United States Department of Agriculture 

Forest Ecosystem 

Health Indicators

Forest Service FS-1151 March 2020
CONTRIBUTING AUTHORS

KaDonna C. Randolph Research Mathematical Statistician Southern Research Station

Forest Inventory and Analysis

Knoxville, TN 37919

Randall S. Morin Research Forester Northern Research Station

Forest Inventory and Analysis

Newtown Square, PA 19073

Kerry Dooley Forester Southern Research Station

Forest Inventory and Analysis

Knoxville, TN 37919

Mark D. Nelson Research Forester Northern Research Station

Forest Inventory and Analysis

St. Paul, MN 55108

Sarah Jovan Research Ecologist Pacific Northwest Research Station

Portland, OR 97205

Christopher W. Woodall Research Forester Northern Research Station

Forest Inventory and Analysis

Durham, NH 03824

Bethany K. Schulz Emeritus Scientist

Research Ecologist

Pacific Northwest Research Station

Forest Inventory and Analysis

Anchorage, AK 99501

Charles H. Perry Research Soil Scientist Northern Research Station

Forest Inventory and Analysis

St. Paul, MN 55108

Cassandra M. Kurtz Forester Northern Research Station

Forest Inventory and Analysis

St. Paul, MN 55108

Sonja N. Oswalt Forest Resource Analyst Southern Research Station

Forest Inventory and Analysis

Knoxville, TN 37919

William H. McWilliams Research Forester Northern Research Station

Forest Inventory and Analysis

Newtown Square, PA 19073

(No longer with the Northern 

Research Station)

Rachel Riemann Research Forester/Geographer Northern Research Station

Forest Inventory and Analysis

Troy, NY 12180
Randall S. Morin, Compiler

USDA Forest Service

Northern Research Station

11 Campus Boulevard

Newtown Square, PA 19073

Randall.S.Morin@USDA.gov

CONTENTS

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Clients and Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Crown Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Tree Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Tree Mortality and Standing Dead Trees . . . . . . . . . . . . . . . . . . 7

Lichen Communities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Down Woody Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Vegetation Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Soil Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Invasive Plant Species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Regeneration and Browse Impact . . . . . . . . . . . . . . . . . . . . . . . . 18

Fragmentation, Urbanization, 

and Landscape Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Beaver damage. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

(Photo by Sjana Schanning, USDA Forest Service)

ONLINE STORY MAP:

https://usfs.maps.arcgis.com/apps/MapJournal/index.html?appid=a434a8d7b3d447c8a747efb4fd22d742#

Forest Ecosystem Health Indicators 1
INTRODUCTION

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA)

Program is the Nation’s continuous forest census. Since 1930, we have collected, analyzed, and reported 

information on the status and trends of America’s forests: how much forest exists, where it exists, who owns 

it, and how it is changing — growing, dying, being harvested, or converted to and from forest land uses. In 

response to widening customer interests, the FIA developed a program that was implemented in the same 

manner on all U.S. forest lands. This included sampling an extended suite of forest health indicators. Many 

of these indicators were developed and initially measured by the Forest Health Monitoring (FHM) Program 

in the 1990s. In 1999, they were transferred to FIA and now are a subset of the FIA inventory.

Originally, the health indicators were sampled on 1 of every 16 standard FIA plots, but this design faced 

budget and logistical constraints. In 2012, FIA redesigned the health program as a flexible system with 

spatial and temporal intensities that are adaptable to meet budgetary constraints, client needs, and regional 

issues. A minimum national set of protocols are “core” to the forest/ecosystem health indicator program. 

These health indicators are collected at intensities ranging from a minimum of approximately 7 percent 

up to 25 percent of the standard plot grid. In addition, the Vegetation Profile and Down Woody Materials 

indicators are sampled on all plots in the Western United States. The FIA indicators discussed in this 

publication are:

 Crown Condition (KaDonna C. Randolph)

 Tree Damage (Randall S. Morin and Kerry Dooley)

 Tree Mortality and Standing Dead Trees (Randall S. Morin and Mark D. Nelson)

 Lichen Communities (Sarah Jovan) (adjunct inventory conducted by National Forest Systems in some 

regions; retired as a national core indicator)

 Down Woody Materials (Christopher W. Woodall)

 Vegetation Profile (Bethany K. Schulz)

 Soil Quality (Charles H. Perry)

 Nonnative Invasive Plants (Cassandra M. Kurtz and Sonja N. Oswalt)

 Regeneration and Browse Impact (William H. McWilliams)

 Fragmentation and Landscape Context (Rachel Riemann)

The Ozone Injury indicator was retired around 2010, but data from 1994 to 2010 are available in the FIA 

database. Sampling and estimation procedures are documented in Smith et al. (2007).

The purpose of this publication is to describe these health indicators by providing:

 Background information about how and why the indicator was developed

 Examples of the data, products, and publications available

 The direction of future research and development

2 Forest Ecosystem Health Indicators
CLIENTS AND PRODUCTS

The FIA Program has a diverse and growing 

set of customers who are interested not only in 

reports and analyses produced by FIA but also in 

using the FIA data. Congress and State legislators 

have long used FIA information as a basis for 

formulating sound forest policy. State forestry 

and other agencies depend on FIA monitoring 

for long-term decision making and policy 

formulation. Forest industry, nongovernmental 

organizations, and a wide range of private 

consultants use FIA information for management 

decisions and planning. 

Government and academic researchers use FIA data 

as a basis for detecting science needs and directing 

scarce funds to priority research. Land managers 

at all levels rely on FIA data for a strategic look at 

forest resources and as a basis for strategic-scale 

forest planning. These users have expressed 

interest in a broader suite of FIA measures that 

includes indicators of forest health. Information 

about a diverse array of forest health attributes, 

beyond trees, serve as indicators of complex forest 

ecosystem processes across the United States.

