Predictor species: Improving assessments of rare species occurrence by modeling environmental co-responses.

ABSTRACT: Designing an effective conservation strategy requires understanding where rare species are located. Because rare species can be difficult to find, ecologists often identify other species called conservation surrogates that can help inform the distribution of rare species. Species distribution models typically rely on environmental data when predicting the occurrence of species, neglecting the effect of species' co-occurrences and biotic interactions. Here, we present a new approach that uses Bayesian networks to improve predictions by modeling environmental co-responses among species. For species from a European peat bog community, our approach consistently performs better than single-species models and better than conventional multi-species approaches that include the presence of nontarge

SUBMITTER: Thompson PR 

PROVIDER: S-EPMC7140998 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature