United States Department of Agriculture

Forest Rocky Mountain General Technical Report

Service Research Station RMRS-GTR-382 August 2018

Rangelands on the Edge: Quantifying the 

Modification, Fragmentation, and Future Residential 

Development of U.S. Rangelands

Matthew C. Reeves, Michael Krebs, Ian Leinwand, Dave M. Theobald, John E. Mitchell
Front cover: Rangelands are diverse ecosystems that provide numerous goods and services. Future development of rangeland 

landscapes will benefit from synoptic perspectives.

All Rocky Mountain Research Station publications are published by U.S. Forest Service employees and are in the 

public domain and available at no cost. Even though U.S. Forest Service publications are not copyrighted, they 

are formatted according to U.S. Department of Agriculture standards and research findings and formatting cannot 

be altered in reprints. Altering content or formatting, including the cover and title page, is strictly prohibited.

Reeves, Matthew C.; Krebs, Michael; Leinwand, Ian; Theobald, David M.; Mitchell, John E. 2018. Rangelands on the 

Edge: Quantifying the modification, fragmentation, and future residential development of U.S. rangelands. Gen. 

Tech. Rep. RMRS-GTR-382. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station. 31 p.

Abstract

Rangelands are increasingly urban, subdivided, and fragmented. About 62 percent of coterminous U.S. rangelands 

occur on private land and are at further risk for conversion. This Rangelands on the Edge (ROTE) project improves 

our understanding of the fate of rangelands from historical, present day, and future perspectives by describing human 

modification, fragmentation, and future residential growth projections for rangeland-dominated vegetation. Since preEuropean settlement, some 340 million acres (over 34 percent) of rangelands, particularly in the Great Plains, have been 

converted to alternative land uses, especially intensive agriculture (croplands, pastureland). Approximately 11 percent of 

private rangelands are likely to experience significant increases in housing development over the next 15 years.

Keywords: fragmentation, rangelands, ecosystem goods and services, sustainability, residential development, human 

modification, fragmentation
Authors

Matthew C. Reeves, Research Ecologist, Human Dimensions Program, USDA Forest Service, Rocky Mountain Research 

Station, Missoula, Montana

Michael Krebs, Contract Biological Scientist, USDA Forest Service, Rocky Mountain Research Station, Missoula, Montana

Ian Leinwand, Contract Landscape Ecologist and GIS Analyst, U.S. Geological Survey, Fort Collins, Colorado.

David M. Theobald, Senior Scientist at Conservation Science Partners, and Affiliate Professor, Colorado State University, 

Fort Collins, Colorado

John E. Mitchell, Emeritus Rangeland Scientist, USDA Forest Service, Rocky Mountain Research Station, Fort Collins, 

Colorado

Acknowledgments

Funds to complete this work were provided by the Renewable Resources Planning Act and National Rangeland 

Management leadership. This work was initiated by Drs. Theobald and Mitchell. Dr. Theobald’s graduate student, Ian 

Lienwand, did much of the heavy lifting and created the datasets depicting human modification and fragmentation. Edward 

Butler and Michael Krebs were critical to the success of this work as the primary developers of graphics and figures, 

especially since we tried to maintain some consistency with the Forests on the Edge project. Finally, 1000 Friends of 

Oregon graciously provided access to a picture used in the document.
ii

Contents

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

Implications........................................................................................................................................2

Rangelands Defined ......................................................................................................................................... 5

Historical Extent of Rangelands........................................................................................................................ 7

Human Modification and Fragmentation.............................................................................................9

Projecting Residential Development to 2030 ....................................................................................14

Data Analysis and Aggregation..........................................................................................................18

Watershed Selection Criteria.............................................................................................................20

Top 15 Modified Watersheds.......................................................................................................................... 21

Top 15 Fragmented Watersheds...................................................................................................................... 23

Top 15 Watersheds With Increased Residential Development......................................................................... 23

Key Findings .....................................................................................................................................24

Special Consideration: Rangelands In The East and Piñon-Juniper .....................................................26

Conclusions......................................................................................................................................28

References........................................................................................................................................28
USDA Forest Service RMRS-GTR-382. 2018 1

Introduction

In 2005, the Forests on the Edge project (Stein et al. 2005) (http://www.fs.fed.us/

openspace/fote/housing.html) began producing a series of publications aimed at evaluating the trends and implications of increased residential development on America’s 

private forestland. This effort increased public awareness and understanding of the pressures on and contributions of private forests and the processes associated with increases 

in housing density. Many of the same issues facing America’s private forests are also 

significant factors and driving forces in rangeland landscapes. Rangeland areas across 

the West are undergoing transitions in demography, economics, and ecosystems as residential development is increasingly built outside of cities, suburbs, and towns. This type 

of exurban development produces a footprint that is 5 to 10 times larger than the urban 

footprint. Other factors such as agricultural expansion and energy development also 

contribute to an increasing anthropogenic footprint. This is an important matter because 

rangelands are a major resource worldwide, occupying 65 million km2, or roughly 50 

percent of the land area of the world (Hobbs et al. 2008). Rangelands occupy about 

662 million acres in the coterminous United States and provide food, fiber, clean water, 

biofuels, opportunities for energy development, and critical habitat for numerous imperiled species. Species such as the lesser prairie chicken (Tympanuchus pallidicinctus), 

black-footed ferret (Mustela nigripes), and Sonoran pronghorn (Antilocapra americana 

sonoriensis) depend on rangeland habitats for survival.

Though it is hard to quantify the value of the goods and services that rangelands 

provide, the amount is substantial. Farm cash receipts for cattle and calves in the United 

States exceeded $67 billion in 2016 (NCBA 2016). Direct expenditures for hunting in 

2001 approached $25 billion (IAFWA 2002). Since Euro-American settlement, more 

intensive forms of land use such as cropland, urban areas, and transportation have 

replaced native rangeland systems. The rate of decline of rangeland area has been slow 

but steady due to population increase and urban expansion in the United States (Mitchell 

2000). For example, the Natural Resources Conservation Service estimated that 406 

million acres of rangeland occurred on private rangelands in 2012, a 3 percent decrease 

from 1982 (USDA 2009); this amounted to a decline of about 470,000 acres per year.

Much of the decline in rangeland area is due to land use changes associated with 

exurban development and subdivisions, which arguably constitute one of the foremost 

threats to intact, high-quality wildlife habitat (Theobald et al. 1997). The effects of residential development on rangeland ecosystem goods and services are numerous. The size 

of the total effect of residential development depends on the total area converted as well 

as the timing of the exposure to development activity (Hamer et al. 2006; Polfus 2011). 

