Identifying conservation priorities in a defaunated tropical biodiversity hotspot
Identifying spatial patterns of biodiversity in heavily defaunated landscapes may require novel methodological and analytical approaches. Our results indicate that to build robust prediction maps it is beneficial to sample over large spa-tial scales, use multiple detection methods to increase detections for rare species, include anthropogenic covariates that capture different aspects of hunting pressure and analyse data within a Bayesian multispecies framework. Our models further sug-gest that more remote areas should be prioritized for anti-poaching efforts to prevent the loss of rare and endemic species.
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