A New Map of Standardized Terrestrial Ecosystems of

the Conterminous United States

Professional Paper 1768

U.S. Department of the Interior

U.S. Geological Survey
Front cover: Map of the conterminous United States showing terrestrial ecosystems that were 

deductively modeled through biophysical stratification of the area into ecosystem footprints 

(physically distinct areas) and subsequent attribution of these footprints with a NatureServe 

ecosystem type. See figure 8 in the text.
A New Map of Standardized 

Terrestrial Ecosystems of the 

Conterminous United States

By Roger Sayre, Patrick Comer, Harumi Warner, and Jill Cress

Professional Paper 1768

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2009

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Suggested citation:

Sayre, Roger, Comer, Patrick, Warner, Harumi, and Cress, Jill, 2009, A new map of standardized terrestrial ecosystems 

of the conterminous United States: U.S. Geological Survey Professional Paper 1768, 17 p. (Also available online.)

ISBN 978–1–4113–2432–9
iii

Contents

Abstract ...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Deductive and Inductive Approaches to Ecosystem Modeling .............................................................2

Methodology ...................................................................................................................................................3

Results .............................................................................................................................................................9

Discussion .....................................................................................................................................................10

Conclusion.....................................................................................................................................................13

Acknowledgments .......................................................................................................................................14

References Cited..........................................................................................................................................14

Figures

 1. Diagram of the vertical structure of an ecosystem, showing the spatial 

integration of biological and nonliving components ...............................................................2

 2. Schematic depiction of the geospatial modeling approach to terrestrial 

ecosystems mapping ...................................................................................................................4

 3–8. Maps of the conterminous United States showing—

 3. NatureServe’s ecological divisions ..................................................................................5

 4. Mesoscale isobioclimate regions, representing areas of distinct 

ombrotype (wet/dry gradients) and thermotype (hot/cold gradients) regimes .........6

 5. Lithology of surficial materials, depicting the distributions of 17 distinct 

substrate types .....................................................................................................................7

 6. Landform classes modeled using 30-m digital elevation data and derived 

from neighborhood analyses of slope and relative relief. ............................................8

 7. Topographic moisture potential index modeled using 30-m digital 

elevation data and derived from analyses of potential accumulation of 

moisture at a point based on topography ......................................................................10

 8. Terrestrial ecosystems that were deductively modeled through biophysical 

stratification of the area into ecosystem footprints (physically distinct 

areas) and subsequent attribution of these footprints with a NatureServe 

ecosystem type ..................................................................................................................11

 9. Map showing terrestrial ecosystems in a 6,000-km2

 section of northeastern Utah ........12

Table

 1. Land surface form classes topographically modeled from combinations of slope 

class and local relief ....................................................................................................................9
iv

Conversion Factors

Multiply By To obtain

Length

meter (m) 3.281 foot (ft)

Area

hectare (ha)

square kilometer (km2

)

2.471

0.3861

acre

square mile (mi2)
A New Map of Standardized Terrestrial Ecosystems of the 

Conterminous United States

By Roger Sayre,1 Patrick Comer,2 Harumi Warner,3 and Jill Cress4

Abstract Introduction

A new map of standardized, mesoscale (tens to thousands Ecosystems provide many benefits to human societies 

of hectares) terrestrial ecosystems for the conterminous United as goods (such as food, fuel, and fiber) and services (such as 

States was developed by using a biophysical stratification water purification, maintenance of soil fertility, and pollinaapproach. The ecosystems delineated in this top-down, deduc- tion). Sustained provision of these goods and services is 

tive modeling effort are described in NatureServe’s classifica- important for human societies, but recent studies like that by 

tion of terrestrial ecological systems of the United States. The the Millennium Ecosystem Assessment (2005) have shown 

ecosystems were mapped as physically distinct areas and were that degraded ecosystems are compromised in their ability 

associated with known distributions of vegetation assemblages to provide these benefits. In order for existing ecosystems to 

by using a standardized methodology first developed for South persist on the planet, they will need to be well managed. Many 

America. This approach follows the geoecosystems concept of U.S. agencies and international organizations now promote 

R.J. Huggett and the ecosystem geography approach of R.G. ecosystem-based management approaches; these groups 

Bailey. include the U.S. Bureau of Land Management (1994), the U.S. 

Unique physical environments were delineated through Department of Agriculture (USDA) Forest Service (2006a, p. a geospatial combination of national data layers for biogeog- 22), the U.S. Geological Survey (as described by Myers and raphy, bioclimate, surficial materials lithology, land surface others (2007)), the United Nations Environment Programme forms, and topographic moisture potential. Combining these (which supports the Secretariat of the Convention on Biologi- layers resulted in a comprehensive biophysical stratification cal Diversity, 2000), and the Group on Earth Observations of the conterminous United States, which produced 13,482 (2005). Management of ecosystems necessarily requires an unique biophysical areas. These were considered as fundamen- understanding of the types, spatial pattern and scales, and tal units of ecosystem structure and were aggregated into 419 distributions of ecosystems that occur within the management potential terrestrial ecosystems. jurisdiction. The ecosystems classification effort preceded the map- Ecosystem definition, classification, and mapping have ping effort and involved the independent development of received considerable attention since ecosystems were first diagnostic criteria, descriptions, and nomenclature for describ- championed by Tansley (1935). Odum (1953), in his seminal ing expert-derived ecological systems. The aggregation and textbook on ecology, recognized ecosystems as systems of labeling of the mapped ecosystem structure units into the biotic communities interacting with their physical environ- ecological systems classification was accomplished in an itera- ment. These early definitional concepts have evolved into dif- tive, expert-knowledge-based process using automated rulesets ferent lines of investigation into ecosystem structure, ecosys- for identifying ecosystems on the basis of their biophysical tem function, ecosystem condition, ecosystem geography, and, and biogeographic attributes. The mapped ecosystems, at a most recently, ecosystem services. The study of ecosystem 30-meter base resolution, represent an improvement in spatial pattern and process in their regional contexts has become the and thematic (class) resolution over existing ecoregionaliza- principal focus of landscape ecologists (Wu and Hobbs, 2007), tions and are useful for a variety of applications, including and ecosystem geographers analyze and map the spatial distri- ecosystem services assessments, climate change impact stud- bution of ecosystems at multiple scales (Bailey, 1996). ies, biodiversity conservation, and resource management. The trend towards ecologically oriented management has 