The effects of ecosystem fragmentation from residential development are seen through 

nest predation, disruption of wildlife dispersal and movement patterns, structural habitat changes, and effects associated with domestic pets and increased human-wildlife 

conflicts (Glennon and Kretser 2005). Ungulates such as mule deer, elk, pronghorn, and 

bighorn sheep migrate long distances (50–100 km) in the fall and spring (Hoekman et 

al. 2006; Sawyer et al. 2009) but these migration routes are increasingly interrupted by 

energy development, tourism, exurban development, and highway mortality (Berger 

2004; Gude et al. 2007).
2 USDA Forest Service RMRS-GTR-382. 2018

Species that are well-adapted to intensively modified urban environments and 

dependent on human-subsidized resources gradually replace those that are intolerant of 

human modifications. This process is referred to as “biotic homogenization” (McKinney 

and Lockwood 1999), characterized by species tolerant of anthropogenic disturbance 

and influence. These issues have led the researchers to suggest that when development, 

even at low densities, “borders wild or undisturbed lands, a buffer of up to 600 feet 

around the development should be considered as affected habitat” (Odell and Knight 

2001). Other effects of residential development can be more subtle (Odell et al. 2003). 

For example, the effect of anthropogenic noise on wildlife patterns is often overlooked 

despite being important determinants of the types and amount of wildlife that occur in 

an area. Chronic exposure to noise can lead to deleterious physiological and behavioral 

effects such as increased stress levels and decreased reproductive success (McKinney 

and Lockwood 1999). Another subtlety is that ranches comprised mainly of rangelands 

(as opposed to pasturelands) demand little water as compared with the other types of development. Thus, an understanding of how residential development may manifest itself 

in the future is essential to assessing the status of rangelands over the next generation.

Land use changes and resulting human modifications tend to (Stein et al. 2005):

• decrease native fish and wildlife populations and their habitats;

• decrease rangeland health;

• reduce opportunities for outdoor recreation;

• reduce water quality;

• alter hydrology;

• change traditional uses of rangelands;

• decrease production of natural goods and services; and

• increase water consumption.

Implications

Changes in housing density and patterns of human modification and fragmentation 

documented by Rangelands on the Edge have implications for the present and future 

condition and sustainability of goods and services derived from rangelands. Increased 

residential development, human modification, and fragmentation lead to a variety of 

challenging situations, as indicated by the following eight examples. 

1. There could be a decrease in native wildlife populations of rangeland obligates, such 

as sage grouse and pronghorn, owing to decreased wildlife habitat quantity, quality, 

and connectivity; increased mortality and conflicts with humans; and increased 

predation from domestic pets (Balogh 2011).

2. Another impact can be decreased biodiversity, increased prevalence of non-native 

species (Ferreira and Laurance 1997; Meekins and McCarthy 2002), and at some 

level, a complete avoidance of areas by some faunal populations (Hansen et al. 2005).

3. Reduced resiliency and adaptability of species to climate change and limited flow of 

genetics across barriers is another impact. Reduced gene flow, through fragmentation, 
USDA Forest Service RMRS-GTR-382. 2018 3

can isolate populations and decrease genetic diversity through drift and inbreeding 

(Allendorf and Luikart 2007).

4. There could be a decrease in ecosystem goods and services such as food and fiber; 

changes in scenic quality and recreational opportunities can degrade recreational 

experiences.

5. Decreased production of protein from livestock from lands that are often unarable 

is another impact from increased residential development, human modification, and 

fragmentation.

6. An increased likelihood for user conflicts as more people seek use of a decreasing 

land base is very possible. Oftentimes, in the western United States as land ownership 

changes, so do landowner views on allowing easement across private land to provide 

access to public land. In this manner, reduction in access to rangeland landscapes 

is therefore not limited to just the mere footprint of the residential development or 

private land itself.

7. Conservation and management of faunal populations through hunting opportunities 

can be paired by fragmentation of open range. In extreme cases, a single new 

dwelling or change in land ownership can reduce recreational access to tens of 

thousands of acres of public land. Figure 1 demonstrates how development can 

directly impact recreational opportunities and disrupt ungulate movements between 

seasonal ranges (Harden et al. 2005). This suggests that procuring easements to 

maintain access to public land may enhance or maintain recreational opportunities for 

the American public at large.

8. There can be a potential for greater wildfire ignition due to residential development 

and concomitant restrictions in management options for mitigating threats to 

rangelands (Russell and McBride 2003).

Rangelands provide critical habitat for numerous species, including some iconic western 

species such as sage grouse, black-footed ferret, and Rocky Mountain bighorn sheep 

(photos courtesy of Matt Reeves and Lane Eskew).
4 USDA Forest Service RMRS-GTR-382. 2018

While Forests on the Edge (FOTE) developed a series of informative publications, 

the effort was generally focused on residential development on forestlands. Concern 

about the effects of modification on America’s rangelands has also risen in recent years 

in recognition that fragmentation of natural ecosystems alters ecological processes, 

leads to declines in biodiversity, and reduces the ability of landscapes to adapt to climate change (Theobald et al. 2012). The present effort called Rangelands on the Edge 

(ROTE) was inspired by FOTE and, when combined with FOTE, enables a more complete understanding of the landscape scale perturbations to America’s rangelands and 

forestlands.

Although not officially affiliated with FOTE, the ROTE project is nevertheless 

complementary to it. In light of this, we attempted to maintain similarities in report 

format and analytical structure to FOTE, so that these two projects can be viewed in 

tandem to provide a more complete, consistent, and seamless picture of landscape-level 

threats to wildlands of the United States. While FOTE originally focused on residential 

development, the current report provides an expanded analysis of the degree to which 

human modification has changed rangeland landscapes. To accomplish this goal, we 

pursued the following objectives: (1) estimate the historical (pre-European settlement) 

extent of rangelands to provide a baseline of change; (2) quantify the degree of human 

modification from a database on detailed land use patterns collected from interpretation 

of aerial photography; (3) analyze the loss and fragmentation of rangeland vegetation 

Figure 1—The trail shown in the aerial 

photographs is no longer accessible, which 

substantially reduces the variety of goods and 

services that could be enjoyed in the future 

on this landscape. Access was apparently 

prohibited around 2008. By identifying 

key parcels, such as this one, stakeholders, 

planners, and managers can collaboratively 

and proactively procure more rigorous modes 

of easement for maintaining access to public 

lands.
USDA Forest Service RMRS-GTR-382. 2018 5

and; (4) estimate the amount of additional residential development on U.S. rangelands 

by 2030.

It is important for the reader to recognize that here we focused on watersheds that 

are dominated (≥50 percent of vegetated area) by rangelands while the FOTE project 

focused on forest-dominated watersheds. In some cases, a watershed might have a 

significant area of rangeland but is addressed in the FOTE project (e.g., see page 12 of 

Stein et al. 2007). As a result, in an effort to complement FOTE, we left out watersheds 

that have already been evaluated and focused on those watersheds dominated by rangelands that were not presented in the FOTE project. 

This work aids identification of watersheds whose sustainable production of natural goods and services is potentially compromised; it also supports future analyses to 

identify imperiled habitats, as well as intact lands acting as corridors for species dispersal. This is important because nationally consistent data describing these conditions are 

lacking and information is needed to improve our understanding of the present character 

of rangeland landscapes. These data enable a large number of questions to be explored 

and answered, but this report only provides a cursory and not a definitive analysis. As 

a result, readers are encouraged to request these data and use them for regional studies. 

