April 1979 

Southeastern Forest Experiment Station 

Asheville, North Carolina 
CONTENTS 

Pugr 

INTRODUCTION I 

1 

Who will provide the information'? ................................................................................... 2 

Purpose of this paper 2 

BACKGROUND ................................................................................................................ 2 

History of forest survey in Southeast 

Traditional timber inventories 

Resources Planning Act-a tu 

Multiresource pilot study in S 

Four ways to gather additional information 

Consulting with specialists and experts 

Adapting existing inventory method 

THE SOUTH CAROLINA PILOT STUDY 

Special features of the pilot study 

Steering committee 

South Carolina study plan 

Inform and involve 

Use interactions 

Information management 

EVALUATION SUBJECTS 

Timber ....................................................................................................................... 2 1 

Soils ......................................................................................................................... 24 

Ecology ................................................................................................ 

Botany ....................................................................................................................... 25 

Use interactions 

Information management 

The role of tech 

DISPLAY OF RESULTS-EXAMPLES 27 
ANALYSIS OF THE DATA ............................................................................................... ,.48 

Developments underway .............................................................................................. ..48 

THE FUTURE ..................................................................................................................... 49 

Improve each new inventory started 

Estimating future needs 

The 1990 Assessment 

Gathering additional i ...................................... 

Reporting results-fu 

LITERATURE CITED ....................................................................................................... .52 

APPENDIX ..................................................................................................................... 53 

Processing systems ....................................................................................................... 66 
New ComcepQ ffor ff orest Survey 

Joe F? McClure, Principal Resource Analyst 

Noel D. Cost, Resource Analyst 

and 

Herbert A. Knight, Resource Analyst 

Asheville. North Carolina 

INTRODUCTION 

The way a nation manages and uses its 

natural resources largely determines its economic 

strength, the integrity and quality of its environment, and the satisfaction and well-being of its 

people. Finite resources such as oil and minerals 

are being exhausted, forcing us to rely on renewable resources-those that can be reproduced and 

perpetuated. America's forest and range resources are good examples. 

As America increases its dependence upon 

forest and range resources, there is a growing 

need to understand the complex interactions 

among their many uses. At issue is the optimum 

allocation of these resources among the various 

uses. The public and its planners and decisionmakers must have adequate. up-to-date information if a rational course of action is to be charted. 

This Paper describes an approach and system for 

obtaining the information. 

NEED FOR BETTER RESOURCE 

INFOR!vlATION 

The Narion ha5 adopted a policy of mult~ple 

use of its forest and rangelands. Strong public 

pressures are being applied by special interest 

groups to favor one use over another. There is an 

acute need for better resource information to help 

resolve these complex resource issues. 

Multiple-use management requires a balance 

of multiresource information. While conventional 

forest inventories have provided a wealth of information on timber, they have not been designed to 

inventory the forests from the standpoint of 

multiple use. From this standpoint, the species 

composition, quantity, and spatial arrangement of 

the lesser vegetation become as important as the 

trees. Whereas rough, rotten, hollow, or dead 

trees might have little or no value fortimher, these 

same trees are valuable for wildlife habitat. 

The idea put forth in this Paper is to build 

multiresource inventories on the foundations already established for timber. The proposal is to 

expand the scope of conventional timber inventories to include the species composition, 

quality, and spatial arrangement of total biomass, 

and nontimber attributes of each significant plant 

community. The primary objective of these inventories would be to monitor the successional 

stages of each significant plant community in both 
the presence and absence of man's intervention. 

Because of the magnitude of the inventory task. 

we envision continued reliance upon sampling as 

opposed to mapping. Nevertheless, ecological information obtained from the inventories would 

contribute greatly to in-place use and management of the resources. 

WHO W1L.L PROVIDE THE INFORMATION? 

Within the research arm of the Forest Service, Renewable Resources Evaluation (RRE) is a 

logical candidate for assuming the added inventory responsibilities. RRE. formerly known as 

Forest Survey. dates from about 1930 (Doig 

1976). Chartered by the McSweeney-McNary 

Forest Research Act of 1928, Forest Survey conducted the conventional forest inventories referred to earlier. Passage of the Forest and Rangeland Renewable Resources Planning Act (RPA) of 

1974 broadened the scope of Forest Survey activities. RRE was directly involved in the initial 

implementation of RPA. 

Organized into regional Work Units. RRE 

possesses a wealth of experience in both inventory and resource analysis. In response to the 

RPA requirements, the RRE Work Unit in the 

Southeast proposed procedures for expanding its 

Forest Survey activity into a multiresource inventory. The Forest Service authorized RRE to test 

these procedures in a pilot study during the fifth 

inventory of South Carolina. 

PURPOSE OF THIS PAPER 

The purpose of this Paper is threefold: (I) to 

summarize the background of RRE's forest inventory activity in the Southeast, (2) todocument 

an approach to multiresource inventories, and 

(3) to report on the status of the South Carolina 

Pilot Study. 

BACKGROUND 

The McSweeney-McNary Forest Research 

Act of 1928 recognized the importance of timber 

resource inventories. Section 9 of this Act 

authorized and directed the Secretary of Agriculture to make and keep current ". . . a comprehensive survey of the present and prospective 

requirements for timber and other forest products 

in the United States and its tenitories and possessions, and of timber supplies including a determination of ways and means to balance the timber 

budget of the United States." In response to this 

Act. the Forest Service orzanized the Forest 

Survey. 

HISTORY OF FOREST SURVEY 

IN SOUTHEAST 

In the Southeast. Forest Survey began statewide forest inventories in Florida and Georgia 

about 1933 (Knight 1972). The inventory method 

was patterned after procedures used in Sweden 

and Finland. Crews followed compass lines 

spaced 10 miles apart and sampled 114-acre plots 

at intervals of 660 feet along these lines. Within 

the forest. crews classified each plot as to forest 

type and stand size. tallied the trees by species 

and size to determine volume, and bored selected 

sample trees to determine diameter growth rates. 

A field canvass of primary wood-using plants provided information for estimating timber cut. 

Data collection in this initial inventory of the 

Southeast extended over 7 years and was completed in Virginia in 1940. After completion of the 

initial inventory of the Region. Forest Survey 

stopped plot sampling during World War I1 hut 

continued to compile. analyze. and report information. Since computers were not yet available, 

most of the computations were performed with 

desk calculators. Nevertheless. these efforts provided planners and decisionmakers with their first 

systematic measure of the timber resource for an 

entire Region. 

In 1946, Forest Survey began its second inventory of the Southeast in South Carolina. This 

inventory was completed in Virginia in 1957. 

Methods differed significantly from those used 

the first time around. Aerial photographs. then 

available for most areas, were used to interpret 

land use and to select and locate ground sample 

plots. Crews located and measured 115-acre 

sample plots randomly selected and systematically distributed by grids printed on aerial photographs. In addition to classifying areas and counting and boring trees, crews tallied stumps of 

recently cut trees to estimate timber removals. 

Again. canvasses of wood-using plants provided 

for breakdowns of the removals by product. Special studies provided utilization factors needed to 

relate the removal estimates to product output. 

A primary objective of the second inventory 

was to determine trends in the timber resource. 

For the first time. crews marked anddescribed the 
locations of the sample plots so they could be 

rrmeasured. Experience had shown that permanent sample plots were needed to improve estimates of timbel- growth. mortality. and removals 

and to monitorchanges in the resources. 

By the midfifties. Forest Survey information 

had been accumulated fol- most of the country. 

With this information, the Forest Service made 

the most extensive review of the Nation's timber 

resources ever undertaken. The Forest Service 

published the results of this review in a 713-page 

repol-t. "Timber Resources for Arnericz's 

Future" (USDA FS 1958). 

Without any delay, Forest Survey began its 

third inventory of the Southeast in 1957: the job 

was completed in 1966. The basic theory of point 

sampling had advanced to accepted application. 

lnstead of tallying all trees on a fixed-area sample 

plot, an angle-gage was used to select sample 

trees based on tree diameter and distance from 

plot center (Grosenbaugh 1952). Crews tried two 

modified versions of this new sampling technique 

during the third inventory cycle. In South Carolina, Florida, Georgia, and the Coastal Plain of 

North Carolina, crews superimposed a single 

basal area (BA-10) plot over each of the old 115- 

acre plots. In all subsequent inventory work, 

crews installed a 10-point cluster of BA-37.5 plots 

at each of the locations. The latter plot design 

significantly reduced the number of sample locations required to achieve the desired minimum 

accuracy. 

In the third inventory, emphasis was placed 

on obtaining more reliable measures of the components of change-timber growth, mortality. 

and removal. While the remeasurement opportunity afforded by permanent plots was under 

study, crews continued to bore trees for diameter 

growth rates and to make stump counts for estimating removals. By 1959, most of the technical 

problems had been worked out and thereafter 

growth, mortality, and removal were estimated 

largely from remeasurement data. 

Other significant sampling procedures introduced toward the end of the third inventory cycle 

included (I) a proportionate distribution of the 

sample plots across all land uses to enhance the 

measure of land-use change, and (2) a tree-volume 

subsample to improve volume prediction equations. The computer was fast replacing desk calculators and tabulators in processing the data. 

The Forest Service undertook another comprehensive review of the Nation's timber resources in the early sixties. Again, Forest Survey 

data provided the basis for the appraisal. This 

appraisal focused on trends and projections of 

prospective timber supplies. "Timber Trends in 

the United States" (USDA FS 1965). 

The fourth inventory of the Southeast was 

begun in 1966 and completed in 1977. During this 

fourth cycle. Forest Survey completed its shift to 

the 10-point cluster of 8.4-37.5 plots to determine 

inventory volume. Estimates of timber growth. 

mortality. and removals were based entirely on 

remeasurement data. Forest Survey continued its 

tree-volume subsample, timber utilization 

studies. and timber product output studies. The 

latter studies are conducted through cooperative 

efforts with the individual States. In 1968. starting 

with the fourth inventory of Florida, Forest Survey intensified its land-use sample both on photos 

and on the ground from a grid of single points to a 

grid of 16-point clusters. 

During the early seventies, the Forest Service made still another appraisal of the Nation's 

timber resources. This appraisal occurred at a 

time when forest policies and forestry practices 

were being seriously questioned and reexamined. 

The appraisal focused on the condition of the 

forests and the identification of opportunities 

available for increasing prospective timber supplies, "The Outlook for Timber in the United 

States" (USDA FS 1973). 

Throughout the first four inventory cycles, 

demand for Forest Survey information on the 

Southeast increased. While the primary objective 

of Forest Survey was to provide data for the national appraisals, State and local uses of the data 

further supported the need for the program. Because of frequent requests for data, Forest Survey 

established a comprehensive data bank and information retrieval system in 1970. Called Forest 

Information Retrieval (FIR). the system provides 

for rapid compilation of forest and timber statistics on a custom basis and at a nominal cost 

(McClure 1972). With FIR, information can be 

compiled in three ways: (I) whole counties 

grouped together, (2) circillar areas around a rpecified point, or (3) irregular boundaries within a 

closed traverse of short-line segments. 

Increased State and local use of the information also generated strong pressure to shorten 

the inventory cycles, intensify the sampling, and 

collect additional information. A National Handbook establishes the goals in each of these areas 

by specifying information required for national 

appraisals, minimum accuracy standards, and the 

periodicity of the inventories. Funding and man- 
power limitations have at times extended the inventory cycles beyond the established goals. At 

other times, cooperative assistance has enabled 

Forest Survey to finish early. 

TRADITIONAL TIMBER INVENTORIES 

All the inventories mentioned thus far 

focused primarily on timber. While they provided 

the official estimates of total forest acreage. detailed classifications and measurements were generally confined to lands classified as commercial 

timberland. Traditional area classifications included forest type, site class, stand size and age. 

stocking condition, and ownership. In the more 

recent inventories, additional area :.lassifications 

have included stand origin, stand hit'-y, physiographic class, slope, aspect, and treat!, opportunity. 

The inventorieb have pr-ovided tree counts 

and their associated volumes by species, diameter. and quality along with their growth, mortality. and removal rates. Together, the area 

'.I, d~sifications, . ' tree counts, and volume estimates 

have adequately described the makeup of the 

forest resources from the standpoint of timber. 

The inventories have largely ignored lesser vegetation and any attributes unlikely to influence 

timber production. 

RESOURCES PLANNING ACTA TURNING POINT 

A growing awareness of the complex interactii~ns among the many forest uses together with 

a recognition of acute problems in the budgeting 

process led Congress to pass the Forest and 

Rangeland Renewable Resources Planning Act 

IRPA) of 1974. RPA directed the Secretary of 

Agriculture to prepare a Renewable Resource 

Assessment not later than December 31, 1975, to 

be updated during 1979, and each loth year thereafter. RPA stated the Assessment ". . . shall include but not be limited to: 

(I) An analysis of present and anticipated 

uses, demand for, and supply of the renewable 

resources of forest, range, and other associated 

lands with consideration of the international resource situation, and an emphasis of pertinent 

supply and demand and price relationship trends: 

(2) An inventory. based on information developed by the Forest Service and other Federal 

agencies, of present and potential renewable resources, and an evaluation of opportunities for 

improving their yield of tangible and intangible 

goods and services. . ." 

RPA superseded the McSweeney-McNarv 

For-est Research Act of 1928 and has been described as a hold new experiment in resolving 

resource issues. In addition to its requirement for 

periodic Assessments, the Act directed the Secretary of Agriculture to develop a long-range Program for the Nation's renewable rcsources that 

will assure an adequate supply of forest and range 

resources in the future while maintaining the integrity and quality of the environment. The Act 

called for the Program to be prepared by December 31. 1975, subject to revision in 1980 and ever-y 

5 years thereafter. 

Because of the short time available, the 1975 

Assessment and Program were prepared from 

existing data obtained from the Forest Service 

and other agencies. In developing the Program. 

the Forest Service grouped all its activities into 

six resource systems: (I) outdoor recreation and 

wilderness, (2) wildlife and fish habitat. (3) range. 

(4) timber, (5) Land and ujater, and (6) human and 

community development. After analyzing data 

available for each resource. the Forest Service 

developed several broad alternative goals for 

each system. The goals ranged from less than the 

current trend in activities to well above current 

program levels. 

For each goal, the agency developed targets 

of measurable outputs of goods and services such 

as acres of wilderness, animal-unit-months of 

grazing, or board feet of timber. Each target was 

translated into specific activities needed to meet 

that target, by relating inputs of dollars and 

materials to outputs of resources, benefits, or 

services. This procedure created more than 5,000 

possible combinations of activities from which to 

select a unified pl-ogram. From these possible 

combinations, the agency developed eight alternative programs for public review. These eight 

altel-native programs offered a variety of reasonable options, ranging fi-om a reduction in present 

levels of operation to intensive management of 

vit-tually all activities. After subjecting the eight 

alternatives to extensive public review, the 

Recommended PI-ogram was appr-oved by the 

Secretary of Agriculture and transmitted to Congress by the President in accordance with RPA. 

The final chapter in the first Assessment addressed the subject of scientific information and 

data needs. The Assessment acknowledged that ... ~nventories of forest, range and inland water 

resources are basic to almost any decision con- 
cerning the management or use of these resources." The Assessment further acknowledged 

the contributions from Forest Survey and pointed 

out needs to accelerate the inventory cycles, intensify the samples to provide more precise local 

data, and expand the Forest Survey to include 

forest and range [resources other than timber. The 

Recommended Program called for the Forest 

Service to expand its research activities in several 

areas, including "resource inventory and evaluation." The agency changed the name of Forest 

Survey to Renewable Reso~~rces Evaluation 

(RRE) and began techniques research on the 

problems associated with multiresource inventories. 

MULTIRESOURCE PILOT STUDY 

IN SOUTH CAROLINA 

The RRE Work Unit in the Southeast was 

authorized to test its proposed multiresource inventory procedures during the fifth forest inventory of South Carolina. South Carolina has a representative range of the forest conditions found in 

the Region. The State contains a portion of the 

Southern Appalachian Mountains. a large area of 

rolling Piedmont conditions laced with narrow 

flood plains, an extensive belt of sandhills, and 

a broad expanse of flat coastal plain interspersed with swamps and broad flood plains. For 

inventory purposes, the State is divided into three 

Survey Units: (I) Southern Coastal Plain. (2) 

Northern Coastal Plain, and (3) Piedmont. The 

mountains occur in the Piedmont Unit and the 

sandhills occur in both Coastal Plain Units. 

Fieldwork began in South Carolina in April 

1977 and was completed in Seprember 1978. The 

new data for the Piedmont became available in 

late 1977. and some of the basic forest statistics 

have been published (Snyder 1978). Currently, 

RRE is subjecting the data to validation analysis 

from the standpoints of both timber and nontimber interests. Plans call for a comprehensive 

and balanced analysis of all the data at the State 

level. 

APPROACH 

The approach taken by Renewable Resources Evaluation was to expand the tirnberoriented inventory into a broader. multiresource 

inventory by making maximum use of established 

inventory methods and providing an orderly transition. The first majol- task was to explore possibilities and select an appropriate course of action. 

The plan that evolved was described in a prorpectus, "Evaluating Renewable Forest and Rangeland Resources in the Southeast." 

Experience with timber inventories provided 

us with a good understanding of the problems 

associated with resource evaluations. There are 

certain similarities in the ways different renewable resources can be inventoried. Hence, computer and data management systems. maps, aerial 

photographs, coding systems, and field-datacollection operations designed for timber inventories could likely be used with minor modifications in dealing with the nontimber resources. It 

was obvious, however, that certain aspects of the 

multiresource inventory would require highly 

specialized methodology and techniques. 

DEFINING RENEWABLE RESOURCES 

One important planning element was a definition and understanding of what should be included as Renewable Resources. Preliminary 

work by the National RPA assessment team produced a working definition and listing of resources 

to be included: 

Rrnr~rjrrhle resurrrcrs-Those resoul-ces 

whose use can he maintained indefinitely if the 

use rate does not exceed the ability to renew the 

supply. Renewable resoul-ces for which the 

Forest Service has some responsibilities include: 

I. Timber 5. Water 

2. Range 6. Recreation 

3. Wildlife 7. Wilderness 

4. Fisheries 8. Land 

Forest and rangeland are two major land-use 

classes which were specifically identified by the 

Resources Planning Act. Therefore, they were of 

par-ticular impot-tance to Forest Service resource 

evaluation5 and needed to be clearly defined. 

Again, preliminary work done on the Assessment 

produced useful definitions for these key classes 

of land use.' 

Forrsr 1ritid.-Land at least 10 percent occupied by forest trees of any size or formerly having 

had such tree cover and not currently developed 

for nonforest use. 

R~r17grlu11cl.-Land on which the native vegetation (climax or natural potential) is predominantly grazses. grasslike plants. fol-by. or shrubs 

'On July I?. 1976. the Forest Service and Soil Cunsrrvation Service jointly agreed on a common set of definirions 

which differ slightly from those presrnrrd here. 
suitable for grazing or browsing, and present in 

sufficient quantity to justify grazing or browsing 

use. Rangelands include grasslands, savannas, 

shrublands. most deserts. tundra, alpine communities, coastal marshes, and wet meadows. 

The Forest Service elected to place renewable resources into six major resource systems. 

which provided additional structure for a resource evaluation. For inventory purposes, the 

definition of a resource system and the six major 

resource systems were:' 

Resource system.-A major Forest Service 

endeavor, mission-oriented, which fulfills statutory or executive requirements and indicates the 

collection of activities from the various operating 

programs required to accomplish the agency 

mission. 