FIA also contributes data and analyses to a variety 

of national and global assessments, including many 

of the Criteria and Indicators of Sustainability for 

reporting under the Montreal Process. FIA data 

are key for producing the reports required by the 

Resource Planning Act (RPA) and are increasingly 

being used to support regional resource assessments 

that are a basis for forest planning.

Scientists and policymakers employ FIA data 

about forest soils, down woody materials, and 

tree biomass to estimate carbon budgets and to 

model the potential for carbon sequestration 

under different management scenarios. The 

fire management community identifies areas at 

highest risk of catastrophic fire and opportunities 

for preventive treatments using the forest 

structure, understory vegetation, and down 

woody debris data. Land managers, equipped 

with data on understory vegetation, track 

invasive species, assess regeneration security, 

and quantify the impacts of browsing. This fills 

critical information gaps for restoring healthy 

young forest habitat that sets the trajectory for 

future forests following disturbance. Forest health 

specialists rely on information about tree condition 

to quantify the occurrence and impacts of abiotic 

and biotic forest disturbances. Surveys of lichen 

communities in some regions of the United States 

are used to provide information on human health, 

air quality, climate, and biodiversity. Indicators 

of forest fragmentation and urbanization help 

policymakers understand trends in the spatial 

distribution of forest land and proximity of forest 

land to urban development. Figure 1. Forest Inventory and Analysis Program plot design for forest 

health indicators.

Forest Ecosystem Health Indicators 3
CROWN CONDITION

KaDonna C. Randolph • Research Mathematical Statistician • Southern Research Station

BACKGROUND

The crown condition indicator describes 

the amount, condition, and distribution of 

foliage, branches, and growing tips of trees. 

In addition to being aesthetically pleasing, 

tree crowns provide shade, temperature and 

wind moderation, and food and habitat for 

many organisms. They also mitigate erosion 

by intercepting rainfall and provide a source of 

fuel for wildfires. Healthy, full crowns suggest 

carbon is being stored, the tree is growing, and 

there are no serious impacts from pathogens, 

air pollutants, or insects. When FIA first 

implemented the indicator, five components 

of crown condition were assessed: live crown 

ratio, crown density, foliage transparency, crown 

dieback, and crown diameter. Schomaker et al. 

(2007) thoroughly describe the methods used to 

assess crown condition. Because live crown ratio 

and crown dieback have proven to be the most 

broadly applicable components, currently these 

are the only crown variables collected as part of 

the core program. 

PRODUCTS AND PUBLICATIONS

Tree crowns reflect the effects of forest stressors 

such as insects, pathogens, and too much or 

too little water. As such, the crown condition 

indicator provides a good general indicator of 

tree health and can be related to tree growth and 

survivorship. Crown assessments can also be used 

to describe forest characteristics such as potential 

fire risk and wildlife habitat. FIA summarizes 

crown condition data approximately every 5 

years at the State, regional, and national levels. 

In addition, independent researchers conducting 

individual studies employ the crown condition 

assessment methods implemented by FIA. 

Examples of published studies that utilize FIA 

crown condition data or the indicator assessment 

methods include: 

 Predicting tree mortality in the Eastern United 

States (Morin et al. 2012)

 Assessing eastern hemlock vulnerability to 

hemlock woolly adelgid in West Virginia and 

Pennsylvania (Fajvan and Wood 2010)

 Evaluating oak decline and mortality in the 

Ozark Highlands (Crosby et al. 2012)

 Assessing the risk of crown fire hazard in 

Washington (Campbell et al. 2010)

RESEARCH AND DEVELOPMENT

Previous studies have established expected crown 

conditions for typically healthy trees in forested 

settings. Continued assessment of tree crowns 

under shifting climatic patterns will reveal if the 

distribution of crown conditions is also shifting. 

Future studies may consider how climate-related 

Figure 2. Live crown ratio is the length of the tree with branches (X) 

divided by the total tree length (Y). Crown dieback is the death of sunexposed twigs in the upper and outermost parts of the crown (areas within 

the dashed lines). (Photo by KaDonna C. Randolph, USDA Forest Service)

4 Forest Ecosystem Health Indicators
changes in crown condition, if they do occur, 

affect tree vitality, forest structure, and other 

characteristics of interest, e.g., wildfire fuels. As 

FIA expands to collect data on trees in urban 

areas, assessments of crown condition will be 

an integral part of accounting the economic and 

environmental benefits of trees and understanding 

the interactions between natural environments and 

human health. 

Year of EAB discovery

Figure 3. Average crown dieback by duration of emerald ash borer (EAB) 

infestation for ash trees assessed in the Eastern United States during 2011–

2015. Bars around the average represent one standard error. Adapted from 

Randolph (2018). (Data source: Forest Inventory and Analysis Program)

TREE DAMAGE

Randall S. Morin • Research Forester • Northern Research Station and 

Kerry Dooley • Forester • Southern Research Station

BACKGROUND

The tree damage indicator identifies the presence 

and type of damages from various causes. This 

indicator is collected on all forested portions of all 

field-measured plots and is taken at the individual 

live tree level, as opposed to plot or stand level. 

This allows for earlier identification of forest 

health problems, as collection will happen before 

tree mortality or stand-level effects are reached.

Previous FIA surveys collected information 

on damages various ways, but a new national 

methodology implemented in 2013 provided 

a means of gathering specific data on types of 

damage. On each tree, up to 3 damages may be 

selected from 24 categories derived from a list 

used by Forest Service forest health programs. 