These data are available from the authors and interested parties should contact the lead 

author.

Rangelands encompass many vegetation types and “rangeland” is viewed as a land cover and not a land use. 

Using the National Resources Inventory (NRI) definition discussed in this report, we estimate 

from Reeves and Mitchell (2011) that there are about 662 million acres of rangelands in the 

coterminous United States.

Rangelands Defined

Many definitions of rangelands exist, but generally speaking, rangelands are a 

land type primarily supporting herbs, shrubs, and grasses that provide food, fiber, clean 

water, biofuels, and cultural heritage and recreation opportunities (table 1). Table 1 

shows the contrasting definitions from the Bureau of Land Management (BLM), the 

U.S. Forest Service through the Forest Inventory and Analysis (FIA) Program, and 

the Natural Resources Conservation Service (NRCS) through the National Resources 

Inventory (NRI). Although several definitions of rangelands are used by U.S. land 

management agencies (provided in table 2), here we adopt the rangeland definition developed by the NRCS. Oftentimes, grazing land is incorrectly used synonymously with 

rangeland. Grazing lands include rangelands but also many other kinds of land types 

including pastures and agricultural landscapes, which provide a variety of feedstuffs for 
6 USDA Forest Service RMRS-GTR-382. 2018

Table 1—Examples of ecosystem goods and services and the benefits they provide.

Rangeland ecosystem

good or service Benefit

Economic Environmental Social/cultural

Forage production 

(for livestock 

consumption)

- Sale or lease of feed for grazing

- Hay production

- Landscapes for biodiversity, 

native species

- Soil stability

- Clean air and water

- Some crops, e.g., nitrogen 

fixers, enrich soil

- Open space

- Rangeland-dependent 

rural communities

Beef and lamb 

production (food for 

human consumption)

- Sale of meat and fiber products

- Ranching operations

- Economic base for ranching 

communities

- See forage production above - Satisfaction people 

enjoy in ranching as a 

way of life

- Open space

Fishing and hunting - Sales of licenses, gear, guide 

services

- Access rights (to fish or hunt) on 

private or public lands

- Promotion of healthy wildlife 

populations

- Biodiversity maintenance

- Control of hunted wildlife

- Pleasure involved in 

fishing and hunting

- Watchable wildlife

Clean water - Satisfaction of household, 

agricultural, and industrial needs

- Sale of bottled water

- Income from water-based 

recreation

(swimming, boating, fishing)

- Habitat for fish and other 

aquatic organisms

- Drinking water for wildlife

- Rejuvenation of channels and 

riparian areas via sediment 

transport and deposition, creating 

bare soil for germination, etc.

- Aesthetic qualities of 

unpolluted water bodies

- Pleasure people 

derive from water-based 

recreation

Wind - Capture and sale of wind energy - Dispersal/dilution of pollutants

- Pollination of wind-pollinated 

plants

- Seed dispersal

- Sense and smell of 

gentle breezes

Wood - Sale of fuelwood and fenceposts - Wildlife habitat

- Spatial diversity in litter, soil 

nutrients, etc.

- Warmth, sight and smell 

of campfires

Seeds and plant 

materials

- Seeds and cultivars for forage 

and land restoration

- Genetic diversity - Human values relating 

to restored rangelands

domestic and wild ungulates. Further, grazing is not a requisite for a rangeland designation because, here, rangelands are viewed as a vegetation cover type rather than a land 

use. Rangelands also occupy many vegetation types. The rangeland statistics mentioned 

in this document consistently conform to the NRI definition unless otherwise noted. 

In addition to defining rangelands, it was necessary to identify where these rangelands 

exist in the coterminous United States. It follows that estimating where rangelands are 

depends on the definition used to identify them.

Here we used the geospatial data describing the extent of rangelands from Reeves 

and Mitchell (2011). Reeves and Mitchell (2011) estimated the extent of U.S. rangeland 

by applying the two contrasting FIA and NRI definitions of rangelands to geospatial 

data describing existing and historic vegetation. The difference between these two 

definitions resulted in a discrepancy of about 62 million acres of more rangeland using 

the NRI definition. In ROTE, we adopted the NRI rangeland definition and associated 

rangeland map from Reeves and Mitchell (2011), which is shown in figure 2. Figure 2 

demonstrates that rangelands of the coterminous United States are primarily found west 
USDA Forest Service RMRS-GTR-382. 2018 7

Table 2—Rangeland definitions used by the USFS FIA and NRCS NRI programs. Also included is the definition adopted by 

the BLM.

Agency Definition

USDA Forest Service (through the FIA 

Program)

Rangeland: “Land primarily composed of grasses, forbs, or shrubs. This 

includes lands vegetated naturally or artificially to provide a plant cover 

managed like native vegetation and does not meet the definition of pasture. 

The area must be at least 1.0 acre in size and 120.0 feet wide,” (USFS 2011, 

p. 93). 

Natural Resources Conservation Service 

(through the NRI Program)

Rangeland: “A land cover/use category that includes land on which the climax 

or potential plant cover is composed principally of native grasses, grass-like 

plants, forbs or shrubs suitable for grazing and browsing, and introduced 

forage species that are managed like rangeland. This would include areas 

where introduced hardy and persistent grasses, such as crested wheatgrass, 

are planted and practices such as deferred grazing, burning, chaining, 

and rotational grazing, are used with little or no chemicals/fertilizer being 

applied. Grasslands, savannas, many wetlands, some deserts, and tundra are 

considered to be rangeland. Certain low forb and shrub communities, such as 

mesquite, chaparral, mountain shrub, and pinyon-juniper, are also included as 

rangeland,” (NRCS 2015). 

Bureau of Land Management Rangeland: “Land on which the indigenous vegetation (climax or natural 

potential) is predominantly grasses, grass-like plants, forbs, or shrubs and is 

managed as a natural ecosystem. If plants are introduced, they are managed 

similarly. Rangelands include natural grasslands, savannas, shrublands, many 

deserts, tundra, alpine communities, marshes, and wet meadows,” (SRM 1998, 

p. 23).

of the 95th meridian. This line corresponds to a level of aridity that generally favors 

production of grasses and shrubs over trees. In the coterminous United States, there are 

about 662 million acres (Reeves and Mitchell 2011), which compares with the NRCS 

estimate of 406 million acres of rangeland that occurred on non-Federal lands in 2012, a 

3 percent decrease from 1982 (USDA 2009).

Further, figure 2 shows that privately owned rangelands represent about 62 percent 

(USDA 2009) of America’s rangelands while the remaining 256 million acres are owned 

by a consortium of Federal, State, and local governments (Reeves and Mitchell 2012). 

Tribal lands are not included in the public land data statistics derived in this project 

since they are sampled during the NRI private land rangeland survey (Ken Spaeth, 

Rangeland Management Specialist, Natural Resources Conservation Service (NRCS) 

personal communication 27 February 2014). The classes used for determining ownership to develop figure 2 are found in table 3.

