An analysis of deforestation: Metrics used to describe pattern change

Forest Ecology and Management 114 (1999) 459±470

An analysis of deforestation: Metrics used to describe pattern change Margaret Katherine Trani1,a,*, Robert H. Giles, Jr.b a b

USDA Forest Service, George Washington±Jefferson National Forests, Roanoke, VA 24019, USA College of For. and Wildl. Res., Virginia Poly. Inst. and State Univ., Blacksburg, VA 24061, USA

Abstract Cartographic modeling was used to examine the in¯uence of deforestation on landscape pattern metrics. Progressive deforestation resulted in an increase in the spatial heterogeneity, fragmentation, and edge characteristics of a landscape while connectivity attributes varied with deforestation stage. Pattern changes in heterogeneity and edge characteristics were curvilinear, with metrics changing direction at the half-way point of deforestation. The progressive loss of forest enhanced edge length, interspersion, and convexity. There was an exponential decline in interior forest and mean patch size, while patch density and interpatch distance increased. The variability displayed by several pattern metrics re¯ect the unpredictability in patch disappearance. The relative contribution of each metric for discriminating between contiguous and fragmented landscape conditions was ranked using discriminant analysis. The results suggested that the mastery of landscape analysis can be directly linked to the choice of the pattern metric. Percent forest interior, contiguity, and convexity were highly signi®cant (P<0.001). Forest loss was also signi®cantly re¯ected by mean patch size, number of patches, mean patch density, and interpatch distance. Metrics that contributed little to discrimination displayed unpredictable behavior or exhibited high variability about their mean values. This paper develops an approach for monitoring the in¯uence of deforestation on the landscape, and examines how patternrelated habitat components are affected by deforestation. The ability to quantify pattern change resulting from deforestation has direct implications to resource management and wildlife habitat assessment. Descriptions of pattern change accompanying deforestation provide a critical component of habitat analyses. # 1999 Elsevier Science B.V. All rights reserved. Keywords: Landscape ecology; Deforestation; Pattern metrics; Environmental assessment; Species persistence; Wildlife habitat analysis

1. Introduction Resource managers are facing some of their greatest challenges as the end of the twentieth century

*Corresponding author. Tel.: +1-540-265-5100; fax: +1-540265-5145; e-mail: [email protected] 1 5162 Valleypointe Parkway, Roanoke, VA 24019-3050.

approaches. The loss of forests world-wide may have contributed to global warming and escalating species extinctions (McNeely et al., 1990). Landscape modi®cation and loss of wildlife habitat continue to be the major factors impacting wildlife resources. These challenges are occurring at a time when there is a growing appreciation of the dynamic processes at the landscape scale (Naveh and Lieberman, 1984; Zonneveld and Forman, 1990).

0378-1127/99/$ ± see front matter # 1999 Elsevier Science B.V. All rights reserved. PII: S0378-1127(98)00375-2

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M.K. Trani, R.H. Giles, Jr. / Forest Ecology and Management 114 (1999) 459±470

The in¯uence of landscape pattern on the dynamics of species populations has become a fundamental issue in resource management. Ecological consequences can differ depending on the pattern imposed on a landscape. Pattern change is often accompanied by changes in the composition and persistence of species dependent on that habitat. Deforestation can result in the decline of some forest birds (Askins et al., 1990); in the decline of large, wide-ranging species (Pelton, 1986); and in the loss of other specialized species (Rosenberg and Raphael, 1986). The absence of forested corridors within a landscape hinders movement for some species (Harris, 1988) while the altered size and shape of forest patches in¯uences both, biotic and abiotic processes (Van Dorp and Opdam, 1987). Deforestation can also change the distribution and availability of spatial resources, in¯uencing the components of forest connectivity (Noss and Harris, 1986) and edge characteristics (Yahner, 1988) that are important for the persistence of other species. The landscape context of management planning makes examining potential methods for evaluating deforestation important. Environmental monitoring dictated by federal laws requires using landscape analyses for projecting future landscape conditions. Using geographic information system technology, it is possible to model landscape deforestation and examine the effect on several measures of landscape pattern. Cartographic models generalize spatial relationships using the location and con®guration of landscape elements. The development of spatial analyses for quantifying how deforestation in¯uences pattern may prove useful for resource managers. The objective of this paper is to examine how deforestation in¯uences landscape pattern. First, general trends in pattern change are presented. Second, the contribution of each metric for discriminating between deforestation conditions is presented with a discussion suggesting their usefulness and limitations. Finally, the management implications for wildlife resources are discussed. 2. Methods Twenty-four pattern metrics were selected for analysis that express aspects of spatial heterogeneity, fragmentation, edge characteristics, and connectivity

Table 1 Landscape pattern metrics selected for examination Landscape expression

Selected Ref.

