping to implement the needed 

actions or passing the landowner on to 

someone else (particularly consulting 

foresters) to further develop and 

implement the plan. 

You may be saying to yourself or to 

each other, "1'11 sure be glad when 

this Hugo mess is over. Then we can 

go back to the way things were." If 

you think that's what you heard me 

say, then you fell asleep at a bad 

time. The aftermath of Hugo and 

responses of foresters and landowners 

to it are not an anomaly in the 

progression of forest management skill 

and understanding. Most of these 

changes were already underway before 

September 21, 1989-Hugo just 

exaggerated the scale of activity a 

little, speeded up the timetable 

somewhat, and forced us to look at some 

new ideas before our inertia might 

otherwise have led us. As proof of 

this, look at the number of hardwood 

management and mixed stand management 

workshops and meetings that are 

springing up everywhere, not just in 

the area affected by Hugo. 

Hurricane Hugo was in very real terms 

an extreme harbinger of what is to 

come. "Kinder, gentler" forestry 

which is less "by the book" and more 

the practice of the art of forestry as 

well as the science is here to stay. 

This isn't bad--we're just learning 

more about forest systems and how to 

work with them rather than against 

them. The move toward naturalfmixed 

stand management is being driven by 

forces that are broader and stronger 

and longer lasting than even the wind 

and fury of Hurricane Hugo. Those of 

us who try to resist the change/ 

maturation that is inevitable will be 

like many of those boats, houses and 

trees that were swept away by the storm 

and left lying about, broken and useless. Those who see the early signs of 

permanent growth and change in the way 

we work with people and help them 

manage their forests will find safety 

in the high ground of new understanding! new ideas, and broader sets of 

optlons . 

REFERENCES 

Baker, James B. 1989. Recovery and 

development of understocked loblollyshortleaf pine stands. Southern Journal 

of Applied Forestry 13(3):132-139. 

Nodine, Stephen K. 1992. Forest landowners' responses to Hurricane Hugo. 

Clemson University Department of Forest 

Resources Forest Research Series No. 

47. 37 pages. 

Straka, Thomas J. and James B. Baker. 

1990. A financial assessment of 

capital-extensive management alternatives for storm-damaged timber. 

Presented at the Hanagement Alternatives for Storm-Damaged Timber 

workshop sponsored by Clemson 

University Extension Forest Resources, 

Feb. 8-10, 1990, Sumter, S.C. 
EVALUATION OF C RY PRO S 
FI -PORT: AN EV~UIATIOM OF THE POST-HUGO 

FO-ST RECOVERY PROG : SALVAGE. 

WILDFIRE ElAZARD MITIGATION. AND REFORESTATION 

Marie Lynn ~iranda' 

Table of Contents 

PARTI: TImERSALVAGE. ................................... PmTlAtIMDIATEACTIOW ................................... PART 1B: WVERNOR'S FOREST DISASTER SALVAGE COUNCIL ...................... Members ........................................ Duties ........................................ Funding ........................................ Structure ....................................... PART 1C: ACTIONS OF SALVAGE COUNCIL COMMITTEES ........................ Government Affairs Committee ............................. Public Information Coxunittee ............................. Utilization Committee ................................. Statistics and Monitoring Committee .......................... ExecutiveCoxunittee .................................. PART1D.CMGMERPQLICIES a................................... 

PART~EzSALVAGERESULTS ................................... PARTIF: COMCLUSIONS ..................................... PART 2: WILDFIRE HAZARD REDUCTION AND MITIGATION ....... PART 2A: WILDFIRE HAZARD REDUCTION AND MITIGATION PLAN: PHASE 

Federal and State Programs .............. Structure ....................... Funding ........................ Goal 1: Fuels Management ............... Goal2: FireSuppression ............... Goal 3: Fire Prevention ................ Results ........................ PART2B: TEIEPIANz PHASE11 ................. Structure ....................... Funding ........................ Goallr FuelsManage~lent ............... Goal2: Firesuppression ............... Goal31 Fire Prevention ................ Results ........................ PART 2C: CONCLUSIONS ..................... PARTS: REFORESTATION .................................... 527 

PART3Ar THEREFORESTATIONCOMEltITTEE ............................. 527 

Funding -- Dire Emergency Funds ............................ 528 

Landownersurvey ................................... 528 

Gime Green ...................................... 528 

Hugo Incentive Program (HIP) ............................. 529 

PART3B: CONCLUSIONS ..................................... 530 

APPENDIX I: REC NDATIONS FROM THE GOVERNOR'S FOREST DISASTER SALVAGE COUNCIL TO THE 

GOVERNORfSECONOMICRECOVERYCOMMISSION. ........................... 532 

Assistant Professor of Public Policy Studies with the assistance of Sofia 

Frankowski and Sharon La Palme. Research Aides. Sanford Institute of Public Policy 

Sciences. Box 90245. Durham. NG 27708.0245 . This research was supported by the 

Economics of Forest Protection and Management Research Work Unit 4851. Southeastern 

Forest Experiment Station. USDA Forest Service . 
EXECUl1l"fVE S 

Hurricane ~ugo 4.4 million of 

South Carolina's 12 million acres of 

forested land, totalling almost $1-2 

billion in lost timber value alone, 

The state's response to this forest 

disaster required two simultaneous 

planning strategies, One strategy 

alleviated immediate emergencies and 

consequences of so much forest 

destruction, including recovering some 

value of the downed and damaged timber 

and preventing and suppressing wildfires, The other strategy addressed 

the long-term goal of restoring South 

Carolina forests to their previous 

stature and economic value by encouraging reforestation. The policy 

response was coordinated by the state 

government and utilized programs, 

personnel, and funding at the state 

and federal level, A review of this 

effort provides lessons to improve 

aspects of each program component-- 

timber salvage, wildfire hazard 

reduction and mitigation, and 

reforestation. 

* State forestry personnel, especially 

the South Carolina Forestry Conmission 

(SCFC), and the Governor's office were 

prepared for extensive forest damage 

and responded immediately. 

The day before Hugo struck, the SCFC 

tried to alert landowners to the 

potential for heavy damage to their 

forest land. SCFC personnel and 

equipment were in place to assist with 

clearing roads and restoring communication. They also watched for and 

suppressed fires, and surveyed the 

forest damage, The Governor's office 

worked with the SCFC, the Forester's 

Council, and State Forester to form 

the Governor's Forest Disaster Salvage 

Council. Council members represented 

all divisions of the forestry sector 

--industry, nonindustrial private, 

state and federal, They took charge 

of implementing a forest emergency 

plan. This organized and quick 

response facilitated the initial steps 

of recovery efforts in the forestry 

sector, as well as material and 

personnel support for post-Hugo 

recovery in many other sectors, 

* Clear goals and delegation of 

responsibilities contributed to many 

successes of the forest recovery 

response. 

The magnitude of the forest disaster 

in South Carolina was unprecedented. 

Some aspects of the recovery plan were 

borrowed from Mississippi's response to 

Hurricane Camille in 1969, However, 

most of the response relied on separate 

committees and planning groups to 

devise program goals and assign responsibilities, This was particularly 

crucial with salvage and wildfire 

hazard mitigation efforts; clear goals 

and responsibilities allowed both programs to begin very soon after Hugo, 

The Governor's Forest Disaster Salvage 

Council began salvage efforts just 

weeks after the hurricane, The responsibilities for the salvage effort were 

divided among several separate committees: government affairs; public 

information; utilization (with transportation, storage, out-of-state movement, and utilization subcommittees); 

and, statistics and monitoring. The 

wildfire hazard mitigation program 

emphasized three goals--fuels management, fire prevention, and fire suppression--which allowed the program to 

go beyond emergency response, Outlining goals and responsibilities 

allowed accountability and communication among all agencies and personnel 

involved. In addition, in the months 

after the hurricane, it kept the governor informed and provided him with 

guidance on how to assist in the forest 

recovery efforts. 

* Each area of the response required 

sustained coordination of federal, 

state, and private efforts. 

In the timber salvage effort, the SCFC 

worked closely with the U.S. Forest 

Service and numerous private industries, small businesses, and individuals, The wildfire hazard mitigation 

effort required coordination among the 

SCFC, the U.S. Forest Service, and the 

Federal Emergency Management Agency 

(FEMA). The duration of FEMAfs 

involvement in the wildfire hazard 

mitigation effort has been particularly 

unique; FEMA provided funding for this 

effort for four program years after the 

hurricane, For the reforestation 

effort, the SCFC worked with the U,S, 

Forest Service and numerous private 

forestry consultants, This coordination across levels of governance was 

sometimes achieved by pulling together 

and utilizing a number of pre-existing 

state, federal or local programs. At 

other times it required state policymakers and forestry agency personnel to 

work creatively to initiate and sustain 

state-federal and state-private sector 

working partnerships. 
alvage, wildfire haeard 

mitigation, and reforestation afforts 

nents of technical, 

educational, legislative, and 

monitoring strategies. 

er salvage, fire hazard mitigation, and reforestation all required 

innovative technical solutions, 

acquisition of quipent and 

mekiner:y, and coordination of plans 

and activities, The hurricane 

destruction and subsequent weather 

conditions presented challenges to 

salvage, construction of fuel breaks, 

and reforestation, To address these 

challenges, in many instances, 

forestry personnel had to gain new 

technical skills, while at the sinme 

time, extend some t-hnical information to landowners, 

Dissemination of post-hurricane 

recovery information through mailings, 

print media, broadcast media, word-ofmouth were crucial to inform a broad 

population of landowners of their 

options, available assistance programs 

and advise on how to avoid future 

disaaters. Thie waa particularly 

important in the fire prevention 

effort, one component of which 

att-pted to enlist residents in the 

Hugo-affected areas to sustain a 12- 

month period of no backyard fires, 

prescribed burning of land, campfires, 

or other human-started fires. 

Lobbying campaigns, public hearings, 

visits to and by politicians kept the 

needs and concerns of landowners on 

political agendas and helped to pass 

some funding and other relief legislation. Reforestation received the 

greatest federal legislative assistance--a total of $11 million was 

secured for cost sharing. Other 

federal legislative efforts for help 

with the salvage operation, tax 

assistance or crop loss compensation 

were unsuccessful. 

Information on the nwnber of landowners assisted and the number of 

acres salvaged, reforested, or protected by fire breaks help to gauge 

whether the level of assistance was 

adequate, and whether assistance was 

distributed among a broad range of 

landowners, Additionally, the salvage 

committee monitored sawtimber, pulpwood, and chip prices, and levels of 

demand and supply, This information 

helped determine whether strategy 

changes were needed and when the 

duties of each of the committees, 

ssions could be turned 

over to pre-existing forestry agencies, 

Integrating all these components best 

utilized the capacities of the state 

and federal agencies involved in the 

forestry disaster response to achieve a 

coordinated effort. 

* Timing was crucial to all parts of 

the forest recovery response. 

Weather factors and deteriorating 

timber quality made t 

operations feasible only during a 

limited window of opportunity. The 

optimal period for salvage was set by 

unusually heavy rains in the fall and 

an early start to warm weather in the 

spring--most operations slowed considerably after June of 1990, However, 

this short period coincided with the 

the landowners were most preoccupied 

with other damage, State policy makers 

and forestry personnel need to design 

policies that take maximum advantage of 

the limited window of salvage opportunityIn the hazard mitigation program, fuels 

management required initial emphasis on 

constructing fuel breaks on lands 

prioritized according to level of risk, 

Fire suppression required that localities throughout the blowdown areas 

received sufficient equipment and 

personnel. Finally, fire prevention 

initially required a large-scale 

campaign to inform residents about the 

fire hazard and urge them to avoid 

burning, 

The advertising efforts for the needscheck and the reforestation cost-share 

program may have been mistimed. In the 

year subsequent to the hurricane, landowners were most concerned with repairing damage to their homes and personal 

property, During this time, the SCFC 

also was pushing salvage and wildfire 

hazard mitigation goals, Greater 

response to Ghne Green and the Hugo 

Incentive Program may have been possible with more strategic timing in 

advertising and program imp1 

* Funding was only available for some 

of the forest recovery efforts. 

Securing federal funding was most 

successful for the wildfire hazard 

mitigation and reforestation programs, 

For wildfire hazard mitigation, federal 

funds came from three sources: FEm, 

the Dire Emergency Supplemental 

Appropriations Act, and the U.S. Forest 
Service. South Carolina state government worked creatively to ensure 

's extensive involvement in hazard 

gation efforts. State forestry 

officials lobbied for FEMA involveaent. The Wvernor's Office issued 

guidelines for localities to follow 

when applying for F funds through 

the new Hazard Mitigation Grant 

Program, Section 404 of the Stafford 

Act. As a result, FEMA's involvement 

in hazard mitigation was achieved by 

expanding the eligibility, funding, 

and revising the justifications2 in 

the 1988 Robert T. Stafford Act. FEMA 

funding was mandated through four 

separate sections of the Stafford Act: 

sections 403, 404, 420, and 421. Dire 

Emergency Funds also were allocated 

for a technical assistance program, 

Gimme Green, that provided free consultations on reforestation needs. 

Cost-share assistance, through the 

Hugo Incentive Program, was appropriated through the U.S. Forest 

Service in 1990 and 1991. 

The priority given to funding salvage 

efforts was very low. State and 

federal funds were high demand from 

many other sectors, and compared to 

other aspects of the hurricane 

recovery, salvage lacked any dramatic 

appeal to prevent human suffering. 

State forestry agencies attempting to 

secure federal assistance in the early 

aftermath of recovery might have been 

more successful by describing forest 

damage in terms of its effects on the 

thousands of small landowners who rely 

on their land as their "nest-egg" and 

by drawing the clear link between 

unsalvaged downed timber and wildfire 

hazards. 

PART 1: TIMBER SALVAGE 

By the time Hurricane Hugo made landfall in South Carolina on Thursday, 

September 21, 1989, agencies in the 

forestry sector had already begun to 

prepare for extensive and severe 

forest damage. The Foresters' 

Council, originally established in 

1942 to respond to forest crises, met 

and decided a course of action within 

a week. This swift response led to 

John M. Ols, Jr. 1990. "Preliminary Information on the Federal 

Government's Response to Recent 

Natural Disasters." Testimony given 

to the Subcommittee on Investigations 

and Oversight on the Federal Emergency 

Management Agency's Response to 

Natural Disaster's. May 1, 1990. 

the creation of the Governor's Forest 

Disaster Salvage council, which spearheaded the aggressive salvage program 

in South Carolina, 

salvage was the first, and shortestterm, part of South Carolina's threepart forest recovery plan; the other 

two parts, wildfire hazard reduction 

and mitigation, and rredorestation, are 

covered in Parts 2 and 3 of this 

report. Hurricane Hugo blew down 6.7 

billion board feet of t 

4.4 million acres of land in South 

Carolina alone. The Governor's Forest 

Disaster Council's strategy for salvaging the downed timber used an approach 

that addressed technical challenges to 

salvaging, pursued legislative measures, informed and educated the 

public, and monitored salvage progress 

and forest product markets. As a 

result, South Carolina landowners were 

able to salvage over 350 million cubic 

feet of downed timber--roughly 13% of 

the timber blowdown. This multilevel 

approach was then used in subsequent, 

more long-term policy responses 

directed at wildfire hazard reduction 

and reforestation efforts. 

The following review of the salvage 

effort reveals how the response worked, 

how it utilized the efforts of local, 

state, and federal forestry personnel, 

the challenges that were encountered, 

and the lessons learned. 

PART 1A: IMMEDIATE ACTION 

Before the hurricane struck, the South 

Carolina Forestry Commission (SCFC) 

compiled action pamphlets "Your Trees 

AFTER HUGO" and distributed them via 

FAX to coastal areas and the media for 

general public information. SCFC 

headquarters and district offices 

remained on full alert in cooperation 

with South Carolina's Emergency 

Preparedness Division (EPD). Offices 

were staffed 24 hours a day with a 

liaison representative at the State 

Emergency Operations Center (SEOC). 

Early Friday morning (September 22), 

SCFG dispatched 155 workers and 89 

truckltractor units to the damaged 

areas and arranged for standby staff 

and equipment to be brought in from 

areas with lesser damage. These work 

crews cleared transport routes and 

assisted local Emergency Operation 

Centers in removing timber from 

communication lines. The Commission 

conducted an initial aerial survey of 

part of the storm-damaged area and 

later that night started flights for a 
systematic damage assessment of 

Charleston County. The surveys helped 

to assess the n er and location of 

roads needing c ring and the extent 

and degree of d ge to forest land. 

Aerial and ground surveys continued 

throughout the next two weeks to 

ge to forest industry 

extended over 4.4 million acres in 24 

counties, totaling 6.7 billion board 

feet valued a ,181 billion. These 

figures are s rized in Table 1. 

By Saturday morning (September 23), 

242 SCFC employees and 124 tractors 

were assisting with the relief effort. 

Fire detection aircraft and fire suppression helicopters were kept on 

standby for the EOC, State Forestry 

statute 48-23-86 gave the State 

Forester responsibility to establish a 

disaster plan in the event of a forest 

emergency; Acting State Forester Jack 

Gould decided there was sufficient 

ge to warrant declaration of a 

Forest Disaster. muld first csntacted John McMillan (Director, 

Division of Energy, Agriculture, and 

Natural Resources) of the Governor's 

Office to notify the Governor of his 

decision, and then declared the Forest 

Disaster through Media Advisory. 

Gould immediately contacted other 

members of the forestry sector, 

including the chair of the Forestry 

Commission (Boris Hurlbutt), the U.S. 

Forest Service (Don Eng), the South 

Carolina Forestry Association (Bob 

Scott), and the Clemson Extension 

Forester (Don Ham), as well as representatives of forest industry and 

major resource agencies. Gould wanted 

to schedule an emergency meeting of the 

Foresters' Council of South Carolina to 

seek its advice, but was unable to contact the chair, Ken Bailey, at this 

point. 

On Sunday (Sept er 24), SCFC met with 

the Highway Department, the National 

Guard, and representatives of South 

Carolina Electric and Gas Company to 

plan the restoration of electric service to Charleston. SCFC prepared the 

Governor's Briefing and presented it to 

John McMillan at the State House. 

By Monday (September 25), Jack Gould 

had reached Ken Bailey, chair of the 

Foresters' Council, and had scheduled 

an emergency meeting of the Council for 

Thursday, September 28. The Governor 

issued a statewide burning ban; SCFC 

advised all districts of the ban. 