Historical Extent of Rangelands

To generate a map of historical rangelands (roughly pre-European settlement; the 

NRI definition was applied here), Ecological Systems (Comer et al. 2003) were used. 

Rangeland ecosystems were identified from the Biophysical Setting (BpS) layer from 

the LANDFIRE database (Rollins 2009) using the definition adopted by the National 

Resources Inventory (USDA). According to this definition, found in table 2, rangeland 

systems are those that, given pre-Euro-American settlement disturbance regimes, would 

have generally maintained less than 25 percent canopy cover by trees, either due to 

natural disturbances or limits to tree growth.
8 USDA Forest Service RMRS-GTR-382. 2018

Examples of these systems include: semi-desert grasslands, tall-grass prairie, some 

Florida flatwood sites (i.e., sites with summer fire regime and high lightning strikes 

producing savannah-like conditions with tree cover generally <25 percent), Great Basin 

piñon-juniper, and sagebrush steppe. Mapping the hypothesized historical extent of 

rangelands was a necessary first step because it enables estimates of total human modification of rangelands nationwide by comparing present versus historical distribution. The 

estimated historical extent of rangelands in the coterminous United States is found in 

figure 3. As depicted in figure 3 rangelands once extended through the Midwest and upper Midwest and also occurred extensively in the southeastern United States, especially 

in Florida. The widespread occurrence of historic rangelands in Florida is a consequence 

of the summer fire regime and extremely high fire return intervals, which often created 

savannah-like conditions where tree cover was often less than 10 percent. Presently, 

forest management encourages forest cover in excess of 10 or even 25 percent, which 

causes many of these lands to be considered forests or “afforested rangeland” as indicated in Reeves and Mitchell (2011).

Figure 2—Location of private and public rangelands, non-rangelands, and urban areas. The “public” versus “private” 

ownership designations are not completely straightforward. 
USDA Forest Service RMRS-GTR-382. 2018 9

Table 3—This table documents how the PADUS data were characterized for the purposes of developing figure 2. Most 

assignments were based primarily on the Owner Type attribute and secondarily on the Manager Name for a couple of 

categories according to the following: PADUS_USGS version 1.4 metadata is located here: https://gapanalysis.usgs.gov/

padus/data/metadata/. 

Owner type (primary) Manager name (secondary) Assignment

Territorial N/A -99 Territorial

Federal N/A 0-Public

American Indian lands N/A 1-Private

Designation N/A 0-Public

Local government N/A 0-Public

State N/A 0-Public

Joint (except for NGO, Private, Unknown 

where Private was assigned) (see 

below)

0-Public

District N/A 0-Public

Unknown (except for NGO, Private, Unknown 

where Private was assigned) (see 

below)

0-Public

NGO N/A 1-Private

Private N/A 1-Private

Joint (included only NGO, Private, and 

Unknown)

1-Private

Unknown (included NGO, Private, and 

Unknown)

1-Private

Human Modification and Fragmentation

In this study, human modification is defined as the degree to which an activity at a 

location modifies an ecological system including the spatial extent (Theobald 2013). To 

estimate human modification for the coterminous United States, interpretation of land 

cover from high resolution (~1-m) color aerial photography from the National Aerial 

Imaging Program (NAIP) was used as the primary source. Leinwand et al. (2010) conducted this work using approximately 6,000 samples drawn from a spatially balanced 

network of random locations. At each sample, a 600 m2 quadrangle was placed over the 

NAIP imagery and trained interpreters collected land use data using a 10-m2 minimum 

mapping unit. At each sample location, three types of features were discerned and 

digitized by trained interpreters using an established protocol (Leinwand et al. 2010). 

The features were: (1) the “footprint” of buildings and structures; (2) human-modified 

land cover (e.g., agricultural fields and parking lots), and; (3) linear features (e.g., roads, 

irrigation ditches, utility lines).

Polygons of land cover that had either been converted to an anthropogenic 

land cover (e.g., house, road) or sustained substantial human modification (e.g., 

mowed lawn) were merged to create a geospatial depiction of “human-modified land 

cover” (HMc) (Leinwand et al. 2010). The HMc polygon layer was then converted 

to a raster layer (90-m resolution) representing the proportion of each cell that was 
10 USDA Forest Service RMRS-GTR-382. 2018

Figure 3—Estimated distribution of rangelands prior to Euro-American settlement, adapted from Reeves and Mitchell (2012).

Fragmentation differs depending on the resource being evaluated. Energy development and agricultural 

development are two sources of fragmentation beyond residential development. Wildlife species will respond 

differently to these types of disturbances. What affects one species may be less impactful to another.
USDA Forest Service RMRS-GTR-382. 2018 11

human-modified. Raster cells that were within the chip boundary were used as sample 

points, resulting in roughly 140,000 sample points representing values of HMc. We randomly selected 90 percent of these points to construct a regression model and reserved 

10 percent for model validation.

After characterizing HMc at 6,000 locations, a classification and regression tree 

(CaRT) modeling approach (Friedl and Brodley 1997) was used to extrapolate HMc for 

all 662 million acres of rangelands. This approach was chosen because the distribution 

of our response and many of the input variables were non-parametric. CaRT approaches 

also are able to handle the nonlinear relationships and complex high-order interactions 

we anticipated in modeling complex land use patterns (De’ath and Fabricius 2000).

CaRT analysis was conducted using the cv.tree function in S-Plus statistical package 

(Insightful Corporation, Seattle, Washington). The resulting estimated extent of HMc 

is found in figure 4. As depicted in figure 4, a broad swath of rangelands, stretching 

from the entire eastern halves of north and South Dakota, all the way through northern 

Texas, have experienced total conversion to other land uses. Other areas experiencing 

such conversions include the western half of Minnesota, the majority of rangelands once 

found in Iowa and Illinois, and much of the Gulf Coast.

Figure 4—Extent and magnitude of human-modified land cover (HMc), aggregated to rangeland-dominated watersheds in the 

coterminous United States.
12 USDA Forest Service RMRS-GTR-382. 2018

Table 4 exhibits the explanatory variables used in the regression model, including 

land cover, topography, soils, roads, land use, public ownership, housing density, and 

geographic location. To create a spatially explicit representation of our models, we converted the cv.tree output into a series of if-then-else map algebra statements in ArcGIS 

9.3.1 (ESRI, Redlands, California).

While this modeling approach enables direct quantification of human modification, it does not, by itself, reveal extent and magnitude of loss since pre-Euro-American 

settlement. Instead, quantifying the extent of historical rangeland that has been lost due 

to human activities associated with intensive land uses was accomplished by combining 

HMc with the historic extent of rangeland vegetation and the National Land Use Dataset 

created by Theobald (2014). Understanding the extent to which human modification has 

altered landscapes is only part of the story and perhaps even less meaningful when using 

it to estimate fragmentation.

