i

Landscape Consequences of Natural Gas Extraction 

in Allegheny and Susquehanna Counties, 

Pennsylvania, 2004–2010

By E.T. Slonecker, L.E. Milheim, C.M. Roig-Silva, and A.R. Malizia

Open-File Report 2013–1025

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013 

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Suggested citation:

Slonecker, E.T., Milheim, L.E., Roig-Silva, C.M., and Malizia, A.R., 2013, Landscape consequences of 

natural gas extraction in Allegheny and Susquehanna Counties, Pennsylvania, 2004–2010: U.S. 

Geological Survey Open-File Report 2013–1025, 34 p., http://pubs.usgs.gov/of/2013/1025.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

Although this information product, for the most part, is in the public domain, it may also contain 

copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured 

from the copyright owner.
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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......................................................................................................... 6 

Disturbance................................................................................................................................................................ 7 

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

Interior Forest............................................................................................................................................................. 9 

Forest Edge ..............................................................................................................................................................10

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

Fractal Dimension.....................................................................................................................................................11

Dominance................................................................................................................................................................11

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

Data ..........................................................................................................................................................................12

Sources .................................................................................................................................................................12

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

Land Cover Update...................................................................................................................................................15

Calculation of Landscape Metrics .............................................................................................................................16

Results: Summary Statistics and Graphics.................................................................................................................. 16

Disturbed Area..........................................................................................................................................................16

Land Cover Metrics of Interest..................................................................................................................................21

Forest Fragmentation................................................................................................................................................23

Interior and Edge Forest ...........................................................................................................................................25

Conclusion................................................................................................................................................................... 28

References Cited......................................................................................................................................................... 29 

Figures

1. Map of the Appalachian Basin Province showing the three Marcellus Shale assessment units ....................... 2 

2. Examples of forested landscapes from Washington 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 issued between 2004 and 

2010 within Pennsylvania, the focal counties of Allegheny and Susquehanna, and their relation to 

the Interior Marcellus Shale assessment unit ................................................................................................... 4

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

National Land Cover Database......................................................................................................................... 5

 5. Example of a natural gas disturbance footprint from Bradford County, Pennsylvania, embedded 

within the National Land Cover Database 2001................................................................................................ 8

6. Conceptual illustration of interior forest and how this critical habitat is affected by linear disturbance.............10

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

to one another .................................................................................................................................................11

8. Examples of spatially explicit features of disturbance that were extracted from aerial photographs 

into a geographic information system format...................................................................................................14
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9. Workflow diagram for creating an updated land cover map.............................................................................15

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

Susquehanna Counties, Pennsylvania ............................................................................................................17

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

Allegheny and Susquehanna Counties, Pennsylvania.....................................................................................25

12. Change in percent interior forest by watershed in Allegheny and Susquehanna Counties, 

Pennsylvania, from 2001 to 2010 ....................................................................................................................28

13. Change in percent of edge forest by watershed in Allegheny and Susquehanna Counties, 

Pennsylvania, from 2001 to 2010 ....................................................................................................................29

Tables

1. Acquisition dates of National Agriculture Imagery Program source data. ........................................................12

2. Cumulative amount of landscape disturbance for natural gas extraction development and 

infrastructure based on disturbance type from 2004 to 2010 by county ............................................................19

3. Percent land cover (2001) and land cover change (2010) calculated for each county.....................................20

4. Landscape metrics by county for 2001 (original land cover) and as updated for natural gas 

development disturbance (2004–2010) ...........................................................................................................22

5. Forest fragmentation metrics by county for 2001 (original land cover) and as updated for natural 

gas development disturbance (2004–2010).....................................................................................................24

6. Change in percent Interior forest and percent edge forest by county for 2001 (original land cover) 

and as updated for natural gas development disturbance (2004–2010)..........................................................27

 
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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)

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).
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Landscape Consequences of Natural Gas Extraction in 

Allegheny and Susquehanna Counties, Pennsylvania, 

2004–2010

By E.T. Slonecker, L.E. Milheim, C.M. Roig-Silva, and A.R. Malizia

Abstract

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

advances in accessing unconventional hydrocarbon-rich geologic formations, have 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 currently 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 this area of 

Pennsylvania. Coalbed methane, which is sometimes extracted using the same technique, is commonly 

located in the same general area as the Marcellus Shale and is frequently developed in clusters of wells 

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 Allegheny County and Susquehanna County in 

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 also used to quantify these changes and is 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. 