Examples include “boring insects,” “root/

butt diseases,” “wild animals,” and “unknown 

damage.” Combined with data from FIA and 

other programs, this indicator can contribute to 

detailed estimations of forest health issues. 

PRODUCTS AND PUBLICATIONS

Collection of this data set is nearing completion 

nationally, and therefore new analyses for 

national products are anticipated. Some products 

that used past iterations of damage or closely 

related data give an indication of how these new 

data will be used:

 Assessment of damage from catastrophic 

weather events (Nelson and Moser 2007, 

Randolph 2015)

 Presence, severity, and hazard reports of regional 

pest activity in association with ancillary data 

sets (Lockman, Bush, and Barber 2016, Morin et 

al. 2016)

 Tree damage chapters in 5-year State reports 

(Meneguzzo et al. 2018, Lister et al. 2018)

As data sets are completed, they will become part of 

standard 5-year reports at the State and national levels.

Absent 2011–2015 2006–2010 Pre-2006

Forest Ecosystem Health Indicators 5
Sugar Maple Insect 

Damage by County

Percent of Sugar 

Maple Trees with 

Insect Damage

> 40 to 100

> 15 to 40

> 10 to 15

> 3 to 10

0 to 3

No Value

Figure 4. Map of the percentage of sugar maple trees with observed insect damage by county for States in the Northern United 

States, 2013 (Morin et al. 2016; story map version).

RESEARCH AND DEVELOPMENT

Tree damage data are available from across the 

country, and the national data from the updated 

protocols will be completed in several years. 

Future work will focus on testing the repeatability 

of the damage protocols and integrating analysis 

and tools with other ancillary data sets. For 

example, tree damage data from FIA can help 

to quantify the impacts of disturbances such as 

invasive forest pests or extreme weather events.

Figure 5. Nectria fruiting bodies on American beech. (Photo courtesy 

of Elizabeth Morin)

6 Forest Ecosystem Health Indicators
TREE MORTALITY 

AND STANDING DEAD TREES

Randall S. Morin • Research Forester • Northern Research Station and 

Mark D. Nelson • Research Forester • Northern Research Station

BACKGROUND

The tree mortality indicator shows the number, 

size, and volume of trees that have died since the 

previous measurement on an FIA plot. Those 

trees also remain part of the inventory as dead 

trees until they are no longer standing. Standing 

dead trees are also sampled on newly installed 

FIA plots. Mortality and dead trees provide 

information on whether changes in abiotic or 

biotic stressors or stand development are creating 

conditions less favorable for tree growth and 

survival. Since the implementation of the annual 

inventory in 1999, the amount of remeasurement 

data available for tree mortality estimation has 

increased substantially.

Mortality is an essential part of all healthy 

forest ecosystems. It contributes to ecosystem 

functioning and diversity by creating dead 

material for nutrient recycling, producing openings 

that result in mosaics of species and ages, and 

providing habitat for wildlife. Mortality may also 

reduce productivity of forests being managed for 

wood production and increase risk of wildfire. 

Changes in the rates and amounts of mortality 

require close scrutiny to identify whether or not 

those variations indicate the presence of a forest 

health issue. Analyses of affected species, their 

ages, disturbance history in the area, and the cause 

of mortality offer essential information for land 

managers and policymakers.

PRODUCTS AND PUBLICATIONS

The tree mortality indicator quantifies a key 

ecological process in forests and can be used 

to estimate a variety of important metrics. For 

Figure 6. Tree 

mortality expressed 

as the ratio of annual 

mortality volume to 

gross annual volume 

growth by ecoregion 

section. (Adapted from 

Ambrose 2018)

MRATIO

0.0775 – 0.3000

0.300001 – 0.6000

0.600001 – 0.9000

0.800001 – 2.0000

2.000001 – 4.2151

insufficient or no data

 State boundary

Forest Ecosystem Health Indicators 7
example, tree mortality can provide information 

about the impacts of biotic and abiotic 

disturbances, habitat characteristics for wildlife 

species that depend on dead trees, fuel loading and 

fire risk, carbon cycling patterns, and sustainability. 

FIA data provide standardized outputs at the national 

level in RPA and FHM reports and at the State level 

in 5-year reports to quantify the status and trends in 

tree mortality and standing dead trees. Some examples 

of published studies that utilize the tree mortality 

indicator include:

 Climate and weather impact assessments (Shaw 

et al. 2005)

 Contribution of standing dead trees and tree 

mortality to carbon stocks and dynamics 

(Woodall et al. 2015, Domke et al. 2013, Fei et 

al. 2019)

 Quantification of native and invasive pest 

impacts (Thompson 2017, Morin and Liebhold 

2015)

 Assessments of fire effects and risk (Shaw et al. 

2017, Whittier and Gray 2016)

RESEARCH AND DEVELOPMENT

Remeasurement data in the FIA database allows 

mortality and standing dead trees to be estimated 

across the country. Integrating these findings with 

other data sources enables researchers to quantify 

the impacts of landscape-level disturbances that 

cause mortality. Most research on mortality and 

standing dead trees focuses on working with 

partners to use these data for contemporary 

forest health issues and to develop online tools 

for analysis and reporting. For example, FIA and 

Forest Health Monitoring survey data have been 

integrated to assess insect and disease impacts to 

characterize wildlife habitat for species dependent 

on snags and den trees.

Figure 7. Hemlock woolly 

adelgid-related hemlock 

mortality in Great Smoky 

Mountains National Park.

(Photo by Songlin Fei, Purdue 

University)

8 Forest Ecosystem Health Indicators
LICHEN COMMUNITIES

Sarah Jovan • Research Ecologist • Pacific Northwest Research Station

BACKGROUND

The national lichen community indicator, begun 

in 1992, is the most extensive and detailed lichenmonitoring program in the world, generating more 

than 5,500 standardized surveys of epiphytic (treedwelling) lichen communities across the United 

States. Federal land managers and researchers use 

these surveys to provide information on air quality, 

climate, biodiversity, and lichen floristics in forests. 

A related ground layer indicator, developed in 

2014, focuses on ground-dwelling lichens and 

moss, providing landscape-scale estimates of 

cover, biomass, carbon, and nitrogen in functional 

groups (e.g., peat moss, wildlife forage lichens, 

nitrogen-fixers). Moss and lichen mats, abundant 

or dominant in some forests, play well-known 

ecological roles in hydrology, carbon storage, 

wildlife migration patterns, and soil stabilization 

and chemistry. Lacking roots, lichens and moss 

derive all nutrition and water from the atmosphere. 

This makes them highly sensitive to air pollutants, 

climate changes, and shifts in habitat conditions 

that affect light, microclimate, and nutrient 

availability. Currently, FIA samples this indicator 

only in the Pacific Northwest, but the program is 

poised to implement this indicator nationally when 

and if funding becomes available.

PRODUCTS AND PUBLICATIONS

The two Indicators have been used in more than 75 

products. The most commonly used metrics include:

 Air quality: The use of lichen communities as 

“canaries in the coal mine” for air quality studies 

dates back to 1866. Clients use the Community 

Figure 8. Map showing all FIA lichen survey sites. (Data source: Forest Inventory 

and Analysis; map created by Joel Thompson, USDA Forest Service)

Plot Type

 FIA - on grid

 FIA - off grid

 NFS

Forest Ecosystem Health Indicators 9
Indicator to inform air quality policy (e.g., EPA 

Integrated Science Assessments 2008, 2017), 

provide managers with empirical guidelines for 

air-quality monitoring in protected areas (i.e., 

”Critical Loads”; Fenn et al. 2008, 2010; Pardo 

et al. 2011), and supplement widely spaced 

instrument monitoring networks at a variety of 

spatial scales (e.g., Jovan and McCune 2005, 

Will-Wolf et al. 2015).

 Climate: The community indicator can be 

employed to model species’ climate tolerances 

(Smith et al. 2017) and to delineate “bellwether” 

zones where climate change is expected to have 

particularly severe effects (Root et al. 2014). 

These, then, provide the building blocks for 

simple, repeatable metrics for tracking climate 

change.

 Carbon: The ground layer indicator accounts 

for a carbon pool not otherwise measured in the 

forest inventory. Lichen and moss ground mats 

can be more than 11.8 in (30 cm) thick and, 

under the right conditions, sit atop extensive 

carbon deposits (i.e., peat; Smith et al. 2015). 

RESEARCH AND DEVELOPMENT

Three research arcs are underway to expand the 

scope or foundation for indicator applications. 

 A pilot for the lichen elemental indicator, a 

very low-cost tool for monitoring air quality 

on the FIA grid by measuring the amounts of 

pollutants accumulating inside lichens, was 

recently completed.

 A 14-month calibration study underway in 

Portland, OR, compares heavy metals in moss 

to levels measured in air and precipitation. This 

study provides the foundation for the lichen 

elemental indicator, as well as guiding pilot work 

using that technique for fine-scaled pollution 

mapping in urban areas. 

 Differentiating climate change effects on lichens 

from other possible drivers is tricky. Ongoing 

experimental work to inform lichen-climate 

metrics includes tracking lichens in climatewarming enclosures (Spruce and Peatland 

Responses Under Changing Environments 

study) and using cameras to track lichen growth 

and recruitment in relation to weather patterns 

(Epiphytic Lichen Observation Network study).

Figure 9. Evernia prunastri

(antlered perfume lichen) 

growing in clean air (left – 

photo by Richard Droker) and 

polluted air (right – photo by 

Sarah Jovan, USDA Forest 

Service). The convoluted 

thallus on the right is called a 

“pollution morph.”

10 Forest Ecosystem Health Indicators
DOWN WOODY MATERIALS

Christopher W. Woodall • Research Forester • Northern Research Station

BACKGROUND

The down woody materials (DWM) indicator 

estimates the amount and condition of dead and 

downed woody material across all U.S. forests. 

Down woody materials can be delineated as detrital 

components of forest ecosystems, including fallen 

twigs and small branches (fine woody debris) and 

fallen tree stems and large branches (coarse woody 

debris). Fine woody debris is less than 3 inches in 

diameter at the point of intersection with a sampling 

transects; coarse woody debris is 3 inches or larger. 

Fine woody debris is further divided into three size 

classes that align with fire behavior model inputs. 

In addition to size, the species and decay class of 

coarse woody debris is measured for the purpose 

of biomass and carbon estimation. 

As coarse woody debris can sometimes be 

assembled into piles during harvest operations, 

there are sampling protocols for residue piles. The 

depth of duff and litter is sampled at the end of 

each sampling transect as an indicator of surface 

fuel loadings. Duff is highly decomposed forest 

biomass to the point of being indistinguishable 

as to its origin. In contrast, litter can be identified 

as leaf material or fractured woody material not 

included in the fine woody debris population. 

Down woody material was sampled across most 

States from 2002 to 2011. Measurements (and 

remeasurements) continued in 2012 using updated 

sample protocols across all States at a greater 

sampling intensity.

