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  1. Free, publicly-accessible full text available November 1, 2024
  2. Abstract Fragmentation and scale

    Although habitat loss has well‐known impacts on biodiversity, the effects of habitat fragmentation remain intensely debated. It is often argued that the effects of habitat fragmentation, or the breaking apart of habitat for a given habitat amount, can be understood only at the scale of entire landscapes composed of multiple habitat patches. Yet, fragmentation also impacts the size, isolation and habitat edge for individual patches within landscapes. Addressing the problem of scale on fragmentation effects is crucial for resolving how fragmentation impacts biodiversity.

    Scaling framework

    We build upon scaling concepts in ecology to describe a framework that emphasizes three “dimensions” of scale in habitat fragmentation research: the scales of phenomena (or mechanisms), sampling and analysis. Using this framework, we identify ongoing challenges and provide guidance for advancing the science of fragmentation.

    Implications

    We show that patch‐ and landscape‐scale patterns arising from habitat fragmentation for a given amount of habitat are fundamentally related, leading to interdependencies among expected patterns arising from different scales of phenomena. Aggregation of information when increasing the grain of sampling (e.g., from patch to landscape) creates challenges owing to biases created from the modifiable areal unit problem. Consequently, we recommend that sampling strategies use the finest grain that captures potential underlying mechanisms (e.g., plot or patch). Study designs that can capture phenomena operating at multiple spatial extents offer the most promise for understanding the effects of fragmentation and its underlying mechanisms. By embracing the interrelationships among scales, we expect more rapid advances in our understanding of habitat fragmentation.

     
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  3. Abstract

    Maintaining the ability of organisms to move between suitable patches of habitat despite ongoing habitat loss is essential to conserving biodiversity. Quantifying connectivity has therefore become a central focus of conservation planning. A large number of metrics have been developed to estimate potential connectivity based on habitat configuration, matrix structure and information on organismal movement, and it is often assumed that metrics explain actual connectivity. Yet, validation of metrics is rare, particularly across entire landscapes undergoing habitat loss—a crucial problem that connectivity conservation aims to mitigate.

    We leveraged a landscape‐scale habitat loss and fragmentation experiment to assess the performance of commonly used patch‐ and landscape‐scale connectivity metrics against observed movement data, test whether incorporating information about the matrix improves connectivity metrics and examine the performance of metrics across a gradient of habitat loss. We tested whether 38 connectivity metrics predict movement at the patch (i.e. patch immigration rates) and landscape (i.e., total movements) scale for a pest insect, the cactus bugChelinidea vittiger, across 15 replicate landscapes.

    Metrics varied widely in their ability to explain actual connectivity. At the patch scale, dPCflux, which describes the contribution of a patch to movement across the landscape independent of patch size, best explained immigration rates. At the landscape scale, total movements were best explained by a mesoscale metric that captures that distance between clusters of patches (i.e. modules). Incorporating the matrix did not necessarily improve the ability of metrics to predict actual connectivity. Across the habitat loss gradient, dPCfluxwas sensitive to habitat amount.

    Synthesis and applications. Our study provides a much‐needed evaluation of network connectivity metrics at the patch and landscape scales, emphasizing that accurate quantification of connectivity requires the incorporation, not only of habitat amount but also habitat configuration and information on dispersal capability of species. We suggest that variation in habitat may often be more critical for interpreting network connectivity than the matrix, and advise that connectivity metrics may be sensitive to habitat loss and should therefore be applied with caution to highly fragmented landscapes. Finally, we recommend that applications integrate mesoscale configuration of habitat into connectivity strategies.

     
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