Creation of forest edges has a global impact on forest vertebrates


Forest edges influence more than half of the world’s forests and contribute to worldwide declines in biodiversity and ecosystem functions. However, predicting these declines is challenging in heterogeneous fragmented landscapes. Here we assembled a global dataset on species responses to fragmentation and developed a statistical approach for quantifying edge impacts in heterogeneous landscapes to quantify edge-determined changes in abundance of 1,673 vertebrate species. We show that the abundances of 85% of species are affected, either positively or negatively, by forest edges. Species that live in the centre of the forest (forest core), that were more likely to be listed as threatened by the International Union for Conservation of Nature (IUCN), reached peak abundances only at sites farther than 200–400 m from sharp high-contrast forest edges. Smaller-bodied amphibians, larger reptiles and medium-sized non-volant mammals experienced a larger reduction in suitable habitat than other forest-core species. Our results highlight the pervasive ability of forest edges to restructure ecological communities on a global scale.

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Figure 1: Global distribution of the 22 study landscapes.
Figure 2: Forest occupancy and edge sensitivities for forest-core species.
Figure 3: Edge sensitivity and body size in forest-core vertebrates.


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We thank D. Coomes for contributions during the early stages of the BIOFRAG project, B. Phalan, P. Stouffer, H. Possingham and the Western Australian Department of Parks and Wildlife for supplying additional data from Ghana, Brazil, Australia and Western Australia, respectively, J. Tylianakis for providing comments on an earlier draft of the manuscript. M.P., V.L. and R.M.E. were supported by European Research Council Project number 281986. This paper represents a contribution to the Grand Challenges in Ecosystems and the Environment Initiative of Imperial College.

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M.P., V.L. and R.M.E. designed the study and wrote the first draft of the manuscript. M.P. conducted all analyses and V.L. developed the methodology. R.M.E. and all other authors contributed data. All authors commented on manuscript drafts.

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Correspondence to M. Pfeifer.

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Reviewer Information Nature thanks P. Potapov, C. Sekercioglu and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Figure 1 Matrix occupancy by matrix species per edge-response type and mean number of species per habitat category.

a, Mean number of species per matrix site (number of matrix sites = 727; 7 for amphibians, 659 for birds, 51 for mammals and 10 for reptiles), weighted so that the contributions of core and edge habitats are equivalent (Methods, equations (7)–(9)). Only species classified as preferring the matrix are shown (that is, matrix core, matrix edge, matrix with no edge response). b, Mean number of species (regardless of edge-response type) in each habitat category showing which habitat can support the largest number of species after addressing the ambiguity resulting from sampling bias across different landscape configurations (Methods, equation (10)). Plots were categorized by their locations into forest-core (n = 2,955), forest-edge (n = 1,404), matrix-core (n = 388) and matrix-edge plots (n = 339). For each configuration we computed the mean number of species present per habitat category plot, which identifies the habitat that can support larger numbers of species. For amphibians, reptiles and mammals, forest-core habitats supported more species than did forest-edge, matrix-core or matrix-edge habitats. By contrast, bird species were found in larger numbers in edge habitats (in forest and matrix) than in core habitats.

Extended Data Figure 2 Distribution of edge sensitivities for seven recognized edge-response types.

Forest-core (n = 519) and matrix-core species (n = 80) displayed significantly higher edge sensitivities compared to generalists (n = 56) and to forest (n = 112) and matrix species (n = 34), with no preference for either edge or core habitats (two-sided pairwise Wilcoxon signed-rank test with Bonferroni correction: P < 0.001). We excluded species that could not be classified (n = 113). Forest-edge species (n = 338) had significantly higher edge sensitivities compared to forest no preference, matrix no preference, generalist and matrix-edge species (P < 0.001). Matrix-edge species (n = 165) also displayed significantly lower edge sensitivities compared to matrix-core species and higher edge sensitivities compared to generalists (P < 0.001). Notched boxes show the median, 25th and 75th percentiles, error bars show 10th and 90th percentiles, and points indicate outliers. Notches display the 95% confidence interval around the median.

Extended Data Figure 3 Significant relationship between edge sensitivity and body size across edge-response types.

This excludes forest-core species that are shown in Fig. 3. Vertical lines indicate median body size of the species per taxonomic group and edge-response type (mammals forest no preference, 43.8 g; mammals matrix edge, 47.0 g; reptiles, unknown 97.5 mm). Smoothed curves and 95% confidence intervals were obtained from general additive models, with the model weighted by a variable that reflects dataset reliability (Methods). General additive models better explained the data than a null model for taxa and edge-response types shown. Edge sensitivity ranges from 0.0 (no declines in local abundance due to edge effects) to 1.0 (local extinction due to edge effects).

Extended Data Figure 4 Illustration of the graph of C − I.

Combinations of C and I values characterize different landscape configurations, although some combinations are impossible by design (areas outside of the bold lines (upper right and lower left corners)). The x axis represents the percentage of tree cover at the scale of a pixel. The y axis represents I, computed from the regional standard deviation of C (a measurement of regional heterogeneity) and the regional average of C subtracted by individual values of C (a measurement of point heterogeneity and direction).

Extended Data Figure 5 Variations of I with C configuration and contrast.

a, Landscape configuration and the amplitude of I. Top, four examples of landscape configurations comprising dense tree cover habitats (green) and matrix (cream). From left to right: creek edge, straight edge, peninsula edge and small forest patch. Bottom, maps of I that correspond to the above landscape configurations. The value of I at the central point (cross) is given for each configuration. The central point is always located on an edge and its distance to the nearest edge is always zero. Nonetheless, I increases in absolute value as the central point is increasingly surrounded by a different type of habitat. b, Forest–matrix contrast and the amplitude of I. Top, Four examples of peninsula edges between matrix (cream, C = 0%) and habitats of varying tree density (shades of green). From left to right: C = 25%, 50%, 75% and 100%. Bottom, maps of I that correspond to the above landscape contrasts. The value of I at the central point (cross) is given for each configuration. The central point is always located on an edge and its distance to nearest edge is always zero. I increases as the edge contrast increases.

Extended Data Figure 6 Computing species abundance surfaces and simulated edge-response types on the graph of C − I.

a, Plots superimposed on a hypothetical map of C. Marker colours correspond to the abundance of a hypothetical species and follow the colour bar shown in c. b, Map of I corresponding to a. c, Graph of C − I: species abundance (warm colour, higher abundance) is plotted as a function of C and I measured at the species’ plots. In this example, the species is predominantly found in sites characterized by a high C and low |I|, and would be classified as a forest-core species. d, Illustration of the training set of edge-response types used for classification. Each of the seven response types has around 15 patterns associated with it in the training set; here we show two examples for the forest-core and forest-edge type and one example for the forest no-preference type. Each graph is a graph of C − I with C on the x axis and I on the y axis. Warmer colours indicate a high abundance, dark blue is 0.

Extended Data Table 1 Summary statistics of species and landscapes assessed in our study
Extended Data Table 2 Attributes describing the geographical context for each landscape
Extended Data Table 3 Number of threatened and not-threatened species for forest-core and all other species in each taxonomic group
Extended Data Table 4 Importance of predictor variables in explaining edge sensitivities of forest-core ectotherms and endotherms

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Pfeifer, M., Lefebvre, V., Peres, C. et al. Creation of forest edges has a global impact on forest vertebrates. Nature 551, 187–191 (2017).

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