Spatial heterogeneity Shannon index Dominance index Number of different classes Simpson index Landscape evenness Interspersion Binary comparison matrix Spatial diversity

Shannon and Weaver, 1963 O'Neill et al., 1988 Murphy, 1985 Pielou, 1977 Romme, 1982 Eastman, 1997 Murphy, 1985 Robinove, 1986

Fragmentation Fragmentation index I Fragmentation index II Percent interior forest Number of forest patches Mean patch density Mean patch size Interpatch distance Percent forest cover

Monmonier, 1982 Ripple et al., 1991 Dunn et al., 1991 Trani, 1996 Ripple et al., 1991 Dunn et al., 1991 Urban and Shugart, 1986 Lauga and Joachim, 1992

Edge characteristics Total forest edge Convexity index Patton index Compactness

Ranney et al., 1981 Berry, 1991 Patton, 1975 Eastman, 1997

Connectivity Connectivity Contiguity index Spatial integrity Patchiness

Forman and Godron, 1986 LaGro, 1991 Berry, 1991 Roth, 1976

(Table 1). Selection was based on their utility for landscape assessment and their potential relevance to wildlife resources. These metrics are described brie¯y in the following, and are discussed in detail elsewhere (Trani, 1996). The spatial heterogeneity metrics express the complexity and variability among the land classes occurring on a landscape. The Shannon, Simpson, and binary comparison matrix indexes are based on the number and proportions of land classes. Dominance measures the extent to which one or more classes dominate the landscape, while evenness refers to how abundance is distributed among those classes. The arrangement of land classes is re¯ected by the spatial diversity, number of different classes, and interspersion metrics.

M.K. Trani, R.H. Giles, Jr. / Forest Ecology and Management 114 (1999) 459±470

The fragmentation category of pattern metrics describe, in some manner, the amount of forest cover on a landscape. This group includes several patch metrics that re¯ect the number (patch density, number of forest patches), size (mean patch size), or degree of isolation (interpatch distance) of forest patches on a landscape. Fragmentation index II (the average distance to non-forested areas) and percent interior forest (the amount of forest area remaining after removing a buffer from the edge of each forested tract) are in¯uenced by the distribution and amount of forest cover. Fragmentation index I re¯ects the number of distinct landscape regions on a map relative to the total number of map pixels. The edge metrics characterize areas where two different land classes come together. Total forest edge refers to the length of edge that exists at the interface between forest and other land classes. The convexity index is a perimeter-to-area ratio that describes the amount of edge per unit area of forest. The Patton and compactness indexes compare the amount of forest edge and area in a landscape to that of a circle, and are considered shape metrics. The connectivity metrics describe the spatial connectedness of a landscape. Patchiness expresses the lack of connectedness while the connectivity index detects the connections among forest patches. Forest contiguity assesses the unbroken adjacency of a forested landscape. The spatial integrity metric describes the spatial balance of a landscape by contrasting the number of forest openings with the number of existing patches. Thirty-eight forested maps (scale: 1 : 24 000) from the George Washington±Jefferson National Forests, Virginia, were selected that represented a variety of landscape conditions. This included continuous, unbroken forested landscapes; contiguous forested landscapes perforated by openings; and landscapes comprised of several forest patches. These maps were used as initial (baseline) conditions for the cartographic modeling process. Progressive deforestation was modeled by duplicating documented forest cover loss patterns (Levinson, 1981; Dunn et al., 1991). First, a 300 m wide buffer zone was generated along the inside edge of each forested area and the zone reclassi®ed as non-forest. A new, 300 m wide buffer zone was then generated along the newly-created forest edges, and the process

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repeated until the entire landscape was replaced by non-forest. The process was accompanied by computation of pattern metrics at each stage of deforestation. The modeling and GIS analysis operations were completed using Idrisi (Eastman, 1997). Pattern metric values were analyzed using SAS (1987) to produce descriptive statistics (e.g. mean and standard errors) during each stage of the modeling process to detect progressive changes in landscape pattern. Graphical displays of selected metrics were then created. Discriminant analysis was used for evaluating the relative contribution of each metric for the discrimination between two conditions of deforestation, contiguous forest and fragmented forest. These two conditions represent diametric stages of the deforestation process, and were selected because of their direct implications to the loss of habitat quality and the persistence of species. To carry out this analysis, a subset of the forest maps used in the modeling process were visually regrouped by USDA Forest Service resource specialists. The criteria used by specialists to assign membership centered on the amount and distribution of forest cover. The maps were placed into one of three categories: contiguous forest, fragmented forest, or uncertain characteristics. Those maps with uncertain status were omitted from further analysis, while unanimous agreement was required for assigning membership into the contiguous or fragmented landscape classes. The contiguous forest class contained maps that had relatively large, continuous forest blocks. In general, these were the maps created from the conditions arising from the ®rst initial stages of the modeling process. The fragmented forest class was represented by landscapes with numerous forest patches or those with large forest blocks punctuated with openings. These maps characterized the mid-to-late stages of the modeling process. Once the contiguous and fragmented classes were established, the suite of landscape metrics was tabulated for each of the paired groupings. The signi®cance of Mahalanobis distance was tested using the Hotelling T2 test and transformed to an F test. F-values and standardized differences were computed to assess the signi®cance of metric discrimination. The following two assumptions were made about the nature of the data:

