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The relative importance of local versus landscape variables on site occupancy in bats of the Brazilian Cerrado
Authors:Poliana Mendes  Kimberly A With  Luciana Signorelli  Jr" target="_blank">Paulo De MarcoJr
Institution:1.Ecology Department, Biological Sciences Institute,Federal University of Goiás,Goiania,Brazil;2.Laboratory for Landscape and Conservation Ecology, Division of Biology,Kansas State University,Manhattan,USA
Abstract:

Context

Species site-occupancy patterns may be influenced by habitat variables at both local and landscape scales. Although local habitat variables influence whether the site is suitable for a given species, the broader landscape context can also influence site occupancy, particularly for species that are sensitive to land-use change.

Objectives

To examine the relative importance of local versus landscape variables in explaining site occupancy of eight bat species within the Brazilian Cerrado, a Neotropical savanna that is experiencing widespread habitat loss and fragmentation.

Methods

Bats were surveyed within 16 forest patches over two years. We used a multi-model information-theoretic approach, adjusted for species detection bias, to assess whether landscape variables (percent cover and number of patches of natural vegetation within a 2- and 8-km radius of each forest site) or local site variables (canopy cover, understory height, number of trees, and number of lianas) best explained site occupancy in each species.

Results

Landscape variables were among the best models (ΔAICc or ΔQAICc < 2) for four species (top-ranked model for black myotis), whereas local variables were among the best for five species (top-ranked model for vampire bats). Neither local nor landscape variables explained site occupancy in two frugivorous species.

Conclusion

Species associated with a particular habitat type will not respond similarly to the amount, distribution or relative suitability of that habitat, or even at the same scale. This reinforces the challenge of species distribution modelling, especially in the context of forecasting species’ responses to future land-use or climate-change scenarios.
Keywords:
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