Figure 10. Locations of 

down woody material 

inventory plots, 

2012–2016, are aligned 

with the distribution 

of forest across the 

United States. (Map by

Dale Gormanson)

Forest Ecosystem Health Indicators 11
PRODUCTS AND PUBLICATIONS

The quantity and condition of DWM is emerging 

as a major factor governing forest ecosystem 

processes such as carbon cycling, fire behavior, 

and tree regeneration. Downed dead wood 

plays a central role in many forest ecosystem 

functions, including wildlife habitat, biodiversity of 

deadwood-dependent organisms, tree regeneration, 

wildfire risk and behavior, nutrient cycles, and 

carbon stocks and cycling. Downed woody material 

data are used to inform National Greenhouse 

Gas Inventories and, when coupled with live tree 

inventory data, they provide a robust quantification 

of forest changes over time. As global change is 

projected to increase the frequency and intensity of 

natural disturbances that cause tree mortality and 

hence create DWM (e.g., invasive pests, droughts, 

windstorms, wildfires), we can expect expanded 

interest and use of DWM data sets to address 

wildfire risks, forest sustainability, and carbon 

estimation and modeling.

Some examples of published studies using the 

DWM indicator include:

 National analysis of dead wood biomass and 

volume (Woodall et al. 2013)

 Carbon stocks and flux associated with downed 

and dead wood (Woodall et al. 2008, Domke et 

al. 2013, Woodall et al. 2015)

 Models of dead wood residence time in forest 

ecosystems (Russell et al. 2013, Russell et al. 2014)

 Relationships between live and downed dead tree 

attributes (Woodall and Westfall 2009, Garbarino 

et al. 2015)

 Fuel loading and fire hazard assessments 

(Woodall and Nagel 2007)

RESEARCH AND DEVELOPMENT

Refinements of the DWM indicator continue, with 

focus on improving the estimation procedures 

associated with deriving biomass and carbon 

attributes from dead wood transect sampling (e.g., 

Harmon et al. 2013), along with assessing sources 

of uncertainty (Campbell et al., in press). Given 

the DWM indicator refinements implemented 

in 2012 to gain a greater sample intensity across 

the Nation, work continues on documenting the 

changes to the sampling and estimation procedures 

and associated databases for the public (Woodall et 

al., in review). Prior work incorporating the DWM 

indicator data into the National Greenhouse 

Inventory focused on calibrating past models 

to align with DWM indicator carbon estimates. 

Current research is exploring ways to adapt soil 

carbon modeling techniques (Domke et al. 2017) 

to the DWM indicator. Emerging work is focused 

on the creation of low-cost fuel moisture sensors 

that may be deployed at a low sample intensity to 

inform real-time assessments of fire hazards across 

the national network of DWM plots.

Figure 11. Snail on a 

downed log. (Photo

by Christopher W.

Woodall, USDA 

Forest Service)

12 Forest Ecosystem Health Indicators
VEGETATION PROFILE

Bethany K. Schulz • Emeritus Scientist Research Ecologist • Pacific Northwest Research Station

BACKGROUND

The Vegetation Profile assesses all vascular 

vegetation to record the arrangement of trees, 

shrubs, forbs, and grasses. Additional levels 

of detail provide information about the most 

abundant species in each growth habit; up to four 

species of large grasses, forbs, shrubs, small trees 

(trees less than 5 inches in diameter) and large 

trees, if they are present with a canopy cover of 

at least 3 percent of the subplot area (Western 

United States only). This is a simplified version 

of the earlier Vegetation Structure and Diversity 

Indicator, which made a complete census of all 

vascular plant species present on a small subset 

of all FIA plots. The Vegetation Profile, with 

species information, is collected on all standard 

inventory plots in the western regions. However, 

in the eastern regions, only a rapid assessment is 

performed and sampling is restricted to a small 

proportion of plots (approximately 18 percent). 

The total of all vegetation growth is important 

when considering the health and range of 

ecological services provided by forests. The 

structure of vegetation can indicate suitability 

for wildlife habitat, the components of fuels in 

wildfire situations, or potential competition for 

reforestation efforts. Information on the most 

abundant species can further define the quality, 

presence of forage species, species that will spread 

or suppress fire, known tree seedling competitors, 

and identify serious infestations of invasive 

plant species. Structure and species information 

better describe the vegetation community with 

more detail than tree data alone. This helps us 

understand the distribution and diversity of the 

forest communities inventoried over time. 

Species per 1/24 acre 

subplot; plot averages

 1.67 – 14

 14 – 21.75

 21.76 – 29.33

 29.34 – 38.5

 38.51 – 72 Figure 12. Average species richness for subplots, 2001 through 2004. (Adapted from Schulz 2011)

Forest Ecosystem Health Indicators 13
PRODUCTS AND PUBLICATIONS

Vegetation structure and composition data 

quantify key components in forests and can 

be used to assess vegetation diversity in terms 

of native and nonnative species richness and 

distribution, physical arrangement of growth habit 

canopy cover, and dominant species by forest type. 

To date, products include:

 Describing how to collect and analyze vegetation 

indicator data (Schulz et al. 2009, Schulz 2016)

 Describing vegetation diversity (Schulz 2011)

 Quantifying distribution of introduced species 

(Schulz and Gray 2013)

 Quantifying biomass contributions of understory 

species (Russell et al. 2014)

 Assessing impacts of air pollutants on forest 

understory diversity (Simkin et al. 2016, Clark et 

al. 2019)

 Resource reports (Barrett and Christensen 2011, 

Pattison et al. 2018)

RESEARCH AND DEVELOPMENT 

Vegetation often reflects impacts of biotic and 

abiotic disturbances, habitat characteristics for 

many wildlife species, fuel loading and fire risk, 

and carbon cycling patterns. The more detailed 

Vegetation Indicator data are still in demand for 

research into patterns of species richness and 

species distribution (Simkin et al. 2016, Clark 

et al. 2019). The current Vegetation Profile is 

a slight modification of what western regions 

have collected in the past: most abundant species 

and cover by growth habit on all plots. As new 

plot data are acquired with remeasurement, 

assessments of changes in species dominance 

and growth habit structure will be possible. These 

data are also being incorporated with other 

FIA data into revisions of national programs 

including LANDFIRE’s modeling efforts and the 

National Vegetation Classification. Research to 

improve estimations of biomass contributions of 

non-tally tree growth forms is ongoing.

