Understanding Species–Habitat Associations: A Case Study with the World’s Bears
David Lance Garshelis
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David Lance Garshelis: IUCN SSC Bear Specialist Group, Cohasset, MN 55721, USA
Land, 2022, vol. 11, issue 2, 1-39
Abstract:
Habitat modeling is one of the most common practices in ecology today, aimed at understanding complex associations between species and an array of environmental, bioclimatic, and anthropogenic factors. This review of studies of seven species of terrestrial bears (Ursidae) occupying four continents examines how habitat models have been employed, and the functionality of their predictions for management and conservation. Bear occurrence data have been obtained at the population level, as presence points (e.g., sign surveys or camera trapping), or as locations of individual radio-collared animals. Radio-collars provide greater insights into how bears interact with their environment and variability within populations; they are more commonly used in North America and Europe than in South America and Asia. Salient problematic issues apparent from this review included: biases in presence data; predictor variables being poor surrogates of actual behavioral drivers; predictor variables applied at a biologically inappropriate scale; and over-use of data repositories that tend to detach investigators from the species. In several cases, multiple models in the same area yielded different predictions; new presence data occurred outside the range of predicted suitable habitat; and future range projections, based on where bears presently exist, underestimated their adaptability. Findings here are likely relevant to other taxa.
Keywords: habitat adaptability; habitat model; habitat selection; habitat suitability; use versus availability; Maxent; presence points; GPS radio-collars; anthropogenic variables; species distribution models (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:2:p:180-:d:731397
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