Landscape Consequences of Natural Gas Extraction in 

Bradford and Washington Counties, Pennsylvania, 

2004–2010

By E.T. Slonecker, L.E. Milheim, C.M. Roig-Silva, A.R. Malizia, D.A. Marr, and G.B. Fisher

Open-File Report 2012–1154

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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Suggested citation:

Slonecker, E.T., Milheim, L.E., Roig-Silva, C.M., Malizia, A.R., Marr, D.A., and Fisher, G.B., 2012, Landscape 

consequences of natural gas extraction in Bradford and Washington Counties, Pennsylvania, 2004–2010: U.S. 

Geological Survey Open-File Report 2012–1154, 36 p.
iii

Contents 

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

Introduction: Natural Gas Extraction .............................................................................................................................. 1

Location ..................................................................................................................................................................... 4

The Biogeography of Pennsylvania Forests............................................................................................................... 4

Key Research Questions ........................................................................................................................................... 6

Landscape Metrics and a Landscape Perspective......................................................................................................... 7

Disturbance................................................................................................................................................................ 8

Forest Fragmentation................................................................................................................................................. 9

Interior Forest........................................................................................................................................................... 10

Forest Edge ............................................................................................................................................................. 11

Contagion................................................................................................................................................................. 11

Fractal Dimension .................................................................................................................................................... 12

Dominance............................................................................................................................................................... 12

Methodology: Mapping and Measuring Disturbance Effects........................................................................................ 12

Data ......................................................................................................................................................................... 13

Sources ................................................................................................................................................................ 13

Collection.............................................................................................................................................................. 13

Land Cover Update.................................................................................................................................................. 16

Calculation of Landscape Metrics ............................................................................................................................ 17

Results: Summary Statistics and Graphics.................................................................................................................. 18

Disturbed Area ......................................................................................................................................................... 18

Land Cover Metrics of Interest ................................................................................................................................. 24

Forest Fragmentation............................................................................................................................................... 26

Interior and Edge Forest .......................................................................................................................................... 28

Conclusion................................................................................................................................................................... 31

References Cited......................................................................................................................................................... 32

Figures

1. Map of the Appalachian Basin Province showing the three Marcellus Shale assessment units (AU), which 

encompass the extent of the Middle Devonian from its zero-isopach edge in the west to its erosional 

truncation within the Appalachian fold and thrust belt in the east ..................................................................... 2

2. A forested landscape in McKean County, Pennsylvania, showing the spatial effects of roads, well pads, 

and pipelines related to natural gas development............................................................................................. 3

3. The distribution of Marcellus and non-Marcellus natural gas permits within Pennsylvania, the focal 

counties of Bradford and Washington, and their relation to the Marcellus Shale Play Interior assessment 

unit.................................................................................................................................................................... 4

4. The distribution of percent forest cover by county based on the U.S. Geological Survey 2001 National 

Land Cover Data............................................................................................................................................... 6

5. The natural gas disturbance footprint of Bradford County, Pennsylvania, embedded within the National 

Land Cover Dataset (NLCD) 2001.................................................................................................................... 9

6. Conceptual illustration of interior forest and how this critical habitat is affected by linear disturbance............ 11

7. The concept of contagion is the degree to which similar land cover pixels are adjacent or “clumped” to 

one another .................................................................................................................................................... 12
iv

8. Examples of spatially explicit features of disturbance that are being extracted from aerial photos into a 

geographic information systems (GIS) format................................................................................................. 15

9. Workflow diagram for creating an updated land cover map............................................................................ 17

10. Gas extraction-related disturbance identified between 2004 and 2010 in Bradford and Washington 

Counties, Pennsylvania .................................................................................................................................. 19

11. Change in number of forest patches from 2001 to 2010 showing increasing fragmentation in Bradford 

and Washington Counties, Pennsylvania ....................................................................................................... 28

12. Change in percent interior forest by watershed in Bradford and Washington Counties, Pennsylvania, 

from 2001 to 2010........................................................................................................................................... 31

13. Change in percent of edge forest by watershed in Bradford and Washington Counties, Pennsylvania, 

from 2001 to 2010........................................................................................................................................... 32

Tables

1. Amount of landscape disturbance for natural gas extraction development and infrastructure based on 

disturbance type. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale sites, 

respectively..................................................................................................................................................... 21

2. Percent land cover presented in descending order for each county. Change in percent forest is shown 

in bold. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale sites, respectively............. 23

3. Landscape metrics. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale sites, 

respectively..................................................................................................................................................... 25

4. Forest fragmentation metrics. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale 

sites, respectively. .......................................................................................................................................... 27

5. Change in percent of interior forest and percent edge forest. MS and non-MS sites refer to Marcellus 

Shale and non-Marcellus Shale sites, respectively......................................................................................... 30
v

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

Horizontal coordinate information is referenced to the North American Datum of 1983

(NAD 83).

SI to Inch/Pound

Multiply By To obtain

Length

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

Area

square meter (m2) 0.0002471 acre 

hectare (ha) 2.471 acre

Horizontal coordinate information is referenced to the North American Datum of 1983

(NAD 83).
1

Landscape Consequences of Natural Gas Extraction in 

Bradford and Washington Counties, Pennsylvania,

2004–2010

By E.T. Slonecker, L.E. Milheim, C.M. Roig-Silva, A.R. Malizia, D.A. Marr, and G.B. Fisher

Abstract

Increased demands for cleaner burning energy, coupled with the relatively recent technological 

advances in accessing unconventional hydrocarbon-rich geologic formations, led to an intense effort to 

find and extract natural gas from various underground sources around the country. One of these sources, 

the Marcellus Shale, located in the Allegheny Plateau, is undergoing extensive drilling and production. 

The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has 

garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids 

for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its

potential effect on water resources. Nonetheless, development of natural gas extraction wells in the 

Marcellus Shale is only part of the overall natural gas story in the area of Pennsylvania. Coalbed 

methane, which is sometimes extracted using the same technique, is often located in the same general 

area as the Marcellus Shale and is frequently developed in clusters across the landscape. The combined 

effects of these two natural gas extraction methods create potentially serious patterns of disturbance on 

the landscape. This document quantifies the landscape changes and consequences of natural gas 

extraction for Bradford County and Washington County, Pennsylvania, between 2004 and 2010. 

Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized 

using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. 

The disturbance patterns were then used to measure changes in land cover and land use using the 

National Land Cover Database (NLCD) of 2001. A series of landscape metrics is used to quantify these 

changes and are included in this publication. 

Introduction: Natural Gas Extraction

The need for cleaner burning energy, coupled with the relatively recent technological advances 

in accessing hydrocarbon-rich geologic formations, has led to an intense effort to find and extract 

natural gas from various underground sources around the country. One of these formations, the 

Marcellus Shale, is currently the target of extensive drilling and production in the Allegheny Plateau, 

extending generally from New York to West Virginia as shown in figure 1 (Coleman and others, 2011). 