I. Outdoor Recreation and Wilderness 

2. Wildlife and Fish Habitat 

3. Rangeland Grazing 

4. Timber Resource 

5. Land and Water 

6. Human and Community Development 

In addition to the six major resource systems. 

the Forest Service identified eight major uses of 

forest and rangeland: 

I. Wildlife 

2. Grazing 

3. Outdoor Recreation 

4. Timber 

5. Water 

6. Wilderness 

7. Other Uses (parks. scenic rivers, historic 

sites. etc.) 

8. Minerals 

Within the broad areas covered by the six 

major resource systems and eight major-use categories, there are numerous individual renewable 

resource subjects which relate in one way or 

another to the general concepts of renewable 

forest and rangeland resources. The question 

was: Which subjects would be appropriate for 

RUE to deal with and how could this be done'? 

FOUR WAYS TO GATHER 

ADDITIONAL INFORMATION 

The approach taken by RRE was based on 

several general concepts. The total land and water 

area of each county and State can be separated 

into land-use classes, each with unique and mean- 

'For its 1980 RPA Program, the Forest Scl-vice is using I I 

resource elements instead of these 6 resource systems. 

ingful characteristics. Each class can be further 

stratified into subclasses that offer relative homogeneous resource-use opportunities. For example, forest lands can be stratified by forest 

type. stocking, ownership. site class. stand age. 

etc.; marshlands can likewise be stl-atitied by 

characteristics such as vegetation type. fresh or 

salt water, size of marsh. coastal or inland. etc. 

Water can be separated into streams and lakes 

and further stratified by width or size. 

Assignment of land-use classes offers two 

distinct advantages: (I) RRE's permanent sample 

grid points falling in each use class can be revisited. subsampled. or otherwise used as a proportionate sample of the entire land base. (2) 

Changes in act-eage in use classes can best be 

measured using a permanent grid of samples in all 

land-use classes. The land-use classes now recognized in the five Southeastern States are: 

I. Commercial Forest 

2. Productive-Reserved Forest 

3. Other Forest (formerly Unproductive 

Forest) 

4. Cropland 

5. Improved Pasture 

6. Natural Range 

7. Idle Farmland 

8. Other Farmland (including farmsteads) 

9. Urban and Other 

10. Marsh 

I I. Water 

Permanent grid points falling in each of the 

above land-use classes are further classified by 

using aerial photographs, direct observation from 

aircraft, or ground checks. Points on forest and 

rangeland are gene]-ally visited on the ground and 

numerous measurements and classitications are 

recorded. Points in other land-use classes are 

simply verified, and a minimum of data is 

recorded. 

Four general methods appeared to be available for gathering additional resource information: 

I. Taking additional measurements and observations at the existing permanent grid samples 

established in all land-use classes in the Southeast. 

2. Other sources of information taken from 

maps and overlays or sample data located by geographic coordinates could be combined with inventory sample data to produce a more complete 

composite description of the area sampled. This 

type information can also be summarized by geographic areaand used to supplement the analysis. 
3. Special sampling schemes could be developed using some combination of remote sensing, conventional or high-altitude aerial photography, direct aerial observation. and ground 

sampling. 

4. Available information could be obtained 

in essentially final form from other sources. Statistics on hunting and fishing. populations. employment, and payrolls, for example, can be obtained in this manner. 

With at least four possible ways to collect or 

otherwise acquire additional data on renewable 

resources. the question became one of where to 

start. We decided to concentrate on the first 

method. The reasoning was that it would take a 

complete inventory cycle of8 to 10 years togather 

new data uniformly across the Southeast, and that 

the process should begin immediately. The other 

methods could be used to gather broad coverage 

information in a relatively short time. Another 

consideration was that most of the information 

needs already identified would require ground 

sampling. 

CONSULTING WITH SPECIALISTS 

AND EXPERTS 

When the RPA passed in 1974, Forest Survey 

had been conducting timber inventories in the 

Southeast for over 40 years. Because timber had 

been emphasized, the project team contained 

specialists in mensuration, timber-resource analysis, sampling, computer science. and timber 

utilization. The responsibilities associated with 

the RPA created a need for additional expertise in 

specialties such as wildlife, range, recreation, 

ecology, hydrology. and soils. In the long term, 

this need for additional expertise could be satisfied by adding specialists to the project staff, but 

an alternative shot-t-term solution was necessary. 

The need to gain expertise without adding 

specialists to the project was partially satisfied by 

selected reading and study of nontimber resources. The more important source, however, 

was through contacts with specialists and experts 

at research stations. universities, State agencies, 

other Federal Agencies, and throughout the 

Forest Service. 

Help of many individuals was enlisted at a 

variety of seminars, meetings. and programs attended by RRE scientists. Specialists in wildlife. 

range. recreation. hydrology. soils, ecology, etc.. 

were asked to provide suggestions for improving 

the inventory in their particular area of expertise. 

The same individual:. were asked to review new 

procedures, to comment on direction. and. 

finally. to visit inventory crews at work in the 

field. Although each individual's contribution 

may have seemed small. the aggregate contribution ofdozens of individual scientists. specialists. 

and experts was vital in developing an experimental multiresource inventory in South Carolina. 

ADAPTING EXISTING INVENTORY 

METHODS 

To expedite the development of a multiresource inventory. the RRE staff searched for 

nontimbel- inventory methods that were already 

operational. It was obvious that there would not 

be enough time to develop and test a completely 

new set of nontimbel- inventory methods and still 

meet the 1980 Assessment target dates. The 

scarch for proven methods was pal-tially successful. The published works of MacAnhur and 

MacArthur (1961) provided several useful concepts and techniques which wet-e adapted into a 

procedure for measuring vegetative profiles. The 

procedure developed in Mississippi (Lentz 1974) 

for ranking wildlife habitat pt-oved valuable and 

added to the inventory. Field procedures used by 

the Tennessee Valley Authority, Norris. Tennessee, were adapted for measuring and coding nontimber variables. The forest range inventory procedures developed in Louisiana (Pearson and 

Sternitzke 1974) were modified slightly and added 

to the inventory. Numerous other procedures 

were gleaned from the literature. A -d finally. a 

number of experimental concepts were added on 

a test basis to achieve a well-balanced coverage of 

the nontimber resources. As the South Carolina 

Pilot Study progressed and other specialists reviewed the fieldwork. a number of additions were 

made to the inventory. 

THE SOUTH CAROLINA 

PILOT STUDY 

In 1976. South Carolina was selected as one 

of the six pilot study areas in the United States to 

be highlighted in the 1980 RPA Assessment. The 

specific mission in South Carolina was to develop 

and test procedures for multiresource inventories 

(USDA FS 1977). RRE in the Southeast had been 

involved in a number of nontimber resource 

studies and had a general conception of the additional inventory needs. The pilot study, therefore, 
permitted the development and testing of a num- new procedure was to quantify and describe a11 

ber of new procedures. There were several the vegetatiofl in South Carolina's fol-ests. The 

I-easons why South Carolina was an excellent theory was that the vegetative makeup of difplace to test new inventory methods: ferent forest conditions reflects the basic ecologiI. The State Forester and the South Care. cal relationships vital to multiresource evalulina Fol-estry Commission were expected to fully ations. 

support this inventory. 

2. The forest industry in South Carolina was 

diversified and its reaction would be representative offor-est industries throughout the Southeast. 

3. The State Extension Forester had indicated his intention of fully supporting and heing 

involved in the new inventory. 

4. Station Research Work Units within the 

State could provide some expert assistance 

needed to bl-oaden the survey. 

5. The South Carolina Wildlife and Marine 

Resout-ces Department had indicated considerable interest in working with RRE in several 

ways. 

6. South Carolina is centrally located in the 

Southeast and has agood reproentation of southeastern forest conditions. 

7. South Carolina is the smallest of the five 

Southeastern States, and can be inventoried in a 

I-easonably short time. Its three Survey Units 

offered thl-ee separate oppot-tunities to try new 

procedures. 

SPECIAL FEATURES OFTHE 

PILOT STUDY 

A SHOWCASE INVENTORY 

Since the South Carolina multiresource inventory was brand-new, it became a showcase as 

soon as word about it spread. Many inquiries 

about procedures were received long before the 

sampling methods and procedures were outlined 

in the field guide. Due to the enthusiasm and 

interest in this new inventory, a number of individuals were invited to review the procedures on 

the ground. Representatives from other RRE 

projects, States. Forest Service Region 8 (R-8). 

Southeastern Area State and Private Forestry 

(SA), National Aeronautics and Space Administration. and Soil Conservation Service visited 

sample plots near Spartanburg. South Carolina. 

Discussion there centered on sampling procedures. plot layout. kinds of information heing 

collected, and reasons for including items in the 

study. Our goal was to obtain critical review of 

our procedures while we were keeping interested 

specialists informed. Many suggestions and idells 

evolved from the mixing of different disciplines 

on the demonstration plots. For example, soil 

experts visiting the demonstration plots showed 

us how slope length should be evaluated. Field 

vrocedures were later modified to aoolv .. , the new 

concept across the entire State. This review gen- Since the sampling needs for nontimber reerated a lot of support for RKE and involved soul-ces and analytical methods were uncertain, specialists who would be helpful in the future. orocedures were develooed to take full advantage 

of 4,230 permanent forest sample locations estab- STEERING lished during the orevious - inventorv of South 

Carolina in 196&68. Consultations with experts 

on soils, hydrology, range, wildlife. ecology, and 

outdoor recreation prior to thc pilot study revealed that many data elements already being 

collected for timber inventories were equally useful in assessing nontimber attributes (Sternitzke 

and Pearson 1974). We looked particularly for 

such link variables, which are indicative of more 

than one Iresource condition. This approach permitted us to make additions instead of building an 

entirely new system. Classifications and measurements made at each sample location focused on 

special infot-mation needs for evaluating wildlife 

habitat. recreation use, range suitability. water 

To encourage formal communication within 

the Forest Service as well as to provide direction. 

an in-Service Steering Committee was formed. 

Its three members were: Let-oy Jones. SA, 

Atlanta; Jim Sabin, National Fot-est System. 

Atlanta; and Dave Olson. Southeastern Station 

(SEFES). Asheville. Representation from all 

arms of the Forest Service pt-ovided a coordinated 

reseal-ch effort. The Steering Committee prepared a study plan. helped arrange for external 

involvement, monitored progress of the inventory, assisted in analysis and evaluation, and assisted in preparation and review of the South 

Carolina reports. 

quality, erosion hazards related to fc~t-estry p1.a~- 

tices. and the use-interaction relationshios associ- SOUTH CAROLINA STUDY PLAN . ~ ~~ 

ated with the numerous forest conditions oc- The study plan that the Steering Committee 

cul-ring throughout the State. A majot-goal in the prepared outlined the objectivr of the pilot 

8 

study, provided a schedule of both In-Service and 

exter-nal involvement, and discussed the types of 

reports that would be produced. The study plan 

named experts and specialists from the three arms 

of the Forest Service who could provide guidance 

and technical expertise. The specialists listed 

were: 

Fot-est Resource Planning: 

James Wells SA 

Recreation: 

David Scott R-8 

Nathan Byrd SA 

Kenneth Cordell SEFES 

Soils: 

John Corliss R-8 

Carol Wells SEFES 

Wtldltfe: 

Malcolm Edwards R-8 

Nathan Byrd SA 

Michael Lennartz SEFES 

Rtchard Harlow SEFES 

Robert Hooper SEFES 

Willlam Moore SEFES 

Range: 

Robert 

Gashwilder 

Nathan Byrd SA 

Clifford Lewis SEFES 

Hydrology: 

George Dissmeyer SA 

James Douglass SEFES 

Ecology: 

Stephen Boyce SEFES 

Botany: 

Levester 

Pendergrass R-8 

Andrew 

Robinson SA 

Specialists ft-om R-8 and the SA (I) reviewed 

data being collected and made recommendations 

for changes. (2) field-tested the feasibility of 

collecting new data, and (3) analyzed and evaluated data collected. Specialists from the Southeastern Station were called upon as needed to 

ensure that the experimental data were being 

collected in a scientifically acceptable manner. 

They were also given opportunities to assist in the 

analysis and reporting. 

IPjFORM AND INVOLVE 

Information about the South Carolina Pilot 

Study wis disseminated to individuals and groups 

in three ways: (1) seminars at univercities. (2) field 

demonstration plots. and (3) wol-k meetings fur all 

experts and specialists identified in the study 

plan. The purpose of a work meeting was to review progress, explore possibilities of analyzing 

data, and seek ways to improve future inventories. 

Regardless of the source. each suggestion or 

new idea was considered. If it fell within the scope 

of the South Carolina Pilot Study and was suited 

to out- type of sampling. it was incorporated into 

the study. 

SEMINARS 

Seminars were conducted at Clemson University, Virginia Polytechnic Institute and State 

University (VIP & SU), University of Georgia, 

Duke University, and University of Florida. We 

hoped to find professors and graduate students 

who could devote full time to items of highest 

priority. These high-priority items included wildlife habitat ranking, forest range, soil erodibility 

characteristics, diversity, fisheries, and biomass. 

Both Clemson University and VPI & SU 

showed great interest in the inventory, and cooperative research agreements were made to 

meet several PI-essing needs. The main objectives 

in the cooperative agreements with Clemson University were: (I) To assess the potential of the 

South Carolina multiresource system to supply 

data useful in recreation planning. (2) To provide 

a method and related criteria for the inventorying 

of nondeveloped, rural recreation resources 

through the RRE field crews. Initially, the agreement was set up to run I year, but the preliminary 

results for the Piedmont Unit looked so promising 

that a I-year extension was granted to Clemson 

University. 

The cooperative agreement signed with VPI 

& SU had two major purposes: 

1. To review the sampling techniques and 

habitat criteria being developed for wildlife habitat analysis. 

2. To review the habitat evaluation procedure used for ranking wildlife habitat 

into suitability classes according to 

potential value. 

The agreement with VPI & SU will run for approximately 2% years. 
JOINT RESEARCH PROJECTS 

Sometimes it is highly desirable for two units 

to join forces on a research problem. When this is 

done, each unit can do what it does best. 

Presently. RRE has made two joint research 

agreements with other units to work on problems 

related to the South Carolina Pilot Study. The first 

agreement, with the Southeastern Station's Endangered and Threatened Wildlife research unit at 

Clemson. South Carolina, has a twofold purpose: 

(I) to estimate the extent and distribution of redcockaded woodpecker habitat in the South, and 

(2) to categorize the avian species and communities associated'with forest types and successional 

stages. The other joint research is with the unit 

studying Utilization and Technical Characteristics of Southern Timber at Athens, Georgia. The 

objective of this joint effort is to reliably predict 

green and dry weights for wood and bark of 140 

tree and shrub species growing in the Southeast. 

With this type of information RRE can express its 

inventories in tons as well as cubic feet. 

ADDING EXPERTISE TO RRE PROJECT 

There are five ways to add additional analytical expertise to the RRE Research Work Unit: 

1. Recruiting and adding specialists to 

RRE. 

2. Adding specialists to other Research 

Work Units and assigning them to work 

with RRE. 

3. Developing cooperative agreements 

with universities. 

4. Having formal arrangements with other 

Research Work Units, Region 8, or SA. 

5. Developing expertise within RRE 

through additional training and education of project staff. 

i The last three of these methods have been 

I utilized. Even though these steps have been I taken, additional analytical expertise is still 

needed. If pressures were not so great for a 

shorter inventory cycle and a more complete and 

intensive sample, the solution would be obvious-reduce the field effort and strengthen all 

I RRE analytical capabilities. This, however, 

i' would be contrary to the wishes of most interested RRE supporters. The compromise soluI tion seems to be to keep the RRE field force 

strong, shorten the inventory cycle, provide adequate sampling intensity along with broad subject-matter coverage, and strengthen analytical 

capability to the extent possible with available 

resources. To accomplish this will require a carefully planned strategy and selection of highly 

qualified specialists. 

RRE plans to strengthen its in-house analytical capabilities by recruiting immediately a qualified ecologist to coordinate the analytical work to 

be done in wildlife. range, ecology. botany. and 

use interactions. Within 5 years, RRE will: 

(I) select at least one individual from the RRE 

field force to add to the Analysis or Techniques 

Section, (2) add a qualified individual to the Techniques Section, (3) recruit a qualified range specialist, and (4) add additional expertise in subject 

areas of quantitative sciences. operations research, soils and hydrology. and botany. 

NEW CONCEPTS AND 

TECHNIQUES 

Despite efforts to use existing techniques 

whenever possible, we found it necessary to develop new techniques in all three areas of the 

inventory process-data collection, data computations. and analysis. For data collection, we 

designed new field forms for rapid data processing, perfected ways of measuring and recording 

lesser vegetation in layers, and provided a set of 

standard procedures for measuring limbs on 

standing and felled trees. Data processing concepts were developed so that the vegetative information could be stored in layers and used for 

wildlife habitat ranking. Search of the literature 

and contacts with individuals did not reveal a 

suitable approach to analysis. Basically, no one 

had tried to use the same data base to assess all the 

different uses, interactions. and conflicts among 

resources. The studies that follow highlight some 

of the major techniques developed and adopted. 

USE INTERACTIONS 

At any point in time some use interactions are 

compatible while others are not, and the degree of 

compatibility tends to change over time. We are 

concentrating attention on interactions among 

timber, wildlife, range, recreation, and soil, 

water, and fisheries as a group. Since different 

management strategies are necessary to optimize 

use, conflicts develop among uses. Since timber is 

a primary product of most managed forests in the 

Southeast, our analysis is designed primarily to 

show interactions between timber production and 

that of other resources. 
Table I demonstrates this approach; it shows 

effects of possible timber treatments on soil and 

water quality. Individual rows in the table show 

the acreages which need silvicultural treatment 

during the next 10 years. These practices are 

needed to increase timber supply, but what are 

the soil and water-quality risks? It is apparent that 

the intensity of silvicultural practice used to take 

advantage of the opportunity will profoundly influence soil and water quality. For example,stand 

conversion could be applied on 50,000 acres. If 

risk class 3 and above were judged unacceptable 

impacts, intensive site preparation would be acceptable on 30,000 acres and unacceptable on 

20,000 acres. For the unacceptable acres, some 

other regeneration technique with less impact 

than mechanical site preparation should be used. 

The acreage requiring special treatment is of great 

interest to State and National policymakers. 

VEGETATlVE PROFILE STUDY 

While planning the South Carolina Pilot 

Study, we contacted individuals in several disciplines, and they confirmed that information on the 

lesser vegetation is important for assessing the 

forest resources. Previously, only trees 1.0 d.h.h. 

and larder had been measured. The concept of 

using lesser vegetation (tree seedlings, shrubs, 

vines, grasses, grasslikes and forbs) to predict 

relative suitability for different wildlife species, or 

to rank range capability, was well documented. 

Lentz (1974) described a wildlife habitat evaluation pl-ogram which depends on the recognition 

of lesser vegetation. MacArthur and MacArthur 

(1961) reported on the relationship between bird 

species diversity and vegetation complexity. 

While RRE field crews were still inventorying Virginia, a procedure for describing lesser 

vegetation was introduced to determine what 

problems would be encountered in collecting the 

vegetative data in wintel-. Some adjustments were 

made before the start of the South Carolina inventory. The study conducted across the State 

incorporated a procedure for determining the horizontal and vertical distribution, density, diversity, and composition of the tree foliage and other 

vegetation associated with forested ecosystems. 

