A general framework for estimating the spatio-temporal distribution of a species using multiple data types
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Species distribution models (SDMs) are useful tools to help ecologists quantify species-environment relationships, and they are increasingly used to help determine the impacts of climate and habitat changes on species. In practice, data are often collections of presence-only sightings from citizen scientists, whose search effort may be highly heterogeneous throughout the study region. Many standard modelling approaches ignore search effort, which can severely bias SDMs. We present a novel marked spatio-temporal point process framework for combining data of differing type and quality. We apply this to combine multiple datasets collected on the endangered Southern Resident Killer Whales, to estimate their monthly effort-corrected space-use.
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