Using data from related species to overcome spatial sampling bias and associated limitations in ecological niche modeling

1. Ecological niche modeling (ENM) is used widely to aid in conservation planning and management, often focusing on rare species characterized by the biased observations associated with restricted geographic ranges, habitat specialization, small population size, and limited natural history information. Generating reliable ENMs for such species is a challenge, however, owing to issues that arise from spatial sampling bias, such as model inaccuracy and overfitting. Here, using virtual scenarios, we assess the utility of integrating occurrence data for closely related species with varying degrees of niche overlap into ENMs of focal species.
2. We consider two approaches to merge related and focal species models: integrating occurrences of focal and related species directly as inputs with which to generate ENMs, versus creating ENMs based on occurrences of focal and related species separately and merging results based on Bayesian inference approaches.
3. Both single, integrated models and...