Coleman and others (2011) defined assessment units (AU) of Marcellus Shale production based on the 

geology of the region.
2

Figure 1. Map of the Appalachian Basin Province showing the three Marcellus Shale assessment units (AU), 

which encompass the extent of the Middle Devonian from its zero-isopach edge in the west to its erosional 

truncation within the Appalachian fold and thrust belt in the east. The Interior Marcellus Shale AU is expected to be 

a major production area for natural gas (Coleman and others, 2011). Base-map data courtesy of the National Atlas 

[(http://viewer.nationalmap.gov/viewer) (U.S. Geological Survey, 2011)].

The overall landscape effects of natural gas development have been substantial. Over 9,600

Marcellus Shale gas drilling permits and over 49,500 non-Marcellus Shale permits have been issued 

from 2000 to 2011 in Pennsylvania (Pennsylvania Department of Environmental Protection, 2011) and 

over 2,300 Marcellus Shale permits in West Virginia (West Virginia Geological and Economic Survey, 

2011), with most of the development activity occurring since 2005.

The Marcellus Shale is generally located 600 to 3,000 meters below land surface (Coleman and 

others, 2011). Gas and petroleum liquids are produced with a combination of vertical and horizontal 

drilling techniques, coupled with a process of hydraulically fracturing the shale formation, known as 

“fracking,” which releases the natural gas.

The hydraulic-fracturing process has garnered much attention because of its use of large

amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to 
3

release contaminants into the environment, and its potential effect on groundwater and drinking-water 

resources.

However, with all of the development of natural gas wells in the Marcellus Shale, it is only part 

of the overall natural gas story in this area. Coalbed methane, which is extracted in similar wells, is 

often located in the same general area as the Marcellus Shale. The coalbed methane wells are much 

shallower and less productive than the Marcellus natural gas wells, but are often located in clusters that 

dot large areas of the landscape, with nearly 60,000 total gas wells. There may be both types of wells 

affecting a given area. With the accompanying areas of disturbance, well pads, new roads, and pipelines 

from both types of natural gas wells, the effect on the landscape is often dramatic. Figure 2 shows a 

pattern of landscape change from forest to forest, interspersed with gas extraction infrastructure. These 

landscape effects have consequences for the ecosystems, wildlife, and human populations that are 

colocated with natural gas extraction activities. This document examines the landscape consequences of 

gas extraction for two areas of current Marcellus Shale and non-Marcellus Shale natural gas extraction 

activity.

Figure 2. A forested landscape in McKean County, Pennsylvania, showing the spatial effects of roads, well pads,

and pipelines related to natural gas development. Inset shows the location of the image. Base-map data courtesy 

of the National Atlas [(http://viewer.nationalmap.gov/viewer) (U.S. Geological Survey, 2011)].
4

Location

This assessment of landscape effects focuses on two counties involved in the Marcellus Shale 

area of development known as the “Play”—Bradford County and Washington County in Pennsylvania. 

These counties were chosen for their position within the “sweet spots” of exceptionally productive 

Marcellus Shale (Stevens and Kuuskraa, 2009). Figure 3 below identifies the selected counties in 

relation to the Marcellus Shale Play and the distribution of Marcellus and non-Marcellus gas extraction 

permits granted by Pennsylvania.

Figure 3. The distribution of Marcellus and non-Marcellus natural gas permits within Pennsylvania, the focal 

counties of Bradford and Washington, and their relation to the Marcellus Shale Play Interior assessment unit. Basemap data courtesy of the National Atlas [(http://viewer.nationalmap.gov/viewer) (U.S. Geological Survey, 2011)].

The Biogeography of Pennsylvania Forests

Forests are a critical land cover in Pennsylvania. Prior to the European settlements, Pennsylvania 

was almost completely forested and even today, with modern agriculture, urban growth, and population 

growth, Pennsylvania is still roughly 60 percent forested. Pennsylvania forests of the 17th century were 

diverse but were dominated by beech and hemlock, which composed 65 percent of the total forest
5

(Pennsylvania Department of Conservation and Natural Resources, 2011). However, in the late 19th

century, Pennsylvania became the country’s leading source of lumber, in which a number of products, 

from lumber to the production of tannic acid, were generated from the forestry industry (Pennsylvania 

Department of Conservation and Natural Resources, 2011). By the early 20th century, most of 

Pennsylvania’s forests had been harvested. Soon after most of the trees were felled, wildfires, erosion, 

and flooding became prevalent, especially in the Allegheny Plateau region (Pennsylvania Parks and 

Forests Foundation, 2010).

The 20th century saw resurgence in Pennsylvania forests. The Weeks Act of 1911 authorized the 

Federal purchase of forest land on the headwaters of navigable rivers to control the flow of water 

downstream and act as a measure of flood control for the thriving steel industry of Pittsburgh. Slowly, 

the forests began to grow back but with a vastly different composition composed of black cherry, red 

maple, and sugar maple species (Pennsylvania Parks and Forests Foundation, 2010). For the most part,

except for a very few isolated areas in north central Pennsylvania and some State parks, the majority of 

forest cover is currently of the new composition and not of virgin forest. Figure 4 shows that today the 

concentrations of forests in Pennsylvania are highest in the central and north-central parts of the State, 

which is also the main area of hydraulic-fracturing activity in the Marcellus Shale. 
6

Figure 4. The distribution of percent forest cover by county based on the U.S. Geological Survey 2001 National 

Land Cover Data. Base-map data courtesy of the National Atlas [(http://viewer.nationalmap.gov/viewer) (U.S. 

Geological Survey, 2011)].

Pennsylvania forests provide critical habitat to a number of plant species, such as the sugar 

maple, the Eastern red cedar, and evergreens, which produce berries in the winter. There were a number 

of species that have been eradicated from the region such as moose, North American cougar, bison, and 

grey wolf (Nilsson, 2005). Today, animal species range from the typical skunk to flying squirrels and 

multiple different varieties of snakes and bats. However, a diverse population of birds depends on the 

forests for survival. In the State of Pennsylvania, there are 394 different bird species that are native, 

including endangered species such as the peregrine falcon and the bald eagle (Gross, 2005).

Key Research Questions

One key aspect of this research is to quantify the level of disturbance in terms of land use and 

land cover change by specific disturbance category (well pads, roads, pipelines, and so forth). This 

quantification will be accomplished by extracting the signatures of disturbance from high-resolution 
7

aerial images and then computing landscape metrics in a geographic information systems (GIS)

environment. 

This research and monitoring effort will attempt to answer the following key research questions:

• What is the level of overall disturbance attributed to gas exploration and development activities and 

how has this changed over time? 

• What are the structural components (land cover classes) of this change and how much change can be 

attributed to each class?

• How has the disturbance associated with natural gas exploration and development affected the 

structure, pattern, and process of key ecosystems, especially forests, within the Marcellus Shale 

Play?

• How will the disturbance stressors affect ecosystem structure and function at a landscape and 

watershed scale?