been associated with the development of a number of differ-

 1U.S. Geological Survey, Reston, VA. ent classifications and maps of ecosystems at scales ranging 

 2Ecology Department, NatureServe, Boulder, CO. from global to local. In the United States, an Interagency 

 3Parallel Inc., Lakewood, CO. Ecosystem Management Task Force (1995) concluded that 4U.S. Geological Survey, Denver, CO. ecosystem delineation is necessary to establish a geospatial 
2 A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

framework for resource management. Global and regional 

ecosystems have been defined in many macroscale (thousands to tens of thousands of hectares) ecoregionalizations 

of the planet (Bailey, 1998a; Olson and others, 2001) and the 

United States (Omernik, 1987; Bailey, 1996; Commission 

for Environmental Cooperation, 1997; Ricketts and others, 

1999; Groves and others, 2000). In the United States, different 

Federal land management agencies use different macroscale 

ecoregional classification systems (for examples, see Omernik, 

1987; Cleland, Avers, and others, 1997; Cleland, Freeouf, 

and others, 2005). In 1996, nine Federal agencies agreed to 

develop a spatial framework of common ecological regions as 

areas within which biotic and abiotic capacities and potentials 

are similar (McMahon and others, 2001). This framework is 

still in development in 2009. Today, standardized maps of 

ecosystems are increasingly available for regions of the United 

States (for example, Lowry and others, 2005; Ryan and others, 

2006), but standardized, nationally comprehensive ecosystem 

maps delineated at management-appropriate scales (tens to 

thousands of hectares) are not yet available. The lack of such 

information resulted in this effort to produce a new map of terrestrial ecosystems for the conterminous United States.

Building on an approach first developed for South America (Sayre and others, 2008), we modeled the standardized, 

mesoscale ecosystems of the conterminous United States by 

using a deductive, biophysical stratification of the region and 

associating the physically distinct areas with known distributions of vegetation assemblages. This approach emphasizes the 

multifactor mapping of ecosystems by their structure components and incorporates a characterization of the bioclimate 

regime and the geomorphology. Bailey (1996) illustrated an 

ecosystem at any point as the vertical integration of climate, 

landform, biota, surface and subsurface waters, soil, and bedrock (fig. 1), and it follows from this definition that ecosystem 

distributions vary spatially because of geographic variation 

in their major structure elements. Standardized ecosystems 

can therefore be mapped as the geospatial integration of these 

fundamental ecosystem structure elements across geographic 

space (Sayre and others, 2008), where ecosystem boundaries represent area-based changes in the structure components. 

This approach is essentially a geographic application of 

gradient analysis (Choesin and Boerner, 2002), where species 

distributions and abundances are related to environmental 

gradients in variables such as temperature and water, light, and 

nutrient availability.

Deductive and Inductive Approaches 

to Ecosystem Modeling

The approach presented herein emphasizes the mapping of NatureServe’s (Comer and others, 2003) ecosystems 

by the mapping and spatial integration of their major structure elements and is accomplished through a comprehensive 

biophysical stratification of the conterminous United States 

Macroclimate

Topoclimate

Landform

Soils

Groundwater

Surface water

Biota

Ecosystem

Bedrock

Figure 1. The vertical structure of an ecosystem, showing 

the spatial integration of biological and nonliving components. 

Reproduced with permission from Robert G. Bailey (1996).

into physically distinct areas. These unique physical environments are considered as the fundamental building blocks of 

ecosystems and have been referred to as “tesserae,” or basic 

landscape elements (Huggett, 1995). This is a top-down, 

deductive modeling approach to mapping previously classified 

and described ecosystems.

It is also possible to map ecosystems by using a bottomup, inductive modeling approach, and concurrent efforts 

are underway to predictively map the same NatureServe 

ecosystems utilized in this study by using point-source data 

from over 100,000 locations. The U.S. Geological Survey 

Gap Analysis Program, which is part of the collaborative 

U.S. Gap Analysis Program (Scott and others, 2001), and the 

multiagency LANDFIRE Program (Ryan and others, 2006) are 

both using inductive modeling to map the current distribution 
Methodology 3

of NatureServe ecosystems using point data sources where Mapping approach.—Ecosystems were mapped as 

environmental attributes at points are associated with known physically distinct areas on the basis of biogeography, biocliecosystem occurrences at those locations. The inductive mod- mate, surficial materials lithology, landform, and topographic 

eling efforts are data intensive, and more than 100,000 points moisture potential. National raster data layers for each of these 

have been used to date. The degree of spatial concordance in ecosystem structure elements were derived using best availthe two sets of results will be assessed to help evaluate the able data sources. The spatial resolution of the source data 

utility of using the less data-intensive deductive method to used to develop the input data layers varied considerably. For 

map global ecosystems. landforms and topographic moisture potential, the national 

datasets were developed at a relatively fine spatial resolution 

of 30 meters (m). The bioclimates data layer was derived from 

Methodology meteorological data having a resolution of 1 square kilometer 

(km2

), and the biogeographic regions data layer was derived 

from source data having the same resolution. The lithology 

Ecosystems classification.—Terrestrial ecological sys- dataset was compiled at a spatial resolution of 15 km2

