Maryland’s Forests 

2008

Resource Bulletin

NRS-58

United States 

Department of Agriculture

Forest 

Service

Northern 

Research Station
 Abstract

The fi rst full annual inventory of Maryland’s forests reports approximately 2.5 million acres of forest land, which 

covers 40 percent of the State’s land area and with a total volume of more than 2,100 cubic feet per acre. Nineteen 

percent of the growing-stock volume is yellow-poplar, followed by red maple (13 percent) and loblolly pine (10 

percent). All species of oaks combined account for 26 percent of the total growing-stock volume. Yellow-poplar 

volume is increasing, particularly in the large-diameter classes. Red maple is the most abundant species in 

terms of number of trees and the population had been rising through the 1980s and 1990s, but current data show 

little change in red maple abundance since 1999. Seventy-six percent of forest land consists of large diameter, 

14 percent contains medium diameter, and the remainder is in small diameter stand size classes or nonstocked 

stands. There were approximately 5.9 billion cubic feet of growing-stock volume in 2008, and the average annual 

growth rate of volume has been approximately 2 percent. Additional information on forest attributes, land-use 

change, carbon, timber products, and forest health is presented in this report. A DVD included in the report 

provides information on sampling techniques, estimation procedures, tables of population estimates, raw data, 

a data summarization tool, and a glossary.

Acknowledgments

The authors would like to thank the many individuals who contributed both to the inventory and analysis of 

Maryland’s forest resources. Primary fi eld crew and Quality Assurance staff over the 2004-2008 fi eld inventory cycle 

included Thomas Willard, William Moir, Stephen Potter, Thomas Albright, Todd Renninger, Jason Gould, Chris Tucci, 

Michael Whitehill, and Richard Starr, Jr. Data management personnel included Carol Alerich, Barbara O’Connell, 

Charles Barnett, Gary Brand, Mark Hatfi eld, and Jay Solomakos. Report reviewers included Anne Hairston-Strang 

and Robert Feldt, Maryland Department of Natural Resources Forest Service; Sally Claggett, Chesapeake Bay 

Program; Eric Sprague, Pinchot Institute; and George McCaskill, U.S. Forest Service, Forest Inventory and Analysis.

Published by: For additional copies:

U.S. FOREST SERVICE U.S. Forest Service

11 CAMPUS BLVD SUITE 200 Publications Distribution

NEWTOWN SQUARE PA 19073-3294 359 Main Road

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November 2011

Visit our homepage at: http://www.nrs.fs.fed.us

Cover: Puckham Branch riparian area in Dorchester County, MD, 2005. Photo by Jack Perdue, Maryland DNR.

Manuscript received for publication May 2011

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on the basis of race, 

color, national origin, gender, religion, age, disability, political beliefs, sexual orientation, and marital or family status. (Not 

all prohibited bases apply to all programs.) Persons with disabilities who require alternative means for communication of 

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14th and Independence Avenue, SW, Washington, DC 20250-9410, or call (202) 720-5964 (voice or TDD). USDA is an equal 

opportunity provider and employer.
T.W. Lister, J.L. Perdue, C.J. Barnett, B.J. Butler, S.J. Crocker, G.M. Domke, D. Griffi th, M.A. 

Hatfi eld, C.M. Kurtz, A.J. Lister, R.S Morin, W.K. Moser, M.D. Nelson, C.H. Perry, R.J. Piva, R. 

Riemann, R. Widmann, and C.W. Woodall 

Contact Author: 

Tonya W. Lister

tlister01@fs.fed.us

610-557-4033

Tonya W. Lister, Andrew J. 

Lister, and Randall S. Morin are 

research foresters with the Forest 

Inventory and Analysis (FIA) 

program, Northern Research 

Station, Newtown Square, PA.

Jack L. Perdue is supervisor of 

Forest Resource Planning with the 

Maryland Department of Natural 

Resources, Annapolis, MD.

Susan J. Crocker, W. Keith Moser; 

Mark D. Nelson, and Chris 

Woodall are research foresters 

with the FIA program, Northern 

Research Station, St. Paul, MN.

Charles H. Perry is a research soil 

scientist with the FIA program, 

Northern Research Station, 

St. Paul, MN.

Brett J. Butler is a research 

forester with the FIA program, 

Northern Research Station, 

Amherst, MA.

Rachel Riemann is a research 

forester with the FIA program, 

Northern Research Station, 

Troy, NY.

Chuck J. Barnett, Richard 

Widmann, and Doug Griffi th are 

foresters with the FIA program, 

Northern Research Station, 

Newtown Square, PA.

Mark A. Hatfi eld, Cassandra M. 

Kurtz, and Ron Piva are foresters 

with the FIA program, Northern 

Research Station, St. Paul, MN.

Grant M. Domke is a post-doctoral 

research forester with the FIA 

program, Northern Research 

Station, St. Paul, MN.

Maryland’s Forests 

2008

About the Authors
Foreword

Our forests remain a critical element in Maryland’s landscape. Not only are they environmentally 

important, but forests also contribute to our economic and social well-being. To know if 

Maryland’s forests are being managed in a sustainable way, we need to be able to take a periodic 

snapshot (analysis) of the status and trends of the forest resources. The U.S. Forest Service, Forest 

Inventory & Analysis (FIA) Program, in partnership with the Maryland Department of Natural 

Resources – Forest Service, has previously inventoried Maryland’s forests in 1950, 1964, 1976, 

1986 and 1999. In 1999, periodic inventories were replaced with annualized inventories in which 

a portion of the fi eld plots are inventoried each year, and a full inventory is completed every 5 

years. The fi rst full inventory using the annualized data for Maryland was completed in 2008 and 

covers the period of 2004 to 2008. This report is an analysis of that inventory.

The forests which are vital to our quality of life have been under continual pressure since colonial 

times. First these threats were the result of unrestricted clearing and harvesting. Land was cleared 

for farming as the once awe-inspiring forests were seen as obstacles to progress. Wood was the 

fuel and building material of choice for a young and growing nation. After World War II, the 

country was growing and forests were lost at an alarming rate to make room for new homes and 

businesses. Today our forests face new threats —exotic invasive plants and insects such as gypsy 

moth and emerald ash borer threaten the health and diversity of our forests. Demographic trends 

continue to change the face of our forests through land-use conversion, forest fragmentation, and 

parcelization.

Still our forests provide us with many benefi ts every day which, unfortunately, we have become 

accustomed to and take for granted. Without healthy forests, we will not have quality air and 

water to meet our most basic needs. Forest land provides habitat for the wildlife we enjoy and is 

so vital to the fabric of our planet. Even during this age of technological advances, wood is still 

our “greenest” and most basic building material, and we are increasingly seeking the forest as a 

place to escape the pressures of modern life.

This document describes and highlights the current status and trends of Maryland’s forests. The 

trends that have been portrayed in earlier versions of this inventory have led to the Maryland 

Seed Tree Law and the Forest Conservation Act. 

I hope you will look beyond the numbers and fi gures presented here to come to a more complete 

appreciation of the grandeur that are our trees and forests and the opportunities and risks we all 

face together. 

Steven W. Koehn

State Forester / Director

Maryland DNR Forest Service
Contents

Highlights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Forest Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Forest Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Forest Health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Literature Cited. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Statistics, Methods, and Quality Assurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DVD

On the Plus Side

There are approximately 2.5 million acres of forest land 

in Maryland, 95 percent of which is timberland.

The rate of forest loss has decreased since 1964 and 

current data show no detectable net loss of forest land 

since 1999. More detailed photointerpretation data 

indicate that the current rate of forest loss is just over 

3,000 acres per year.

There have been some gains in forest land area, 91 

percent of which are due to the conversion of agricultural 

land to forest.

Eighty-seven percent of Maryland’s forest land occurs in 

contiguous blocks that are at least 100 acres in size.

Sixty-six percent of sawtimber volume in Maryland is in 

higher tree grades (1 or 2).

The amount of sawtimber volume, particularly of 

hardwoods, is increasing. 

More than 200 million tons of carbon are contained 

in the forests of Maryland, more than half of which is 

found in live trees and saplings.

Tree growth exceeds losses from mortality and removals 

in Maryland and the growth to removals ratio has 

increased to 2.6 in the current inventory.

Tree mortality is only 0.7 percent of total volume, and 

trees with poor condition crowns generally occur at low 

levels and evenly across the state. 

The loblolly pine population is stable with levels of 

removals nearly equaling growth as indicated by a growth 

to removals ratio of 1.1.

Data suggest that the number of oak saplings in the 

smallest (1 to 3 inch) diameter class has increased 

steadily since 1986 and that overall there is no change in 

the number or volume of oaks since 1999.

Maryland’s wood products industry generates more than 

$300 million of economic activity and employs more 

than 8,000 people.

Seventeen percent of Maryland’s forest land is in 

wetlands which provide many ecosystem services such as 

water fi ltration and storage, nutrient cycling, fl ood and 

erosion control, carbon sequestration, and habitat for 

wildlife.

Problem Areas

Forest area loss is not being offset by gains in forest in 

three counties of Maryland.

Ninety-one percent of the forest loss in Maryland is due 

to forest conversion to developed uses which is likely 

permanent forest loss.

Sixty percent of Maryland’s forest land is less than 300 

feet from an agriculture use or developed edge, which 

is close enough for the forest land to be infl uenced or 

disturbed by the edge.

Localized forest fragmentation, particularly in Carroll 

and Howard Counties, has led to a relatively high 

percentage (>30 percent) of the remaining forest in these 

counties in patches <100 acres in size.

Species composition is shifting toward large diameter 

yellow-poplar stands, with oaks declining in relative 

volume in the larger diameter classes. This may have 

implications for wildlife, including oak-dependant 

species.

Highlights

1

Old growth oaks, Garrett County, MD, 2004. Photo by Jack Perdue, 

Maryland DNR.
2

Red maple is the most abundant (in terms of number 

of trees) species and second most dominant in terms of 

sawtimber volume, and data suggest that its abundance 

increased through the late 1990s and is now stabilizing.

In the process of harvesting industrial roundwood, 

15.1 million cubic feet of harvest residues were left on 

the ground. Almost a quarter of the harvest residue 

generated is from growing-stock sources (wood material 

that could be used to produce products). 

The area of forest in the small diameter size-class 

has been decreasing, and this could affect wildlife 

populations that rely on these areas.

Multifl ora rose was the most common invasive plant 

encountered on the invasive inventory plots and was 

present on over 30 percent of the plots.

Issues to Watch

Ninety-one percent of the gains in forest land are due to 

agricultural reversion to forest, but as the area of land in 

agriculture continues to diminish, gross gains in forest 

land will likely decrease.

Maryland’s forests are changing in composition, with 

yellow-poplar and red maple increasing in the larger 

diameter classes. These changes will have an impact on 

Maryland’s forest industry and on wildlife populations in 

the future.

The numbers of trees in the smaller diameter classes and 

the area of stands in the small stand size classes have been 

decreasing, while the area of forest in the larger stand 

size and age classes has been increasing. This, coupled 

with an increase in stand age, may suggest loss of early 

successional habitat which is important for some wildlife 

species in decline (northern bobwhite, fi eld sparrow, 

prairie warbler, and American woodcock).

A large amount of Maryland’s private forests is likely to 

change hands in the near future as older land owners 

transfer property to their heirs. It is unclear how these 

future forest owners will manage and care for their lands.

Invasive plant species are a concern in Maryland, and 

there is some evidence of lower frequencies of tree 

seedlings and saplings on plots with higher amounts of 

these invasives.

The emerald ash borer, an exotic beetle, was found in 

Maryland and poses a threat to ash trees in both urban 

and forest environments. Other pests, including gypsy 

moth and hemlock wooly adelgid, are also expected to 

cause damage to Maryland’s forests. The spread of these 

pests needs to be carefully watched.

Forest fragmentation is occurring at a higher rate in the 

previously more intact forests of western Maryland. As 

population pressures and real estate preferences continue 

to change, forest loss associated with urbanization will 

have a greater impact in these counties.
3

Background

View from Weverton Heights, Washington County, MD, 2006. Photo by Jack Perdue, Maryland DNR.
4

 BACKGROUND

Data Sources and Techniques

Forest Inventory

Information on the condition and status of forests in 

Maryland was obtained from the U.S. Forest Service, 

Northern Research Station’s Forest Inventory and 

Analysis (NRS-FIA) program. Previous inventories of 

Maryland’s forest resources were completed in 1950 

(Northeastern Forest Exp. Stn. 1955), 1964 (Ferguson 

1967), 1976 (Powell and Kingsley 1980), 1986 

(Frieswyk and DiGiovanni 1988), and 1999 (Frieswyk 

2001). This report focuses on data collected from 2004 

to 2008, hereafter referred to as the 2008 inventory. 

Sampling Phases

The 2008 Maryland inventory was conducted in three 

phases. In Phase 1 (P1), a geographic information system 

(GIS) was used to obtain initial land use assessments 

on each plot, and to obtain stratifi cation information 

that was used during the estimation process to increase 

the precision of estimates. In Phase 2 (P2), fi eld crews 

visited fi eld plots to measure inventory variables such 

as tree species, diameter, and height. P2 inventory 

plots have been established throughout Maryland, with 

approximately one plot for every 6,000 acres (Fig. 1). In 

Phase 3 (P3), fi eld crews visited a subset of P2 plots to 

obtain measurements for an additional suite of variables 

associated with forest and ecosystem health. The three 

phases of the FIA program as implemented in this 

inventory are discussed in greater detail in “Maryland’s 

Forests 2008: Statistics, Methods, and Quality 

Assurance,” on the DVD in the inside back cover pocket 

of this bulletin.

National Woodland Owner Survey

Information about family forest owners is collected 

annually through the U.S. Forest Service’s National 

Woodland Owner Survey (NWOS). The NWOS 

was designed to increase our understanding of owner 

demographics and motivation (Butler et al. 2005). Data 

presented here are based on survey responses from 88 

randomly selected families and individuals who own 

forest land in Delaware and Maryland. For additional 

information about the NWOS, visit: www.fi a.fs.fed.

us/nwos.

Timber Product Output Inventory

This study was a cooperative effort of the Maryland 

Department of Natural Resources, Forest Service, and 

the Northern Research Station (NRS). A questionnaire, 

designed to determine the size and composition 

of Maryland’s forest products industry, its use of 

roundwood (round sections cut from trees), and its 

generation and disposition of wood residues, was 

fi lled out for all primary wood-using mills within the 

state. Completed questionnaires were sent to NRS for 

editing and processing. As part of data editing and 

processing, all industrial roundwood volumes reported 

on the questionnaires were converted to standard units 

of measure using regional conversion factors. Timber 

removals by source of material and harvest residues 

generated during logging were estimated from standard 

product volumes using factors developed from logging 

utilization studies previously conducted by NRS. 

Frequently Asked Questions

What is a tree?

Trees are perennial woody plants with central stems 

and distinct crowns. In general, the Forest Inventory 

and Analysis (FIA) program of the U.S. Department of 

Agriculture, Forest Service defi nes a tree as any perennial 

woody plant species that can attain a height of 15 feet 

at maturity. A complete list of the tree species (common 

and scientifi c names) measured in this inventory can be 

found in “Maryland’s Forests 2008: Statistics, Methods, 

and Quality Assurance,” on the DVD in the inside back 

cover pocket of this bulletin.

What is a forest?

A forest can come in many forms depending on climate, 

quality of soils, and the available gene pool for the 

dispersion of plant species. Forest stands range from very 
5

 BACKGROUND

tall, heavily dense, and multi-structured to short, sparsely 

populated, and single layered. FIA defi nes forest land as 

land that is at least 10 percent stocked by trees of any 

size or formerly having been stocked and not currently 

developed for nonforest use. The area with trees must be 

at least 1 acre in size and 120 feet wide. Forest land can 

exist in urban and agricultural areas as long as it meets 

the above criteria and doesn’t have maintained or mowed 

understory. Examples of land with tree cover that are not 

considered forest land by FIA defi nitions include: pasture 

land under tree cover that has been grazed, urban parks 

with a maintained understory, and treed residential areas 

where underlying grass is maintained.

What is the difference between timberland, reserved 

forest land, and other forest land?

From an FIA perspective, there are three types of 

forest land: timberland, reserved forest land, and other 

forest land. In Maryland, 95 percent of forest land is 

classifi ed as unreserved and productive timberland, 

nearly 5 percent is reserved and productive forest land, 

and less than 1 percent is unproductive reserved or 

unreserved forest land. Timberland is unreserved forest 

land that meets the minimum productivity requirement 

of 20 cubic feet per year. Reserved forest land is land 

withdrawn from timber utilization through legislation or 

administrative regulation. Other forest land is commonly 

found on low lying sites or high craggy areas with poor 

soils where the forest is incapable of producing 20 cubic 

feet per acre. In earlier inventories, FIA measured trees 

only on timberland plots and did not report volumes 

on all forest land. Since the implementation of the new 

annual inventory in Maryland in 2004, FIA has been 

reporting volume on all forest land. 

The second remeasurement of Maryland is in its third 

fi eld season, and by 2013, FIA will be able to compare 

two sets of growth, mortality, and removal data. Much 

of the trend reporting in this publication is focused on 

timberland, because comparing current data to data from 

older periodic inventories requires timberland estimates.

How do we estimate a tree’s volume?

The volume for a specifi c tree species is usually 

determined by the use of volume equations developed 

specifi cally for a given species. Sample trees are felled 

and measured for length, diameter, and taper. Volume 

equations have been developed at the Northern Research 

Station for each tree species found in the region. Models 

have been developed from regression analysis to predict 

volumes within a species group. We produce individual 

tree volumes based upon species, diameter, and 

merchantable height. Tree volumes are reported in cubicfoot and International 1⁄4-inch rule board-foot scale.

How much does a tree weigh?

Specifi c gravity values for each tree species or group 

of species were developed at the U.S. Forest Service’s 

Forest Products Laboratory and applied to FIA tree 

volume estimates for developing merchantable tree 

biomass (weight of tree bole). To calculate total live-tree 

biomass, we have to add the biomass for stumps (Raile 

1982), limbs and tops (Hahn 1984), and belowground 

stump and coarse roots (Jenkins et al. 2004). We do not 

currently report live biomass for foliage. FIA inventories 

report biomass weights as oven-dry short tons. Oven-dry 

weight of a tree is the green weight minus the moisture 

content. Generally, 1 ton of oven-dry biomass is equal to 

1.9 tons of green biomass.

How do we estimate all the forest carbon pools?

FIA does not directly measure the carbon in standing 

trees; it estimates forest carbon pools by assuming that 

half the dry biomass in standing live/dead trees consists 

of carbon. Additional carbon pools (e.g., soil, understory 

vegetation, belowground biomass) are modeled based on 

stand/site characteristics (e.g., stand age and forest type).

How do we compare data from different inventories?