Table I.-Area of commercial forest, by treatment opportunity and soil- and water-quality risk clasr 

No treatment needed 

Salvage cut 

Harvest 

Commel-cia1 thinning 

Precommercial thinning 

Clearing or release 

Stand conversion 

Artificial regeneration 

Treatment 

opportunity 

Total 1,000,000 284.000 375.000 12 1.500 139.500 80.000 

Soil- and watrl--qu;~lity ri\k definitions. 

I. During the recovery period of the activity. the watsr-quality irnpltcr hhould he \light t~u*pr.ndcd \dimen[ It.\\ rhiin 100 

milligrams pel- liter1 and soil erosion le,, than [he rate of new \oil dcvelopmenr. 

2. W;itei-quality during the recovery period of [he iicrivcry ran be impatred I%u\prnded \edirncnt g~r:tle! than 1110 mill~gr,~rn\ per 

lirrt). but suil rrohion should not exceed the rate of new roil dr\,elopmrnt. 

1 Watcvqoality impact can be hcgh and \oil emiion can rrcerd the raic of new roll drvrlopmrn[ diw~ng Ihc rccuvc'ry pclii~d al 

the silvicultur~i ;~ctivity. 

4. W211e+quitliry impecr ciin be \c~~uub and \oil crubiun can cxcrrd the ralc of new ruhl dcirlopmrnr f"8 \ 10 20 ycarr ;~fleltreatment 

5. Watcl--qu;ility impact can be very serious and soil erosioncan rrcerd ihr rate of neu roil devuloprnrnt li,~mol-c th;~n ?O )s.il-r 

after trralmrnl. 

Total 

Soil- and water-quality risk class' 

I 7 3 4 5 
A Common Link therefore decided to produce profiles in which 

values are estimated at I-foot intervals from the 

The species composition. level of stocking, ground to the tops of tree crowns. B~ combining and structural features of the stand directly influ- values for these individual [.foot layers on 

ence the benefits derived from forests. The vege- puter, we should be able to provide all the infor. 

tative makeup of forests and ranges can be viewed mation most users will want, 

as the common link for study of uses and use 

interactions. To illustrate, we know that herbage Broad Species Classes - and browse near the ground offer bothgrazing and 

browsing opportunities to animals. By determining the kinds and amounts of herbage and browse 

across extensive areas of forest land, we can 

quantify acres available for wildl~fe use and determine if this use is compatible with timber pro- , .. 

Field data for vegetative profiles can be collected by individuals with relatively little training 

in identification of shrub, vine, and grass species. 

Aftereach vegetative layer is identified, the broad 

classes of vegetation within the layer are recorded. The broad classes of vegetation recog- uucclon. nized are yellow pines, other softwoods, hardBuilding Upon Existing Timber Inventory woods, tropicals, shrubs, vines. grasses and 

grasslikes, and forbs and others (mosses. lichens. 

For years, RKE has collected information on 

trees 1.0 inch d.b.h. or larger, from a 10-point 

clustet- sample. In South Carolina, we measured 

lesser vegetation at points I, 2, and 3 of each 

10-point cluster. At each of these three sample 

points. all vegetative layers are examined on a 

plot with a 35-foot radius. Number of vegetative 

layers. species composition, and relative amounts 

are tallied. For each naturally occurring layer, a 

stocking percentage based on a space occupancy 

is determined. To estimate space occupancy, 

each vegetative layer is mentally divided into individual cubic feet of space, and the proportion of 

these cubic feet which contain vegetation is estimated. 

The tally of live trees made on all 10 points is 

used to calculate the space that is occupied by tree 

crowns. The tree classifications that are used to 

calculate crown volume are d.b.h., crown ratio 

(percentage of total height containing green live 

foliage), tree height, crown class (a measure of the 

position of the crown in the stand), and tree stocking. During data processing, the tally of trees 1.0 

inch d.b.h. and larger from the 10-point cluster 

sample is combined with the tally of lesser vegetation to produce a vegetative profile. The profile 

in figure I depicts the vertical and horizontal 

structure and illustrates how broad species 

classes occupy the horizontal and vertical space 

within the sample acre. 

- 

etc.). Within each broad class, there is a detailed 

list of species. Each species list includes a category called "other." A shrub species that cannot 

be identified is simply recorded as "other shrub 

species." This approach allows the cruiser to record the proper broad-species-class code and to 

account for the space occupied by every species 

he can recognize. 

Potential Values of Vegetative Profiles 

Results from the vegetative profile study will 

open up new avenues in resource evaluation. 

Some potential uses are: 

I. To show distribution of plant species. 

2. To show the frequencies ofoccurrence of 

understory plants. 

3. To determine general availability of 

herbage and browse. 

4. To estimate live understory and overstory fuel for predicting fire behavior. 

5. To make inferences about water infiltration, surface runoff, water quantity, and 

water quality. 

6. To serve as a base for estimating weight 

of lesser vegetation. 

7. To monitor plant species diversity, distribution. and composition over time. 

EVALUATION-SUBJECT APPROACH 

TO ANALYSIS 

P 

One-Foot Sensitivity There are no standard guidelines to follow in 

the analysis of multiresource data. One approach 

As a common link, the vegetative profile will is to group the various data elements into subsets 

be used by many different disciplines. The heights pertinent to a particular evaluation subject. Over 

of interest are quite variable (Lentz 1974), and we the years, RRE's involvement in limited studies 

could not anticipate all possible demands. We of deer browse, hydrology, and red-cockaded 

woodpecker habitat has provided some experience with the evaluation-subject approach. Experience gained from our studies and information 

from elsewhere indicate that many items tallied to 

evaluate timber are equally useful for evaluating 

other forest benefits. 

We first identify those data elements having 

common value to all the evaluation subjects. 

These elements, which we call link variables, include items such as sample location, forest type, 

stand age, stand size, stand origin, site descriptions, and ownership class. Next, we add the 

more specific data elements to their appropriate 

evaluation subject. Here, a series of summary 

cards has proven helpful. Each summary card 

contains the basic link variables plus those data 

elements pertinent to the particular evaluation 

subject. These summary cards are used to develop frequencies, distribution rates, relationships, and correlations among the various resources and evaluation subjects. 

BIOMASS INVENTORY CONCEPT 

For years, RRE in the Southeast has collected biomass data from standing and felled trees 

for producing volume prediction equations. Quite 

recently, RRE modified its measurement procedure to include all the components in a tree, 

except the foliage and small twigs. Since additional data are being collected on lesser vegetation and foliage and twigs of larger trees, we can 

predict total biomass for different forest conditions. We will do additional subsampling to establish weight estimates. Total biomass as defined by 

RRE will not include roots. 

Traditional State and regional inventories 

have usually been designed to provide volume 

estimates of wood from a I-foot stump to a 4.0- 

inch-diameter outside bark (0.b.) for trees 5.0 

inches d.b.h. and larger. This standard was established in 1963. During the same year, a comprehensive standing- and felled-tree volume study 

was incorporated into the inventory. The measurement procedure was designed to identify the 

stump and saw log portion, upper stem and top of 

main stem and forks, and all usable limbs. The 

only components not measured were minor limbs 

(limbs not suitable for pulpwood) and tips of 

usable limbs. This method of measuring trees 

provided the necessary data for predicting the 

standard merchantable volume. 

Renewed interest in use of wood for energy 

and trends toward whole-tree use created a need 

for measures of the volume in trees 1.0 to 4.9 

inches d.b.h., and in all limbs of trees 5.0 d.b.h. 

and larger. In 1975, measurement procedures 

were modified to include saplings and all limbs. 

The details for measuring standing trees are provided in another publication (Cost 1978b). 

Since all components of trees 1.0 inch d.h.h. 

and larger are being measured. total-tree volume 

can be estimated. Cubic volume in the stump. 

main stem, forks, and limbs of merchantable trees 

can be displayed. Volume in saplings can eitherbe 

included or excluded. Cost (1978a) pointed out 

that 30 percent of the total hardwood volume in 

the mountains of North Carolina was in saplings 

and in stumps. tops, and limbs of trees 5.0 inches 

d.b.h. and larger. 

From cubic volume, weight can be estimated. Steps have already been taken to assemble 

conversion rates by species. Once this is accomplished, RRE can report timber statistics in both 

weight and volume. 

The data being collected on vegetative profiles will provide estimates of the quantity and 

distribution of lesser vegetation in the understory 

and of tree foliage and small twigs in the midstory 

and overstory. If it is decided that total biomass is 

the main objective, we could develop weight estimates of the lesser vegetation and tree foliage by 

subsampling a variety of forest conditions. At 

each subsample location, the vegetation within a 

known space could be clipped and weighed. 

Weight conversions could be developed and applied to the entire population for biomass estimates. 

INFORMATION MANAGEMENT 

The timber and nontimber data collected in 

South Carolina can be assembled and presented in 

many different ways for a wide array of users. 

Many types of tables and charts can be generated 

and presented in RRE reports. In addition, by 

screening the data base, estimates of acreage 

meeting certain requirements can be generated on 

request. 

In 1970, RRE Project Researchers at the 

Southeastern Forest Experiment Station made a 

breakthrough in both the storage of data and the 

retrieval of information. The result was a Forest 

Information Retrieval (FIR) system which provides information on a customized basis. The 

breakthrough in mass storage and retrieval permitted us to screen and interrogate our active data 

base as needed. The FIR system is a specialized 

set of advanced computer programs that searches 

RRE data tapes and compiles customized forest 

resource information. With the system, requests 

that previously required weeks or months to compile can now be processed in a fraction of the 

pt-evious time and at a reasonable cost. The system is currently geared to provide up to 44 tables 

of forest resource information, all clearly labeled 

for the analysis of any geographic area in the 

Southeast. The user of the system can have the 

information compiled in three ways: (1) whole 

counties grouped together, (2) circular areas 

around a specified point, or (3) irregular boundaries within a closed'traverse of short line segments. In addition to the FIR System, we routinely present resource data in tables for States 

and for Survey Units (major subdivisions of 

States). A Unit report contains mainly statistical 

tables and is meant to rapidly convey basic findings. Tables in Unit reports provide data by 

county. The State report contains the 26 standard 

tables and meets all other requirements of the 

RRE Handbook. It is released within 1 year after 

fieldwork is completed. This report includes a 

thorough analysis of the timber situation for an 

entire State. 

The presumption in the standard-table approach is that most significant combinations of 

data can be compiled in a predetermined form that 

will satisfy both current and future needs. This 

approach has not always proved adequate in 

answering new questions. By storing the basic 

data in a highly accessible form, a screening 

process can be used as needed to answer specific 

questions or to produce a chart. Figure 2 is one 

example of a screening which depicts the occurrence of loblolly pine on rolling upland sites in 

the Southeast. 

The multiresource inventory will obviously 

generate numerous records and a tremendous 

amount of data dealing with many resource uses. 

To disseminate the wealth ofnew information, we 

will expand oul- FIR system, analysis, and reporting to accommodate the full range of forest values 

and uses. 

WIL-DLIFE HABITAT RANKING METHODS 

I ' Earlier work by Lentz (1974) showed that 

plot data from broad-scale inventories can be 

used to rank habitat suitability for certain animals. Since a number of wildlife-related attributes 

were observed and measured in the South Carolina inventory, we decided to develop a screening 

process which would rank each plot in terms of its 

habitat suitability. A review of the literature revealed that habitat criteria were available for 

game animals. but generally lacking for nongame 

birds and animals. Several wildlife experts were 

asked to provide habitat criteria for as many different birds and animals as possible. From their 

responses and from available literature, we assembled enough detailed data to develop screening criteria for 12 animal species or species 

groups. 

1. Gray squirrel 

2. Grouse 

3. Bobwhite quail 

4. Turkey 

5. Pileated woodpecker 

6. White-tail deer 

7. Red-cockaded woodpeckel 

8. Beaver 

9. Cottontail rabbit 

10. Small mammal group 

I I. Raccoon 

12. Wood duck 

We decided to use two types of screening 

because some birds and animals are highly specialized in their ecological preferences. The two 

methods were: 

Ranking method.-This method is used for 

all animals that do not have specialized needs. For 

each wildlife species, a set of habitat variables are 

described. Each variable is graduated from good 

to poor and assigned a numerical value. The habitat of each forest condition sampled is ranked 

either good, fair, or poor for a particular wildlife 

species, based on the total accumulated points 

from its habitat variables. The ranking criteria for 

gray squirrel are presented as an example (fig. 3). 

Discrete method.-This method is used to 

determine habitat suitability for beaver and redcockaded woodpeckers. Only good, Pair, and no 

habitat classes are considered for beaver. For the 

red-cockaded woodpecker, a remnant-tree class 

was included with the good, fair, and no habitat 

classes. To qualify as good, every attribute of 

good habitat must be present. If any attribute is 

missing, the next lower class is considered, and so 

on. The screening of habitat suitability is very 

dependent on structural features of the stand. For 

screening, five distinct vegetative layers were 

recognized: 

1. Ground layer 0 to I foot 

2. Shrub layer I to 5 feet 
Figure 2.-RRE sample plots assigned loblolly pine type on rolling upland siter in the Southeast. 
GRAY SQUIRREL HABITAT CRITERIA 

Habitat Variable Point Value 

1. Forest type and stand agea. bottomland hardwood types 41 + years; other forest types 61+ 

years 3 

b. bottomland hardwood types 25 to40 years; other forest types 

41 to 60 years 2 

c. bottomland hardwood types 16 to 24 years; other forest types 

21 to40 years 1 

2. Vegetative stocking of desirable species in the midstory by l-foot 

strataa. 26 percent or more 3 

b. 11 to 25 percent 2 

c. 1 to 10 percent 1 

3. Vegetative stocking of total vegetation in the overstory by l-foot 

strataa. 76 percent or more 3 

b. 51 to 75 percent 2 

c. 26 to 50 percent 1 

4. Vegetative stocking of hardwoods in the overstory by l-foot 

strataa. 8 1 percent or more 3 

b. 5 1 to 80 percent 2 

c. 21 to 50 percent 1 

Habitat Rank Determination 

Habitat Rank Code Total Accumulated Points 

Good 3 9 to 12 

Fair 2 5 to 8 

Poor I 1 to4 

No habitat 0 0 

Figure ).-Habitat criteria for gray squirrel. 

3. Understory 5 to 15 feet 

4. Midstory 15 to 30 feet 

5. Overstory 30+ feet 

The level of stocking within a vegetative 

layer is one of the key criteria for evaluating habitat by the ranking method. Levels of stocking 

within a layer were analyzed in two ways: 

1. Stocking by I-foot strata 

Each l-foot zone within a designated 

layer is examined for a specified level of 

stocking. Either stocking of all vegetation or that of desirable species can be 

analyzed. 

2. Stocking percentage within a layer 

This stocking concept pertains to the 

quantity of vegetation that occupies the 

entire Payer. 

TIMBER MANAGEMENT 

AND TREATMENT 

During the fourth inventory cycle, started in 

1966 and completed in 1977, a number of improvements were made to provide a more complete 

picture of the region's timber resource. We classified the forest in ways that permitted evaluation of 

opportunities for increasing timber supplies. Two 

significant changes were made to improve forest 

resources evaluation. These included: (I) measuring stand age to nearest year, and (2) adding 

several new variables to enhance the identification of treatment opportunities. A few examples 

of significant improvements are summarized 

below. 
Stand History 

A procedure for classifying stand history was 

developed and added to RRE in 1970. This new 

approach provided information previously lacking on levels of forestry activity and the geographic location of various forestry practices. 

Activities such as harvesting, thinning, highgrading, and natural disturbance were identified. 

Treatment Opportunity 

Treatment opportunities and the related 

factors limiting or influencing such opportunities 

have been indirectly considered by RRE for many 

years. In 1970, a procedure was added to specifically identify and quantify forest areas by 

treatment opportunity classes. Some of the 

classes recognized are salvage, harvest, thinning, 

TSI, regeneration. Results indicate the value of 

this information in making statewide and regional 

evaluation of opportunities for increasing future 

timber supplies. For areas covering several counties, this information provides a guide for 

planning and a basis for allocating program 

efforts. 

Sampling One Condition 

When fixed-area plots and single-point variable plots were used in the Southeast, procedures 

were developed for minimizing overlap through 

the shifting of plot centers. When the 10-point 

cluster plot was adopted in 1963, provisions were 

made for substituting points for those which fell 

outside the commercial forest, but the shifting of 

points to keep the effective sampling area within 

one forest condition was discontinued. A special 

plot classification in the fourth inventory of 

Georgia indicated that about one out of every 

three samples straddled two or more distinct 

forest conditions. When overlap or straddling is 

permitted across plantations and natural stands, 

distinct types, sites, or stand sizes, unrealistic or 

nonexistent conditions are portrayed. 

A study in central Georgia of only those plots 

contained within a single condition indicated that 

estimates of average volume per acre did not 

change significantly. These findings resulted in 

changing procedures so that each sample plot is 

confined within the forest condition identified by 

point 1. 

Stand Age 

Another recent improvement in inventory 

techniques is the redefining of stand age. RRE 

field crews had difficulty in classifying stand age 

at sample locations. Causes for this difficulty 

were: (1) sample plots were allowed to straddle 

two or more conditions, and (2) a wide range of 

tree diameters at given sample Locations misled 

field crews into assigning a mixed age. 

In 1972, several Fteps were taken to enhance 

the validity of the stand-age classification: 

(I) even-aged management was assumed at each 

sample location, (2) each sample plot was confined to a single forest condition identified by 

point 1 of a 10-point sample cluster, (3) stand age 

was based on stocking of trees which could be 

featured together in timber management, and 

(4) greater emphasis was placed on making an 

adequate number of increment borings for determining stand age. The results of these adjustments are reflected in a report titled "Stand-Age 

Profile of North Carolina's Timberland" (Knight 

1977). 

Stand Characteristics 

Like stand age, other stand classifications 

were modified or redefined in order to better 

describe the existingforest conditions. One useful 

stand classification that was modified was stand 

origin. It is used to identify plantations and to 

separate them into useful categories. Other modifications were made to the stand size and seed 

source classification. For years, RRE field crews 

recorded only one stand size, either sawtimber, 

poletimber, sapling and seedling, or nonstocked. 

Since most forest stands except pine plantations 

have two size classes, the stand size classification 

was expanded to reflect both the primary and 

secondary size class of the dominant and prevalent stems on the sample acre. Seed source was 

redefined to indicate the presence or absence of 

suitable seed trees by species class. The suitability of a particular species as a seed source is 

dependent upon its square feet of basal areaon the 

sample acre. 

Availability Factors 

Physical factors prevent intensive culture on 

some commercial forest land. As part of the inventory, a number of key variables were measured and added to the data base for screening 

purposes. These key variables can be used to 

answer questions that have economic implications. For instance: How many acres of pine sites 

are suited to mechanical site preparation and 

planting? How many acres of forest land in need 

of silvicultural treatment would require relatively 

little road construction to make them accessible 

for mechanical planting? How much area and 

volume would be excluded if small drains and 
narrow stream margins were not available for 

commercial timber production because of environmental concerns? There are additional questions that can be answered with the variables collected in the South Carolina inventory. Some of 

the key variables are: 

Accessibility (Describes the degree of difficulty involved in moving men and equipment to the edge of aforest stand) 

Operability (Identifies stands which present special management problems due to 

water conditions or steep slope) 

Slope 

Aspect 

Physiographic class (Based on soil, 

terrain, soil moisture, slope, and other 

nonvegetative conditions) 

Shape of forest condition 

Size of forest condition 

EVALUATION SUBJECTS 

A multiresource inventory can be regarded 

as a single integrated activity during planning and 

data collection. In analysis and interpretation, 

however, the entire inventory becomes too unwieldy; a breakdown into specific subject areas is 

a practical necessity. This separation allows the 

computer systems analyst and the resource analyst to focus attention on one data subset at a time, 

and it permits specialists to examine the data in 

their areas of expertise. It can also lead to better 

balanced and more uniform analysis and evaluation of various resource uses. We do not imply 

that each evaluation subject should be given equal 

space or time, but rather that each subject should 

be separately and fully considered. Some of the 

possible categories for separation are listed and 

described below. 

