Combining threat and occurrence models to predict potential ecological traps for Andean bears in the Cordillera de Mérida, Venezuela

Ecological traps occur when rapid environmental change makes organisms’ habitat selection cues misleading and leads them to prefer poor quality habitats. Such traps can threaten the persistence of affected populations, so techniques to predict and map potential traps are of great conservation interest. Here we present a novel method for visualizing such traps and their uncertainty at large scales in a natural landscape, by combining a spatially explicit model of anthropogenic threats with one of occurrence probability. We began with poaching and occurrence data for Andean bears in the Cordillera de Merida, Venezuela, and applied a partitioning procedure to generate 10 replicates of three partially independent data subsets. To the first subset, we fit a previously developed model of poaching probability, while we used the second and third subsets to fit, validate and select the best of four occurrence probability models. We then combined replicates of the poaching probability model with those of the best occurrence probability model to predict the spatial distribution and uncertainty of potential ecological traps. The best occurrence model predicted high probabilities in the center and in the northern parts of Cordillera de Merida, with variation among replicates in the same areas. Predicted areas of occurrence covered 10 217 ± 2762 km 2 (24%) of the study area. However, more than a third of this area had a high probability of being an ecological trap. Furthermore, these potential ecological traps were next to or within the largest national parks and were surrounded by large areas with high occurrence probability and low poaching probability. Future research should focus on independent verification of potential occupancy and ecological traps, as well as on bear dispersal behavior. In areas where ecological traps are confirmed, targeted education and law enforcement will be most effective, while in confirmed safe harbor areas, increasing connectivity will be equally important. Our approach will be useful to identify potential ecological traps at the landscape level created by hunting and other human activities elsewhere in the world.