To understand and quantify how human modification has fragmented rangelands, 

we measured the distance from human-modified areas into the interior of rangeland 

“patches” with GISFrag (Ripple et al. 1991; Theobald 2003). This approach provides a 

spatial depiction of fragmentation where longer distances indicate a more contiguous, 

less fragmented pattern of rangelands. Note that our approach avoids the challenge of 

arbitrarily defining a threshold for patch size, which has been widely discussed for forested ecosystems (e.g., Kupfer et al. 2006) but is even more problematic for rangeland 

ecosystems (Hobbs et al. 2008). We removed small groupings of rangeland cells (<15 

acres) to reduce the effect of very small patches of rangeland that often result from 

artifacts of remote sensing classification. Fragmentation was computed using HMc 

thresholds of 50 percent. For example, in the case of quantifying fragmentation using 

the 10 percent threshold, at each pixel, the fragmentation algorithm searches outward to 

find the next pixel that is at least 10 percent modified and calculates the Euclidean distance between the cells. This is just one approach to estimating landscape fragmentation 

among numerous others. The estimated extent of fragmentation, using this approach, is 

found in figure 5. As shown in figure 5, patterns of fragmentation are similar to those 

of modification suggesting that large swaths of rangeland have experienced near total 

conversion to other land uses.

A notable caveat to these data describing modification and fragmentation exists. 

These data represent the landscape circa 2010 and it is possible that other significant 

modifications and resulting fragmentation may have occurred since that time. As a 

result, developing a more updated depiction of landscape conditions requires new data 

describing such activities as new breakings (where native prairie is plowed for agricultural purposes) and energy development with associated infrastructure such as roads as 

well as well pads.
USDA Forest Service RMRS-GTR-382. 2018 13

Table 4—A list of explanatory variables used to estimate human modification of cover in rangelands (HMc).

Input type Description Processing

Geographic

Travel time (minutes) to population centers 

≥100 km, 10 km, 1 km

Calculate cost distance from US Census places with 

population ≥100 km, 10 km, 1 km, using cost weights on 

transportation infrastructure (Esri Streetmap 2006) based on 

speed limit and slope (270 m) 

U.S. subregion from ESRI State layer Dissolve State polygons into subregions and rasterize at 90 m 

Housing density Block housing density estimate for 2000 Resampled SERGoM (Theobald 2005) from 90 m to 100 m 

resolution

Land cover

Major land cover types from Nature Serve 

Ecological Systems Nature Serve Land Cover at 90 m resolution

Percent impervious surface

Impervious surface model developed from CaRT analysis 

based on data collect from sample chips. (Theobald et al. 

2009; Theobald et al. in prep.)

Land use Oil and gas wells

Converted active wells using 1 km radius kernel density 

function, updated using presence of active wells (Copeland et 

al. 2009; Leinwand 2010)

National Land Use Dataset (90 m) Theobald 2014

Ownership

General land ownership from protected area 

database by class

Rasterized PAD-US v1.1 (CBI Version) polygons to general 

ownership classes (i.e., Private, USFS, BLM, Other Federal, 

State, Regional/ Local Gov., NGO, BIA) at 90 m resolution

Public or private land ownership Dissolved ownership into public and private classes rasterize 

to 90 m resolution 

Road

Road class (highway, secondary, local, other) Rasterize Esri Streetmap 2006 by road class

Roaded area within 270 m ESRI Streetmap converted to 30 m, then Euclidean Distance 

tool out to 270 m

Road density (km/km2) within 1 km kernel Density tool, used 1,000 meter moving window, kernel 

density

Human use by traffic volume (number of 

people/cars assuming time-decay function) Theobald 2008

Soil

Soil index variables (1 = well drained to 4 = 

poorly drained)

Rasterized State Soil Geographic (STATSGO) Database 

polygons to 90 m resolution based on soil attributes, https://

sdmdataaccess.nrcs.usda.gov/ accessed 20 February 2018.

Annual flood frequency (1 = frequent (> 50% 

chance); 2 = occasional (5–50% chance); 3 = 

rare (<5% chance)

Available water capacity (AWC)

Clay content of soil (% soil <2 mm)

Soil index variable (1 = well drained to 7 = 

poorly drained)

Hydric soil indicator (1 if hydric)

Soil erodibility k-factor

Liquid limit (% moisture by weight)

Organic matter content (% by weight)

Permeability rates (inches/hr)

Total thickness of all sampled soil layers (in)

Topographic

Digital elevation model from USGS NED 

(30 m) Upscaled (mean) to 90 m from 30 m

Slope (degrees) Slope computed at 30 m, upscaled (mean) to 90 m

Topographic Position Index (Weiss 2000) Computed at 90 m
14 USDA Forest Service RMRS-GTR-382. 2018

Projecting Residential Development to 2030

In general, the overall extent of the privately owned U.S. rangeland base has 

slowly decreased by 4 percent from 1982 to 2012. However, the loss has not been 

distributed evenly and there are hotspots of residential development that must be addressed to present a complete picture of the situation. In addition, the total extent of 

residential development is perhaps less important to sustaining rangeland goods and 

services than where and how the development is occurring. To aid our understanding of this situation, the final spatially explicit dataset produced here represents a 

projection of residential housing development to 2030. The process for developing 

these data is described in Theobald (2005). Here, we provide an abbreviated review 

of methods to enable a cursory understanding of how the projections of residential 

development were made. Residential development was projected across the landscape, 

to the year 2030, using the Spatially Explicit Regional Growth Model (SERGoM; 

Theobald 2005). SERGoM is a hierarchical (national to State to county) deterministic 

Figure 5—Extent and magnitude of fragmentation, aggregated to rangeland-dominated watersheds in the coterminous United 

States.
USDA Forest Service RMRS-GTR-382. 2018 15

Residential development creates new 

kinds of landscapes for both humans 

and animals. Sometimes residential 

development can aid the dispersal and 

establishment of invasive species such 

as cheatgrass. When new residential 

development occurs in areas of migration 

corridors, sometimes conflict can occur 

providing opportunities for managers and 

communities to collaborate to maintain 

and facilitate regional patterns of wildlife 

movement (photos courtesy of Joe Riis, 

Matt Reeves, and Perry Backus).

model that calculates the number of additional housing units needed in each county 

to meet the demand specified by population projections, based on the ratio of housing 

units to population (downscaled from census tract to block). Housing units are spatially allocated within a county in response to the spatial pattern of land ownership, 

previous growth patterns, and travel time accessibility. The model is dynamic in that 

as new urban core areas emerge, the model recalculates travel time from these areas.

In the first step, the number of new housing units in the next decade is forced to 

meet the demands of the projected county-level population. There is significant variability in the population per housing unit ratio (area-weighted mean = 2.509, SD = 

2.383), so that in the 2000 Census, 440 counties had <2.0 people/unit and 70 counties 

<1.5 people/unit. Rather than using a single nationwide conversion factor, population 

growth was converted to new housing units by the county-specific housing unit per 

population ratio for 2000.