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The spatial heterogeneity metrics demonstrated pronounced changes during the gradual loss of forest, producing curvilinear trends for seven metrics and one bimodal distribution. Although each pattern metric returned to its initial value once forest cover was eliminated, their distributions differed in both symmetry and shape (Fig. 1). The Simpson index (not shown) duplicated the Shannon index distribution; number of different classes and spatial diversity emulated the binary comparison matrix distribution. The Shannon, Simpson, and evenness indexes were characterized by a steady increase until 50% of the landscape remained forested, at which point their values steadily declined as forest disappeared. Because the predominant land class (forest) was being replaced by non-forest, heterogeneity escalated; how-

1. The metrics were normally distributed within each group. 2. The variance±covariance matrices of the groups were equal in size. The discriminant function is not seriously affected by limited departures from normality or by limited inequality of variances (Davis, 1986). 3. Results 3.1. General trends in landscape pattern change Table 2 presents the changes in landscape pattern resulting from the progressive deforestation process.

Table 2 Pattern changes resulting from progressive deforestation, George Washington±Jefferson National Forests, Virginia Landscape expression

Progressive forest shrinkage Stage 1 a

none mean Spatial heterogeneity Shannon index Dominance index Number of different classes Simpson index Landscape evenness Interspersion Binary comparison matrix Spatial diversity Fragmentation Fragmentation index I Fragmentation index II (km) Percent interior forest Number of forest patches Mean patch density (No./ha) Mean patch size (ha) Interpatch distance (km) Percent forest cover Edge characteristics Total forest edge (km) Convexity index Patton index Compactness Connectivity Connectivity index Contiguity index Spatial integrity Patchiness a

SE

mean

Stage 2 SE

mean

Stage 3 SE

mean

Stage 4 SE

mean

SE

0.000 0.000 1.000 0.000 0.000 0.000 0.000 0.000

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.490 0.207 1.581 0.331 0.572 1.720 8.671 58.167

0.01 0.01 0.03 0.01 0.01 0.12 0.50 3.49

0.663 0.050 1.626 0.461 0.909 1.613 9.313 62.567

0.01 0.02 0.03 0.01 0.02 0.10 0.54 3.51

0.541 0.177 1.427 0.371 0.661 1.039 6.043 42.700

0.03 0.03 0.02 0.02 0.05 0.25 0.27 2.04

0.294 0.299 1.166 0.184 0.325 0.439 2.959 17.567

0.04 0.04 0.05 0.03 0.06 0.06 0.48 2.60

0.010 0.000 100.000 1.000 0.111 900.000 0.000 100.000

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.082 0.579 51.233 2.233 0.244 539.300 0.176 79.967

0.01 0.04 2.23 0.31 0.03 47.60 0.05 0.03

0.052 0.495 30.367 3.900 0.422 254.800 0.639 51.233

0.01 0.03 3.08 0.48 0.05 43.60 0.10 2.23

0.043 0.429 17.267 2.967 0.344 174.200 1.036 30.367

0.01 0.03 2.92 0.32 0.04 35.40 0.13 3.08

0.022 0.310 6.533 1.033 0.118 105.400 0.380 12.600

0.01 0.03 1.80 0.15 0.02 23.40 0.16 2.54

12.000 0.013 1.130 0.886

0.00 0.00 0.00 0.00

21.740 0.030 1.795 0.606

1.18 0.01 0.11 0.03

18.240 0.043 1.568 0.664

0.82 0.01 0.06 0.02

12.180 0.058 1.465 0.703

0.61 0.01 0.04 0.02

5.040 0.065 1.208 0.592

0.74 0.01 0.11 0.05

0.000 2.000 0.000 0.000

0.00 0.00 0.00 0.00

0.139 1.869 0.200 45.170

0.04 0.01 0.60 11.32

0.082 1.787 ÿ2.700 35.490

0.03 0.02 0.48 6.12

0.032 1.717 ÿ2.133 25.157

0.02 0.03 0.33 4.61

0.000 1.395 ÿ0.067 0.850

0.00 0.12 0.12 0.85

Each stage represents a forest zone shrinkage of 300 m from the inside edge of all existing forest land classes.