On Tuesday (September 26), SCFC compiled damage estimates. This inforxnation was relayed to the Governor 

through his press secretary and 

released to the public through a news 

conference held at Forestry Conuaission 

headquarters, Media advisories were 

sent via FAX to all major television 

stations and newspapers. 

On Wednesday (September 27), the 

Federal Emergency Management Agency 

(FEMA) conducted a meeting for agency heads to discuss and coordinate 

response activities throughout the 

disaster area. At this point, FEMA did 

not have any explicit role in responding to the effects of the hurricane on 

the forest sector. FEHA's responsibilities post-disaster include: 

coordinating the roles of emergency 

response agencies; providing assistance 

for individuals and families affected 

by the disaster; and providing funds 

for the repair of damaged public 

Table l--Timber Damage from Hurricane Hugo in South Carolina. 

Sawtimber Pulpwood Sawtixnber Pulpwood 

Damage Damage Saleable Saleable 

Volume Volume Value Value 

(mF)* (millions) (millions) 

Pine 

Hardwood 

Total value of damage to all timber = $1.181 billion 

* MMBF = million board feet, a board foot is a unit of volume with the dimensions 

12" by 12" by lm. 
fa~ilities.~ Although FEW& did not 

have any obvious role or jurisdiction 

in the salvage and recovery of South 

Carolina forests, the Forestry Commission and the Governor's Forest 

Disaster Salvage Council would begin 

meeting with FEM to discuss emergency 

funding. South Carolina Officials 

understood that creative policy making 

and strong leadership were required if 

the forest sector was to benefit from 

FEMA support. The 

Commission and the Governor's Council 

were aware that FEMA funds for the 

forest sector had to be justified on 

the basis of public safety andfor 

public health.' In the coming weeks, 

several meetings between FEMA representatives and the Governor's Council 

would take place to discuss funding of 

salvage, reforestation, and wildfire 

prevention and suppression efforts. 

On Thursday, September 28, the 

Foresters' Council held its emergency 

meeting. Thirty five members and 

guests attended, including representatives of the Governor's Office, SCFC, 

Clemson University Extension Service, 

U.S. Forest Service, U.S. Soil Conservation Service (SCS), consulting 

foresters, industry, and media. The 

Forestry Commission presented a Basic 

Salvage Council Plan to create the 

Governor's Forest Disaster Salvage 

Council; the plan was accepted by the 

Foresters' Council. The plan borrowed 

from Mississippi ' s plan following 

Hurricane Camille, and set a goal of 

salvaging 25% of the damaged timber.' 

Officials in Mississippi communicated 

their willingness to offer advice on 

any aspect of the timber salvage 

effort, if called upona6 An elevenperson ad-hoc committee was designated 

by the Foresters' Council to present 

the plan to the Governor's Office, 

solicit input, and select Salvage 

Council members, 

On Friday, September 29, Jack Gould 

(SCFC), Bob Scott (SCFA), Bill 

Sullivan (SCFA), and Corky Lee (SC 

Forest Industries) met with Warran 

Tompkins, Chief of Staff to Governor 

Campbell, to request an Executive 

Order creating the Governor's Forest 

Disaster Salvage Council. For the 

next week (September 30 - October 6), 

the Commission continued intensive 

assessment of needs concerning aerial 

photography, FEM eligible expenses, a 

forest survey of damaged areas by the 

USFS Inventory Analysis Group 

(Asheville), truck weight concessions, 

railroad rate changes, specialized 

forest fire control needs, and basic 

reforestation planning. 

On Wednesday, October 4, Dean Carson 

(SCFC) contacted the offices of U.S. 

Senator Ernest Hollings and U.S. 

Senator Strom Thumond regarding Agricultural Conservation Program (ACP) and 

Forestry Incentives Program (FIP) 

special allocations, USFS in Atlanta 

advised SCFC of an invitation to provide a Congressional Briefing to 

legislative delegates in Washington, 

DC. Acting State Forester, Jack Gould, 

and salvage Council Chair, Scott 

Wallinger, appeared before the U.S. 

House of Representatives and the U.S. 

Senate for a briefing on the Forest 

Disaster and SCFC needs on Tuesday, 

October 10. They addressed Hugo's 

damage, salvage efforts, and wildfire 

implications, as well as the assistance 

needs of South Carolina's forest 

landowners. 

On Thursday, October 5, one week after 

the request, the Governor issued an 

Executive Order (89-45) creating the 

Governor's Forest Disaster Salvage 

Council. 

PART lBr GBVERNORFS FOREST 

DISASTER SALVAGE COUNCIL 

Members 

Governor Campbell's Executive Order 

established a governor-appointed 17- 

member Salvage Council consisting of 

representatives from the USFS (Don 

Eng), SCFA (Bob Scott), SCFC (Jack 

Gould), S.C. Society of Consulting 

Details of FEMAPs responsibilities 

and policy response to Hurricane Hugo 

can be found in : Marie Lynn Miranda. 

Coordinatinq Federal, State, and 

Private Sector Response to Natural 

Disasters: A Case Study of Hurricane 

Huqo, Sanford Institute of Public 

~olicy, February 1994, 

~estimon~ ofMac Lupold. Effects of 

Hurricane Nuqo on Forest Resources. 

Hearing before the Subcornittee on 

Forests, Family Farms, and Energy of 

the Committee on Agriculture. November 

6, 1989, Moncks Corner, SC. 

Allan P.C. Marsinko, Thomas J. 

Straka, and Jeffrey L. Baumann. 1993. 

"Hurricane Hugo's Effect on South 

Carolina: The Impact After Three 

Years" in Journal of Forestrv, 

September 1993, pp. 9-17. 

Minutes of the initial meeting of the 

Governor's Forest Disaster Salvage 

Council from Scott Wallinger. October 

6, 1989. 
Foresters (Dwight Stewart), Agricultural Stabilization and Conservation 

Service (Bryan Patrick), Governor's 

Office (Ralph Strong), S,C. DeparLanent 

of Agriculture (Leslie Tindal), S,C, 

State Senate (Hon, John Drmond and 

Hone John Courson), S,C, House of 

Representatives (Hon. Thomas Lbehouse 

and Hon, Woodrow McKay), Cl 

University Extension Service (Don 

Ham), and forest industry (Mtchell 

Scott, Collmrs Lumber Mill, Jim 

Baygreen, Georgia-Pacific Corp., Bill 

Sullivan, International Paper Company, 

Corky Lee, Stone Container Corp,, and 

Scott Wallinger, Westvaco, Timberlands 

Division,) 

Duties 

The Councilrs mandate included the 

following duties: 

* to make immediate determinations 

of all needs of the forest products industry; * to explore in detail all avenues 

of assistance; and * to make specific recommendations 

of the most efficient and effective procedures for realizing 

the greatest return on the 

ged resources, 

By the Council's second meeting on 

October 13, committees were organized 

and its mandate had been translated 

into more concrete responsibilities, 

including : 

1) Initiate an aggressive salvage 

effort. 

2) Broaden the base of markets for 

wood products, 

3) Expand logging and transportation, 

4) Promote wood products storage, 

5) Communicate salvage techniques 

and strategies. 

6) Remove regulatory hurdles impeding the salvage. 

7) Record and monitor salvage 

activities and results, 

8) Work within the antitrust laws, 

Funding 

SCFA provided $25,000 up front to 

facilitate the salvage operations. 

The Association was then reimbursed by 

a variety of sources, From that 

$25,000, an Executive Secretary was 

salaried; most others involved were 

volunteers, All office costs (printing, telephone, etc,) were absorbed by 

SCFC, Other than the $25,000 for the 

Executive Secretary's salary, no 

funding was glade available for the 

salvage effort. Eventually, the South 

Carolina Senate allocated approximately 

$10,000 to partially reimburse the 

SCFA, Later, another $12,000 was 

allocated by the S,C, House and Senate 

from discretionary fundsS7 

Structure 

On advice from the Forestry Commission, 

the Governor appginted Scott Wallinger 

(of Westvaco Corporation) Chair of the 

Salvage Council. Mac Lupold was 

appointed the full-time Executive 

Secretary for a provisional term of 90 

days (through December 1989) with 

continuation after that on a month-tomonth basis contingent upon need, 

availability, and funding; he remained 

in his paid position until June 1, 

1990, Lupoldrs salary was $375/day 

(gross), including all benefits and 

costs except travel, meals, lodging, 

and telephone. He operated from his 

home office in Holly Hill, with office 

space and support staff in Columbia 

provided by SCFC and SCFA, 

The Council was initially broken into 

five committees: Information, Utilization, Transportation, Environment, and 

Inspection. However, at the Executive 

Committee meeting on October 17, the 

proposed duties were reorganized under 

four committees: Public Information, 

Utilization, Government Affairs, and 

Statistics and Monitoring, Because the 

tasks for the Environment Committee 

were primarily technical and could be 

handled by other standing committees, 

the responsibilities of that committee 

were parceled out to other committees, 

primarily the Government Affairs Committee, The Transportation Committee 

became a subcommittee under Utilization, and the Inspection Committee 

changed its name to Statistics and 

Monitoring. The Chair of the Council, 

Executive Secretary, and the four 

Committee Chairs formed the Executive 

Committee, which was charged with 

keeping the Council updated on committee activities and facilitating action. 

At the Salvage Council's initial meeting, the members discussed committee 

responsibilities. By October 17, the 

committee responsibilities and chair 

persons were finalized as listed below. 

Governor's Forest Disaster Salvage 

Council, Briefing Book for the Economic Recovery Commission. 8 January 

1990. 
nt Affairs, Bob Scott (SCFA), 

Chair 

* Initiate, draft, and promote the 

adoption of state and federal 

legislation and/or regulations 

to enhance salvage operations 

and forest regeneration. 

Public Information, Don Ham (Clemson 

University Extension), Chair 

* Develop an information network 

to target timber landowners, 

foresters, buyers, processors, 

and the general public using 

press, print, and Educational 

Television (ETV), 

Utilization, Bill Sullivan (International Paper), Chair 

* Initiate an aggressive salvage 

program to reclaim as much 

downed timber as possible. * Promote an aggressive program of 

storage of salvaged logs and 

pulpwood under standing water or 

water spray, by individual companies and through collective 

storage facilities, to absorb 

one-third of the salvageable 

material. 

This committee was further divided 

into four subcommittees: 

Out-of-State Movement, Storage, 

Utilization, and Transportation. 

Statistics and Monitoring, Jack Gould 

(SCFC), Chair 

* Survey mill capacity for 

salvaged materials, * Determine weekly salvage 

remova 1. * Facilitate a USFS 24 county 

survey of the damaged area, * Establish county monitoring 

teams to report weekly salvage 

status. * Provide constant review of 

conditions in the field to 

ensure mxhm salvage, 

This committee was further divided 

into two subcommittees: 

Statistics and Monitoring 

PART 1C: ACTIONS OF SWAGE 

COUNCIL COMMITTEES~ 

Government Affairs C 

The Government Affairs Committee worked 

to initiate and encourage the development of state and federal legislation 

that would help fund the salvage operation and other aspects of the forest 

disaster relief efforts, The Executive 

Cornittee assisted the Goverment 

Affairs Committee in developing a longterm priority list of legislative 

proposals and in lobbying state and 

federal officials. 

Shortly after Hugo, with minimal lobbying effort by the Salvage Council, two 

non-legislative initiatives were 

enacted (one by Governor Campbell and 

one by the Department of Health and 

Environmental Control) aiding salvage 

operations almost immediately, By 

October 4, the governor issued an 

executive order allowing the Highway 

Department to increase the gross weight 

limits for log trucks from 80,000 to 

90,000 lbs. This increase was first 

granted for 60 days, until December 5, 

1989. At the request of the Council, 

Governor Campbell issued an extension 

er 5 for 60 additional days, 

And, again in January, he extended the 

executive order 60 more days until 

April 4. However, by early February, 

there was some sentiment that the truck 

weight limit was being abused and that 

small rural farm to market roads were 

being overused by logging trucks, On 

February 15, Captain Corbin of the 

Highway Patrol expressed concern to the 

Council about extending the 90,000 

pound weight limit, He cited a higher 

than normal violation pattern for 

trucks carrying excess weight, trucks 

violating the tree length requirement 

at night, roads being overused in some 

locations, and uninsured, underinsured, 

or unregistered salvage vehicles. 

Csrbin mphasized that the conditions 

must be improved immediately or the 

* This section of the report is based 

on information available from: "Hugo 

Timber Salvage Information," a weekly 

newsletter created and distributed by 

the South Carolina Governor's Forest 

Disaster Salvage Council from 13 

October 1989 to 1 June 1990. 
truck weight would not be extended 

past March 15, The Council warned 

loggers of the possible cancellation 

of the weight extension, However, the 

Governor chose to cancel the extension 

of the weight limit on March 15. 

A second state initiative, issued 

through the Department of Health and 

Enviromental Control, established a 

special wastewater permitting procedure, Short-term log storage and 

sprinkler operations were exempted 

from the usual permitting process, 

typically a six-month procedure, A 

workshop on notification andlor 

permitting for wet storage sites was 

held on January 16, Hills needed to: 

locate sites; describe sprinkler 

systems and the type of recirculation 

pond (if used); set a time frame; and 

communicate with DHEC in order to meet 

the April 6 deadline to operate prior 

to notification or permit, DHEC 

stated that logs cobld be stored 

before the mills notified DHEC, but 

plans had to be submitted within 30 

days; no logs could be stored on an 

unreported site after July 1. DHEC 

declared that a closed-loop recirculation system had to meet a 10-year, 24-hour rain capacity and only 

required notification (not permitting). Wet sites where sprinkled 

water was not collected required 

permits to operate and required a 

monthly water runoff sampling. The 

Council advised DHEC that pine sawlogs 

would probably be placed in wet 

storage as late as May and June for 

use in the wet months of December to 

March 1991. Hardwoods, they claimed, 

would be logged in the dry months of 

1990 to 1993 and stored with use the 

following winter months, 

The Executive Committee recommended 

that the Government Affairs Committee 

concentrate on the following legislative proposals, defined as the "1990 

Hugo Forest Disaster Relief Needs": 

STATE I) Income tax casualty 

loss (to recover 5 

to 6 percent of 

actual and lost 

timber value) ; 

2) Investment tax 

credits for reforestation costs; and 

3) Funding for Council 

expenses for 1989- 

1990 ($88,000), 

FEDERAL 1) $750,000 for Forest 

Resurvey ; 

2) $100millionfora 

reforestation cost 

sharing program; and 

3) Forest Crop Loss Bill 

(shilar to farm crop 

loss bills for 

freezes, droughts, 

hurricanes, etc,) 

At the state level, the Salvage Council 

lobbied for these proposals at a meeting of the House Agriculture Subcommiter 12, during which Bob 

Scott, Mac Lupld, and Jack Gould 

presented infomtion on Congressional 

Hugo legislation status, salvage progress, and the SCFC fire prevention, 

pre-suppression program. In addition, 

the S.C, Tax Commission proposed three 

more specific legislative tax incentives for private forest landowners: 

1) Property tax relief; 

2) Casualty tax provisions to 

allow a loss on SC tax 

returns in excess of basis; 

and 

3) Investmenttaxcredit for 

reforestation applied to SC 

taw returns, 

The Council, SCFC, and USFS conducted a 

tour for House Committee members on 

January 3 in the Moncks Corner area, 

They hoped an on-the-ground observation 

of the damage, salvage operations, and 

comments from landowners would assist 

in preparing relief legislation. 

In late January, Executive Committee 

Chair Scott Wallinger sought the 

Governor's support for a South Carolina 

casualty tax write-off provision, By 

early February, the Council detailed 

the casualty tax legislation's effects 

on the average forested landowner, 

Losses from Hugs totalled $1 billion on 

4 million acres of private t 

with an average loss of $250 

The average casualty tax write-off as 

determined by the terms of the proposed 

legislation would be $9.28 per acre. 

Using the average S,C. t 

90 (2) acres, the average tax credit 

would be $835.00, split into $167.00 

over five years, This proposed legislation did not include any provision 

for a timber basis, It was based on a 

75% casualty tax cap, and it used a 

5 112% tax rate (average for South 

Carolina), The Council encouraged 
landowners to maintain records of the 

salvage and to develop a photograph 

trail of forest damages for tax purposes in case pending legislation 

passed and a professional appraisal 

was necessary. 

Despite all the lobbying efforts, 

little progress was made in advancing 

any of these proposals through the 

South Carolina legislature. The 

casualty tax write-off provision and 

funding of the Salvage Councilfs 

operations were endorsed in the March 

report issued by the Governor's 

Economic Recovery Commission. The 

Economic Recovery Commission was 

charged with recommending how the 

governor should address the short-term 

and long-term needs of the state five 

months after Hurricane Hugo. The 

writers of the report argued that the 

casualty tax programfs estimated 

revenue losses of $6 million per year 

would be offset by federal reforestation program dollars estimated to 

total $5.5 million over five years. 

However, this endorsement failed to 

sway the South Carolina legislature. 

At the federal level, the Government 

Affairs Committee lobbied for $750,000 

to fund the USFS Forest Resurvey, $100 

million for reforestation cost sharing, and $280 million for a "Crop 

Loss" proposal. In addition, they 

provided information to a Congressional delegation on tax and financial 

assistance to landowners, 

The Government Affairs Committee's 

agenda for Hugo relief legislation was 

brought to the forefront after a 

public hearing of the House Subcommittee on Forests, Family Farms, and 

Energy in Moncks Corner, an area 

particularly hard hit by Hugo. The 

hearing, titled "Effects of Hurricane 

Hugo on Forest Resources" was 

requested by S.C. Congressperson 

Tallon, member of the House Agriculture Committee, in order for 

Congressional Representatives to "hear 

firsthand from the people most 

affected by the hurricane."' The 

meeting was attended by four subcomers (Volkmer, MS; Olin, VA; 

Harris, AL; and Herger, GA) as well as 

South Carolina representatives Tallon 

and Spratt and Senator Hollings, Jack 

Gould, Mac Lupold, Bill Sullivan, and 

Scott Wallinger all made statements. 

Lupold and Wallinger, on behalf of the 

Salvage Council, sought $30 million 

from FEHA or through special legislation for storage of logs, chips, and 

lumber and for logger assistance. 