Landscape Metrics and a Landscape Perspective

An important and sometimes overlooked aspect of contemporary gas exploration activity is the 

geographic profile and spatial arrangement of these activities on the land surface. The function of 

ecosystems and the services they provide are due in large part to their spatial arrangement on the 

landscape. Energy exploration and development represents a specific form of land use and land cover 

change (LULCC) activity that substantially alters certain critical aspects of the spatial pattern, form, and 

function of landscape interactions.

Changes in land use and land cover affect the ability of ecosystems to provide essential 

ecological goods and services, which, in turn, affect the economic, public health, and social benefits that 

these ecosystems provide. One of the great scientific challenges for geographic science is to understand 

and calibrate the effects of land use and land cover change and the complex interaction between human 

and biotic systems at a variety of natural, geographic, and political scales (Slonecker and others, 2010).

Land use and land cover change, such as the disturbance and the landscape effects of energy 

exploration, is currently occurring at a relatively rapid pace prompting immediate scientific focus and 

attention. Understanding the dynamics of land surface change requires an increased understanding of the 

complex nature of human-environmental systems and requires a suite of scientific tools that include 

traditional geographic data and analysis methods, such as remote sensing and GIS, as well as innovative 

approaches to understanding the dynamics of complex natural systems (O’Neill and others, 1997; 

Turner, 2005; Wickham and others, 2007). One such approach that has gained much recent scientific 

attention is the landscape indicator, or landscape assessment, approach, which has been developed with 

the science of landscape ecology (O’Neill and others, 1997). 

Landscape assessment utilizes spatially explicit imagery and GIS data on land cover, elevation, 

roads, hydrology, vegetation, and in situ sampling results to compute a suite of numerical indicators 

known as landscape metrics to assess ecosystem condition. Landscape analysis is focused on the 

relation between pattern and process and broad-scale ecological relationships such as habitat, 

conservation, and sustainability. Landscape analysis necessarily considers both biological and 

socioeconomic issues and relationships. This research explores these relationships and their potential 

effect on various ecosystems and biological endpoints.

The landscape analysis presented here is based largely on the framework outlined in O’Neill and 

others (1997). There are many landscape metrics that can be computed and utilized for some analytical 

purpose. However, it has been shown by several researchers (Wickham and Riitters, 1995; Riitters and 

others, 1995; Wickham and others, 1997) that many of these metrics are highly correlated, sensitive to 

misclassification and pixel size, and, to some extent, questionable in terms of additional information 
8

value. The key landscape concepts and metrics reported here are discussed below. The actual formulae 

used to compute these specific metrics can be found in software documentation for FRAGSTATS and 

ATtILA (McGarigal and others, 2002; Ebert and Wade, 2004). Computation details for percent interior 

forest and percent edge forest are documented by Riitters and others (2000).

The concept of landscape metrics, sometimes called landscape indices, is derived from the 

emerging field of landscape ecology and is rooted in the realization that pattern and structure are 

important components of ecological process. Landscape metrics are spatial/mathematical indices that 

have been developed that allow the objective description of different aspects of landscape structures and 

patterns (McGarigal and others, 2002). They characterize the landscape structure and various processes 

at both landscape and ecosystem level. Metrics such as average patch size, fragmentation, and interior 

forest dimension capture spatial characteristics of habitat quality and potential change effects on critical 

animal and vegetation populations.

Two different geostatistical landscape analysis programs were used to measure the landscape 

metrics presented in this report. FRAGSTATS (University of Massachusetts, Amherst, Mass.) is a 

spatial pattern analysis program for quantifying numerous landscape metrics and their distribution, and 

is available at: http://www.umass.edu/landeco/research/fragstats/fragstats.html (McGarigal and others, 

2002). ATtILA (Analytical Tools Interface for Landscape Assessments) (U.S. Environmental Protection 

Agency, Las Vegas, Nev.) is an Arcview 3.x extension [Environmental Systems Research Institute 

(Esri), Redlands, Calif.] developed by the USEPA that computes a number of landscape, riparian, and 

watershed metrics, and is available at: http://www.epa.gov/esd/land-sci/attila/ (Ebert and Wade, 2004). 

Metrics are presented here at the county level and mapped at the watershed level (12-digit Hydrologic 

Unit Codes).

Disturbance 

Disturbance is a key concept in a landscape analysis approach and in ecology in general. Gas 

development activities create a number of disturbances across a heterogeneous landscape. In landscape 

analysis, disturbances are discrete events in space and time that disrupt ecosystem structure and function 

and change resource availability and the physical environment (White and Pickett, 1985; Turner and 

others, 2001). When natural or anthropogenic disturbance occurs in natural systems, it generally alters 

abiotic and biotic conditions that favor the success of different species, such as opportunistic invasive

species over predisturbance organisms. Natural gas exploration and development result in spatially 

explicit patterns of landscape disturbance involving the construction of well pads and impoundments, 

roads, pipelines, and disposal activities that have structural impacts on the landscape (fig. 2).

Development of multiple sources of natural gas will result in increased traffic from construction, 

drilling operations (horizontal and vertical), hydraulic fracturing, extraction, transportation, and 

maintenance activities. The mere presence of humans, construction machinery, infrastructure (for 

example, well pads and pipelines), roads, and vehicles alone may substantially impact flora and fauna. 

Increased traffic, especially rapid increases on roads that have historically received little activity, can 

have detrimental impacts to populations (Gibbs and Shriver, 2005). Forest loss as a result of 

disturbance, fragmentation, and edge effects has been shown to negatively affect water quality and 

runoff (Wickham and others, 2008), to alter biosphere-atmosphere dynamics that could contribute to 

climate change (Bonan, 2008; Hayden, 1998), and to affect even the long-term survival of the forest 

itself (Gascon and others, 2007). The initial step of landscape analysis is to determine the spatial 

distribution of disturbance to identify relative hotspots of activity. Disturbance in this report is presented

as both graphic files and tables of summary statistics. This knowledge allows greater focus to be placed 

on specific locations. Figure 5 provides an example of the distribution of natural gas extraction in 
9 

Bradford County, Pennsylvania. The figure also shows how that disturbance is placed with respect to 

the local land cover. 

Figure 5. The natural gas disturbance footprint of Bradford County, Pennsylvania, embedded within the National 

Land Cover Dataset (NLCD) 2001. Base-map data courtesy of the National Atlas 

[(http://viewer.nationalmap.gov/viewer) (U.S. Geological Survey, 2011)].

Forest Fragmentation

Fragmentation of forest and habitat is a primary concern resulting from current gas development. 

Habitat fragmentation occurs when large areas of natural landscapes are intersected and subdivided by 

other, usually anthropogenic, land uses leaving smaller patches to serve as habitat for various species. 

As human activities increase, natural habitats, such as forests, are divided into smaller and smaller 

patches that have a decreased ability to support viable populations of individual species. Habitat loss 

and forest fragmentation can be major threats to biodiversity, although research on this topic has not 

been conclusive (With and Pavuk, 2011). 