LAND BASE 

A clear definition of the land base for renewable resources including physical extent and location is necessary for a rational inventory. The 

inventory should identify specific areas with vat-ious specific resource-use potentials. We define 

the land base to include both land and inland 

water falling within the recognized political 

boundaries of each State. 

There are many advantages in having a single 

common land base for evaluating all the renewable forest and rangeland resources. It avo~ds 

overlaps and gaps when the resources are combined, and it reduces inventory costs by eliminating duplication of field effort. Use of a single common land base also improves measures of use 

interaction. 

The South Carolina inventory is designed to 

provide a broad range of information about the 

land base. It provides area statistics by land-use 

class at the county, survey unit, and State level. 

Trends in land use are measured both from aerial 

photographs and from permanent ground 

samples. The periodic remeasurement of permanent samples in all land-use classes provides a 

complete measure of change which can be used to 

evaluate impacts of resource use. The following 

evaluation subjects are all tied directly to this 

common inventory land base. 

TIMBER 

The objective of a timber-oriented inventory 

is to produce area and volume statistics in a useful 

form for analysts, managers, planners. and 

decisionmakers. The familiar timber resource reports usually contain tables of statistical information by forest type, ownership, site class. stand 

size, etc. The new multiresource inventory will 

not reduce the amount of timber data being collected. Collecting timber and nontimber data 

simultaneously will probably significantly increase the amount of useful timber-related information. 

Some new information on timber is being 

collected as part of the multiresource inventory. 

New items include stand history, which is coded 

in terms of treatments and disturbances since the 

previous inventory. The condition of the forest at 

each sampling point is used to determine a treatment opportunity based on a set of standards for 

the Southeast. The structure of the forest at each 

sample is completely measured to enhance the 

classification and description of forest stands for 

management purposes. Several new variables describe the physical factors limiting harvest, treatment, and management of portions of the commercial forest. These chat-acteristics include 

slope, aspect, accessibility, size of condition. 

operability, physiographic class, and a better 

measure of the stocking. Other improvements and 

refinements in inventory techniques have been 

made in t-ecent years. including items such as 

stand age, stand origin, and seed source. 
WILDLIFE 

Wildlife-related information in the new inventol-y is confined to measuring, classifying, and 

evaluating habitat. Our sampling process is well 

suited for estimating the amounts of forest and 

rangelands that have the vegetative structure, 

species composition, and special features required by a given species of wildlife. In contrast, 

our procedures are totally unsuited for estimating 

populations of individual wildlife species. For 

wildlife habitat, we measure the vegetative structure, composition, and density in the overstory, 

midstory, and understory to estimate the abundance and distribution of wildlife plants and the 

adequacy of the vegetative community to provide 

cover, shelter, nest sites, and foraging substrate. 

We also note the presence of cavities and snags, 

which are extremely important to certain species 

of wildlife. Other special features recorded include cover items such as holes, caves, dens, 

brush piles, and hollow logs. The presence of 

water is also recorded in various ways to improve 

the description of forest habitats. 

Individual wildlife species range over areas 

from a few feet to many miles. Some species 

require specific habitat conditions, while others 

adapt well to a wide range of conditions. Some 

species migrate, while others remain in one area 

throughout their lives. There are also numerous 

variations in food requirements. sensitivity to disturbance, and living space needs. Some species 

spend most of their time below ground, some 

prefer ground level, and some favor selected vegetative layers above ground. This high degree of 

variation in species habitat selection makes the 

inventory task extremely complex. 

To help organize our thinking about wildlife 

habitats, we have recognized five broad classes of 

vertebrates. 

I. Migratory Species-Species that use a 

particular forest condition seasonally outside of 

the breeding season. 

2. Threatened and Endangered SpeciesSpecies given special status and protection because of unsatisfactory population levels. 

3. Recluse Specirs4pecies that require 

large, remote, solitary, or secluded areas of undeveloped or isolated forest. They are sensitive to 

development and encroachment of civilization. 

4. Adaptable Species4pecies that do not 

require a single specific habitat but are highly 

flexible and can successfully shift from one forest 

condition to another. Species may thrive in diverse or mixed forest conditions. 

5. Sensitive Species-Species that require 

a special combination of habitat characteristics to 

survive'and reproduce. These species are very 

sensitive to habitat disturbance. 

Our inventory methods are poorest for quantifying habitat of migratory species. The threatened and endangered group includes species from 

the other groups and is actually not a separate 

inventory problem. The recluse group is probably 

better suited to in-place mapping than to broadscale inventory sampling. The remaining two 

groups are the largest and our procedures are 

probably suited to them. The suitability of habitat 

for sensitive species can be ranked by screening 

for certain attributes at each sample location. 

Adaptable wildlife species probably do best 

where a diversity of conditions is present over a 

small area. 

RANGE 

Before the range resource can be evaluated. 

the land base suitable for range must be determined. Sufficient forage for grazing of livestock is 

present in a wide variety of situations. In the 

Southeast, the land-use classes of major importance to range evaluations include forest lands, 

natural range, and marsh, which are classed as 

forest and rangeland, as well as improved pasture 

and cropland. which are excluded from our inventory responsibility. The inventory will determine the current area in each land-use class and 

also measure the rates of change and trends in 

area. 

Within land-use classes. we are measuring 

the quantity. quality, and distribution of vegetation suitable for livestock forage. In addition. wc 

are noting fencing, burning, and current utiliration. Our inventory will also show that water is a 

limiting factor. A few plants are poisonous or 

noxious to livestock and can be identified as a 

limiting factor to range use. Other species of 

plants are preferred or are of special importance 

to livestock and can be rated accordingly. 

RECREATION 

Our survey crews will note evidence of recl-eational uses such as hunting. tishing. and camping, for which signs can be found. Other recreation-related inventory information includes the 

presence of various types of trails. posting of 

forest land, and the presence of water. General 

information that may prove valuable in judging 

recreation potential includes slope. soil textul-e, 

land-use pattern. accessibility. and a complete 

description of the vegetation PI-esent at the 

sample location. 

SOILS 

A limited amount of information on soils is 

being collected during the inventory so that certain soil characteristics can be directly related to 

other resource data at ground sample locations. 

The soils portion of the inventory was carefully 

designed to prevent any duplication of effort or 

overlap with the soil surveys being conducted by 

the Soil Conservation Set-vice. One of our primary goals is to be able to inventory environmental impacts due to management actions which 

disturb the site. We are tallying a rough estimate 

of soil texture which, combined with slope, can be 

used to rank areas into erosion-risk classes. Other 

information recorded includes soil structure, 

compaction, and position on slope. Together, 

these soils characteristics are useful in judging the 

relative stability of the site. The inventory also 

includes information on litter depth, humus 

depth, percentage of bare ground, and acomplete 

description of the vegetative cover. 

WATER 

For inventory purposes, water is treated both 

as a separate land-use class and as a special characteristic of the forest. As a land-use class, water 

is separated into lake-like and stream-like categories. It is further classified as to size or width 

and as fresh or salt water. The amount, kind, and 

distribution of water directly influence many of 

the other evaluation subjects such as timber, wildlife, recreation, and range. 

Water in 01- near a site may enhance its value 

for a particular use or create a management problem, depending upon the use being contemplated. 

The inventory therefore describes the proximity 

of water to the forest and rangelands being 

sampled. We distinguish between temporary and 

permanent water and estimate average depth of 

temporary water. 

The presence of water is used to evaluate the 

suitability of the forest in meeting the needs of 

wildlife, recreation, and livestock. It is also 

treated as a limiting factor to timber management 

and harvesting opel-ations. And it is a critical input to the next evaluation subject-fisheries. 

FISHERIES 

Fotiest and range activities can influence the 

quality of fish habitat. As described in the preceding segment, the inventory measut-es the amount, 

kind, and distribution of water. This information 

on inland waters should help in evaluating fisheries. Other useful inventory information includes the proximity of water to various forest 

disturbances and the degree of erosion taking 

place. 

BIOMASS 

The estimation of total biomass as defined by 

the ecologists is not ourgoal. We do not deal with 

roots, insects, birds nests, or other matter of a 

similar nature. Thus. we can only estimate the 

biomass of aboveground woody fiber. We can 

categorize this material by species. structure. and 

space occupied. Despite the restrictions, our biomass totals should prove useful because they include a very high proportion of all aboveground 

biomass. And the data are being collected uniformly across the entire State. 

Traditional timber inventories have usually 

been designed to estimate only the volumes of 

material meeting certain merchantability standards. Large quantities of lower value material 

have been excluded. The South Carolina inventory, therefore. will provide a more complete 

measure of the forest biomass. 

A comprehensive standing- and felled-tree 

volume study was initiated in the Southeast in 

1963. The results provide the basic data needed to 

determine volumes in sapling-size trees (trees 1.0 

to 4.9 inches d.b.h.) and in stumps, tops, and 

limbs of trees 5.0 inches d.b.h. and larger. The 

lower quality trees, commonly called rough trees 

and rotten cull trees, can also be included in these 

volume summaries. Wood volume, bark volume, 

or a combination of wood and bark volume can be 

presented. 

The remaining step in estimating biomass is 

to convert volumes into weights. A separate effort 

is now underway to find the best available conversion rates for the various species of trees found 

in the Southeast. Precise conversions of volume 

to weight will require additional work because of 

variations in wood and bark, tree size, location 

within the tree, and geographic location. 

Data being gathered on understory vegetation include the quantity, distribution, and space 

occupied by various species of tree seedlings, 
shrubs, vines, grasses, and forbs. These data will 

provide a basis for estimating additional vegetative mass. 

ECOLOGY 

Since inventory coverage is very broad, it 

seems desirable to examine the data from apurely 

ecological standpoint. Information on the vegetative structure of all the forest lands in South Carolina offers a unique opportunity to study ecological relationships on a very broad scale. The inventory will provide a picture of the composition 

of overstory, midstory, understory, shrub layer, 

ground layer, and various combinations on a 

statewide basis. The inventory will also provide 

data on species associations, and the occurrence 

of trees. shrubs, vines, grasses, and forbs at various stages of succession. It will identify recently 

disturbed areas and the vegetative responses to 

those disturbances. 

A new procedure for displaying and analyzing the vegetative composition and structure of 

individual sample areas or aggregates of many 

sample areas is called the vegetative profile. This 

technique, explained in greater detail elsewhere 

in this Paper, is an example of how the massive 

amount of detail data being collected can be combined into a single clear display of the ecological 

structure of forest vegetation: 

BOTANY 

There are many aspects of the multiresource 

inventory that are of special interest and value to 

botanists. The inventory will show how the distribution of individual plant species is associated 

with various site conditions and other species. 

Understory species such as honeysuckle, kudzu. 

and poison ivy are of considerable interest because of their potential to create problems. The 

distribution associations of many other plants are 

in need of validation and confirmation. Botanists 

are also concerned about trends in the quantity 

and distribution of certain plants. Information obtained from the remeasurement of permanent 

samples will be useful in assessing trends and will 

help in the selection of plant species as threatened 

or endangered. In some cases, a plant species may 

be removed from the threatened and endangered 

list if it can be shown that its distribution is acceptable and its population trends are stable or 

increasing. 

USE lNTERACTIONS 

Since our resource base is finite, all uses 

interact to some degree. In resource inventories 

and evaluations, therefore, interactions must be 

considered whenever two or more resource uses 

are being analyzed. Not all interactions are necessarily bad or harmful. Some can be harmonious 

and compatible. Over long periods, however, the 

tendency is for use interactions to be competitive 

and to generate conflicts. 

The evaluation subjects discussed in this section are the uses which tend to interact. The most 

visible interactions involve timber, wildlife, 

range. recreation, and acomposite of soils, water, 

and fisheries. A given piece of forest land cannot 

simultaneously support two or more uses which 

require conflicting management actions. The role 

of inventory is to gather and display the information needed to select a desirable balance of 

forest use. Measuring and classifying the forest as 

a single entity establishes a common data base to 

which specialized information about individual 

resources can be added. 

In theory, use interactions can be thought of 

as a matrix in which each use interacts with every 

other use, both singly and in combinations. This 

model is very complex and suggests many analyses that are of very little interest. Furthermore, it 

fails to recognize the practical and biological significance of the timber overstory in forests. In the 

Southeast, timber is the intended product of most 

managed forests. In addition, the condition of the 

timber overstory largely controls the biological 

process beneath. in our first analyses of interactions, therefore, we will focus on timber's relation to other uses. The data will be organized to 

show the impacts and trade-offs that might be 

expected if timber production is maximized. 

Maximizing timber production would require 

harvesting, regeneration, and treatment strategies that may have rathet- serious impacts on wildlife, range, recreation, and the quality of the environment. On the other hand, the constraining of 

timber in favor of increases in the other uses can 

be evaluated in terms of reduced forest products 

output at higher prices. This approach does not 

make any attempt to evaluate use interactions 

between wildlife and range or recreation and environmental factors. 

INFORMATION MANAGEMENT 

The multiresource inventory described here 

will obviously generate numerous records and a 

tremendous amount of data that must be properly 

managed before it can be fully analyzed and evaluated. The bulk of these data is recorded on forms 

in the field, then transferred onto data cards and 

magnetic tape for processing and storage. A number of specialized processing systems are used to 

convert the raw field data into final data storage 

records. Each system is composed of several individual computer programs which perform a set of 

mathematical and logical transformations as the 

data pass through the computer. The final records 

are sorted and stored for later use in the RRE 

master data base. This data base contains the 

accumulated inventory data for the five Southeastern States. 

The primary test of an information management system, however, is its ability to retrieve 

information in desirable forms. If the mass of data 

produced by an inventory can be retrieved rapidly 

in forms suitable for a variety of analysts. such as 

providing customized responses to many different users, it has passed the test. 

The FIR system used by RRE in the Southeast is a highly advanced user-oriented system for 

mass data storage and retrieval. It is designed to 

provide rapid retrieval of inventory information 

on a customized basis. The methods for storing, 

cataloging, updating, and retrieval are all common enough. The unique aspects of the system 

are that it is relatively inexpensive to operate and 

has proved to be both flexible and dependable. 

THE ROLE OF TECHNIQUES 

Research on inventory techniques is a highly 

specialized activity that can be conducted during 

multiresource inventories. This research requires 

a unique feel for what is needed, suitable, practical, and possible, coupled with an ability to make 

things work. 

The initial step in techniques research is to 

identify needs and recognize opportunities. This 

requires a thorough grasp of inventory objectives, 

an appreciation of information needs, an understanding of priorities, and considerable expertise 

in inventory methods. ltems selected for study 

should have high priority, be within the scope of 

the inventory objectives, and be amenable to 

solution. 

The next step is to judge the suitability of 

existing methods and procedures. Quite often an 

inventory need can be met by adapting or modifying a piece of equipment, a field-measurement 

procedure, or a computer program rather than 

developing a totally new item or procedure. An 

entirely new technique must be taught to field 

crews, as must the use of new equipment. Hence, 

use of an existing procedure, method, or tool 

often saves a lot of time and money. 

Where something new is needed, its development requires innovation and the forming of new 

concepts. This process is like that of other research; success requires both thought and persistence. A newly conceived procedure is usually 

incomplete and lacking in detail. Additional development is usually required before it is ready for 

testing. 

All new methods and procedures do not require the same degree of testing. Some are so 

straightforward that it is obvious to inventory 

specialists how well they will work and the problems that might develop. Other methods and procedures do, however, require extensive field 

testing and possible modification before they become part of the regular inventory. 

DISPLAY OF RESULTS-EXAMPLES 

Multiresource data are now available for one 

of the three Survey Units in South Carohma-the 

Piedmont. In this chapter we illustrate the kinds 

of information available for this Region. We 

emphasize that these illustrations are only a few 

examples. Upon completion of the inventory, we 

plan to make a comprehensive and balanced analysis of all the data collected. 

Initial estimates of forest and nonforest areas 

in the Piedmont Region were developed from 

classification of 23,83 1 sample clusters systematically spaced on aerial photographs. Field crews 

verified the photo classifications on the ground at 

1,614 of the 16-point cluste~s. A linear regression 

was fitted to the data to develop the relationship 

between the photo and ground classifications. 

This procedure provided for adjusting the initial 

estimates of area for change in land use since date 

of photography and for photo misclassifications. 

The Piedmont Region of South Carolina encompasses more than 6.8 million acres of land and 

water. The inventory provided a breakdown of 

this total area into meaningful land classes (table 

2). Forest occupied almost 4.6 million acres, or 

two-thirds of the total area. By county, percentage of total area in forest ranged from 85 

percent in Fairfield County to only 42 percent in 
Anderson County (table 3). Anderson, Spartanburg, and Greenville Counties each have sizable 

urban centers. In addition, a large part of Anderson County was inundated by Lake Hartwell, one 

of several major reservoirs in the State. As of 

1977, less than 1 percent of the forests in the 

Piedmont had been withdrawn from timber use, 

as indicated by the productive-reserved forest 

classification. 

Table 2.-Tural arra. by land classes. Piedmont of South 

Carolina, 1977 

Land clarr I ~cres 1 Pcrccnt 

Commercial forest 4.528.036 66.3 

Productive-reserved forest 38.746 0.6 

Other forest - - 

Total forest 4,566.782 66.9 

Cropland 580,348 8.5 

Improved pasture 728,065 10.7 

Natural range - - 

Idle farmland 161,337 2.4 

Other farmland 94,316 1.4 

Marsh 2.319 ('1 

Urban and other 

Water 

Total nonforest 2,256.258 33.1 

All classes 6.823.040 100.0 

~p 

'Lcss than 0. I percent. 

Over the past 40 years. Forest Survey has 

monitored extensive changes in land use in this 

Region. Forest Survey first inventoried the 

Region's forests in 1936. At that time, forests 

occupied only 3.2 million acres or less than halfof 

the total area; about an equal acreage was in agricultural use. Between 1944 and 1969, according to 

Census of Agriculture statistics, the Region experienced a reduction of more than 1.2 million 

acres in cropland harvested. A strong correlation 

between the age distribution of pine timber stands 

in 1977 and the timing of these reductions in cropland harvested confirms that much of this cropland reverted to pine forests. This successional 

reversion from cropland to pine timber accounts 

for today's concentration of pine timber stands in 

the younger age classes (table 4). Over time. hardwood species tend to develop in the understory of 

these pine forests and without substantial intervention by man will gr-adually replace the pines. 

Table ;.-Counties ranked by percentage of tutal area in 

forest. Piedmont of South Carolina, 1977 

In forest 

Area Percent 

Fairfield 

Union 

McCurrnick 

Chester 

Nswberry 

Edgefield 

Lancaster 

Greenwood 

Abbevillr 

Oconrr 

Laurcns 

Pickens 

Saluda 288,000 187.758 65.2 

Cherokee 22.800 155.752 61.6 

York 446.080 269.252 60.4 

Greenville 508.800 299.82 1 58.9 

Spartanburg 532,480 271.268 50.9 

Anderson 197.280 208.201 41.9 

All counticr 6.823.040 4.566.782 66.9 

We contend that this is the kind of information 

needed to make assessments. 