Additionally, options for collecting more detailed 

species information with the Vegetation Profile 

(e.g., full species census on one subplot) have 

been tested and used in Alaska (Pattison et al. 

2018). This option allows for assessments of 

species richness.

Figure 13. An FIA field crew 

member navigates the dense 

understory on Kuiu Island in 

southeast Alaska. Devil’s club 

(Oplopanax horridus) is the 

dominant vegetation in the 

foreground. (Photo by Gerard 

Dean, USDA Forest Service)

14 Forest Ecosystem Health Indicators
SOIL QUALITY

Charles H. Perry • Research Soil Scientist • Northern Research Station

BACKGROUND

Soils are the foundation of the forest ecosystem, 

and they are nonrenewable over the course 

of management timescales. The Soil Quality 

indicator seeks to document changes in relevant 

physical and chemical characteristics of forest 

soils. Physical characteristics impact the growth 

and distribution of trees by influencing the ability 

of roots to access nutrients and water. Important 

characteristics monitored by FIA include bulk 

density, soil texture, forest floor thickness, depth 

to any restrictive horizons, and compaction. 

The forest floor and the top 8 inches of soil 

are sampled in the field for laboratory analyses 

because soil nutrients reflect the relative fertility 

of the soil as well as the legacy of some human 

impacts (e.g., acid deposition). The Soil Quality 

indicator assesses soil pH; carbon, nitrogen and 

phosphorus content; and extractable levels of 

major cations (sodium, potassium, calcium, 

magnesium, and aluminum) and sulfur along 

with several micronutrients. Soils evolve rather 

slowly, so this indicator features “on” and “off ” 

measurement cycles to maximize the opportunity 

to detect change within a constrained budget. 

PRODUCTS AND PUBLICATIONS

The soil’s physical and chemical properties may 

be influenced by natural and anthropogenic 

processes as well as management actions, so 

Ca:Al molar ratio

(minimum value)

Greater than 1.5

1.1 - 1.5

0.6 - 1.0

0.3 - 0.5

0.0 - 0.2

Figure 14. Spatial distribution of minimum Ca:Al molar ratios for the top 4 inches of soil across the conterminous United 

States. At the time of this analysis, sampling had not begun in New Mexico, Oklahoma, or Mississippi. (Adapted from 

Perry and Amacher 2012)

Forest Ecosystem Health Indicators 15
continued monitoring is vital to understanding 

forest health and productivity. The first round 

of remeasurement is currently underway, so this 

update reflects products and publications based 

on one round of sampling. Change detection will 

be an important feature of the indicator in the 

near future. 

The FIA program has published many analyses 

documenting soil conditions at the State level. 

These studies document how different forests 

occupy different niches in the landscape. We 

also have published regional- and national-scale 

analyses, including several focused on the legacy 

of acid deposition. Simply put, acid deposition 

leaches mobile cations from the soil, shifting 

the balance from calcium to aluminum. This 

negatively impacts tree health because trees use 

calcium (but not aluminum) in root and leaf 

development as well as in the construction of 

cell walls. 

RESEARCH AND DEVELOPMENT

Soils are but one part of an increasingly complete 

database of physical and biological components, 

and current research focuses on converting plotlevel information into continuous map services 

that are easier to distribute and more accessible 

for analysis by partners. Given the importance 

of carbon, much of the current work concentrates 

on soil carbon stocks. The resulting maps reflect 

our understanding of soil-forming processes, 

using predictors such as air temperature and 

precipitation, the ratio of precipitation to potential 

evapotranspiration, elevation, forest-type group, and 

surface geology. These novel products are finding 

application in the National Greenhouse Gas Inventory 

and will serve as the foundation of future guidance 

on best practices for inventory compilation. You can 

access this geospatial data through agency and open 

data portals. 

Figure 15. Soil 

core from a Forest 

Inventory and Analysis 

Program plot. (Photo 

by Charles H. Perry, 

USDA Forest Service)

16 Forest Ecosystem Health Indicators
INVASIVE PLANT SPECIES

Cassandra M. Kurtz • Forester • Northern Research Station and

Sonja N. Oswalt • Forest Resource Analyst • Southern Research Station

BACKGROUND

The Invasive Plant Species (IPS) indicator assesses 

the percentage of cover and presence of select IPS 

on a subset of FIA plots. The plants monitored 

vary by region and are determined based on 

their identification as IPS of regional concern on 

forested landscapes. The data collected provide 

information about IPS presence and spread as well 

as changing growing conditions. IPS can affect 

ecosystem health by displacing native plants and 

altering wildfire risk, nutrient availability, and 

habitat suitability. IPS data help land managers 

and policymakers track the spread, abundance, 

and risk of these species in forests.

PRODUCTS AND PUBLICATIONS

The IPS indicator has been used in various sitelevel analyses as well as for early detection. In 

most areas of the country, only a subset of forested 

plots is sampled for IPS, so coarse sampling may 

lead to high standard errors—a factor to keep in 

mind when assessing results. Combining IPS data 

with other plot data allow for the study of their 

relationships with trees, saplings, regeneration, and 

other site characteristics. Annual and cyclical State 

reports often include the results of IPS sampling. 