Although many human and natural activities result in habitat fragmentation, gas exploration and 

development activity can be extreme in their effect on the landscape. Numerous secondary roads and 

pipeline networks crisscross and subdivide habitat structure. Landscape disturbance associated with 
10

shale-gas development infrastructure directly alters habitat through loss, fragmentation, and edge 

effects, which in turn alters the flora and fauna dependent on that habitat. The fragmentation of habitat 

is expected to amplify the problem of total habitat area reduction for wildlife species, as well as 

contribute towards habitat degradation. Fragmentation alters the landscape by creating a mosaic of 

spatially distinct habitats from originally contiguous habitat, resulting in smaller patch size, greater 

number of patches, and decreased interior to edge ratio (Lehmkuhl and Ruggiero, 1991; Dale and others, 

2000). Fragmentation generally results in detrimental impacts to flora and fauna, resulting from 

increased mortality of individuals moving between patches, lower recolonization rates, and reduced 

local population sizes (Fahrig and Merriam, 1994). The remaining patches may be too small, isolated, 

and possibly too influenced by edge effects to maintain viable populations of some species. The rate of 

landscape change can be more important than the amount or type of change because the temporal 

dimension of change can affect the probability of recolonization for endemic species, which are 

typically restricted by their dispersal range and the kinds of landscapes in which they can move (Fahrig 

and Merriam, 1994). 

While general assumptions and hypotheses can be derived from existing scientific literature 

involving similar stressors, the specific impacts of habitat loss and fragmentation in the Marcellus Shale

Play will depend on the needs and attributes of specific species and communities. A recent analysis of 

Marcellus well permit locations in Pennsylvania found that well pads and associated infrastructure 

(roads, water impoundments, and pipelines) required nearly 3.6 hectares (9 acres) per well pad with an 

additional 8.5 hectares (21 acres) of indirect edge effects (Johnson, 2010). This type of extensive and 

long-term habitat conversion has a greater impact on natural ecosystems than activities such as logging 

or agriculture, given the great dissimilarity between gas-well pad infrastructure and adjacent natural 

areas and the low probability that the disturbed land will revert back to a natural state in the near future 

(high persistence) (Marzluff and Ewing, 2001). Figure 6 shows an example of the concept of the 

landscape metric of forest fragmentation. 

Interior Forest 

Interior forest is a special form of habitat that is preferred by many plant and animal species and 

is defined as the area of forest at least 100 meters from the forest edge (Harper and others, 2005). 

Interior forest is an important landscape characteristic because the environmental conditions, such as 

light, wind, humidity, and exposure to predators, within the interior forest are very different from areas 

closer to the forest edge. Interior forest habitat is related to the size and distribution of forest patches and 

is closely tied to the concept of forest or habitat fragmentation—the alteration of habitat into smaller, 

less functional areas. The amount of interior forest can be dramatically affected by linear land use 

patterns, such as roads and pipelines, which tend to fragment land patches into several smaller patches 

and destroy available habitat for certain species. Figure 6 shows the general concept of increased 

fragmentation and reduced interior forest. 
11

Figure 6. Conceptual illustration of interior forest and how this critical habitat is affected by linear disturbance. (A) 

High interior area, (B) Moderate interior area, and (C) Low interior area (Riitters and others, 1996).

Forest Edge 

Forest edge is simply a linear measure of the amount of edges between forest and other land uses 

in a given area, and especially between natural and human-dominated landscapes. The influence of the 

two bordering communities on each other is known as the edge effect. When edges are expanded into 

natural ecosystems, and the area outside the boundary is a disturbed or unnatural system, the natural 

ecosystem can be affected for some distance in from the edge (Skole and Tucker, 1993). Edge effects 

are variable in space and time. The intensity of edge effects diminishes as one moves deeper inside a 

forest, but edge phenomena can vary greatly within the same habitat fragment or landscape (Laurance

and others, 2007). Factors that might promote edge-effect variability include the age of habitat edges, 

edge aspect, and the combined effects of multiple nearby edges, fragment size, seasonality, and extreme 

weather events.

Spatial variability of edge effects may result from local factors such as the proximity and 

number of nearby forest edges. Plots with two or more neighboring edges, such as smaller fragment 

plots, have greater tree mortality and biomass loss. Edge age also influences edge effects. Over time, 

forest edge is partially sealed by proliferating vines and second underbrush growth, which will influence 

the ability of smaller tree seedlings to survive in this environment. Likewise, the matrix of adjoining 

vegetation plots will have a strong influence on edge effects. Forest edges adjoined by young regrowth 

forest provide a physical buffer from wind and light. Extreme weather events also affect the temporal 

variability in edge effects. Abrupt, artificial boundaries of forest fragments are vulnerable to 

windstorms, snow and ice, and convectional thunderstorms that can weaken and destroy exposed forest 

edges. Periodic droughts can also have a more pronounced effect on forest edges that are exposed to 

drier wind conditions and higher rates of evaporation. 

Contagion

Contagion is an indicator that measures the degree of “clumpiness” among the classes of land 

cover features and is related to patch size and distribution. Contagion expresses the degree to which 

adjacent pixel pairs can be found in the landscape. Figure 7 shows the general concept of contagion and 

gives examples of low, medium, and high contagion. Contagion is valuable because it relates an 
12

important measure of how landscapes are fragmented by patches. Landscapes of large, less-fragmented 

patches have a high contagion value and landscapes of numerous small patches have a low contagion 

value (McGarigal and others, 2002).

Figure 7. The concept of contagion is the degree to which similar land cover pixels are adjacent or “clumped” to 

one another. (A) Low contagion, (B) Moderate contagion, and (C) High contagion (Riitters and others 1996).

Fractal Dimension

Fractal dimension describes the complexity of patches or edges within a landscape and is 

generally related to the level of anthropogenic influence in a landscape. Fractal dimension generally 

measures the relationship of a patch by a perimeter-to-area proportion. Human land uses tend to have 

simple, circular, or rectangular shapes of low complexity and, therefore, low fractal dimensions. Natural 

land covers have irregular edges, complex arrangements and, therefore, higher fractal dimensions. The 

fractal-dimension index ranges between 1 and 2, with 1 indicating high human influences in the 

landscape and 2 with natural patterns and low human influence (McGarigal and others, 2002). 

Dominance

Dominance is a measure of the relative abundance of different patch types, typically 

emphasizing either relative evenness or equity in the distribution. Dominance is high when one land 

cover type occupies a relatively large area of a given landscape, and is low when land cover types are 

evenly distributed. Dominance is the complement to evenness, and is sometimes used as an alternative 

measure of the relative area of one land cover type over others in the landscape. 

Although there are many metrics associated with dominance, here we report on a simple 

landscape metric—the Simpson’s Evenness Index, which is basically a measure of the proportion of the 

landscape occupied by a patch type divided by the total number of patch types in the landscape 

(McGarigal and others, 2002).