For evaluation purposes, we need to relate 

the timber component of the forest resource to the 

distribution in table 4. On the 4.5 million acres of 

commercial forests in the Piedmont, the solidwood content between a I-foot stump and a?-inch 

top of all live trees 5.0 inches d.b.h. and larger 

averaged 1,462 cubic feet per acre (table 5). The 

sawtimber component of this timber inventory 

averaged 3,750 board feet per acre' (table 6). In 

addition, these forests contained an average of 

664 saplings per acre (table 7). Together tables 5 

through 7 quantify the distribution of timber by 

stand-age class and forest types. Whet-e needed. 

these distributions can be furthet- [refined by 

ownership and site classes and can be developed 

for smallergeographic areas within the Region. 

Wildlife evaluations can be based on quantities of forage in various vegetative layers or on 

values assigned to plots as habitat for certain 

species. Here we show the ranking of gray 

squit-re1 habitat suitability and a screening of potential red-cockaded woodpecker habitat. 

Our plot data on gray squirrel habitat for the 

Survey Unit show that conditions are best for this 

animal in the hardwood-forest type (table 8 and 

fig. 4). By county. the proportion of commet-cia1 
All classes 4,528,036 405,930 1,849,923 673,600 1,470,056 128,527 

Table 4.-Area of commercial forest land by stand-age class, by forest types, 

Piedmont of South Carolina, 1977 

Table 5.-Average volume of all live timber1 per acre of commercial forest land by 

stand-age class, by forest types, Piedmont of South Carolina, 1977 

Stand-age 

class 

(years) 

All classes 

All 

types 

Stand-age 

class 

(years) 

.... Cubic feet ..... 

242 258 

645 527 

1,187 1,039 

1,590 I ,307 

2,100 1,615 

2,184 1,770 

2,165 2,326 

2,623 1,749 

1.65 1 2,177 

1,487 1,260 

'Trees 5.0 inches d.b.h. and larger. 

Forest type 

All 

types 

forest qualifying as good habitat ranged from 55 

percent in Anderson County to only 18 percent in 

. Chesterand Fairfield Counties (table 9). 

Previous estimates of the extent of habitat 

suitable for the red-cockaded woodpecker have 

been based largely on limited field studies, localized surveys. and generalized forest types. In 

1975. a new estimating procedure was developed 

using RRE data to systematically identify favorable red-cockaded habitat across the entire 

Southeast. Wildlife experts knowledgeable about 

habitat requirement3 of the red-cockaded woodpecker provided descriptive information. The following criteria were used to scan computer tapes 

of recorded plot data: commercial forest land. 

pine forest types. sawtimber stands, stand age of 

40 years or more. and basal area of 20 square feet 

or more. 

Pine 

plantations 

Forest type 

Upland 

hardwood 

Natural 

pine 

Lowland 

hardwood 

Pine 

plantations 

Oakpine 

Natural 

pine 

Oakpine 

Upland 

hardwood 

Lowland 

hardwood 
Table 6.-Average volurne of sawtimber per acre of commercial forest land by 

stand-age class. by forest types. Piedmont of South Carolina, 1977 

(&9 

10-19 

20-29 

30-39 

40-49 

50-59 

60-69 

70-79 

80 + 

All cla5ses 

Stand-age 

class 

(years) 

Board feet' .... 

405 480 

1,110 1,675 

2.28 1 1,198 

4,086 2,554 

6.864 3,947 

7,632 4,504 

8,374 8,555 

10,649 5,512 

7.057 9,161 

'International %-Inch Rule 

All 

types 

Table 7.-Average numbel- of saplings' per acre of commel-cinl fore\t land by 

stand-age class. by forest types. Piedmont of South Cat-olina. 1977 

Foreit type 

All classes 

Pine 

plantations 

Stand-age 

class 

(years) 

Number 

72 1 

85 1 

865 

768 

627 

686 

592 

525 

533 

'Trees 1.0 to 4.9 inches d.b.h 

All 

types 

The screening procedure was done in steps. 

We first identified all sample plots assigned a pine 

forest type (fig. 5). We sequentially added additional criteria, eliminating plotseach time until all 

the constraints had been imposed. Then, a final 

map (fig. 6) and statistical table (table 10) were 

generated. 

Habitat variables for the red-cockaded 

Natural 

pine 

woodpecker are being refined. After these refinements are made, the data can be rescreened for 

improved estimates of suitable habitat. 

For range, we can relate the forage component of the forest resource to broad forest type 

and stand age. For all forest types, forage yield is 

high when stands are established and decreases 

rapidly to age 20 (fig. 7). At this time, the tree 

Oakpine 

Upland 

hardwood 

Forest type 

Lowland 

hardwood 

Pine 

plantations 

Natural 

pine 

Oakpine 

Upland 

hardwood 

Lowland 

hardwood 
Table 8.--Gray squirrel habitat suitability by stand-age class. by forest type, 

Piedmont of South Carolina, 1977 

0-9 

10-19 

20-29 

30-39 

4049 

50-59 

60-69 

70-79 

80+ 

All classes 

Stand-age 

class 

(years) 

GOOD 3.0 . 

2.5 . 

% ,,IR 2o ' 

2 

k ' 15. 3 

POOR 1.0 

Forest type 

classes Pine Natural Hard- 

'0 = Unsuiled. 

I = Poor 

2 = Fair. 

3 = Good. 

We think that many characteristics of forest 

stands will prove important in determining recreational value. One of the items of special interest 

p,Nr tallied on each plot is evidence of human recreational use. This evidence included such things as 

hiking trails, shotgun shells, tree stands, campfire 

rings, bait containers, trail-bike tire tracks, or 

other visual evidence of use by people. From this 

information we can obtain relative estimates of 

those forest conditions which people seemingly 

prefer for dispersed outdoor recreazion. The information is not intended to measure actual use. 

We find that 40 percent of the use by people 

occurred in two age classes (30 to 39 and 40 to 49 

years) (table 12). In addition, 48 percent of all 

recreational use took place in hardwood stands. o 20 30 o 50 60 10 80 90 32 percent in natural pine, 16 percent in oak-pine 

STaNO AGE IYLARSi and 4 Dercent in pine plantations (fig. - 9). SpartanFigure 4.Aray squirrel habitat suitahilily. by stand-age class burg County had the highest percentage of use 

and forest type, Piedmont. South Carolina, 1977. and Newberry County the lowest in the Piedmont 

canopy is usually fully closed and competition for 

light, moisture, and nutrients is intense. It often 

remains so until the stand is very old. Forage 

production in hardwood stands is generally 

greater than production in pine plantations. For 

the Survey Unit, hardwood stands experience the 

highest grazing use (fig. 8). Grazing use is highest 

in Cherokee County and lowest in McCormick 

county (table I I). 

Unit (table 13). 

RRE field crews collected hydrological and 

soils data that can be used to develop general 

information about the condition of the resources 

and to define general trade-offs between various 

resource management strategies. The following 

are some examples of analyses that can be made 

from RRE data. 

Average humus and litter depths at various 

stand ages are shown by forest type in figures 10 
Table 9.-Area of commercial forest land and its percentage distr~bution by habitat 

quality for gray squirrel, by county, Piedmont ofSouth Carolina. 1977 

Table 10.-Area with potentla1 habitat for the red-cockaded woodpecker, by State 

and ownership class. Southeast 

County 

............... Thousund acres .................... 

Florida 320 94 36 76 114 

Georgia 885 53 75 130 627 

South Carolina 705 15 1 39 88 427 

North Carolina 1,406 32 118 138 1,118 

Acres .................... Percent ....................... 

At~beville 219,883 7 28 24 41 

Anderson 208,201 I 9 35 55 

Cherokee 154,802 17 15 3 1 37 

Chester 290,619 10 25 47 18 

Edgefield 234,637 18 18 38 26 

Fairfield 386,015 8 30 44 18 

Greenville 278,448 - 20 28 52 

Greenwood 205,672 7 38 33 22 

Lancaster 235,604 14 21 29 36 

Laurens 305,701 I I 2 1 37 3 1 

McCormick 206,778 I2 21 37 30 

Newberry 3 15,829 4 20 47 29 

Oconee 280,294 2 19 37 42 

Pickens 209,464 7 18 3 1 44 

Saluda 187,758 8 20 44 28 

Spartanburg 271,227 10 20 35 35 

Union 272,352 10 23 35 32 

York 264,752 2 28 3 1 39 

All counties 4,528,036 8 23 36 33 

All 

classes 

Virginia 

Southeast 

State 

'Include5 otherprlvate lands under long-term lase 

Quality of squirrel habitat 

National 

Forest ownerships 

and I I. Figure 10 suggests that topsoil develop- In the Piedmont Unit, the highest incidence 

ment is slower under planted pine than under of soil erosion occurred in Cherokee County and 

other timber types. It is apparent in figure I I that the lowest in Oconee County (fig. I2 and table 14). 

pine litter accumulates rapidly but decomposes Table 15 shows a breakdown of soil-texture 

slowly. Hence, topsoil development is slower in classes by county. These data may be valuable in 

piiv plantations than in hardwood stands. explaining erosion or site productivity. 

Unsuited 

Other 

public 

Poor Fair Good 

Forest 

industry' 

Other 

private 
Figure 5.-KKE ,ample plots assigned a pine fore\[ rypr, Southeast 

33 
Figure 6.-Potential habitat for the red-cockaded woodpecker. Southeast 

34 
NATURAL PINE 

I 

O 10 20 30 40 50 60 70 80 90 

STAND AGE (YEARS) 

Figure 7.-Prrcenrage of desirable forage, by forest type. by Figure 8.-Percentage of grazed commercial foreit land, by 

stand age. Piedmont. SouthCarolina. 1977. forest type, Piedmont ofSouth Carolina. 1977. 

Table I I.-Area of commercial forest land and its percentage distribution, by 

grazing intensity and county, Piedmont of South Carolina, 1977 

Abbeville 

Anderson 

Cherokee 

Chester 

Edgefield 

Fairfield 

Greenville 

Greenwood 

Lancaster 

Laurens 

McCormick 

Newberry 

Oconee 

Pickens 

Saluda 

Spananburg 

Union 

York 

All countieh 

County 

Acres 

219,883 

208,201 

154,802 

290,619 

234,637 

386,015 

278,448 

205,672 

235,604 

305,701 

206,778 

315,829 

280,294 

209,464 

187,758 

27 1,227 

272,352 

264,752 

4,528,036 

. . . Percent . . . 

12 6 

10 5 

15 6 

5 4 

2 - 

7 3 

4 4 

8 - 

2 2 

10 2 - 1 

3 - 

2 1 

6 4 

2 3 

7 3 

14 4 

I2 3 

6 3 

All 

classes 

I None = No evidence of grazing. 

Light = Less than 35 percent of plants grazed. 

Medium = 35 to 70 percent of plants grazed. 

Heavy = More than 70 percent of plantsgrazrd. 

Grazing intensity' 

None Light Medium Heavy 

Table [?.-Use by people, by stand-age class and forest type, Piedmont of 

South Carolina 

... 

0-9 8 

10-19 10 

20-29 18 

30-39 20 

4049 20 

50-59 16 

60-69 4 

70-79 2 

80+ 2 

All classes 100 

Stand-age 

class 

(years) 

............. Percent use ...... 

27 7 9 

48 13 9 

23 36 16 - 19 21 

- I I 26 - 10 I0 - 4 3 

- - 3 

- 0 3 

100 I00 I00 

Forest type 

classes Pine Natural Hardpine wood 

ALL USES 

PP =PLANTED PINE 

NP=NATURAL PINE 

OP =OAK-PINE 

H HARDWOOD 

FISHING CAMPING HUNTING 

HIKING TRAIL BIKES OTHER USE 

24% 13% PP5% OP 11% 

38 % 

48% 23% 0" 9% 36% 

Figure 9.-Distribution of svtdence of dirprrsrd outdoor recrratlun on cornrnerciai forest land. by use. 

by forest type, Piedmont ofSouthCarollnii, 1977. 

Table 13.-Area of commercial forest land and its percentage distribution of use by 

people. by county. Piedmont of South Carolina, 1977 

County A11 

clabses 1 No / PeopIeuse people use I I I 

Acres .... Percer~r ... 

Abbeville 219,883 82 18 

Anderson 208,201 58 42 

Cherokee 154,802 70 30 

Chester 290,619 93 7 

Edgefield 234,637 90 10 

Fairfield 386,015 88 12 

Greenville 278.448 68 32 

Greenwood 205,672 86 14 

Lancaster 235,604 93 7 

Laurens 305.70 1 76 24 

McCormick 206,778 90 10 

Newberry 3 15,829 99 I 

Oconee 280,294 78 22 

Pickens 209,464 69 3 1 

Saluda 187,758 85 15 

Spartanburg 27 1.227 50 50 

Union 272,352 75 25 

York 264,752 83 17 

All counties 4.528.036 80 20 

0 0 20 30 40 50 60 70 80 90 

STAND AGE IYEARSI 

0 -. 2 

$00 &' 

0.6 

Q 2 0.4 

s 0.2 

Figure I(].-Average humus depth, by forest type, by stand 

age. Piedmont ofSouth Carolina. 1977. 

rb OAK-PINE 

- : '\ 

- 

. 

- PINE PLANTATION 

. 

Table 16 shows a soil and water risk classification for interpreting potential soil- and waterquality trade-offs. Approximately 1.3 million 

acres of land need some sort of silvicultural practice during the next 10 years (table 16). These 

practices are needed to increase timber supply, 

but what are the risks to soil and water quality? It 

is apparent from table 16 that the type of silvicultul-al practice used to take advantage of the 

opportunity will influence soil and water quality. 

For example, stand conversion and artificial rePINE PLANTATION 

I 

,,''-,>- 

i;; \ OAK-PINE 

- - 

10 20 30 40 50 60 70 80 90 

STAND AGE (YEARS] 

Figure I [Average litter depth, by forest type, by stand age, 

Piedmont of South Carolina, 1977. 

generation with site preparation could be applied 

on 507,406 acres. If risk class 3 and above were 

judged unacceptable impacts, intensive site preparation would be acceptable on 328,58 1 acres and 

unacceptable on 178,825 acres. For the unacceptable acres, some other regeneration technique 

with lower risks should be used. 

From the standpoint of total wood fiber. the 

conventional forest inventory measures of grow- 
Figure 12.-Proportion of commercial forest with soil erosion. 

by county. Piedmont ofSouth Carolina, 1977. 

Table 14.-Areaof commercial forest land and its percentage distribution by degree 

of soil erosion, by county, Piedmont of South Carolina, 1977 

County 

Acres ............ Percent ............... 

Abbeville 219,883 85 8 2 5 

Anderson 208,201 83 I2 5 - 

Cherokee 154,802 38 28 22 12 

Chester 290,619 89 9 - 2 

Edgefield 234,637 94 2 2 2 

Fairfield 386,015 80 17 2 I 

Greenville 278,448 8 1 8 7 4 

Greenwood 205,672 94 6 - - 

Lancaster 235,604 90 6 - 4 

Laurens 305,701 88 7 3 2 

McCormick 206,778 75 I? 9 4 

Newberry 315,829 89 10 - I 

Oconee 280,294 95 2 - 3 

Pickens 209,464 88 10 - 2 

Saluda 187,758 85 15 - - 

Spartanburg 27 1,227 6 1 22 10 7 

Union 272.352 43 17 18 22 

York 264,752 69 19 9 3 

All counties 4,528,036 80 12 4 4 

All 

classes 

Degree of soil erosion 

None Low Medium High 
Table 15.-Area of commercial forest land and its percentage distribution by 

soil-texture class, by county, Piedmont of South Carolina. 1977 

i ing stock have been rather conservative. They 

I have included the solid-wood content between a 

I-foot stump and a minimum 4.0-inch top of only 

! the central stems in selected trees 5.0 inches 

d.b.h. and over. Substantial volumes in rough and 

rotten trees, stumps, tops, limbs. and saplings are 

excluded. With the gradual trend toward closer 

i utilization and renewed interest in the use of wood 

I for fuel, there is a need for inventories of total 

wood fiber. I 

I Table 17 shows the distribution of total 

aboveground volume of all trees on commercial 

i forest land. by class and species group, in the 

I Piedmont of South Carolina. Table 18 shows the 

per-act-e distribution of this total volume by standI age class for major forest types. The largest difI ferences between conventional measures of 

I growing stock and measures of total volume occur 

i in hardwoods. Table 19 shows a more refined i distribution of hardwood timber volume by I-inch 

I 

I d.b.h. classes and class of material. With the ac- 

! cumulation of data from a special volume study 

i conducted as a subsample in conjunction with the 

County 

ongoing inventory, average tree characteristics 

can now be developed for each major species in 

the Region (table 20). The collection of dataon the 

lesser vegetation is still another step toward the 

ultimate objective-to be able to quantify total 

biomass within the forests across the range of 

forest conditions. 

The multiresource inventory provides a 

wealth of information for studying the ecology of 

various plant species. The frequency of occurrence of a particular species can be related to 

variou? forest types, conditions, and species associations. This kind of information helps to 

identify the environment required for the growth 

and development of certain species and to study 

successional changes that occur within a particular plant community over time. Table 21 shows 

the distribution and ranking of the five most prevalent species or species groups observed within 

oak-hickory stands in the Piedmont of South 

Carolina. The species composition within five 

vegetative layers is compared over time using 

20-year-age classes. Table 22 gives the frequency 

Acrrs ........ ............ Prrcrnt ..... ....... ..... 

Abbeville 219,883 4 22 27 27 20 

Anderson 208,201 5 28 49 13 5 

Cherokee 154,802 3 33 17 35 I2 

Chester 290,619 2 26 - 57 l 5 

Edgefield 234,637 16 24 46 12 2 

Fairfield 386,O 15 28 3 1 5 19 17 

Greenville 278,448 2 32 53 I I 2 

Greenwood 205,672 5 2 1 40 12 22 

Lancastel- 235,604 9 23 7 40 2 I 

Laurens 305,701 I 32 37 12 18 

McCormick 206,778 1 30 27 26 16 

Newberry 3 15,829 27 14 I 46 12 

Oconee 280,294 8 43 13 3 I 5 

Pickens 209,464 2 29 55 13 I 

Saluda 187.758 12 15 48 25 - Spartanburg 27 1,227 5 34 29 22 I0 

Union 272,352 7 33 40 20 - 

York 264.752 - 34 12 46 8 

All counties 4,528,036 8 28 28 26 10 

All 

classes 

Soil textul-e class 

Sands Sandy 

loam Loam Clay Clay 

loam 
Table 16.-Area of commercial forest land and its percentage distribution, by soil- and water-quality risk 

class, by treatment opportunity, Piedmont of South Carolina. 1977 

Treatment 

opportunity 

1 All / Soil- and water-quality risk classes1 

No treatment 

Salvage cut 

Harvest 

Commercial thinning 

Precommercial thinning 

Cleaning and release 

Stand conversion 

Artificial regeneration without site preparation 

Artificial regeneration after site preparation 

Total 

I . ... 

classes 

Acres 

3,223,011 

39,304 

209,064 

212,896 

32,590 

285,150 

155,948 

18,615 

35 1,458 

4,528,036 

................. .. Percent 

25 39 16 

41 20 39 

20 32 7 

52 40 4 

43 28 13 

25 41 16 

23 45 14 

64 29 - 

32 3 1 10 

1 

Definitions for cuil- and water-quality risk classec: 

I. Dul-(ng the recovery permd of the activity. the water quality impact \hould be rlieht !ru\pendrd \rdimrnr It\\ th;in 

IOU milligram\ per liter1 and coil erucion less than the riitr af new soil dcvelopmenr. 