. All 

tems for the conterminous United States have been defined by datasets were reconciled to a common 30-m raster data surface 

NatureServe as spatially co-occurring assemblages of vegeta- for the conterminous United States.

tion types sharing a common underlying substrate, ecological All input data layers were spatially combined, in a 

process, or gradient (Comer and others, 2003). The ecological hierarchical sequence, to develop a comprehensive biophysisystems are described in the NatureServe Explorer database cal stratification of the conterminous United States by bioge-

(NatureServe, 2008). This classification uses diagnostic classi- ography, bioclimate, surficial materials lithology, landform, 

fiers such as climate type, topographic position, and substrate and topographic moisture potential. This union produced the 

type to characterize upland and wetland ecosystems at typical set of unique physical environments that represent the essengeographic scales of tens to thousands of hectares. Each eco- tial building blocks, or structure units, of ecosystems. These 

system type exhibits one of four spatial patterns on the land- ecosystem structure units were subsequently aggregated and 

scape: matrix forming, large patch, small patch, or linear. The labeled with an ecosystem code from the NatureServe classifimatrix-forming types typically dominate regional landscapes, cation. Spatial pattern was included in the analysis to deterresponding to climatic pattern at regional scales. Large-patch mine the sensitivity of the ecosystem delineation model to 

ecosystems are generally driven by natural disturbances within ecosystem size and spatial pattern. Source data, methods, and 

the regional matrix. Small-patch types are typically constricted a graphical depiction of each of the input data layers follow. A 

in their location by physical factors such as a bedrock outcrop- schematic of the input data layers and their spatial combinaping or soil moisture regime. Linear ecosystems typically tion to produce ecosystems is depicted in figure 2.

form where local environments and ecological dynamics Biogeographic regions.—NatureServe’s ecological diviproduce linear patterns, such as in coastal zones or along river sions of the United States (Comer and others, 2003) were used 

corridors. to stratify the conterminous United States into 12 subcontinenNatureServe’s ecosystem classification followed the tal biogeographical units (fig. 3). These units reflect broadinitial development of the National Vegetation Classification scale homogeneity in vegetation distributions as a product of 

(NVC) (Grossman and others, 1998; NatureServe, 2008), climate, phytogeographic history, disturbance regimes, and 

which was established by the Federal Geographic Data Com- geographic isolation. These units thus reflect major, recogmittee as the reporting standard to be used by Federal agencies nized phytogeographic distributions (Takhtajan, 1986).

for vegetation description and assessments (Federal Geo- Bioclimate regions.—Bioclimate regime strongly influgraphic Data Committee, 1997, 2008). Difficulty in mapping ences the differentiation and distribution of terrestrial ecosysvegetation units at the finest levels (vegetation alliances and tems and is one of the key input layers in the ecosystem delineaassociations) of the NVC (Comer and others, 2003) and an tion process. Mesoscale isobioclimate regions (fig. 4) were 

interest in relating vegetation units to their natural biophysi- identified as areas with homogeneity in ombrotype (wet/dry gracal setting led to an effort to aggregate spatially co-occurring dient) and thermotype (hot/cold gradient). These regions were 

vegetation units from the NVC into a new ecosystem classifi- mapped by using the DayMet data, a set of meteorological raster 

cation (Comer and others, 2003). This ecosystem classification data surfaces for the Nation having a spatial resolution of 1 km2

system has been adopted as the classification framework for (Thornton and others, 1997). These data layers were constructed 

various agency efforts, such as the U.S. Geological Survey from spatial interpolations of daily temperature, precipitation, 

(USGS) Gap Analysis Program (Scott and others, 2001) and radiation, and humidity data collected from meteorological 

the multiagency fire management program, LANDFIRE (Ryan stations over an 18-year period (1980–1997). The methodoland others, 2006), and NatureServe is considered a credible ogy used to produce the isobioclimate classes (Rivas-Martinez 

authority for providing the Federal Government with biodi- and Rivas y Sáenz, 2009) was derived from a consideration of 

versity information (USDA Forest Service, 2006b, p. 26). At bioclimatology and its relationship to phytogeography.

the time of this writing, 690 terrestrial ecosystems have been This approach develops a number of bioclimatic indidescribed for the conterminous United States. ces calculated from a variety of data on temperature and 
4 A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

Geospatial Approach—Terrestrial Ecosystems Mapping

Input Layers Products

1a Biogeographic Region

(12 classes) Product 1

Mesoscale Bioclimate/Biogeographic Regions

(435 classes) 1b Isobioclimates

(127 classes)

2a Surficial Materials Lithology

(17 classes)

Product 2

2b Land Surface Forms Local Abiotic Environments

(10 classes) (813 classes)

2c Topographic Moisture Potential

(4 classes)

ECOMAP Sections Product 3 Product 4

(for aggregation and labeling support) Ecosystem aggregation and NatureServe

Footprints labeling Ecosystems

(13,482 classes) (419 classes)

+

+

+

+

=

Figure 2. Schematic depiction of the geospatial modeling approach to terrestrial ecosystems mapping, identifying the input data 

layers, the combination sequence, and resulting products for the conterminous United States.

precipitation (such as average temperature of the coldest 

month, total precipitation of the warmest 4-month period, a 

continentality index, and a thermicity index). The values of 

these indices are compared with established thresholds for the

differentiation of thermotypic (hot/cold gradients) and ombrotypic (wet/dry gradients) regions, and the results are used in 

sets of decision rules to identify classes. The classification is 

implemented in four levels: macrobioclimates, bioclimates, 

thermotypes (thermoclimatic belts), and ombrotypes (ombroclimatic belts). The final isobioclimates dataset represents 

areas of distinct thermotype and ombrotype; 127 of these isobioclimates were mapped for the conterminous United States.