M.K. Trani, R.H. Giles, Jr. / Forest Ecology and Management 114 (1999) 459±470

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Fig. 1. Changes in selected spatial heterogeneity and edge metrics during the progressive loss of forest cover. Error bars represent mean values (SE). Trend lines connect the mean metric values at each stage of forest loss.

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ever, once non-forest comprised over half of the landscape, spatial heterogeneity declined. Each of the roving-window metrics (binary comparison matrix, spatial diversity, number of different classes, and interspersion) displayed positivelyskewed distributions. Initial values for the ®rst three metrics escalated rapidly until 50% forest cover was reached and then tapered off gradually. Interspersion of land classes, however, reached a threshold during the ®rst stage of deforestation (80% forest cover). Each of these metrics re¯ects both, spatial arrangement and land±class proportion. It is possible that the in¯uence of the arrangement component (absent in the traditional heterogeneity metrics discussed above) strongly in¯uences the asymmetry of their distributions among the landscapes observed. The bimodal pattern of the dominance index during deforestation was quite different from the other heterogeneity metrics. Dominance values began at zero, then increased until the landscape was 75% forested. Dominance was reduced as forest loss continued until the proportion of forest equaled non-forest. Dominance values began to climb once more as non-forest predominated the landscape; values returned to zero when deforestation was complete. The progressive loss of forest cover also brought about changes in edge characteristics (Fig. 1). Edge length increased steadily until a peak was reached at 80% forest cover; then declined with continued deforestation. There was an incremental increase in perimeter-to-area ratio (convexity) as forest cover receded; more variability was displayed with each successive stage. Once forest loss became complete, the values returned to zero. Compactness values ¯uctuated in opposite directions as the shapes of forest patches were altered during the continued loss of forest. Patton's index also re¯ected changes in forest shape, but did not ¯uctuate to the extent observed for compactness. Both the Patton and compactness values were quite variable during the beginning and latter stages of deforestation. As deforestation began, the initial pattern of a landscape was established as a series of patches, forest clearings, or with irregular forest boundaries. This pattern was retained somewhat as forest cover continued to be lost. Variability in values escalated once the majority of forest was removed, re¯ecting the splitting of one patch into two remnants and the disappearance of other patches. The variability in

convexity values was also greatest during this last stage of deforestation. The behavior of the fragmentation metrics during deforestation was quite varied (Fig. 2). Percent interior forest and mean patch size values decreased exponentially with forest cover loss. There was a rapid drop in both metrics up until the point when half of the forest cover remained; at that point, values fell slowly. The reduction in patch size often re¯ected the creation of new, smaller patches. Patch density rose steadily until 50% of the forest cover was removed; patches were then lost with each successive stage. (Number of forest patches, not pictured, exhibited a similar response.) Interpatch distance increased past the 50% deforestation stage, followed by a fairly rapid fall. The variability displayed by several pattern metrics during the later stages of deforestation re¯ect the unpredictability in patch disappearance. Fragmentation index II values re¯ected the steady decline in distance to non-forest at each interval once the deforestation process began. (Fragmentation index I, not pictured, exhibited a similar response.) The progressive loss of forest cover also brought about changes in landscape connectivity characteristics (Fig. 2). Contiguity declined with each stage of deforestation, dropping rapidly after forest loss surpassed the 75% level. At this point, variability in values was three times that observed during the earlier intervals, re¯ecting the distribution of the remaining forest area. If the forest remnants occurred within the corners of a landscape, contiguity values were lower than if the forested area occurred within a single landscape quadrant. Patchiness displayed a curvilinear trend during deforestation. (Connectivity, not pictured, showed a similar response). Both metrics started at zero with a totally forested landscape and then rose as patches were formed. Values sharply declined between 50± 75% forest loss, as patches disappeared from the landscape. When total deforestation was reached, values returned to zero. Patchiness was expected to consistently escalate until forest loss was complete, re¯ecting the increasing distance between patches. Patches are continually disappearing during the deforestation process, and forest patches farthest away from others are eliminated as quickly as those patches situated closely together.

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Fig. 2. Changes in selected fragmentation and connectivity metrics during the progressive loss of forest cover. Error bars represent mean values (SE). Trend lines connect the mean metric values at each stage of forest loss.