Methodology: Mapping and Measuring Disturbance Effects

High-resolution aerial imagery for each of four timeframes—2004, 2005/2006, 2008, and 

2010—were brought into a GIS database, along with additional geospatial data on Marcellus and nonMarcellus well permits and locations, administrative boundaries, ecoregions, and geospatial information 
13

on the footprint of the Marcellus Shale Play in Pennsylvania. The imagery was examined for distinct 

signs of disturbance related to oil and gas drilling and development. The observable features were 

manually digitized as line and polygon features in a GIS format. The polygons and line features were 

processed and aggregated into a raster mask used to update existing land cover data. Summary statistics 

for each county were developed and reported. Detailed landscape metrics were calculated and mapped 

over watersheds (HUC-12 hydrounits) within and intersecting the boundary of each county.

Data 

Sources

High-resolution aerial imagery from the National Agricultural Imagery Program (NAIP) was 

downloaded for each timeframe. NAIP imagery is flown to analyze the status of agricultural lands 

approximately every 2 to 3 years (U.S. Department of Agriculture, Farm Service Agency, 2011). The 

NAIP imagery consists of readily available, high-resolution data that are suitable for detailed analysis of 

the landscape. NAIP imagery is available from the U.S. Department of Agriculture Geospatial Data 

Gateway Web site (U.S. Department of Agriculture, Natural Resources Conservation Service, 2011). 

Drilling permits for Marcellus Shale and non-Marcellus Shale natural gas were obtained from 

the Pennsylvania Department of Environmental Protection Permit and Rig Activity Reports for 2004–

2010 (Pennsylvania Department of Environmental Protection, Office of Oil and Gas Management, 

2011). 

The U.S. Geological Survey (USGS) Watershed Boundary Dataset Hydrologic Unit Code 12-

digit (HUC12) for Pennsylvania was downloaded from the USGS National Hydrography Dataset Web 

site (U.S. Geological Survey, 2011). 

The Marcellus Shale Play assessment unit boundaries were downloaded from the USGS Energy 

Resources Program Data Services Web site (U.S. Geological Survey, 2012). 

The 2001 National Land Cover Dataset (NLCD) was acquired for use as the baseline land cover 

map. The NLCD is a 16-class land cover classification scheme applied consistently across the United 

States at a 30-meter spatial resolution (Homer and others, 2007). The NLCD may be acquired using the 

Multi-Resolution Land Characteristics Consortium Web site (U.S. Geological Survey, 2011). 

Collection

These data were brought into a GIS database for spatial analysis. Using the 2004 imagery as a 

baseline, the imagery was examined for distinct signs of disturbance related to oil and gas drilling and 

development. These mapped disturbance features include: 

• Well Pads - Cleared areas related to existing permits or displaying the characteristics of a shale or 

coalbed gas extraction site.

• Roads - Vehicular transportation corridors constructed specifically for shale or coalbed gas 

development. 

• Pipelines - New gas pipelines constructed in conjunction with one or more well pads. 

• Impoundments - Manmade depressions designed to hold liquid and in support of oil and gas drilling 

operations. 

• Other - Support areas or activities such as processing plants, storage tanks, and staging areas.

The collection of gas extraction infrastructure was a manual process of visually examining highresolution imagery for each county over four dates to identify and digitize (collect) changes in the land 

cover resulting from the development of gas extraction infrastructure. Specifically, we examined NAIP 
14

1-meter data for the years 2004, 2005/2006, 2008, and 2010, identifying landscape changes that 

occurred after 2004. We selected those changes that appeared to be gas extraction related or were in 

proximity to other gas extraction infrastructure and digitized the maximum extent of landscape 

disturbance over the years of interest. We focused on features attributable to the construction, use, and 

maintenance of gas extraction drill sites, processing plants, and compressor stations, as well as the 

center lines for new roads accessing such sites, plants, and stations, and the center lines for new 

pipelines used to transport the extracted gas. Figure 8 shows examples of digitized natural gas extraction 

features. These data were collected within shapefiles per county, using ArcGIS 10.0 (Esri, Redlands, 

Calif.). One shapefile was generated for sites (polygons), one was generated for roads, and one was 

generated for pipelines (lines). Roads and pipelines were generally buffered to 8 and 12 meters, 

respectively, for overall area assessments. All sites were initially classified as gas extraction related or 

points of interest. Points of interest were unlikely to be related to drilling, but were of potential future 

interest and excluded from further processing. All data collected were reviewed by another team 

member for concurrence and consistency. 
15

Figure 8. Examples of spatially explicit features of disturbance that are being extracted from aerial photos into a 

geographic information systems (GIS) format.
16

Land Cover Update

Using the collected and reviewed data, the polygons and line features were processed and 

aggregated into a raster format used as a mask to update existing land cover data from NLCD 2001. 

Figure 9 shows the processing flow to accomplish this task consistently across all counties. 

Each feature within the shapefiles was then processed to determine its permit status and area. 

Each county's shapefiles were then merged and internal boundaries dissolved resulting in a disturbance 

footprint for that county. The disturbance footprint was then rasterized and used to conditionally select 

the pixels in the 2001 NLCD to reclassify as a new class: gas extraction disturbance. To consistently 

perform this processing, a set of models was developed using the ArcGIS Modelbuilder (Esri, Redlands, 

Calif.). 
17

Figure 9. Workflow diagram for creating an updated land cover map.

Calculation of Landscape Metrics

Landscape-wide and land cover class fragmentation statistics for each county were developed 

and reported using FRAGSTATS, while land cover class-detailed statistics, forest fragmentation 

statistics, including patch metrics and forest condition (interior, edge, and so forth) metrics were 

calculated over smaller watersheds (HUC12) intersecting with the county using ATtILA. The collected 

statistics were then summarized, charted, and mapped for further analysis. 
18

In addition to the summary of features noted above, a series of landscape metrics was calculated 

for each county based on the change related to gas development activities between 2004 and 2010. To 

do this, the metrics were calculated from the 2001 NLCD dataset (Homer and others, 2007). Following 

that calculation, the 2004–2010 cumulative spatial pattern of disturbance was digitally embedded into

the 2001 NLCD dataset and the metrics were recalculated for each county. 

Results: Summary Statistics and Graphics

This section presents a summary of landscape alterations from natural gas resource development, 

along with the ensuing change in land cover and landscape metrics for each county using metrics 

suggested by O’Neill and others (1997). These metrics are then calculated and presented based on the 

sources of that disturbance: Marcellus sites and roads, non-Marcellus sites and roads, and other 

infrastructure, which includes nonpermitted sites, processing facilities and their associated roads, and 

pipelines and their associated roads. Nonpermitted sites are defined as disturbed areas that appear to be 

Marcellus or non-Marcellus gas extraction sites that do not have a permit within 250 m. These data are 

presented in tabular form with some graphic presentations provided where appropriate. Examples of the 

spatial distribution of selected landscape metrics are shown at the watershed level for each county. GIS 

data of all disturbance features are available upon request. 