Surficial materials lithology.—Different substrate types 

at the Earth’s surface influence distinct vegetation distributions at local, regional, and continental scales (Kruckeberg, 

2002), underscoring the importance of including lithology 

as a primary structure element of ecosystems. A surficial 

materials dataset produced by the USGS for the conterminous United States (Soller and Reheis, 2004) was used as the 

source lithology data layer for the ecosystem mapping. These 

lithology classes were derived from a consideration of texture, 

internal structure, thickness, and environment of deposition 

or formation of surficial materials (Soller and Reheis, 2004) 

and were compiled from bedrock and soils maps at a scale 

of 1:5,000,000. This surficial materials map depicts broadly 

defined common map units for the purpose of providing an 

overview of the existing data and knowledge. The lithology 

classes from this data layer were aggregated into a set of 17 

ecologically meaningful lithologies and mapped (fig. 5) as key 

substrates that typically control or influence the distribution of 

terrestrial ecosystems.

Land surface form classes.—Regional physiography and 

land surface forms strongly influence the differentiation and 

distribution of terrestrial ecosystems, and the landform input 

layer is a key part of the ecosystem delineation process. Nine 

landform classes (flat plains, smooth plains, irregular plains, 

escarpments, low hills, hills, breaks/foothills, low mountains, 

and high mountains/deep canyons) were topographically 
Methodology 5

Laurentian and Acadean

Central Interior and Appalachian

Gulf and Atlantic Coastal Plain

North American Pacific Maritime

Eastern Great Plains

Mediterranean California

Madrean Semidesert

North American Warm Desert

Western Great Plains

Inter-Mountain Basins

Rocky Mountain

0 500 1000KILOMETERS

0 250 500 MILES

Biogeographic Regions - NatureServe Ecological Divisions

Caribbean

Figure 3. Map of the conterminous United States showing NatureServe’s ecological divisions (Comer and others, 2003), modified 

from Bailey (1998b) and identifying broad areas of phytogeographic similarity (general homogeneity of vegetation assemblages). The 

homogeneity is due to evolutionary history, geographic isolation, disturbance history, and climate. 

modeled from combinations of slope class and local relief Whereas Hammond’s methodology was based on three 

(fig. 6). The methodology used to produce these land surface variables, slope, local relief, and profile type, MoRAP’s methform classes built on the approach of Dikau and others (1991) odology used only slope and local relief (True and MoRAP 

to automate land surface form classification by using a digital Staff, 2002). Slope was classified as gently sloping or not 

elevation model and was developed by the Missouri Resource gently sloping by using a slope threshold of 8 percent. Local 

Assessment Partnership (MoRAP). The MoRAP approach relief was divided into five classes (0–≤15 m, >15–≤30 m, 

used a moving neighborhood analysis window and a land sur- >30–≤90 m, >90–≤150 m, and >150 m). Slope classes and 

face classification method modified from Hammond (1964). relief classes were subsequently combined to produce eight 

The USGS 30-m National Elevation Dataset (Gesch, 2007) land surface form classes (flat plains, smooth plains, irregular 

was the data source, and a 1-km2

 window was used for neigh- plains, escarpments, low hills, hills, breaks/foothills, and low 

borhood analysis (True and others, 2000; True and MoRAP mountains). A ninth class, high mountains/deep canyons, was 

Staff, 2002). added to the landform classification by using an additional 
6 A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

Supraboreal

Hyperhumid

Mesoboreal

Humid

Hyperhumid

Thermoboreal

Subhumid

Hyperhumid

Cryorotemperate

Dry

Ultrahyperhumid

Mesotemperate

Semiarid

Ultrahyperhumid

Orotemperate

Dry

Ultrahyperhumid

Thermotemperate

Semiarid

Ultrahyperhumid

Supratemperate

Semiarid

Ultrahyperhumid

Infratemperate

Semiarid

Humid

Mesomediterranean

Arid

Hyperhumid

Oromediterranean

Semiarid

Humid

Thermomediterranean

Hyperarid

Humid

Supramediterranean

Arid

Hyperhumid

Inframediterranean

Hyperarid

Subhumid

Mesotropical

Arid

Humid

Thermotropical

Hyperarid

Subhumid

0 500 1000KILOMETERS

0 250 500 MILES

Isobioclimates

Tropical Thermotypes Mediterranean Thermotypes Temperate Thermotypes Boreal Thermotypes

Figure 4. Map of the conterminous United States showing mesoscale isobioclimate regions, representing areas of distinct ombrotype 

(wet/dry gradients) and thermotype (hot/cold gradients) regimes; 127 isobioclimates were identified and mapped.

local relief class (>400 m). The relations among slope, relief, By use of the 30-m USGS National Elevation Dataset 

and landform class are depicted in table 1. The tenth landform (Gesch, 2007) a topographic position index (TPI) was calcuclass, drainage channels (wet or dry), was derived indepen- lated; the TPI represents the difference between the elevation 

dently from the other classes by using the slope position of a cell and the mean elevation of its neighborhood within 

algorithm (Weiss, 2001). a 1-km2

 moving window. Six slope position classes were 
Methodology 7

Carbonate Residual Material

Non-Carbonate Residual Material

Alkaline Intrusive Volcanic Rock

Silicic Residual Material

Extrusive Volcanic Rock

Colluvial Sediment

Glacial Till, Clayey

Glacial Till, Loamy

Glacial Till, Coarse-Textured

Glacial Outwash and Glacial Lake Sediment, Coarse-Textured

Glacial Lake Sediment, Fine-Textured

Hydric, Peat and Muck

Eolian Sediment, Coarse-Textured (Sand Dunes)