Marcellus Shale generally extends 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. 
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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 Map

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

The overall landscape effects of natural gas development have been considerable. 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 have been issued 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 (m) below the land surface 

(Coleman and others, 2011). Gas and petroleum liquids are produced using 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 

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

resources.
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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 ways, is 

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

much shallower and less productive and are often located in clusters that cover large areas of the 

landscape, with nearly 60,000 total gas wells established. Both types of wells may affect 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 an example of 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. Examples of forested landscapes from Washington County, Pennsylvania, showing the spatial effects 

of roads, well pads, and pipelines related to (A) Marcellus Shale and (B) Conventional natural gas development. 

Left-hand side shows areas prior to development; right-hand side shows areas after development. Inset shows the 

location of the images. Base-map data courtesy of The National Map [(http://viewer.nationalmap.gov/viewer)

(U.S. Geological Survey, 2011a)]. 
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Location

This assessment of landscape effects focuses on two counties, Allegheny County and 

Susquehanna County in Pennsylvania, within the Marcellus Shale area of development known as the 

“Marcellus Shale Play,” or the Interior Marcellus Shale AU. These counties were chosen for their 

position within the “sweet spots” of exceptionally productive Marcellus Shale within the Interior 

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

to the Interior Marcellus Shale AU and the distribution of Marcellus and non-Marcellus gas extraction 

permits granted by Pennsylvania from 2004 to 2010. 

Figure 3. The distribution of Marcellus and non-Marcellus natural gas permits issued between 2004 and 2010 

within Pennsylvania, the focal counties of Allegheny and Susquehanna, and their relation to the Interior Marcellus 

Shale assessment unit. Base-map data courtesy of The National Map [(http://viewer.nationalmap.gov/viewer) (U.S. 

Geological Survey, 2011a)]. 

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

century, Pennsylvania became the country’s leading source of lumber, and 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 a 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, this time 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. 

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

Land Cover Database. Base-map data courtesy of The National Map [(http://viewer.nationalmap.gov/viewer) 

(U.S. Geological Survey, 2011a)]. 
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Pennsylvania forests provide critical habitat to a number of plant and animal species. Plant 

species include the sugar maple, the eastern redcedar, and evergreens that produce berries in the winter. 

There were a number of animal species that have been eradicated from the region, such as elk, moose, 

North American cougar, bison, and grey wolf (Nilsson, 2005). Today, animal species range from the 

more commonly found animals such as skunks 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 piping plover (Gross, 2005). 

Key Research Questions

An important 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 

aerial images and then computing landscape metrics in a geographic information system (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 disturbance 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 LULCC and the complex interaction between human and biotic systems at a 

variety of natural, geographic, and political scales (Slonecker and others, 2010).

LULCC, such as the disturbance and the landscape effects of energy exploration, is currently 

occurring at a relatively rapid pace that is 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 includes 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 
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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 assessment presented here is based largely on the framework outlined in O’Neill 

and others (1997). Many landscape metrics can be computed and utilized for some analytical purpose. 

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

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 

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 

(McGarigal and others, 2002) and Analytical Tools Interface for Landscape Assessments (ATtILA) 

(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 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 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 levels. 

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 (U.S. Environmental Protection Agency (USEPA), Las Vegas, Nev.) is an Esri 

(Environmental Systems Research Institute, Redlands, Calif.) Arcview 3.x extension that computes a 

number of landscape, riparian, and watershed metrics and is available at http://www.epa.gov/esd/landsci/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 
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explicit patterns of landscape disturbance involving the construction of well pads and impoundments, 

roads, pipelines, and disposal activities, which 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 (Hayden, 1998; Bonan, 2008), and to affect 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 Bradford County, 

Pennsylvania, and it also shows how that disturbance is placed with respect to the local land cover. 