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Table 3 Effectiveness of landscape metrics as discriminators of pattern differences between fragmented and contiguous landscapes, George Washington±Jefferson National Forests, Virginia Landscape expression

Mean I contiguous a

Mean II fragmented b

Standardized differences c

F value d

Percent interior forest Contiguity index Convexity index No. of different classes Mean patch size Percent forest cover Number of forest patches Mean patch density Binary comparison matrix Interspersion Interpatch distance Fragmentation Index I Spatial diversity Total forest edge Patchiness index Landscape evenness Simpson index Shannon index Dominance index Spatial integrity Fragmentation index II Connectivity index Patton index Compactness

0.650 1.929 0.020 1.367 652.300 0.798 1.389 0.154 5.443 0.948 0.103 0.032 36.722 14.570 15.389 0.556 0.319 0.487 0.167 ÿ0.278 1.144 0.028 1.490 0.693

0.203 1.715 0.056 1.706 195.800 0.470 4.059 0.451 10.121 1.885 0.887 0.074 64.647 20.890 60.518 0.738 0.405 0.586 0.107 ÿ2.176 0.385 0.103 1.678 0.641

3.874 2.786 ÿ2.442 ÿ2.197 2.054 1.997 ÿ1.929 ÿ1.928 ÿ1.808 ÿ1.785 ÿ1.652 ÿ1.420 ÿ1.418 ÿ1.314 ÿ1.022 ÿ0.916 ÿ0.906 ÿ0.816 0.678 0.661 0.584 ÿ0.526 ÿ0.446 0.404

131.2 *** 67.9 *** 52.1 *** 42.2 *** 36.9 *** 34.9 *** 32.5 *** 32.5 *** 28.6 *** 27.9 *** 23.9 *** 17.6 *** 17.6 *** 15.1 *** 9.1 ** 7.3 ** 7.2 ** 5.8 * 4.0 3.8 3.0 2.4 1.7 1.4

a

The metric mean representing landscapes with large, continuous forest blocks. The metric mean representing landscapes with patchy forest cover. c Represents the mean difference for a metric divided by the corresponding pooled standard deviation. Absolute values 1.0 indicate effective discrimination. d Indicates the significance of a metric in the discriminant equation. * Significant (P<0.05). ** Significant (P<0.01). *** Significant (P <0.001). b

There was little change in the behavior of spatial integrity during the initial stages of deforestation, when patches were shrinking and forest openings expanding (the two parameters for this metric). With 50% deforestation, values plummeted as the number of patches exceeded the number of forest openings. The metric then reversed direction and approached zero as openings coalesced and patches disappeared on the landscape. 3.2. Metric effectiveness for describing conditions of deforestation Table 3 lists the relative contribution of each pattern metric for discerning pattern differences between two

deforestation conditions. The measure of the difference between the multivariate means, Mahalanobis distance (157.58), and its associated F statistic (29.22, P<0.001) indicate a signi®cant difference between the contiguous and fragmented groups. The group centroids on the discriminant axis were 11.29 (contiguous) and ÿ146.28 (fragmented). The group means were wellseparated, indicating that discrimination between the two pattern groups was relatively clear. The magnitude of the standardized differences provides the ®rst means for assessing metric effectiveness; 15 metrics were considered effective based on this criterion. The role of each metric in the discriminant equation is indicated within the F-value column; 18 metrics proved to be signi®cant discriminators using this criterion.

M.K. Trani, R.H. Giles, Jr. / Forest Ecology and Management 114 (1999) 459±470

Percent forest interior contributed the most information for discriminating between the fragmented and contiguous forested landscapes. There was three times more interior forest area measured in the contiguous forest maps than measured on the fragmented landscapes. Contiguity and convexity were the next most ef®cient discriminating metrics. Moving from contiguous forest to a fragmented landscape pattern, edge length increased while forest cover receded; convexity expresses both of these parameters. The division and loss of forest area characteristic of many fragmented landscapes were re¯ected in the signi®cance of mean patch size, percent forest cover, number of patches, mean patch density, interpatch distance, and fragmentation index I. The roving-window heterogeneity metrics, based on the analysis of a spatially-de®ned 33 pixel neighborhood, were also quite valuable for discrimination between the contiguous and fragmented landscape conditions. These included number of different classes, binary comparison matrix, interspersion, and spatial diversity. Some of the metrics contributed little to the discrimination process between the contiguous and fragmented landscapes. In general, these metrics: (1) were unpredictable in behavior, with value shifts in opposite directions; (2) demonstrated high variability about their mean values; or (3) were not sensitive to pattern alteration, changing very little between the different landscape conditions. Compactness, Patton's index, and spatial integrity were virtually the same for both groups. Both, connectivity and fragmentation index II were not sensitive to differences in these patterns. Mean connectivity values actually increased in the fragmented class. The low position of fragmentation index II in this process was unexpected; distance to non-forest was one-third less in the fragmented landscapes than it was in the contiguous setting. Fragmented patterns also made little difference in dominance values, the only spatial heterogeneity metric that was not signi®cant. 4. Discussion 4.1. Discriminant analysis and landscape pattern analysis Discriminant analysis appears useful for evaluating the relative contribution of pattern metrics for the