Eolian Sediment, Fine-Textured (Glacial Loess)

Saline Lake Sediment

Alluvium and Fine-Textured Coastal Zone Sediment

Coastal Zone Sediment, Coarse-Textured

0 500 1000KILOMETERS

0 250 500 MILES

Surficial Materials Lithology

Water

Figure 5. Map of the conterminous United States showing lithology of surficial materials, depicting the distributions of 17 distinct 

substrate types.

identified by comparison of the TPI and the standard deviation potential at any point on the surface of the Earth is also a funcof the neighborhood elevation (Weiss, 2001). Two of these tion of surface topography (accumulation of water), substrate 

slope classes, valleys and lower slopes, were combined to pro- porosity (drainage), and evapotranspiration (loss of moisture 

duce a drainage channels landform class, which was added to to atmosphere).

the other nine landform classes but was not shown in figure 6. To better account for surface moisture potential, a 

Topographic moisture potential index.—The substrate topographic moisture potential index (fig. 7) was developed 

moisture regime strongly influences the differentiation and to distinguish potential wetlands from uplands on the basis of 

distribution of terrestrial ecosystems (Bailey, 1996). Although topographic setting. Surface moisture potential was derived 

isobioclimate maps characterize surface moisture potential from a combination of computed topographic characteristics 

on the basis of long-term precipitation patterns, the moisture and mapped wetlands boundaries. The source of data for 
8 A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

Flat Plains

Smooth Plains

Irregular Plains

Escarpments

Low Hills

Hills

Breaks/Foothills

Low Mountains

0 500 1000KILOMETERS

0 250 500 MILES

Land Surface Forms

High Mountains/Deep Canyons

Figure 6. Map of the conterminous United States showing landform classes modeled using 30-m digital elevation data and derived 

from neighborhood analyses of slope and relative relief. 

this assessment is the nationwide Elevation Derivatives for were extracted and a histogram of their statistical distributions 

National Applications (EDNA) dataset (Verdin, 2000; Franken was calculated. Subsequently, on the basis of an evaluation of 

and others, 2001). The 30-m EDNA hydrologic derivative these histograms, CTI thresholds were developed to separate 

database was derived from the USGS 30-m National Elevation potential wetlands from uplands. A similar process was used to 

Dataset (Gesch, 2007) and contains a national compound assess the distributions of CTI values for known locations of 

topographic index (CTI) data layer (http://edna.usgs.gov/ mesic and dry uplands. After the range of CTI values for these 

Edna/datalayers/cti.asp). The CTI is a topographically derived three different substrate moisture regimes (potential wetlands, 

measure of the slope in a raster cell and the contributing area mesic uplands, and dry uplands) was determined, the CTI 

from “upstream” raster cells and thus expresses the potential dataset was recalculated to identify the topographic moisture 

for water flow to a point. potential.

Potential accumulation at a point (CTI) was compared The final step in the generation of the data layer repwith independent estimates of water accumulation by obtain- resenting the national topographic moisture potential was 

ing geospatial data from a number of sample locations to partition the dry uplands class into two subclasses, a dry 

representing wetland/upland boundaries from the National uplands class and a very dry uplands class. As applicable to 

Wetlands Inventory (NWI) dataset (U.S. Fish & Wildlife northern temperate latitudes, very dry uplands were defined 

Service, 2009). Where these “shorelines” (the interface as dry uplands with relatively steep, south-facing slopes, and 

between wetlands and adjacent land) occurred, the CTI values identification of this class was based on the slope and aspect 
Results 9

Table 1. Land surface form classes topographically modeled 

from combinations of slope class and local relief.

[The methodology to produce the land surface form classes was developed 

by the Missouri Resource Assessment Partnership (MoRAP); see True and 

MoRAP Staff (2002). km2, square kilometer]

Slope class Local relief

(meters)

Land surface 

form class

Gently sloping—Slope <8 percent 

in more than 50 percent of area 

in 1-km2 neighborhood.

Not gently sloping—Slope <8 

percent in less than or equal 

to 50 percent of area in 1-km2

neighborhood.

≤15

>15–≤30

>30–≤90

>90

≤30

>30–≤90

>90–≤150

>150–≤400

>400

Flat plains

Smooth plains

Irregular plains

Escarpments

Low hills

Hills

Breaks/foothills

Low mountains

High mountains/

deep canyons.

datasets derived from the USGS 30-m National Elevation 

Dataset. The final topographic moisture potential dataset for 

the conterminous United States contains four classes: potential 

wetlands, mesic uplands, dry uplands, and very dry uplands.

Ecosystem labeling process.—The ecosystem “footprints” (ecosystem structure units) resulting from the union 

of the input layers described above characterize the physical 

potential of the environment and represent the building blocks 

that were attributed with NatureServe ecosystems labels. The 

labeling process was semiautomated and iterative and was 

accomplished by ruleset formulation and subsequent spatial 

implementation of these rules using the ecosystems footprint 

data. The rulesets were derived independently of the mapping effort in an expert-knowledge-based process. A labeling 

rule was developed for each NatureServe ecosystem, associating it with a particular biogeographic region, bioclimate, 

lithology, landform, and topographic moisture potential. The 

rulesets were organized as a matrix of ecosystem types and 

their attribute classes, and the matrix was used as a labeling 

look-up table in the geographic information system (GIS). The 

rulesets were developed by the principal author of the ecosystems classification (Comer and others, 2003) on the basis of 

the published ecosystem descriptions and known locations of 

vegetation assemblages. Rulesets were iteratively revised after 

each implementation of the spatial model. Four iterations were 

implemented to conclude the labeling process.