Comparing new inventories with older datasets is 

common to analyze trends or changes in forest growth, 

mortality, removals, and ownership acreage over time 

(Powell 1985). A pitfall occurs when the comparison 

involves data collected under different schemes or 

processed using different algorithms. Recently, signifi cant 

changes were made to the methods for estimating treelevel volume and biomass (dry weight) for northeastern 
6

 BACKGROUND

states, and the calculation of change components (net 

growth, removals, and mortality) was modifi ed for 

national consistency. These changes will improve the 

ability to report consistent estimates across time and 

space—a primary objective for FIA. Regression models 

were developed for tree height and percent cull to reduce 

random variability across datasets.

Before the Component Ratio Method (CRM) was 

implemented, volume and biomass were estimated using 

separate sets of equations (Heath et al. 2009). With 

the CRM, determining the biomass of individual trees 

and forests has become simply an extension of our FIA 

volume estimates. This allows us to obtain biomass 

estimates for growth, mortality, and removals of trees 

from our forest lands, not only for live trees, but also for 

their belowground coarse roots, standing deadwood, and 

down woody debris.

Another new method, termed the “midpoint method,” 

has introduced some differences in methodology for 

determining growth, mortality, and removals to a 

specifi ed sample of trees (Westfall et al. 2009). The 

new approach involves calculating tree size attributes 

at the midpoint of the inventory cycle (2.5 years for a 

5-year cycle) to obtain a better estimate for ingrowth, 

mortality, and removals. Although the overall net change 

component is equivalent under the previous and new 

evaluations, estimates for individual components will 

be different. For ingrowth, the midpoint method can 

produce a smaller estimate because the volumes are 

calculated at the 5.0-inch threshold instead of using 

the actual diameter at time of measurement. The actual 

diameter could be larger than the 5.0-inch threshold. 

The estimate for accretion is higher because growth on 

ingrowth, mortality, and removal trees are included. As 

such, the removals and mortality estimates will also be 

higher than before (Bechtold and Patterson 2005).

A word of caution on suitability and 

availability

FIA does not attempt to identify which lands are suitable 

or available for timber harvesting especially because 

suitability and availability are subject to changing 

laws and ownership objectives. Simply because land is 

classifi ed as timberland does not mean it is suitable or 

available for timber production. Forest inventory data 

alone are inadequate for determining the area of forest 

land available for timber harvesting because laws and 

regulations, voluntary guidelines, physical constraints, 

economics, proximity to people, and ownership 

objectives may prevent timberland from being available 

for production.
7

 Forest Features

Old loblolly pine, Worcester County, MD, 2006. Photo by Jack Perdue, Maryland DNR.
8

FOREST FEATURES

Figure 1.—Distribution of forest land and approximate locations of FIA forest 

inventory plots in Maryland, 2008.

Physiographic province 

boundary

FIA plot

Nonforest

Forest

Projection: MD State Plane, NAD83. 

Sources: NLCD 2001, TIGER/Dynamap 2000. 

Geographic base data are provided by the National 

Atlas of the USA. FIA data and tools are available 

online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: T. Lister. April 2011.

Allegheny 

Plateau

Ridge and 

Valley

Piedmont

Lower 

Coastal 

Plain

Upper 

Coastal 

Plain

What we found

FIA data show that there has been an approximate 16 

percent loss in forest land area between 1964 and 2008 (Fig. 

2). Data indicate that after the high rate of decrease between 

1964 and 1976, the rate of forest loss has decreased. 

Between 1999 and 2008, the trend of forest loss appears to 

continued, however sampling error is too high to call the 

change signifi cant at the State level. 

An analysis of the changes in percent forest land at the 

county level show that most of the fl uctuation has occurred 

in the suburbs of Baltimore and Washington, D.C. (Fig. 3). 

Timberland 

Forest land 

2.0

2.2

2.4

2.6

2.8

3.0

3.2

1940 1950 1960 1970 1980 1990 2000 2010 2020 

Area (million acres) 

Inventory Year 

Figure 2.—Area of forest land by inventory year, 1950, 1964, 1976, 1986, 1999, 

and 2008. (Error bars show 68 percent confi dence intervals around the mean.)

Forest Area

Background

Maryland is at the confl uence of a unique range of 

physiographic, ecological, economic and demographic 

conditions. Surrounding the Nation’s capital and 

containing a section of the U.S. Interstate 95 corridor, the 

landscape of the eastern portion of the state is characterized 

by a mixture of urban and suburban land uses interspersed 

with agricultural and other human-impacted ecosystems. 

The Chesapeake Bay is the dominant natural feature 

in this portion of the state and its social and economic 

impacts on Maryland are far-reaching. Wetland and 

riparian forests are also a prominent feature in this portion 

of Maryland. The State is host to over 300,000 acres of 

forested wetlands, with the majority of these wetland areas 

around the Chesapeake Bay and to the east. Further west, 

forest begins to dominate in the areas that exhibit more 

topographic relief. These forests, and those that remain in 

the more developed eastern portions of the State, play a 

critical role in the protection of water quality, maintenance 

of biodiversity, generation of wood products, and other 

ecosystem services that contribute to Maryland’s unique 

role in the mid-Atlantic region.

Maryland can be divided into fi ve physiographic provinces 

(Fig. 1). The Lower Coastal Plain province, or Maryland’s 

“Eastern Shore”, includes land east of the Chesapeake 

Bay. The forest land here has a large softwood component 

including the majority of the State’s loblolly pine (Pinus 

taeda) resource. The Upper Coastal Plain province 

includes higher elevation coastal plain land west of the Bay. 

Moving north, the Piedmont province extends west to the 

Catoctin Mountain which forms the boundary between 

the Piedmont and Ridge and Valley province. The rolling 

hills of the Piedmont were once dominated by an oak/

chestnut forest, but now the oak-pine, oak-hickory, and 

mixed forests exist. The Ridge and Valley province has the 

greatest topographic relief with mountain ridges 2,000 feet 

in elevation to river valleys with 200 foot elevations. Here 

again the oak-hickory forest type dominates. The northern 

hardwood forest type is found in the Allegheny Plateau 

province that lies furthest to the west and has the State’s 

highest elevations.
9

FOREST FEATURES

Figure 3.—Forest-land area as a percent of total land area by county 

and inventory year, Maryland, 1964-2008.

These are the least forested areas of the State so small 

changes in forest land area have a greater impact on the 

percent forest in the county. While the 2008 FIA data 

showed no statistically signifi cant net loss of forest land at 

the State level, there were some counties where losses and 

gains appear signifi cant (Fig. 4). Anne Arundel, Allegany, 

and Garrett Counties each lost forest land between 1986 

and 2008 and Somerset County has likely gained forest 

land since 1999. The loss of forest land in Anne Arundel 

County is not surprising due to its suburban location 

between Baltimore and Washington, D.C. Allegany and 

Garrett Counties, the western-most counties in the State, 

maintained the highest percentages of forest area, but both 

lost forest land likely due in part to low density residential 

growth. Gains in Somerset County may be due in part to 

its location on the Eastern Shore and its large wetland area.

1964

1976

1986

1999

2008 

Projection: Maryland State Plane, NAD83. Sources: FIA 2008, TIGER/Dynamap 

2000. Geographic base data are provided by the National Atlas of the USA. 

FIA data and tools are available online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: T. Lister. April 2011.

1 - 30

31 - 40

41 - 50

51 - 60

61 - 80

Percent Forest

1986

1999

2008

0

50

100

150

200

250

300

350

 Allegany Garrett Anne Arundel Somerset 

Forest Land Area (1,000 acres) 

County

Figure 4.—Trends in forest-land area by select counties, Maryland, 1986, 1999, 

and 2008. (Error bars show 68 percent confi dence intervals around the mean.)

What this means

Forest change dynamics in Maryland are due to a 

complex interaction of patterns of population growth, 

land development, reversion of agricultural land to 

forest, conservation policies and the availability of land 

open to development. More counties in Maryland 

exhibited forest loss than showed forest gain. As 

development continues on some of the central and 

eastern shore counties, and as conservation rules are 

enacted, rates of forest area loss may decrease. The 

increase in rates of development in Allegany and Garrett 

Counties over the past 10 years is due to population 
10

FOREST FEATURES

Developed Agriculture Other nonforest 

0 20 40 60 80 

Additions to 

Forest

Depletions from

Forest

Area (1,000 acres) 

growth and real estate preferences, and make these 

counties, which have the largest blocks of contiguous 

forest in the State, vulnerable to habitat fragmentation 

and associated impacts on wildlife, water quality, and 

aesthetic value. As land available for development 

becomes scarcer in the central and eastern counties, it is 

likely that more pressure will be put on these relatively 

intact forests to the west. 

Land Use Change

Background 

Eastern forests offer habitat for forest-dwelling species, 

protect drinking water, serve as buffers for rivers and 

bays against sedimentation and nutrient enrichment, 

and provide economic and other benefi ts for humans 

(Sprague et al. 2006). They are, however, under 

increasing pressure as the demand for housing increases 

(Claggett et al. 2004). Urban development is occurring 

at a rapid pace. Nowak et al. (2005) predicted that the 

area of urban land in the United States will nearly triple 

from 2000 to 2050.

Although the area of forest land in 1999 was not 

statistically different from the forest land estimate in 

2008, we can say with confi dence that Maryland has 

had an estimated net loss of more than 450,000 acres of 

forest land over the last 45 years due in part to population 

growth and urban development pressures. With continued 

development in the Washington-Baltimore corridor and 

suburbs, pressure to expand developed areas remains 

strong. Figure 2 shows this trend of decreasing forest area, 

but the dynamics of forest change are more complicated. 

When we compare forest land estimates between 

inventories, the difference between the two estimates is the 

net change in forest land area. The gross amount of forest 

loss is actually higher, but some of these losses have been 

offset by gains in forest land in other parts of the State. 

In an effort to explore the dynamics of these gross 

changes in land use, a photo-based inventory of land use 

change in Maryland was conducted using FIA defi nitions 

(Lister et al. 2009). The goal of this special study was to 

develop a methodology to obtain more precise estimates 

of the amount of change in forest area than offered by 

the FIA ground plot data.

What we found

Results of the special study show a net loss (taking 

into account both losses and gains in forest land) of 

28,000 acres of forest land in Maryland from 1998 to 

2007, which averages to be more than 3,000 acres per 

year (Fig. 5). The gross forest loss (66,000 acres) was 

primarily due to conversion to development, accounting 

for 91 percent of the total forest loss. Ninety-one 

percent of the forest gains were from conversion of 

agricultural land back to forest. 

Figure 6 shows the distribution of forest loss in Maryland 

between 1998 and 2007 based on results of a photobased inventory. A high proportion of forest loss is in the 

growing suburbs of Baltimore and Washington, D.C., 

an area of the State that has experienced the greatest 

pressure from urban expansion. For example, the highest 

proportion of forest loss plots (3 percent) is found in 

Prince George’s County, which borders Washington, 

D.C. From 2000 through 2007, more than 22,000 new 

housing units were approved for construction, making 

this one of the fastest growing counties in the State.

Figure 5.—Estimates of areas of different land-use change categories, 

Maryland, 1998-2007. (Error bars are for total forest loss and gain and show 68 

percent confi dence intervals around the mean.)
11

FOREST FEATURES

What this means

As the population of Maryland continues to grow, forest 

and agricultural land is likely to be converted to developed 

uses. Historically, the majority of this new development 

occurred on agricultural land, but the results of this 

study indicate that new development is now more likely 

to occur on forest land than agricultural land. With 

continued development and urbanization in Maryland, 

it is likely that there will be more conversion of forest 

land to developed uses. This situation is compounded by 

the fact that currently the gains in forest land are coming 

mostly from agricultural reversion, so not only is there less 

agriculture land available for development, but there is less 

agricultural land available for conversion to forest. The 

end result may be greater net loss of forest land. 

Maryland has many policies and programs to promote 

forest sustainability. For example, the 1991 Forest 

Conservation Act requires that retention of forest be an 

important consideration during the planning process 

for land development projects. In addition, nearly all of 

Maryland is within the Chesapeake Bay watershed, and 

there are several initiatives, including the Chesapeake 

Bay Critical Areas Program, that include forest 

protection guidelines aimed at improving water quality. 

Understanding land-use dynamics helps planners ensure 

that Maryland’s forests and the associated ecosystem 

services they provide are managed sustainably.

Figure 6.—Distribution of land-use plots highlighting forest loss, Maryland, 

1998-2007.

Figure 7.—Forest ownership, Maryland and Delaware, 2006.

57%

19%

3%

17%

4%

Maryland

64%

28%

<1%

<1% 8%

Delaware

Family

Other Private

Federal

State

Local

Photo plot

Photo plot with forest loss

Prince George’s County

Forest Ownership

Background

It is forest land owners who ultimately control the fate 

of the forest and decide if and how it will be managed. 

By understanding the priorities of forest land owners, 

leaders of the forestry and conservation communities 

can better help these owners meet their needs, and in 

so doing, help conserve the region’s forests for future 

generations. FIA conducts the National Woodland 

Owner Survey (NWOS) to better understand who owns 

the forests, why they own forest land, and how they 

use the forest land they own (Butler 2008). Data for 

Maryland and Delaware are combined here because of 

the small sample size in these states.

What we found

Most forests of Maryland and Delaware are privately 

owned – 76 percent in Maryland and 92 percent in 

Delaware (Fig. 7). Of these private acres, 74 percent are 

owned by families, individuals, and other unincorporated 

groups, collectively referred to as family forest owners.

One hundred and fi fty-six thousand family forest 

owners in Maryland and an additional 28,000 family 

forest owners in Delaware control 1.7 million forested 

acres across the two states. Eighty-three percent of these 

Projection: Maryland State Plane, NAD83. Sources: Lister et al. 2008, TIGER/Dynamap 2000. Geographic 

base data are provided by the National Atlas of the USA. FIA data and tools are available online at

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: T. Lister. April 2011.

Baltimore

Washington, D.C.
12

FOREST FEATURES

Owners

Area

0 20 40 60 80 100 

Privacy

Family legacy

Nature protection

Part of home

Aesthetics

Percent

owners have between 1 and 9 acres of forest land (Fig. 8); 

the average holding size is 9 acres. The primary reasons for 

owning forest land are related to aesthetics, the forest land 

being part of a home site, and nature protection (Fig. 9). 

Although timber production is not a major ownership 

objective, 44 percent of the family forest land is owned 

by people who have commercially harvested trees. Thirtythree percent of the land is owned by people who have a 

written management plan, and 41 percent of the land is 

owned by people who have received management advice. 

to pass the land onto heirs or sell it in the near future. 

Family legacy is a major ownership objective and it is also 

a major concern. What can be done to help the forest 

owners and the land? It is clear that timber production is 

not in the forefront of forest owners’ minds, but it is also 

clear that many owners are not averse to harvesting and 

other activities in the woods. It is important to provide 

programs that meet the owners’ needs. 

Urbanization and 

Fragmentation of Forest Land

Background

The expansion of urban lands that accompanies human 

population growth often results in forest fragmentation, 

or the breaking up of large blocks of forest into smaller, 

isolated patches (Wilcox and Murphy 1985). Forest 

fragmentation and habitat loss is recognized as a major 

threat to wildlife populations worldwide (Rosenberg et al. 

1999), particularly for species that require interior forest 

conditions for all or part of their life cycle (Donovan and 

Lamberson 2001), and species that are wide-ranging, 

slow-moving, and/or slow-reproducing (Forman et 

al. 2003). Forest fragmentation can also affect forest 

ecosystem processes through changes in micro-climate 

conditions, and affects the ability of tree species to move 

in response to climate change (Iverson and Prasad 1998).

In addition to the negative effects on forested 

ecosystems, the fragmentation and urbanization of forest 

land may have direct economic and social effects as 

well. For example, smaller patches of forest or patches 

in more populated areas are less likely to be managed 

for forest products (e.g., Kline et al. 2004, Wear et al. 

1999) and are more likely to be “posted” (i.e., not open 

for public use; Butler 2008), potentially affecting local 

forest industry, outdoor recreation opportunities, and 

local culture. Forest land is also a signifi cant factor 

in the protection of surface and groundwater, and 

fragmentation and urbanization of that forest land has 

Area

Owners

0

10

20

30

40

50

60

70

80

90

1-9 10-19 20-49 50-99 100-199 200-499 500-999 1,000+ 

Percent

Size of Family Forest Holdings (acres) 

Figure 8.—Percent of total forest land and number of owners distributed across 

family forest holding size classes, Maryland and Delaware combined, 2006.

What this means

The average parcel size is decreasing and much of this 

forest land will soon be changing hands; 13 percent of 

the family forest acres is owned by someone who plans 

Figure 9.—Primary ownership objectives of family forest owners, Maryland 

and Delaware, 2006.
13

FOREST FEATURES

been observed to affect both water quality and quantity 

(e.g., Hunsaker et al. 1992, Riva-Murray et al. 2010).

The metrics presented here relate to some aspects of 

urbanization or fragmentation which are suspected of, 

or have been documented to have an effect on the forest, 

its management, or on its ability to provide ecosystem 

services and products (Riemann et al. 2008). These 

measures are forest edge versus interior, proximity to 

roads, patch size, local human population density, and 

the extent of houses intermixed with forest.

What we found

In Maryland, 40 percent of the forest land is greater than 

300 feet from an agriculture use or developed edge. This 

ranges from 10 percent in agricultural Carroll County to 

more than 60 percent in the western counties of Garrett 

and Allegany (Table 1). Figures 10 and 11 illustrate 

where and to what extent forest land is affected by roads. 

As both Forman (2000) and Riitters and Wickham 

(2003) reported, this can be quite extensive, even in areas 

that appear to be continuous forest land from the air. 

Allegany 79 36 64 39 97 9

Anne Arundel 47 79 27 20 86 55

Baltimore 34 86 23 24 80 0

Calvert 64 87 35 19 96 58

Caroline 31 43 28 37 84 10

Carroll 23 90 10 30 61 53

Cecil 38 69 31 26 85 34

Charles 64 68 42 30 95 20

Dorchester 35 17 46 49 86 2

Frederick 31 62 41 37 78 18

Garrett 76 28 60 39 95 2

Harford 40 73 27 32 82 41

Howard 28 87 17 25 71 63

Kent 25 35 25 37 80 5

Montgomery 30 68 20 27 76 50

Prince George’s 43 69 30 29 85 40

Queen Anne’s 27 33 26 36 82 12

St. Mary’s 56 84 37 22 94 39

Somerset 42 34 43 42 90 5

Talbot 26 51 24 25 75 10

Washington 39 59 50 33 84 12

Wicomico 42 43 37 38 87 13

Worcester 50 21 48 43 93 3

Maryland 43 55 40 33 87 21

a

 Percent forest estimate based on NLCD 2001. Values are generally higher than estimates from FIA plot data. 

b

 Approximating the forest land potentially affected by underlying development.

c

 Approximating the forest land undisturbed by edge conditions. 

d

 Approximating the forest land outside the effects of roads. 

e

 Approximating the forest land with potentially enough core area for sustainable interior species populations. 

f

 Approximating the forest land not available for commercial forestry. 

