Abstract

Corridors are popular conservation tools because they are thought to allow animals to safely move between habitat fragments, thereby maintaining landscape connectivity. Nonetheless, few studies show that mammals actually use corridors as predicted. Further, the assumptions underlying corridor models are rarely validated with field data. We categorized corridor use as a behavior, to identify animal-defined corridors, using movement data from fishers (Martes pennanti) tracked near Albany, New York, USA. We then used least-cost path analysis and circuit theory to predict fisher corridors and validated the performance of all three corridor models with data from camera traps. Six of eight fishers tracked used corridors to connect the forest patches that constitute their home ranges, however the locations of these corridors were not well predicted by the two cost-based models, which together identified only 5 of the 23 used corridors. Further, camera trap data suggest the cost-based corridor models performed poorly, often detecting fewer fishers and mammals than nearby habitat cores, whereas camera traps within animal-defined corridors recorded more passes made by fishers, carnivores, and all other non-target mammal groups. Our results suggest that (1) fishers use corridors to connect disjunct habitat fragments, (2) animal movement data can be used to identify corridors at local scales, (3) camera traps are useful tools for testing corridor model predictions, and (4) that corridor models can be improved by incorporating animal behavior data. Given the conservation importance and monetary costs of corridors, improving and validating corridor model predictions is vital.

Highlights

  • Conservation corridors are widely regarded as useful tools for improving landscape connectivity because they are thought to facilitate animal movement between otherwise separate but potentially suitable habitats (Simpson 1940; Forman 1995; Rosenberg et al 1997; Gilbert-Norton et al 2010)

  • Our results suggest that (1) fishers use corridors to connect disjunct habitat fragments, (2) animal movement data can be used to identify corridors at local scales, (3) camera traps are useful tools for testing corridor model predictions, and (4) that corridor models can be improved by incorporating animal behavior data

  • We identified possible corridors from least-cost path analysis as cells whose least-cost path density is C2, i.e., at least two least-cost paths overlapped within the cell, and required that these overlapping paths were each traveling in opposite directions

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Summary

Introduction

Conservation corridors are widely regarded as useful tools for improving landscape connectivity because they are thought to facilitate animal movement between otherwise separate but potentially suitable habitats (Simpson 1940; Forman 1995; Rosenberg et al 1997; Gilbert-Norton et al 2010). Experts visually identify potential corridors (Hilty et al 2006) More sophisticated methods such as cost-based models (e.g., least-cost mapping; Adriaensen et al 2003 and circuit theory; McRae et al 2008) use algorithms to analyze landscape resistance to predict corridors. This landscape resistance, or ‘cost’, is thought to represent the energy or mortality risk for an animal to move through an area, or its unwillingness to do so. Despite intending to predict and facilitate animal movements, most corridor studies do not directly incorporate animal behavior into their models

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