Results

The five input data grids were combined to produce 

the ecosystems footprints data layer for the conterminous 

United States. This product is essentially a characterization 

of physically distinct areas at a base resolution of 30 m and 

in a digital data format and, as such, describes the physical 

geography of the conterminous United States in a manner 

heretofore unavailable. The integration of the five input data 

layers produced 49,168 unique combinations of biogeography, 

bioclimate, lithology, landform, and topographic moisture 

potential. Of these unique footprint types, 13,482 met a minimum pixel count threshold (20,000 pixels) and were used in 

the labeling process. The threshold value of 20,000 pixels was 

chosen because the sum of the area from all footprints with 

pixel counts under this value was less than 1 percent of the 

total area being mapped. Excluding open water, 98.7 percent 

of the footprint pixels were classified as terrestrial ecosystem 

types, and the remaining 1.3 percent of pixels were classified 

as unknown.

During the labeling process, the 13,482 ecosystem footprints were associated with a NatureServe ecosystem type. 

This labeling process was aggregative, illustrating the primarily many-to-one (multiple ecosystem footprints to one unique 

ecosystem) nature of the data. However, several one-to-many 

(one unique footprint type for multiple ecosystem types) 

relationships were also observed in the labeling process. In 

these instances, the same physical environment could support different vegetation assemblages in different parts of the 

country, likely as a result of a different evolutionary history. 

These one-to-many relationships were resolved by incorporating into the analysis a finer biogeographic data layer, 

consisting of units from the USDA Forest Service’s ECOMAP 

sections (Cleland, Freeouf, and others, 2005). The sections 

data were not spatially combined with the footprints dataset 

but were incorporated into the labeling process through ruleset 

revisions. The decision to use ECOMAP sections to increase 

the biogeographic resolution of the analysis was based on 

the availability of information on the presence or absence of 

NatureServe ecosystems in ECOMAP sections.

The ecosystem structure footprints were aggregated into 

419 terrestrial ecosystems (fig. 8). This product represents 

a new map of standardized, replicable, mesoscale terrestrial 

ecosystems for the conterminous United States. The 419 

ecosystems mapped through this process represent 60 percent 

of the total number of ecosystems (690) described for the conterminous United States at the time of this writing. To convey 

a sense of the types, numbers, and distributions of ecosystems 

in a local to regional context, figure 9 presents a map of these 

ecosystems in a 6,000-km2

 area in northeastern Utah.

As would be expected from their generally larger size, 

most of the ecosystems mapped (72 percent) were either 

matrix-forming or large-patch ecosystems, as opposed to the 

smaller linear and small-patch ecosystems, and the method 

discriminated 70 percent of the total number of larger ecosystems (matrix and large patch), but only 47 percent of the 

smaller ecosystems (linear and small patch). The deductive 

modeling approach appears to be robust for the delineation of 

these larger ecosystem types but limited in the resolution of 

small-patch and linear ecosystems.
10 A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

Discussion conterminous United States has been subject to considerable 

land cover change (Loveland and others, 2002), and what is 

mapped in this study as a potential ecosystem type may in 

The mapped ecosystem distributions presented herein fact be developed or in agricultural use. In a future analysis, 

should be regarded as potential, rather than actual. They impervious surfaces and other altered landscapes will be 

should be interpreted as the probable vegetation assemblages masked out to determine the probable distribution of actual, 

that would be expected to occur as a biotic response to the rather than potential, ecosystems.

physical potential of the environment, in the absence of The accuracy of the ecosystem map is currently being 

significant human disturbance. Mapping the probable dis- evaluated. Ideally, a national field campaign would be contributions of potential ecosystems has a particular utility for ducted to assess the accuracy of the input layers as well as 

ecosystem restoration, as it characterizes expected (historical) the final ecosystem map at a randomly selected set of points 

biotic responses to the physical environment. Much of the representing each of the 419 ecosystem types. Such an 

Water

Very Dry Uplands

Dry Uplands

Mesic Uplands

0 500 1000KILOMETERS

0 250 500 MILES

Topographic Moisture Potential Classes

Potential Wetlands (Periodically Saturated or Flooded Land)

Figure 7. Map of the conterminous United States showing topographic moisture potential index modeled using 30-m digital elevation 

data and derived from analyses of potential accumulation of moisture at a point based on topography.
Discussion 11

assessment is beyond the scope of the current effort. However, deductive and the inductive modeling methods. The top-down, 

the USGS Gap Analysis Program (GAP) and the multiagency deductive model described herein is currently planned (Sayre 

LANDFIRE Program each have considerable amounts of point and others, 2007) as the method for mapping standardized, 

location data, with both environmental and ecosystem type robust, and practical global ecosystems as an ecosystems 

attributes. When the GAP and LANDFIRE inductive model- and biodiversity program (Muchoney, 2008) of the Global 

ing efforts are complete for the conterminous United States, Earth Observation System of Systems (GEOSS), an interthe results from the deductive method and those inductive governmental protocol commissioned by the Group on Earth 

modeling methods will be compared. Planning is underway for Observations (2005).