Table 1.—Distribution of forest land by urbanization and fragmentation measurements, expressed as a percent of the total forest land area in each county

 Forest land Forest land Forest land

 with house > 295 ft (90 m) Forest land located in a block

 density > 15.5 from an ag Forest land located in with population

% forest land per square or developed > 980 ft patches > 100 densities > 150/mi2

 County in countya mileb edgec

 from a roadd acres in sizee (57.9/km2)f
14

FOREST FEATURES

Much of the forest land in western and parts of southern 

Maryland still occurs primarily as a contiguous forest 

matrix within which urban development, agriculture, 

roads, and other nonforest areas occur (Riiters et al. 

2000). Forested areas containing higher proportions of 

small patches (patches <100 acres) occur in the more 

agricultural and urbanized counties in central Maryland 

(Fig. 12). Carroll and Howard Counties have over 30 

percent of their forest land in patches less than 100 acres 

in size. (Fig. 13). Seven counties in western and southern 

Maryland have less than 10 percent of their forest land in 

patches less than 100 acres.

The wildland-urban interface (WUI) is commonly 

described as the transition zone where human 

development intermingles with undeveloped wildland 

vegetation, and is associated with a variety of humanenvironment confl icts (Radeloff et al. 2005). Radeloff 

et al. (2005) defi ne this area in terms of the density of 

Figure 10.—Distribution of forest land by distance to the nearest road classes 

(includes all roads), Maryland, 2000-2001.

0 5 10 15 20 25 

on road

< 200

200-330

330-650

650-980

980-1,310

1,310-1,640

1,640-1,970

1,970-2,300

2,300-2,620

2,620-2,950

2,950-3,280

>3,280

Percent of Forest 

Distance to Road (feet) 

Figure 11.—Distribution of forest land by distance to the nearest road classes 

(includes all roads), Maryland, 2000-2001.

Projection: Maryland State Plane, NAD83. Sources: National Land 

Cover Dataset 2001, TIGER/Dynamap 2000. Geographic base data 

are provided by the National Atlas of the USA. FIA data and tools are 

available online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: R. Riemann. March 2011.

On road

< 330 ft

330 - 1,640 ft

1,640 - 3,280 ft

> = 3,280 ft

Forest – Distance to Road

Urban development

Barren

Agriculture

Water

Nonforest Land Cover

Figure 12.—Forest cover (percent) in patches less than 100 acres, by 

62.1-square-mile grid cell, Maryland, 2000.

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Allegany

Anne Arundel

Baltimore

Calvert

Caroline

Carrol

Cecil

Charles

Dorchester

Frederick

Garrett

Harford

Howard

Kent

Montgomery

Prince Georges

Queen Annes

St. Marys

Somerset

Talbot

Washington

Wicomico

Worcester

Proportion of Forest Land

County

>50,000

5,000-50,000

500-5,000

100-500

<100

Patch Size (acres)

Figure 13.—Distribution of forest land by patch size and county, Maryland, 

2000.

> 30

20 - 30

10 - 20

< 10

Percentage of 

Forest in Patches 

less than 100 Acres

Projection: Maryland State Plane, NAD83. Sources: National Land 

Cover Dataset 2001, TIGER/Dynamap 2000. Geographic base data 

are provided by the National Atlas of the USA. FIA data and tools 

are available online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: R. Riemann. March 2011.
15

FOREST FEATURES

houses (greater than 15.5 houses per square mile), the 

percentage of vegetation coverage, and the proximity of 

this zone to developed areas. Figure 14 illustrates that 

55 percent of the forest land in Maryland has house 

densities of more than 15.5 houses per square mile. 

Individual counties range from 21 percent of the forested 

area (Worcester County) to nearly 90 percent of the 

forested area (Howard and Carroll Counties) exceeding 

the 15.5 houses per square mile threshold. 

Local human population density near forested areas has 

been shown to affect the viability of commercial forestry 

(Wear et al. 1999). In Maryland, 21 percent of the forest 

land is located in a U.S. census block with population 

densities above 150 people per square mile (Table 1), 

however this varies considerably across the region, from 

2 percent in southeastern Maryland to 63 percent in 

Howard County. 

percent is greater than 980 feet from a road. In contrast, 

Calvert County, also with a relatively large proportion 

of its land area in forest (as seen from the air/satellite 

classifi cation) presents a very different situation. Calvert 

County forest land, which occupies 43 percent of the 

land area, occurs largely mixed with housing densities 

above 15.5 per square mile (87 percent of the forest 

land). Ninety-six percent of the forest land present 

occurs in patches greater than 100 acres in size, but only 

35 percent can be considered interior forest and only 19 

percent is greater than 980 feet from a road. 

What this means

Edge effects vary somewhat with distance from forest 

edge, depending on the type of effect and species of 

vegetation or wildlife, (e.g., Chen et al. 1992, Flaspohler 

et al. 2001, Rosenberg et al. 1999), but 100 to 300 feet 

is frequently used as a general range for the ‘vanishing 

distance’ or the distance into a patch where the edge 

effect disappears and interior forest conditions begin.

The pervasiveness of roads in the landscape is also an 

indicator of forest fragmentation and urbanization (Figs. 

11 and 12). Road effects diminish when distances range 

from about 330 feet for secondary road, 1,000 feet for 

primary roads in forest (assuming 10,000 vehicles per 

day), and 2,650 feet from roads in urban areas (50,000 

vehicles per day) (Forman 2000). Roads result in a 

variety of effects, including hydrologic, chemical (salt, 

lead, nutrients), sediment, noise, as pathways for the 

introduction of invasive species, habitat fragmentation, 

and increases in human access. These effects impact 

forest ecosystem processes, wildlife movement and 

mortality, and human use of the surrounding area. The 

entire State falls within an area of high road densities, 

with more than 60 percent of the land area within 1,250 

feet of the nearest road (Riitters and Wickham 2003). 

Actual ecological impacts of roads will vary by the width 

of the road and its maintained right-of-way, number 

of cars, level of maintenance (salting, etc.), number of 

wildlife-friendly crossings, hydrologic changes, how 

pervious road surfaces are, location with respect to 

important habitat, etc. These variables also suggest some 

Projection: Maryland State Plane, NAD83. Sources: 

National Land Cover Dataset 2001, TIGER/Dynamap 2000, 

U.S. Census 2000. Geographic base data are provided by the 

National Atlas of the USA. FIA data and tools are available 

online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: R. Riemann. March 2011.

0

< 15.5

15.5 - 127

127 - 1,920

> 1,920

Nonforest

Water

Housing Density

houses/mi2

 (2000 Census, 

block-level data)

Figure 14.—Housing density, by class, in forested areas of Maryland, 2000-

2001.

Table 1 summarizes these factors and shows the extent 

to which the current forest land base is being infl uenced 

by one or more of the factors. For example, in rural 

Allegany County, which is 79 percent forested, 36 

percent of that forest land is potentially affected by house 

densities greater than 15.5 per square mile, while 64 

percent of the forest land is far enough from an edge to 

be considered interior forest conditions. Nearly all of the 

forest land is in large patches (>100 acres), but only 39 
16

FOREST FEATURES

of the changes that can be made to moderate the impact 

of roads on the forest (Charry and McCollough 2007, 

Forman 2000, Forman et al. 2003).

Habitat requirements for wildlife vary by species, but for 

reporting purposes it is often helpful to summarize forestpatch data using general guidelines. Many wildlife species 

prefer contiguous forest patches that are at least 100 acres 

(Riemann et al. 2008). This patch area is often used as 

a minimum threshold containing enough interior forest 

to be a source rather than a sink for populations of some 

wildlife species. Without considering the impact of roads 

or houses that don’t substantially break the tree canopy, 

87 percent of Maryland’s forest land is in patches larger 

than 100 acres. Given the pervasiveness of houses and 

roads within the forest landscape in Maryland, and the 

high proportion of forest land that is less than 300 feet 

from an agricultural or forest edge, patch size alone will 

not be a good indicator of wildlife habitat quality. Patch 

size is also limited by geography rather than land use 

pattern and roads in some parts of Maryland. Counties 

with large tidal rivers (e.g., Talbot, Queen Anne’s, Kent) 

have inherently smaller patches. It is also important to 

remember that while 87 percent of forest land is in 100 

acre or larger blocks, these forest blocks can be heavily 

parcelized and owned by many individuals. 

Human population density is generally recognized as 

having a negative effect on the viability and practice of 

commercial forestry (Barlow et al. 1998, Kline et al. 

2004, Munn et al. 2002, Wear et al. 1999). In a Virginia 

study, Wear et al. (1999) identifi ed a threshold of 150 

people per square mile as that population density at 

which the probability of commercial forestry dropped to 

practically zero. In Maryland, 21 percent of forest land 

occurs within census blocks that exceed that threshold of 

150 people per square mile. 

With population pressures and urban growth increasing 

in Maryland, it is important to continue to monitor 

forest fragmentation and urbanization to ensure that 

the forest resources of the State continue to provide 

important ecological benefi ts.
17

Forest Resources

Pine plantation and regeneration, Garrett County, MD, 2009. Photo by Jack Perdue, Maryland DNR.
18

FOREST RESOURCES

Forest Structure and Density

Background

To understand the ecology and economic value of 

a forest, it is common to describe the structure of 

the forest in terms of the area in different stand-size, 

stocking, and age classes. Foresters in our country 

typically use stem diameter at breast height (d.b.h.), or 

diameter at 4.5 feet above the ground, as a measure of 

tree size, and trees per acre as a metric of stem density. 

FIA defi nes stand-size class as the predominant d.b.h. 

class of trees in the stand: small diameter (less than 5.0 

inches d.b.h.), medium diameter (5.0 to 8.9 inches 

d.b.h. for softwoods and 5.0 to 10.9 inches d.b.h. 

for hardwoods), or large diameter (≥ 9.0 inches for 

softwoods and ≥ 11.0 d.b.h. for hardwoods). Similarly, 

stocking, or a measure of site occupancy by trees, is 

another measure of forest structure that, depending upon 

how it is calculated, can integrate size and stem density 

to provide an index of how close to fully utilized the site 

is by trees. Stocking tables and charts have been created 

by foresters to aid in the calculation of this index. 

Five values of the stocking index are reported by FIA: 

nonstocked (0 to 9 percent), poor (10 to 34 percent), 

moderate (35 to 59 percent), full (60 to 100 percent) 

and overstocked (>100 percent). As stands become 

overstocked, trees become crowded, productivity 

decreases, more trees die, and stem quality often 

decreases. Poorly stocked stands are not fully occupied 

by trees, are less valuable, and might benefi t from some 

silvicultural treatment that improves site occupancy 

and value. FIA classifi es economically valuable trees as 

growing-stock trees and thus knowledge of stocking 

values for growing-stock trees, as well as the ratio of 

growing stock to all live stocking, can help resource 

specialists manage forests for economic value. 

What we found

Large-diameter stands dominate the forest land area (76 

percent) in Maryland. The area of small- and mediumsized forest stands in Maryland has decreased by 32 

1999

2008

0

500

1,000

1,500

2,000

2,500

Small Medium Large 

Area of Forest Land (1,000 acres) 

Stand-size Class 

Figure 15.—Area of forest land by stand-size class, Maryland, 1999 and 2008. 

(Error bars show 68 percent confi dence intervals around the mean.)

1999

2008

0

200

400

600

800

1,000

1,200

1,400

1,600

Nonstocked

Poorly

Medium

Fully

Overstocked

Area of Forest Land (1,000 acres) 

Stocking Class 

Figure 16.—Area of forest land by stocking class of all live trees, Maryland, 

1999 and 2008. (Error bars show 68 percent confi dence intervals around the 

mean.)

percent from 1999 to 2008, while the area of largediameter stands increased by 11 percent (Fig. 15).

Data indicate that since 1999, Maryland’s forests have 

become less fully stocked. An estimated 1.1 million acres 

(46 percent) of Maryland’s forests are fully stocked with 

live trees, which is a nearly 300,000 acre decrease from 

the area of fully stocked forest in 1999 (Fig. 16). The 

area of forest in the medium stocking class, increased 

(42 percent), and the acreage of nonstocked and poorly 

stocked stands showed little change since 1999. The 

acreage in the poorly and nonstocked class is relatively 

small (253,000 acres). A similar pattern is observed when 

just considering growing-stock trees (Fig. 17).
19

FOREST RESOURCES

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Large

diameter

Medium

diameter

Small

diameter

Proportion of Forest Land 

Stand-size Class 

Poorly stocked 

Medium stocked 

Fully stocked 

Overstocked

According to the 2008 data, 57 percent of forest 

stands are at least 61 years old (Fig. 18). The ageclass distribution is shifting toward older stands, with 

signifi cant decreases in the area of forests less than 60 

years old and signifi cant increases in the area of forest 

greater than 60 years old (Fig. 18).

old) are much more likely to be overstocked than young 

large diameter stands. The proportion medium-stocked 

forest tends to increase as both age and diameter class 

increases. Finally, relatively equal proportions of fully 

stocked forests occur across all diameter and age classes. 

What this means

The forests of Maryland are maturing in terms of age 

and diameter-class distributions. At the same time, there 

has been a slight shift from forest land dominated by 

full and overstocked stands to forest land dominated 

1999

2008

0

200

400

600

800

1,000

1,200

1,400

1,600

Nonstocked

Poor

Medium

Full

Overstocked

Area of Forest Land (1,000 acres) 

Stocking Class 

Figure 17.—Area of forest land by stocking class of growing-stock trees, 

Maryland, 1999, and 2008. (Error bars show 68 percent confi dence intervals 

around the mean.)

Figure 18.—Distribution of forest land by age class, Maryland 1999 and 2008. 

(Error bars show 68 percent confi dence intervals around the mean.)

1999

2008

0

100

200

300

400

500

600

700

800

900

0-20 21-40 41-60 61-80 81-100 100+ 

Area of Foreset Land (1,000 acres) 

Age Class 

Eighty-eight percent of the nonstocked stands are 

young (less than 20 years old) and the distribution of 

overstocked stands is also skewed toward these younger 

age classes (Fig. 19). Similar patterns can be observed 

when examining the relationship between the relative 

area of each stocking class by size class (Fig. 20): younger, 

small-diameter stands (those generally less than 20 years 

Nonstocked

Poorly stocked 

Medium stocked 

Fully stocked 

Overstocked

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0-20 21-40 41-60 61-80 81-100 100+ 

Proportion of Forest Land 

Age Class 

Figure 19.—Distribution of forest land (proportion) by stocking class and age 

class, Maryland, 2008.

Figure 20.— Distribution of forest land (proportion) in stocking classes by 

diameter class, Maryland, 2008.
20

FOREST RESOURCES

-10

0

10

20

30

40

50

60

2 4 6 8 10 12 14 16 18 20 22 24+ 

Percent Change 

Diameter Class (inches) 

by poorly and medium-stocked stands, refl ecting the 

loss of area of young, small-diameter stands that tend 

to be dense and often overstocked. As patterns of land 

use have changed in Maryland, there are fewer stand 

replacing activities occurring – relatively more forest 

is lost to development than is subject to stand removal 

and subsequent forest regeneration. These changes in 

size- and age-class structure are thus expected, and will 

continue unless forest management practices or natural 

processes, such as fi re, or signifi cant tree mortality alter 

this pattern.

Numbers of Trees

Background

Summaries of the number of trees by diameter class and 

species are useful to forest managers. Not only do these 

summaries provide information on forest sustainability, 

but they also inform ecologists interested in topics 

such as species diversity indices. Changes in diameter 

distributions lead to changes in forest composition 

as cohorts of similar sized trees move through the 

successional process. If, for example, there are not an 

adequate number of small-diameter trees of a certain 

species, it is less likely that the species will play a 

prominent role in the future forest. 

What we found

There are more than 1.4 billion live trees 1-inch or larger 

(d.b.h.) on Maryland’s timberland, or an average of 

606 trees per acre. The overall number of trees has not 

changed signifi cantly since the last inventory (1999). 

However there are differences when comparing changes 

in numbers of trees by diameter class (Figs. 21 and 22). 

FIA results suggest that relative numbers of trees in the 

larger size classes increased between 1999 and 2008 and 

trees less than 9 inches d.b.h. decreased in number (Fig. 

22). This trend of decreasing numbers of small-sizeclass trees and increasing numbers of trees greater than 

11 inches d.b.h. has been observed in each successive 

inventory since 1976. The data indicate that there are 

more trees in 2008 in the 12 inch and above size class 

than there have been at any point since 1976 (Fig. 21). 

There are 385 million (162 trees per acre) live trees 5 

inches d.b.h. or greater and 1.05 billion saplings (443 

trees per acre) on timberland in Maryland. Red maple 

(Acer rubrum) is the most common tree species in 

Maryland, accounting for 19 percent of all saplings and 

14 percent of the live trees 5 inches and larger in d.b.h. 

(Fig. 23). Sweetgum (Liquidambar styracifl ua) is the 

second most common tree species, accounting for 12 

percent of the saplings and 9 percent of the live trees 5 

Figure 21.—Number of growing-stock trees on timberland by diameter 

class, Maryland, 1976, 1986, 1999, and 2008.

Figure 22.—Percent change in the numbers of growing-stock trees by 

diameter class, Maryland, 1999-2008.

1976

1986

1999

2008

0

20

40

60

80

100

120

140

160

6 8 10 12 14 16 18 20 21-29 30+ 

Number of Trees (millions) 

Diameter Class (inches) 
21

FOREST RESOURCES

inches d.b.h. or greater. American holly (Ilex opaca) is 

the third most common tree in Maryland due mainly to 

the abundance of sapling-sized trees of this species; 92 

percent of the American holly trees in Maryland are less 

than 5 inches in diameter. Loblolly pine is fourth with 5 

percent of the saplings and 15 percent of the live trees 5 

inches and larger. Although the sampling errors are high 

when looking at tree data by species, there was a notable 

increase in American beech (Fagus grandifolia) trees in 

Maryland since 1999. Beech frequency increased by 56 

percent overall, with a 65 percent increase in the number 

of sapling-size beech trees and a 29 percent increase in 

the numbers of trees greater than 5 inches d.b.h. Red 

maple, which, according to past inventories had been 

increasing in frequency in Maryland and in other areas 

of the country, remained stable in terms of numbers of 

larger trees and has increased only slightly in numbers of 

saplings from 1999 to 2008.

What this means

A shift in the numbers of trees away from saplings 

toward trees within the larger diameter classes can be a 

result of several factors, including the implementation of 

conservation practices aimed at protecting forests, changes 

in harvesting rates, natural forest maturation in the 

absence of disturbance, predation of young trees by deer 

and the conversion of early successional forests to nonforest 

land uses. Of these factors, changes in development 

patterns and conservation practices may have played the 

strongest roles in the maintenance of larger diameter 

stands. As open space has become scarcer in the central 

and Eastern Shore counties and societal values have moved 

toward forest conservation, particularly in the Chesapeake 

Bay region, more restrictive land-use regulations have 

affected land management and development preferences. 