Additional regional, national, and scientific 

articles containing IPS results are available in print 

and online. Some examples of published studies 

that utilize the IPS indicator include:

 National and regional patterns of forest plant 

invasions (Oswalt et al. 2015, Oswalt and Oswalt 

2011, Kurtz 2013)

 Quantification of factors related to the spread 

and distribution of invasive plant species (Riitters 

et al. 2017, Guo et al. 2017, Jo et al. 2017)

RESEARCH AND DEVELOPMENT

IPS data are currently available for all 50 States. 

This relatively new availability has allowed 

for broad-scale IPS analyses. However, the 

inherent and necessary variability of the species 

monitored and other regional differences make 

comparisons of species at national scales 

challenging. Nevertheless, studies exploring the 

change in presence and spread of IPS continue 

to grow, informing our understanding of climatic 

influences, urban interfaces, long-term impacts, 

and more. Ways to further explore the IPS data 

include regional studies, online data dashboards, 

and interactive story maps.

Invasive plant 

species found 

per plot

+ 1 – 2

 3 – 4

 5 – 7

 8 – 15

Figure 16. Number of invasive plant species (IPS) observed per plot 

on Forest Inventory and Analysis IPS plots (2005–2010). Depicted plot 

locations are approximate (Kurtz 2013).

Figure 17. Showy foliage and flowers of the invasive plant saltcedar, which 

is native to Eurasia. Within the United States, this tree is most commonly 

observed in the West, an arid region where it has heavily impacted water 

supply and displaced many species (Kurtz 2013). (Photo by Cassandra M.

Kurtz, USDA Forest Service)

Forest Ecosystem Health Indicators 17
REGENERATION AND BROWSE IMPACT

William H. McWilliams • Research Forester • Northern Research Station

BACKGROUND

The maturation of Midwest and Northeast 

U.S. forests has led to an imbalance in age class 

structure, as young forest habitat has become rare. 

Stressors like white-tailed deer, invasive plants, 

climate variability, other limiting factors and 

their impacts on young tree seedlings have made 

regeneration of forests difficult. Young forest 

characteristics set the trajectory for composition, 

structure, and function over the life of a forest. 

This means that values the public has come to 

expect from healthy young forest are largely 

missing, and novel approaches will be needed to 

restore healthy young forest under stress to replace 

older forests as stand-initiation events occur, e.g., 

mortality or harvest. 

Increased concern about regeneration caused the 

Northern Research Station (NRS) FIA, in 2012, to 

implement a suite of Regeneration Indicator (RI) 

measurements on Phase 3 plots. The RI tracks all 

established seedlings down to 2-inches tall and plotlevel browse impacts. The approach was adapted 

from protocols from a quarter-century study of 

regeneration in Pennsylvania (McWilliams et al. 

2016). FIA currently samples this indicator only 

in the Northern United States, but the program is 

poised to implement the indicator nationally when 

and if funding becomes available.

PRODUCTS AND PUBLICATIONS

RI science products address a range of information 

gaps related to restoring sustainable forests 

across the Midwest and Northeast United States. 

Examples include:

Subcontinental-scale visualization of browse 

impacts (McWilliams et al. 2018).

 Technique for estimating regeneration security 

for NRS-FIA region (Vickers et al. 2018, in 

review).

 Regeneration Status chapters for NRS-FIA 

5-year State reports (e.g., Albright et al. 2017).

 Assisting forest and deer agencies in balancing 

habitat in Pennsylvania (McWilliams et al. 2017).

RESEARCH AND DEVELOPMENT

The RI fills a critical information gap for 

policymakers and managers working to regenerate 

Figure 18. White-tailed deer 

herd. (Photo from Adobe Stock 

Images)

18 Forest Ecosystem Health Indicators
desirable native species to sustain future forest 

values and provide healthy young forest habitat 

to support wildlife that depend on young forest. 

Research is needed to develop analytics that 

evaluate regeneration security and to identify 

problem areas where more intensive management 

may be required. These fundamental data provide 

a platform for conducting geospatial analyses 

using related geodatabases—e.g., fragmentation, 

population, or land use—to answer larger, more 

complex questions.

Natural research extensions are:

 Implementing a public estimation portal for core 

analytical products

 Building trend estimates and analyses as 

remeasured samples become available

 Comparing understory-overstory tree 

abundance/composition for taxonomic groups 

and ecoregions

 Developing advance regeneration security 

statistics.

 Capturing the value of geospatial analytics, 

visualization, and data.

 Broadening the scope of regeneration security 

estimation algorithms, e.g., coppice and 

plantation management.

Figure 19. Probability of occurrence 

for moderate or high ungulate browse 

impacts on forest land, Midwest 

and Northeast United States, 2017.

(Adapted from McWilliams et al. 2018)

Forest Ecosystem Health Indicators 19
FRAGMENTATION, URBANIZATION, AND 

LANDSCAPE CONTEXT

Rachel N. Riemann • Research Forester/Geographer • Northern Research Station

BACKGROUND

Forest fragmentation, urbanization, and habitat loss 

are associated with diminished regional biodiversity 

and are recognized as a major threat to animal 

populations worldwide, particularly for species that 

require interior forest conditions for all or part of 

their life cycle, and for those that are wide ranging, 

slow moving, and/or slow reproducing. Changes 

in the size of remaining forest patches, in their 

level of connectivity to other large patches, in the 

amount of general forest cover surrounding each 

patch, and in the amount of forest-nonforest edge 

directly affect the amount and quality of interior 

forest conditions. The same factors also affect 

forest ecosystem function and resilience, its ability 

to protect the quality and quantity of surface and 

ground water resources, its ability to supply forest 

products, and the ease with which nonnative, 

invasive, or generalist species can gain a foothold 

and spread throughout the landscape.