467

discrimination between two conditions of deforestation. Using standardized differences and the F-statistic as guidelines, it was possible to rank the effectiveness of metrics for quantifying the patterns that result from deforestation. Whether a manager is monitoring deforestation or evaluating potential locations for timber harvest, knowledge about which landscape metrics are sensitive enough to detect those changes in pattern is important. This information also permits the reduction of the number of pattern metrics required for landscape analysis, reducing the risk of including highly correlated variables. Identifying sensitive metrics also fosters an understanding of the underlying attributes that characterize landscapes. The pattern differences between the fragmented and contiguous forest landscapes included variation in the amount of forest interior present, the degree of forest contiguity, the characteristics of forest edge, the mean size of forest patches, and in several spatial heterogeneity attributes. Metric selection also involves considering relevance for use in speci®c environmental monitoring applications, particularly an understanding of why the metric is useful for detecting pattern change. For example, the roving-window metrics were effective because of their ability to detect local area variation. Finally, metric selection should include consideration of the initial pattern of a landscape. If a landscape contains forest patches, or if the potential for patch formation exists, then using patch metrics is warranted. However, if the landscape comprises expansive contiguous forest cover, then using other metrics (e.g. forest interior, percent forest cover, contiguity) may be preferable. 4.2. Forest wildlife management within a landscape context Deforestation alters landscape pattern, in¯uencing conditions for species and communities. The recognition of these changes, and the knowledge of how best to describe them, has direct implications to resource management and wildlife habitat assessment. There is an extensive literature suggesting that deforestation affects the persistence and abundance of wildlife resources. The persistence of many populations is linked to the number, size, and degree of isolation of forest patches. For example, reduction in

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M.K. Trani, R.H. Giles, Jr. / Forest Ecology and Management 114 (1999) 459±470

patch size results in population declines for a number of species (Ambuel and Temple, 1983; Lynch and Whigham, 1984). Remnant patches of forest surrounded by open habitat constitute unfavorable habitat for many wildlife species. Continued deforestation reduces further the size of patches, increases the distance among remaining patches, and makes the ¯ow of animals between patches dif®cult. For other species, fragmented landscapes become population sinks that are sustained by immigration from nearby forest tracts (Robinson and Wilcove, 1994). The modeling process illustrated how deforestation in¯uences habitat loss and isolation (e.g. subdivision and attrition). These pattern changes, in turn, altered the heterogeneity, fragmentation, edge, and connectivity characteristics within a landscape. At a local level, these changes may result in eliminating, displacing, or enhancing species and their populations. There are other known effects on wildlife from changes in pattern arising from deforestation. Matthiae and Stearns (1981) found that the relative abundance and diversity of mammals decreased with forest loss in Wisconsin. Red squirrel (Tamiasciurus hudsonicus), fox squirrel (Sciurus niger), and red fox (Vulpes vulpes) were less abundant as forest size declined. Rosenberg and Raphael (1986) also reported that ®sher (Martes pennati), gray fox (Urocyon cinereoargenteus), and ringtail cat (Bassariscus astutus) were sensitive to fragmentation in the Paci®c northwest. Decline in these mammals was attributed to species requirements that are not met for minimum habitat size and speci®c habitat components. Forest size is also a primary determinant of the richness and size of bird assemblages. Galli et al. (1976) and Van Dorp and Opdam (1987) reported a direct relationship between number of bird species and forest area. Species that are intolerant of fragmentation tend to be highly migratory, are forest-interior specialists, build open nests, and nest on the ground (Whitcomb et al., 1981). These include the swallowtailed kite (Elanoides for®catus), broad-winged hawk (Buteo platypterus), and the barred owl (Strix varia) (Hamel, 1992). On deforested landscapes where there has been a loss of forest interior area, habitat quality is reduced for the worm-eating warbler (Helmintheros vermivorus), black-and-white warbler (Mniotilta varia), hooded warbler (Wilsonia citrina), and other species requiring large forest expanse (Hamel, 1992).

In contrast, widespread permanent residents such as the brown-headed cowbird (Molothrus ater) tend to predominate in landscapes in¯uenced by deforestation (Askins, 1994). Deforestation also alters the vegetational composition of landscapes (Ranney et al., 1981). At the boundaries of forest and non-forest land classes, characteristic edge associations composed of xericadapted and shade-intolerant species become established, often having long-term effects on forest composition (Whitney and Runkle, 1981). These changes bene®t species favoring edge habitat and a diversity of vegetative communities. These species include bobcat (Felis rufus), striped skunk (Mephitis mephitis), and wild turkey (Meleagris gallopavo). Deforestation also favors species that thrive in disturbed environments such as blue jay (Cyanocitta cristata), crow (Corvus brachyrhynchos), and raccoon (Procyon lotor). These studies suggest that there is a connection between deforested landscapes and the conservation of species and their habitats. Species occupy landscapes and the pattern of the landscape either supports or inhibits their survival (Golley, 1989). This emphasizes the importance of examining potential methods for analyzing landscape pattern. The successful description of pattern change accompanying deforestation provides a critical component of habitat analyses. 5. Conclusion The role that pattern plays in the conservation of species suggests that a landscape perspective bene®ts resource management. Landscape pattern will continue to be modi®ed by deforestation; when these changes in¯uence a species negatively, an understanding of how this can alter pattern provides resource managers with a basis for making land-use decisions. The results of the discriminant analysis suggest that the mastery of landscape analysis can be linked to the choice of the pattern metric. Some of the pattern metrics had similar values for very different landscapes, highlighting the importance of an awareness of metric sensitivity prior to application for environmental assessment. Concern about global and regional deforestation will continue to emphasize pattern analysis, requiring a knowledge of metric behavior for describing this process.

