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The role of seasonal migration in predicting amphibian population persistence across fragmented tropical landscapes: an individual-based model

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Anthropogenic habitat disturbances often create discontinuity between the multiple classes of natural habitats that many species need to complete their life cycles. This process, termed habitat split, is common across Neotropical landscapes and negatively impacts several classes of vertebrates and invertebrates. For instance, habitat split—often arising from habitat loss and fragmentation—exposes aquatic-breeding amphibians to risky migrations through disturbed environments as they move between natural terrestrial habitats and aquatic breeding sites, contributing to population declines. In contrast, terrestrial-breeding amphibians should not be impacted by this form of habitat split because they may spend their entire life cycle in the same terrestrial habitat. We used available field data and natural history information to develop Individual-Based Models (IBM) that account for seasonal migrations to quantify the impact of different levels of habitat split on population survival of Brazilian amphibians. Our IBM results align with our observed field data, indicating a disproportionate decline in the occurrence and population abundances of migrating aquatic-breeding amphibians compared to non-migratory terrestrial-breeding amphibians in regions with high habitat split. An intermediate dispersal optimum for aquatic-breeding frogs was suggested by our IBM, indicating that long-distance dispersal might not always be advantageous for population persistence, likely due to tradeoffs between reproduction and migration risk. Our spatial model framework factoring breeding migration could be applied widely across ecoregions of interest and help inform targeted habitat restoration strategies to curb localized amphibian declines and extinctions.

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Amphibia, Amphibian declines, Anura, Atlantic forest, Deforestation, Dispersal, Migration, Reproductive mode

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Biodiversity and Conservation.

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