Other testimony was presented by 

industry representatives, consultants 

and landowners, During the hearing, 

the U.S. Forest Service presented its 

proposed funding needs, totaling $243 

million. 

Rep. Volkmer, Chair of the Subcommittee 

commented, "It's obvious that the 

national news media never got to the 

woods to illustrate the tremendous loss 

to South Carolina's forest landowners. 

Your timber losses, salvage efforts, 

fire danger, and reforestation needs 

will be actively presented to the 

Congress. "'O Subsequent to the hearing, Tallon, Spratt, and Hollings 

cosponsored three of the several bills 

proposed in both the U.S. House and 

Senate to provide relief to forest 

landowners. 

The Government Affairs Committee worked 

with Senator Strom Thurmond to prepare 

the Hugo Forestry Restoration Act. In 

the House, Representative Tallon 

introduced a companion bill, the 

Hurricane Hugo Forestry Restoration 

Act. Thurmond's bill ($1728) would 

authorize $100 million in cost share 

assistance to landowners who wished to 

reestablish timber stands damaged by 

Hugo. Although the Salvage Council 

recommended a 90% cost share for landowners with 100 acres or less and 65% 

for those with more than 1000 acres, 

the bill provided 75% and 50% cost 

share ratios. This bill was immediately referred to the Senate Committee 

on Agriculture, Nutrition, and Forestry 

after being introduced on October 5 and 

never received any other action. The 

comwnents of Thurmondfs bill were 

evektually subsumed by the Hugo Relief 

Omnibus Bill. This bill, introduced by 

Senators Mitchell (Democratic ~ajorityLeader) and Dole (Republican Minority 

Leader), would have amended the Robert 

T. Stafford Disaster Relief and Emergency Assistance Act to deal specifically with recovery of losses by forest 

landowners. Besides providing $100 

Harold Volkmer, Representative. 

Opening statement at hearing of the 

House Subcommittee on Forests, Family 

Farms, and Energy Effects of Hurricane 

Huso on Forest Resources. Moncks 

Corner, SC, November 6, 1989. lo - Ibid. 
million in reforestation cost share 

assistance (Thu ndrs bill), the 

omnibus bill proposed three other 

measures : 

(I) A $200 million Forest Land Bank 

Program for Eaaergency Relief for 

Forest and Enviromentally Sensitive Areas, This set up a 

program for timberland owners 

similar to the Conservation 

Reserve Program offered to 

agricultural landowners, Timber 

landowners could receive compensation beyond the cost of 

salvage in order to insure 

reforestation, 

(2) $30 million for salvage operations. This proposal included 

$10 million for the Salvage 

council administrative costs, 

logger assistance, and storage 

costs, The other $20 million 

would provide loans to businesses involved with logging and 

storage, 

(3) $5,8milliontotheS.C. 

Forestry Commission for 

Additional Fire Suppression 

Equipment and Programs. 

This bill incorporated all three of 

the Salvage Council's legislative 

priorities, However, the Senate never 

took action on this Omnibus bill, 

Attempts to pass a separate scaled 

down bill for $50 million for site 

preparation and clean up also failed. 

SCFA's Bob Scott, chair of the Government Affairs Committee, said, "We 

missed a golden opportunity to get 

these bills passed. There was strong 

sentiment on our side. I don't think 

we'll have that same degree of concern 

when Congress reconvenes next year as 

there will be new concerns and different priorities. . It's going to 

require a better organized nationwide 

lobby effort to get the legislation 

approved next year , " l1 

Tax assistance legislation was also 

proposed in the House and Senate. 

Senator Hollings' and Representative 

Spratt's proposed legislation provided 

for deduction of business and investment losses, Their bills, both titled 

the Hurricane Hugo Tax Assistance Act 

(S.1748 and HR.3655), were referred to 

l1 Governor's Forest Disaster Salvage 

Council, "Hugo Timber Salvage 

Information," 1 December 1989. 

the Senate Finance Committee and the 

House Ways and Means Committee, respectively. Like the previous Hurricane 

Hugo relief measures, after these bills 

were referred to committees, all action 

on them stopped, Neither the Senate or 

the House approved the acts before 

Congress adjourned on November 22, 

In March, Executive Comittee Chair 

Scott met with ers and staff of the 

S,C, Congressional delegation to create 

a national lobbying effort for Hugo 

legislation. The campaign involved 

allied forestry and farm organizations, 

industry coalitions, and leaders of 

natural resource agencies. Over the 

next several months, legislation was 

enacted providing funds for reforestation and wildfire prevention efforts 

(detailed in Parts 2 and 3 of this 

report), although salvage efforts were 

overlooked. 

Public Information Committee 

The Public Information Committee 

prepared articles explaining the 

responsibilities of the Salvage Council 

and updating committee activities. 

The Committee's goal was to keep the 

public informed about the Hugo forest 

disaster and recovery efforts. They 

urged landowners to contact professional foresters for advice on 

salvaging downed timber, safety 

concerns, and the elevated wildfire 

hazard risk. 

The committee issued press releases, 

prepared flyers on logging, trucking, 

and hunter safety, and compiled information for landowners on conversion 

relationships (tons, cords, and MBF). 

Once or twice weekly, the Council 

published listings of "wants and needsw 

of loggers, landowners, consultants, 

buyers, and trade companies. By midOctober, the Clemson Extension Service 

agreed to provide a full-time writer 

for the Council's effort; in November, 

the Extension Service hired Julie 

Walters-Steele, 

The committee used television, videos, 

and educational television (ETV) in 

their efforts to keep the public and 

the forest community informed about the 

state of the relief efforts. At the 

request of the Council, ETV prepared a 

ten-minute salvage background feature, 

a "Crosstalk" special entitled "Hurricane Hugo's Effect on South Carolina's 

Forests," four public service announcements, several focus features, and a 

documentary of the salvage effort. 
The committee made several attempts to 

schedule Governor Campbell for a 

salvage tour in Sumter County. The 

media was invited to attend. The 

three woodland stops and bus commentary focused on the salvage status, 

the hardwood resource and hardwood 

salvage problems, forest rehabilitation, legislative issues, fuels 

mnagaent-, and the economic outlook 

for forestry. A March 2nd and 16th 

tour were postponed; eventually, the 

tour was held on April 25. 

Utilization Committee 

The conunittee formulated a reasonable 

salvage goal, In late November, seven 

weeks after the storm, the committee 

determined that the "at best" salvage 

goal was 25% by volume and 10% by 

value. That estimate considered low 

volume, inaccessible and unloggable 

areas, product change from pine 

sawtimber to pulpwood in the snapped 

trees, logging and millluser capacities, logging and transportation 

conditions, and time frames for each 

product use. 

The Transportation Subcommittee 

negotiated discounts with rai~r~ads 

for pulpwood and wood rack cars, 

distributed bumper stickers to 

identify trucks involved with Hugo 

salvage, and investigated the possibility of shipping wood out-of-state. 

The railroads responded to the committee's requests: both CSX and 

Norfolk-Southern offered rate 

reductions and various equipment 

alternatives. Santee-Cooper volunteered 45 to 50 of its aluminum coal 

cars (25 ton capacity) for free use 

for 15 to 20 weeks; those cars could 

be cleaned and used for chips until 

late spring. Stone released 250 

woodrack cars for use at Panama City 

and Norfolk-Southern made 300 woodrack 

cars available. By November 8, the 

subcommittee had located 3500 surplus 

woodrack cars from CSX Railroad. 

However, both CSX and Norfolk-Southern 

Railroads reported very few requests 

for equipment in the salvage effort in 

late November. The companies had 

surplus shortwood pulpwood racks, 

gondolas, and bulkhead flat cars, but 

few used them. In January, NorfolkSouthern extended its rate reduction 

until April 8 because bad weather in 

South Carolina had slowed down the 

salvage. 

The committee convinced the state to 

allow out-of-state loggers to work in 

South Carolina without fuel stickers 

or registrations. After the governor's 

original executive order increasing truck weight limits to 90,000 pounds 

from 80,000 pounds, the transportation 

subcommittee was instrumental in convincing the Governor to extend his 

executive order until January to 

increase salvage harvests. The 

transportation subcommittee encouraged 

the Governor to extend the weight 

allowance until at Peast June, but 

concerns of abuse of the limits 

resulted in the governor canceling the 

order on March 15. 

Transportation Subcommittee members 

contacted 64 State Forestry and Logging 

Associations to locate additional 

loggers. The subcommittee convinced 

the North Carolina Governor to accept 

South Carolina fuel stickers and 

registrations, and located available 

ocean-going barges for transportation 

of salvaged logs. 

The Storage Subcommittee needed to: 

project wet (underwater and sprinkler) 

and dry storage capacity; disseminate 

information on the technical data, 

design, and cost of wet storage 

options; and inventory locations for 

storing particular types of wood for a 

particular length of time. Wet storage 

delayed blue stain and insect attack, 

thus preserving the volume and value of 

timber that could not be utilized 

immediately, The committee projected 

that storage could protect timber from 

blue stain and insects for up to two 

years. 

The storage subcommittee had the difficult job of anticipating the need for 

wet storage facilities in the face of 

unpredictable logging conditions 

(slowed by rain) and, later, an 

unpredictable market. The committee 

was successful in identifying sites for 

wet storage. By November 13, the SCFC 

had offered to provide water-sprinkler 

storage areas for Hugo-damaged timber 

to those interested in establishing 

log-buying/storage areas. The 

available sites included a pond in 

Manchester State Forest and a seed 

orchard in Wedgefield, SC. The 

Forestry Commission also offered to 

assist with technical data on wet 

storage. By mid-December, over 30 wet 

storage sites had been established or 

would soon be available, with a 

capacity of 160 million board feet or 

20% of the salvage goal. In addition, 

the Land Resources Conservation 

Conunission (LRCC) stated that the use 

of an owner's pond was acceptable as a 
water source. Lakes within the 

Francis Marion National Forest were 

proposed as potential storage sites, 

but were not used because of concerns 

about the difficulty in retrieving 

wood from the lakes and impacts on 

water quality. l2 

Many of these storage sites went 

unused early on in the salvage 

efforts. Milling operations utilized 

the salvaged t er as fast as it was 

logged and were reluctant to store 

timber until it was absolutely necessary. Manufacturers to whom the milling operations were selling lumber do 

not like stored wood because it can be 

splotchy and stained, Not until 

February or March did some mills begin 

to consider using storage, By April, 

however, 139 million board feet of 

pine and 6 million board feet of hardwood sawtimber, worth $38 million, 

were in wet storage. Most logs were 

stored for only a few months, but in 

some instances, storage was used for 

over a year.13 Towards the end of the 

salvage effort, wood prices began to 

rise again; some companies, in hindsight, would have placed more logs in 

wet storage. 

During this time, Lupold, the Council's Executive Secretary, met with 

DHEC officials to discuss the technical aspects of wet storage. Industry 

officials also met to discuss the 

issue of wet storage and to obtain a 

time extension for temporary storage. 

The USFS conducted a research program 

on sampling log storage piles (from 

wet storage) every two months to monitor lumber quality. The Forest Service found that the quality of stored 

lumber was maintained for longer than 

they had anticipated. Clemson extension agents found that serious problems did not occur when "processing 

the sprinkled logs into lumber, 

veneer, and plywood, and no product 

degrade could be attributed to 

sprinkler tora age."'^ 

The committee considered storing chips 

left in the woods from salvage and 

fuel reduction operations to be 

recovered at a later date. The 

eomittee also found that mills were 

sawing wider 1 er than usual (2x8, 

2x10, and 2x12) because some salvaged 

trees had large diameters. The 

committee encouraged storage of this 

low volume product to protect its high 

market value, 

The Out-of-State )(o 

detemined that the 

manufacturing capacity in the ast 

that could use South Carolinap 

wood was favorable. 

volme of salvage matterial that 

actually left the state was lhited 

because there was a constant 

s and pulpwvlod within the state. 

tely, 90% sf the salvag 

was used in-statemZ5 

The Subcommittee found that the chipping capacity in South Carolina could 

be greatly increased by using 2nd and 

3rd shifts and by operating seven days 

a week, but there was no economical way 

to move chips from chipping sites to 

the pulp mills more quickly. Chip cars 

were in short supply. Members planned 

to contact pulp mills in the southeast 

for commitments. By October 20, two 

sawmills had diverted over 200 log cars 

and 65 new chip cars to the salvage 

effort. Gondolas were brought into the 

area for log movement. The subcommittee determined the needs of the pulp 

and paper mills for chips, shortwood, 

pulpwood, and hardwood, and found 

several mills in Virginia, North 

Carolina, Georgia, Florida, and Alabama 

that were low on inventory. They found 

that there were opportunities available 

for exported logs; the problem was 

finding an economical means of 

delivery. 

The Council worked with state ports to 

determine reasonable port unloading, 

storage, and ship loading charges. 

State ports were not comtnonly used for 

the export of wood and lumber products, 

This resulted in tariffs plus 

stevedoring charges at approximately 

l2 Steve Nodine, Clemson University 

Extension Forester, personal communication, 

Allan P. Marsinko, Thomas J. Straka, 

and Jeffrey L. Bamann. 1993. 

"~urricane- Hugo : A South Carolina 

Update" in Journal of Forestry, 

er 1993~9-17. 

Syme, John and J. R. Saucier, 1992, 

"Impact of Hugo T 

Primary Wood Manufacturers in South 

Carolina." U,S.D.A, Gen. Tech. Rep, 

SE-80. 28 p, lS Allan P. Marsinko, Thomas J. Straka, 

and Jeffrey L. Baumann. 1993. 

"Hurricane Hugo: A South Carolina 

Update" in I 
$135/MBF, making log exports prohibitively expensive. 

The subcommittee presented its salvage 

program to the Southeastern Technical 

Comittee of pulp and paper procurement personnel of the American Pulpiation on Nov 

er, there was 

state movement due to wet logging 

conditions. In-state consmption, 

however, matched the logging effort, 

The heavy rains after the hurricane 

prevented loggers from starting the 

salvage for several weeks. During 

this time, the Utili~ation Subcornmittee distributed publications on 

logging safety, coordinated the Wildlife Department for hunter safety and 

use of rifles, refined a list of wood 

users for mailings, and began to 

address fire concerns for when the 

tops of downed trees dried out. After 

the weather cleared up and logging 

began, it urged landowners with standing timber to keep it off the market 

so that damaged material could be used 

first. The subcommittee contacted 38 

pulp and paper mills and 75 sawmills 

out-of-state by phone or letter to ask 

them to use Hugo-damaged wood. The 

committee convinced the Governorus 

Office to contact railroad CEOs and 49 

pulp and paper CEOs to ask for their 

help and cooperation, By October 27, 

the subcommittee found that hardwood 

stands were often in low-lying, wet 

areas preventing logging operations, 

but pine sawtimber stands were dryer, 

and as long as the rains held off, 

were logged. 

The Committee served as an information 

clearinghouse providing forest landowners with information on available 

loggers and equipment. By November 

13, the subcommittee had contacted 37 

of 65 logger and forestry associations 

throughout the U,S, and Canada about 

South Carolina's need for loggers and 

had begun an inventory of South 

Carolina logging capacity, number of 

crews involved, and out-of-state input 

in the logging effort, A meeting in 

er revealed mixed opinions 

about the need for loggers; since some 

still had a need, the Council continued to locate out-of-state loggers, 

The Comittee initiated many small 

projects to facilitate salvage. They 

provided 500 road signs advising "Hugo 

Logging Ahead". They issued a statement urging caution at sawmills 

because of the danger associated with 

compression breaks. More heavy rains 

er caused all logging operations on the Francis Marion to close. 

By that point, most higher-elevation 

sites (where flooding was not a 

problem) had been logged, 

The comittee found that professional 

foresters handling logging sales were 

selling logs at 50 to 75% of pre-Hugo 

prices depending on the damage to the 

stand. The comittee compiled over 200 

notices of needs and capabilities to 

list in the "Classified Ads," an 

attachment sent out to over 500 

businesses with the "T 

Information" newsletter. 

Statistics and Monitoring 

committee 

The Statistics and Monitoring Committee 

developed salvage response forms, had 

them reviewed by industry representatives, and mailed them to over 250 wood 

processing companies in South Carolina, 

North Carolina, and Georgia by October 

20. These surveys were designed to 

determine production capacity, wet 

storage plans, and weekly consumption 

of salvaged wood. The Statistics 

Subcomittee received weekly reports 

from mills accepting primary forest 

products from the salvage. It then 

gave those numbers to the SCFC, which 

compiled the information for weekly 

progress reports; the progress reports 

were attached to the "Timber Salvage 

Information" weekly newsletter and 

distributed to over 500 people. The 

subcommittee also helped organize and 

report results form the U.S, Forest 

Service Resurvey of the 24 disaster 

counties. 

er 20, the Monitoring Subcornrnittes had received these comments from 

the field about the salvage: 

Number 

1) can't sell wood 7 1 

2) unsatisfactory price 49 

3) poor logging conditions 28 

4) tight quotas 22 

5) not enough loggers 20 

6) USFS flooding market 4 

7) free wood 3 

The Monitoring Subcommittee also 

learned that there was some need for 

more shortwood products and markets, 

loggers tended to prefer clearcutting 

salvage areas, and owners of small 

tracts were having difficulty finding 

buyers for their downed t 
Executive C 

The Council's Committee met 

weekly. They published a weekly "Timber Salvage Info tion" newsletter, 

which was distributed to over 500 

ers of the forestry commu 

The newsletter contained info 

on comnaittee progress, report 

vage status, and listed "classified 

ads" to match needs with availability 

of loggers and uipent. The c 

tee reviewed t r sale procedures 

for the Franci rion National Forest 

and other timber salvage alternatives. 

They listened to c 

Governor's Office, 

gress, private landowners, and consulting foresters on the economic effect 

that Forest Service sales would have 

on stumpage prices, availability of 

loggers, and local wood processing 

capacity. The committee also discussed the proposed forest survey and 

specific committee tasks. 

By October 20, at the suggestion of 

the Executive Committee, Council Chair 

Scott Wallinger contacted George 

Leonard, Associate Chief of USFS to 

discuss the economic impact that a 

large volume of pine sawtimber might 

have on the existing Hugo area manufacturing capacity over the next 

several months, Wallinger urged the 

USFS to release factual data on their 

current sales procedures to counteract 

various rumors that they would flood 

the market with National Forest timber. He suggested three alternatives: 

1) minimize the short-term volume 

available to wood-using facilities; 2) 

install major wet storage sites 

throughout the forest for mill 

consumption in one to two years; and 

3) secure loggers from outside the 

Hugo area. Wallinger assured the USFS 

that the Council would be willing to 

assist in any way possible in securing 

storage funds, environmental compliance, loggers, and wet storage 

technology. 