The second step was to compute a location-specific average growth rate from the 

previous to current time step (e.g., 1990 to 2000). These growth rates were computed 

for each 100-m cell using a moving neighborhood (radius = 1.6 km). For each State, 

the average growth rate for each of 16 development classes was quantified. These 16 

classes were found by overlaying four density classes (urban, suburban, exurban, and 

rural) with four accessibility classes measured as travel time (number of minutes one 

way) from the nearest urban core (see below): 0–10, 10–30, 30–60, and >60 minutes. 
16 USDA Forest Service RMRS-GTR-382. 2018

Growth rates averaged over the classes generated from the housing density and accessibility patterns that reflect the previous time step were then joined to a map that 

depicts the current time step housing density and accessibility pattern. Because these 

classes and rates are computed locally, both within-county heterogeneity and crossboundary patterns can be captured. This allows rates of growth to vary across the 

nation, across a region, and even within a county, and does not assume stationarity. 

The distribution of new housing units was adjusted according to accessibility to the 

nearest urban core. That is, growth typically occurs at locations on the urban fringe. 

Accessibility from all developable land to the nearest urban core was computed—

based not simply on straight-line distance, but in terms of minutes of travel time from 

a location along the main transportation network (major roads and highways) to the 

nearest urban core. An urban core area is defined here as a contiguous cluster (>100 

ha) at urban housing density, but alternative definitions could be developed. Because 

it is difficult to forecast when roads will be enlarged or where new roads will be 

constructed, travel time to move across locations that are not on the network of major 

roads was modeled as an average travel time of 15 miles per hour (24.2 km/hour). 

Travel speed was assumed to be 70 mph (113 km/hour) on interstates, 55 mph (89 km/

hour) on highways, and 45 mph (72.4 km/ hour) on major county roads. An accessibility surface was then created from a cost weight based on travel time from urban areas 

along major roads. New housing units are allocated as a function of the accessibility 

surface. Here, the allocation is based on the distribution of new units realized in the 

previous decade, but other weightings could be applied to develop denser or more dispersed growth scenarios. Accessibility is computed at each decadal time step because 

new “islands” of urban core may emerge over time. This allows complex growth patterns to be modeled, and it incorporates the emergent nature of development patterns. 

The third step was to add the map layer of new housing density to the current housing 

density (i.e., adding new housing units to 2000 housing density). SERGoM assumes 

that housing density cannot decline over time. This is a reasonable assumption when 

examining patterns of expansion in suburban and exurban areas. However, this current 

implementation is limited when investigating urban-centric processes, such as urban 

decay or expansion of commercial land use into urban and suburban residential areas. 

The result of implementing SERGoM in these three steps provides estimated growth 

in percent change from the baseline of 2000 to 2010. This baseline was used since 

the original projections were completed in 2011 and are being published here, in this 

context, for the first time. The estimated intensity and extent of projected residential 

development is found in figure 6.
USDA Forest Service RMRS-GTR-382. 2018 17

Figure 6—Projected percent increase in residential development in rangeland watersheds across the United States by 2030. 

Lower left inset indicates projected residential development for the area near Phoenix, Arizona, at the pixel-level (90 m). 

Watershed-level percent class breaks are as follows: Low: >0–1.7; Medium: 1.7–5.8; and High: 5.8–13.3. Inset pixellevel percent class breaks are as follows: Low: 1–10; Medium: 10–30; and High: 30–91. Likewise, the upper right inset 

provides an example of a watershed, encompassing much of the Wasatch Front, where significant residential development 

is expected to occur but the watershed does not meet the threshold criteria of 50 percent of the area being dominated by 

rangeland vegetation.

Rangelands exhibit land use strategies 

becoming increasingly influenced by housing 

development that competes with more 

traditional uses (photo: Carrie MacLaren, 

courtesy of 1000 Friends of Oregon).
18 USDA Forest Service RMRS-GTR-382. 2018

Data Analysis and Aggregation

Data describing human modification, fragmentation, and increased residential development by 2030 were produced for all coterminous U.S. rangelands at 90-m spatial 

resolution. All these data were subsequently aggregated to watersheds in an effort to be 

consistent with the analysis framework found in FOTE. An example of these data, at the 

pixel level, can be seen in figure 7, which depicts the estimated HMc at every pixel considered to be rangeland. These estimates of HMc clearly show the extent of conversion 

of rangelands to other land uses, especially agriculture.

Here, in the inaugural ROTE report, we present a snapshot of these data to facilitate communication of the ideas they foster. Where appropriate, linkages between 

FOTE and ROTE analysis methods were maintained. Analysis of the ROTE data was 

conducted in a similar manner to FOTE in terms of display and aggregation. Both 

FOTE and ROTE sought to characterize results in relation to watersheds of the United 

States, recognizing the contributions of wildlands to providing clean and abundant water 

resources. In accordance with this understanding, results were aggregated to watershed—and State—levels using the following data sources:

Figure 7—Extent and magnitude of human-modified land cover (HMc), displayed at a spatial resolution of 90 m. Pixel-level 

data such as these were also developed for fragmentation and projections of residential development. 
USDA Forest Service RMRS-GTR-382. 2018 19

1. Fourth-level watershed boundaries defined by Steeves and Nebert 1994 (sixth code 

hydrologic unit codes, i.e., HUCs)

2. Rangeland extent (Reeves and Mitchell 2011)

3. Human modification (Theobald 2013)

4. Rangeland fragmentation (Theobald 2013)

5. Projected residential development to 2030 (Theobald 2005)

Several key concepts are important for the reader to understand. All analyses were 

done for rangeland landscapes only. Additionally, in the case of evaluating projected 

rangeland development, only the “buildable” areas located within rangeland landscapes 

were identified. To illustrate, consider the case of a very large watershed with a high 

proportion of rangelands under Federal ownership with a few urban areas (like many 

areas in the western United States). The projected residential growth in the Federal 

ownerships will be zero and when the mean of projected residential development is 

computed, the watershed will appear to exhibit almost no growth at all. This is misleading. Likewise, the same will be true in watersheds with a high proportion of private land 

dominated by complex terrain that may be unsuitable for building. To account for these 

issues, it is important to understand the method and implications of how values of “0” 

were dealt with in the ROTE analysis framework. For analyzing human modification 

and aggregating to watersheds, the values of zero were left intact. This has implications 

for interpretation of the results. By allowing values of zero (no modification) to influence watershed-wide results, the question most appropriately answered with this process 

is, “Across the entire extent of a watershed, regardless of jurisdiction, what is the 

average amount of modification?” The result of this analysis is shown in figure 4. This 

is different from asking the question, “On lands that are modified, what is the average 

amount of modification?” This would yield a different result, especially in watersheds 

exhibiting a large proportion of public lands where modification is likely to be considerably less than watersheds dominated by privately owned rangelands. 