Disturbed Area

Documenting the spatially explicit patterns of disturbance was one of the primary goals of this 

research, and this section describes the extent of disturbed land cover for Bradford and Washington 

Counties in Pennsylvania. The spatial distribution of disturbance influences the impacts of that 

disturbance. Figure 10 shows the distribution of disturbance within Bradford and Washington Counties. 

In Washington County, the disturbance occurs in two general clusters: the northwest, which is mostly 

Marcellus Shale development, and the southeast, which is mostly non-Marcellus Shale development. On 

the other hand, Bradford County shows most of the disturbance at the western portion of the county, 

with some minor disturbance in the east. The detailed insets show the disturbance footprints in the 

context of the surrounding land cover. 
19

Figure 10. Gas extraction-related disturbance identified between 2004 and 2010 in Bradford and Washington 

Counties, Pennsylvania. Base-map data courtesy of the National Atlas [(http://viewer.nationalmap.gov/viewer) (U.S. 

Geological Survey, 2011)].

Table 1 lists the disturbance area attributable to all sites and impoundments and their associated 

roads and pipelines. The disturbance area is presented first as a total disturbance for all gas extraction 

infrastructure, including all sites, roads, and pipelines. Total disturbance is broken into two sections: 

disturbance for all sites and their associated roads and disturbance for pipelines. The disturbance area 

for all sites and roads is further broken into disturbance for Marcellus Shale sites and roads, nonMarcellus Shale sites and roads, sites with permits for both Marcellus and non-Marcellus drilling, and 

sites lacking an identifiable permit (for example, processing facilities or incomplete permit data). 

Additionally, disturbance area associated with impoundments is presented for those impoundments 

greater than 0.40 hectares and for those that are less than 0.40 hectares. Because land disturbance or 

access roads may be associated with multiple infrastructure (for example, pipelines may cross areas also 

disturbed for drill sites), the values for disturbed areas and road miles within break-out categories such 

as “MS sites and roads” do not sum up to the higher level category, in this instance “All sites and 

roads.” The results indicate the following: 
20

• While Bradford County is larger (~300,000 hectares) than Washington County (~223,000 hectares), 

Bradford County has 210 Marcellus and 19 non-Marcellus sites compared to 170 Marcellus and 501 

non-Marcellus sites in Washington County. 

• The mean hectares of disturbance per site are smaller (1.3 hectares) in Washington County than in 

Bradford County (2.0 hectares) because of the greater number of smaller non-Marcellus sites. 

• The mean disturbed hectares for Marcellus sites is almost identical for both counties (3.0 hectares

for Bradford and 2.9 hectares for Washington), whereas the mean disturbed hectares per nonMarcellus sites is almost three times larger in Bradford County than in Washington County. A visual 

examination of the Bradford non-Marcellus sites reveals several large sites that include 

impoundments or multiple wells. 

• Washington County has almost four times the number of sites that include processing and 

transportation facilities and nonpermitted sites than Bradford County, and these sites have a much 

larger mean size (18.5 hectares). This difference may be attributed to the processing facilities for 

“wet gas,” multiple hydrocarbons that are commonly extracted in this area.

• Both counties have about the same number of sites with both Marcellus and non-Marcellus permits. 

The disturbance associated with dual sites is included in the disturbance measures for both 

Marcellus and non-Marcellus sites.

• Bradford County has almost 20 times the number of large impoundments (greater than 0.40 

hectares) and these impoundments are almost twice the mean size of those in Washington County, 

implying a difference in water access, storage, and usage.
21

Table 1. Amount of landscape disturbance for natural gas extraction development and infrastructure based on 

disturbance type. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale sites, respectively.

Land cover update Count

Site only 

hectares

Footprint 

disturbed 

hectares

Road 

kilometers

Pipeline 

kilometers

Hectares 

per site

Disturbed 

hectares 

per site

Road 

kilometers 

per site

Bradford County (300,991.7 hectares)

All infrastructure 642 1,300.3 1,506.3 74.82 178.4 2.0 2.3 0.2

All sites and roads 262 742.4 73.7

MS sites and roads 210 616.7 865.8 66.1 3.0 4.1 0.3

non-MS sites and roads 19 49.2 58.4 5.8 2.5 3.1 0.3

Other infrastructure/ 

 unpermitted sites and 

 roads 44 116.5 143.0 5.5 2.6 3.2 0.2

Dual sites 11 39.9

Pipelines 97 432.7 450.3 77.4 178.4

Impoundments (>0.40 ha) 561 1,203.7 2.1

Impoundments (<0.40 ha) 121 22.7 0.2

Washington County (223,469.0 hectares)

All infrastructure 949 1,196.86 1,847.17 277.2 216.0887 1.3 1.9 0.3

All sites and roads 832 1,057.48 272.1

MS sites and roads 170 496.45 728.54 88.0 2.9 4.3 0.5

non-MS sites and roads 501 390.01 1,019.60 162.0 0.8 2.0 0.3

Other infrastructure/ 

 unpermitted sites and 

 roads 173 214.37 385.48 73.4 1.3 2.2 0.5

Dual sites 12 43.4

Pipelines 117 523.4 598.2 63.4 216.1

Impoundments (>0.40 ha) 29 34.0 1.2

Impoundments (<0.40 ha) 130 11.9 0.1

Land cover change is the initial impact of disturbance and has long-term effects on ecological 

goods and services. Table 2 lists the percent land cover by county for 2001 and percent land cover and 

change for the updated 2010 landscape. The land cover change for the updated landscape is further 

broken into the values attributable to Marcellus sites; non-Marcellus sites; other infrastructure including 

nonpermitted sites; and pipelines, each with their associated roads. Given that the natural land cover of 

Pennsylvania is forest (Kuchler, 1964), the 2001 land cover provides a measure of the impacts prior to 

most natural gas resource development; the changes between 2004 and 2010 have only increased these 

impacts. Of particular interest are the forest cover and its relation to the critical value 59.28 percent 

from percolation theory (Gardner and others, 1987; O’Neill and others, 1997). Below this value, the 

forest structure rapidly breaks down into isolated patches, thereby changing forest resilience and habitat 

corridors. The results indicate the following: 

• In both Bradford and Washington Counties, the primary land covers are forest (56 percent for each), 

agriculture (35 percent and 27 percent, respectively), and developed (5 percent and 14 percent,
22

respectively). Natural gas resource development had the greatest impact on forest and agricultural 

land cover. 

• Both counties had less than 59.28 percent forest in 2001 and forest has been further impacted by 

natural gas resource development. Percent forest declined by 0.12 percent in Bradford County and 

by 0.42 percent in Washington County. 
23

Table 2. Percent land cover presented in descending order for each county. Change in percent forest is shown in bold. MS and non-MS sites refer to 

Marcellus Shale and non-Marcellus Shale sites, respectively.