Don Eng, USFS Supervisor, provided an 

update on the timber sales procedures 

and status, He stated that the 

Francis Marion had 70% of its mature 

pine trees on the ground and that no 

live trees over a 45 degree angle 

would be cut. Since the Council's 

involvement in the UsFS salvage 

effort, Eng said, positive steps were 

taken by the Forest Service at the 

national, regional, and local levels 

to lessen the impact on the local 

forest economy. For example, the 

Forest Service was considering the 

following actions: storing 40 to 50 

million board feet of wet log storage 

in the forest, additional wet storage 

by buyers at their mills, using whole 

tree chipper operations with chip piles 

left in storage for later removal, and 

using loggers from other national 

forest areas. The Forest Service 

pursued all of these options except wet 

storage within the National Forest. 

At an October 26 meeting of the Salvage 

Council, the Council endorsed the 

iate need for a USFS resurvey of 

the 24 county area to determine the 

mortality due to Hugo by ownership 

class, species, and age class, The 

estimated cost of the survey was 

$750,000; efforts to secure federal 

funding were pursued by the Executive 

Committee and Government Affairs 

Committee. After many unsuccessful 

attempts at securing funds from FEMA 

and through President Bush's discretionary funds, the Council eventually 

obtained $750,000 for survey work by 

the Forest Inventory Analysis (FIA) 

research unit at the Southeastern 

Forest Experiment Station. 

FIA began the survey on February 20th 

and eventually surveyed 2,530 forest 

plots in 23 counties. Noel Cost, 

Project Leader of FIA, prepared status 

reports published bi-weekly with the 

"Timber Salvage Information" newsletter. The Council requested that two 

interim reports be prepared first on 

the heavily damaged and moderately 

damaged counties. The first report 

appeared in the March 2 edition of the 

newsletter documenting progress as of 

February 23. The crews had visited 77 

plots in a severely damaged five county 

area (Charleston, Sumter, Lee, 

Clarendon, and Berkeley counties) and 

found 59% of the total pine volume and 

65% of the total hardwood volume was 

damaged. By this date, only 5 of the 

77 plots visited had any salvage cutting activity. The March 2 newsletter 

reported that a total of 292 plots had 

been examined, and less than one 

percent had experienced any salvage 

harvest activity. 

The Executive Committee was a coinitiator of many of the Council's funding 

and legislative proposals, The 

Executive Committee arranged meetings 

during November among the Council, SC 

Forestry Commission, and the Federal 

Emergency Management Agency (FEMA) 

officials to request money from FEMA 

for additional fire suppression equipment and programs. The Executive 
codttee also initiated the effort to 

secure loan money (by FEW& or special 

legislation) for storage loans (for 

logs, chips, and er ) , logger 

assistance, and a istrative costs 

of the Council, Although the loan 

program never passed 

e MitchelllDole 

eventually provi 

tion funds totalling $e04 million, 

er 23, the Executive Committee was considering options for 

longer-term alternatives for the 

salvaged wood, The weather was good, 

and if it continued, the alternatives 

included t 

1) Establishwet log storage inthe 

woods and at mills, 

2) Contact companies about export 

potential, 

3) Set up shortwood operations at 

rail sidings to utilize surplus 

woodrack cars. 

4) Contact out-of-state pulp and 

paper companies to release some 

chip cars for the Hugo effort. 

5) Adapt woodracks, lumber flats, 

and gondolas (all in surplus) 

for moving logs by sail, 

6) Investigate barge movement of 

logs and chips. 

7) Try chipping in woods for later 

recovery, 

Executive Secretary Mac Lupold presented the Council's program to 

various groups throughout the salvage 

effort to solicit their help, He 

asked the S.C, State Development Board 

to assist with rail loading and wet 

storage sites and the American Pulpwood Association to encourage procurement personnel to receive wood out-ofstate, to free up some chip cars to 

South Carolina for 6 to 10 months, and 

to accept shortwoodo He asked Timber 

Products Inspection to convey the 

importance of pine sawlog utilization 

in the salvage effort, and the Agricultural Communications Center at 

Clanson' Extension Service to 

encourage Clemsonfs role through 

targeted communications, 

In late January, the Council presented 

12 recornendations to the Governor's 

Economic Recovery Commission (see 

Appendix). The recornendations 

included all the state and federal 

legislative proposals on the Council's 

(Government Affairs Committee and 

Executive Committee) agenda as well as 

additional reforestation programs, 

fire prevention, property tax and 

capital gains tax provision, Eight of 

the twelve proposals were endorsed by 

the Governor's Economic Recovery 

Comission in their March 26 report, 

On May 2, the Executive Cornittee met 

to review the Councilfs activities and 

needs related to salvage, fire control, 

and reforestation, The committee 

agreed that the salvage effort had made 

sufficient progress so that daily 

responsibilities should shift back to 

the normal state agencies. Thus, the 

Council recommended that the duties be 

distributed as follows: 

Responsibility Orqanization 

Salvage Volume Reportinq SCFC 

~e~islative ~atteks - 

Reforestation 

FEW Fire Prevention 

Log Storage 

Utilization, Loggers, User 

Listings, Wet Storage 

Forest Survey 

Council Reports 

Casualty Tax Questions 

SCFA 

SCFC 

SCFC 

DHEC 

SCFC 

USFS 

SCFC 

Clemson 

With the support of Governor Campbell, 

the Council remained intact to support 

longer range programs for fire suppression and reforestation, On June 1, Mac 

Lupold completed his paid position as 

Council Executive Secretary; he continued to serve as a member of the Executive Cornittee. SCFC continued to 

collect and analyze salvage data. 

A ~eforestation Committee was 

established in mid-December to address 

reforestation concerns. It worked with 

the Salvage Council although it was not 

part of the Council; its mission was 

much more longterm in nature compared 

to the Salvage Council's, The work of 

the Reforestation Committee and the 

entire reforestation effort will be 

covered in Part 3 of this report. 

PART ID: OTHER POLICIES 

In early November, FEMA joined a multiagency planning group to develop a Hugo 

area fire plan and to discuss salvage 

alternatives that might qualify for 

federal funds. The Interagency Hugo 

Hazard Reduction Planning Team consisted of the SCFC, USDA Forest Service, FEMA, and the Governor's Forest 

Disaster Salvage Council and met in 

Columbia for a week in mid-November to 

create a mitigation plan that considered fire prevention, fuels management, 

fire suppression, and timber salvage. 

Section 421 (d) of the FEMA enabling 

legislation, the Stafford Act, granted 

funds to states for timber salvage when 
salvaging costs exceed the value 

received for the timber, Although 

this was used mainly to assist in 

wildfire hazard reduction, it also 

aided reforestation by reducing site 

preparation costs, 

The Farmers Home Abinistration ( 1 

wade loans to forest landowners after 

Hugo, The Business and Industrial 

(B&I) Loan Program through DARBE 

(Disaster Assistance for Rural Business Enterprises) used existing private sources to provide guarantees of 

up to 90% of unpaid principal or up to 

$2.5 million. These loans were made 

specifically to businesses that were 

directly or indirectly affected by 

adverse weather conditions in 1988 or 

1989. Interest rates were negotiated 

between lender and borrower, Tree 

farmers, either individually or collectively, could obtain a 4% disaster 

loan if they obtained the loan for 

storage of their own logs, paid the 

logger, and either stored the logs 

themselves or contracted with a mill 

to store the logs until the product 

was used. Ten B&I loans were made to 

private businesses providing over $13 

million. l6 

By February 2, the Soil Conservation 

Service (SCS) determined that $34 

million was needed for debris removal 

on woodland watercourses, The Council 

recommended to the Economic Recovery 

Commission that the debris removal 

begin as soon as possible to improve 

logging and site preparation conditions, Phase I, October to December 

1989, cleared 210 miles and was funded 

by $3.9 million from SCS's 1990 

appropriations. Phase 11, February to 

mid-March 1990, cleared an additional 

461 miles, funded by $12.5 million 

from the President's discretionary 

fund, On March 14, SCS issued a 

Congressional Update listing remaining 

needs as $36,702,872 to clear 1,502 

more miles of clogged woodland 

watercourses. 

PART 1E: SWAGE RESULTS 

The destruction in the wake of Hugo 

challenged traditional mechanized - 

logging techniques, During the 

salvage operation, crews supplemented 

conventional logging methods by using 

wide-tired skidders, helicopters, 

chain saws, cable systems, and animal 

logging. The quantity of downed 

timber combined with wet conditions 

resulted in twice the normal timber 

harvest time.17 

After ten week. of logging, only 8.3% 

of the salvage goal had been achieved, 

If salvage progressed at this rate, 

only 50% of the -25% by volume" goal 

was attainable after one year, To 

reach the goal of 750 MBF of pine 

r by June, the weekly salvage 

rate needed to be 20 to 25 MBF per 

week. In fact, only four of the 

previous 18 weeks reached pine sawtimber salvage volumes greater than 20 

NBF, with an overall average of about 

17 MBF. Pine sawtimber (and pulpwood) salvage did eventually increase. 

Rain kept loggers from working in the 

wetter hardwood forest stands, while 

pine stands were on dryer land, Economics also served as an incentive to 

focus on pine salvage; pine sawtimber 

comprised 80% of the estimated salvage 

value to landowners. By the end of 

June, the pine sawtimber goal was 99.6% 

complete, while hardwood sawtimber 

salvage had only reached 10% of its 

goal. 

The upland counties, Calhoun, 

Fairfield, Kershaw, Lancaster, and 

York, had 20% or more damaged volume 

salvaged as of mid-March, The two 

worst-hit and wettest counties, 

Berkeley and Charleston, had a salvage 

rate of only 4 to 5%. Counties with 

scattered damage in the Pee Dee area 

(Darlington, Dillon, Florence, Horry, 

Marion, and Marlboro) also reported 

less than 5% salvage, 

Weather was a siqnificant factor influencing salvage operations. Heavy rain 

during the months of November and 

December slowed salvage logging, 

especially for hardwoods. By as late 

as May and June, saturated, wet soils 

still prevented loggers from getting to 

areas with 10-20 MBF per acre,lg At 

the same time, the wet weather and cool 

l6 Connally Bradley, Community and 

Business Programs Specialist, personal 

communication, October 1992, l7 Mac Lupold, Salvage Council Executive Secretary, Personal interview, 

July 1992. l8 Governor's Forest Disaster Salvage 

Council. "Hugo Timber Salvage Information Newslettern, December 1989, l9 Lupold, Mac. *Salvage of Storm 

~axnaged Timber" in ~urricane Huqo: 

Recoverins from Disasters, Proceedings 

of the 72nd Annual Meeting and Regional 

Technical Conference, ~anuary 20-22, 

1993, Appalachian Society of American 

Foresters, 
temperatures minimized insect damage 

and kept bark tight on the wood, 

delaying bluestain. However, by March 

1990, bluestain was advanced by the 

onset of 85 degree weather. High heat 

in the spring also shortened the pine 

salvage period because pines died more 

quickly than hardwoods, 

As of March 16, 217 million board feet 

were sold from the Francis Marion 

National Forest, Less than 100 million board feet had been cut by midMarch. Stumpage price varied from 

approximately $12 per MBF for helicopter sales to more than $100 per MBF 

for easily accessible areas. 

Sixty-two percent of the original 

salvage goal (25% of damaged timber) 

was met by November 1990, This figure 

is a bit misleading because the salvage emphasis was so unevenly split 

between softwood and hardwood. The 

softwood goal was met (sawtimber - 

99.64% of goal met; pulpwood - 106,65% 

of goal met). But for hardwood, only 

10-15 percent of the goal was met 

(10.38% of sawtimber goal and 15.16% 

of pulpwood goal), For comparison 

purposes, South Carolina salvaged two 

times the entire loss of timber following Hurricane Camille in 1969. 

The decision of the USFS not to allow 

wet storage in Lake Marion and Lake 

Moultrie within the Francis Marion 

National Forest has been criticized as 

contributing to a premature end to the 

salvage efforte20 Without storage 

sites in the National Forest, mills 

filled up quickly, and, with slower 

movement of logs and timber, loggers 

were discouraged from coming to the 

area , 

Table 2 lists the percent of forest 

land area affected and the percent of 

volume salvaged by ownership class, 

Although 66.4% of the damaged forest 

acres were non-industrial private 

forest (NIPF) lands, only 47% of the 

timber volume salvaged occurred on NIFF 

lands, Though the USFS and industry 

made an effort not to absorb all the 

loggers, some landowners had a hard 

time getting their land logged. In 

addition, salvage rates among NIPF 

lands varied, Some landowners who had 

a previous association with a consulting forester or were participants in a 

cooperative forest management program 

with forest industry were "hooked into 

the system" and had a better chance of 

finding a logger. With loggers in 

short supply (one person estimated 60 

to 70% more loggers were needed2'), 

many landowners--especially those with 

small tracts, were unable to salvage 

their downed timber. 

The uneven participation of private 

nonindustrial landowners in salvage 

efforts may be due in part to inadequate communication, Communication 

efforts failed to convey a sense of 

urgency (damaged timber was a perishable product); this part of the policy 

response also lacked a clearly laid out 

media campaign. Shortly after Hugo, 

the Salvage Council, SCFC, and SCFA 

handed over the duties of educating 

forest landowners and encouraging 

salvage (and reforestation) to Clemson 

Table 2: Percent of damaged forest land and percent salvaged by ownership class.22 

% of Damaged % of Salvaged 

Acres Damaged Acres ~cres' 

Nonindustrial Private Landowner 2,995,604 

Forest Industry 1,092,775 

Publicly Owned Land 420,358 

' Does not equal 100% because 22% of salvaged timber was reported as coming from an 

unknown source, 

20 John Syme, Clemson University Cooperative Extension. Personal interview, May 

1992. 

Mac Lupold. Personal interview, July 1992. 22 Governor's Forest Disaster Salvage Council Statistics and Monitoring Committee 

Progress Report, 1 November 1990. 
University's Cooperative Extension 

on had traditional 

expertise in extension education and 

was thought to possess a mechanism for 

rapid comunication. Also, SCFC was 

devoting its efforts to fire prevention and mitigationz3 and SCFA ot 

have the means to network." n 

approached the comunication 

utilizing existing mailing lists and by 

nars encouraging landowners to use 

essional consulting foresters, 

The mailing lists, however, were not 

current, and the sdnars were few in 

n r. The location of Cleaaaon in 

the western part of the state made 

some question if extension agents 

could comprehend the consequences of 

the disaster on landowners without 

having shared their experience. For 

future disasters, bfac Lupold recommends more seminars; more in-field, 

show-me training; more direct meetings 

with landowners; and a greater 

emphasis on long-term education. 

Though there was a glut in the market 

for pinewood, small hardwood operations still needed logs. Owners and 

procurement personnel with small 

independent 1 to 2 species hardwood 

operations for 8 to 12 loads per week 

complained about a lack of available 

logs. All of the plants had a strong 

order file, but they were receiving no 

logs. Hardwood salvage picked up 

toward the end of May/June. 

After the salvage operation was complete, the hurricane's potentially 

devastating effect on the people 

dependent on the longterm health of 

the forest sector began to be as 

apparent as the damage to the forest 

itself. Many small loggers who relied 

on buying timber from private landowners went out of business. These 

loggers had a limited range of operation, and little sophisticated equipment. Small loggers who worked on 

contract for forestry companies 

(Georgia-Pacific, International Paper, 

or Westvaco) fared better and were 

able to stay in business.25 

During the salvage, most mills used 

all the raw material they could get, 

and, in many cases, increased their 

operating hours. Once the salvage was 

over, a supply squeeze closed down 

many mills. The impact on mills 

depended on their size, location, and 

the extent to which they required 

er for operations, Forty-three 

mills are located in the Hugo-affected 

areaO2' Some sawtimber mills found 

their buying radius of 50-75 miles to 

include only Hugo-d ged area, By 

March of 1992, many these small or 

medium sized mills had already closed, 

others were expected to foll 

Those on the border of the d 

(such as plants in Walterboro and 

Umplett) were forced to look for timber 

sources in Georgia or other areas of 

the stateO2* Pulpwood operations that 

survived the supply crunch either: 

prior to Hugo, routinely received 

pulpwood from upland areas in the 

northwest portion of the state; or were 

large milling operations with 

diversified operations and/or the 

capital to modify operations to use 

more pulpwood. 

A few processors whose land was not 

damaged and who were close enough to 

purchase salvaged timber actually 

received some short-term benefit from 

Hugo. Purchasing salvaged timber at 

depressed prices assured higher future 

prices for their own timber once the 

salvage timber supply ran out.29 

PART IF: CONCLUSIONS 

South Carolina forestry agency personnel, state official^, and landowners 

lacked any means to prevent hurricane 

destruction to the forest resource. 

Their response instead needed to focus 

on preventing further forest catastrophes, protecting lives and surrounding property, and reducing financial 

losses of forest landowners. South 

Carolina's response to these challenges 

provides some useful lessons for future 

recovery programs aimed at forest 

disasters, Some important lessons are 

outlined below. 

23 Mac Lupold, Salvage Council 

Executive Secretary. Personal 

interview, July 1992. 24 Robert Scott, SC Forestry 

Association, Personal interview, May 

1992. 

25 John Howard, Forester, South 

Carolina Forestry Commission, 

interview, 27 May 1992, 26 Allan P.C. Narsinko, Thomas J. 

Straka, and Jeffrey L, Baumann. 1993, 

"Hurricane Hugo's Effect on South 

Carolina: The Impact After Three 

Years" in ~ournal- of Forestry, 

September 1993, pp. 9-17, 27 - Ibid. 28 John Syme, Clemson University, - - 

Personal communication, 28 l4aY-1992. 29 Ibid. 
All organizations involved in the 

forest recovery efforts, the SCFC, the 

Forester's Council, SCFA, and the 

state forester, were prepared for 

iate action. The SCFC quickly 

organized to send personnel and 

equipment to d ged areas. They assisted the state" sergency 

Preparedness Division in clearing 

road@ and restoring comunica$ion 

lines. The state forester, Jack 

Gould, quickly brought together the 

SCFC, the Forester's Council, and the 

SCFA to design a forestry emergency 

plan that proposed creating the 

Governor's Forest Disaster Salvage 

Council. By exercising such a well 

coordinated response, the forestry 

organizations facilitated: (1) the 

initial steps of forest recovery; (2) 

material and personnel support for 

other aspects of post-Hugo recovery; 

and (3) the governor's ability to stay informed and rely on advice concerning 

actions to aid in salvage efforts. 

