Bringing circuit theory into spatial occupancy models to assess landscape connectivity

Abstract Occupancy models were originally developed to better understand species distribution while accounting for imperfect detection. Because species distribution is not only shaped by habitat quality but also by the ability of individuals to reach suitable habitats, spatial dynamic occupancy models have been proposed to extend the original framework by defining that site colonisation was a function of the Euclidean distance to occupied sites. However, not all sites in the landscape are equally accessible due to the presence of barriers, that of corridors, etc. To account for connectivity between sites, the Euclidean distance has recently been replaced by a least‐cost path distance, which explicitly accounts for landscape resistance, but assumes that individuals will follow the optimal route. To relax this assumption, we first developed a new spatial occupancy model that incorporates commute‐time distance derived from circuit theory to model accessibility across sites. This distance has the advantage of modelling movement as a random walk and accounting for the fact that colonisation could be achieved from multiple paths. Our approach allows for the explicit estimation of landscape connectivity from detection/non‐detection data and a direct measure of connectivity uncertainty. We implemented the model in the Bayesian framework using the nimble R package, which allows useful R connectivity functions to be called from within the model. Second, we carried out a simulation study to assess the performance of our model by considering four scenarios depicting an increasing level of landscape resistance. Third, to illustrate our new approach, we studied the recolonisation of two carnivores in France. We quantified the degree to which rivers facilitate Eurasian otter ( Lutra lutra ) colonisation and highways impede Eurasian lynx ( Lynx lynx ) colonisation. Overall, spatial occupancy models provide a flexible framework to accommodate any distance metric designed to align with species dispersal ecology.

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Publication Details

Journal
Methods in Ecology and Evolution
Published
2024-09-23
DOI
https://doi.org/10.1111/2041-210x.14418
Citations
8
Primary Topic
Wildlife-Road Interactions and Conservation
Type
article
Field-Weighted Citation Impact
3.67
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article

Bringing circuit theory into spatial occupancy models to assess landscape connectivity

Nolwenn Drouet‐Hoguet, Julien Steinmetz, Sarah Bauduin, Maëlis Kervellec et al.
8 citations
Methods in Ecology and Evolution
Wildlife-Road Interactions and Conservation
3.67
article

Bringing circuit theory into spatial occupancy models to assess landscape connectivity

Nolwenn Drouet‐Hoguet, Julien Steinmetz, Sarah Bauduin, Maëlis Kervellec, Delphine Chenesseau, Thibaut Couturier, Jean‐Michel Vandel, Pierre Defos du Rau, Christophe Duchamp, Olivier Giménez
article en
8 citations

Abstract

Abstract Occupancy models were originally developed to better understand species distribution while accounting for imperfect detection. Because species distribution is not only shaped by habitat quality but also by the ability of individuals to reach suitable habitats, spatial dynamic occupancy models have been proposed to extend the original framework by defining that site colonisation was a function of the Euclidean distance to occupied sites. However, not all sites in the landscape are equally accessible due to the presence of barriers, that of corridors, etc. To account for connectivity between sites, the Euclidean distance has recently been replaced by a least‐cost path distance, which explicitly accounts for landscape resistance, but assumes that individuals will follow the optimal route. To relax this assumption, we first developed a new spatial occupancy model that incorporates commute‐time distance derived from circuit theory to model accessibility across sites. This distance has the advantage of modelling movement as a random walk and accounting for the fact that colonisation could be achieved from multiple paths. Our approach allows for the explicit estimation of landscape connectivity from detection/non‐detection data and a direct measure of connectivity uncertainty. We implemented the model in the Bayesian framework using the nimble R package, which allows useful R connectivity functions to be called from within the model. Second, we carried out a simulation study to assess the performance of our model by considering four scenarios depicting an increasing level of landscape resistance. Third, to illustrate our new approach, we studied the recolonisation of two carnivores in France. We quantified the degree to which rivers facilitate Eurasian otter ( Lutra lutra ) colonisation and highways impede Eurasian lynx ( Lynx lynx ) colonisation. Overall, spatial occupancy models provide a flexible framework to accommodate any distance metric designed to align with species dispersal ecology.

Methods in Ecology and EvolutionVol. 15(11)
Centre National de la Recherche Scientifique (FR), École Pratique des Hautes Études (FR), Université de Montpellier (FR), Centre d'Écologie Fonctionnelle et Évolutive (FR), French National Agency for Water and Aquatic Environments (FR), Institut de Recherche pour le Développement (FR), Office Français de la Biodiversité
Life in Land
Openalex Percentile: Top 7%
Wildlife-Road Interactions and Conservation
3.67
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