a collaboration to assess both (1) the accuracy of the ecosys- It should be emphasized that although the NatureServe 

tem data presented herein using in situ data and (2) the spatial ecosystem classification was used as the target classification 

concordance between the ecosystem maps resulting from the for this work, other ecological unit classifications could be 

Water

Sparsely Vegetated Ecosystems

Herbaceous Wetland Ecosystems

Woody Wetland Ecosystems

Steppe/Savanna Ecosystems

Shrubland Ecosystems

Herbaceous Ecosystems

0 500 1000KILOMETERS

0 250 500 MILES

Terrestrial Ecosystems

Forest and Woodland Ecosystems

Figure 8. Map of the conterminous United States showing terrestrial ecosystems that were deductively modeled through biophysical 

stratification of the area into ecosystem footprints (physically distinct areas) and subsequent attribution of these footprints with a 

NatureServe ecosystem type. For this map, 419 NatureServe ecosystems were mapped, each with multiple spatial occurrences; in the 

figure explanation, the ecosystems are shown grouped by general biome categories. Figure 9 shows some of these ecosystems in more 

detail for a small area in Utah.
12 A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

Figure 9. Map showing terrestrial ecosystems in a 6,000-km2 section of northeastern Utah and depicting the types, numbers, and 

spatial patterns of ecosystems at a local to regional scale.

Colorado Plateau Mixed Bedrock Canyon and Tableland

Colorado Plateau Mixed Low Sagebrush Shrubland

Colorado Plateau Pinyon-Juniper Shrubland

Colorado Plateau Pinyon-Juniper Woodland

Great Basin Foothill and Lower Montane Riparian Woodland and 

Shrubland

Inter-Mountain Basins Aspen-Mixed Conifer Forest and Woodland

Inter-Mountain Basins Big Sagebrush Shrubland

Inter-Mountain Basins Big Sagebrush Steppe

Inter-Mountain Basins Cliff and Canyon

Inter-Mountain Basins Greasewood Flat

Inter-Mountain Basins Juniper Savanna

Inter-Mountain Basins Mat Saltbush Shrubland

Inter-Mountain Basins Montane Sagebrush Steppe

Inter-Mountain Basins Semi-Desert Grassland

Inter-Mountain Basins Semi-Desert Shrub-Steppe

Inter-Mountain Basins Shale Badland

Middle Rocky Mountain Montane Douglas-Fir Forest and Woodland

North American Arid West Emergent Marsh

Rocky Mtn. Cliff, Canyon, and Massive Bedrock

Rocky Mtn. Lodgepole Pine Forest

Wyoming Basins Dwarf Sagebrush Shrubland and Steppe

Water

Rocky Mtn. Lower Montane-Foothill Riparian Woodland and Shrubland

Rocky Mtn. Poor-Site Lodgepole Pine Forest

Rocky Mtn. Subalpine Dry-Mesic Spruce-Fir Forest and Woodland

Southern Rocky Mtn. Dry-Mesic Montane Mixed Conifer Forest and 

Woodland

Southern Rocky Mtn. Mesic Montane Mixed Conifer Forest and 

Woodland

Southern Rocky Mtn. Montane-Subalpine Grassland

Southern Rocky Mtn. Ponderosa Pine Savanna

Southern Rocky Mtn. Ponderosa Pine Woodland

Rocky Mtn. Subalpine-Montane Riparian Shrubland

Great Basin Semi-Desert Chaparral

Great Basin Pinyon-Juniper Woodland

Terrestrial Ecosystems

Columbia Plateau Silver Sagebrush Seasonally Flooded Shrub-Steppe

Utah

0 10 20 KILOMETERS

0 5 10 MILES
Conclusion 13

used as the set of possible labels for aggregating the footprints. problematic. For example, the landforms data, derived from 

An interesting exercise would be to aggregate the ecosystem the USGS 30-m National Elevation Dataset, produced relafootprints into local or regional ecosystem classifications tively fine, dispersed, geomorphological structures. However, 

through the development of appropriate labeling rulesets as the coarser, more regional scale lithology data might indicate 

was done here for the NatureServe classification. The Nature- the same lithology for all these distinct landforms, which 

Serve ecosystems classification strongly emphasizes vegeta- may have ranged from plains to mountains. Moreover, an 

tion distributions and is itself built from a reconfiguration of edge effect (imperfect alignment of superimposed layers) was 

the National Vegetation Classification, and so the mapped often noted when comparing the boundaries of lithological 

ecosystems presented herein are quite biological in nature. It features and other inputs. A possible solution to this problem 

would be possible to aggregate the footprints in another man- in the future might include the development of a geostatistical 

ner that more strongly emphasized geo-ecosystems (Huggett, attribution procedure for assigning a “most probable” attribute 

1995), rather than bio-ecosystems. from the coarser dataset (geology) to the features mapped with 

It should also be emphasized that these ecosystems finer resolution data (landforms), especially in cases where a 

were mapped from a spatially explicit consideration of their direct relationship between the two has been identified.

structure elements. Proponents of holistic ecosystem ecology Secondly, more biogeographic specificity was necessary 

maintain that ecosystems cannot be fully understood through to discriminate ecosystems than was originally planned. The 

reductionist approaches and caution that reducing ecosystems original 12 ecological divisions used in the stratification were 

to their abiotic and biotic components does not sufficiently inadequate to resolve the one-footprint-to-many ecosystems 

explain the causes and dynamics of spatial ecosystem patterns cases, and it was necessary to add a finer level biogeographic 

(Li, 2000). However, processes associated with ecosystem unit in the labeling step. In the future, incorporating a much 

function (such as cycling of water, energy, and nutrients finer biogeographic unit than, for example, a continental-scale 

(Bormann and Likens, 1979)), as well as emergent ecosystem subdivision, is recommended.

properties (such as self-organization and directionality (Salt, 

1979)), were not considered as primary delineation elements, 

as these functions and properties are not readily mappable. 