The technical solutions required to 

harvest hurricane-damaged timber provide many useful lessons. By using 

diverse and innovative harvesting 

techniques, loggers working in South 

Carolina overcame some problems with 

inaccessible damaged timber. Developing wet storage techniques was crucial 

to preserve timber for future markets. 

The biggest technical constraint on 

harvesting was weather. Initially, 

unusually rainy weather in the fall of 

1989 left lowland sites waterlogged 

and unharvestable. Later, hot spring 

days encouraged fungus growth and 

death in many damaged pine trees. 

Landowners had a limited window of 

opportunity to salvage their damaged 

timber. Salvage became unfeasible 

once timber was further damaged by 

fungus, blue stain, and insect infestation. The onset of insect and 

fungal damage after Hugo was slowed by 

the cooler, unusually rainy weather in 

the fall and winter. The rain also, 

however, left some soils too wet 

throughout the winter to handle 

logging equipment. Salvage operations 

were then cut short with an early 

start to warm weather in the spring. 

This short optimal period for salvaging coincided with the time when 

landowners were most preoccupied with 

other damage to their houses and 

personal property. As a consequence, 

of the 1.33 billion cubic feet of 

damaged timber on NIPF land, the 

percentage salvaged totalled only 9%. 

Unlike damage losses to homes, cars, 

or other personal property, timber loss 

is uninsurable. State policy makers 

and forestry personnel need to design 

policies that take maxhm advantage of 

the limited window of salvage 

opportunity. 

The Salvage Council successfully balanced a couple of competing objectives. 

Primarily, they were interested in 

mxbizing the amount of timber salvaged and recovering as much value of 

the damaged resource as possible. 

However, they also needed to consider 

the source of the salvaged timber. 

South Carolina's forest industry and 

Francis Marion National Forest were 

more able than non-industrial private 

forest landowners to secure loggers, 

provide equipment, and find buyers for 

their timber. In respon$e, salvage 

Council and Francis Marion National 

Forest personnel cooperated to help 

private landowners salvage their 

timber. They attempted to recruit as 

many out-of-state loggers as possible 

and find out-of-state markets for 

salvaged timber. 

Dispersing information and developing 

educational materials was immediately 

important to let landowners know how to 

avoid further forest disasters and 

their range of options. Landowners 

were contacted through mailings. While 

NIPF landowners had 66% of the damaged 

land, their land accounted for 47% of 

total salvaged acreage. At the same 

time, salvage operations on Francis 

Marion National Forest were not 

hindered from reaching the goal of 

salvaging up to one third of the area's 

damaged timber. 

The priority given to funding salvage 

efforts was very low. Funding for 

salvage on private land was never made 

available at either the s t a t e o r 

federal level. State funds were in 

demand by many other sectors and 

federal funds were stretched between 

South Carolina and California after the 

Loma Prieta earthquake in October. 

Compared to other aspects of hurricane 

recovery--rebuilding homes, providing 

food, clothing, and water, and ensuring 

health and sanitation--salvage lacked 

any dramatic appeal to prevent human 

suffering. State forestry agencies attempting to secure federal assistance 

in the early aftermath of recovery 

might have been more successful by 

describing forest damage in terms of 

its effects on the thousands of small 

landowners who rely on their land as 

their "nest-egg" and by drawing the 
clear link between unsalvaged downed 

ildfire hazards. To 

involvenrent , state 

governments will have to lobby for 

revision of the Stafford Act. 

No state or federal legislative precedents were set providing disaster 

relief for forest landowners. The 

Salvage Council made proposals for 

legislation at the state and federal 

level modeled after tax relief and 

crop loss provisions for agricultural 

crop farmers, but none were passed. 

Essentially, forests remained an 

uninsurable asset. The Council was 

more successful in putting its energy 

into pursuing cost-share assistance 

for reforestation--a more traditional 

federal role in forest legislation, 

Monitoring gave crucial information to 

forestry personnel throughout the 

state on the status of the salvage 

operation. Monitoring created the 

capacity for the Salvage Council and 

other forestry personnel to make 

changes in the salvage operation as 

needs arose. For instance, salvage 

operations on the Francis Marion 

National Forest were regulated so as 

not to flood the market with damaged 

timber. However, monitoring did not 

always facilitate needed changes in 

the salvage operation. Some reasons 

for this are not easily solvable, such 

as the difficulty of predicting future 

prices, demand, and supply of timber. 

For instance, it became apparent late 

in the salvage operations that more 

wood could have been stored in earlier 

stages to take advantage of price 

increases later on. 

Forest recovery efforts continued well 

beyond the time salvaging ended in 

June 1990. Although salvaging was a 

short-ten effort, this does not 

diminish its importance; salvaging 

facilitated subsequent efforts to 

reduce the risk of wildfire and to 

promote reforestation, Salvaged 

forest land reduced the amount of fuel 

created by downed and damaged timber. 

Salvaging also was an important first 

step to prepare sites for artificial 

regeneration. 

PART 2: WILDFIRE: HAZARD 

REDUCTION AND MITIGATION 

The 2,3 million acres of timber 

damaged by Hurricane Hugo in South 

Carolina caused a tremendous shortterm salvage problem, and sparked 

major concerns about long-term fire 

hazards in the state. South Carolina 

boasts over 12 million acres of forestland. Hugo moderately or severely 

ged =re than 2.3 million of those 

acres, the largest timber blowdown area 

caused by a natural disaster in the 

United States. Massive mounts of fuel 

litter still r in on the ground (50% 

southern pine and 50% hardwoods), 

creating the potential for uneontrollabls wildfire. Since less than 25% of 

the downed timber was salvaged, the 

remaining acres of twisted trees 

created a dramatic increase in the 

probability of catastrophic wildfires. 

The elevated fire risk will likely last 

for five to ten years after the disaster, until the crowns of regenerated 

stands shade the debris. At that 

point, the temperatures will decrease 

and the humidity will increase, allowing the downed timber to decompose more 

rapidly. 

The Hurricane Hugo Wildfire Hazard 

Reduction and Mitigation Plan (Phase I 

and 11), developed by a State and 

Federal Interagency Planning Team, 

outlined policies designed to address 

the fire danger. This part of the 

evaluation of the post-hugo forest 

recovery programs Posks at the Wildfire 

Hazard Mitigation Program in two sections. The sections cover Phase I and 

Phase I1 of the program. For each we 

discuss: the coordination among the 

federal, state, and local efforts; 

organizational structure; sources of 

funding; program goals and the plan to 

fulfill these goals; and, the results 

of each Phase. 

PART 2A: WXLDFIM HAZARD 

RlEDUCTION AND MITIGATION PLAN: 

PHASE 

In response to the elevated threat of 

serious wildfire, a State and Federal 

Interagency Hazard Mitigation Team was 

formed to create a plan to reduce the 

30 Information in this section based 

on: 

1) Interagency Planning Team. 

~urricane ~uqo wildfire ~azard 

Reduction and Mitiqation Plan. 

November 1989. 

2) Interagency Planning Team. 

~urricane HUGO ~ildf ire ~azard 

Reduction and -Mitisation Plan: Phase 

- 11, June 1990. 

3) Progress reports for the 

Hurricane Hugo Wildfire Hazard 

Reduction and Mitigation Project. 

3120190-6/15/92, 
SOUTH ZONE h I Joint 

COORDINATOR 

I I 

Foredry Specialist 

Equipment 

- Charlestan Co. 

Teams 

- Foresfry Specialist 

Berkeley Co. 

Air 

Tankers 

LL Forestry Specialist 

Dorchester Co. 

Suppression ___ Forestry Specialist 

Personnel 

- Williamsburg Co L L 

Foredry Specialist 

Uarendon Co. 

NORTH ZONE 

COORDINATOR 

I I 

Equipment 

( Forestry Specialist 

1 Lee Co. 

Air I 

Forestry Specialist 

Lancaster Co. 

Suppression 

Kershaw Co. Personnel 

Figure 1--Organizational structure of personnel implementing the Wildfire Hazard 

Reduction and Mitigation Plan, Phase I. NOTE: * positions funded by South 

Carolina Forestry Commission. 
danger, The Team consisted of representatives from the South Carolina 

Forestry Conamission (SCFC), the 

Governorrs Forest Disaster Salvage 

Council, the U,S, Forest Service 

(USFS), and the Federal Emergency 

Nanagement Agency (F ) The group 

developed the Wildfire Hazard Reduction and Mitigation Plan, including 

goals for fuels =nag-ant, fire 

ression, fire prevention, and 

er salvage, No current or former 

program existed in South Carolina or 

elsewhere to serve as a model, South 

Carolina's plan was the first state 

level, post-disaster fire mitigation 

program of its kind. 

Federal and State Programs 

The Plan integrated federal, state, 

and local resources and progr 

a single comprehensive wildfire 

prevention and suppression program, 

FEMA, under the Stafford Act, is 

authorized to assist state and local 

governments by performing work and 

services to save lives and protect 

property, These services include 

debris removal from public and private 

property, clearance of roads, and 

warning the public of further risks 

and hazards. In addition, FEMa may 

provide grants to state and local 

governments to reduce the risk of 

future damage, to suppress wildfires 

that threaten severe destruction 

(that, by themselves, would constitute 

a major disaster), and to salvage 

timber, where the cost of salvage 

exceeds the payment received for the 

salvaged timber, 

The USDA Forest Service administers 

two federal programs that were 

incorporated into the Hazard Hitigation Plan: the Rural Conamunity Fire 

Protection Program (RCFPP) and the 

Rural Fire Prevention and Control 

Program (RF'PCP), The Rural Community 

Fire Protection Program authorizes the 

Secretary of Agriculture to provide 

financial and technical assistance to 

State Foresters to organize, train, 

and equip fire departments in rural 

areas and in cornunities of less than 

10,000 people, This program disburses 

approximately $3.5 million annually 

across the nation, South Carolina 

receives approximately $45,000 a year 

to assist 85 fire departments. The 

departments must match the federal 

grants with their own money and must 

use the funds to buy needed equipment 

including hoses, pumps, tools, tanks, 

safety clothing, breathing apparatus, 

etc. Because the Farmer's Home 

Administration provides loans for 

costly fire trucks and stations, the 

FEM money my not be used toward those 

purchases, 

The Rural Fire Prevention and Control 

Program provides money for state 

governments to secure and process fire, 

law enforcement, weather, smoke management, and prescribed fire information 

and data, In fiscal year 1989, RFPCP 

allocated $278,050 to the South 

Carolina Forestry Commission for those 

purposes. The information obtained was 

used to analyze and plan fire control 

activities, Fire weather, smoke 

management, and prescribed burn information was disseminated to the SCFC, 

Cooperators, and the general public to 

enhance prescribed burn programs 

throughout the state, In addition, 

RFPCP: reviews telecoxnxnunications 

system to provide better contact 

between the SCFC and the public; 

updates radio communications to enhance 

information flow during emergencies; 

revises and updates County Fire Organization and Fire Prevention Plans to 

bprcrve coordinated efforts of all 

agencies involved in emergencies; and 

identifies high risk wildfire/urban 

interface areas to help develop 

protection plans. 

At the state level, the South Carolina 

Forestry Coxnxnission oversees fire 

prevention, pre-suppression, and 

suppression of wildfires, In 1989, the 

agency operated with a budget of $19.4 

million 

Structure 

The organizational structure created to 

implement Phase 1 is diagramed in 

Figure 1, The Planning Team created an 

entire substructure, the Coordination 

Team, within the already-established 

structure of the SCFC. That is, the 

Hugo Coordinator (newly-created position) reported directly to the Assistant State Forester, Field Operations 

(established position) at the SCFC. 

The Hugo Coordinator was responsible 

for managing the entire FEMA-funded 

portion of the Plan, He and his staff 

operated out of a leased double-wide 

office trailer located at the SCFC 

Columbia office. The Coordinator 

headed a staff including an Operations 

Coordinator, a Financial Management 

Accountant, a Public Information 

Officer and Assistant, a Personnel 

Officer, two Zone Coordinators, and 

nine Forestry Specialists. 
The Operations Coordinator reported 

directly to the Hugo Coordinator and 

was responsible for equipment leased 

from FEMA, monitoring salvage operations, contracting work authorized by , compiling costs, overseeing 

final inspections, receiving reports 

from the North Zone and South Zone 

Coordinators, and compiling those 

reports into monthly progress reports 

for FEW%, 

The Financial Management Accountant 

was responsible for compiling all 

FEm-approved costs, tracking costs, 

submitting requests and preparing 

vouchers for payments, and keeping 

files on all financial documents. 

The State Public Information and 

Education Officer and assistant were 

funded by FEMA with any remaining 

balance covered by the state, They 

were responsible for the entire 

Information and Education program, 

including all press releases, public 

service announcements, press conferences, mailings, video tapes, and 

television and radio spots. In 

addition, the Officer was responsible 

for developing and implementing a 

massive outreach program for young 

children, 

The State Personnel Office was funded 

by the State through SCFC; this office 

processed all necessary personnel 

activity. The remaining staff positions (zone coordinators and forestry 

specialists) were funded by FEMA. In 

addition, a joint State/Federal Coordinating Center was created to coordinate fire suppression activities by 

state and federal personnel in or near 

the Francis Marion National Forest; 

the center was staffed by members of 

the USFS and the SCFC, 

Zone Coordinators and Forestry 

Specialists were responsible for 

identifying high wildfire risk areas 

for fuel hazard reduction projects, 

acquiring right of entry permission 

from landowners for Team projects, 

scheduling and supervising heavy dozer 

teams, identifying property lines, and 

ahinistering contracts. In addition, 

they were supposed to speak to groups 

to promote fire prevention, work with 

schools, keep in contact with local 

media, inspect sites for fire threats, 

assist residents in reducing their 

fire hazards, schedule and coordinate 

prevention patrols, ensure personal 

contacts with residents in rural 

areas, and work with the Fire 

Prevention Council, the S t a t e F i r e 

Marshall's Office, local fire departments, and state and county agencies, 

Each Zone Coordinator and Forestry 

Specialist was given a FEMA-funded 

pickup truck with a 250 gallon slip-on tank and a radio, The South Zone 

Coordinator was in charge of activities 

in Charleston, Berkeley, Dorchester, 

Williamsburg, and Clarendon counties, 

and the North Zone Coordinator was 

responsible for Sumter, Lee, Lancaster, 

and Kershaw counties. The SCFC, under 

their own authority, provided part-time 

criminal investigators to investigate 

arson, 

The USFS served as technical advisor to 

both SCFC and FEMA, The USFS conducted 

training programs for the forest 

specialists hired by SCFC to work in 

each of the nine blowdown counties. In 

addition, FMNF staff helped with public 

information. Staff went door to door 

to residents within the FMNF distributing fire prevention information. They 

helped with TV advertisements, posting 

road signs, and distributing t-shirts 

and hats, Finally, they constructed 

250 miles of fire breaks in FMNF with 

FEW funds, 

Funding 

Federal funding for Phase 1 came 

through two programs, In November, 

1989, the Plan was submitted to the 

Federal Emergency Management Agency 

(FEMA) and subsequently approved with 

initial funding of $9.3 million over a 

nine month period ending September 30, 

1990, FEMA funding was mandated 

through four separate sections of the 

Stafford Act: sections 403, 404, 420, 

and 421. These programs covered debris 

removal, road clearing, damage mitigation, wildfire suppression, and timber 

salvage for hazard mitigation. The 

Governor's Office assisted localities 

with the process to obtain FEMA funding, particularly through Section 404 

of the Stafford Act, Section 404 was a 

new harzard mitigation grant program 

and the Governor's Office issued a 

report giving localities clear guidelines on how to complete an application 

for a hazard mitigation grant." In an 

unrelated program, the Dire Emergency 

Supplemental Appropriations Act 

provided $500,000 for fire prevention; 

Office of the Governor. "State 

Hazard Mitigation Grant Program: 

Applicant's Guide." undated 

publication. 
this money was distributed to 117 fire 

departments in the Hugo area. 

The Forest Service allocated $1.266 

million in 1989-90 to fund fire prevention and mitigation activities. 

These funds were used primarily for 

buying equipment and carrying out 

operations. 

Goal 1: Fuels Management 

The fuels management section of the 

Plan attempted to reduce the risk of 

wildfires to life and property, with 

the following priority: 

1) TOWS, municipalities, and 

communities; 

2) Individual homes; 

3) Other structures [unspecified]; 

and 

4) Control lines to reduce risk of 

catastrophic fire. 

The goal was to be achieved by constructing fuel breaks in "risk areas," 

defined as "an area of heavy blowdown 

fuel accumulation which constitutes a 

threat or risk of wildland fire capable of destroying towns, municipalities and communities, residences, or 

other structures."" Fuels management risk areas were prioritized as follows : 

1) Cornunities or areas with histories of high fire occurrence 

and heavy fuel accumulation near 

towns or communities; 

2) Areas with heavy fuel accumulation that threaten homes or 

other structures; and 

3) Areas with heavy accumulation to 

provide access and control 

lines, as in existing wood roads 

and old fuel breaks. 

Other methods of fuels manaqement were 

considered, including chipping, hand 

piling, and clearing 100- to 200-foot 

wide fuel breaks, but 10- to 20-foot 

wide fuel breaks were chosen as the 

most cost-effective way to prevent 

large-scale fires. Fire suppression 

guides advised that a fire line with 1 

112 times the depth of the downed fuel 

would provide a sufficient control 

line. After Hugo, the fuel accumulation was five to ten feet deep, so 10- 

to 20-foot fuel breaks were considered 

32 Interagency Planning Team. 

Hurricane Huso Wildfire Hazard 

Reduction and Mitisation Plan. 

November 1989, p. 9. 

an effective width. In addition, this 

method would not cause fuel cleared 

from the lines to accumulate into piles 

and windrows (providing more hazardous 

material for fires). 

Fuel break construction proceeded under 

a 30170 Management Plan. Thirty percent of fuel break miles were to be 

constructed with I? -leased heavy 

equipment. The remainder were to be 

built by private sector contractors. 