2. Water quality during the recovery period of the activity can he impaired (suhpended sediment gri'iitcr 1h.m 100 

milligrams per liter). but cuil erociun should not srcrrd the rate of new sail development. 

3. Water-qu:iliry impact can he hlgh and soil erosion can exceed the rate of new v,il development duving the recovel-y 

period of thc cilviculIural itctivity. 

4. W;ltel--quality impact can be ~eriorlr and roil rn,\ion can rrcrrd rhr lare of ncw \oil devclopmrnt ti^ 5 to 20 year, 

after lrratmmt. 

5. W;iter-qutlity imp:ict can be very \erlou\ and soil erosion can encccd the rate ofnew \oil dcvclopmcnt formore rhan 

?!I yral-5 after treatment. 

of occurrence of major species on plots in the 

oak-hickory type, again by stand-age class. 

In multiple-use management, a diversity of 

conditions must be maintained. The diversity of 

forest ecosystems must be sufficient to accommodate the production of the desired combination 

of human benefits. These benefits include coniferous and hardwood timber products, outdoor 

recreation, solitude, clean water, and habitat for 

all endemic plants and animals. 

In multiresource inventories, one objective is 

to measure forest diversity in some way. In the 

South Carolina inventory, crews recorded important items related to forest diversity within a 450- 

acre circular area around each sample plot on 

commercial forest: (I) the percentage of forest, 

2 

and (2) the number of different forest conditions 

distinguishable on aerial photographs. Table 23 

shows the results of the classifications made at 

1,O 19 sample plots in the Piedmont. At 67 percent 

of the sample locations, more than 75 percent of 

the surrounding450-act-e area was forested. At 50 

percent of the sample locations, three different 

forest conditions occurred within the surrounding 

450-acre area. 

Finally, we reemphasize that the analysis of 

the multiresource inventory data collected in 

South Carolina is outside the scope of this Paper. 

In this chapter, we have merely given examples of 

the sorts of information that were gathered and 

the ways in which the information might be reported. 

3 4 5 
Table 17.-i'otal abovegl-ound volume of all trees on commercial forest land. by class and species group, 

Piedmont of South Carolina, 1977 

Sapling-size trees: 

Growing-stock 824.93 1 405,015 69,677 160,335 189,904 

Class of volume 

Non growing-stock 414,452 40,826 10,662 131,144 23 1,820 

Total 1,239,383 445,841 80,339 29 1,479 42 1.724 

Growing-stock trees: 

Poletimber-size trees 

Stumps 182.900 87,772 2,987 30.255 6 1,886 

Bolewood 2,067,400 1,004,371 34,178 417,164 6 1 1,687 

Tom and limbs 416,266 242.669 8.258 57.470 107.869 

All 

species 

Total 

Sawtimber-size trees I Stumps 189.715 105,335 2,297 40,183 4 1,900 

I 

! Saw log portion 3,129.476 1.847,9 16 40,29 1 523,660 717,609 

Upper-stem portion 428,041 215,224 4,693 78,151 129,973 

i Tops and limbs 342,845 153,628 3,349 60,748 125,120 

1 Total 4,090,077 2,322.103 50,630 702,742 1,014.602 

Rough and rotten trees: 

Stumps 55,782 7,949 41 1 18.456 28,966 

Bolewood 542,794 77,857 4,02 1 174,598 286,318 

Tops and limbs 133,139 18,595 960 53,243 60,341 

Total 731,715 104,401 5,392 246.297 375,625 i 

Total. all volume classes 8,727,741 4,207,157 181,784 1,745,407 2,593.393 

i 

Pine Other 

softwood 

Soft 

hardwood 

Hard 

hardwood 
Table 18.-Average total aboveground volume of wood' per acre of commercial forest land by st:lnci-age 

class. by forest types, Piedmont of South Carolind, 1977 

Lowland 

hardwood 

Stand-age 

class 

(years) 

All classes 

Forest type 

All 

types Pine Natural Upland 

pine hardwood 

'Trees 1.0 incher d.b.h. and larger, excluding bark 

feet ..... 

- 

0.01 

.I? 

.8 1 

1.61 

3.86 

5.78 

6.97 

6.93 

7.10 

5.80 

6.17 

5.26 

6.09 

6.88 

5.94 

9.47 

10.87 

5.45 

8.44 

Table 19.-Average aboveground cubic-foot volume in hardwoods, by d.b.h. class and volume material 

class, Piedmont of South Carolina, 1977 

I Includes both mainstem and fork volume to a4.0-inch topoutside bark 

lncludes limbs of all sizes. 

Diameter class 

(inches) 

Crown volume 'Total 

aboveground 

volume 

Bole volume' 

Stump TOPS Limbs Saw 2 log 

portion 

Upper 

stems 
Table 20.-Average tree characteristics for loblolly pine in the Southeast 

Inches 

0.95 

1.06 

1.20 

1 .29 

1.40 

1.49 

1.62 

1.70 

1.76 

1.85 

1.92 

2.03 

2.06 

2.18 

2.27 

2.40 

DBH 

class 

............ Fret ............ ... Cubic feet ... 

39.4 16.9 - 1.76 2.47 - 

44.2 24.5 - 3.22 3.95 - 

48.2 30.3 - 4.96 5.78 - 

53.5 36.9 - 7.40 8.30 - 

58.4 42.9 24.6 10.49 1 1.49 36.3 

62.7 47.9 32.9 14.02 15.17 58.7 

65.2 50.8 33.2 17.63 18.96 82.6 

67.5 53.5 42.5 21.62 23.14 108.9 

70.0 56.4 46.6 26.25 27.94 139.6 

73.5 60.0 50.5 31.69 33.62 176.2 

75.2 62.2 53.5 37.14 39.25 215.5 

77.4 63.8 55.7 43.30 45.71 259.6 

77.2 63.8 56. 1 48.58 51.40 299.3 

82.1 68.8 61.0 57.74 60.61 364.4 

76.3 63.3 55.9 59.04 63.29 378.1 

84.3 70.8 64.0 7 1.54 75.27 464.4 

'International %-Inch Rule. 

45 

Double 

bark at 

d.b.h. 

Boardfoot 

volume' 

Lengths Cublc-foot volume 

Total 

height 

Bole 

length 

Saw log 

length 

Merchantable 

volume 

Total 

volume 
Table 2 I .-Distribution of plant species by age class and vegetative layer for oak-hickory stands, Piedmont 

of South Carolina, 1977 

Overstory 0-19 

(30+ feet) 20-39 

40-59 

60-79 

80+ 

Midstory 0-19 

(15-30 feet) 20-39 

4&59 

60-79 

80+ 

Understory 0-19 

(5-15 feet) 20-39 

10-59 

60-79 

80 + 

Shrub layer 0-19 

(1-5 feet) 20-39 

40-59 

60-79 

80+ 

Ground layer 0-19 

(0-1 foot) 20-39 

40-59 

60-79 

so+ 

Vegetative 

layer 

Age 

cla.;s 

(years) 

Ranking of five most prevalent species 

First Second Fifth 

Sweetgum Yellow-poplar Loblolly pine Red maple White oak 

White oak Yellow-poplar Sweetgum Hickory Scarlet oak 

White oak Yellow-poplar Sweetgum Hickory Southern red oak 

Yellow-poplar Sweetgum Hickory White oak Black oak 

Hickory White oak Chestnut oak Sweetgurn Yellow-poplar 

Sweetgum Elm Loblolly pine Red maple Water oak 

White oak Sweetgum Hickory Red maple Post oak 

White oak Hickory Sweetgum Red maple Water oak 

White oak Hickory Red maple Black oak Sweetgum 

Hickory White oak Hackberry Beech Sourwood 

Dogwood Sweetgum Redcedar Elm Red maple 

Sweetgum Dogwood Hickol-y White oak Honeysuckle 

Dogwood Red maple Hickory Sweetgum Blue beech 

Dogwood Hickory Elm Other shrubs Red maple 

White oak Yellow-poplar Laurel Dogwood Blackgum (upland) 

Honeysuckle Greenbrier Sweetgum Blackberry Dogwood 

Honeysuckle Greenbrier Wild grape Blackberry Dogwood 

Laurel Red maple Dogwood Honeysuckle Hickory 

Other shrubs Switch-cane Laurel Honeysuckle Dogwood 

Laurel Switch-cane Red maple Hickory Dogwood 

Othergrasses Honeysuckle Forbs Blackberry Greenbrier 

Honeysuckle Greenbrier Poison ivy Other grasses Forbs 

Honeysuckle Forbs Wild grape Other grasses Greenbrier 

Forbs Honeysuckle Ferns Other grasses Poison ivy 

Forbs Switch-cane Blueberry Ferns Other grasses 

Third Fourth 
Table 22.-Major species of plant groups in the oak-hickory forest type and thei~ 

frequency of occurrence. by stand-age class. Piedmont of South Carolina. 1977 

Plant 

species 

All / Stand-age class 

Honeysuckle 

Greenbrier 

Sweetgum 

Blackberry 

Dogwood 

Forbs 

Redcedar 

Elm 

Red maple 

Loblolly pine 

Water oak 

White oak 

Yellow-poplar 

Other grasses 

Poison ivy 

Wild grape 

Hickory 

Post oak 

Scarlet oak 

Laurel 

Blue beech 

Southern red oak 

Ferns 

Other shrubs 

Switch-cane 

Black oak 

Blueberry 

Blackgum (upland) 

Hackberry 

Beech 

Sourwood 

Chestnut oak 

age 

classes 

........ ..... Percentage ofstrmple locations .... .... 

63 70 62 65 53 29 

79 78 82 82 70 7 1 

70 74 68 7 1 63 57 

38 70 42 27 23 14 

80 63 82 84 87 86 

89 83 85 90 97 100 

46 39 53 5 1 30 14 

44 52 52 40 37 - 

80 70 70 88 83 57 

26 41 28 18 33 29 

37 39 35 41 30 - 

70 37 75 80 73 86 

66 52 62 69 83 7 1 

79 8 1 72 83 73 7 1 

54 39 60 58 53 57 

82 67 87 88 77 43 

83 52 88 88 97 100 

34 30 35 38 23 29 

34 33 30 36 37 43 

11 6 7 12 23 29 

15 7 12 17 27 29 

53 39 60 60 40 14 

52 48 42 54 60 86 

52 37 48 59 50 57 

I I I I 5 11 13 43 

4 1 20 40 49 53 29 

37 33 38 38 30 43 

56 43 58 60 67 43 

6 2 3 7 7 14 

20 4 27 2 1 20 43 

38 28 32 42 47 57 

10 4 10 8 23 43 

0-19 20-39 40-59 60-79 80+ 
...................................... Number of sumplrs ................................ 

Table 23.-Distribution of samples in commercial forest land, by percent forest and number of fol-est 

conditions within a 450-acre circular area around the sample location, Piedmont of South Carolina, 1977' 

3u5 

46-55 

5645 

66-75 

7-5 

8C100 

Total 

Percent forest 

within 450-acre 

circular area 

Intended as one measure offorest diversity and forest habitat interspersion 

ANALYSIS OF THE DATA 

Total 

number of 

samples 

The multiresource inventory was begun to 

provide managers and pulicymakers with information about renewable forest resources other 

than timber. For this purpose, field data are not 

nearly enough. The new data must be analyzed 

and interpreted. 

For the first time. foresterb, range scientists, 

wildlife biologists, recreation specialists, ecologists, and others will be able to draw upon a common d.ata base. Thisdoesnot mean, however, that 

all needs can be served by a single analysis. Each 

discipline will want to evaluate benefits from a 

differ-ent perspective. 

We can only hope that all the disciplines will 

start with a common understanding of the basic 

ecological relationships. The plant communities 

that occupy forests and rangelands develop in 

predictable sequences, and certain benefits can be 

expected from each stage in the sequence. For 

example, a stand of young hardwood saplings and 

seedlings offers no immediate timber benefits, but 

may offer excellent browse for deer. By cutting 

and regenerating the stand, we reap the timber 

benefit and renew the deer browse habitat. However, harvesting also eliminates the mast and dens 

for squirrels. The scope of resource analysis must 

be expanded to take these ecological relationships 

into consideration. 

DEVELOPMENTS UNDERWAY 

Number of forest conditions within 450-acre area 

Computer modeling is a useful technique for 

improving resource analysis. We call attention to 

the DYNAST system developed at the Southeastern Station (Royce 1977). DYNAST consists 

of three complementa~y models adapted to different management purposes. The timber model, 

DYNAST-TM, harmonizes management actions 

for the production of timber. The optimum benefit 

model, DYNAST-OB, optimizes a specified 

benefit such as wilderness experience, recreation, 

visual appeal, habitat for a specific animal or 

plant, timber, water, or energy production. The 

multiple benefit model, DYNAST-MR. harmonizes forest management for multiple benefits. 

The DYNAST system is based on the relationship between the benefits produced and the 

distribution of a forest's stands in different stages 

of development (called habitats). The continuum 

of succession must be divided into habitats that 

are significant for the benefits being considered. 

The classification will vary for different types of 

forest and can be modified whenever a new relationship is discovered between a particular age 

class and a particular benefit. 

The multiresource inventory being tested in 

South Carolina seems to provide an ideal classification of forest habitats for input into the 

DYNAST models. Plans call for analvses of the 

I 2 3 4 5 6 7 X 9 
South Cat-olina data using DYNAST. 

Cut-rently, resource analysts with RRE in the 

Southeast are studying the size and age distributions, species composition, and succes\ional 

trends among the major forest types in South 

Carolina. Preliminary findings suggest that with 

few exceptions land-use patterns and forestry 

PI-actices at-e fragmenting the forests into smaller 

parcels or stands. For example, in the Piedmont 

Region. about 30 percent of the commercial timberland is bt-oken up into distinct forest conditions of less than 10 acres (Knight 1978). There is 

also mounting evidence of a strong successional 

trend from pine to hardwood species. 

Other developments underway include 

analyses of the multiresource data from the standpoints of outdoor recreation and wildlife habitat. 

The outdoor recreation study has been a]-ranged 

through a cooperative agreement between RRE 

and Clemson University (Saunders, Stachoviak, 

and Howard 1978). The wildlife habitat study has 

been arranged through a cooperative agreement 

between RRE and Virginia Polytechnic Institute 

and State University. 

The long-term objective of RRE in the Southeast is to develop and maintain expertise required 

to fully analyze and integrate all resource elements. For the present, our resource analysts 

who are most familiar with the data should establish the basic ecological relationships and make 

the initial interpretations of the findings. This procedure will identify the limitations and proper use 

of the data. After the basic ecological relationships are established, outside researchers are encouraged to help extend the analysis of the data 

through both independent and cooperative 

efforts. 

THE FUTURE 

We are optimistic about the future of multiresource inventories. We have identified an important task and made good progress toward its 

completion. As future assessments are planned 

and additional information needs develop, 

changes are inevitable. Our goal, therefore, is to 

maintain the expertise needed to make changes 

while we are collecting, processing, and analyzing 

resource information for the Southeast. 

IMPROVE EACH NEW 

INVENTORY STARTED 

Southea5tern Stater are inventorled in an 

established sequence. As work in one State nears 

completion, planning and pl-eliminary inventory 

work are underway in the next State. In every 

inventory cycle. however, each State is treated as 

a new start. Past work is reviewed, procedures 

are examined, and various changes are made before work is started in the next State. Major 

changes are usually avoided within a State because inconsistencies in the data within a State 

would create difficulties in both present and 

future measurements. We are constantly looking 

for ways to improve procedures, and we think 

each new inventory is a little better than the preceding one. By the time a State is revisited, therefore, the accumulated improvements are quite 

significant. 

ESTIMATING FUTURE NEEDS 

The frequency of inventories, commonly referred to as the survey cycle, has Huctuated between 8 and I I years since 1945. If current manpower and sampling intensity are maintained, we 

will be able to conduct multiresource inventories 

on an $-year cycle. Many people argue that the 

cycle should be reduced to5 years. Even if this is 

done, it will take 5 years to uniformly gather a 

piece of new information across the entire Southeast. To partially offset the timelag between wanting information and having it. the RRE inventory 

staff tries hard to estimate future needs and to 

collect data to meet these needs. The record 

shows that RRE has been fairly successful. For 

example, biomass studies were initiated in 1963 

and the demand for this information has recently 

intensified. A new class of management-related 

information, including treatment opportunity, 

stand history, timber availability, and improved 

stand age, was added to the inventory in 1970. 

User interest in this information is now on the 

increase. 

The challenge and risk associated with anticipating future resource-information needs are considerably greater with multiple resources, but so 

are the potential benefits. 

THE 1990 ASSESSMENT 

Most of the tramition to a multiresoitrce inventory, described in this Paper, was accomlished under stringent deadlines. A response to 

the RPA was needed; the 1980 Assessment due 

dates were firm; many separate initiatives already 

in motion required inventory involvement. Now 

that data needs for the 1980 Assessment have 

largely been satisfied and the South Carolina Pilot 

Project is nearing completion. it is time to consider what the 1990 Assessment needs will be and 

how they will be met. Several assumptions can be 

made in this regard. First. deadlines will be established requiring final data by mid-1988. Further. 

the Forest Service will want to use the best possible data base. and this base will be shared by 

various resource uses. We can also speculate that 

the 1990 Assessment will place much greater 

emphasis on use interactions and the display of 

alternatives for mixing and balancing combinations of resoul-ce use. If these assumptions hold 

true, RUE in the Southeast must strengthen both 

techniques research and resource analysis. and it 

must condirct multiresource inventories in 

Florida. Georgia, North Carolina, and Virginia. 

We expect to complete the initial rn~~ltiresource 

inventory of the Southeast by 1984. and to complete a second generation multiresource inventory and remeasurement of South Carolina and 

Florida by 1988. for use in the 1990 Assessment. 

GATHERING ADDITIONAL 

INFORMATION 

A descrihed earlier in this Paper, there are 

four ways we can gatheradditional resource information. We can collect additional information at 

each sample, overlay other data, acquire information already compiled in final form, or initiate 

special studies. The South Carolina Pilot Study 

placed emphasis on the first method and greatly 

increased the amount of data collected at both 

forest and nonforest sample locations. The next 

phase of increased data collection will involve the 

remaining methods of gathering additional information. 

The key to overlaying independent data 

sources is to have common geographic locators. 

Various mapping and computer techniques can be 

used to merge information from different sources 

if a compatible coordinate system is used. Past 

inventories in the Southeast have used an arbitrary coordinate system sensitive to the nearest 

mile. A study conducted by KKE (Cost 1976) 

shows that as location accurxy is increased. the 

cost also increases. A decision to abandon the 

existing system in favor of a standard, but more 

expensive. coordinate system will have to be 

made if RRE inventory data and data from othersour-ces are to be combined. 

Many sources of information are available to 

the resource analyst. Some of these outside 

sources at-e completely reliable. some are not. 

Despite questions of reliability, we must often use 

outside sources for types of data that we cannot 

efficiently collect. 

The remaining way to gather additional information is through special studies. Such studies 

are often used when gathering of certain data is 

too complicated or too time consumingfor regular 

inventory crews. Special studies may also require 

expensive. specialized equipment. In these 

studies. we subsample from the regular inventory 

plots, or we select an independent sample. New 

studies will likely be needed to: (I) validate wildlife habitat rankings, (?) develop weight conversion factors for space occupancy stocking estimates. (3) determine average weights per cubic 

foot for minor tree species, and (4) closely monitor the management actions in harvested pine 

stands. 

