SummaryForest edges influence more than half the world’s forests and contribute to worldwide declines in biodiversity and ecosystem functions. However, predicting these declines is challenging in heterogeneous fragmented landscapes. We assembled an unmatched global dataset on species responses to fragmentation and developed a new statistical approach for quantifying edge impacts in heterogeneous landscapes to quantify edge-determined changes in abundance of 1673 vertebrate species. We show that 85% of species’ abundances are affected, either positively or negatively, by forest edges. Forest core species, which were more likely to be listed as threatened by the IUCN, only reached peak abundances 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.

Aim Predicting extinctions before they are realized has proven difficult, yet is increasingly important for biodiversity conservation as habitat destruction continues unabated around the world. We evaluated whether habitat suitability models can be used in conjunction with species-area relationships (SAR) to detect apparent extinction debts as implicated by the conservation status assigned to bird species.Location KwaZulu-Natal province, South Africa. Methods We modelled historic distributions of coastal forests using MaxEnt, a presence-only technique for modelling species distributions. The model provided an estimate of forest loss. We then conducted 293 point counts to survey birds within remaining forest fragments and employed an information-theoretic framework to test for the best fit SAR model. Extinction debts were calculated using the estimate of forest loss and the empirical SAR data.Results Our model suggests extensive forest loss (82%) within a naturally fragmented landscape. The power function provided the best fit for bird SAR. Fourteen bird species are predicted to go extinct from coastal forests. Predicted extinctions closely matched the number of threatened species locally but not globally. Predicted extinctions also only matched globally threatened species that reach their northernmost distribution limit within coastal forests, but not species that reach their southernmost distribution limit here.Main conclusions We found that habitat suitability models could be used in conjunction with SAR to estimate extinction debt implied by conservation statuses of extant species. Our approach assumed that forest loss drives extinction debts but also provided the opportunity to link forest loss and the likelihood of extinction. Models of historical forest distribution may provide guidelines of where to implement restoration actions. Maintaining matrix habitats that link forest fragments and targeted landscape level restoration that increases fragment area and link isolated fragments will be important to prevent predicted extinctions.

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AimWe used a hierarchical fractal-based sampling design to test how sampling scale influences i) beta diversity and ii) inferences on the modelled contribution of niche-versus dispersal-based assembly processes in structuring tree and bird assemblages. Location Coastal forest fragments, South AfricaMethods We surveyed 103 tree and 267 bird points within eight forest fragments and partitioned beta diversity (β sor ) into its turnover (β sim ) and nestedness (β nes ) components. We evaluated how sampling at fine, intermediate and coarse scales influenced beta diversity components and compared how tree and bird beta diversity respond to sampling grain variation. We then explored the relative contributions of niche-and dispersal based assembly processes in explaining spatial turnover as a function of sampling grain and/or study taxon by using multiple regression modelling on distance matrices and variance partitioning. 1Results Beta diversity (β sor ) of trees and birds was mainly explained by spatial turnover (β sim ) at all sampling scales. For both taxonomic groups, β sor and β sim decreased as sampling scale increased.Beta diversity differed among trees and birds at fine, but not at coarse sampling scales. Dispersalbased assembly processes were the best predictors of community assembly at fine scales, whereas niche-based assembly processes were the best predictors at coarse scales. Most of the variation in tree community composition was, however, explained at fine scales (by dispersal-based assembly processes), while most of the variation in bird community composition was explained at coarse scales (by niche-based assembly processes).Main conclusions Our study shows that inferences from beta diversity are scale dependent. By matching the grain of the data with the grain at which predictor variables and associated processes are likely to operate, multi-scale sampling approaches can improve biodiversity conservation and should be part of incentives directed at ecological sensible conservation plans.

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