The 30% fuels mnagement plan included 

a t o t a l s f 3420 miles of fuel break 

construction (2300 miles in the South 

Zone and 1120 miles in the North Zone). 

The Team estimated that each unit (one 

heavy dozer and two men with chainsaws) 

could construct approximately two miles 

of fuel break per day, so 19 units 

could complete 38 miles a day, and 3420 

miles in 90 days. The estimated cost 

for the initial 30% was over $2.9 

million. Another 7,980 miles were to 

be contracted to private crews at an 

estimated cost to FEMA of $3.3 million. 

Goal 2: Fire Suppression 

The fire suppression section of the 

Plan attempted to: 

I) Provide early detection and 

reporting of all fires; 

2) Provide rapid initial attack with 

specialized equipment and 

increased manpower; 

3) Provide intensified mop-up 

operations to prevent breakovers 

and reduce residual smoke; and 

4) Provide management and logistical 

support for multiple fires of 

long durations. 

The fire suppression general strategy 

set the following priorities: 

1) Eliminate life hazards; 

2) Protect structures and property; 

3) Confine fire within existing fire 

breaks; and 

4) Construct fire lines to minimize 

the size of the fire. 

To manage the large area of backlogged 

fuel effectively, the Hugo area was 

divided into two smaller areas, the 

North Zone and the South Zone. Three 

operating bases within these zones were 

proposed: Camden (North Zone), Manning 

(South Zone), and Moncks Corner (South 

Zone.) Each zone was supplied with its 

own equipment and personnel. Equipment 

assignments included air tankers, 

detection aircraft, heavy equipment, 

water handling equipment, and staging 

areas for crews. The Plan called for 
adding two detection aircraft to the 

existing forces and increasing the 

er of flight hours of the aircraft 

in operation. 

Fire prevention and suppression personnel in each zone were augmented by 

a task force, consisting of a Zone 

Coordinator and Forest Specialists, 

The Zone Coordinator mnaged resources 

to support existing county and district fire suppression operations. 

The Forest Specialists worked with the 

Zone Coordinator on public information 

(promoting the program, speaking to 

school groups, and working with the 

media) and fire prevention and suppression (inspect fire threats, assist 

local fire department in suppression, 

and assist residents in reducing fire 

threats) . The presence of the Forest Service in 

the South Zone made possible a special 

cooperative wildland fire suppression 

effort between the SCFC and the 

Francis Marion Dispatch Center. 

According to the Cooperative Fire 

Control Agreement, state resources 

would respond to fires on federal 

lands and federal resources would 

respond to fires on state land* 

District, state, county, and Forest 

offices were to maintain open communications channels; radios (and personnel, if necessary) were to be 

exchanged between the Kingstree and 

Marion offices. 

Goal 3: Fire Prevention 

The fire prevention campaign had two 

main purposes: 1) to advise the 

public of the danger to life and 

property from wildfire; and 2) to 

educate the public about the dangers 

of indiscriminant outdoor burning in 

Hugo-affected areas. Its short-term 

objective was to saturate every person 

five years and older with fire prevention messages by the end of January 

1990. In the next year, the campaign 

wanted to sustain an awareness of the 

fire danger through reinforcement 

techniques. In the three to five 

years after the storm, the Public 

Information office wanted to encourage 

the responsible use of fire. 

The Public Information Coordinators 

attempted to saturate people with the 

message of fire prevention using all 

media avenues. The cornerstone of 

this program was the GIMME 12 campafgn. The objective and slogan of 

thls campaign was "Gimme 12 months of 

fire safety". GIMMP, 12 was advertised 

in newspapers, on posters, through 

public service announcements, and on 

parade banners, Mayors were encouraged 

to make public proclamations endorsing 

the program; schools were given information packets on prevention and fire 

safety and were rewarded for fire 

prevention education efforts. GIM 12 

stickers and b~~llper stickers as well as 

stationary were distributed, and the 

campaign was advertised on roadside 

signs. 

Additional infoxnuition efforts included 

an initial 45-day campaign emphasizing 

the potential for wildfires, protection 

of homes and lives, and an "avoid burning" message. This shorter campaign 

coincided with the time of greatest 

chance for severe and dangerous forest 

fires predicted by local fire experts. 

Continual public information efforts 

also included weekly news releases to 

newspapers and public service announcements informing people in Hugo-affected 

areas of precautions, fire situations, 

alerts, burning bans, etc. 

Results 

The procuraent of additional equipment 

and hiring and training of extra personnel proceeded as planned. All 

Forest Specialists were trained and 

assigned to the nine blowdown counties 

by mid January 1990. Two 1400-gallon 

scooper type air tankers were contracted for the fire season. Thirty 

temporary firefighters were employed, 

trained, and equipped to suppress 

fires. By March 1990, much of the 

fuels management and fire suppression 

equipment was or soon would be under 

lease. USFS detailers conducted fuel 

assessments of all Hugo counties from 

mid-December 1989 through March 1990. 

By October of 1990, crews with heavy 

dozers and chainsaws had constructed 

over 1800 miles of firebreaks around 

threatened homes and communities, and 

in national forests. Over 3000 landowners had been contacted regarding 

fuel break construction on their 

property, with a very high acceptance 

rate.33 Most of the fire breaks were 

constructed to eliminate fire hazards 

and protect structures and property 

(priorities 1 and 2), while improving 

33 It is estimated that about 95% of 

all landowners that were contacted by 

SCFC for fire break construction 

granted permission (personal communication, SCFC personnel). 
existing fire breaks (priority 3) only 

began in the later months of the 

program year. 

During the first 5 mnths of the GI 

12 campaign, over 300,000 households 

had hen reached through direct mailings; radio and TV spots were broadcast; and t-shirts, baseball caps, 

painters caps and banners appeared 

throughout the Bugo area. 

Spring fires were down by 40% compared 

to an average year, with only one 

occupied residence burned and no 

deaths. In the four-month period from 

1 December 1989 to 15 March 1990, 693 

fires burned 4,243 acres in the nine 

county Hugo area compared to the same 

period in the previous year during 

which 1,210 fires burned 6,943 acres. 

However, rainfall for the southern 

region of the state during these 

periods also differed, For instance, 

the city of Charleston in the '89 

through '90 period saw a net precipitation surplus of 2.82 inches, while 

during the same period the previous 

year there was a precipitation deficit 

of 6.78 inches. In addition, 

Charleston's precipitation for 

September and October of 1989 was 

above normal by 9.57 inches, while 

September and October of 1988 was 

above nonnal by only 2.59 inches, Wet 

weather after Hugo helped reduce the 

risk of fire by causing the water 

table to rise and moistening soil. 

Because of the perceived tremendous 

success of Phase I and the extended 

threat of wildfire, the Interagency 

Team developed a proposal for Phase 

11, a five-year continuation of fire 

prevention, detection, and suppression. However, before Phase I1 was 

approved, the Interagency Team 

requested a time extension of Phase I; 

it was approved through December 1990. 

PART 2B: THE PLAN: PHASE 11 

The purpose of Phase 11 was to solicit 

additional funding and support from 

and the USFS to continue to 

implement the Hurricane Hugo Wildfire 

Hazard Reduction and Mitigation Plan 

over the next five years. Phase 11 

built on the moment- of Phase I and 

set the goals of: 1) eliminating the 

threat of catastrophic wildland fires 

in the Hugo area; and 2) reducing the 

occurrence of wildland fire by at 

least 50% over the next five years, 

Structure 

Like the Phase I plan, Phase 11 

outlined a personnel structure that 

worked within and supplemented the 

current SCFC structure. Phase 11 of 

the Plan proposed aupenting the SCFC 

staff by creating 75 new positions. 

Although some jobs were changed and/or 

responsibilities redefined, many of 

these positions were shilar to those 

under Phase I. The fire management 

coordinator--analogous to the Hugo 

Coordinator under Phase I--oversaw the 

entire project. The fire management 

assistant, like the operation coordinator of Phase I, reported to the fire 

management coordinator and provided 

coordination at the district level. 

The documents and reports manager 

covered all the duties of the financial 

manager under Phase I. The writer/ 

editor and the fire prevention coordinator continued the public education 

responsibilities of the Phase I plan's 

information and education specialist, 

And the Forest Specialists under Phase 

I were renamed Fire Hazard Mitigation 

Specialists under Phase I1 and assisted 

county rangers in fuels management, 

fire prevention, pre-suppression, and 

suppression activities, 

In the field, personnel structure 

remained essentially the same as in 

the Phase I plan: 18 heavy dozer 

operators/crewmernbers, 35 seasonal 

firefighters to assist county fire 

wardens, and two tanker base operators. 

The North and South zones still 

existed, although the southern 

operating bases changed from Manning 

and Moncks Corner to Kingstree and 

Walterboro. All of the proposed 

positions (with the exception of the 

fire prevention coordinator) were to be 

funded by FEMA. 

Funding 

er 1990, FEMA gave partial 

approval to Phase I1 and eventually 

appropriated $3 million for the 1990- 

1991 program year. Each year, FENA 

based continued funding upon an 

assessment of whether a fire emergency 

still exists. This assessment was 

positive in 1991 and 1992. A smary 

of FEMAts funding for the fire hazard 

mitigation program is shown below in 

Table 1: 

In addition, USFS allocated another 

$1.4 million for Phase If, bringing 

their total contribution to $2.7 
ry of FEMA funds for the 

Hurricane Hugo Wildfire Hazard Reduction and Mitigation Project 1989 - 

1993, 

Program Year Funding mount 

(in millions) 

million, SCFC has contributed $4,327 

million above and beyond the annual 

$11 million it spends to provide 

statewide forest fire protection. The 

State also provided $500,000 to 

purchase heavy truck tractors to 

replace ones leased from FEMA, 

Goal 1: Fuels Management 

To build on the success of the Phase I 

fuels management plan, Phase I1 set 

the goal of safely incorporating the 

use of prescribed fire in its effort 

to minbize the throat to life and 

property from wildfire, To achieve 

this goal, the Team planned to continue the construction of 20-foot wide 

fuel breaks, begin on-site inspections 

of prescribed burn operations to 

ensure safe and acceptable practices, 

and initiate a Burning Qualification 

Program to provide training in postHugo burning operations. Additionally, a Prescribed Burning Program was 

planned to reduce fuel loading, establish fuel breaks, and provide protective strips in high risk areas, 

Goal 2: Fire Suppression 

The Phase I1 fire suppression plan 

remained virtually the same as Phase 

I, focusing on protecting the lives 

and homes of the 750,000 people living 

in the Hugo blowdown area, The Phase 

I1 Plan pointed to the success of 

Phase I as proof that its rapid 

detectionlquick suppression method 

worked well and needed to be 

continued. 

Goal 3: Fire Prevention 

The Phase I1 Fire Prevention Plan 

revolved around a public information 

and education program about the safe 

use of outdoor fire, An annual 

campaign, called Take 5, was planned 

for five years. Its primary emphasis 

varied from year to year to allow 

flexibility as fire hazard conditions 

changed, In addition, each year's 

campaign would have a primary message 

and a secondary message; the secondary 

message would become the next year's 

primary message to provide reinforcement and continuity, The campaign plan 

follows : 

- Year Primary focus 

1989-90 Avoid burning ("Gimme 12") 

1990-91 Safe burning ("Take 5") 

1991-92 Law Enforcement 

1992-93 Hazard Reduction Burning 

1993-94 irep proofing Interface Homes 

1994-95 Preserving Lifestyles 

Through the 1992-1993 campaign year, 

the campaign used paid advertising, 

After that, the campaign relied solely 

on print media and public service 

announcements to reach its audience. 

Results 

Fuel break construction continued 

through June 1991, resulting in a total 

of 4500 miles cleared, involving 5500 

landowners, A goal of 5000 miles by 

September 1991 was hampered by wet 

conditions in the winter 1990 - 1991 

and spring 1991, Construction was 

prematurely stopped because of a 

greater need for equipment in fire 

suppression activities. 

Like 1989-1990, the fire season of 

1990-1991 was another below average 

year for wildfires, A total of 1,364 

fires burned, The following year, 

however, had the worst wildfire 

occurrence since 1985, During 1991- 

1992, 2603 fires burned over 21,300 

acres. 

PART 2C: CONCLUSIONS 

In the aftermath of Hurricane Hugo, the 

Interagency Hazard Mitigation Team 

faced a complex combination of circumstances, First, prior to 1989, Hugo 

had been the most destructive and 

devastating hurricane to hit the United 

States; response and recovery was bound 

to take longer than previous natural 

disasters merely because of the magnitude of the damages. State policymakers and forestry agency personnel 

worked creatively to ensure federal 

involvement in the wildfire hazard 

mitigation efforts. The organized 

response by the staters forestry agency 

and the Governor's office gave irmediate attention to severity of the forest 

disaster and the need for a wildfire 

hazard mitigation plan to ensure safety 

and avoid compounding the disaster. 

State forestry officials lobbied for 

FEMA involvement, and the Governor's 
Office issued guidleines offering a 

model for localities to follow when 

applying for P funds through the 

new Hazard Mit ion Grant Program, 

f the Stafford Act. As a 

s involvement in hazard 

s achieved by expanding 

the eligibility, funding, and revising 

the justifications3"n the 1988 Robert 

T. Stafford Act, While F 

pated post-Andrew efforts in Florida 

to last at least a year and was active 

in Mobile, Alabama for 9 months after 

Hurricane Frederick, FEMA has participated in South Carolina's fire prevention efforts ongoing for four years 

after Hugo, FEMA defined its continuing involvement not as recovery, but 

as emergency response, since the fire 

hazard threatens life and property. 

FEMA officials have decided that the 

fire hazard still persists and, consequently, have continued funding phase 

I1 of the fire hazard reduction and 

mitigation plan. 35 

The goals of the Wildfire Hazard 

Mitigation Program were well defined. 

Clear goals were essential to begin 

the program soon after the hurricane 

and to organize the numerous agencies 

taking part in this 24 county effort. 

In addition, by emphasizing fuels 

management and fire prevention, as 

well as fire suppression, the program 

clearly went beyond emergency 

response. The plan maximally utilized 

the expertise of the SCFC by placing 

the Coordination team within SCFCts 

organizational structure and explicitly outlining the responsibilities 

and priorities of all personnel to 

guide their work. This aided in 

accountability and communication among 

all agencies and personnel involved, 

A multilevel approach to wildfire 

hazard reduction was found to be most 

successful by dividing the Hugo 

damaged area into zones and coordinating some activities at the zone 

level and others at the state level. 

Zone coordinators directed the technical and monitoring components of the 

strategy, using the priorities and 

guidelines for fuel break construction 

developed at the state level, The 

fire prevention education program was 

directed at the state level. 

Wildfire hazard mitigation was a 

multi-year program and required 

sustained coordination of efforts 

across levels of governance. The plan 

effectively pulled together and 

utilized a number of pre-existing 

at the federal, state, and 

els, Each program and level 

of government provided their own 

particular expertise or essenti 

resources: funding came from F 

rily, as well as the USFS 

SCFC; equipent was procured through 

to suppl-ent local etations; and 

personnel came from SCFC, the Forest 

Service, or were hired and trained by 

these agencies. 

Throughout Phase I and Phase 11 of the 

plan, the sequence and thing of 

efforts to achieve each of the goals 

was crucially important. Fuels management required initial emphasis on constructing fuel breaks on lands prioritized according to level of risk. Fire 

suppression required that localities 

throughout the blowdown areas were 

assigned sufficient equipment and 

personnel, Finally, fire prevention 

initially required a large-scale campaign to inform residents about the 

fire hazard and urge them to avoid 

burning. Dealing first with these 

initial high priority issues eventually allowed many aspects of the program to 

move to a maintenance mode in Phase 11. 

As with every other aspect of the 

disaster response, the wildfire hazard 

mitigation efforts were greatly 

affected by chance factors. The fire 

hazard created by the blowdown of so 

much timber was in part regulated by 

factors exogenous to and superseding 

most state and federal responses (i,e. 

tree growth rates and weather). 

Weather significantly affected the 

success with which many of the program 

goals were met. While heavy rains in 

1989 kept fuels and soils moist, it 

slowed fuel break construction in many 

areas, Lower than average fire 

occurrence in two fire seasons (1989- 

1990 and 1991-1992) was followed by 

above average number of fires in 1991- 

1992 once there was a net rain deficit. 

Wildfire hazard mitigation programs 

need to consider how exogenous weather 

factors might affect the success of the 

policy response, 

3'John M. Ols, Jr, 1990. "Preliminary Information on the Federal 

Government's Response to Recent Natural 

Disasters," Testimony given to the 

Subconunittee on Investigations and 

Oversight on the Federal Emergency 

Management Agency's Response to Natural 

Disasters. May 1, 1990. 

FIEMA Region IV official, personal 

communication. November 1992. 
PART 3: REFORESTATION 

When Hurricane Hugo struck on 

er 21, 1989, it leveled over $1 

billion worth of forest resources in 

South Carolina. The South Carolina 

Forestry r om mission (SCFC) estimated 

that more than one million acres of 

ged land needed reforestation; 

approxdtely 679,000 of those acres 

were on private lands. The Hugo 

Reforestation Committee, a group 

representing all facets of the forest 

sector, formed to address the 

reforestation needs of non-industrial 

private forest (NIPF) landowners. 

Since then, $11 million of federal 

funds have been disbursed through the 

South Carolina Forestry Commission to 

help South Carolina landowners 

reforest. The funds have supported 

"Gimme Green" (a free needs assessment) and the Hugo Incentive Program 

(a cost share agreement for reforestation), 

The South Carolina case provides an 

example of how state and federal 

agencies formulated forestry assistance policy in the face of emergency 

conditions. The challenges to these 

agencies were: (1) to effectively 

provide reforestation infomation to 

the thousands of landowners with 

devastated forest land; and (2) to 

insure an equitable distribution of 

reforestation aid. An analysis of 

each program's results provides 

lessons to other states on how to 

target assistance programs to NIPF 

landowners. 

PART 3At THE REFORESTATIOISI 

CONNI TTEE 

On December 14, 1989, less than three 

months after Hugo hit South Carolina, 

the Hugo Reforestation Committee 

formed to consider reforestation plans 

for 679,000 acres of NIBF land, The 

committee represented all areas of the 

forest sector, including consulting 

foresters, forest industry, landowners, the South Carolina Forestry 

Association (SCFA), the South Carolina 

Wildlife Federation, the South 

Carolina Forestry Commission (SCFC), 

Clemson University Extension Service, 

the U.S. Forest Service (USFS), and 

South Carolina Wildlife and Marine 

Resources. 