REPORTING RESULTSFUTURE OUTLOOK 

We have not yet formulated a strategy for 

disseminating our results. Perhaps some combination of publications. direct consultation, data 

transfers, and customized responses will be satisfactory. We really do not know. Wedo know that 

when we broadened the scope of our inventories, 

we also broadened the interested audience. Many 

of the new users ofour results may not yet view us 

as a source of information. We will continue to 

look for new ways to make the multiresource 

inventory as useful and as available as possible. 

We encourage specialists in ecology, hydrology, 

outdoot- recreation, range, soils, and wildlife to 

assist and cooperate with RRE in the evaluation 

and dissemination of the inventory findings. 
LITERATURE CITED 

Boyce. Stephen G. 

1977. Man.igemrn1 of eastern hardwood forests ful~ 

multiple benefits (DYNAST-MI31 US. Dep~ 

Agric.. Fur. Srrv.. Rcs. Pap. SE~l68. I16 p. 

Southeast. For. Exp. Sln.. Abhcvillc. "l. C. 

Coil. Noel D. 

1976. Accuracy and cost of qsvrral methods fbr geograpically locating forest survey sample plots~ 

US. Dcp. gric. For. Ssrv.. Res. Nolr SL~Z34. 

4 p. Southcast. Fur. Exp. Stn, Ashrvillc. N. C. 

Cost. Noel D. 

1978a. Abokrground vulumr of hardwoods in the 

Mountain Reeion of North Carolina. US. D~D. 

Agric.. For. Srrv.. Rss. Note SE-266. 4 p. 

Southeiist. For. Enp. St". Ashrvillc. N C. 

Cast. Noel D. 

197Xb. Multiresourcr inventories-a technique fur 

nrsasuring volumes in ctanding trees. US. Dep. 

Agric.. For. Sel-v. Res. Pap. SE-196. 18 p. 

Southeast. For. Exp. Stn.. Ashrville. N. C. 

Doig. Ivan 

1976 When the Douglas firs were counted: the beginnjngofthr Forest Survey. J. For. Hictol-y XI): 

2 1-27. 

Groscnbaurh. Le-is R. 

1952. Plorlrss t~mhrr ehtcmates . . . new. Fast. eJsy 

J. For. SO: 32-37. 

Knight. Herbert A. 

1971. Furrsl resources in the southeast survey munl~ 

tors fourdecades ofchange. South. Lumberman 

11?(?800): 147-149. 

Knight. Hcrbert A. 

1977. Sland-age profile of North Carolcn;i's timbrr~ 

land. US. Dcp. Agric.. Far. Sel-v.. Rewur. 

Bull. SE-38. I5 p. Southeast For. Exp. Stn., 

Ashev~llr. N. C. 

Knight. Herbert A. 

1978 Sires of timber stands in the P~rdmunr ofSouth 

Carolin;i. US. Dep. Agric.. For. Serv.. Ro. 

Note SE-267. 5 p. Southeast. Fur. Enp. Stn.. 

Ashrville. N. C. 

Lcnti. Robert J. 

1974 Summary of WHEP. "Wildlife habitat evaluation program." for the .Alabama River Basin. 

US. Dcp. Agri~. . Fur. Srrv S;\. S&PIZ InServicc Kcp.. 61 p. Jackqon Field Oi'lics. 

Jackbun, bliss. 

MacArrhur. Rahrrt H.. and John W. blacAi-rhur 

I961 On bird specie5 divrr\~ty. Ecology 11.594-5'JX. 

McClure. Joe P. 

1972. Customircd iorr5r inform;~tton retrieval tor. 

Farmer 31( 101.6-7. 

Pe;!rson. Flcnry A.. and He~bcl-1 S. Sternirrkr 

1974. Forest range invmlary: a multiple~oic sij~vcy 

J. Range Management:2715):1OL407. 

Saunders. P.tul K.. W~lliacn V. Srnchc,vlak. and Gordon E. 

Howard 

1978. Inventory on nondrvrloped. rui;il rcc~cnrion 

resources ~n South C,~rol~na. Dzp. Recreat. .lnd 

Park Adm.. Clemson Llniv. Kc,. Rep. 12. 128 p.. 

Clemson. S. C. 

Snyder. Nolan L. 

1978. Fore51 ulau\tlc< tbr the Piedmont uf South Ciiro~ 

lira. 1977. US. Dep. Agric.. Fur. Se~v.. Rcsour. 

Rull. SE~45. 33 p. Southe~rt. Fol. Exp. Stn. 

.Aiheviile. N C. 

Sternitrke. Hrrhrrl S.. and Henry A. Prnt\on 

1974. Fui-est-range resuurcer rtatistccr for Southwr<t 

Loulslana Parishe,. U.S. Dep. Agric.. Fur. 

Serv.. Rrwul-. Bull. SO-50. 22 p South. For. 

Exp. St". New Orleanc. 1.3. 

US. Drpitrtmcnt uf Agriculture. Forest Scrvicc 

1958. rimher rehuurccs fuc Amrrica'c future. U.S 

Dep. Agric.. Fur. Scrv.. Fur. Resour. Rep. 14. 

713 p.. Washington. D.C. 

U.S. Department of Agricultore. Forest Sc~vtce 

1965. Timber trends in the United Sure\. L1.S Dep. 

Agric. Fur. Srrv.. Fol. Rewilr. Rep. 17. 135 p.. 

Washington. D.C. 

US. Department ufAgr~cultorr. Forest Ssrvicc 

1973. The outlook for timber in the United Sr.trc,. 

US. Drp. Agric. For Serr.. Rr\,,ur. Rep. 20. 

367 p.. Washington. D.C. 

US. Depllrtrncnt of Agricullul-e. Forest Scri.ice 

I. Field instl-uctionh fhr South Carulimi. 1977. 

Soulheart. For. Exp. Stn.. RRE Field M;inilal. 

Ashsvillr. N. C. 
APPENDIX 



P.I. by ___ >-Salt 2-1-5 acres >-31-110 tset I herrai 3-6-10 aczes 1-111-190 Feet 2 GioYnd 

water Class 4-11-15 acres 4-191-270 Feet 3- Deleted 

5-16-20 acres 1-271-310 feet Date of p:. 

>-Sire6-21-21 acxes 6-351-430 feet 

7- 2 6- 30 acres 7-431-510 feet 

8-31-11 acres 8-511-590 feet 

I 51iC3kDUii INE TLxT:IPI 

T-mIT 0s DIII"?BIIICF WO 

OLD P2ST D.sTT;Ra*>cE r~ssL~,c~.'Io~ 

L 

- 

- 

Yi 

2 

5 

34 

2 

- 

- 

- 

- 

- 

I 

- 

- 

- 

- 

- 

- 

- 

- 

1 

- 

- 81 Logqn9 10 ~mzccts 

82 TSX 2s a>,*sms 

dl IYiiiCnYlunF 30 r,<* 81 -d Cl.lnny a0 m-dS BI cmurision ro ia w.nrn.i fCl**/ or noncom 60 i"ppi..lion 

.FrSI.I ID...L 1-d 70 OfhmI 

1 13, 

I 12, 

! 126 

128 ! LO7 

i 113 

111 I ,I> 

12, 

l,> 

I 

I 

I oa> 271 

010 

260 

; 241 

222 i 060 

I 090 

129 i 

I 9>> 

! ,6> 

j 69< 

693 

3.J 

i 333 

&a, 

723 

65, 

970 

66Z I 535 

'52 

It6 I 59" 

317 

"53 

61: ! 73% 

-. 69, 

920 

621 

I 

1 5ao 

5x1 -, 370 

90. -, 837 ! so> 

i 82, 

a13 

832 

826 i d9, I 311 

1 <a0 

i 59, 

5% 

-I ex 

038 

-, 680 

822 

i 52, 

a,n 

I 835 

833 

! 806 

I n17 

e,a ! 812 

>,a j a04 

e27 

8"> 1 Oil I ,>I 

I a16 

-I 

I 80, 

eel i wo 

I 819 

893 

I ,a* 

$68 7 39, 

43, 

310 

421 

661 

66" 

760 

701 

0 NO 

I Baal, 

2 T.P bi.n*ng. 

1 BinnCh 

BIIll d.f.Cr Yld tnB br~~*.q. 5 8..lal dFLICi _d bi.nrh ,ru6r 6 TOP br-*a91 ma branch .rvbi 

7 Basal LIFL.Cr, top b.m*.o. 

Mb bCMCh 

Ti9 1 ::; 

521 I 722 

121 

a11 

712 

931 

352 

I B. 

ill 

! I15 

999 
: CIISYI.r Iqy=i. 

PIOC i//s . ,i.d.Ys >" ie.c, . <*.a* fS*C, 

1 117.75 2SB.7, 

1/1 acrr a>.>* ,*7.,6 

1,s aez* 52 66 93.34 

STMD SZZL 

iZY 5ic3nnui 

1- -1 s-**:"bcr 

2- -2 P"I8k.:"be~ 

3~ -3 JIPljiY i ieid:."" 

am w~~s~~c~~a 

mn "3s PaTmW 

0 W~"~~~~~L 

1 rsolac*d c"rs~k 1-3- kb.m I" scr*m ." -d h"&"*d ,," -11 PLdir by rontoirrr urrr 

> Ias.atcd r"~-*t hmtws*" 1" 

-"a 30 acrps *"d b"*>dd U" 

.I. siaFI b, "On?ariit ,lie3 

3 z,ol*td rsr*st betv""" 50 

*"d 10s scrss -6 b0""6*d 

IidDI by "onroierr 

* 1 s-,*,,. d ,sc*mk kk"*"" 10" 

&"d >DO *crns -""ad I,, lidls hY "Onr0rl.r YS.. 

i 2 lmnj, nmrO* r-.nrei or 

s_l/j Of LD/*lr bO""d.d 

blth BY nonroreir "rrr 

6 nay I_ll, ICsrrejPd, 

.xlDSUlm-.h&Ve* fOle.: n.CDs 

ljVId by IriiPs 

infri.perl.d """rarrir 

7 I"tmc=xd zsrsst a"a """. rsr**t *s"c th- 

*"d m*por 

B sLltie~/d hloCkj Of fijCIr 

10Ds.ly iellfei by "-lou"i 

,t z-zm~c Land 

9 roresc araaa "5 m"mr 200 

acz"s 

S7MD mPJGI,* 

L N" jY.dDniF "L Pla"cln/. 

i s."ce s"s"ny tZrnSS pl*,kd or 

s".lCd wITn .FSFPt-IP iyYiYll 

1 ?rl"l to lljr J"rYmY riels llmrl. 

""8CR us rsrrr arQUIED 

FOR iS.?.FEELShm S-nXG 

BY D.B.". c-s 

D.b% . s~=* -c =crs 

. ucre . ,,> "2 9d 47 

L/a 7, 39 

57 29 

40 20 

1" 26 1, 

12 19 10 

16 15 

16 12 

>8 1" 

10 

I, - 2 a inch trsri 

OSSYII"Y >" Sllmpl inOYlli 

>* co""t"a am 1 

SrnXIWG STLhn-s FOP TRESS 

L acz* 

*is- : ... . e.ismr "'C . "1 ' Yl:Tirr 

ssdLsa9 600 .I, 

560 18 

a60 .z> 

,do .23 

.a2 

10 155 .65 

12 1,s . *, la 00 1.11 

L6 '72 1.33 

10 '0 1.67 

20* 53 1.9s 

o NO sIId LOYISP 

1 "1110" PI.F 

I OfnFz jOfl"UOd 

i D*~~i*ls hYYIFDd sIei t.iii (I.. ".l,"~-~~~l%~, rnlpl 

rYPIIO. 10llnnd *LIFIL.Y-. CIIFllY 

bSr* nairn"rr rra as*, rairi 

C&, ,.nesrjur u-, iumnorr. 

er ash 

4 or/lj nudl"Ud lsld trel SPFCll* 

- WSGrn? rn C""i 

, "r UI* =-nqa*l. 1:-d 

rjFI. Wqsr_q ljr" or m FOlfliST 

">a -,w**lF .:mo -LC- 

, L u?cl, lmr.YI rreE wnlreiirl *a 

=maqm*lc mt-"* crsws 

Xa55:811111 

SEC7,OX I"m7. 

0 SCUP m8ct.s" 

IS* ier;lan. rrrn 

1 -/- jlCrjOn, rlln it- 

, Top jl/ri"n_ main sisn 

4 il" sFCr>"n. LOI* 

5 upper ;t.. rpcfxon. Lor* 

6 TOP IPLnon. ?-I* 

I .Liz *Il 1.- I"Ctio. 

Y:lili*i. 11* 

s minor i-nai 

-. 

lPilCMt LYI cis-, 

: 0~3 

2 10~13 

3 20-29 

a 33-39 

5 ao~49 

l0.59 

7 60-63 

6 ,a-79 

9 S0~89 

0 90.99 

jFId"U ncr.pm*lr i":".ml. 

r I~~~ rli plmira or 

sceasa v>cho": mcc""c*,8 s"z"..la, 

I PjlYi to inst sY/"eY tjCII PLs"-.d 

il.dPd .Cilc-,e 

sw"."~,. 

MOPJZOWT~ %O?F ""mIZO2<TXl SLOPS 

C"~~10~ PER 70 CO~C~I"~ *En ,GO 

FEET OP SLOPE OIST. rez, "F S,BPE B,S?. 

Pmxcs"c * rc*k PSZCS>.t FSSt 

ee< *<_ 

0.1 0.1 

10 0.4 10 c.5 

1s 0.8 15 1.1 

20 1.a zo 2.0 

25 2.1 25 3.0 

30 2.3 30 4.2 

35 3.3 >s 5~5 

a0 5.0 a0 7.2 

as 6.2 d5 8.8 

50 7.d 50 10.6 

55 8.7 55 12.a 

60 3.9 $0 14.2 

6, 11.3 65 16.2 

70 I>., 70 18.2 

80 15.3 80 21.9 

9" 17.3 90 25.6 

2" 20.5 100 29 3 

110 23.0 110 32.a 

1x0 25.2 

-

120 36.0 

- 

TEZATWrn 0"P"L-ITX 

0 vm creS-"t "-*as* 

1 SllYIID ="f 

2 "asmqk 

I c"-cxc.&l th."n.nq 

4 PriLO-.iLl.l thl."l,,q 

I CiD__s. z.IF.I.. 0. Orher illrEaL*ilti 

c"tr>"q 

6 sun* -""-rs2m" 

3 xjrjfjCia, rrirnrinr.on "..hour 

pICIYafle" 

a LlilflSld II.L"°i.r.D" nfcli IiTL 

pr*p~r8c.o" 

- /

I PO.>* rnrm 

r.krn *r poimi rrtho"r m 

"r s-st~t"k>"q. * e">"c :*" sas, :r<d mr>q>"A: 

l"cat.c" ,": .""""c"r, a 

a -h>tLmd ,"<aL>"~ 

I bSLnt iml.l"led "f o:lO.n"i 

LoilrlY1 blii ."Ys"~YIy :aP- 1 

a s~irilYtP ,paint. 2 r 

-- S*,WLE XI:,> 

I L-.plr Lrcrr.o,, cprrri L.2, 

q>a,. ry ah .,,,:cs*r."d co:msr, 

Lnrr,; 1-4 kInr La,: 

I _@IC lrrlriOn L"nrer iYILl 

""I~.L.Y-d COI".C.I :Oilit 

"f :."* ,l,r ,"L"IY *id i 

.riYcllO,, "5 i:llf la P1. 

1 LOclciO,, SO"TFI ."..I 

Y"r.IPr"ld ~-.~~.~l LOi 

1-d at c-- "f ,a~t SLr""" 

rFCOn.rl"Sr13" .Id PLOI L 

..POl.lbll 

C""5 

I OF" qjOa 

2 Dr.;nMT 

1 COd.N"-Z 

4 lnfeiaeWnr~ 

3 NsrrOmn 

iy,,o.TiO- b.1,),:3 aii-iii~ii =s~ni ~=~irlni rYaii. 

: jOdl iOYld b/ "nsilj built :,,is rnF sr-a. 

, ii"ld. .* d.frliY1T c. biild inr= ms 11-a. 

"Pis iiilliF"lr ."placT.ill r0 bull6 LOT. fh. 

d,e jlol*. Itljr PI,.ICII "b.iiCl*.. 

-- 0PEmBIL:TY 

: Yo pjahl- 

> iYlirFd ,.","ill iI. crnd.rlnnl >" "iSL"*i 

, Xlllliaf. ,lope ,.rirnqing :0~,9 plispnr,. I;iegulni rrlrrlr. 

-VCi iiOVl * COidifioli Li..Ting mr type rqu,p".": 'hal 

:OYld b/ OYLr=teC ,>C>." the :.rp.t coid:r.un ljXFd l*L dry r.rn.l Lo;elt i",.dif.m fYPILil of nilrl- 

~h lCl ..a I"LImI.Pd eii nrrnr or iSllld. 

5 S1".cE IIDpF1 ,.YFl.ll"Y 4O.i* OIIC."~,. ilOX*" Lerili.. ox 

Oms/ Id"FII. "rO""* C"nd.Ti.n. "hlLl 0i.li.Fllli Iu7it P"lliP6 hd"erjF oPFmrLn* condirioil C.L~PC tY ~"'.'~,~i -rrri ;ra*.emI IICPLI ID eiiCFnf "I -rE. 

'""'Drrlwc VZcrr~TIa* cusi 

o Nr ngniiiinni inh.a.r.nq uioetrrian 

1 sS~:njco, .innu -a isr nrisnrs 2 SFnrllild. ">th FIVcr i.i9F ieig:.rS 

3 scarillC* llj10 it-. -d mil lll.Ohc. 

I Inr.ard.nrr drnilt", r.lll i:*ni. -* :"" hr:ghtI 

5 i"f/-edj~cj iens.fi, ".rn *.rm< sr nmlgnri 

O i"ila.di.cP d."Ilw. ".rn rrrni -d trill .Flyhrr 

7 Olns* *.rn jOnll M* Low hlilhll 

B menre rrrn errher lmrr ,r-. ar r-n nr.gh:l 

P DSrnS% wLV laze* -Ems -0 tan he.qhts 

SmeE ,"*rc*"<, 

&sv:"T <mm"r*"s, 

0 0-9 

1 10-13 o no LIPFLf 

2 20->3 1 118.12 

3 30.33 2 23.67 

Aa-49 , en~ll2 

5 50.59 I Ill~ii, 

m,wER 0, .mL~s,A:Eo sP=~, 7-1 

-- ".,. . rc" ?o> 10 ipir. oi nrsv xl 

23 

10 18 

11 15 

12 1, 

1, IC 

14 

15 

,b 

17~- 

L9-X 

I". 

11 ,,AL.s,,a, Fsf-bc 

12 SL3 

1, :"dlLa H,sc~l. 9ea*ra. 

Y, 3ute 

16 CO""CY i_z.L19aI 

2, TOIL.L ."d",fri 

a0 cmrner 

50 r-cr~o*""< lemsCa 

61 IISCF. .rl"., iOrpOl*f" 

70 IISL.i. Pii"., .ie."idYl 

BU X l prl"., COI;-Or.cC 

9" Cii". . i"li"il". 

. 

5°C 0' '""I' COXO2~ 

1 * I_.qYL_ B/nPCb i*Y."i 

*h." =d no-, b"""d&lY. 