The analysis procedure and assumptions are the same for analysis of fragmentation 

where zeroes were used for analysis purposes since areas of “zero” modification theoretically represents robust corridors for species dispersal. The result of this fragmentation 

analysis is found in figure 5. In contrast, the watershed level analysis of residential 

development did not include areas of “zero or no development.” So the correct question 

to be answered using this framework is, “On lands where residential development is 

expected to increase, what is the expected amount of increase across each watershed?” 

The assessment of projected residential development, at the national level, is found in 

figure 6 while the results are summarized to States and displayed in table 5.

Two other points are critical to understand about the analysis portrayed in figure 

6. First, many of the areas of the country that are experiencing high residential growth 

in areas where rangelands are common (such as the Wasatch Front near Salt Lake City, 

Utah, and Rocky Mountain Front near Denver, Colorado) are not evaluated in figure 6. 

This occurs because the watersheds they belong to are dominated by forest (i.e., <50 

percent rangeland), or the amount of urban land cover prevents rangelands from being 

the dominant land cover. Hence, readers are encouraged to obtain the data describing the 
20 USDA Forest Service RMRS-GTR-382. 2018

increased residential growth by 2030 from the lead author to perform their own analyses 

to meet the needs of other projects. 

Watershed Selection Criteria

Several strategies were used to determine which watersheds should be used to 

aggregate HMc, fragmentation, and projected housing development. Unlike FOTE we 

did not differentiate between public or private lands for the purposes of characterizing 

the extent of modification. It is logical to expect, however, that most (but not all) of 

the modification and resulting fragmentation estimated across rangelands is found on 

privately owned lands.

Table 5—Historic area, modified area, projected residential development by 2030, and fragmentation for States where 

rangelands occupy 1 million acres in a State. Note that not all States are included in the analysis because they do not meet 

the criterion of possessing a watershed dominated by ≥50 percent rangeland. Here the fragmentation metric represents the 

distance between modified pixels where modification is ≥50 percent.

State Historic area Modified area

Projected additional 

residential 

development by 

2030

Fragmentation (average 

distance between 

modified pixels)

- - - - - - - - - - - - - - - - - - -Acres * 1,000- - - - - - - - - - - - - - - - - - - - - - - - -Miles- - - - - -

Arizona 66,974 3,587 364 8.45

California 70,874 13,319 1,354 3.8

Colorado 45,916 13,494 256 1.37

Florida 12,096 4,801 438 0.79

Iowa 23,108 20,219 93 0.01

Idaho 29,763 5,885 77 3.16

Illinois 20,247 17,684 188 0.01

Kansas 46,799 35,102 115 0.03

Minnesota 21,708 18,233 116 0.05

Missouri 15,027 10,397 132 0.01

Montana 67,604 16,540 28 1.43

Nebraska 47,538 26,579 74 0.43

New Mexico 68,636 5,969 137 5.31

Nevada 67,266 1,858 161 8.64

North Dakota 43,214 30,478 29 0.11

Oklahoma 28,851 17,124 125 0.16

Oregon 34,488 5,014 80 3.09

South Dakota 45,924 23,716 46 0.4

Texas 128,547 46,551 1,129 1.72

Utah 38,748 2,845 166 6.29

Washington 17,249 7,530 102 0.78

Wisconsin 11,423 7,002 146 0.04

Wyoming 49,306 4,092 13 2.13

Total 1,001,306 338,019 5,369 NA
USDA Forest Service RMRS-GTR-382. 2018 21

For communicating the primary elements of the study, we chose to use watersheds 

that were dominated by rangelands, where rangelands occupy ≥ 50 percent of the area. 

To determine this quantity, the fractional amount of existing vegetation occupied by 

rangelands in each watershed was estimated from Reeves and Mitchell (2011, 2012). 

Since fragmentation, human modification, and projected residential development are 

produced at a 90-m spatial resolution, they can be aggregated to any summary unit 

that makes sense for a given study. In addition, for figures 3, 4, and 5 summarizing 

watershed attributes for each State, top-ranked watersheds were selected that had the 

majority (>50 percent) of their area within the represented State. This was done to avoid 

depicting watersheds in one State that had larger overlapping areas in another. It more 

fairly characterizes watersheds with the most modified, most fragmented, and highest 

projected increase in residential development within each State. This is necessary because some watersheds cover multiple States. 

Top 15 Modified Watersheds

At a watershed scale, patterns of human modification, displayed in figure 8, follow 

an increasing gradient of modification from west to east reflecting increasing agricultural land use. Within these patterns, identification of the top 15 most modified watersheds 

Figure 8—Top 15 most modified watersheds dominated by rangelands.
22 USDA Forest Service RMRS-GTR-382. 2018

required selection criteria yielding only those watersheds currently occupied by ≥50 

percent rangeland vegetation. The resulting analysis revealed that the most highly modified rangeland-dominated watersheds are those with a high agricultural component in 

the Central Plains region.

In addition to this analysis, the most modified rangeland-dominated watershed in 

each State is identified in figure 9. Although private ownership was not used as a selection criterion for identifying the watersheds with the greatest modification, as indicated 

in figure 2, the most modified rangelands occur in regions where private ownership 

dominates the landscape. In addition, the most highly modified watershed in each State 

invariably occurs in areas dominated by agricultural land uses.

This assessment could be improved by accounting for the impacts of invasive 

species as agents of permanent change. Invasive species such as cheatgrass (Bromus 

tectorum), knapweed (Centaurea spp.), and feral faunal species such as wild horses and 

burros (Equus spp.) and pigs (Sus spp.) are causing ecological harm (e.g., Cushman et 

al. 2004; Downing and Snell 2016 ) and slowly and steadily reducing the likelihood 

of rangelands to maintain production of goods and services in the future. This type of 

modification, however, is beyond the scope of this report but methods such as those 

employed by Reeves and Baggett (2014) could be used with relatively high-resolution, 

remotely sensed data to estimate degradation due to faunal invasive species.

Figure 9—Most modified (highest amount of average human-modified cover) rangeland-dominated watershed in each State. 
USDA Forest Service RMRS-GTR-382. 2018 23

Top 15 Fragmented Watersheds

One might expect patterns of fragmentation to mirror those of human modification, since a result of the analyses and assumptions employed here required lands to be 

modified (≥50 percent) before they can be fragmented. However, figure 10 reveals that 

regions may be only slightly modified but still exhibit a high degree of fragmentation.

The relationship between modification and fragmentation depends on how the 

modifications are juxtaposed with one another. The present analysis reveals that, as 

landscapes approach 40 percent modification, they become almost fully fragmented. 

Fragmentation based on the modification threshold of ≥50 percent was used for analysis 

and display purposes. Fragmentation here is represented as the Euclidean distance 

between modified cells (50 percent modified is the threshold). Using this threshold, the 

most fragmented watershed in each State is shown in figure 11, while the top 15 fragmented watersheds are identified in figure 12. The most fragmented watersheds occupy 

the eastern boundary of rangelands in the United States, while those in the interior and 

southwestern United States are relatively intact, with little fragmentation. Five of the top 

15 most fragmented watersheds occur in Kansas alone.

