Modelling Habitat Connectivity Using Circuit Theory for Mammal Conservation Corridors

Habitat fragmentation is a significant barrier to the ability of terrestrial mammals to move freely across landscapes and also disrupts the genetic flow among populations. In this study, we employed circuit theory to investigate habitat connectivity and identify conservation corridors for mammals in fragmented landscapes. Circuit theory utilizes the fundamentals of electrical resistance theory to establish connections among landscapes as a conductive surface, representing landscape heterogeneity by assigning resistance values based on land cover, topography, and anthropogenic features. We developed resistance surfaces using ecological and movement data for species of interest to derive many possible dispersal pathways for mammals. Throughout the study area, we utilized Circuitscape to illustrate connectivity, which helped identify key corridors that maximize movement between core habitat patches or areas of high current density, where movement is most likely to occur. Results show that classic corridor models generally ignore alternative, but ecologically relevant routes that can be captured with a circuit-based approach. Overall, our results suggest that integrating circuit theory into conservation planning is a sound mechanism for identifying multifunctional corridors that enhance landscape permeability and resilience. This method helps prioritize areas to conserve, restore, and use sustainably, thereby maximizing the probability of persistence of mammal populations in an increasingly fragmented landscape.

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Publication Details

Journal
Natural and Engineering Sciences
Published
2025-09-01
DOI
https://doi.org/10.28978/nesciences.1763898
Primary Topic
Wildlife-Road Interactions and Conservation
Type
article
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article

Modelling Habitat Connectivity Using Circuit Theory for Mammal Conservation Corridors

D. Roselin Jenifer, Tapas Kumar Mohapatra, Sahil Khurana, S RenukaJyothi et al.
Natural and Engineering Sciences
Wildlife-Road Interactions and Conservation
article

Modelling Habitat Connectivity Using Circuit Theory for Mammal Conservation Corridors

D. Roselin Jenifer, Tapas Kumar Mohapatra, Sahil Khurana, S RenukaJyothi, Debkumar Ghosh, Sunny Verma
article en

Abstract

Habitat fragmentation is a significant barrier to the ability of terrestrial mammals to move freely across landscapes and also disrupts the genetic flow among populations. In this study, we employed circuit theory to investigate habitat connectivity and identify conservation corridors for mammals in fragmented landscapes. Circuit theory utilizes the fundamentals of electrical resistance theory to establish connections among landscapes as a conductive surface, representing landscape heterogeneity by assigning resistance values based on land cover, topography, and anthropogenic features. We developed resistance surfaces using ecological and movement data for species of interest to derive many possible dispersal pathways for mammals. Throughout the study area, we utilized Circuitscape to illustrate connectivity, which helped identify key corridors that maximize movement between core habitat patches or areas of high current density, where movement is most likely to occur. Results show that classic corridor models generally ignore alternative, but ecologically relevant routes that can be captured with a circuit-based approach. Overall, our results suggest that integrating circuit theory into conservation planning is a sound mechanism for identifying multifunctional corridors that enhance landscape permeability and resilience. This method helps prioritize areas to conserve, restore, and use sustainably, thereby maximizing the probability of persistence of mammal populations in an increasingly fragmented landscape.

Natural and Engineering SciencesVol. 10(2)
Openalex Percentile: Top 76%
Wildlife-Road Interactions and Conservation
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Modelling Habitat Connectivity Using Circuit Theory for Mammal Conservation Corridors — D. Roselin Jenifer, Tapas Kumar Mohapatra, et al. · Natural and Engineering Sciences (2025) | TGRS Research Map | TGRS