In the absence of either natural or anthropogenic stand 

replacing events, this trend of increase in the relative 

numbers of larger diameter trees will continue.

Species Composition and 

Distribution

Background

Forest species composition is the result of a number of 

processes: seed dispersal patterns, the distribution of 

microsites suitable for seed germination, soil nutrient 

and moisture status, competition between other plant 

species for light and resources, predation, and macro scale 

environmental patterns such as climate and topography. 

Ecologists and forest managers are very interested in species 

composition because of the effects it has on wildlife, forest 

productivity, timber values, and forest health characteristics. 

The relative volume of oaks (Quercus sp.) has been in decline 

in many areas of the Northeast, and this is of particular 

concern because of their economic and wildlife values.

What we found

Red maple is by far the most abundant species in Maryland 

in terms of number of trees, and occurs in roughly the 

same proportion across all diameter classes (Fig. 24). 

However, oak and yellow-poplar (Liriodendron tulipifera) 

represent a much higher proportion of the total number 

of larger diameter trees. Loblolly pine has relatively more 

medium-sized trees than small or large diameter trees.

1999

2008

0 100 200 300 

Red maple

Sweetgum

American holly

Loblolly pine

Blackgum

American beech

Yellow-poplar

Black cherry

Pawpaw

Sweet birch

Number of Trees (millions) 

Species

Figure 23.—Number live trees on timberland by species, Maryland, 1999 and 

2008. (Error bars show 68 percent confi dence intervals around the mean.)
22

FOREST RESOURCES

0 

5 

10 

15 

20 

25 

30 

35 

40 

1970 1980 1990 2000 2010 

Percent of Total Growing-stock Volume 

Inventory Year 

Oaks 

Yellow-poplar 

Red maple 

Loblolly pine 

Sweetgum 

Hickory 

Beech 

The relative frequency of several important tree species has 

changed over the years (Fig. 25). The relative frequency 

of sweetgum and red maple have increased in terms of 

proportion of growing-stock volume since 1976, however 

the 2008 estimates show relatively little change from 

1999. Data suggest that oaks in particular have shown a 

steady decline in terms of proportion of growing-stock 

volume since 1976, while yellow-poplar has increased 

dramatically. In terms of number of trees, the abundance 

of oak trees declined signifi cantly from 1986 to 1999, 

however the current inventory shows no change in the 

overall abundance or volume of oaks since 1999. Figure 

26 shows the diameter distribution for number of oak 

trees. Although the total number of small-diameter oak 

saplings has increased, the increase only occurred in the 

small-sapling-size class (1 to 3 inch d.b.h.); the larger 

saplings and small-diameter tree classes (3 to 12 inch 

d.b.h.) all showed decreases in number of trees since 1999 

and larger decreases since 1986 (Fig. 26).

Distribution maps of the top fi ve species (in terms of 

volume) are shown in Figure 27. Red maple is clearly 

a generalist, with relatively more basal area distributed 

throughout the state. In the Coastal Plain physiographic 

region, loblolly pine is a prominent species, and 

associated species like sweetgum are also relatively 

dominant as well. Yellow-poplar does not have a high 

relative dominance in the Coastal Plain, but becomes 

more prevalent in the Piedmont and further west. White 

oak, though not as widespread as red maple, shows itself 

to be a generalist as well, with a relatively high likelihood 

of occurrence in the Ridge and Valley region and a lower 

likelihood of occurrence in the eastern Coastal Plain 

where the soils are sandy.

Figure 24.—Relative species abundance by diameter class, Maryland, 2008.

Figure 25.—Change in relative percent of growing-stock volume for select 

species and species groups, Maryland, 1976, 1986, 1999, and 2008.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

2 4 6 8 10 12 14 16 18 20 22+ 

Relative Abundance (proportion) 

Diameter Class (inches d.b.h.) 

Others

Loblolly pine 

Sweet gum 

Yellow-poplar 

American beech Red maple 

Black cherry Hickory

Black gum Oaks

American holly 

Figure 26.—Number of oak trees on timberland by diameter class and 

inventory year, Maryland, 1986, 1999, and 2008.

1986

1999

2008

0

10

20

30

40

50

60

70

2 4 6 8 10 12 14 16 18 20 22 24+ 

Number of Oak Trees (millions) 

Diameter Class (inches) 
23

FOREST RESOURCES

Projection: Maryland State plane, NAD83. 

Sources: FIA 2008, TIGER/Dynamap 2000. Geographic 

base data are provided by the National Atlas of the 

USA. FIA data and tools are available online at 

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: D. Griffi th. March 2011.

Nonforest/no estimate

< 10

10 - 19.9

> 20

Percent of Live Basal Area

White Oak

Red Maple Yellow-poplar

Loblolly Pine Sweetgum

What this means

Studying trends in the relative frequency or volume of 

tree species by diameter class can give some clues about 

the composition of the future forest. In the case of 

Maryland, it appears that as large oaks are claimed by 

mortality or cutting, the gaps created will be susceptible 

to colonization by red maple, blackgum (Nyssa sylvatica), 

or sweetgum, all of which have been increasing in relative 

frequency for many years and occupy a relatively larger 

proportion of the total number of trees in the smallerdiameter classes. Decreases in the oak proportion over 

time might be attributed to a combination of inadequate 

regeneration (due to predation by deer, competition in 

the understory by shade tolerant, generalist species, and 

lack of fi re) and selective cutting of larger, more valuable 

trees. The future forest might be more heavily dominated 

by generalist species, particularly red maple, and the oaks 

may continue to decrease in relative dominance.

Figure 27.—Species distribution of common trees in terms of basal area (ft2/acre), Maryland, 2008
24

FOREST RESOURCES

Biomass of Live Trees and 

Forest Carbon

Background

Total aboveground tree biomass is calculated as the 

sum of the weights of different components of the tree: 

the bole, stump, top, and limbs. Biomass is a measure 

of dominance similar to tree volume and is sometimes 

used as an index of ecological importance. In particular, 

biomass is of interest to scientists and policymakers who 

wish to characterize the local, regional, and global carbon 

cycle and its effect on climate change. Live tree biomass 

and carbon are directly related to one another because 

the carbon content of wood and bark is approximately 

50 percent of dry biomass. The live tree carbon estimates 

are derived by dividing the dry biomass weight in half. 

Collectively, forest ecosystems represent the largest 

terrestrial carbon sink on earth. The accumulation of 

carbon in forests through sequestration helps to mitigate 

emissions of carbon dioxide to the atmosphere from 

sources such as forest fi res and burning of fossil fuels. 

What we found

Aboveground tree carbon is distributed mainly in the 

Upper Coastal Plain, Alleghany Plateau, and Ridge 

and Valley provinces (Fig. 28). Forests with the largest 

amount of tree biomass and carbon are found west of 

the Chesapeake Bay in the central portion of the Upper 

Coastal Plain.

Maryland’s forests currently contain almost 204 million 

tons of carbon. Live trees and saplings represent the 

largest forest ecosystem carbon stock in the State at 

nearly 105 million tons, followed by soil organic matter 

(SOM) at more than 70 million tons (Fig. 29). Within 

the live tree and sapling pool, merchantable boles 

contain the bulk of the carbon (about 65 million tons, or 

almost three-quarters of the total aboveground live tree 

carbon in the State) followed by roots (17 million tons) 

and tops and limbs (15 million tons).

The total live tree biomass in Maryland is over 176 

million dry tons. Most of this biomass is from hardwood 

trees, and most is found in trees between 10 and 22 

inches d.b.h. (Fig. 30). Saplings and nongrowing-stock 

boles make up a relatively small amount of the live tree 

biomass in the state (Fig. 31). 

Most of Maryland’s forest carbon stocks are found in 

stands 41 to 100 years old (Fig. 32). Early in stand 

development, most of forest ecosystem carbon is in the 

SOM and belowground tree components. As forest 

stands mature, the ratio of above- to belowground 

Nonforest

Less than 10

10 - 19.9

20 - 29.9

Greater than 30

Aboveground 

Tree Carbon (tons/ac)

Projection: Maryland State Plane, NAD83. 

Sources: FIA 2008, TIGER/Dynamap 2000. Geographic base 

data are provided by the National Atlas of the USA. FIA data 

and tools are available online at http://www.fi a.fs.fed.us/tools-data/

Cartography: D. Griffi th. March 2011.

Figure 28.—Distribution of aboveground live tree carbon in Maryland, 2008.

1%

2%

6% 4%

35%

Live trees and saplings 

Soil organic matter

Total understory 

Standing dead

Down dead

Litter

Saplings

Tops and limbs

Merchantable boles

Stumps

Live tree roots 

2%

9%

32%

7%

2%

Total Forest Carbon Stocks 

204 million short tons

Figure 29.—Estimated total carbon stocks on forest land by component, 

Maryland, 2008.
25

FOREST RESOURCES

Forest C Stocks per Acre (short tons)

Forest-type Group

(acres)

C in litter 

C in soil 

C in live biomass 

C in dead wood 

0 20 40 60 80 100 120 

Oak/gum/cypress

18,225

Aspen/birch

346,574

Exotic softwoods

11,528

Elm/ash/cottonwood

5,857

Maple/beech/birch

183,667

Oak/pine

1,555,477

White/red/jack pine

137,594

Oak/hickory

67,822

Loblolly/shortleaf pine

108,744

Other hardwoods

1,880

Exotic hardwoods

25,165

Nonstocked

2,730

Other exotic softwoods

 27,348

Aboveground

Belowground

Acres

0

200,000

400,000

600,000

800,000

0

10

20

30

40

50

60

70

0-20 21-40 41-60 61-80 81-100 100+ 

Acres

Forest C Stocks (million short tons) 

Age Class (yrs) 

Growing-stock bole 

(≥5 inches d.b.h.) 

Growing-stock tops/limbs/stumps 

(≥5 inches d.b.h.) 

Saplings (<5 inches d.b.h.) 

Nongrowing-stock bole 

(≥5 inches d.b.h) 

Nongrowing-stock tops/

limbs/stumps (≥5 inches d.b.h.) 

3% 1% 

5% 

20% 

71% 

carbon shifts and by age 41 to 60 years, the aboveground 

components represent the majority of ecosystem carbon. 

This trend continues well into stand development as carbon 

accumulates in live and dead aboveground components. 

A look at carbon by forest-type group on a per-unit-area 

basis found that 8 of the 13 groups have between 80 to101 

tons of carbon per acre (Fig. 33). Despite the similarity in 

per-acre estimates, the distribution of forest carbon stocks 

by forest-type group is quite variable. In the elm/ash/

cottonwood group, for example, 53 percent (about 50 tons) 

of the forest carbon is in the SOM, whereas in the oak/ 

hickory group, only 29 percent is in the SOM. Figure 30.—Distribution of live-tree biomass (trees at least 1 inch d.b.h.) on 

timberland by species group and 2-inch diameter class, Maryland, 2008.

Figure 31.—Percentage of live-tree biomass (trees 1 inch d.b.h. and larger) on 

forest land by aboveground component, Maryland, 2008.

Figure 32.—Above- and belowground carbon stocks on forest land by stand 

age class and area by stand age, Maryland, 2008.

Softwoods

Hardwoods

0

2

4

6

8

10

12

14

16

18

20

4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42+ 

Biomass (million dry tons) 

Diameter Class (inches) 

Figure 33.—Carbon stocks on forest land by forest-type group and carbon 

pool per acre, Maryland, 2008.

What this means

Since the area of forest land changed little since the 

last inventory, trees with larger diameters and relatively 

more carbon are increasing in frequency, and total forest 

volume is increasing, we can conclude that forests in 

Maryland are accumulating carbon. The majority of 

forest carbon in the State is found in medium-aged 

stands dominated by relatively long-lived species. This 
26

FOREST RESOURCES

suggests that Maryland’s forest carbon will continue 

to increase as stands mature and accumulate carbon in 

above- and belowground components. Biomass and 

carbon accumulation has implications for acquiring 

carbon credits through the framework established by the 

Regional Greenhouse Gas Initiative (of which Maryland 

is a member), climate change research, and biofuel and 

other wood product development potential. 

Volume of Growing-stock 

Trees

Background

Growing-stock volume is the amount of sound wood 

in live, commercially valuable trees. It is a measure of 

wood that could be put to commercial use and thus 

gives an indication of potential value. Forest owners 

and managers need to understand the potential value of 

forests when evaluating management plans and inventory 

results with respect to economic implications.

What we found

Ninety-six percent of the volume in Maryland is in 

growing-stock trees, which are trees with good form and 

the species are commercially important. The remaining 

volume is in cull trees, classifi ed as either rough (3 

percent) or rotten (1 percent) (Fig. 34). The volume of 

growing-stock trees in Maryland is 5.9 billion cubic feet, 

or 2,153 cubic feet per acre. Volume has increased by16 

percent since 1999. This is an estimated annual increase of 

1.8 percent per year which is similar to the rate of increase 

experienced from 1976 to 1986 (1.9 percent per year), 

but more than the rate of increase that was experienced 

between 1986 and 1999 (1 percent per year). Hardwood 

species dominate, accounting for 85 percent of the total 

growing-stock volume in Maryland and hardwood species 

are also responsible for the overall growing stock increases 

as softwood volume has remained relatively constant for 

the past 30 years (Fig. 35). 

Since 1976, there has been a shift in growing-stock 

volume toward larger trees (Fig. 36). Substantial 

increases have occurred in the 14-inch diameter class 

through the 28-inch diameter class. From 1986 to 1999, 

the growing-stock volume in this diameter class range 

increased by 25 percent and from 1999 to 2008, there 

was a 33 percent increase. These changes are consistent 

with changes in the number of trees by diameter class 

discussed in a previous section. 

Yellow-poplar is the leading species in growing-stock 

volume, with 1.1 billion cubic feet, or 19 percent of the 

total. Red maple accounts for 13 percent of the total 

volume, or 656 million cubic feet, and loblolly pine 

ranks third with 10 percent of the total (580 million 

cubic feet) (Fig. 37). The growing-stock 

Growing-stock trees 5.9 billion ft3

Tree Grade

Rough trees 184 million ft3

Rotten trees 44 million ft3

96% 3% 1%

Hardwoods

Softwoods

0

6

5

4

3

2

1

1970 1975 1980 1985 1990 1995 2000 2005 2010

Growing-stock Volume (billion ft3

)

Inventory Year

Figure 34.—Volume by components, Maryland, 2008.

Figure 35.—Growing-stock volume on timberland by species group and 

inventory year, Maryland, 1976, 1986, 1999, 2008. (Error bars show 68 percent 

confi dence intervals around the mean.)
27

FOREST RESOURCES

volume of all oak species combined is 1.6 billion cubic 

feet, representing about 26 percent of the total. Yellowpoplar showed a substantial increase of 50 percent since 

1999. Looking at net growth by diameter class, yellowpoplar exhibited more growth than all oaks combined in 

trees greater than 20 inches d.b.h. (Fig. 38).

1999

2008

Species

0 500 1,000 1,500 

Yellow-poplar 

Red maple 

Loblolly pine 

White oak 

Sweetgum

Chestnut oak 

Black oak 

Black cherry 

Northern red oak 

Scarlet oak 

American beech 

Blackgum

Growing-stock Volume (million ft3)

Yellow-poplar 

All oak spp. 

-2

-1

0

1

2

3

4

5

6

7

2 6 10 14 18 22 26 30 34 38 41.0+ 

Net Growth (million ft3/year)

Figure 36.—Growing-stock volume on timberland by diameter class and Diameter Class (inches d.b.h.) 

inventory year, Maryland, 1986, 1999, 2008. (Error bars show 68 percent 

confi dence intervals around the mean.)

1986

1999

2008

0

100

200

300

400

500

600

700

800

900

6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42+ 

Growing-stock Volume (million ft3)

Diameter Class (inches d.b.h.) 

Figure 37.—Growing-stock volume on timberland by species, Maryland, 1999 

and 2008. (Error bars show 68 percent confi dence intervals around the mean.)

Figure 38.—Net growth of yellow-poplar and oak species growing stock on 

timberland by diameter class, Maryland, 2008.

What this means

The total volume of hardwood trees in Maryland’s forests 

has increased steadily since 1976, while that of softwoods 

has remained relatively steady. Total softwood volume, 

which consists mostly of loblolly pine, is remaining 

constant due to some combination of timber management 

strategies, forest loss to development, and volume increase. 

The stability of the amount of softwood volume through 

time could be perturbed, however, with unsustainable 

forest management or increasing forest loss. 

Examining the shift in volume by diameter class from 

one time period to another reveals that Maryland’s 

forests are maturing. In general, relatively more volume 

is accumulating in larger rather than smaller diameter 

classes. Sawtimber-size trees (those greater than 11 

inches in d.b.h.) are usually found in the canopy, and 

contain most of the volume. Yellow-poplar is increasing 

in importance (percentage of total basal area) mostly 

in the canopy stratum due to its competitive advantage 
28

FOREST RESOURCES

and its frequency in the population within the largediameter (and volume) -size classes. Oaks are increasing 

in volume but are becoming relatively less important 

than yellow-poplar in terms of volume. These changes 

in species importance will lead to changes in the value 

of Maryland’s forests for wildlife and for the production 

of timber products. Management of species composition 

can have an impact on the value of the future forest 

as Maryland’s forests continue to mature and the next 

generation of trees develops in the understory.

Sawtimber Quality and 

Volume

Background

Sawtimber trees are live trees of commercial species that 

contain either one 12-foot or two noncontiguous 8-foot 

logs that are free of defect. Hardwoods must be at least 

11 inches d.b.h. and softwoods must be 9 inches d.b.h. 

to qualify as sawtimber. Sawtimber volume is defi ned as 

the net volume of the saw log portion of live sawtimber, 

measured in board feet, from a 1-foot stump to minimum 

top diameter (9 inches for hardwoods and 7 inches for 

softwoods). Estimates of sawtimber volume, expressed 

as board feet (International 1⁄4-inch rule), are used to 

determine the monetary value of wood volume and to 

identify the quantity of merchantable wood availability.

The amount and quality of merchantable sawtimber in 

the State has a far-reaching impact on the economics 

of the State’s forest industry. To understand sawtimber 

quality in Maryland, FIA generates estimates of total 

volume by tree grade, which is an index of wood quality. 

Tree grade depends on the species, the amounts of knotfree bole and cull, tree form, and tree diameter, and is 

typically used to help assess the potential value of the 

sawtimber resource. Tree grades 1 and 2 yield the highest 

quality wood for lumber. High quality timber is typically 

used for making cabinets, furniture, fl ooring, or other 

millwork, while lower quality timber is used for pallets, 

pulpwood, or fuelwood.

What we found

There are 22.6 billion board feet of sawtimber in 

Maryland which amounts to 9,545 board feet per 

acre. Sawtimber volume has increased by nearly 40 

percent since 1999, the same percentage increase as was 

estimated between 1986 and 1999. Hardwood species 

comprise the majority of the sawtimber volume and 

also account for its increase (Fig. 39). Figure 40 shows 

the breakdown of sawtimber volume by tree grade. 