The primary concerns of the Reforestation Comittee were as follows:36 

(1) To create a "Forest Rehabilitation Vision" to consider the 

necessary state, industry, local, 

and individual effort needed to 

rehabilitate SCrs forest lands; 

(2) To consider the impact of various 

financial scenarios on what the 

forest in the disaster area would 

look like in 10 or 20 years; 

(3) To inform legislators about 

reforestation progress and the 

need for and timing of future 

funds; and 

(4) To prepare a plan to assure that 

the South Carolina resource would 

be restored and ultimately surpass the current forest growth 

capacity while maintaining a good 

balance of forest types, age 

classes, and habitats, 

Joe Mills (SCFC) chaired the Committee 

and Steve Scott (SCFC) served as its 

Executive Director. The Committee 

split into three subcommittees, and 

Mills appointed chairpersons for each: 

Public Education/Information, chaired 

by George Kessler (Chm.son University 

Extension Service); Technical Assistance, co-chaired by Pete Bischoff 

(SCFC) and Jeff Baumann (SCFC); and 

Reforestation Promotion, chaired by 

Alan Alexander (SCFC). 

The Public Education/Information 

Subcommittee was responsible for: 

educating and training foresters and 

landowners about reforestation; 

producing educational and training 

materials and technical publications; 

conducting landowner meetings, opinion 

surveys, interviews, and demonstrations; and issuing news releases. 

The Technical Assistance Subcommittee 

was charged with: providing technical 

assistance to landowners; developing 

and assisting with regeneration techniques and equipment; training site 

preparation and tree planting vendors; 

assuring seed availability; conducting 

mapping, surveying, and photography; 

and providing herbicide information to 

landowners. Before assessments of 

reforestation needs had been completed, 

the technical assistance subcommittee 

was divided into an artificial regeneration section and a natural regeneration section. Once work in the field 

began, however, this division of duties 

and expertise became impractical; most 

landowners found they could not rely 

exclusively on either natural or artificial regeneration and needed technical assistance on both procedures, 36 GOvernor % Fore~t Di~aotsr Salvage Council Newsletter. 2 January 1990. 
The Reforestation Promotion Subc 

tee was supposed to create and hplement a proanotional c-paign for the 

reforestation effort, and produce and 

distribute-public service announcements, television and radio spots, 

print advertisements, and pronrotional 

literature, 

weeks after its initial meting, 

the Reforestation Committee proposed 

offering every private landowner in 

the Hugo area a free reforestation 

needs-check in the fall, Though there 

was no money available at that time, 

the group decided the needs-checks 

were necessary for the Committee to 

understand fully the extent of the 

problem, The Codttee planned to use 

volunteers for all parts of its plan 

until Dire Emergency Funds were appropriated for technical assistance in 

July 1990. Once the money was 

approved and designated to be disbursed through the South Carolina 

Forestry Commission (SCFC), the 

Committee was used strictly in an 

advisory capacity, The SCFC solicited 

input from the Comittee, but SCFC had 

final responsibility for the use of 

the money- Because the Chair, Executive Director, and Subcommittee heads 

were all SCFC employees, the transition from Committee responsibility to 

Commission responsibility was smooth, 

Funding--Dire Emergency Funds 

The Dire Emergency Funds were the 

first funds made available in South 

Carolina to the forest sector. 

Because of the efforts of South 

Carolina Senators Hollings and 

Thumond, the USFS, and the President, 

Congress allocated $5 million over a 

three-year period to SCFC for NIPF 

technical assistance. The money, 

appropriated through the Dire Emergency Supplemental Appropriations Act, 

was used to fund the Committee's 

reforestation plan, which included the 

GREEN program and a landowner 

survey, It provided funds to hire 

additional foresters and consulting 

foresters for site check inspections, 

obtain equipment for county foresters, 

provide travel support for foresters, 

promote the inspection through the 

on Extension Service, train area 

foresters, and provide herbicides for 

r stand improvement activities on 

NIPF land, 

Landowner Survey 

In September, Clefflson Extension Service conducted a landowner survey for 

the Reforestation Committee. The 

primary objective of the survey was to 

ask NIPF landowners "What do you need 

to enable you to restore your land to a 

forested condition?w37 A series of 

questions addressed: 

ges NIPF landowners 

suffered to their land, other 

private property, and quality of 

life; 

(2) forest management actions they 

had taken so far; 

(3) forest unagment actions they 

were planning for the future; 

(4) what they required to carry out 

those plans; and 

(5) any change in attitude towards 

their forest land, 

The answers to the survey revealed 

several important points. First, in 

excess of 60% of landowners had already 

conducted either reforestation (natural 

or artificial) or harvesting (thinning 

or final harvest) activities on their 

land previous to Hugo. More than half 

the landowners had made contact with a 

forester since Hugo, indicating interest in maintaining their land in 

forest. However, the survey also 

revealed that many landowners changed 

their attitude towards their lands. 

Timber production became less of a 

priority. Landowners were less willing 

to make the potentially high forest 

management investment required now for 

what was perceived as an even more 

uncertain future outcome, While assistance programs, such as cost-sharing or 

reforestation tax incentives, could 

help alleviate some of these worries, a 

relatively small number of NIPF landowners used them or even knew of the 

programs. 38 

Ginme Green 

In the first weeks of July 1990, the 

Committee's proposed reforestation 

needs-check, "GIW GREEN," started; 

direct mail, billboards, and advertisements on radio, television, and in 

newspapers were used to alert landowners to the free check-up. The SCFC 

also set up a toll free number that 

landowners could use to make requests. 

In October, the SCFC, the USFS, and 

Clemson Extension Service jointly 

37 Stephen K, Nodine. 1992, Forest 

Landowners' Responses to Hurricane 

Huqo, Forest Research Series No. 47. 

Department of Forest Resources, Clemson 

University. 

38 - Ibid. 
trained public, private, and industry 

foresters on reforestation methods. 

er, the Comission had 

started requesting proposals from 

private consulting firms to provide 

technical assistance to landowners 

through GI EN. Thirty firms 

submitted 1s. By February 

1991, SCFC ntracts with 29 

consulting 

GREEN program emphasized 

natural regeneration. The SCFC and 

Clemson Extension Service advocated 

natural regeneration for several 

reasons. First, it was biologically 

viable. 1989 had been a good seed 

year, and seedlings had just gotten 

started when Hugo str~ck.'~ Post-Hugo 

conditions, especially the more open 

conditions on salvaged land, were 

ideal for pine regeneration. Second, 

though cost-share funds were available, they could not meet the demand 

for subsidized reforestation. Natural 

regeneration represented a low-cost 

method that saved funds for those 

stands absolutely requiring artificial 

regeneration, Finally, the SCFC 

wanted to give landowners positive 

news (egg. "your land is well-stocked" 

or "you need to use minimal inputs to 

restore your forest") rather than add 

to the landowners' sense of 10~s.'~ In 

brochures advertising the program, the 

SCFC and Clemson Extension Service 

advised landowners to "wait for natural regeneration" and only consider 

artificial regeneration if the chances 

for natural regeneration looked 

unlikely." They also advised that any 

salvaging of damaged land should avoid 

taking live trees. 

During the request period from 15 

October 1990 through 1 January 1991, 

1072 landowners signed up for the free 

reforestation needs-check, representing approximately 309,000 acres, 

State foresters and consulting 

foresters hired by SCFC conducted the 

site check-ups. While these landowners constituted only a small 

proportion of the estimated 37,000 

private landowners whose timberland 

was damaged by hug^,'^ their combined 

acreage represented just under half 

the total number of private acres 

estimated by the SCFC to need 

reforestation. Predominantly 

landowners with large landholdings 

participated; the average tract size 

was 288 acres. By April 1992, 

foresters had serviced over 960 

requests covering 223,000 acres. Most 

of the acres were in pine (84%). 

Foresters conducting the site checks 

determined that: artificial regeneration was needed on 23% of the sites; 

natural regeneration could be used on 

21% of the sites; and 54% were adequately stocked. 43 

Hugo Incentive Program (HIP) 

In January 1991, less than one month 

after the check-ups began, Congress 

appropriated another $3 million of 

emergency reforestation money. With 

support from Senator Hollings, Senator 

Thumond, the President, and lobbying 

by the USFS, the proposed funds were 

included in a provision in the Interior 

Appropriation Bill for the U.S. Forest 

Service. The allocation provided costshare funds for reforestation to be 

administered through the SCFC. The 

Hugo Incentive Program (HIP) is the 

only federally-funded landowner assistance program in the country being 

completely administered by a state 

agency. 

Landowners in the 24-county disaster 

area with forest stands damaged 35% or 

more in need of artificial reforestation could apply for HIP cost-share 

GREEN field foresters 

determined handowner reforestation 

needs. HIP did not place landowner 

acreage ownership limitations, but 

corporations with over $5 million 

annual gross income did not qualify. 

75% cost-share would be provided, based 

on the average cost for the prescribed 

methods of reforestation. Compared to 

the Forestry Incentives Program (FIP), 

HIP reduced the amount contributed by 

the landowner from 50% to 25%. 

Originally, a cap was set at $25,000 

per landowner. Due to the unexpected 

number of applications, the cap was 

lowered to $10,000 per landowner. 

39 SCFC personnel, personal cornmunication, November 1992. 

" SCFC personnel, personal communication, November 1992. 

Brochure entitled "Step Two-- 

Restoring the Forest After Hurricane 

Hugo," July 1990. 

42 South ~arolina Forestry Association 

pamphlet: "The Facts About Hurricane 

Hugo and Forestry in South Carolina." 

undated. 

43 Allan P. Marsinko, Thomas J. Straka, 

and Jeffrey L. Baumann. 1993. 

"Hurricane Hugo's Effect on South 

Carolina: The Impact After Three 

Years," Journal of Forestry, September 

1993, p. 9-17. 
The initial signup period was March 

11-22, 1991. 1,017 people submitted 

1096 applications. Servicing those 

applications with the $25,000 cap 

would have required approximately $16 

million--much more than the $3 million 

originally allocated. Some applicants 

did not qualify for assistance either 

because their land did not have 

ge or because they 

could not afford to pay their 25% 

share of the cost-share. 

~enerally, HIP participants received 

three visits from a field forester. 

The first was the initial needs-check 

to make sure the applicant qualified 

and to decide which methods of reforestation should be used. When natural 

regeneration was not an option, 

foresters recommended the lowest cost 

artificial regeneration method available. On the second visit, the 

project forester checked the land to 

make sure it had been prepared for 

planting properly. If the land met 

specifications, the landowner could 

receive partial payment. On the third 

visit, the forester checked the 

planted trees. At that point, the 

landowner received the remainder of 

the cost-share payment. HI? provided 

no up-front payments; that is, the 

landowner initially paid for the work, 

and when the work was completed, the 

landowner was reimbursed. In most 

instances, landowners received costshare assistance for 100 acres or 

less. Most landowners were able to 

use a combination of natural regeneration and artificial regeneration on 

their lands. 

In April 1992, another official signup 

period was held." SCFC received 

another 160 applications. The SCFC 

estimated that it would be able to 

fund most of the applicants because 

some already-approved applicants had 

not reforested as much land as they 

had planned, leaving some surplus 

funds. By June 1992, approximately 

1000 landowners had been assisted. 

Cost-share assistance covered work on 

31,000 acres with landowners, on 

average, receiving assistance to 

ref orest 3 1 acres . 45 

Congress appropriated another $3 

million for this program in the 1991- 

92 budget, bringing the total federal 

contribution to $11 million. This 

money should allow SCFC to provide 

assistance to all landowners who 

qualified, using the $10,000 cap. 

PART 3Bt CONCLUSIONS 

The success of the reforestation effort 

in South Carolina can be evaluated on 

the basis of several measures. One 

measure is the numbers of acres reforested. The ~eforestation C 

SCFCrs managment objective was to 

encourage reforestation and growth in 

order to restore South Carolina's 

forested land to its pre-Hugo condition. The extent of reforestation 

efforts on Hugo-damaged timberland may 

not be reflected fully in the (relatively low) rates of participation in 

either the GI= GMEN campaign or 

 HIP.'^ The foresters performing GIMME 

GREEN site checks emphasized natural 

regeneration whenever it was a viable 

option, and, in general, HIP only 

funded artificial regeneration. Consequently, the 31,000 acres of cost-share 

funded reforestation greatly underestimates the total reforestation 

activity (natural and artificial) in 

the Hugo affected area. Educational 

efforts of the Reforestation Committee 

and SCFC designed to teach NIPF landowners successful natural regeneration 

techniques may have greatly enhanced 

the forest recovery process. 

Another measure of the effectiveness of 

the reforestation effort is the number 

of landowners participating in either 

GIMME GREEN or HIP. This measure 

allows policy makers to evaluate the 

success of forestry assistance policy 

in disbursing forestry assistance 

equitably across landowners. Many 

industry and state personnel have 

commented that the majority of landowners participating in GIMME GREEN and 

HIP had previously participated in 

forestry assistance programs, or were 

part of a cooperative forest management 

agreement with industry, or had an 

established relationship with a 

forester. According to this line of 

reason, landowners who were unfamiliar 

with forestry assistance or who had no 

" The terminology here is a bit confusing. Signups were never actually 

closed; "official" signups were simply 

publicized more. '' SCFC personnel, personal communication, November 1992. 46 There was a great deal of overlap in 

landowner participation in Ghe Green 

and HIP. Thus, enrollment in both 

programs may only account for 5% of 

over 40,000 NIPF landowners in the Hugo 

area. (Clemson University personnel, 

personal communication, December 1992). 
relationship or association with a 

forester were helped much less often. 

Active forest managers generally made 

several forestry management decisions 

prior to Hugo that facilitated their 

participation in HIP. Prior to Hugo, 

these landowners were more likely to 

have: (1) obtained forestry advice 

from a consulting or industry 

forester; (2) reforested their lands 

by artificial means; and (3) kept 

undergrowth to a minimum through 

prescribed burning, As a reault, 

after Hugo, these landowners were more 

likely to readily make contact with a 

logge; (because of their previous 

connection to forestry organizations) 

and to have successful salvage on at 

least some of their damaged timberland.47 In turn, salvaged timberland 

made artificial regeneration less 

costly (due to less site preparation) 

and more successful, In contrast, 

landowners who had no established 

relationship with a forester were at a 

disadvantage when competing for scarce 

salvage loggers and quickly allocated 

forestry assistance funds. Even if 

they were interested, these landowners 

may have found Hugo assistance pnrc~- 

grams difficult to pursue. 

Landowners also differ in their land 

management objectives. Active forest 

managers tend to: (1) place greater 

value on timber production; and (2) 

invest in more intensive reforestation 

and management practices (site prep 

costs after Hugo approached $250/ 

acre4*) over the short term. Other 

landowners: (1) may place more value 

on non-forest benefits; and (2) may 

have less intensive forest management 

plans. Landowners characterized by 

the second group of objectives may 

have participated less often in the 

assistance programs for at least three 

reasons. First, they may have 

intended to use natural regeneration 

from the beginning and decided that 

applying for HIP assistance was not 

worth the time, Second, landowners 

interested in natural regeneration may 

not feel the need for forestry advice. 

Third, these landowners may have 

gotten sufficient information about 

regeneration techniques through 

alternative sources, such as 

pamphlets, news programs, and 

magazines. 

Landowners who place greater value on 

nontimber outputs engaged in passive 

natural regeneration at the very 

least, but also may have decided to 

more actively reforest at a later date 

(after taking care of other, perhaps 

more pressing, losses) or participated 

in other incentive programs. In particular, the Forest Stewardship Program 

(FSP) and the Stewardship Incentive 

Program (SIP) aphasize management for 

multiple resources. Through FSP, landowners can obtain help to write a 

1 stewardship mnagement plan, 

SIP, which began in Kay 1992, provides 

cost-share assistance for ixnplesnenting 

the plan. Both programs enable landowners to address, in addition to 

timber management, management of fish 

and wildlife habitat, recreation, and 

soil and water quality. Because of 

this multiple resource management 

emphasis, both programs may be attracting NIPF landowners who did not want to 

take advantage of Gimme Green or HIP, 

In South Carolina, over 550 landowners 

have requested help in developing a 

stewardship management plan (see Table 

1). Throughout the South, 75% of the 

landowners participating in FSP are, 

for the first time, managing their land 

under a written plan. Many of these 

landowners, throughout the South and in 

South Carolina, may be participating in 

an assistance program for the first 

time . 

Table 1--Summary of the Forest Stewardship Plan Requests by District. 

District Number of Acres 

Requests 

Camden 114 49,077 

Florence 33 8,322 

Kingstree 86 40,510 

Newberry 110 25,305 

orangeburg 91 34,842 

Spartanburg 66 18,969 

Walterboro 54 32,018 

TOTALS 554 209,043 

47 Salvage was generally more successful and easier on lands managed with 

prescribed burning because the undergrowth was scarce and did not contribute to the difficulty of logging fallen 

and twisted trees (industry personnel, 

personal communication, November 1992). 