SYItOllq ~.dtn.t"-L~"..h ie 

1 I senan, n.r.ii an* or 

PiOUille"j..lre"ljO"s, . * OiYI1-i. SrnPIC lsc*t,~," 

cs"zra, ar*s. 

1 1 ..l%", or 

nrscr.s.~"s. ~x>e"~.o"s. "~ bOYlemy J_?LF iocjrjln 

:hs c*"crsl ares. 

4 =* m~ -?* d.3t.:.c: arsas 1 

IjVse rYIPrh"l bi- ICiiilS, . sr ha,* se s."s:ar rar->t c 

sac,. o<nr.Ol _ _ mr a> 

=csa. 

5 T"" m*rs JXmcL"=> aress i 

ll"kca :"q*:n*r b" vcr.Ps, s 

ef hmmm -c ~%rA>*~ <SZ**C < 

iarnrzrn ir rrr in t 

a>mtLzck *r*a~ 

6 it i.31. frm9*.% a: b-as 

Land CYPISII Of ion9 "*ii"l 

mArq.>o, "&crow cmress SLr' 

13"< ,-as "L rlYFirjd Land 

"' T"' "Y'T'.> 

-- L3Flf.n" (lair ria& 0 HmnS 

1 ca".r.sm b*LOW *.".h. 

2 ca".k.ss *s"* -.b.h. 

I CI".CjCl belo" %,,d *""" i 5 ,.. 

"YNSI lil= -- xt1-9, 

6 60.69 5 158.202 

1 70-79 6 2YI.i47 

8 80-83 , 2aa-292 

9 90. 8 23,-,,1 

GR0l.N" Lam USE 

2" z*",.erc:a, roL-~k 

AO OnprdUFri"~ LOrFIi 

5c Pros :"rest r*ssr"v2 

6. iilOlmd 

6. pl,tljr 

61 YIljrnl jmqela/d 

"a Id," taz",s,,o 

66 okheX :-,ma, L"c. 

rssS:**da 

b7 Uzb- -* 0m"X 

68 F.a:m 

91 c~x~"s "ater 

92 #s"-c*"s,,x ,at"r 

60 

1 DSsLr*,* trss 

2 &cc~~c*le u** 

1 mu9n tjCI 

4 xsrcen trss 

CODISG sum" 

som,< CrnOLWA 

mu ,937 
... 

0 

211 X-Mm "NL..<dY 

z22 PO"6Smi... 

060 i=*Ces.r 

090 IPrYEI 

129 aLr* PIN "Am "Ammo$ 

00, xl<*r 

008 _.1=* 

009 Ba"hmY 

023 B1lSLby- * BIYbrri 

6 B1~srm ?=hrfo 011 Bi-l*, 

020 BYLL.ICnyI 

029 Cnin*.p'n 

012 m"il(.-".Uinq-,n~* all sld*D.iq 034 rnlik_ 

3 P.LtY.".h 

0% HI 

018 

03s 

011 ".IC.Y.Y 

041 e~~kl._rr~ 

6 XY~TMI~. 

047 L.suzCl 

048 

081 *Infl.toe 

ow sww 

052 PI166 PilVlk 

5 ~dadmdian 

0% w.. 055 Il"-pnl.rff. 

056 IPIFL*",n 

161 if. mmmOif 

03, Ifil"b*i" bYOh 

058 SWC 

053 

069 "%bum074 X-iflr 

7 X.r*-hll=l 

076 "a"m" 017 Qfnar .NnbI 

-" CLWmITra 0 NO,," 

0 1 LOCild 

1 5-11 Yeas -.h.,U1 1 

cand.t'.n. or ..rpw.. 1 NO cillpll~img 

=-C"rr>T "ithl" fh. for*,* " NO huntln8 

5 NO Lirhlng 

6 My durnrlng 

7 0th~ sjg,,l 

8 msrco"ra~t 

n *"= s nth*. l"'*"",l 

I on- Di -- _*cs 1" rhD fDi%.r 

C0ndlf.o" c0"Uin. Epml,h *os. - 

Tams 

o *m bro".ing 

I LLqhe biorsinq - dltLlsuit fo 

fjnd bra.= PL."f, ." .m*L;. 

US. *M 5 PFrSsnr ll_n 

gj_ld 

1 *D#Liare br-.i"* - LzeW."n). 

I-8 brOl.%nrj ^" ._I* 

1 8S.V h_".L_ - sm.inns -re LllM 13 PYClnf -< /_IY_ 

en Me .n_10 lSjs hj_.d 

0 -. 1 L4hr gird"9 - dl<llsult L.

tjnd 9i...d .I"-. L... M." 

35 3 *c pl."r. s_ld 

I maer.r. qi.riw - tnqmc9 

<ha 97.IlW 0" M. ...PI IIZ.. 

Vn.i.l,y 15 ul 70 . oc *l,"L. 

Y- sx./Dd. 

I "*.V 9r.z3.v - -bmL". 
PLANT SPECIES:' 

Code Common name . Scienritic name 

YELLOW PIYES 

Lohioily pine Pitiir~ iardu 

Longleaf pine Pinur poiitslri.~ 

Pltch pins Pinus riyidit 

Pond pine Pint,s xeroiino 

Sand pine Pinirs ciiirirn 

Shortleaf pine Pi,>irs rchir>oio 

Slash pins Piriiis riiioirii 

Spruce pine Pinlri glnhru 

Fable-Mountain pine Piniir prrti~rns 

Virginia pine Pint,.? cir,qinionii 

OTHER SOFTWOOD 

Atlantic while-cedar Chomorcvporir ihwider 

Baldcypress To.rudiiirn disrichilrn var. di.~richim 

Fir Ahies spp. 

Eastern hemlock Trupa canuden~ir 

Northern whits-cedar 'Thuju iuocodenralis 

Pondcypress T~.rodiiim diriichrm var. ni(ions 

Eastern redcrdar Jimipenis oiryiniona 

Spruce Picra spp. 

Eastern white pine Pirirrs srn,h~ls 

SOFT HARDWOODS 

American basswood Tilia omerirunu 

Black cherry Pntnirr serorino 

Blackgum (lowland) rVysso rvlaorico 

Blackgum (upland) Nyssn sylaiiiica 

Boxrlder Acrr neg~indo 

Buckeye Aesculirs rpp. 

Butternut Jirglans rinrreo 

Cottonwood Popsl<rr spp. 

Cucumbertree Mugnuliu ucurninoru 

Elm L'irnirs spp. 

Hackberry Celii. oci idrniali.~ 

Loblolly-bay Gordoniu ln.~innrhirs 

Magnolia MugnolLt spp. 

Red maple Ace? rirhrurn 

Silverbell (in mountains) Holusiu spp. 

Silver maple Acrr rncchurin~~,n 

Sweetbay Mu~nolia uirpiniunii 

Sweetgum Liyrridiirnharsryracdliio 

American sycamore Pluronirs nccidunrnlis 

Water tupelo N~rra nqeniica 

Willow Solix spp. 

Yellow-poplar Liriodendron rirlipiferu 

HARD HARDWOODS 

Ash Froxinrrr ~pp 

American beech F'ipur prandifi~lio 

Birch (except yellowl Berirln spp. 

Black locust Rohinio psrirdoncocio 

Black oak Qvernrs uelirri~in 

Black walnut Ji<glans nigro 

Bur oak Qarrcss rnurrociirp<i 

Cherrybark oak Qerrcrrsf~lcoru var. poyodrrefhlio 

Chestnut oak Q~rerc~<sprinrrs 

Chinkapin oak Qr~erctis rnsrhlenhergii 

Flowering dogwood CornirsJloridu 
Florida maple Acer harbatrrrn 

Hickory Cory" spp. 

American holly lirr opoco 

Honeylocust C;irdiirin rr-ioioorhos 

L;iurel oak Quercirs ioi~rifi>iiri 

L.ive oak Qiien.t<s airgi<iiar~o 

Mulberry Morils spp. 

Ovrrcup oak Qlrercus i?roro 

Common persimmon (forest grown) Diosp~ror uir,qi,iionii 

Pin oak Qiirrcrrs polr~rtris 

Port oak Qtmvct<r stell~~to 

Northern red oak Querct4.s rilhrci 

Scnrlrr oak Qlrrrciis cocci~~ra 

Shingle oak Quercus itnhricorio 

Shumard oak Qrrrrcs.~ shtrniiirdii 

Southern red oak Qerrcii.sjh/cutu 

Sugar maple Acer socchonirn 

Swamp chestnut oak Qiirrcirs miihoirrii 

Swamp white oak Qrrrrcsr hicotor 

Water oak Qt<e?ci(s nism 

Whlte oak Qorrcirs nihri 

Willow oak Qi(rrcirs plirl1o.s 

Yellow birch Brli<!o olteyhonirnsis 

MISCEL.LANEOUSTREES 

Bear oak Qiwrcus i/icrfo/i<i 

Blackjack oak Quercl<s miirilandiia 

Bluejack oak Qrrrrci<s inrano 

Dwarf live oak Qiiurcvs spp. 

Dwarf post oak Qilircirs spp. 

Turkey oak Qi~zrcirs lorui~ 

Other scrub oaks Qirr'n.irs rpp. 

Ailanthus Ailiinlhiis spp. 

American mountain-ash Sorh~s americanu 

American hornbeam Cirrpintr.7 carolininna 

Catalpa Carulpn spp. 

Chalk maple AC~I spp. 

American chrsrnut Cnstiinerr dentoto 

Chinaberry Meiin uredornrh 

Domestic fruit (apple. etci rMrilirr spp. 

Fire cherry Pntniu spp. 

Eastern hophornbeam O~rrvn uir~ioiono 

Mountain maple Acrr spicno,m 

Ogeechre tupelo Nys.~a ogeche 

Osage-orange Marlrrrn pomifrro 

Common persimmon (field grown) Diospyms uir~iniona 

Planertree (waterelm) Pionern oysotiiii 

Rsdbay Per.s~u horhonio 

Ea\tern redbud Curci.~ cnnudm~i~ 

Royal paulownia Pori/oa,nin tomeniosii 

Sassafras Sassczfros nlhid~m 

Serviceberry Amrlonchirr spp. 

Carolina silverbell (ercrpt mountains) Hoirsiu corolinri 

Sourwood Oiydrndrirm nrhoreirn~ 

Striped maple ACE?'~C~SY/L'O~~(.~~~ 

Orher miscellaneous trees 

TROPICALS 

Casuarina Clrsrriirinii spp. 

Cajeput-tree Mrialr~irn Ip~rcodendron 

Caribbean pine Piniri curihaeo 

Citrus Cirrirx spp. 

Euciilyptus Ei~~o/.vptr~~ rpp. 

Mahoeany Sv.it.rmirr cpp. 

Silk-oak Creuillro rohilsrit 
034 

035 

036 

038 

039 

044 

045 

046 

047 

048 

(187 

049 

052 

Ihh 

053 

054 

055 

056 

079 

OX? 

OX3 

OX4 

OX5 

OXh 

OXH 

OX9 

I34 

13 

lih 

Orhrr tropical\ 

Cabbage palmetlo 

Other palms 

SHRUBS 

Alder 

Plitmr ar;llea 

Norrhsrn bayberry 

Blackberry 

Blueberry 

Biue~tem palmetro 

Brhmblcs 

BufT.tlo-nut 

Chinkapin 

Devil's-w;ilking\tick 

Elderberry 

Gallberry 

Ferterhuih 

Haw 

Hawthorn 

Harcl 

Comrnon 5weetleaT 

Huckleberry 

Hydrangea 

blountain-iiiul-el 

Mitngrovr 

Mistletoe 

Pawpaw 

Plum 

Prlvet 

Kosrbay rhododendron 

Rucs 

Saw-p;dmetto 

Spicebush 

St. Johnhwun 

Su-;twberry bu\h 

Sumac 

Sw;~mp cyrill;~ 

Viburnum 

Southern b.cybsny 

Wltch-hazel 

Y;lopun 

Orhrr \hrub\ 

VINES 

Cllmhcng lo\r 

Cru\\vinc 

Dewberry 

Greenbrier 

J;tpanere honcy\ockle 

Kud~u 

Poi\on ~vy 

&',t;,'~" 

rrumpct creeper 

Virgln);, c~eeper 

Summer grape 

Yellow jc\\itmcnc 

Othcl vine* 

GRASSES ANIICKA 

H,ihiilglic\\ i& orhe) ~,c\t~~rcgiic\\~\i 

Hlue\rcm. hig 

Hlucrlem. hronm\cdgc 

Hlu~.\rem. \Icnd~.r 

Hlue\rcm. crucplng 

Ahitr! spp. 

Rliod~~dct~dro,i roIe~i~/~~i<ii?iit,i 

rMyricu pmwluoilXo 

Kirhirs ipp. 

Vucciniir,,t spp. 

Sah<tl nzinor 

Rtrhrrs hpp. 

Pynrluriii pshera 

Cuianca spp. 

Aruli<i rpit>oso 

S',,,thl,~i,., \pp. 

Ilpr spp. 

Lynriiu lr,iido 

1lr.v ipp. 

Cr<rror*.ir.> hpp. 

Coryli<., cpp. 

S~mplocos ,i,wro,i<t 

ti'ivir,rriiciu \pp. 

Hydriirip<,<i \pp. 

Kaitriio i~!rif;diu 

Rh,;i~phoni \pp 

Pli~irudcndron hpp 

Asi,,linii upp. 

Prrma.! \pp. 

Ligir.vlri,l?l ipp. 

Hiir,dodoidror? ,,iii.rit,~!i,?i 

Rora \pp. 

S<,rer?oo rcpe,r.\ 

L~,I<I<,~, h<,,,:,,,,, 

H~p~ricirni \pp 

El,<>,~"t?,$,., <,ttz<,r,c,,,,<<> 

Klirn rpp. 

Cvrillii r<rierriijL,~(i 

Vihurt~u,r, yp. 

rMirica wnlrrii 

l/<,,,,<,,,,<,/,.~ "!,~,V,,,i<<,,<, 

l1e.r ~ot~ii~orio 
I M 

IJ? 

143 

114 

145 

167 

146 

I47 

lax 

IJY 

168 

151 

Bli~e\tcm. little 

Bt~i\tlegr.~\s 

C,irpcrgl;,\i 

C'utovrl-muhly 

Furcur 

1n~ll;tn glesr 

M;trsh-gla,s 

Panlcums 

Pi,,p:,l~zm 

Cummon seed 

S;lw~gl;li.. 

Sedgcs 

Switch-c:inu 

Pinrl;ind rhreu awn (wivegt;t\sl 

Uniulits 

Othel grashes 

Othei gsassl~kc\ 

Atidropopoir .siopii,iir.$ 

Seroriri 5pp. 

A.u,rii>prrr spp. 

,W,~/z/~~,rh~~r,~i~~ <, r,w~tz.s~, 

Fe,iircii \pp. 

Sor-,q/iaro-rrih 5pp. 

Sparlitla spp. 

Pl8r?iciri,i spp. 

P'ispii/i,i,i ,pp. 

P/ar~8,q,~8irt,.s C,,,~,II~U!!~~ 

Cloi/iii,,>,,ai,iok wisi. 

Cvpenrr bpp. 

A,?rridi,?iiria rrclo 

Ai-iriidii .srri<rii 

- 

L1,iioio bpp. 

- 

FOREIS ANDOTHERS 

C;,ctu* opir,ir,<i spp. 

Comporitc\ Ctiillpo~iitie 

FCI-~S Pr~rii/o,>iii.i(i 

I.ef,"rn~'\ - 

Lichenr 

Forb, - 

M,,\c\ - 

7 LCornmon and scientific names liqtcd ,tccurJing to rhe 

fulluwing cuurco: Dean. Bl;lnche Evans. 1968. Trecr and 

\hiubs in the hrart of Dixie. Z4h p. South. Unlv Pre\\. 

Birrrningham. Ale.: Ferxtld. Mel-l-itt Lyndon. I95O. G~my', 

rn;inu;tl of hut;i?y. 8th rd.. rewvitten and rrp'tnded. 1.632 p. 

Am. Buok Co.. New York: Kri\cy. Haciilnd P.. and W~lltam 

A. Daylun. 1441. Sutndardizcd plant names. Zded.. rev. 675 p. 

J. Horace McF;~rlsnd Cu.. Harrisburg. Pa : Little. Elhrrt L. 

Jr. iV53, Check 1151 of n,ltivr kind n;ttoliilircd tWrr\ of the 

L'nitrd St;itc~lincludingAI;~~ki~l. U.S. Drp. Agric. For.Scvv.. 

.Agric. Hi~ndb. 41. 471 p. US. Guv. Print. OR.. Wabhtngtun. 

D.C.: US. Dep;ll-tmcnt of Agr~culri~~'s. Foiert S?l\icr. 1Yhi. 

Fol-at Survey h;lndbouk. FSH 4813. I. US. Dcp. Agric.. Foi. 

Sel-v.. W;lshington. D. C.: and US. Urp;cl-tment of Agl-icultuve. Soil Consel-untion Srrv~r. 1965. ImpuvGinl nllivc 

gras\r\ for r;tnge cunsrlvntlon in Fiorid;~. lh p. CIS. Drp. 

Agrlc.. Soii C,,n\cr. Ssl-v.. G;t~nr\villr. Fia. 
INVENTORY PROCESSING SYSTEM 
FIR PROCESSING SYSTEM 

- - - - - - - - - - - 

INVENTORY 

PROCESS1 NG - - - - - - - - - - - "A" SYSTEM 

OUTPUT '8" SYSTEM 

SUMMARY f3 

" A" 

SUMMARY UNIT TAPE 

UNlT TAPE 

SUMMARY " A" 

AND MAP MASTER 

STOCK 

CARDS E 
VOLUME PROCESSING SYSTEM 

I 

A 

I 

I 

VOLUME 

SECTIONS 

\ 

I 

I 

TREE 

SUMMARY 

I 

4 

I 

I 

I 

I 

CONTROL CONTROL I 

CARDS CARDS 

4, 

I -+.-. 

SPECIAL 

FACTORS 

\ I 

VOLUME 

EQUATIONS 

'Y \ 
McClul-e, Joe P.. Noel D. Cost. and Herbert A. Knight 

1979. Multiresonrce inventorie-a new concept for forat sr~rvey 

U.S. Dep. Agric. For. Serv.. Kes. Pap. SE-191, h8p. Southeast. For. Exp. Stn.. Asheville. N. C. 

A hrief historical revirw shows why Forest Service Renewable 

Resources Units ere capable of rnultiresource surveys. A practical 

appl-oach to such surveys has been developed at the Sonrheastern 

Forest Experiment Station and demonstr;ited in South Carolina. 

KEYWORDS: Mensuration. forest inventories. resource ev;llu;ltion. 

rni~ltiple use. 

- 

McClure, Joe P.. Noel D. Cost. and Herbert A. Knight 

1979. Multiresource inventorics-a new concept for fore51 survey. 

U.S. Dep. Agl-ic. For. Serv.. Res. Pap. SEIYI. 68p. Southeast. For. Exp. Stn., Asheville. N. C. 

A hrief historical review show5 why Forcht Service Renewable 

Resources Units ar-e capable of rnultireso~~rce surveys. A PI-actical 

appl-oach to s~~ch surveys has been dcveloped at the Southexstern 

Forest Experiment Station and demonst~~ted in South Carolina. 

KEYWORDS: Mensuratio~i, fol-esr inventories, resource evaluation. 

multiple use.