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A sparse observation model to quantify species interactions in time and space

View ORCID ProfileSadoune Ait Kaci Azzou, Liam Singer, Thierry Aebischer, Beat Wolf, View ORCID ProfileDaniel Wegmann
doi: https://doi.org/10.1101/815027
Sadoune Ait Kaci Azzou
aDepartment of Biology, Université de Fribourg, Chemin du Musée 10, CH-1700 Fribourg, Switzerland
bSwiss Institute of Bioinformatics, 1700 Fribourg, Switzerland
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  • ORCID record for Sadoune Ait Kaci Azzou
Liam Singer
aDepartment of Biology, Université de Fribourg, Chemin du Musée 10, CH-1700 Fribourg, Switzerland
bSwiss Institute of Bioinformatics, 1700 Fribourg, Switzerland
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Thierry Aebischer
aDepartment of Biology, Université de Fribourg, Chemin du Musée 10, CH-1700 Fribourg, Switzerland
bSwiss Institute of Bioinformatics, 1700 Fribourg, Switzerland
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Beat Wolf
ciCoSys, University of Applied Sciences Western Switzerland, Fribourg, Switzerland
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Daniel Wegmann
aDepartment of Biology, Université de Fribourg, Chemin du Musée 10, CH-1700 Fribourg, Switzerland
bSwiss Institute of Bioinformatics, 1700 Fribourg, Switzerland
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  • For correspondence: daniel.wegmann@unifr.ch
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Summary

  1. 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.

  2. 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 species while accounting for imperfect detection. It further implements a sparse model that deals well will a large number of potentially highly correlated environmental variables.

  3. By integrating both spatial and temporal information, we extend the notation of overlap coefficient between species to time and space to study niche partitioning.

  4. Synthesis and applications. We illustrate the power of Tomcat through an application to camera trap data of eight sympatrically occurring duiker Cephalophinae species in the the savanna - rainforest ecotone in the Central African Republic and show that most species pairs show little overlap. Exceptions are those for which one species is very rare, likely as a result of direct competition.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 21, 2020.
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A sparse observation model to quantify species interactions in time and space
Sadoune Ait Kaci Azzou, Liam Singer, Thierry Aebischer, Beat Wolf, Daniel Wegmann
bioRxiv 815027; doi: https://doi.org/10.1101/815027
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A sparse observation model to quantify species interactions in time and space
Sadoune Ait Kaci Azzou, Liam Singer, Thierry Aebischer, Beat Wolf, Daniel Wegmann
bioRxiv 815027; doi: https://doi.org/10.1101/815027

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