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This paper provided an approach for monitoring the in¯uence of deforestation on the landscape, and may serve as a guide for examining how pattern-related habitat components are affected by deforestation. The continued development of spatial analysis techniques will contribute to further awareness of the dynamics of landscape pattern. Successful application of landscape analysis depends on the ability to quantify pattern for accurately forecasting landscape modi®cation. Acknowledgements This study was partially funded by the Southern Regional Of®ce of the USDA Forest Service and the George Washington±Jefferson National Forests. Acknowledgment goes to Drs. James Campbell, Timothy Gregoire, and Dean Stauffer for their statistical expertize and to Drs. James Smith and Paul Angermeier for their counsel during the initial research plan. References Ambuel, B., Temple, S.A., 1983. Area-dependent changes in the bird communities and vegetation of southern Wisconsin forests. Ecol. 64(5), 1057±1068. Askins, R.A., 1994. Open corridors in a heavily forested landscape: Impact on shrubland and forest-interior birds. Wildl. Soc. Bull. 22, 339±347. Askins, R.A., Lynch, J.F., Greenberg, R., 1990. Population declines in migratory birds in eastern North America. Current Ornithology 7, 1±57. Berry, J.K., 1991. Assessing variation, shape, and pattern of map patches. GIS World, August±October issues. Davis, J.C., 1986. Statistics and Data Analysis in Geology. John Wiley and Sons, New York, NY. pp. 646. Dunn, C.P., Sharpe, D.M., Guntenspergen, G.R., Stearns, F., Yang, Z., 1991. Methods for analyzing temporal changes in landscape pattern. In: Turner, M.G., Gardner, R.H. (Eds.), Quantitative Methods in Landscape Ecology. Springer-Verlag, New York, NY. pp. 173±198. Eastman, J.R., 1997. Idrisi. Clark Labs for Cartographic Technology and Geographic Analysis. Worcester, MA. Forman, R.T.T., Godron, M., 1986. Landscape Ecology. John Wiley and Sons, New York, NY. pp. 619. Galli, A.E., Leck, C.F., Forman, R.T.T., 1976. Avian distribution patterns in forest islands of different sizes in central New Jersey. Auk 93(2), 356±364. Golley, F.B., 1989. Landscape ecology and biological conservation. Landscape Ecol. 2(4), 201±202.