In Maryland, 57 percent of the sawtimber volume is 

in grades 1 or 2. The board foot volume in grades 2 

and 3 has changed very little since 1999, however, the 

highest quality, grade 1 increased. Yellow-poplar is the 

top species with 5.8 billion board feet, or 26 percent of 

the total sawtimber volume, up from 20 percent of total 

Hardwoods

Softwoods

0

5

10

15

20

25

1970 1975 1980 1985 1990 1995 2000 2005 2010 

Sawtimber Volume (billion bd ft) 

Inventory Year 

Grade 1 

Grade 2 

Grade 3 

Not graded 

15% 14% 

30% 20% 

24% 16% 

31% 

50% 

0 

5 

10 

15 

20 

25 

1999 2008 

Sawtimber Volume (billion bd ft) 

Inventory Year 

Figure 39.—Sawtimber volume on timberland by species group and 

inventory year, Maryland, 1976, 1986, 1999, 2008. (Error bars show 68 percent 

confi dence intervals around the mean.)

Figure 40.—Sawtimber volume on timberland by tree grade, Maryland, 

1999 and 2008.
29

FOREST RESOURCES

sawtimber volume in 1999 (Fig. 41). Figure 42 shows 

the proportion of tree grades for select tree species. In 

Maryland, loblolly pine has the largest volume in tree 

grades 1 and 2, followed by yellow-poplar and northern 

red oak (Quercus rubra) (Fig. 42). These species, as well 

as most other oak species and sweetgum, have at least 

half of their sawtimber volume in tree grade 2 or better. 

Of the other major species in the State, beech had the 

lowest portion of volume in grades 1 and 2, followed by 

Virginia pine (Pinus virginiana), black cherry (Prunus 

serotina), and red maple. Many beech trees in Maryland 

are degraded because of large amounts of rotten wood. 

Red maple is graded lower than other species because it 

typically has more defects and smaller diameters. Beech 

and red maple also do not self prune as well as other 

species such as yellow-poplar.

What this means

Since tree diameter is one of the factors infl uencing 

tree grade, the maturing of Maryland’s forests (the 

accumulation of relatively more volume in the higher 

diameter classes) has led to a simultaneous increase in 

tree grades and thus potential value. The yellow-poplar 

resource is clearly increasing in tree grade at a much 

higher rate than other species due to its rapid growth rate 

and straight form, especially for trees that have reached 

codominant status. Softwood sawtimber volume, most 

of which is loblolly pine, has stayed relatively fl at since 

1976. This is due in part to an equilibrium of several 

factors: forest loss in areas where loblolly pine dominates, 

increase in volume in larger diameter classes, and timber 

management practices that promote sustainable harvests. 

As species composition in sawtimber-size classes and 

higher quality tree grades changes, so, too, will the 

economics of the forest industry in Maryland. Ideally, 

management practices and cutting preferences will adapt 

to promote the maintenance of a sustainable supply of 

high quality sawtimber.

Growth, Removals, and 

Mortality

Background

The concept of forest sustainability has many parts: the 

maintenance of forest cover, ecological and economic 

value, and forest productivity. One way to understand 

the status of forest sustainability is to look at the 

Figure 42.—Proportion of sawtimber volume on timberland by species and 

tree grade, Maryland, 2008.

1999

2008

Species

0 2 4 6 8 

Yellow-poplar 

Red maple 

Loblolly pine 

White oak 

Sweetgum

Northern red oak 

Chestnut oak 

Black oak 

Scarlet oak 

American beech 

Black cherry 

Virginia pine 

Sawtimber Volume (billion bd ft) 

Grade 1 Grade 2 Grade 3 Not graded 

0 0.2 0.4 0.6 0.8 1.0

Yellow-poplar 

Red maple 

Loblolly pine 

White oak 

Sweetgum

Northern red oak 

Chestnut oak 

Black oak 

Scarlet oak 

American beech 

Black cherry 

Virginia pine 

Proportion of Sawtimber Volume 

Species

Figure 41.—Volume of sawtimber on timberland for major species, 

Maryland 1999 and 2008. (Error bars show 68 percent confi dence intervals 

around the mean.)
30

FOREST RESOURCES

components of volume change: growth, removals, and 

mortality. Growth is the increase in volume over a 

specifi c time period. Removals harvested trees, trees on 

timberland that has been reclassifi ed to reserved forest 

land (e.g., by the establishment of a protected area), or 

trees on forest land lost to a nonforest land use. Mortality 

is the loss of live volume that occurs when a tree dies. 

Growth, removals, and mortality data are collected on 

each remeasured tree in each inventory cycle, so trends in 

these metrics can be calculated over time. 

What we found

In Maryland, tree growth has exceeded losses from 

mortality and removals. Figure 43 shows the components 

of annual volume change. The average annual net growth 

of growing stock on timberland is 138.9 million cubic feet, 

or 75 cubic feet per acre per year. Losses due to mortality 

average 44 million cubic feet annually, and removals 

averaged 67 million cubic feet annually. These components 

result in an annual net gain of 110 million cubic feet. 

Removals include tree volume that was harvested but the 

land will likely remain in forest (64 percent), tree volume 

lost due to a change to nonforest use (27 percent), and 

tree volume that remains in forest but is now reserved or 

protected from harvest removal (9 percent).

Figure 44 shows how growth (as a percentage of total 

growing-stock volume) increased from 2.1 to 3.0 percent 

between 1999 and 2008, and while removals and 

mortality changed little. The overall growth-to-removals 

-100

-50

0

50

100

150

200

250

Gross

growth

Mortality Net 

growth

Removals Net 

change

Volume (million ft3)

Components of Change 

Figure 43.—Components of average annual change in growing-stock volume, 

Maryland, 1999-2008.

Growth

Removals

Mortality

Volume (million ft3) 

2.1 1.6 0.73 3.0 1.1 0.74

0

50

100

150

200

250

1999 2008

Inventory Year

Figure 44.—Average annual net growth, removals, and mortality on 

timberland and as a proportion of total growing-stock volume, Maryland, 1999 

and 2008. (Error bars show 68 percent confi dence intervals around the mean.)

Species

5.9

1.1

2.1

2.9

3.7

6.1

2.0

10.6

12.2

0 10 20 30 40 50 60 

Yellow-poplar 

Loblolly pine 

Red maple 

Sweetgum

White oak 

Black cherry 

Northern red oak 

Chestnut oak 

American Beech 

Volume (million ft3)

Net growth 

Removals

Figure 45.—Average annual net growth, removals, and growth-to-removals 

(G:R) ratio for major species, Maryland, 2008. G:R for all species is 2.6. (Error 

bars show 68 percent confi dence intervals around the mean.)

ratio (G:R) doubled between 1999 and 2008 from 1.3 to 

2.6. The hardwood G:R nearly tripled during this same 

time period (1.3 to 3.6). 

Yellow-poplar has one of the highest G:R at 6.1 (Fig. 45). 

Loblolly pine, the species with the second highest growth 

rate (and 30 percent of all removals), has a G:R of only 1.1, 

indicating that the population is relatively stable. Oaks, as 

a group, which represent 17 percent of all removals, have 

a G:R of 3.5. However, several species, including Virginia 

pine, fl owering dogwood, and yellow birch, have negative 

growth estimates. A loss of growth can occur on live trees 

due to damage, rot, or other causes.
31

FOREST RESOURCES

What this means

FIA data suggest that net growth has been increasing 

over time. Substantial increases appear to have been 

driven by the growth of yellow-poplar. The G:R of 

this species far exceeds that of oaks, suggesting that the 

yellow-poplar component of Maryland’s forests will 

become more important in the future.

Loblolly pine is an important commercial species in 

Maryland and the impressive growth of this species may 

be due to improved management. After the 1986 FIA 

inventory results showed decreases in pine volumes, the 

Maryland Department of Natural Resources (MD DNR) 

formed the Loblolly Pine Task Force to address the issue. 

The current inventory results indicate that loblolly pine 

growth has increased and that growth exceeds removals 

with a G:R of 1.1. 

The slow growth that some species such as Virginia pine 

exhibit may be partially due to shifts in competitive 

advantage as Maryland’s forests mature and shadeintolerant species become less prevalent. As the 

population of Virginia pine trees get older, they become 

more susceptible to environmental stressors, growth 

rates decline, and mortality rates increase (Burkman 

and Bechtold 2000). These cyclical patterns in forest 

composition have occurred in the past and are likely 

to occur in the future. Maryland’s hardwood forests 

are more susceptible to the variations of ecological 

processes that occur in unmanaged natural systems 

where competition and successional patterns determine 

competitive advantage and fl oristic dominance.

Mortality

Background

The loss of tree volume to mortality is a natural process. 

Excessive mortality, however, can be an indicator of 

poor forest health and can be caused by insects, disease, 

humans or other animals, competing vegetation, weather 

events, old age, or a combination of these factors. In 

very dense stands, more trees die due to competition for 

resources. In open, sparse stands, trees might be more 

susceptible to extremes in wind and precipitation, or 

prone to damage by animals. In addition to per-species 

diameter-class and volume distributions, per-species 

mortality estimates can give a clue to the composition of 

the future forest. 

What we found

In Maryland, the average annual mortality was 44 million 

cubic feet, or 18 cubic feet per acre per year. Although 

the data suggest that mortality has been increasing since 

the 1986 inventory, it is still only 0.7 percent of the total 

growing-stock volume. Although the total mortality of 

softwoods is lower than that of hardwoods, total softwood 

mortality relative to the softwood growing-stock volume 

(known as relative mortality) is much higher than that 

of hardwoods relative to hardwood volume (Fig. 46). In 

1999 and 2008, most mortality consisted of trees greater 

than 11 inches d.b.h.

Total 

Softwoods

Hardwoods

0

0.2

0.4

0.6

0.8

1

1.2

1986 1999 2008 

Relative Mortality

Inventory Year 

Figure 46.—Average annual mortality as a proportion of growing-stock 

volume on timberland by species group and inventory year, Maryland, 1986, 

1999, and 2008.

The only dominant species that shows a signifi cant 

change (in this case, a decrease) in mortality between 

1999 and 2008 is sweetgum (Fig. 47). All of the other 

dominant species show similar levels of volume in the 

two time periods. Red maple shows the largest relative 

mortality (proportion of the total current volume of that 
32

FOREST RESOURCES

species) of the nine most dominant species (Fig. 48). 

Several of the oak species have some of the higher relative 

mortality values. Yellow-poplar, a species that has been 

increasing in dominance, exhibits low relative mortality.

higher relative level of mortality of red maple and several 

of the oak species is not surprising. Red maple is not very 

resistant to physical damage from weather events and once 

this damage occurs, the trees become more vulnerable 

to insect or disease attack, loss of vigor, and death. With 

respect to the oaks, the distribution of oaks tends toward 

the large-diameter classes. These larger, more mature trees 

might be, as a group, reaching the end of their natural 

life span, and are becoming more susceptible to the 

aforementioned damaging agents. Yellow-poplar, on the 

other hand, with some of the lower relative mortality, tends 

as a group toward some of the early to mid-successional 

size classes. Trees at this stage in their life cycle tend to be 

more vigorous and resistant. As insects and disease threats 

emerge, managers should continue to monitor mortality 

rates of susceptible species like ash (Fraxinus spp.), 

fl owering dogwood (Cornus fl orida), and oaks. 

Timber Products

Background

The harvesting and processing of timber products produces 

a stream of income shared by timber owners, managers, 

marketers, loggers, truckers, and processors. In 2007, the 

wood products and paper manufacturing industries in 

Maryland employed 8,290 people, with an average annual 

payroll of $319 million (U.S. Census Bureau 2007). To 

better manage the State’s forests, it is important to know the 

species, amount, and location of timber being harvested.

Surveys of Maryland’s wood-processing mills are conducted 

periodically to estimate the amount of wood volume that 

is processed into products. This is supplemented with 

the most recent surveys conducted in surrounding states 

that processed wood harvested from Maryland. These 

data include information from four common mill types: 

sawmills which make wood planks and boards, pulp 

mills which make fi brous pulp used to make paper and 

other products, cooperage mills that make barrels, casks 

and tanks and excelsior mills which make wood shavings 

commonly used as packing material.

Figure 47.—Average mortality for major species, Maryland, 1999 to 2008. 

(Error bars show 68 percent confi dence intervals around the mean.)

Figure 48.—Mortality as a proportion of total growing-stock volume for major 

species, Maryland, 1999 to 2008. Average relative mortality for all species is 0.7.

Species

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 

American beech 

Yellow-poplar 

Sweetgum

Black oak 

Loblolly pine 

Black cherry 

Chestnut oak 

White oak 

Northern red oak 

Red maple 

Relative Mortality 

Species

1999

2008

0 2 4 6 8 10 

Black oak 

Black cherry 

Sweetgum

Northern red oak 

Yellow-poplar 

Chestnut oak 

White oak 

Loblolly pine 

Red maple 

Mortality (million ft3)

What this means

Mortality levels are generally at or below 1 percent for 

all species across the State. These mortality levels do not 

indicate any dramatic deviations from that expected 

from natural processes such as succession, periodic loss 

of vigor and death from insect or physical damage, or 

competition with other individuals for resources. The 
33

FOREST RESOURCES

0 2 4 6 8 10 

Loblolly/shortleaf pine 

Other pines 

Other softwoods 

Yellow-poplar 

Red oaks 

White oaks 

Soft maple 

Black cherry 

Sweetgum

Hard maple 

Other hardwoods 

Industrial Roundwood Harvest (million ft3

)

Species Group 

What we found

In 2008, 20 saw mills, 1 pulp mill, 1 cooperage mill, 

and 1 excelsior/shavings mill were surveyed to determine 

what species were processed and where the wood material 

came from. These mills processed 45.9 million cubic feet 

of industrial roundwood. Less than half of the processed 

roundwood was actually harvested from Maryland’s forest 

land. The remainder was brought in from neighboring states.

In 2008, 27.4 million cubic feet of industrial roundwood 

was harvested from Maryland’s forest land. Saw logs and 

pulpwood each accounted for 46 percent of the total 

industrial roundwood harvested (Fig. 49). Other products 

harvested included excelsior, post, poles, pilings, veneer 

logs, and cooperage. Loblolly and shortleaf pine accounted 

for almost a third of the total industrial roundwood harvest 

(Fig. 50). Other important species groups harvested were 

the yellow-poplar, oaks, maples, and black cherry.

In the process of harvesting industrial roundwood, 15.1 

million cubic feet of harvest residues were left on the 

ground. More than three-fourths of the logging residue 

came from nongrowing-stock sources (logging slash), 

such as crooked or rotten trees, nonforest trees, tops 

and limbs, and dead trees (Fig. 51). The processing of 

industrial roundwood by the State’s primary wood-using 

mills generated another 413,600 dry tons of wood and 

bark residues. More than 55 percent of the mill residues 

generated were used for miscellaneous products such as 

animal bedding and small dimension products. Another 

20 percent of the mill residues were used for mulch, 

and 17 percent were used for fi ber products. Less than 

1 percent of the mill residues were not used for other 

products (Fig. 52).

4% 3%

<1%

<1%

46%

46%

Saw logs 

Pulpwood

Veneer logs 

Cooperage

Excelsior

Post, pole, and piling

8%

28%

8%

9%

47%

Sawtimber

Poletimber size 

Saplings, limbwood, cull,

dead trees,and nonforest trees

Logging slash 

Logging residue

0 

25 

50 

75 

100 

Bark residues Coarse residues Fine residues 

Volume of Mill Residues (1,000 dry tons) 

Fiber products 

Industrial fuel 

Domestic fuel 

Mulch 

Miscellaneous uses 

Not used 

Figure 51.—Residue generated by industrial roundwood harvesting by 

growing stock and nongrowing stock, and used for product and harvest 

residue, Maryland, 2008.

Figure 49.—Industrial roundwood and fuelwood production by product, 

Maryland, 2008.

Figure 50.—Industrial roundwood harvested by species group, Maryland, 2008.

Figure 52.—Disposition results of mill residues generated by primary woodusing mills, Maryland, 2008.
34

FOREST RESOURCES

What this means

The demand for wood products is likely to increase, 

placing a greater demand on the resource. An important 

consideration for the future of the primary woodproducts industry is its ability to retain industrial 

roundwood processing facilities. The number of wood 

processing mills has been steadily declining. The loss of 

processing facilities makes it harder for landowners to 

fi nd markets for the timber harvested from management 

activities on their forest land.

Another important issue is the volume of harvest residues 

that are generated but go unused. Almost a quarter of 

the harvest residue generated is from growing-stock 

sources (wood material that could be used to produce 

products). Industrial fuelwood or increased pulpwood 

markets could lead to better utilization of merchantable 

trees. The use of logging slash for industrial fuelwood at 

cogeneration facilities and pellet mills could also result 

in better utilization of the forest resource. The desire to 

utilize all harvested material however must be balanced 

by the ecological value of leaving some behind at the 

logging site. Logging slash that prevents erosion and soil 

loss and later recycles nutrients back into the soil is a 

valuable use of some harvest residues. 
35

Forest Health

Light seeping through a hardwood canopy, New Germany State Park, Garrett County, MD, 2009. Photo by Jack Perdue, Maryland DNR.
36

FOREST HEALTH

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1950 1964 1976 1986 1999 2008 

Proportion of Forest Land 

Inventory Year 

Small diameter 

Nonstocked

Large diameter 

Medium diameter 

0 - 20 

21 - 40 

41 - 60

61 - 80 

81 - 100 

101 - 150 

151 - 200 

0

100

200

300

400

500

600

700

Small

diameter

Medium

diameter

Large

diameter

Forest Land Area (1,000 acres) 

Stand Age (years) 

Young Forest Habitat

Background 

Maryland’s forests provide habitat for numerous species 

of mammals, birds, reptiles, and amphibians, as well as 

for fi sh, invertebrates, and plants. Several indicators of 

wildlife habitat abundance can be derived from FIA data. 

Forest composition and structure affect the suitability 

of habitat for each species. Some species depend upon 

early successional forests or the ecotone (edge) between 

different forest stages. Yet other species require old 

growth forests or interior forests. Many species require 

multiple structural stages of forests to meet their needs 

during different phases of their life history. Abundance 

and trends in these structural and successional stages 

serve as indicators of population carrying capacity for 

wildlife species (Hunter et al. 2001). 

According to the Maryland Wildlife Diversity 

Conservation Plan (MD DNR 2005), there is a critical 

need to maintain a diversity of natural communities 

including natural shrublands, old fi elds, and other forms 

of early successional habitat. Several of Maryland’s 

species of greatest conservation need are associated with 

young forests, like American woodcock (Scolopax minor) 

and golden-winged warblers (Vermivora chrysoptera), 

both of which are showing alarming declines in 

population during the past several decades.

Other species require interior forest, which is discussed 

in the ‘Forest Fragmentation and Urbanization’ section, 

or old-growth forest, which was once a dominant feature 

throughout most of the Maryland landscape but is 

currently scattered and rare in the state and region. 