Moreover, this mapping approach is entirely vertical and does Conclusion

not use data on lateral flows (for example, of water, nutrients, 

or energy) associated with key ecosystem processes, again New national classifications and maps were developed 

owing to difficulties in conceptualizing and mapping those for bioclimates, surficial materials lithology, landforms, and 

flows at mesoscales over the entire conterminous United topographic moisture potential index, and these were comStates. Although ecosystem function is indirectly considered bined to map distinct physical environments at the finest 

in the model in certain cases (for example, where fire- spatial resolution yet attempted. These ecosystem footprints 

dependent vegetation occurs on dry, exposed substrates or were then deductively associated with previously classified 

where linear riparian ecosystems form along river corridors), and described ecosystems, and a new map of 419 terrestrial 

it is not included in the geospatial analysis. The method used ecosystems was produced for the conterminous United States 

here to map ecosystem distributions by spatially delineating with a 30-m cell size. This ecosystems map provides an initial, 

and integrating their structure components across geographic comprehensive, and consistent delineation of standardized 

space will be subject to refinement in the future as innovative terrestrial ecosystems across the conterminous United States 

approaches for mapping ecosystem function and processes at a resolution considerably finer than existing ecoregionalizaover large areas are further developed. tions of the area (Omernik, 1987; Bailey, 1996; Commission 

The new national datasets for bioclimates, surficial for Environmental Cooperation, 1997; Ricketts and others, 

materials lithology, landforms, and topographic moisture 1999; Groves and others, 2000).

potential index were produced as initial, robust representations This ecogeographic regionalization approach closely 

of the primary structure elements of ecosystems and are best follows the disciplinary emphasis of ecosystem geography 

considered as rigorous and appropriate input data layers for (Bailey, 1996) and the geoecosystems concept (Huggett, 

geospatial ecosystem delineation, rather than as exhaustive 1995). The approach was more successful in delineating the 

treatments of those themes. Nevertheless, these intermediate larger matrix-forming and large-patch ecosystems than the 

products may be useful for other applications (such as engi- small-patch and linear ecosystems. The same physical envineering, land capability analysis, resource management, and ronment could produce different biotic responses (vegetation 

biodiversity conservation), and their utility for those applica- assemblages), likely because of differences in evolutionary 

tions should be considered and evaluated. history, geographic isolation, and disturbance history. To 

Two very important lessons were learned from this work, separate different ecosystems occurring on similar abiotic 

which need to be considered in future applications of this templates, it was necessary to incorporate a finer grained bioecosystem mapping methodology. First, the use of multiple geographic stratifier than was originally contemplated.

input datasets of variable spatial resolution, although neces- These new ecosystems show considerable promise 

sary to incorporate the best available data, was somewhat for use in studies examining impacts on ecosystems from a 
14 A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

number of sources (for example, climate change, invasive spe- Annette Kulyk, USGS

cies, fire, and land cover change). Not only do they represent Alexa McKerrow, USGS

a standardized geospatial framework for the impact studies, John Mosesso, USGS

but they are also the very entity experiencing the impacts, as Doug Muchoney, USGS

opposed to some other entity or geography (such as watershed, Mark Myers, USGS

land cover class, or pixel). The potential for climate change to Tom Owens, USGS

alter the location and abundance of ecosystems in the future is Richard Pike, USGS

more easily addressed through an understanding of the abiotic Sandra Poppenga, USGS

components that control ecosystem distributions. Similarly, Salvador Rivas y Sáenz, Centro de Investigaciones 

the ecosystems could be useful for studies of the production Fitosociológicas [Phytosociological Research Center]

and value of ecosystem goods and services (benefits), as the Salvador Rivas-Martinez, Centro de Investigaciones 

ecosystems are in fact the source of these benefits. There may Fitosociológicas

be considerable utility in using the ecosystems, which are Barbara Ryan, World Meteorological Organization 

the very service provider units, as a standardized geographic (formerly USGS)

accounting unit in assessments of ecosystem services. Finally, Lisa Scales, USGS

there is much promise in using the ecosystems as a standard Sarah Shafer, USGS

unit for resource management and conservation. Federal agen- Jonathan Smith, USGS

cies with a mandate to manage their land holdings with an Dave Soller, USGS

ecosystem-based management approach, for example, would Jeff Spooner, USGS

find a spatial delineation of the ecosystems in their jurisdic- Mike Starbuck, USGS

tions helpful. Moreover, biodiversity conservationists with an Diane Stephens, USGS

interest in conserving representative examples of all unique Doug Stoeser, USGS

ecosystems (Groves, 2003) may welcome the ecosystems data- Ione Taylor, USGS

set as a source of conservation targets (Redford and others, Alicia Torregrosa, USGS

2003) for planning and implementing conservation programs. Diane True, University of Missouri

Bea Van Horne, USGS

Jim Vogelmann, USGS

Acknowledgments Andrew Weiss, Washington State Department 

of Fish and Wildlife

The authors would like to acknowledge many individuals Stan Wilds, Parallel Inc.

who provided data, advice, method and product reviews, meet- Tom Winter, USGS

ing support, analytical support, editing, and inspiration. We Alberto Yanosky, Guyra Foundation, Paraguay

appreciate the help from colleagues inside and outside the U.S. Paul Young, USGS

Geological Survey (USGS), and names are listed alphabeti- Zhiliang Zhu, USGS

cally below.

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Sayre and others—A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States—Professional Paper 1768