2021
DOI: 10.1111/ecog.05411
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A sparse observation model to quantify species distributions and their overlap in space and time

Abstract: 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 activit… Show more

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Cited by 10 publications
(8 citation statements)
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“…The use of two‐species occupancy models that incorporate temporal overlap (e.g. Ait Kaci Azzou et al, 2021 ; Kellner et al, 2022 ) could allow us to further understand how ecologically similar species aggregate or segregate temporally across an ecological community in response to global change. Finally, understanding interspecific spatial associations among terrestrial mammals and other vertebrates could reveal important insight about whether the patterns of co‐occurrence shown in this study are taxon‐specific or found more widely in tropical forest systems.…”
Section: Discussionmentioning
confidence: 99%
“…The use of two‐species occupancy models that incorporate temporal overlap (e.g. Ait Kaci Azzou et al, 2021 ; Kellner et al, 2022 ) could allow us to further understand how ecologically similar species aggregate or segregate temporally across an ecological community in response to global change. Finally, understanding interspecific spatial associations among terrestrial mammals and other vertebrates could reveal important insight about whether the patterns of co‐occurrence shown in this study are taxon‐specific or found more widely in tropical forest systems.…”
Section: Discussionmentioning
confidence: 99%
“…multispecies occupancy models; Mackenzie et al 2004, Rota et al 2016) or spatiotemporal models (e.g. co‐detection modelling: Cusack et al 2017; time‐dependent observation modelling: Ait Kaci Azzou et al 2021) can yield a more complete picture of fine‐scale avoidance of competitors, and how human disturbance might be mediating these interactions. The coefficient of temporal overlap is a useful tool in measuring the average temporal overlap between species and large‐scale responses to human disturbance, but it can overlook fine‐scale interactions that are essential to allow coexistence.…”
Section: Discussionmentioning
confidence: 99%
“…Methods like GPS telemetry and camera trapping facilitate inference on both spatial and temporal distribution simultaneously. Furthermore, using indices that simultaneously estimate predator–prey overlap in space and time, such as occupancy models with a continuous‐time detection process (Kellner et al, 2022) or Bayesian time‐dependent observation models (Ait Kaci Azzou et al, 2021), can avoid these issues and provide more accurate estimates of human impact on encounter probabilities. Applying our proposed framework to such inferences would provide a rigorous test of how humans influence predator–prey outcomes across dimensions.…”
Section: Linking Predator–prey Overlap To Ecological Outcomesmentioning
confidence: 99%