469

Hamel, P.B., 1992. Land Manager's Guide to the Birds of the South. The Nature Conservancy, Chapel Hill, NC. pp. 417. Harris, L.D., 1988. Landscape linkages: The dispersal corridor approach to wildlife conservation. Trans. N. Am. Wildl. and Nat. Resour. Conf. 53, 595±607. LaGro Jr., J., 1991. Assessing patch shape in landscape mosaics. Photogrammetric Eng. Remote Sensing 57(3), 285±293. Lauga, J., Joachim, J., 1992. Modelling the effects for forest fragmentation on certain species of forest-breeding birds. Landscape Ecol. 6(3), 183±193. Levinson, J.B., 1981. Woodlots as biogeographic islands in southeastern Wisconsin. In: Burgess, R.L., Sharpe, D.M. (Eds.), Forest Island Dynamics in Man-dominated Landscapes. Springer-Verlag, New York, NY. pp. 13±39. Lynch, J.F., Whigham, D.F., 1984. Effects of forest fragmentation on breeding bird communities. Biol. Conserv. 28, 287± 324. Matthiae, P.E., Stearns, F., 1981. Mammals in forest islands southeastern Wisconsin. In: Burgess, R.L., Sharpe, D.M. (Eds.), Forest island dynamics in man-dominated landscapes. SpringerVerlag, New York, NY. pp. 55±66. McNeely, J.A., Miller, K.R., Reid, W.V., Mittermeier, R.A., Werner, T.B., 1990. Conserving the World's Biological Diversity. The International Union for the Conservation of Nature and Natural Resources, World Resources Institute, Conservation International, World Wildlife Fund-US, and the World Bank. Gland, Switzerland and Washington, DC. pp. 146. Monmonier, M.S., 1982. Computer-Assisted Cartography: Principles and Prospects. Prentice-Hall, Englewood Cliffs, NJ. pp. 214. Murphy, D.L., 1985. Estimating neighborhood variability with a binary comparison matrix. Photogrammetric Eng. Remote Sensing 51(6), 667±674. Naveh, Z., Lieberman, A.S., 1984. Landscape Ecology: Theory and Application. Springer- Verlag, New York, NY. pp. 356. Noss, R.F., Harris, L.D., 1986. Nodes, networks, and MUM's: Preserving diversity at all scales. Environ. Manage. 10, 299± 309. O'Neill, R.V., Krummel, J.R., Gardner, R.H., Sugihara, G., Jackson, B., DeAngelis, D.L., Milne, B.T., Turner, M.G., Zygmunt, B., Christensen, S.W., Dale, V.H., Graham, R.L., 1988. Indices of landscape pattern. Landscape Ecol. 1(3), 153± 162. Patton, D.R., 1975. A diversity index for quantifying habitat edge. Wildl. Soc. Bull. 3, 171±173. Pelton, M., 1986. Habitat needs of black bears in the East. In: Kulhavy, D., Conner, R. (Eds.), Wilderness and Natural Areas in the Eastern United States: A Management Challenge. Stephen F. Austin State Univ., Nacogdoches, TX. pp. 49± 53. Pielou, E.C., 1977. Mathematical Ecology. Wiley Publishing, New York, NY. pp. 385. Ranney, J.W., Bruner, M.C., Levenson, J.B., 1981. The importance of edge in the structure and dynamics of forest islands. In: Burgess, R.L., Sharpe, D.M. (Eds.), Forest Island Dynamics in Man-Dominated Landscapes. Springer-Verlag, New York, NY. pp. 67±96.

470

M.K. Trani, R.H. Giles, Jr. / Forest Ecology and Management 114 (1999) 459±470

Ripple, W.J., Bradshaw, G., Spies, T.A., 1991. Measuring landscape pattern in the Cascades Range of Oregon. Biol. Conserv. 57, 73±88. Robinove, C.J., 1986. Spatial diversity index mapping of classes in grid cell maps. Photogrammetric Eng. and Remote Sensing 52(8), 1171±1173. Robinson, S., Wilcove, D., 1994. Forest fragmentation in the temperate zone and its effects on migratory songbirds. Bird Conserv. Internat. 4, 233±249. Romme, W.H., 1982. Fire and landscape diversity in subalpine forests of Yellowstone National Park. Ecol. Monogr. 52, 199± 221. Rosenberg, K.V., Raphael, M.G., 1986. Effects of forest fragmentation in Douglas-fir forests. In: Verner, J., Morrison, M.L., Ralph, C.J. (Eds.), Wildlife 2000: Modeling Habitat Relationships of Terrestrial Vertebrates. Univ. of Wisconsin Press, Madison, WI. pp. 263±272. Roth, R.R., 1976. Spatial heterogeneity and bird species diversity. Ecol. 57, 773±782. Shannon, C.E., Weaver, W., 1963. The mathematical theory of communication. Univ. of Illinois Press, Urbana, IL. pp. 117. Trani, M.K., 1996. Landscape pattern analysis related to forest wildlife resources. Ph.D. Dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA. pp. 183.

Urban, D.L., Shugart Jr., H.H., 1986. Avian demography in mosaic landscapes: Modeling paradigm and preliminary results. In: Verner, J., Morrison, M.L., Ralph, C.J. (Eds.), Wildlife 2000: Modeling Habitat Relationships of Terrestrial Vertebrates. Univ. of Wisconsin Press, Madison, WI. pp. 273± 279. Van Dorp, D., Opdam, P.F.M., 1987. Effects of patch size, isolation, and regional abundance on forest bird communities. Landscape Ecol. 1(1), 59±73. Whitcomb, R.F., Robbins, C.S., Lynch, J.F., Whitcomb, B.L., Klimkiewicz, M.K., Bystrak, D., 1981. Effects of forest fragmentation on avifauna of eastern deciduous forest. In: Burgess, R.L., Sharpe, D.M. (Eds.), Forest Island Dynamics in Man-Dominated Landscapes. Springer-Verlag, New York, NY. pp. 125±205. Whitney, G.G., Runkle, J.R., 1981. Edge versus age effects in the development of a beech±maple forest. Oikos 37, 377± 381. Yahner, R.H., 1988. Changes in wildlife communities near edges. Conserv. Biol. 2(4), 333±339. Zonneveld, I.I., Forman, R.T.T. (Eds.), 1990. Changing Landscapes: An Ecological Perspective. Springer-Verlag, New York, NY. pp. 286.