What we found 

Peak distribution of small-diameter stand-size class, 

which is an indicator of early successional stages, 

occurred during 1950 (22 percent), falling below 10 

percent of all forest land during the 1986 and current 

inventories (Fig. 53). Concurrently, distribution of largediameter stand-size class has increased steadily from less 

than 50 percent during 1950 to 76 percent during the 

current inventory, with medium diameter forest showing 

the opposite trend, decreasing from about 26 percent 

during 1950 to 14 percent in the current inventory 

(Fig. 53). Most Maryland forest land is in stand-age 

classes over 40 years, and a small fraction is older than 

150 years. Small-diameter stand-size class comprises 

only minor fractions of forests older than 20 years, but 

predominates young forests (0 to20 years) (Fig. 54).

Figure 53.—Proportion of forest land by stand-size class, Maryland, 1950-2008.

Figure 54.—Area of forest land by age class and stand-size class, Maryland, 

2008.
37

FOREST HEALTH

What this means 

Decreasing abundance of small- and medium-diameter 

stand-size classes is offset by increasing abundance in 

large-diameter class. Most of the large-diameter class is 

less than 100 years of age. While both stand-size class 

and stand-age class are indicators of successional stages 

of forests, the two attributes are not interchangeable 

and are best used in combination. The data suggest that 

the amount of early successional habitat in Maryland 

may be decreasing. Early successional habitat is a critical 

component of Maryland’s forests. Not only does a 

healthy, sustainable forest depend upon an adequate 

quantity of young trees, but many species of wildlife 

use this habitat type, including several species that are 

considered to be in need of conservation. These include 

bird species such as the northern bobwhite (Colinus 

virginianus), fi eld sparrow (Spizella pusilla), prairie 

warbler (Dendroica discolor), and American woodcock 

(Scolopax minor). There is a need to maintain forest 

conditions in multiple stand-size and age classes to 

provide habitats for all forest-associated species.

Standing Dead Trees

Background 

Nesting cavities and standing dead trees (at least 5 inches 

d.b.h) provide critical habitat components for many 

forest-associated wildlife species. Standing dead trees 

that are large enough to meet habitat requirements for 

wildlife are referred to as ‘snags’. Standing dead trees 

serve as important indicators not only of wildlife habitat, 

but also for past mortality events and carbon storage. 

The number and density of standing dead trees, together 

with decay classes, species, and sizes, defi ne an important 

wildlife habitat feature across Maryland’s forests.

What we found 

More than 35 million standing dead trees are present 

on Maryland forest land. This represents an overall 

density of 14.2 standing dead trees per acre of forest 

land. Ten species groups each contributed more than 1 

million standing dead trees, with the top group, ‘other 

eastern hard hardwoods’ exceeding 4.7 million (Fig. 55). 

Species in this group include black locust, oak, birch, 

dogwood, common persimmon, American holly and 

white mulberry. Relative to the total number of live trees 

in each species group, seven species groups exceeded 

fi ve standing dead trees per 100 live trees, four of which 

exceeded 10 standing dead trees per 100 live trees, with 

‘other yellow pines’ leading all groups with more than 21 

standing dead trees per 100 live trees (Fig. 56). Eightysix percent of standing dead trees were smaller than 11 

inches d.b.h., with more than 40 percent between 5 and 

6.9 inches d.b.h. (Fig. 57). Most standing dead trees 

were classifi ed in the three intermediate decay classes, 

with the fewest number in the class of most decay. This 

pattern was consistent across most decay classes (Fig. 57).

0 2 4 6 

Other eastern hard hardwoods 

Loblolly and shortleaf pine 

Select white oaks 

Other eastern soft hardwoods 

Other yellow pines 

Other red oaks 

Soft maple 

Other white oaks 

Sweetgum

Yellow-poplar 

Ash

Tupelo and blackgum 

Select red oaks 

Noncommercial hardwoods 

Other eastern softwoods 

Eastern hemlock 

Hickory

Eastern white and red pine 

Hard maple 

Beech

Black walnut 

Cypress

Cottonwood and aspen 

Standing Dead (million trees) 

Species Group 

Figure 55.—Number of standing dead trees by species group, Maryland, 2008.
38

FOREST HEALTH

What this means 

Snags result from a variety of causes, including diseases 

and insects, weather damage, fi re, fl ooding, drought, and 

competition, and other factors. ‘Other yellow pines’ species 

group had the highest density of standing dead trees per 

100 live trees, attributable mostly to Virginia pine, which 

accounted for more than 90 percent of standing dead trees 

in this species group. Compared to live trees, the number of 

standing dead trees is small, but they contain signifi cantly 

more cavities than occur in live trees (Fan et al. 2003). 

Standing dead trees provide areas for foraging, nesting, 

roosting, hunting perches, and cavity excavation for wildlife, 

from primary colonizers such as insects, bacteria, and fungi 

to birds, mammals, and reptiles. Most cavity nesting birds 

are insectivores that help to control insect populations. 

Providing a variety of forest structural stages and retaining 

specifi c features like snags on both private and public lands 

are ways that forest managers maintain the abundance and 

quality of habitat for forest-associated wildlife species in 

Maryland.

Forested Wetlands

Background 

Wetlands are transitional areas between terrestrial and 

aquatic ecosystems characterized by some combination 

of water above or near the soil surface, wet soil types, and 

plants that only grow in wet conditions. Wetlands have 

unique plant and animal communities that have adapted 

to these conditions and offer many ecosystem services such 

as water fi ltration and storage, nutrient cycling, fl ood and 

erosion control, carbon sequestration, and providing habitat 

for wildlife, including, in the case of estuarine wetlands, 

many commercial marine species. Wetlands are extensive 

in Maryland, especially in coastal areas in and around the 

Chesapeake Bay (Tiner and Burke 1995).

The U.S. Fish and Wildlife Service conducts the National 

Wetlands Inventory (NWI) using the Cowardin wetland 

classifi cation system (Cowardin et al. 1979) to map the 

nation’s wetlands. FIA uses a geographic information 

Figure 56.—Number of standing dead trees per 100 live trees by species 

group, Maryland, 2008.

0 5 10 15 20 25 

Other yellow pines 

Eastern hemlock 

Cypress

Select white oaks 

Ash

Other red oaks 

Other white oaks 

Other eastern soft hardwoods 

Loblolly and shortleaf pine 

Other eastern softwoods 

Other eastern hard hardwoods 

Eastern white and red pine 

Yellow-poplar 

Select red oaks 

Black walnut 

Cottonwood and aspen 

Hickory

Soft maple 

Tupelo and blackgum 

Sweetgum

Hard maple 

Noncommercial hardwoods 

Beech

Number of Standing Dead Trees per 100 Live Trees 

Species Group 

All limbs and branches present 

Few limbs and no fine branches 

Only limb stubs present 

Few or no limb stubs remain 

No evidence of branches remain 

Decay Classes 

0 

1 

2 

3 

4 

6 8 10 12 14 16 18 20 22 23.0+ 

Standing Dead Trees (millions) 

Diameter Class (inches) 

Figure 57.—Distribution of standing dead trees by decay and diameter classes 

for standing dead trees, Maryland, 2008.
39

FOREST HEALTH

system to layer the Cowardin wetland classes to spatially 

corresponding Maryland FIA plots. FIA then uses the 

wetland category as a classifi cation variable in the data 

summaries presented in this report.

What we found 

Seventeen percent of Maryland’s forest land falls in 

wetland areas. Sixty-one percent of the forested wetland 

area is concentrated in the lower Eastern Shore in Caroline, 

Dorchester, Wicomico, Worcester, and Somerset Counties 

(Fig. 58). The large stand-size class dominants both the 

forested wetland and non-wetland areas in Maryland, 

however there appears to be a greater acreage of smallsize class stands in the wetland areas (Fig. 59). Species 

composition is similar among forested wetland and nonwetland areas in Maryland as the most abundant species 

5 inches in d.b.h. and greater in wetland areas are the 

same as in non-wetland areas (red maple, American holly, 

blackgum, and loblolly pine; Fig. 60). However, the relative 

dominance, in terms of numbers of trees, is different. 

Blackgum and loblolly pine show greater abundance in 

Maryland wetland areas due to the fact that these species 

can grow in wetter environments and are more salt-tolerant 

than some of their competitors, allowing them to exist in 

higher numbers in brackish estuarine wetland.

Figure 60.—Percent of total number of growing-stock trees in each class for 

select species on wetland and non-wetland forest, Maryland, 2008.

Figure 58.—Area of forested wetland by county, Maryland, 2008.

< 1 

1 - 10

10 - 30

> 30

Forest Wetland Area 

(thousand acres)

Projection: MD State Plane, NAD83. Sources: FIA 2008, TIGER/Dynamap 

2000. Geographic base data are provided by the National Atlas of the USA. 

FIA data and tools are available online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: T. Lister. April 2011.

Wetland

Non-wetland

0

10

20

30

40

50

60

70

80

90

Large Medium Small 

Percent of Forest Land 

Diameter Stand-size Class 

Wetland 

Non-wetland

0

5

10

15

20

25

30

35

Red

maple

Sweetgum American 

holly

Blackgum Loblolly 

pine

Percent of all Growing-stock Trees 

What it means 

Maryland’s unique location surrounding the central portion 

of the Chesapeake Bay creates a wetland-rich environment 

that is one of the State’s natural treasures. The lower Eastern 

Shore hosts the majority of the State’s forested wetlands and 

there are a number of wildlife refuges in the area, including 

the Black Water National Wildlife Refuge, that have been 

designated to help protect these important ecosystems 

and the associated wildlife that frequent there. These 

include three forest-dependant species that are considered 

“recovering species”: the endangered Delmarva fox squirrel 

(Sciurus niger cinereus), the threatened American bald eagle 

(Haliaeetus leucocephalus), and the recently delisted migrant 

peregrine falcon (Falco peregrinus). It is thus important to 

monitor these areas, looking for shifts in acreage, species 

composition, and forest health. As FIA begins its fi rst cycle 

of remeasurement under the annual system and the U.S. 

Fish and Wildlife Service wetland maps continue to be 

improved and updated, the integration of FIA and wetlands 

data will provide opportunities for this monitoring.

Figure 59.—Percent of forest land by diameter size class in wetland and 

nonwetland areas, Maryland, 2008.
40

FOREST HEALTH

Down Woody Materials 

Background

Down woody materials, in the form of fallen trees and 

branches, fulfi ll a critical ecological niche in Maryland’s 

forests by providing valuable wildlife habitat. Down 

woody material also contributes to forest fi re hazards via 

surface woody fuels. 

Since dried wood is a greater fi re hazard risk, one way to 

determine down woody material’s fi re hazard potential 

is to classify it by the amount of time it take for the 

material to dry out. These classes are called time-lag fuel 

classes. Larger coarse woody debris takes longer to dry 

out than smaller fi ne woody pieces. For example, timelag fuel classes for small fi ne woody debris equal 1 hour, 

medium woody debris equal 10 hours, large fi ne woody 

debris equal 100 hours, and coarse woody debris equal 

1,000+ hours (Woodall and Monleon 2008).

What we found

The fuel loadings of down woody materials (time-lag 

fuel classes) are not exceedingly high in Maryland 

(Fig. 61). When compared to the neighboring states of 

New Jersey and Delaware, Maryland’s fuel loadings of all 

time-lag fuel classes are not substantially different. The 

size-class distribution of coarse woody debris appears to 

be heavily skewed (85 percent) toward pieces less than 

8 inches in diameter at point of intersection with plot 

sampling transects (Fig. 62A). With regard to decay-class 

distribution of coarse woody debris, 78 percent of coarse 

woody debris pieces are in decay class 3 and 4 (Fig. 62B), 

typifi ed by moderate- to heavily-decayed logs that are 

sometimes structurally sound but missing most or all 

of their bark and with extensive sapwood decay. Coarse 

woody debris volume per acre decreases slightly as livetree density (basal area per acre) increases. Stands with 

the greatest volumes of coarse woody debris were more 

often those with low levels of standing live tree basal 

area (Fig. 63). 

0

100

200

300

400

500

600

0.0-30.0 30.1-60.0 60.1-90.0 90.1-120.0 120.1+ 

Coarse Woody Debris (ft3/acre)

Basal Area (ft2/acre)

Figure 63.—Means coarse woody debris volumes (ft3/acre) on forest land in 

Maryland, 2008. (Error bars show 68 percent confi dence intervals around the 

mean.)

New Jersey 

Maryland

Delaware

0

0.5

1

1.5

2

2.5

3

3.5

4

1-hr 10-hr 100-hr 1,000+-hr 

Fuel Loadings (tons/acre) 

Fuel-hour Classes 

Figure 61.—Means and associated standard errors of fuel loadings (tons/acre, 

time-lag fuel classes) on forest land in Maryland and neighboring states, 2008. 

(Error bars show 68 percent confi dence intervals around the mean.)

85%

13%

2%

Coarse Woody

Diameter (inches) 

15%

41%

37%

2% 5%

Decay Class

3.0-7.9

8.0-12.9

13.0-17.9

1

2

3

4

5

Figure 62.—Mean percentage of coarse woody debris pieces per acre 

by transect diameter (inches) (A) and decay classes (B) on forest land in 

Maryland, 2008.

A B
41

FOREST HEALTH

What this means

Only in times of extreme drought in Maryland would 

these low amounts of fuels pose a hazard across the state. 

Of all down woody components, the largest amount was 

in coarse woody debris (i.e., 1,000+-hr fuels). However, 

coarse woody debris volumes were still relatively low and 

were represented by small, moderately decayed pieces. The 

scarcity of large coarse woody debris resources may also 

indicate a lack of high quality wildlife habitat. Because 

fuel loadings are not exceedingly high across Maryland, 

potential fi re dangers are outweighed by the benefi ts of 

down woody material for wildlife habitat and carbon sinks.

Lichen Communities

Background

Lichens are symbiotic, composite organisms of members of 

as many as three kingdoms. The dominant partner, in terms 

of biomass, is a fungus. Fungi are incapable of producing 

their own food so they typically provide for themselves as 

parasites or decomposers. The lichen fungi (kingdom Fungi) 

cultivate partners that manufacture food by photosynthesis. 

Sometimes the partners are algae (kingdom Protista), other 

times cyanobacteria (kingdom Monera), formerly called 

blue-green algae. Some enterprising fungi associate with 

both at once (Brodo et al. 2001).

Lichen community monitoring is included in the 

FIA Phase 3 (P3) inventory to assess the impact of air 

pollution on forest resources, or spatial and temporal 

trends in biodiversity. This long-term lichen monitoring 

program in the United States dates back to 1994. The 

objective of collecting lichen data is to determine the 

presence and abundance of lichen species on woody 

plants. Lichens occur on many different substrates (e.g., 

rocks), but FIA sampling is limited to standing trees or 

branches that have recently fallen to the ground. 

A close relationship exists between lichen communities 

and air pollution, especially acidifying nitrogen- and 

sulfur-based pollutants. A major reason lichens are 

so sensitive to air quality is their total reliance on 

atmospheric sources of nutrition. By contrast, it is 

diffi cult to separate tree-growth responses specifi c to air 

pollution from other stressors (McCune 2000).

What we found

Eighty-four lichen species (gamma diversity) were 

sampled on lichen plots in Maryland (Table 2). The 

most common lichen genus, Punctelia, was present on 17 

percent of the plots (Table 3). The genus with the highest 

number of species sampled was Cladonia (7 species).

Lichen diversity is estimated by the number of species 

found at a site; this measure is termed species richness. 

Richness values fell into the low to medium categories 

across Maryland (Table 2). Figure 64 shows the spatial 

distribution of lichen species richness scores. 

Table 2.—Lichen community summary table for Maryland, 1994-2003

Number of plots surveyed 12 

Number of plots by species richness category 

 0-6 species (low) 4

 7-15 species (medium) 8 

 16-25 species (high) 0 

Median 9

Range of species richness score per plot (low-high) 5-13

Average species richness score per plot (alpha diversity) 8.8

Standard deviation of species richness score per plot 3

Species turnover rate (beta diversity)a

 9.5

Total number of species per area (gamma diversity) 84

a Beta diversity is calculated as gamma diversity divided by alpha diversity.

 

Parameter
42

FOREST HEALTH

Projection: Albers, NAD83. Sources: NLCD 1992, FIA 2003. Geographic base data 

are provided by the National Atlas of the USA. FIA data and tools are availabe at 

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: R.S. Morin. Dec. 2010.

Lichen Species 

Richness Score

Low

 Medium-low

 Medium-high

 High

 Water

 Nonforest

Projection: Albers, NAD83. Sources: MRLC Consortium 1992, NADP 2002.

Geographic base data are provided by the National Atlas of the USA. FIA data 

and tools are available online at http://www.fi a.fs.fed.us/tools-data/

Cartography: R.S. Morin. Dec. 2010.

Sulfate as SO4

-2

(mg/ha)

 8 - 13

 13 - 17

 17 - 22

 22 - 26

 26 - 30

 Water

 Nonforest

Figure 64.—Estimated lichen species richness, Maryland, 2000-2003.

Projection: Maryland State Plane, NAD83. Sources: NLCD 2006, 

FIA 2003. Geographic base data are provided by the National 

Atlas of the USA. FIA data and tools are available online at 

http://www.fi a.fs.fed.us/tools-data/

Cartography: R.S. Morin. Feb. 2011

Lichen Species 

Richness Score

< 6

 6 - 8

 8 - 10

 > 10

 Water

 Nonforest

What this means

In general, species richness scores were highest in the 

western, mountainous region of the State and the eastern 

Piedmont region. Showman and Long (1992) reported 

that mean lichen species richness was signifi cantly lower 

in areas of high sulfate deposition compared to low 

deposition areas. Sulfate deposition levels have been 

relatively homogenous across Maryland and are moderate 

compared to other areas in the northeastern United States 

(Fig. 65). In the northeastern United States, there is a 

general pattern of lower lichen species richness scores in 

high deposition areas and vice versa (Fig. 66). Other factors 

may affect the distribution of lichen species, including 

intrinsic forest characteristics and long-term changes in 

climate. The lichen species richness scores reported here will 

serve as baseline estimates for future monitoring at the State 

and regional level.

Punctelia 17.0 5

Phaeophyscia 15.0 2

Physcia 14.3 4

Cladonia 9.5 7

Flavoparmelia 8.2 1

Myelochroa 6.8 3

Parmotrema 6.1 6

Pyxine 4.1 2

Parmelia 3.4 3

Canoparmelia 2.7 2

Hypotrachyna 2.0 2

Parmelinopsis 2.0 2

Usnea 2.0 3

Heterodermia 1.4 2

Hyperphyscia 1.4 1

Candelaria 0.7 1

Cetraria 0.7 1

Flavopunctelia 0.7 1

Hypogymnia 0.7 1

Physciella 0.7 1

Rimelia 0.7 1

Total 100 51

 All Specimens Species

 Genus (percent) (count)

Table 3.—Percentage of specimens and number of species for lichen sampled, 

Maryland, 1994-2003

Figure 65.—Mean sulfate ion wet deposition, northeastern U.S., 1994-2002. 