Figure 5. Example of a natural gas disturbance footprint from Bradford County, Pennsylvania, embedded within 

the National Land Cover Database (NLCD) 2001. Base-map data courtesy of The National Map

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

Forest fragmentation is the alteration of forest into smaller, less functional areas. 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 important 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. The development of numerous 

secondary roads and pipeline networks crisscross and subdivide habitat structure.

Landscape disturbance associated with shale-gas development infrastructure directly alters 

habitat through loss, fragmentation, and edge effects, which, in turn, alter 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 toward 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). Fragmented habitats generally result in detrimental impacts to 

flora and fauna, caused by 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 (ha) per well pad, with an 

additional 8.5 ha 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 m 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 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 amount of interior forest can be dramatically 

affected by linear land use patterns, such as roads and pipelines, which tend to fragment land patches 
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into several smaller patches and destroy available habitat for certain species. Figure 6 shows the general 

concept of increased fragmentation and reduced interior forest. 

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 edge 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 than larger plots with less edges. Edge age also 

influences edge effects. Over time, forest edge is partially sealed by proliferating vines and second 

growth underbrush, 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 than found in 

interior forests. 
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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 

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 (after 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 perimeter-to-area proportional relationship of a patch. 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, which is sometimes used as an 

alternative measure of the relative area of one land cover type over others in the landscape.
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Although there are many metrics associated with dominance, here we report on a simple 

landscape metric—the Simpson’s Evenness Index, which is 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 

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 within and intersecting the boundary of each county.

Data 

Sources

High-resolution aerial imagery from the National Agriculture 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). 

Table 1 identifies the source imagery dates for each county and year. 

Table 1. Acquisition dates of National Agriculture Imagery Program (NAIP) source data.

Year Source imagery dates (chronological from left to right)

Allegheny County

2004 2004-06-20 2004-07-03 2004-08-02 2004-09-01 2004-09-03 2004-10-07

2005 2005-06-23 2005-08-24 2005-09-07 2005-09-10 2005-09-11

2006 2006-10-07 2006-10-08

2008 2008-06-07 2008-07-02 2008-07-15 2008-07-18 2008-07-29 2008-09-03

2010 2010-06-08 2010-06-18 2010-08-31 2010-09-02

Susquehanna County

2004 2004-06-12 2004-06-21 2004-08-23 2004-09-20

2005 2005-06-23 2005-06-24

2006

2008 2008-06-13 2008-09-02 2008-09-04 2008-10-10

2010 2010-07-11 2010-08-07 2010-09-01
13

13

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 12-digit Hydrologic Unit 

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

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

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 Database (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-m spatial resolution (Homer and others, 2007). The NLCD may be acquired using 

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

NLCD 2001 was resampled to 10-m pixel size.

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 features include the following: 

• Sites—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 

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

occurred after 2004. 

Changes that correlated with natural gas extraction permits, appeared to be natural gas extraction 

related, or were in proximity to other gas extraction infrastructure were selected and digitized to the 

maximum extent of landscape disturbance. The focus of the data collection was 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. One shapefile was generated for sites (polygons), one was generated for roads (lines), and one was 

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

for overall area assessments. The buffered distance was selected as the average from measurement of 

roads and pipelines in the counties. 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. 
14

14

Figure 8. Examples of spatially explicit features of disturbance that were extracted from aerial photographs 

into a geographic information system (GIS) format.
15

15

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 both 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, the result of which was 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. 

Figure 9. Workflow diagram for creating an updated land cover map. The workflow is implemented using 

ArcGIS ModelBuilder scripts to process the digitized data and embed in the resampled NLCD 2001.
16

16

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. 