Land cover

Original 

land cover

Updated with 

all 

infrastructure Change

Updated 

with MS 

sites and 

roads Change

Updated with 

non-MS sites 

and roads Change

Updated with 

other 

infrastructure Change

Updated 

with 

pipelines Change

Bradford County

Forest 56.12 56.01 -0.12 56.06 -0.06 56.12 -0.01 56.11 -0.01 56.07 -0.05

Agriculture 35.47 35.20 -0.27 35.31 -0.16 35.46 -0.01 35.44 -0.03 35.38 -0.09

Developed 4.96 4.95 -0.01 4.96 0.00 4.96 0.00 4.96 0.00 4.96 -0.01

Grassland - 

 herbaceous 0.16 0.16 0.00 0.16 0.00 0.16 0.00 0.16 0.00 0.16 0.00

Water 0.96 0.96 0.00 0.96 0.00 0.96 0.00 0.96 0.00 0.96 0.00

Barren 0.11 0.11 0.00 0.11 0.00 0.11 0.00 0.11 0.00 0.11 0.00

Wetlands 0.75 0.75 0.00 0.75 0.00 0.75 0.00 0.75 0.00 0.75 0.00

Scrub - shrub 1.46 1.45 -0.01 1.45 -0.01 1.46 0.00 1.46 0.00 1.46 0.00

Gas extraction 

 disturbance 0.41 0.41 0.23 0.23 0.02 0.02 0.04 0.04 0.15 0.15

Washington County

Forest 56.6 56.18 -0.42 56.5 -0.1 56.46 -0.14 56.53 -0.07 56.45 -0.16

Agriculture 27.35 26.99 -0.37 27.2 -0.15 27.25 -0.11 27.29 -0.06 27.26 -0.09

Developed 13.64 13.61 -0.03 13.64 0 13.63 -0.01 13.64 -0.01 13.63 -0.02

Grassland - 

 herbaceous 1.53 1.51 -0.01 1.52 0 1.52 0 1.52 0 1.52 0

Water 0.62 0.62 0 0.62 0 0.62 0 0.62 0 0.62 0

Barren 0.2 0.2 0 0.2 0 0.2 0 0.2 0 0.2 0

Wetlands 0.04 0.04 0 0.04 0 0.04 0 0.04 0 0.04 0

Scrub - shrub 0.01 0.01 0 0.01 0 0.01 0 0.01 0 0.01 0

Gas extraction 

 disturbance 0.83 0.83 0.27 0.27 0.26 0.26 0.14 0.14 0.27 0.27
24

Land Cover Metrics of Interest

There are numerous landscape metrics, many of which are redundant. Table 3 lists the total area, 

number of patches, total edge, mean fractal index, contagion, and dominance metrics for the 2001 

county landscape and the metrics and change for the updated 2010 landscape. The metrics and change 

for the updated landscape are further broken into the values attributable to Marcellus sites; nonMarcellus sites; other infrastructure including nonpermitted sites; and pipelines, each with their 

associated roads. These metrics were chosen for their overall indication of human impacts on the 

landscape and environmental quality (O’Neill and others, 1997). Increase in edge, especially between 

dissimilar land covers, indicates declining resilience of the natural land cover and movement of species, 

while the decrease in the mean fractal index (1≤x≤2) indicates an increase in human use. Evenness 

(0≤x≤1, where 0 indicates one land cover and 1 indicates even distribution across land cover classes) 

indicates the relative heterogeneity of the landscape and is the inverse of the dominance measure 

(McGarigal and others, 2002) recommended by O’Neill and others (1997). Contagion (0<x≤100, 

disaggregated to aggregated) is an indicator that measures the degree of “clumpiness” among the classes 

of land cover features. The results indicate the following: 

• Total edge increased by 611.9 kilometers and 1,160.9 kilometers for Bradford and Washington 

Counties, respectively, with the largest amount attributable to pipeline construction.

• Fractal index is low for both, indicating a high level of human presence in these counties, and 

decreases with natural gas resource development. Bradford County shows a decrease of 0.0013, 

most of which is attributable to pipeline construction. Washington County shows a decrease of 

0.0052, of which half is attributable to pipeline construction. 

• Contagion shows a moderate level of clumped land cover. Bradford County has a slightly higher 

level of contagion than Washington County. The influence of infrastructure type (all, Marcellus, 

non-Marcellus, other, and pipelines) was similar for Bradford County, but more variable for 

Washington County. The greatest influence (an increase of 1.422) on contagion in Washington 

County was from other infrastructure; the remaining infrastructure types all had similar effects. This 

effect may be associated with the construction of the large processing facility in Houston, Pa. 

• Evenness also shows a moderate level of heterogeneity for both counties with no one land cover 

dominating. Evenness has similar values for each infrastructure type. Given that the expected land 

cover is all forest and has an evenness value approaching 0, this value indicates a substantially 

disturbed landscape. 
25

Table 3. Landscape metrics. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale sites, respectively.

[Note: Categories are not mutually exclusive]

Metric

Original land 

cover

Updated with all 

infrastructure Change

Updated with 

MS sites and 

roads Change

Updated with 

non-MS sites 

and roads Change

Updated with 

other 

infrastructure Change

Updated with 

pipelines and 

roads Change

Bradford County

Total area 

 (hectares) 300,991.7 300,991.7 0 300,991.7 0 300,991.7 0 300,991.7 0 300,991.6 0

Total edge (km) 26,712.4 27,324.3 611.9 26,948.5 236.1 26,732.7 20.3 26,744.3 31.9 27,124.4 412

Mean fractal index 1.1068 1.1055 -0.0013 1.1061 -0.0007 1.1067 -1E-04 1.1067 -0.0001 1.1057 -0.0011

Contagion 70.7925 71.7554 0.9629 71.9771 1.1846 72.315 1.5225 72.2781 1.4856 72.0422 1.2497

Evenness 0.6359 0.6295 -0.0064 0.628 -0.0079 0.6261 -0.0098 0.6263 -0.0096 0.6273 -0.0086

Washington County

Total area 

 (hectares) 223,469.0 223,469.0 0 223,469.0 0 223,469.0 0 223,469.0 0 223,469.0 0

Total edge (km) 24,270.1 25,431.1 1,160.9 24,515.9 245.7 24,704.1 433.9 24,466.8 196.6 24,833.9 563.8

Mean fractal index 1.1301 1.1249 -0.0052 1.1286 -0.0015 1.1282 -0.0019 1.1292 -0.0009 1.1273 -0.0028

Contagion 68.3976 68.8579 0.4603 69.6523 1.2547 69.5983 1.2007 69.8187 1.4211 69.5614 1.1638

Evenness 0.6696 0.6667 -0.0029 0.6669 -0.0027 0.6617 -0.0079 0.6661 -0.0035 0.6668 -0.0028
26

Forest Fragmentation

Disturbance in the landscape will affect forests by fragmentation, which is the process of 

dividing large land cover (for example, forest) into smaller segments called patches. A patch is defined 

as adjacent (forest) pixels, including diagonals. A landscape with many small patches is representative 

of a highly fragmented landscape. Fragmented forests provide habitat for edge species, but are poor for 

interior species, and are unlikely to provide migration corridors. 