Top 15 Watersheds With Increased Residential Development

Future residential development in areas dominated by rangelands is projected to be 

greatest near existing urban centers (e.g., where parcels are closer to utilities and roads 

and land is suitable for development) and is shown in figure 6. As demonstrated in figure 13, the top 15 watersheds experiencing the highest growth rates are clustered mainly 

in California and the southwestern United States. In fact, 13 of the top 15 of the watersheds expected to experience the highest projected growth rates are found in California. 

Figure 10—Relationship between human-modified cover and fragmentation calculated for each 

watershed in the coterminous United States.
24 USDA Forest Service RMRS-GTR-382. 2018

In addition to presenting the top 15, the watershed experiencing the greatest growth rate 

in each State is shown in figure 14.

Key Findings

The historic (pre-European settlement) extent of rangelands in the coterminous 

United States was roughly 1 billion acres. Based on figure 7, we estimate that 34 percent 

or 343 million acres of historical rangelands have been modified and converted to other 

land uses (table 5). The proportion of historic rangeland lost in each State ranged from 

a high of 88 percent for Iowa to a low of 3 percent for Nevada. In terms of total area, 

Texas had the greatest historic, modified, and existing rangeland areal extent. Figure 7 

clearly demonstrates the extent and magnitude of change, especially in the Great Plains 

regions where fertile soils and favorable growing conditions enable widespread and 

intensive modification. Conversion of former rangeland to agriculture is a well-known 

phenomenon and does not, by itself, yield useful information. Recognition of this situation gave rise to analyzing the extent of modification in a variety of ways. The analysis 

of spatial patterns of modification enables estimates of fragmentation at a national scale 

across the extent of rangelands. This novel approach enables a new perspective on 

Figure 11—Most fragmented (smallest average distance between areas exhibiting ≥50 percent human-modified cover) 

rangeland-dominated watershed in each State.
USDA Forest Service RMRS-GTR-382. 2018 25

Figure 12—Top 15 most fragmented (smallest average distance between areas exhibiting ≥50 percent human-modified cover) 

watersheds dominated by rangelands.

where and how rangelands are being changed. Present patterns of fragmentation follow 

similar patterns of modification, but residential development projections are unique.

Areas with the highest degree of projected residential development are plainly not 

occurring in areas that have historically exhibited the highest levels of modification. 

Indeed, agricultural development has had the greatest impact, especially on the Great 

Plains. These lands are generally more productive, while in contrast the greatest expected changes in residential growth rates are occurring primarily in the arid southwestern 

United States and California. This has significant implications for regional planners 

since the demand for water is going to increase commensurately with residential growth 

occurring in these relatively arid regions.

As shown in figure 13, 13 of the top 15 watersheds with the greatest anticipated 

growth rates are found in California. Over the next 18 years or so, we estimate an 

additional loss of 5.6 million acres of rangelands (about 280,000 acres lost annually) 

to residential development, with over 1 million acres of rangeland loss estimated for 

California and Texas alone. This amount of increased residential development is about 

1.4 percent of the current privately owned rangeland base of 409 million acres (USDA

2009). Our analysis does not account, however, for potential conservation efforts that 
26 USDA Forest Service RMRS-GTR-382. 2018

may slow the rate of development in some rangeland types. Further, it is important 

to understand that although the biggest changes in residential development occur in 

areas with large populations, greater relative effects on rangeland systems may occur 

elsewhere. For example, as pointed out in FOTE (Stein et al. 2007), Ravalli County, 

Montana, may continue to experience rapid changes in ecosystem goods and services 

based on the issues outlined in this document, such as increased prevalence of invasive 

species, greater conflicts between users, decreased land base for recreation, greater 

fragmentation of rangelands, etc. Likewise, areas such as Bend, Oregon, the Rocky 

Mountain Front in Colorado, and Bozeman, Montana, are also experiencing rapid 

change; thus, we encourage future analyses that may yield insights useful for planners 

using the data we developed here in ROTE. 

Special Consideration: Rangelands in the East and Piñon-Juniper

Because this study focuses on rangelands, which by definition typically exhibit 

tree cover ≤25 percent (table 2), most of the analyses portrayed in this report focus on 

western watersheds dominated by non-forest vegetation. There are, however, some 

Figure 13—The top 15 rangeland-dominated watersheds with the greatest projected increase in residential development. 
USDA Forest Service RMRS-GTR-382. 2018 27

Figure 14—The rangeland-dominated watershed with the greatest projected increase in residential development in each 

State. 

unique areas east of the 95th meridian where rangelands are common, especially in 

Louisiana, Florida, and Georgia. Therefore, despite the general lack of eastern watersheds evaluated in this report (due to relatively low area of rangeland compared with 

other cover types), we encourage readers to obtain data produced here because, as 

shown in figure 2, data were produced for eastern landscapes. 

Likewise, in the western United States, many stands of piñon-juniper and oak 

woodlands that might be considered forest using the Forest Inventory and Analysis 

(FIA) definition are often considered rangelands using the National Resources Inventory 

(NRI) definition. This is an important concept because FOTE (Stein et al. 2005) 

identified the piñon-juniper areas as mapping challenges. This mapping difficulty was 

partially overcome in ROTE through increased thematic resolution of the LANDFIRE 

geospatial products by specifically identifying and accounting for some piñon-juniper 

areas being classified as rangelands, which were not fully evaluated in FOTE (see page 

11 of Stein et al. 2005). Many of the landscapes dominated by piñon-juniper vegetation 

were included in ROTE. 
28 USDA Forest Service RMRS-GTR-382. 2018

Conclusions

Conversion of rangelands for exurban development will continue, more rapidly in 

some areas and more slowly, if at all, in others. California and Texas are expected to be 

impacted the most, followed by Florida, Arizona, and Colorado. States with less dense 

human populations, like Wyoming, Montana, and North Dakota, will be impacted the 

least. This process is expected to take place primarily around urban centers, that is, on 

the edge of rangelands, as our title infers. The higher relative value of land for housing in areas of expanding U.S. population makes such a trend inexorable. Mitigation 

of housing development impacts is most commonly enacted by local governments 

and developers themselves. Examples include setting aside and managing open space 

(e.g., https://vimeo.com/224369869, accessed 29 October 2017) through conservation 

easements (http://www.hcn.org/issues/271/14648) or outright purchase, and layouts of 

exurban developments that concentrate structures, allowing larger open areas for natural 

resource management and aesthetics.

In this inaugural Rangelands on the Edge report, modification, fragmentation, and 

projected residential development were quantified for coterminous U.S. rangelands. 

Because the assessment was produced with primarily regional to national applications 

in mind, the data are probably less reliable at finer spatial scales (<1 km2). Nevertheless, 

spatial information about future patterns of land use change provides an important 

mechanism for identifying future challenges and fostering dialogue among scientists, 

managers, and counties as they strive to implement policies aimed at maintaining sustainable production of goods and services from our nation’s rangelands.

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