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 of the 

disturbance. 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 Allegheny and Susquehanna 

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

disturbance. Figure 10 shows the distribution of disturbance within Allegheny and Susquehanna 

Counties. In Allegheny County, disturbance is clustered along the eastern edge of the county, with the 

greatest concentration in the northeast. Most of this disturbance is non-Marcellus related. In 

Susquehanna County, disturbance is clustered in the southwest quadrant and is related to Marcellus 

Shale natural gas extraction. The detailed insets show the disturbance footprints in the context of the 

surrounding land cover. 
17

17

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

Susquehanna Counties, Pennsylvania. Base-map data courtesy of The National Map

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

Table 2 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 then divided into sections; 

the first includes disturbance for all sites and their associated roads, and the second includes disturbance 

for pipelines and impoundments. The disturbance area for all sites and roads is further divided into 

disturbance for Marcellus Shale permitted sites and roads, non-Marcellus Shale permitted sites and 

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

and sites with permits for both Marcellus and non-Marcellus drilling. Additionally, the disturbance area 

associated with impoundments is presented for those impoundments greater than 0.4 ha and for those 

less than 0.4 ha. Because land disturbance or access roads may be associated with multiple 

infrastructural components (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: 
18

18

• While Allegheny and Susquehanna Counties are roughly equal in size (192,000 and 216,000 ha, 

respectively), Allegheny County has one-third the number of Marcellus sites with 39 sites compared 

to 151 sites in Susquehanna County. In contrast, Allegheny has 40 times the number of nonMarcellus sites as in Susquehanna (468 and 11 sites, respectively). 

• The mean number of hectares of disturbance per site is smaller (0.8 ha) in Allegheny County than in 

Susquehanna (2.4 ha) because of the greater number of smaller non-Marcellus sites. 

• The mean number of disturbed hectares for Marcellus sites is greater for Susquehanna County (3.1 

ha) than for Allegheny (2.2 ha), while the mean number of disturbed hectares per non-Marcellus site 

is approximately four times larger in Susquehanna (3.4 ha) than in Allegheny (0.7 ha). A visual 

examination of the Susquehanna non-Marcellus sites reveals several large sites, which include 

multiple wells or impoundments that may be related to hydraulic fracturing for coalbed methane

production. 

• Allegheny County has approximately five times the number of “other” sites (processing and 

transportation facilities and nonpermitted sites) than Susquehanna County (132 and 24 sites, 

respectively). The Allegheny sites appear to be mainly nonpermitted. The Allegheny sites also have 

a smaller mean size than the Susquehanna sites (0.9 ha versus 2.2 ha). 

• Allegheny County has approximately six times the number of large (>0.4 ha) impoundments as in 

Susquehanna County (63 and 10 impoundments, respectively) and approximately five times the 

number of small (<0.4 ha) impoundments (284 and 51, respectively). The mean size of large 

impoundments is similar for both counties, as is the mean size of small impoundments. 

Land cover change is the initial impact of disturbance and can have long-term effects on 

ecological integrity and functions. Table 3 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 divided 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 landscape structure rapidly breaks down into isolated patches, thereby changing forest 

resilience and habitat corridors. The results indicate the following: 

• In both Allegheny and Susquehanna Counties, the primary land covers are forest (41 percent and 64

percent, respectively), agriculture (5 percent and 28 percent, respectively), and developed (51 

percent and 4 percent, respectively). The high level of development in Allegheny County may be 

attributed to the city of Pittsburgh and its surrounding suburbs. 

• Allegheny County had less than the critical amount of forest in 2001, and that forest has been further 

impacted by natural gas resource development. Percent forest declined by 0.07 percent (134.7 ha). 

• Susquehanna County had greater than the critical amount of forest in 2001. That forest has declined 

by 0.09 percent (194.3 ha) from natural gas resource development. 

• Susquehanna County agriculture declined by 0.17 percent (367.1 ha) from natural gas resource 

development. 
19

19

Table 2. Cumulative amount of landscape disturbance for natural gas extraction development and infrastructure 

based on disturbance type from 2004 to 2010 by county.

