The devil is in the detail: Environmental variables frequently used for habitat suitability modeling lack information for forest-dwelling bats in Germany
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Philipps-Universität Marburg
Abstract
In response to the pressing challenges of the ongoing biodiversity crisis, the protection
of endangered species and their habitats, as well as the monitoring of invasive species
are crucial. Habitat suitability modeling (HSM) is often treated as the silver bullet to
address these challenges, commonly relying on generic variables sourced from widely
available datasets. However, for species with high habitat requirements, or for mod-
eling the suitability of habitats within the geographic range of a species, variables at
a coarse level of detail may fall short. Consequently, there is potential value in con-
sidering the incorporation of more targeted data, which may extend beyond readily
available land cover and climate datasets. In this study, we investigate the impact of
incorporating targeted land cover variables (specifically tree species composition) and
vertical structure information (derived from LiDAR data) on HSM outcomes for three
forest specialist bat species (Barbastella barbastellus, Myotis bechsteinii, and Plecotus
auritus) in Rhineland-Palatinate, Germany, compared to commonly utilized environ-
mental variables, such as generic land-cover classifications (e.g., Corine Land Cover)
and climate variables (e.g., Bioclim). The integration of targeted variables enhanced
the performance of habitat suitability models for all three bat species. Furthermore,
our results showed a high difference in the distribution maps that resulted from using
different levels of detail in environmental variables. This underscores the importance
of making the effort to generate the appropriate variables, rather than simply relying
on commonly used ones, and the necessity of exercising caution when using habitat
models as a tool to inform conservation strategies and spatial planning efforts.