Fragmentation may be evaluated by change in the number of patches, and change in the mean 

and (or) median patch size. Table 4 compares the changing forest patch metrics for the 2001 land cover, 

the updated 2010 land cover, and subsets of the updated 2010 land cover based on Marcellus 

infrastructure, non-Marcellus infrastructure, other infrastructure, and pipelines. The results indicate the 

following: 

• Forests became more fragmented due to natural gas resource development. Both Bradford and 

Washington Counties contained more, but smaller forest patches in 2010 than in 2001. 

• Bradford County forest patches increased by 306 patches; most (~235 patches) are attributable to 

pipeline construction. These patches initially averaged over 40 hectares, but that average was 

reduced by almost 3 hectares in 2010. 

• Washington County forest patches increased by almost 1,000 patches; most (~505 patches) are 

attributable to pipeline construction. These patches initially averaged about 35 hectares and were 

reduced by 7.5 hectares to a mean of about 27 hectares. Non-Marcellus sites and pipelines had the 

greatest effect on these values.

• Pipeline construction was the source of most of the increase in forest patch number. 
27

Table 4. Forest fragmentation metrics. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale sites, respectively. 

[Note: Categories are not mutually exclusive] 

Distribution 

statistics

Original 

land cover

Updated with 

all infrastructure Change

Updated with 

MS sites and 

roads Change

Updated with 

non-MS sites 

and roads Change

Updated with 

other 

infrastructure Change

Updated with 

pipelines Change

Bradford County

Number of

patches 4,188.00 4,494.00 306.00 4,263.00 75.00 4,198.00 10.00 4,194.00 6.00 4,423.00 235.00

Forest patch

 area mean

(hectares) 40.33 37.51 -2.82 39.58 -0.75 40.23 -0.10 40.27 -0.06 38.16 -2.18

Forest patch 

 area median 

 (hectares) 0.81 0.74 0.74 0.80 0.80 0.81 0.81 0.81 0.81 0.80 0.80

Washington County

Number of 

 patches 3,660 4,644 984 3,809 149 4,043 383 3,798 138 4,165 505

Forest patch 

 area mean 

 (hectares) 34.56 27.04 -7.52 33.15 -1.41 31.21 -3.35 33.26 -1.30 30.29 -4.27

Forest patch 

 area median 

 (hectares) 0.73 0.62 -0.11 0.72 -0.01 0.65 -0.08 0.72 -0.01 0.71 -0.02
28

Figure 11 illustrates the spatial distribution of the change in the number of forest patches 

by watershed. Note the relation between disturbance and the change in the number of forest 

patches. The increase of over 50 forest patches in some watersheds indicates an increasingly 

fragmented landscape with habitat implications for many species. 

Figure 11. Change in number of forest patches from 2001 to 2010 showing increasing fragmentation in 

Bradford and Washington Counties, Pennsylvania. Base-map data courtesy of the National Atlas 

[(http://viewer.nationalmap.gov/viewer) (U.S. Geological Survey, 2011)].

Interior and Edge Forest

Forest condition (interior and edge) is another way to evaluate the state of the forest. In 

particular, interior forest is subject to more rapid decline than other segments of the forest. Table 

5 shows the change in interior forest and edge forest based on natural gas resource development 

and the types of natural gas extraction infrastructure. Figures 12 and 13, respectively, illustrate

the spatial distribution by watershed of change in percent interior forest and the spatial 

distribution of change in percent edge forest. The results indicate the following: 

• Bradford County lost 0.12 percent forest, which contributed to a 0.32-percent loss 

of interior forest and a gain of 0.11 percent in edge forest. 
29

• Washington County lost 0.42 percent forest, which contributed to a 0.96-percent 

loss of interior forest and a gain of 0.38 percent in edge forest. 

• For both counties, pipeline construction was the major contributor to forest loss, 

although in Washington County, non-Marcellus sites were a close runner-up. 

• A tentative pattern appears in that the interior forest loss is approximately twice 

that of the overall forest loss, and the gain in edge forest approximates that overall 

forest loss.
30

Table 5. Change in percent of interior forest and percent edge forest. MS and non-MS sites refer to Marcellus Shale and non-Marcellus Shale sites, 

respectively. 

[Note: Categories are not mutually exclusive]

Distribution 

statistics

Original 

land cover

Updated with 

all infrastructure Change

Updated 

with MS 

sites and 

roads Change

Updated with 

non-MS sites 

and roads Change

Updated with 

other infrastructure Change

Updated 

with 

pipelines Change

Bradford County

Number of 

 patches 4,188.00 4,494.00 306.00 4263.00 75.00 4,198.00 10.00 4194.00 6.00 4,423.00 235.00

Percent forest 56.67 56.65 -0.02 56.60 -0.07 56.66 -0.01 56.66 -0.01 56.61 -0.06

Percent interior 

 forest 38.32 38.00 -0.32 38.22 -0.10 38.31 -0.01 38.31 -0.01 38.17 -0.15

Percent edge 

 forest 13.21 13.32 0.11 13.24 0.03 13.21 0.00 13.22 0.01 13.28 0.07

Washington County

Number of 

 patches 3,660.00 4,644.00 984.00 3,809.00 149.00 4,043.00 383.00 3,798.00 138.00 4,165.00 505.00

Percent forest 56.96 56.54 -0.42 56.85 -0.11 56.81 -0.15 56.89 -0.07 56.80 -0.16

Percent interior 

 forest 31.95 30.99 -0.96 31.76 -0.19 31.59 -0.36 31.80 -0.15 31.49 -0.46

Percent edge 

 forest 18.22 18.60 0.38 18.28 0.06 18.36 0.14 18.27 0.05 18.45 0.23
31

Figure 12. Change in percent interior forest by watershed in Bradford and Washington Counties, Pennsylvania,

from 2001 to 2010. Base-map data courtesy of the National Atlas [(http://viewer.nationalmap.gov/viewer) (U.S. 

Geological Survey, 2011)].

Conclusion

The results presented here show how natural gas extraction in Pennsylvania is affecting the 

landscape configuration. Agricultural and forested areas are being converted to natural gas extraction 

disturbance. The disturbance and effects of both Marcellus and non-Marcellus development are clearly 

different over both counties in that Bradford County has very little non-Marcellus development, but it is 

important to note that the combined effect of both activities is substantial. 

The fractal dimension, contagion, and dominance were reported based on O’Neill and others’ 

recommendations (1997); however, they do not appear to be important in these counties. They may be 

of greater importance for other counties and are reported here for consistency.
32

Figure 13. Change in percent of edge forest by watershed in Bradford and Washington Counties, Pennsylvania,

from 2001 to 2010. Base-map data courtesy of the National Atlas [(http://viewer.nationalmap.gov/viewer) (U.S. 

Geological Survey, 2011)].

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