Indicators of forest fragmentation, landscape 

context, and urbanization describe the spatial 

distribution of forest land, the spatial context in 

which the forest land occurs, and the proximity 

of forest land to human populations and urban 

development. FIA/FHM use remotely sensed 

landscape data to develop forest fragmentation 

indicators that describe the spatial distribution of 

forest land itself—including spatial integrity index 

(forest patch size, degree of forest connectivity, 

local forest density), amount of interior or core 

forest, and the amount and type of forest edge. 

Landscape context indicators, such as landscape 

pattern type, describe the local land cover around 

forest land and the proportion that is natural, 

agricultural, or associated with urban development. 

Urbanization indicators describe the forest’s 

proximity to different types of urban development, 

such as roads or local densities of houses or human 

populations. 

PRODUCTS AND PUBLICATIONS

The suite of landscape pattern metrics quantifies 

aspects of fragmentation and urbanization 

known to have an effect on forest ecosystems, 

their management, or on their ability to provide 

ecosystem services.

Spatial integrity index

Unconnected

Low integrity

Medium integrity

High integrity

Core

Nonforest

Figure 20. Spatial integrity index of forest land at the 250- and 30-meter scale in a region north of Grand Rapids, MI. (Adapted from Pugh et al. 2017)

20 Forest Ecosystem Health Indicators
1971

1985

1999

Agriculture

Forest

Urban development

Figure 21. Forest becoming increasingly fragmented and 

urbanized over time in southeastern Massachusetts. (Created from 

the MassGIS land cover dataset - https://docs.digital.mass.gov/

dataset/massgis-data-land-use-1951-1999)

Some examples of published studies that utilize 

these indicators include:

 FIA State 5-year reports (e.g., recent reports—

Pugh et al. 2017, Crocker et al. 2017, Albright et 

al. 2017) 

 Vermont’s forest fragmentation report to its State 

legislature (Vermont Department of Forests, 

Parks and Recreation 2015) 

 Effects of forest fragmentation and urbanization 

on stream conditions (Riemann et al. 2004, RivaMurray et al. 2010) 

 Trends of forest interior conditions in the United 

States (Riitters and Wickham 2012) and distance 

from forest to roads (Riitters and Wickham 2003)

Some examples of datasets that we plan to make 

publicly available:

 Fragmentation metrics such as forest density, 

forest connectivity, and forest patch size

 Forest by Wildland Urban Interface (WUI) 

house density class 

 Road density

 Forest edges

 Forest density

 Neighborhood density of each nonforest land 

cover type

RESEARCH AND DEVELOPMENT 

All of the above landscape pattern metrics will 

continue to be updated as new landscape data 

sets and census data become available, and data 

sets will be archived and made available to the 

public. Work will continue with partners and user 

communities to further fine-tune the data offered 

and increase integration with issues, questions, 

and applications. Effort will be focused on data 

delivery, developing data tools to ensure that 

the data will be easily updated over time, and 

integrating the data sets into online tools for 

analysis, reporting, and storytelling.

Forest Ecosystem Health Indicators 21
SUMMARY

FIA began implementing a nationwide, 

field-based forest ecosystem health indicator 

monitoring effort in the 1990s, and it currently 

collects forest health measures in 47 States. The 

suite of FIA forest health indicators delivers 

critical information about complex forest 

ecosystem processes across the United States. The 

program continues to deliver reports and analyses 

that contribute to critical national and global 

assessments, but, increasingly, a new and diverse 

set of customers are demanding access to the data 

for their own analyses and integration of tools 

and systems to improve forest health science and 

develop new indicators of forest ecosystem health.

After nearly 2 decades of collecting, analyzing, 

and reporting on forest health, FIA has updated 

its sampling techniques with flexible spatial 

and temporal intensities for these indicators, in 

response to fluctuating budgets. This also allows 

the program to improve field operation efficiency, 

address emerging user demands, and adjust to 

evolving forest health science.

The enhanced Phase 2 sampling scheme can 

change in response to budgetary fluctuations 

(i.e., flexibility) without compromising longterm analytical capabilities. Although the 

enhanced indicator protocols collect less detailed 

information on each sampled plot, substantially 

more plots are sampled, increasing the statistical 

power of future forest health analyses and 

improving the reliability of estimates in important 

national assessments. For example, since 2012, 

the number of samples in the DWM indicator has 

increased to a nearly 7-times sample, while crown 

condition and vegetation diversity has increased 

to approximately a 4-times sample. These changes 

represent a continuation of efforts to address 

current budget realities and adapt for the future 

while continuing to meet customer and partner 

needs.

ACKNOWLEDGMENTS

Thanks to Susan Crocker, Linda Heath, and 

Greg Reams for their constructive reviews, 

which resulted in substantial improvements to 

this brochure, and to Mila Alvarez for her help 

with navigating the publication process. Thanks 

also to the Forest Health Monitoring Program 

for designing and implementing the original 

sampling protocols in the 1990s and to the Forest 

Inventory and Analysis Program for continuing 

this important monitoring and research. 

22 Forest Ecosystem Health Indicators
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Cover image by Robert Balog, Pixabay Cover photo: View of massive redwood trees in Jedediah Smith Redwoods 

State Park, CA. (Photo by Nate Hovee)