South Carolina Forestry Commission 

personnel, interview, May 1992. 
APPENDIX 
LIST AUTHORS 

Page 

Abt, Robert C. 305,306 

Adkins, Jim 452 

Anderson, Robert L, 28 

Askew, George 8. 454,456,475 

Aust, W. Michael 253,261 

Baker, James B. 283 

Barry, Patrick J. 28,385 

Baumann, Jeffrey L. 106,160,277,289 

Bixler, Robert D. 336 

Blood, E. R. 226 

Bourgeois, D. M, 480 

Buford, Marilyn A. 34,101 

Burch, John R. 305,306 

Burger, James A. 253,261 

Carlson, Danny L. 405 

Clark, Alexander, I11 223,399 

Colvin, William 13 

Conner, William H. 6,454,456,461,475 

Cook, Allen E. 83 

Doggett, Coleman 28 

Duever, Michael J. 72,73,74,81,82 

Dunham, P. H. 480 

Egbert, Charles D, 450 

Escano, Ronald E. F. 387 

Faust, Timothy D. 179,188,189 

Freeman, Wray E. 18 

Fuller, Mark 179,188,189 

Gardner, L. R. 226 

Gartner, David L. 101 

Gerhardt, D. W. 442 

Gresham, Charles A. 64,226,266 

Haight, Robert G. 106,289,293,315 

Hamilton, Joe 452 

Hammitt, William E. 336 

Herrick, Theresa A. 336 

Holmes, Thomas P. 391 

Hook, Dona1 D. 34,44,101 

Hooper, Robert G. 387,398,405,417 

Kellison, R. C. 52 

Kjerfve, B. 226 

Knight, Herbert A. 319 

Kramer, Randall A. 391 

Lander, T. Barton 306 

Lea, Russ 52 

Lee, Patrick 452 

Lipscomb, Donald J. 64,226,437 

Lloyd, F. Thomas 244 

Loeb, Susan 398 

Page 

Lupold, H. M. 21 

Marsinko, Allan P. C, 106,160,279, 

289,315,450 

McAdie, Colin J. 417 

McAlister, Robert H. 179,188,202,223 

McCollom, Jean M. 72,73,74,81,82 

McKee, William H., Jr, 253 

Michener, W. K. 226 

Miller, Thomas 380 

Milling, Thothy E. 405 

Miranda, Marie Lynn 498 

Myers, Richard K. 244 

Nagel, David 452 

Nix, Lawrence E. 44 

Nodine, Stephen K. 319,347,447,491 

Pacheco, Gerardo 305,306 

Peralta, P. N. 202 

Pittman, Kenneth 52 

Purvis, John C, 2 

Putz, Francis E. 92 

Reaves, Dixie Watts 391 

Reisinger, T. W. 261 

Remion, Michael C. 170 

Rice, James T. 189 

Saucier, Joseph R. 194,223,353 

Sharitz, Rebecca R. 83,92 

Sheffield, Raymond M. 122,174,306 

Sluder, Earl R. 466 

Smith, William D. 293 

Smock, L. A. 226 

Stokes, B. J. 261 

Straka, Thomas J. 106,160,279,283, 

289,293,315,450 

Swain, Kenneth M., Sr, 28 

Syme, John H. 194,202,353 

Taylor, William E. 405 

Teel, Jaime 452 

~hom~son, Michael T . 122,169 

Tippett, Mark D, 253 

Vaitkus, Milda R. 83 

Van Blaricorn, Donald 44 

Van Lear, David H. 244 

Watson, J. Craig 387,405 

Williams, James G. 44 

Williams, Thomas M. 34,64,226, 

271,437 

Yates, Harry O., 111 380 

Zarnoch, Stanley J. 179 
AI)DITIOWAI; REPORTS 

EN, David H. 1991. An insert technique for constructing artificial redcockaded wrrodpwker cavities. USDA For. Ser. SEFES Gen. Tech. Rep, SE-73. 

19 p. 

, Patrick J. Biological evaluation of southern pine beetle infestations on 

the Francis mrion Rational Forest in South Carolina--1990, Field office 

report #91-1-36, Hay 1991. 

, Patrick J., Mark Carter, Michael 6. Remion, Andrew J. Boone, and J. David 

Ruff. A cooperative study between the USDA Forest Service (Forest Health 

Unit) and the South Carolina Forestry Comission (Insect and Disease Section) 

to mnitor the rapidity of invasion of Hurricane Hugo damaged t 

bark beetles-blue stain fungi and to evaluate the potential impact of 

regeneration weevils on reforestation efforts. A collection of trip reports, 

etc .--7 separate short reports. 

CONKLE, Jennifer R. 1994. The effects of tree shelters and soil drainage class on 

the growth and survival of twelve heavy-seeded species. M.S. Thesis, 

Department of Forest Resources, Clanson University, Clemson, SC, 

COOPEMTIW EXTENSION SERVICE. 1990. Step Two--restoring the forest after 

Hurricane Hugo. EC 665. Clemson University CES in cooperation with SC 

Forestry Codssion. 6 col, brochure* 

, Harold W. Francis Marion Seed Orchard trip report to Forest Supervisor, 

Francis Marion/Sumter National Forest, Oct. 20, 1989. 2 p. 

, Donald L. 1989, Salvage and use of hurricane-damaged timber. Hurricane Hugo 

Information. Clemson University CES, Department of Forestry, 2-page flyer. 

KESSLER, George D. 1989. Decision-making guidelines for storm damaged trees. 

Storm Recovery. Clemson University CES, Department of Forestry, l-page 

flyer. 

MEYERS, J. Michael, Francisco J. Vilella, and Wylie C. Barrow, Jr. 1993. Positive 

effects of Hurricane Hugo: record years for Puerto Rican parrots nesting in 

the wild. P. 1,10 in USDI Fish and Wildlife Service Endangered Species Tech. 

Bull. 18(1). 

NODINE, Stephen K. 1992. Forest landownersr responses to Hurricane Hugo. Coll. 

of Forest and Recreation Resources, Dept. of Forest Resources, Clemson 

University For. Res. Series No. 47. 37 p. 

REHION, Mike and Andy Boone. Status report on aerial pine bark beetle 

pre-suppression surveys conducted by the South Carolina Forestry Gomission 

within the Hurricane Hugo impacted area during the period February 1990 

through January 1994. 

MMION, Mike and Andy Boone. 1992. Final summary report on the use of the South 

Carolina Forestry ~omimission~s portable sawmill within the Hurricane Hugo 

hpacted area. 

REMIOM, M. C., -drew J. Boone, David Ruff, and Patrick J. Barry. Feb. 1991. 

Field study on Hurricane Hugo d ge to loblolly pine in South Carolina. 

2 P* 

=MIOR, Michael C. 1991. Observations on loblolly pine sapling stand damaged by 

Hurricane Hugo on Manchester State Forest. Jan. 28, 1991. 

=MION, Michael C., Andrew J. Boone and Patrick J. Barry. Pine bark beetle 

suppression project for South Carolina - fiscal years 1990-1993. Dire 

mergency Supplemental Appropriations Bill. Biological evaluation of pine 

bark beetle infestations in the Hurricane Hugo area. 
SABIN, Guy E. 1989. Comparing timber prices by various methods of measure. Storm 

Recovery. Clemson University CES, Department of Forestry, 2-page flyer. 

SABIN, Guy El 1989. Tax treatment of timber damaged by Hurricane Hugo. Storm 

Recovery. Clemson University CES, Department of Forestry, 2-page flyer. 

SOUTH CAROLINA FORESTRY COMNISSION, No date. Hugo ~imber Salvage Tips. 1 page 

flyer . 

SOUTH CAROLINA FORESTRY COMISSION. Miscellaneous reports including Governor's 

Tour Summary, FEW documents, Economic Study, Timber Salvage, Wet Storage, 

Export Results with State Parts, Legislative Reports, Minutes of Executive 

Committee, Minutes of Governor's Forest Disaster Council Meetings, Mailing 

List. 

TAYLOR, William E. and Robert G. Hooper. 1991. A modification of Copeyonfs 

drilling technique for making artificial red-cockaded woodpecker cavities. 

USDA For. Ser. SEFES Gen. Tech. Rep. SE-72. 29 p. 

WADE, Dale Do, James K, Forbus, and James M. Saveland. 1993. Photo series for 

estimating post-hurricane residues and fire behavior in Southern pine. USDA 

For. Serv, SEFES Gen. Tech. Rep. SE-82. 19 p. 

The articles listed below are from: 

JOURNAL OF COASTAL RESEARCH, Special Issue #8 (Pages 1-3561, Spring 1991. Charles 

W. Finkl, Editor-in-Chief, 4310 N.E. 25th Avenue, Ft. Lauderdale, FL 33308 USA. 

BIRKEMEIER, William A*, Eugene W. Bichner, Brian L. Scarborough, Mark A. McConathy, 

and William C. Eiser. Nearshore Profile Response Caused by Hurricane Hugo. 

BRENNAN, James W, Meteorological Summary of Hurricane Hugo. 

BUSH, avid M. Impact of Hurricane Hugo on the Rocky Coast of Puerto Rico. 

CELY, John Ehmett. Wildlife Effects of Hurricane Hugo. 

COCH, Nicholas K. and Manfred P. Wolff. Effects of Hurricane Hugo Storm Surge in 

Coastal South Carolina. 

DAVIS, K. B., C, A. Barans, B. W. Stender, D. J. Schmidt, and 0. Pashuk. Shelf 

Water conditions of the South Atlantic Eight Six Weeks After Hurricane Hugo. 

GARDNER, L. R,, W. K, Michener, E, R. Blood, T. M. Williams, D. J. Lipscomb, and 

W, H. Jefferson. Ecological Impact of Hurricane Hugo--Salinization of a 

Coastal Forest. 

GARDNER, L. R., W. K. Michener, B. Kjerfve, and D. A. Karinshak. The Geomorphic 

Effects of Hurricane Hugo on an Undeveloped Coastal Landscape at North Inlet, 

South Carolina. 

GAYES, Paul T. Post-Hurricane Hugo Nearshore Side Scan Sonar Survey; Myrtle Beach 

to Folly Beach, South Carolina. 

HALL, Mary Jo and Susan D. Halsey. Comparison of Overwash Penetration from 

Hurricane Hugo and Pre-Storm Erosion Rates for Myrtle Beach and North Myrtle 

Beach, South Carolina, USA. 

HOOK, D. D., M. A, Buford, and T. M. Williams. Impact of Hurricane Hugo on the 

South Carolina coastal plain forest. 

HUBBARD, Dennis K., Karla M. Parsons, John C. Bythell, and N. D. Walker. The 

effects of Hurricane Hugo on the reefs and associated environments of 

St, Croix, U.S. Virgin Islands--a preliminary assessment. 

KATUEJA, Michael P, The effects of Hurricane Hugo on the Isle of Palms, South 

Carolina: from destruction to recovery. 
KNOTT, Donald MI and Robert M. Martore. The Short-Term Effects of Hurricane Hugo 

on Fishes and Decapod Crustaceans in the Ashley River and Adjacent Marsh 

Creeks, South Carolina. 

LENNON, Gered. The nature and causes of hurricane-induced ebb scour channels on a 

developed shoreline. 

SH, ~hristopher P. and Philip M, Wilkinson. The impact of Hurricane Hugo on 

coastal bird populations. 

NELSON, Donald D. Factors effecting beach morphology changes caused by Hurricane 

Hugo, Northern South Carolina, 

SAFFER, Herbert S, Hurricane Hugo and implications for design professionals and 

code-writing authorities, 

SEXTON, Walter J, and Miles 0. Hayes. The geologic impact of Hurricane Hugo and 

post-storm shoreline recovery along the undeveloped coastline of South 

Carolina, Dewees Island to the Santee Delta. 

SPARKS, Peter R. Wind conditions in Hurricane Hugo and their effect on buildings 

in coastal South Carolina, 

STAUBLE, Donald K,, William C. Senbergh and Lyndell 2. Hayes. Effects of Hurricane 

Hugo on the South Carolina coast. 

THIELER, E, Robert and Robert S. Young. Quantitative evaluation of coastal 

geomorphological changes in South Carolina after Hurricane Hugo. 

VAN DOLSH, Robert F. and Gregg S. Anderson. Effects of Hurricane Hugo on salinity 

and dissolved oxygen conditions in the Charleston Harbor estuary. 

WELLS, John T. and Jesse McNinch. Beach scraping in North Carolina with special 

reference to its effectiveness during Hurricane Hugo. 

The articles listed below are from: 

BIOTROPICA, Special Issue Vol. 23, No. 4. Special Issue Editors: Lawrence R. 

Walker, Nicholas V. L. Brokaw, D. Jean Lodge, and Robert B. Waide. Julie S. 

Denslow, Executive Director, Association for Tropical Biology, Department of 

Ecology, Evolution and Organismal Biology, Tulane University, New Orleans, LA 

70118. 

ASIANS, Robert A. and David N. Ewert. Impact of Hurricane Hugo on bird populations 

on St. John, U.S. Virgin Islands. 

BELLINGHAM, P, J. Landforms influence patterns of hurricane damage: evidence from 

Jamaican montane forests. 

BLOOD, E. R., P. Anderson, P. A, Smith, C. Nybro, and K. A. Ginsberg. Effects of 

Hurricane Hugo on coastal soil solution chemistry in South Carolina. 

BROMW, Nicholas V. L. and Jason S. Grear. Forest structure before and after 

Hurricane Hugo at three elevations in the Luquillo Mountains, Puerto Rico. 

BROKAW, Nicholas V. L. and Lawrence R. Walker. Summary of the effects of Caribbean 

hurricanes on vegetation, 

CHENGXIA, You and William H. Petty. Effects of Hurricane Hugo on Manikara 

biodentata, a primary tree species in the Luquillo Experimental Forest of 

Puerto Rico. 

COVICH, Alan P., Todd A. Crowl, Sherri L. Johnson, Dennis Varza, and David L. 

Certain. Post-Hurricane Hugo increases in Atyid shrimp abundances in a 

Puerto Rican montane stream. 

FERNANDEZ, Denny S. and Ned Fetcher, Changes in light availability following 

Hurricane Hugo in a subtropical montane forest in Puerto Rico. 
FRANGI, Jorge L, and Ariel E. Lugo. Hurricane damage to a flood plain forest in 

the Luquillo Mountains of Puerto Rico. 

, C. A,, T. M. Williams, and Do J. Lipscomb. Hurricane Hugo wind damage to 

southeastern U.S, Coastal forest tree species. 

GUZmN-GRAJmES, Susan M. and Lawrence R. Walker. Differential seedling responses 

to litter after Hurricane Hugo in the Luquillo Experimental Forest, Puerto 

Rico , 

LODGE, D. Jean and William H, NcDowell. Smary of ecosystem-level effects of 

Caribbean hurricanes, 

LODGE, D. Jean, F, N. Scatena, C. E. Asbury, and M. J. Sanchez. Fine litterfall 

and related nutrient inputs resulting from Hurricane Hugo in subtropical wet 

and lower montane rain forests of Puerto Rico. 

LYNCH, James F. Effects of Hurricane Gilbert on birds in a dry tropical forest in 

the Yucatan Peninsula. 

PARROTTA, John A, and D, Jean Lodge. Fine root dynamics in subtropical wet forest 

following hurricane disturbance in Puerto Rico. 

REAGAN, Douglas P, The response of Ano2is lizards to hurricane-induced habitat 

changes in a Puerto Rican rain forest. 

REILLY, Anne E. The effects of Hurricane Hugo in three tropical forests in the 

U.S, Virgin Islands, 

SANFORD, Robert L., Jr., William J. Parton, Dennis S. Ojima, and D. Jean Lodge. 

Hurricane effects on soil organic matter dynamics and forest production in 

the Luquillo Experimental Forest, Puerto Rico: Results of simulation 

modeling, 

SCATENA, F. N. and M. C. Larsen. Physical aspects of Hurricane Hugo in Puerto 

Rico . 

STUDIER, P, A., J. M. Meillo, R. D. Bowden, M. S. Castro, and A. E. Lugo. The 

effects of natural and human disturbances on soil nitrogen dynamics and trace 

gas fluxes in a Puerto Rican wet forest. 

TANNER, E, V. J,, V. Kapos, and J. R. Healey. Hurricane effects on forest 

ecosystems in the Caribbean. 

WAIDE, Robert B. The effect of Hurricane Hugo on bird populations in the Luquillo 

Experimental Forest, Puerto Rico. 

WAIDE, Robert B. Summary of the response of animal populations to hurricanes in 

the Caribbean, 

WALKER, Lawrence R. Tree damage and recovery from Hurricane Hugo in Luquillo 

Experimental Forest, Puerto Rico. 

WALKER, Lawrence R,, D. Jean Lodge, Nicholas V. L. Brokaw, and Robert B. aide. An 

introduction to hurricanes in the Caribbean. 

WHIGHW, Dennis F,, Ingrid Olmsted, Edgar Cabrera Cano, and Mark E. Harmon. The 

impact of Hurricane Gilbert on trees, litterfall, and woody debris in a dry 

tropical forest in the northeastern Yucatan Peninsula. 

WILL, Tom, Birds of a severely hurricane-damaged Atlantic Coast rain forest in 

Nicaragua, 

WILLIG, Michael R. and Gerardo R. Camillo. The effect of Hurricane Hugo on six 

invertebrate species in the Luquillo Experimental Forest of Puerto Rico. 

WOOLBRIGHT, Lawrence L, The impact of Hurricane Hugo on forest frogs in Puerto 

Rico . 
Follow 

Pesticide 

Label Exactly 

This publication reports research involving pesticides. It does not 

contain reco-ndations for their use, nor does it imply that the uses 

discussed here have been registered. All uses of pesticides must be 

registered by appropriate State andlor Federal agencies before they 

can be recommended. 

CAUTION: Pesticides can be injurious to humans, domestic animals, 

desirable plants, and fish or other wildlife-if they are not handled or 

applied properly. Use ail pesticides selectively and carefully. Follow 

recommended practices for the disposal of surplus pesticides and 

pesticide containers. 

Haymond, Jacqueline L.; Harms, William R., eds. 1996. Hurricane Hugo: 

South Carolina forest land research and management related to the storm. 

Gen. Tech. Rep. SRS-5. Asheville, NC: U.S. Department of Agriculture, 

Forest Service, Southern Research Station. 540 p. 

This compilation includes 69 published and previously unpublished articles 

relating to the effects of Hurricane Hugo, a Category 4 storm, on forests 

primarily in South Carolina. The articles record the response of the forests to the 

storm and the activities of those who care for these forests. Broad topics include 

historical background, damage assessment, forest restoration, and evaluation of 

recovery programs. 

i 
The Forest Service, U.S. Department of 

Agriculture, is dedicated to the principle of multiple 

use management of the Nation's forest resources for 

sustained yields of wood, water, forage, wildlife, and 

recreation. Through forestry research, cooperation with 

the States and private forest owners, and management 

of the National Forests and National Grasslands, it 

strives-as directed by Congress-to provide 

increasingly greater service to a growing Nation. 

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prohibits discrimination in its programs on the basis of 

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political beliefs, and marital or familial status. (Not all 

prohibited bases apply to all programs). Persons with 

disabilities who require alternative means for 

communication of program information (braille, large 

print, audiotape, etc.) should contact the USDA Office of 

Cornmuriieations at (202) 720-5881. To file a complaint, 

write the Secretary of Agriculture, U.S. Department of 

Agriculture, Washington, DC 20250, or call (202) 720- 

7327. USDA is an equal employment opportunity 

employer.