Figure 66.—Estimated lichen species richness, northeastern U.S., 2000-2003.
43

FOREST HEALTH

Crown Health

Background

The crown condition of trees is infl uenced by various 

biotic and abiotic stressors. Abiotic stressors include 

drought, fl ooding, cold temperatures or freeze injury, 

nutrient defi ciencies, soil physical properties affecting 

soil moisture and aeration, and toxic pollutants. Biotic 

stressors include native or introduced insects, diseases, 

invasive plant species, and animals.

Seasonal or prolonged drought has been a signifi cant 

and historical stressor in Maryland. Droughts have 

occurred in some regions of the State during 1999 and 

2002; alternatively, some of the wettest years on record 

were recorded in 2003 and 2004 (NCDC 2010). These 

extreme precipitation events can produce conditions that 

facilitate insect and disease outbreaks and can be even 

more devastating to trees that are already stressed by pest 

damage or other agents.

Invasions by exotic diseases and insects are one of the 

most important threats to the productivity and stability 

of forest ecosystems around the world (Liebhold et al. 

1995, Pimentel et al. 2000, Vitousak et al. 1996). Over 

the last century, Maryland’s forests have suffered the 

effects of well known exotic and invasive agents such 

as Dutch elm disease (Ophiostoma ulmi), chestnut 

blight (Cryphonectria parasitica), European gypsy 

moth (Lymantria dispar), beech bark disease complex, 

and hemlock woolly adelgid (Adelges tsugae). Another 

important invader that is currently invading Maryland’s 

forests is emerald ash borer (Agrilus planipennis).

Tree-level crown measurements are collected on P3 

plots. They include vigor class, crown ratio, light 

exposure, crown position, crown density, crown dieback, 

and foliage transparency. Three factors were used to 

determine the condition of tree crowns: crown dieback, 

crown density, and foliage transparency. Crown dieback 

is defi ned as recent mortality of branches with fi ne 

twigs and refl ects the severity of recent stresses on a 

tree. Crown density is defi ned as the amount of crown 

branches, foliage, and reproductive structures that block 

light visibility through the crown and can serve as a 

predictor of growth in the near future. Finally, foliage 

transparency is the amount of skylight visible through 

the live, normally foliated portion of the crown. Changes 

in foliage transparency can also occur because of 

defoliation or from reduced foliage resulting from stresses 

during preceding years. A crown was labeled as ‘poor’ 

if crown dieback was greater than 20 percent, crown 

density was less than 35 percent, or foliage transparency 

was greater than 35 percent. These three thresholds were 

based on preliminary fi ndings by Steinman (2000) that 

associated crown ratings with tree mortality.

What we found

The occurrence of poor crowns in Maryland was very 

low and evenly distributed across the State (Fig. 67). The 

only species with greater than 10 percent of live basal 

area containing poor crowns is red maple (Table 4). The 

highest proportion of red maple basal area containing 

poor crowns was found in the southeastern part of 

Maryland (Fig. 68). 

Projection: Maryland State Plane, NAD83. Sources: NLCD 2006, FIA 2008. Geographic base 

data are provided by the National Atlas of the USA. FIA data and tools are available online at 

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: R.S. Morin. Feb. 2011.

Percent of Live 

Basal Area with 

Poor Crowns

< 5 

5 - 10 

10 - 25 

> 25 

Water 

Forest 

Nonforest

Figure 67.—Percent of live basal area with poor crowns, Maryland, 2008.
44

FOREST HEALTH

What this means

Red maple is the most numerous tree species in 

Maryland and contains the second highest volume of 

wood. It is an important species due to its value as a 

timber and pulp species and its attractive fall foliage. 

Red maple mortality has remained stable since the 1999 

inventory (Fig. 47). The occurrence of poor crowns is 

unlikely to be related to a forest health problem. Many 

insects and diseases occur on red maple but none of 

them typically have major impacts. Maryland’s Eastern 

Shore had the highest proportion of red maple with 

poor crowns, an area of the state that also has the highest 

concentration of fresh and brackish wetlands. Poor red 

maple crowns in this area might be due in part to stress 

from saturated soils or the tree’s sensitivity to salt. 

Table 4.—Percent of live basal area with poor crowns, Maryland, 2008

Red maple 11

Loblolly pine 1

Yellow-poplar <1

White oak <1

Sweetgum <1

Chestnut oak <1

Northern red oak <1

Black cherry <1

Black oak <1

Scarlet oak <1

 Percent of Basal Area 

Species with Poor Crowns

Figure 68.—Percent of red maple live basal area with poor crowns, 

Maryland, 2008.

Projection: Maryland State Plane, NAD83. Sources: NLCD 2006, FIA 2008. Geographic base 

data are provided by the National Atlas of the USA. FIA data and tools are available online at 

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: R.S. Morin. Feb. 2011.

Percent of Live 

Basal Area with 

Poor Crowns

< 5 

5 - 10 

10 - 25 

> 25 

Water 

Forest 

Nonforest

Ozone Bioindicator Plants

Background

Ozone (O3) is a byproduct of industrial operations 

and is found in the lower atmosphere. Ozone forms 

when nitrogen oxides and volatile organic compounds 

go through chemical transformation in the presence 

of sunlight (Brace et al. 1999). Ground-level ozone is 

known to have detrimental effects on forest ecosystems. 

Certain plant species exhibit visible, easily diagnosed 

foliar symptoms of ozone exposure. Ozone stress in a 

forest environment can be detected and monitored by 

using these plants as indicators. FIA uses a set of these 

indicator plants to monitor changes in air quality across 

a region and to evaluate the relationship between ozone 

air quality and the indicators of forest condition.

The ozone-induced foliar injury on indicator plants 

is used to describe the risk of impact within the forest 

environment using a national system of sites (Smith et al. 

2003, Smith et al. 2007). These sites are not co-located 

with FIA samples. Ozone plots are chosen for ease of 

access and optimal size, species, and plant counts. As 

such, the ozone plots do not have set boundaries and 

vary in size. At each plot, between 10 and 30 individual 

plants of three or more indicator species are evaluated 

for ozone injury. Each plant is rated for the proportion 

of leaves with ozone injury and the mean severity of 

symptoms using break points that correspond to the 

human eye’s ability to distinguish differences. A biosite 

index is calculated based on amount and severity 

ratings where the average score (amount * severity) for 

each species is averaged across all species at each site 

and multiplied by 1,000 to allow risk to be defi ned 

by integers (Smith et al. 2007). Ozone plots were 

monitored in Maryland between 1994 and 2007.

What we found

Ozone indicator plants sampled are listed in Table 

5; the most common plants sampled are blackberry 

(Rubus spp.), sweetgum, and spreading dogbane 

(Apocynum androsaemifolium) (Table 5). Blackberry 
45

FOREST HEALTH

had the greatest severity of injury while big leaf aster 

(Eurybia macrophylla) had the greatest amount of injury. 

Maryland data indicate that risk of foliar injury due to 

ozone has been moderately variable, but on a downward 

trend since the mid 1990s (Table 6 and Fig. 69) as have 

ozone exposure levels (Fig. 70). 

Table 6.—Regional summary statistics for ozone bioindicator program, Maryland, 1994-2007

Table 5.—Plants species sampled for ozone injury by severity and amount of 

injury, Maryland, 1994-2007

Blackberry 2,420 19.0 24.2

Big leaf aster 30 9.1 30.0

White ash 471 6.1 15.8

Black cherry 851 5.7 5.1

Spreading dogbane 1,188 4.9 6.8

Sweetgum 1,391 4.8 5.1

Milkweed 937 4.2 13.0

Yellow-poplar 691 0.7 2.2

Pin cherry 23 0.0 0.0

Sassafras 1,078 0.0 0.0

Unknown 90 0.0 0.0

 Number of Injury Injury

 plants severity amount

Species sampled (percent) (percent)

1994 9 9 76.5 392 202 37.1 

1995 9 9 21.6 316 79 40.4 

1996 5 5 66.8 248 76 34.9 

1997 5 4 48.8 240 57 38.1 

1998 12 21 48.1 414 86 35.1 

1999 10 3 24.8 338 29 42.2 

2000 7 2 .4 261 27 21.8 

2001 27 16 9.5 1,820 143 36.3 

2002 8 3 11.0 1,109 49 48.1 

2003 9 2 4.9 762 31 25.6 

2004 9 3 1.0 833 35 19.1 

2005 9 9 14.7 671 94 25.7 

2006 9 5 1.2 844 18 30.6 

2007 8 4 .2 922 16 30.2 

a

 Averaged from state values 

 

Maximum

Number of Number of Average Number Number SUM06

Sample biosites biosites biosite of plants of plants valuea

year evaluated with injury index evaluated injured (ppm-hrs)

0

10

20

30

40

50

60

70

80

90

1994 1996 1998 2000 2002 2004 2006 

Biosite Index 

Year 

0

10

20

30

40

50

60

1994 1996 1998 2000 2002 2004 2006 

Maximum SUM06 Exposure (ppm-hrs)

Year 

Figure 69.—Biosite index, Maryland, 1994-2007. See corresponding text for 

description of biosite index.

Figure 70.—Maximum SUM06 exposure levels (ppm-hrs), Maryland, 1994-2007. 

See text for description of SUM06.
46

FOREST HEALTH

What this means

Ozone exposure rates have been decreasing slightly with 

corresponding decreases in foliar injury. This is in contrast 

to evidence of medium and high risk reported by others in 

portions of the mid-Atlantic region (e.g., Coulston et al. 

2003).

A typical summer O3 exposure pattern for the northeastern 

United States is shown in Figure 71. The term SUM06 

is defi ned as the sum of all valid hourly O3 concentrations 

that equal or exceed 0.06 ppm. Controlled studies have 

found that high O3 levels (shown in Fig. 71 as orange 

and red) can lead to measurable growth suppression in 

sensitive tree species (Chappelka and Samuelson 1998). 

Smith et al. (2003) reported that even when ambient 

O3 exposures are high, the percentage of injured plants 

can be reduced sharply in dry years.

Projection: Albers, NAD83. Sources: NLCD 1992, EPA 2006. Geographic base data are 

provided by the National Atlas of the USA. FIA data and tools are available online at 

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: R.S. Morin. April 2011.

 < 10

 10 - 15

 15 - 20

 > 20

 Water

 Nonforest

Figure 71.—Typical June through August 12-hour SUM06 ozone exposure 

rates in northeastern U.S., 2000-2006.

SUM06 Ozone 

Exposure (ppm-hrs)

Forest Soils

Background

FIA collects data to evaluate soil physical and chemical 

properties on P3 plots. Soils are an important 

component of the forest ecosystem. They supply water, 

oxygen, heat, and physical support to vegetation. Soils 

also play a role in cycling carbon through the forest. 

Carbon stocks in soils are important long-term stores 

of carbon accumulated in woody biomass and foliage. 

Accumulating and decaying leaf litter stores carbon on 

the forest fl oor. Measurements of current carbon stocks 

throughout the forest help managers understand the 

importance of different forest types and landscapes in the 

carbon cycle. 

The soils that sustain forests are infl uenced by a number 

of factors, including climate; the trees, shrubs, herbs, 

and animals living there; landscape position; elevation; 

and the passage of time. Climate-soil interactions are 

one signifi cant way that humans infl uence the character 

and quality of the soil and indirectly affect the forest. 

For example, industrial emissions of sulfur and nitrogen 

oxides lead to “acid rain.” The deposition of acids strips 

the soil of important nutrients, notably calcium and 

magnesium. The loss of calcium and magnesium results 

in a shifting balance of soil elements toward aluminum, 

which is toxic to plants in high concentrations. We can 

use the ratio of aluminum to calcium and magnesium as 

measures of the impact of acid deposition on forest soils; 

larger ratios suggest a shift towards more aluminum.

What we found

Carbon stocks in the forest soil were modeled using data 

from throughout the mid-Atlantic region (Delaware, 

Pennsylvania, Maryland, New Jersey, Virginia, and 

West Virginia). Forest fl oor carbon in this region is well 

modeled by three factors: ecological section (a broad 

landscape of similar geology and vegetation), latitude, 

and longitude. Due to the dominance of oak/hickory 

forests in the region, forest-type group is not a strong 
47

FOREST HEALTH

Figure 72.—Modeled forest fl oor carbon storage (Mg/ha), Maryland, 

2004-2006.

Projection: Maryland State Plane, NAD83. Data sources: FIA. Geographic 

base data provided by the National Atlas of the USA. FIA data and tools are 

available online at http://www.fi a.fs.fed.us/tools-data/

Cartography: C. Perry. March 2011.

Forest Floor 

Carbon (Mg/ha)

 High: 31

 Low: 0

 Sample locations

Plot locations are approximate.

predictor of forest fl oor carbon. The largest amounts 

of forest fl oor carbon are near the Atlantic Ocean and 

forests in the western mountains store only moderate 

amounts. Forest fl oor carbon generally increases from 

northwest to southeast (Fig. 72). Similarly, carbon in the 

forest mineral soil is strongly correlated with ecological 

province and longitude (Fig. 73). The carbon stocks in 

mineral soil also have a strong gradient from west to east. 

Data collected from P3 plots affi rms that elemental ratios 

in soil are useful predictors of tree vigor, but the effect of 

these elements varies across species. For instance, it has 

been shown that the crown-to-tree height ratio of white 

oaks increases with the aluminum-to-calcium ratio (Fig. 

74), but decreases with the aluminum-to-magnesium 

ratio (Fig. 75). By contrast, the uncompacted live crown 

Figure 73.—Carbon storage in the shallow mineral soil (0-20 cm), 

Mg/ha, Maryland, 2004-2006.

Projection: Maryland State Plane, NAD83. Data sources: FIA. 

Geographic base data provided by the National Atlas of the USA. 

FIA data and tools are available online at http://www.fi a.fs.fed.us/tools-data/

Cartography: C. Perry. March 2011.

Mineral Soil 

Carbon (Mg/ha)

 High: 76

 Low: 49

 Sample Locations 

Plot locations are approximate.

ratio of black cherry declines with increases in aluminum 

relative to these two elements (Figs. 74, 75). Data 

indicate that yellow-poplar and red maple do not appear 

to be affected by changes in these elemental ratios. 

What it means

Tree species occupy different niches in the landscape. 

This provides a competitive advantage for colonization, 

growth, and reproduction. Atmospheric deposition 

can change the soil substrate through additions and/or 

removals of nutrients and pollutants. These changes in 

the soil infl uence the ability of existing trees to thrive 

0

10

20

30

40

50

60

70

80

Low Med High 

Uncompacted Live Crown Ratio 

Al:Ca Molar Ratio 

Red maple 

Yellow-poplar 

Black cherry 

White oak 

Red maple 

Yellow-poplar 

Black cherry 

White oak 

0

10

20

30

40

50

60

70

80

Low Med High 

Uncompacted Live Crown Ratio 

Al:Mg Molar Ratio 

Figure 74.—The Al:Ca molar ratio compared to uncompacted crown ratio, 

Outer Coastal Plane Mixed Province.

Figure 75.—The Al:Mg molar ratio compared to uncompacted crown ratio, 

Outer Coastal Plane Mixed Province.
48

FOREST HEALTH

and reproduce in their current locations, and can alter 

the ability of other trees to colonize new landscapes. 

For example, our observations suggest that red maple 

and yellow-poplar have a competitive advantage in 

landscapes altered by acid deposition. It is important to 

document and understand natural and anthropogenic 

processes in the soil since they profoundly infl uence the 

current forest and success of future forest management 

plans. In turn, these changes in tree species composition 

across the landscape infl uence carbon sequestration rates 

by forests. 

Understory Vegetation

Background

Forest understory vegetation enhances soil stability, 

provides nutrition and shelter for wildlife, regulates 

microclimate, and adds economic and aesthetic value 

to the forest. Assessments of the forest understory plant 

community provide information on forest structure, 

health, site quality, and other site characteristics. Botanical 

data can reveal the locations of rare and endangered 

species, as well as of invasive and nonnative species. In 

2007 and 2008, detailed understory fl oristic data were 

collected on nine P3 plots and invasive plant data were 

collected on 46 P2 invasive plots in Maryland. Both types 

of plots are used to assess the presence and cover of plant 

species on forest land. P3 plots consist of a complete 

assessment of the understory vegetation while on P2 

invasive plots the vegetation evaluation is limited to the 43 

target invasive plant species listed in Table 7. The species 

on the target list were selected based on stakeholder 

interest and regional occurrence data. To maintain 

regional consistency, the target list was not customized 

specifi cally for the State of Maryland and as a result, 

some species on the list including black locust (Robinia 

pseudoacacia), may be arguably native in some parts of the 

State and not in others.

Table 7.—Invasive plant species target list for P2 invasive plots, 2007 to 

present

Tree Species

Black locust (Robinia pseudoacacia) 

Chinaberry (Melia azedarach)

Norway maple (Acer platanoides)

Princesstree (Paulownia tomentosa)

Punktree (Melaleuca quinquenervia)

Russian olive (Elaeagnus angustifolia)

Saltcedar (Tamarix ramosissima)

Siberian elm (Ulmus pumila)

Silktree (Albizia julibrissin)

Tallow tree (Triadica sebifera)

Tree of heaven (Ailanthus altissima)

Shrub Species

Amur honeysuckle (Lonicera maackii)

Autumn olive (Elaeagnus umbellata)

Common barberry (Berberis vulgaris)

Common buckthorn (Rhamnus cathartica)

European cranberrybush (Viburnum opulus)

European privet (Ligustrum vulgare)

Glossy buckthorn (Frangula alnus)

Japanese barberry (Berberis thunbergii)

Japanese meadowsweet (Spiraea japonica)

Morrow’s honeysuckle (Lonicera morrowii)

Multifl ora rose (Rosa multifl ora)

Showy fl y honeysuckle (Lonicera x bella)

Tatarian bush honeysuckle (Lonicera tatarica)

Vine Species

English ivy (Hedera helix)

Japanese honeysuckle (Lonicera japonica)

Oriental bittersweet (Celastrus orbiculatus)

Herbaceous Species

Black swallow-wort (Cynanchum louiseae) 

Bohemian knotweed (Polygonum x bohemicum) 

Bull thistle (Cirsium vulgare)

Canada thistle (Cirsium arvense)

Creeping jenny (Lysimachia nummularia)

Dames rocket (Hesperis matronalis)

European swallow-wort (Cynanchum rossicum)

Garlic mustard (Alliaria petiolata)

Giant knotweed (Polygonum sachalinense)

Japanese knotweed (Polygonum cuspidatum)

Leafy spurge (Euphorbia esula) 

Purple loosestrife (Lythrum salicaria)

Spotted knapweed (Centaurea biebersteinii)

Grass Species

Common reed (Phragmites australis)

Nepalese browntop (Microstegium vimineum)

Reed canarygrass (Phalaris arundinacea)
49

FOREST HEALTH

What we found

P3 vegetation data were collected in 2007 through 2008 

from nine plots, where 113 plant species were observed. 