[Note: Categories are not mutually exclusive. MS, Marcellus Shale site; non-MS, non-Marcellus Shale site; >, greater than, 

<, less than] 

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

Allegheny County (192,342 hectares)

All infrastructure 647 364.8 531.5 226.7 13.2 0.6 0.8 0.3

All sites and roads 633 332.38

MS sites and roads 39 76.7 86.6 10.9 2 2.2 0.3

Non-MS sites and 

roads 468 207.5 349.9 117.7 0.4 0.7 0.3

 

Other infrastructure/ 

nonpermitted 

sites and roads

132 63.3 120 69.5 0.5 0.9 0.5

 Dual sites 7 15.2 2.2 

Pipelines 14 32.34 27.3 2.9 13.2 2.3 

Impoundments 

(>0.4 hectares) 63 56.3 0.9 

Impoundments 

(<0.4 hectares) 284 31.3 0.1 

Susquehanna County (216,043 hectares)

All infrastructure 294 680.2 705.8 55.3 86.9 2.3 2.4 0.2

All sites and roads 178 446.5 

 MS sites and roads 151 419 468.4 50.4 2.8 3.1 0.3

 Non-MS sites and 

roads 11 29.8 37.3 6.1 2.7 3.4 0.5

 

Other infrastructure/ 

nonpermitted 

sites and roads

24 43.3 53.5 7.9 1.8 2.2 0.3

 Dual sites 11 26.9 2.4 

Pipelines 116 213.6 235.1 21.2 86.9 1.9 

Impoundments

(>0.4 hectares) 10 10.7 1.1 

Impoundments

(<0.4 hectares) 51 4 0.3 
20

Table 3. Percent land cover (2001) and land cover change (2010) calculated for each county. 

[MS, Marcellus Shale site; non-MS, non-Marcellus Shale site]

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

Allegheny County

Forest 41.33 41.26 -0.07 41.33 0 41.28 -0.05 41.31 -0.02 41.33 0 

Agriculture 5.12 5.11 -0.01 5.12 0 5.12 -0.01 5.12 0 5.12 0 

Developed 50.87 50.86 -0.01 50.87 0 50.86 -0.01 50.87 0 50.87 0 

Grasslandherbaceous 0.72 0.72 0 0.72 0 0.72 0 0.72 0 0.72 0 

Water 1.78 1.78 0 1.78 0 1.78 0 1.78 0 1.78 0 

Barren 0.14 0.14 0 0.14 0 0.14 0 0.14 0 0.14 0 

Wetlands 0.03 0.03 0 0.03 0 0.03 0 0.03 0 0.03 0 

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

Gas extraction 

disturbance 0.09 0.09 0 0 0.06 0.06 0.03 0.03 0.01 0.01

Susquehanna County

Forest 64.24 64.15 -0.09 64.19 -0.05 64.24 0 64.24 -0.01 64.2 -0.05

Agriculture 28.18 28.01 -0.17 28.05 -0.12 28.17 -0.01 28.17 -0.01 28.13 -0.05

Developed 4.44 4.43 -0.01 4.43 -0.01 4.44 0 4.44 0 4.44 0 

Grasslandherbaceous 0.1 0.1 0 0.1 0 0.1 0 0.1 0 0.1 0 

Water 1.16 1.16 0 1.16 0 1.16 0 1.16 0 1.16 0 

Barren 0.09 0.09 0 0.09 0 0.09 0 0.09 0 0.09 0 

Wetlands 0.69 0.69 0 0.69 0 0.69 0 0.69 0 0.69 0 

Scrub-shrub 1.1 1.1 0 1.1 0 1.1 0 1.1 0 1.1 0 

Gas extraction 

disturbance 0.28 0.28 0.18 0.18 0.02 0.02 0.02 0.02 0.1 0.1
21

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Land Cover Metrics of Interest

There are numerous landscape metrics, many of which are redundant. Table 4 lists the total area, 

number of patches, total edge, mean fractal index, contagion, and evenness 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 divided into the values attributable to Marcellus sites, non-Marcellus 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 unlike 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 class 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 changes occurred based on 2004-2010 natural gas development: 

• Total edge increased by 177.8 kilometers and 283.6 kilometers for Allegheny and Susquehanna 

Counties, respectively, with the largest amount attributable to non-Marcellus development in 

Allegheny and to Marcellus site and pipeline development in Susquehanna. 

