A sparse observation model to quantify species distributions and their overlap in space and time

Liam Singer, Sadoune Ait Kaci Azzou, Thierry Aebischer, Madleina Caduff, Beat Wolf & Daniel Wegmann
Camera traps and acoustic recording devices are essential tools to quantify the distribution, abundance and behavior of mobile species. Varying detection probabilities among device locations must be accounted for when analyzing such data, which is generally done using occupancy models. We introduce a Bayesian Time-dependent Observation Model for Camera Trap data (Tomcat), suited to estimate relative event densities in space and time. Tomcat allows to learn about the environmental requirements and daily activity patterns of...

Registration Year

  • 2021
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Resource Types

  • Dataset
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Affiliations

  • University of Applied Sciences and Arts Western Switzerland
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  • University of Fribourg
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