Species were broadly categorized based on the classifi cation 

system of the USDA Natural Resources Conservation 

Service PLANTS database (NRCS 2011). The greatest 

number of classifi ed species were categorized as trees (33), 

followed by forb/herbs (23) (Table 8). Of these species, 87 

were native to the United States and 11 were introduced 

(Table 9). The most commonly observed species was red 

maple, which occurred on 89 percent of the plots (Table 

10), followed by blackgum (Nyssa sylvatica), virginia creeper 

(Parthenocissus quinquefolia), and white oak (Quercus alba), 

all of which were observed on 78 percent of the plots. Of 

the 16 most commonly observed species, 15 were of woody 

growth form, and none belonged to the list of 43 target 

invasive plant species. Garlic mustard (Alliaria petiolata) 

and Japanese barberry (Berberis thunbergii) were the most 

common nonnative plant species, each occurring on 33 

percent of the P3 plots (Table 11).

Table 8.—Number of species on Maryland P3 plots by growth habit (NRCS 

2011), 2007-2008

 Forb/herb 23

 Graminoid 6

 Shrub 8

 Shrub, subshrub, vine 4

 Subshrub, shrub 3

 Subshrub, shrub, forb/herb 1

 Tree 33

 Tree, shrub 13

 Tree, shrub, subshrub 1

 Vine 5

 Vine, forb/herb 1

 Vine, shrub 1

 Unclassifi ed 14

 Total 113

 Number of Species or 

Growth Habit Undifferentiated Genera

Table 9.—Number of species on Maryland P3 plots by domestic or foreign 

origin (NRCS 2011), 2007-2008

 Introduced to the U.S. 11 9.7

 Native and introduced to the U.S. 1 0.9

 Native to the U.S. 87 77

 Unclassifi ed 14 12.4

 Number of 

Origin Species Percent

Table 10.—Top 16 identifi able plant species or undifferentiated genera found 

on Maryland P3 plots, the percent of the plots where the species occurred (in 

brackets), and the mean number of all tree seedlings and sapling species per 

acre on the plots, 2007-2008

Red maple 

(Acer rubrum [89]) 990 764

Blackgum 

(Nyssa sylvatica [78]) 910 632

Virginia creeper 

(Parthenocissus quinquefolia [78]) 864 723

White oak 

(Quercus alba [78]) 1,110 809

Roundleaf greenbrier 

(Smilax rotundifolia [67]) 800 662

American holly 

(Ilex opaca [56]) 1,464 1,013

Eastern poison ivy 

(Toxicodendron radicans [56]) 225 255

Sweetgum 

(Liquidambar styracifl ua [56]) 1,464 1,013

White ash 

(Fraxinus americana [56]) 1,330 1,028

American beech 

(Fagus grandifolia [44]) 1,662 1,172

Black cherry 

(Prunus serotina [44]) 319 356

Eastern redcedar 

(Juniperus virginiana [44]) 1,624 1,172

Partridgeberry 

(Mitchella repens [44]) 1,331 806

Sassafras 

(Sassafras albidum [44]) 650 723

Scarlet oak 

(Quercus coccinea [44]) 712 356

Sedge 

(Carex spp. [44]) 1,031 900

 Tree Seedlings Tree Saplings 

Species per acre per acre

On the 46 P2 Invasive plots, 20 of the 43 target invasive 

species were detected. Multifl ora rose (Rosa multifl ora) 

and Japanese honeysuckle (Lonicera japonica) were the 

most commonly recorded species, found on 35 and 33 

percent of the 46 plots, respectively (Table 12). 

Data suggest that many invasive plant species are 

distributed fairly homogeneously across Maryland. For 

example, the occurrence of multifl ora rose and Japanese 
50

FOREST HEALTH

Table 11.—Nonnative plant species found on Maryland P3 plots, the percent of 

the plots where the species occurred (in brackets), and the mean number of all 

tree seedlings and sapling species per acre on the plots

Garlic mustard 

(Alliaria petiolata [33]) 250 200

Japanese barberry 

(Berberis thunbergii [33]) 200 350

Burningbush 

(Euonymus alata [22]) 1,987 1,349

Multifl ora rose 

(Rosa multifl ora [22]) 300 300

Tree of heaven 

(Ailanthus altissima [22]) 300 300

Asian bittersweet 

(Celastrus orbiculata [11]) 450 150

Golden clover 

(Trifolium aureum [11]) 1,550 1,691

Japanese honeysuckle 

(Lonicera japonica [11]) 225 225

Princesstree 

(Paulownia tomentosa [11]) 450 150

Sweet cherry 

(Prunus avium [11]) 450 150

Tall oatgrass 

(Arrhenatherum elatius [11]) 0 450

 Tree Seedlings Tree Saplings 

Species per acre per acre

Table 12.—Invasive species found on Maryland P2 invasive plots, the percent 

of the plots where the species occurred (in brackets), and the mean number of 

all tree seedlings and sapling species per acre on the plots, 2007-2008. Twenty 

of the 43 invasive species FIA monitors were recorded

Multifl ora rose 

(Rosa multifl ora [35]) 1,423 421

Japanese honeysuckle 

(Lonicera japonica [33]) 1,399 473

Garlic mustard 

(Alliaria petiolata [26]) 605 281

Japanese barberry 

(Berberis thunbergii [21]) 290 353

Black locust 

(Robinia pseudoacacia [19]) 492 290

Nepalese browntop 

(Microstegium vimineum [19]) 1,052 285

Tree of heaven 

(Ailanthus altissima [9]) 768 431

Autumn olive 

(Elaeagnus umbellata [7]) 2,474 299

Oriental bittersweet 

(Celastrus orbiculatus [7]) 2,250 299

Morrow’s honeysuckle 

(Lonicera morrowii [5]) 256 384

Norway maple 

(Acer platanoides [5]) 1,231 646

Amur honeysuckle 

(Lonicera maackii [2]) 300 375

Canada thistle 

(Cirsium arvense [2]) 300 375

Common buckthorn 

(Rhamnus cathartica [2]) 0 0

Common reed 

(Phragmites australis [2]) 0 0

Creeping jenny 

(Lysimachia nummularia [2]) 1,574 0

English ivy 

(Hedera helix [2]) 0 0

Princesstree 

(Paulownia tomentosa [2]) 450 150

Siberian elm 

(Ulmus pumila [2]) 5,337 130

Tatarian honeysuckle 

(Lonicera tatarica [2]) 0 0

 Tree Seedlings Tree Saplings 

Species per acre per acre
51

FOREST HEALTH

What this means 

The majority of plants in Maryland are native and 

represent a diverse mix of species of various growth 

forms. Ten percent of the plants sampled were nonnative. 

Some of these nonnative species are listed as invasive 

plants that have the potential to negatively affect the 

native plant community. Invasive plants can physically 

displace native plants by outcompeting them for space 

and other resources, and, like the common buckthorn 

(Rhamnus cathartica), can change soil chemistry and thus 

alter the suitability of a site for native species.

In Maryland, forest managers are concerned about the 

prevalence of invasive species, including multifl ora rose, 

as these shrubs form dense mats that can survive across 

a broad range of light levels ranging from full sun to 

shade. Once established in the forest, multifl ora rose can 

outcompete native vegetation, creating a homogeneous, 

species-poor understory. Seedling and sapling density 

data suggest that areas with more cover of invasives 

generally have lower numbers of tree seedlings and 

saplings than areas with less invasive cover, but one must 

be cautious in drawing conclusions from this data due to 

the small sample size. 

Figure 77.—Presence or absence of Japanese honeysuckle (Lonicera 

japonica) in Maryland observed on P2 invasive plots, 2007-2008.

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 

Percent of Plots 

Number of Invasive Plants per Plot 

Figure 78.—Number of invasive plant species present on each plot for P2 

invasive plots in Maryland, 2007-2008.

Projection: MD State Plane, NAD83. Sources: FIA2007-2008, 

ERSI data and maps 2005. Geographic base data are provided by the

National Atlas of the USA. FIA data and tools are available online at

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: C. Kurtz. May 2011.

honeysuckle on P2 invasive plots is shown in Figures 

76 and 77. Many invasive plant species have similar 

site preferences, such as open, disturbed areas that are 

exposed to seed sources from other nearby populations 

of plants. Figure 78 shows that an invaded plot often has 

more than one invasive species present. 

Figure 76.—Presence or absence of multifl ora rose (Rosa multifl ora) in 

Maryland observed on P2 invasive plots, 2007-2008.

Projection: MD State Plane, NAD83. Sources: FIA2007-2008, 

ERSI data and maps 2005. Geographic base data are provided by the

National Atlas of the USA. FIA data and tools are available online at

http://www.fi a.fs.fed.us/tools-data/ 

Cartography: C. Kurtz. May 2011.

Multifl ora Rose

 Absence

 Presence

Japanese Honeysuckle

 Absence

 Presence
52

FOREST HEALTH

What this means 

Ash trees make up a small but important component of 

Maryland’s forested landscape. Found in both upland 

and riparian sites and planted in urban settings, ash 

contributes to the structural and ecological diversity of the 

State. Since the introduction of EAB to North America, 

millions of ash trees across the eastern U.S. have been 

killed or removed. Ash mortality and the identifi cation 

of new EAB infestations will have a large impact on 

the future makeup of Maryland’s forests. Continued 

monitoring of ash resources will help to identify the 

long-term impacts of EAB within the State. Additionally, 

efforts to slow the spread of EAB will be enhanced by 

discontinuing the transportation of fi rewood.

Emerald Ash Borer

Background

The emerald ash borer (Agrilus planipennis) (EAB) is a 

wood-boring beetle native to Asia. In North America, 

EAB has been identifi ed as an invasive pest of ash 

species (Poland and McCullough 2006). Trees and 

branches as small as 1-inch diameter have been attacked, 

and while stressed trees may be preferred, healthy trees 

are also susceptible (Cappaert et al. 2005). In areas with 

a high density of EAB, tree mortality generally occurs 1 

to 2 years after infestation for small trees and after 3 to 

4 years for large trees (Poland and McCullough 2006). 

The spread of EAB has been facilitated by human 

transportation of infested ash material. 

EAB was fi rst introduced to Maryland’s Prince George’s 

County from Michigan via infested nursery stock in 

2003 (Sargent et al. 2009). Infested trees were later 

found near the nursery, so nursery stock and all ash trees 

within one-half mile of the site were destroyed. EAB 

was not detected again in Maryland until 2006 (Sargent 

et al. 2009). 

What we found

Ash is distributed across Maryland with major 

concentrations occurring in the central and western 

portions of the State (Fig. 79). An estimated 14.2 

million ash trees (greater than 1-inch in diameter) are 

found on forest land, which amounts to 130.4 million 

cubic feet of volume. White ash is the most dominant 

ash species, making up 68 percent of the total. Present 

on nearly 81,000 acres, or 4 percent of forest land, 

ash is rarely the most abundant species. Ash generally 

represents less than 25 percent of total live-tree basal 

area (Fig. 80).

Figure 80.—Presence of ash on forest land as a percentage of stand basal area 

(BA) (expressed as ash BA per acre/total live BA per acre), Maryland, 2008.

0

500

1,000

1,500

2,000

2,500

No ash 0.1 - 25.0 25.1 - 50.0 50.1 - 75.0 

Forest Land (1,000 acres) 

Ash BA per Acre/Total Live BA per Acre (percent) 

Figure 79.—Distribution of ash on forest land, Maryland, 2008.

Projection: MD State Plane, NAD83. Sources: FIA 2008. Geographic 

base data are provided by the National Atlas of the USA. FIA data 

and tools are available online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: S. Crocker. May 2011. Procesing note: This map was 

produced by linking plot data to MODIS satellite pixels (250 m) using 

gradient nearest neighbor techniques. The resulting image was 

resampled to 500 m pixels.

 11 - 60

 6 - 10 

 2 - 5

 Less than 2

Basal Area of Ash

(ft2

/acre)
53

FOREST HEALTH

Asian Longhorned Beetle

Background

The Asian longhorned beetle (Anoplophora glabripennis) 

(ALB) is an exotic wood-boring insect that attacks a 

variety of hardwood species found in Maryland. Larval 

activity girdles the trunk, resulting in tree mortality 

(USDA Forest Service 2008). ALB was fi rst identifi ed in 

New York City in 1996, has subsequently been found 

in Chicago, IL; two cities in northern New Jersey; and 

in the cities of Boston and Worcester, MA (APHIS 

2010). Though not currently found in Maryland, 

the transportation of infested packing materials and 

wood products makes ALB a threat to statewide forest 

resources. ALB will attack a number of hardwood 

species. However, maple (most favored), birch, willow, 

and elm are the preferred hosts. Occasional hosts 

include poplar and ash (APHIS 2010). 

What we found

Twenty-two percent of trees on Maryland’s forest land, 

or 327.2 million trees, are susceptible to ALB (Fig. 81). 

Of this group, maples are the most dominant species 

(93 percent), followed by ash and elm. Susceptible host 

species account for 1.0 billion cubic feet of total live-tree 

volume on forest land. Present throughout the State, 

these species are most abundant in Garrett, Allegany, 

Dorchester Counties (Fig. 82). 

Projection: MD State Plane, NAD83. Sources: FIA 2008. Geographic 

base data are provided by the National Atlas of the USA. FIA data 

and tools are available online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: S. Crocker. May 2011. 

31 - 55 

16 - 30 

5 -15 

Less than 5

Number of Trees 

Susceptible to ALB

(millions of trees)

Figure 82.—Distribution of ALB-susceptible trees by county, Maryland, 2008.

Figure 81.—Number of ALB-susceptible trees by host preference and species 

group, Maryland, 2008.

0

50

100

150

200

250

300

350

Birch Elm Maple Willow Ash Mimosa Poplar 

Preferred host Occasional host 

Number of Trees (millions) 

Host Species Group 

What this means

ALB has caused major economic losses in China, where 

it is a pest of urban trees and trees in windbreaks and 

plantations (Haack et al. 2010, MacLeod et al. 2002). 

Since its introduction to the United States, ALB has been 

a signifi cant source of urban tree mortality. However, 

with a wide range of susceptible host species, this insect 

could also have a substantial impact on hardwood forests 

across Maryland. 

Hemlock Woolly Adelgid

Background

White ‘wool’ on the branches of eastern hemlock (Tsuga 

canadensis) is a telltale sign of a hemlock woolly adelgid 

(HWA) (Adelges tsugae) infestation. A tiny, sap-feeding 

insect from Asia, HWA was fi rst reported in Virginia in 

1951 (USDA Forest Service 2010). By 1986, the adelgid 

had spread north to Maryland. In many parts of eastern 

hemlock’s range, tree decline and mortality generally 

occurs within 4 to 10 years of infestation (USDA Forest 

Service 2010). The rate of tree mortality increases if 

infested trees also experience drought, attack by secondary 

insects and diseases, or other environmental stresses.
54

FOREST HEALTH

What we found

Hemlock is found in the Piedmont and Appalachian 

regions of Maryland (Fig. 83). The highest density of 

hemlock occurs in western Maryland’s Garrett County. 

There are an estimated 2.8 million hemlock trees (greater 

than 1-inch diameter) on forest land, which comprise 

25.3 million cubic feet of live volume. Hemlock makes 

up 2 percent of total conifer growing-stock volume. 

However, with 807,000 cubic feet per year of average 

annual mortality, it accounts for 9 percent of conifer 

mortality. When mortality is divided by volume, the rate 

of hemlock mortality is 4.8 percent. In comparison to 

other conifers, hemlock has the second highest mortality 

rate in the State. Overall, hemlock mortality has been 

increasing since 1986 (Fig. 84). 

What this means

Hemlock represents a unique and important part of 

Maryland’s forest resource. The species is found in cool, 

moist ravines with well drained soils; on low ridges; and 

along lakeshores (Harlow et al. 1996); its disappearance 

could affect soil stability and quality. Hemlock occurs 

in both pure and mixed stands (Harlow et al. 1996) and 

its mortality can impact a variety of species. Continued 

monitoring of the hemlock resource will help to quantify 

the effects of HWA in Maryland. 

Figure 83.—Distribution of hemlock on forest land, Maryland, 2008.

Projection: MD State Plane, NAD83. Sources: FIA 2008. Geographic 

base data are provided by the National Atlas of the USA. FIA data 

and tools are available online at http://www.fi a.fs.fed.us/tools-data/ 

Cartography: S. Crocker. May 2011. Procesing note: This map was 

produced by linking plot data to MODIS satellite pixels (250 m) using 

gradient nearest neighbor techniques. The resulting image was 

resampled to 500 m pixels.

11 - 45

6 - 10

2 - 5

Less than 2

Basal Area of Hemlock 

(ft2

/acre)

Hemlock

All conifers 

All species 

0

1

2

3

4

5

6

1986 1999 2008 

 Mortality (percent) 

Figure 84.—Average annual mortality of hemlock growing stock as a percent 

of the total volume of growing stock on timberland, by species and inventory 

year, Maryland, 2008.
55

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DVD Contents

Maryland’s Forests 2008 (PDF)

Maryland’s Forests: Statistics, Methods and Quality

Assurance (PDF)

Maryland Inventory Database (CSV fi le folder)

Maryland Inventory Database (Access fi le)

Field guides that describe inventory procedures (PDF)

Database User Guides (PDF)
Lister, T.W.; Perdue, J.L.; Barnett, C.J.; Butler, B.J.; Crocker, S.J.; Domke, G.M.; Griffi th, D.; Hatfi eld, M.A.; 

Kurtz, C.M.; Lister, A.J.; Morin, R.S.; Moser, W.K.; Nelson, M.D.; Perry, C.H.; Piva, R.J.; Riemann, R.; 

Widmann, R.; Woodall, C.W. 2011. Maryland’s Forests 2008. Resour. Bull. NRS-58. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. 60 p. [DVD included].

The fi rst full annual inventory of Maryland’s forests reports approximately 2.5 million acres of forest 

land, which covers 40 percent of the State’s land area and with a total volume of more than 2,100 cubic 

feet per acre. Nineteen percent of the growing-stock volume is yellow-poplar, followed by red maple 

(13 percent) and loblolly pine (10 percent). All species of oaks combined account for 26 percent of the 

total growing-stock volume. Red maple is the most abundant species in terms of number of trees. There 

were about 5.9 billion cubic feet of growing-stock volume in 2008, and the average annual growth rate of 

volume has been about 2 percent. Additional information on forest attributes, land-use change, carbon, 

timber products, and forest health is presented in this report. A DVD included in the report provides 

information on sampling techniques, estimation procedures, tables of population estimates, raw data, 

a data summarization tool, and a glossary.

KEY WORDS: Forest resources, forest health, forest inventory, Maryland

Maryland’s Forests 2008

Statistics, Methods, 

and Quality Assurance

 United States 

Department of 

Agriculture

Forest Service

 Resource Bulletin 

NRS-58
http://www.nrs.fs.fed.us