• Mean fractal index is very low for both counties, indicating a high level of human influence in these 

counties. 

• Contagion shows a moderate level of clumped land cover for both counties. The influence of 

infrastructure type (all, Marcellus, non-Marcellus, other, and pipelines) was similar for Allegheny

but more variable for Susquehanna. 

• 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 an evenness value approaching zero, this value indicates a substantially disturbed 

landscape.
22

22

Table 4. Landscape metrics by county for 2001 (original land cover) and as updated for natural gas development disturbance (2004–2010). 

[Note: Categories are not mutually exclusive. MS, Marcellus Shale site; non-MS, non-Marcellus Shale site] 

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

Allegheny County

Total area 

(hectares) 192,337.5 192,337.5 0 192,337.5 0 192,337.5 0 192,337.5 0 192,337.5 0 

Number of 

patches 7838 8278 440 7843 5 8129 291 7961 123 7887 49

Total edge 

(kilometers) 15,529.7 15,707.5 177.8 15,534 4.3 15,648.5 118.9 15,595 65.3 15,543.5 13.9

Mean fractal 

index 1.1195 1.1196 0.0001 1.1195 0 1.1196 0.0001 1.1197 0.0002 1.1195 0 

Contagion 71.7896 73.0912 1.3016 73.2896 1.5 73.1569 1.3673 73.2224 1.4328 73.2775 1.4879

Evenness 0.5674 0.5681 0.0007 0.5674 0 0.5679 0.0005 0.5676 0.0002 0.5675 0.0001

Susquehanna County

Total area 

(hectares) 216,036.2 216,036.2 0 216,036.2 0 216,036.2 0 216,036.2 0 216,036.2 0 

Total edge 

(kilometers) 18,030.1 18,313.7 283.6 18,161.4 131.3 18,044.2 14.1 18,049.6 19.5 18,232.5 202.4

Mean fractal 

index 1.1279 1.1262 -0.0017 1.1269 -0.001 1.1277 -0.0002 1.1278 -0.0001 1.1272 -0.0007

Contagion 72.814 73.8077 0.9937 73.9671 1.1531 74.2343 1.4203 74.2253 1.4113 74.0474 1.2334

Evenness 0.5056 0.5078 0.0022 0.5069 0.0013 0.5057 0.0001 0.5058 0.0002 0.5065 0.0009
23

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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 less likely to provide migration corridors. 

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

and (or) median patch size. Table 5 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 changes occurred based on 2004–2010 natural gas development: 

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

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

• Allegheny County forest patches increased by 114; most (about 79 patches) are attributable to nonMarcellus development. These patches initially averaged about 25 ha, but that average was reduced 

by almost 1 ha in 2010. 

• Susquehanna County forest patches increased by almost 156; most (about 121 patches) are 

attributable to pipeline construction. These patches initially averaged about 67.1 ha and were 

reduced by 4.8 ha to a mean of about 62.3 ha. Pipeline construction had the greatest effect on these 

values.

• Both Allegheny and Susquehanna Counties have large differences between the forest patch mean 

area and median area values: 25.0 ha mean to 1.8 ha median and 67.1 ha mean to 0.7 ha median, 

respectively. These large differences indicate a skewed population of forest patch sizes including 

many small forest patches and few large forest patches.
24

24

Table 5. Forest fragmentation metrics by county for 2001 (original land cover) and as updated for natural gas development disturbance (2004–2010). 

[Note: Categories are not mutually exclusive. MS, Marcellus Shale site; non-MS, non-Marcellus Shale site] 

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

Allegheny County

Number of 

patches

3,177 3,291 114 3,177 0 3,256 79 3,205 28 3,190 13

Forest patch 

mean area 

(hectares)

25.02 24.11 -0.91 25.02 0.00 24.39 -0.63 24.79 -0.23 24.92 -0.10

Forest patch 

area median 

(hectares)

1.77 1.62 -0.15 1.77 0.00 1.65 -0.12 1.71 -0.06 1.72 -0.05

Susquehanna County

Number of 

patches

2,069 2,225 156 2,102 33 2,076 7 2,074 5 2,190 121

Forest patch 

mean area 

(hectares)

67.08 62.29 -4.79 65.98 -1.10 66.85 -0.23 66.91 -0.17 63.33 -3.75

Forest patch 

area median 

(hectares)

0.66 0.64 -0.02 0.65 -0.01 0.65 -0.01 0.65 -0.01 0.64 -0.02
25

25

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 more than 40 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 the increasing fragmentation in 

Allegheny and Susquehanna Counties, Pennsylvania. Base-map data courtesy of The National Map

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

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 6 

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 changes occurred based on 2004–2010 natural 

gas development:
26

26

• Allegheny County lost 0.07 percent forest (134.6 ha), which contributed to a 0.26 percent 

loss of interior forest (500.2 ha) and a gain of 0.14 percent in edge forest (250.1 ha). 

Non-Marcellus site development was the major contributor to forest loss. 

• Susquehanna County lost 0.09 percent forest (194.3 ha), which contributed to a 0.22 

percent loss of interior forest (453.7 ha) and a gain of 0.10 percent in edge forest (216.1 

ha). Marcellus site development and pipeline construction were the major contributors to

forest loss. 

• The metrics suggest that the interior forest loss is two to three times that of the overall 

forest loss, and the gain in edge forest equals the loss of forest. 
27

27

Table 6. Change in percent Interior forest and percent edge forest by county for 2001 (original land cover) and as updated for natural gas 

development disturbance (2004–2010). 

[Note: Categories are not mutually exclusive. MS, Marcellus Shale site; non-MS, non-Marcellus Shale site]

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

Allegheny County

Number of 

patches 3,177 3,291 114 3,177 0 3,256 79 3,205 28 3,190 13

Percent forest 42.08 42.01 -0.07 42.08 -0.00 42.03 -0.05 42.05 -0.03 42.08 -0.00

Percent interior 

forest 21.59 21.33 -0.26 21.58 -0.01 21.41 -0.18 21.48 -0.11 21.58 -0.01 

Percent edge 

forest 14.77 14.91 0.14 14.77 0.00 14.86 0.11 14.83 0.06 14.77 0.00

Susquehanna County

Number of 

patches 2,069 2,225 156 2,102 33 2,076 7 2,074 5 2,190 121

Percent forest 64.99 64.90 -0.09 64.94 -0.05 64.99 -0.00 64.99 -0.00 64.95 -0.05

Percent interior 

forest 46.33 46.11 -0.22 46.23 -0.10 46.31 -0.02 46.31 -0.02 46.17 -0.16 

Percent edge 

forest 13.81 13.91 0.10 13.85 0.04 13.81 0.00 13.82 0.01 13.90 0.09
28

28

Figure 12. Change in percent interior forest by watershed in Allegheny and Susquehanna Counties, 

Pennsylvania, from 2001 to 2010. Base-map data courtesy of The National Map

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

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 Susquehanna 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 recommendations of 

O’Neill and others (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. 
29

29

Figure 13. Change in percent of edge forest by watershed in Allegheny and Susquehanna Counties, 

Pennsylvania, from 2001 to 2010. Base-map data courtesy of The National Map

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

References Cited

Bonan, G.B., 2008, Forest and climate change; Forcings, feedbacks, and the climate benefits of trees: 

Science, v. 320, p. 1,444–1,449. 

Coleman, J.L., Milici, R.C., Cook, T.A., Charpentier, R.R., Kirschbaum, Mark, Klett, T.R., Pollastro, 

R.M., and Schenk, C.J., 2011, Assessment of undiscovered oil and gas resources of the Devonian 

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