Rethinking connectivity modeling for high-mobility ungulates: insights from a globally endangered equid

Abstract

ContextMaintaining connectivity is crucial for wildlife conservation in human-occupied landscapes. Structural connectivity modeling (SCM) attempts to quantify the degree to which physical features facilitate or impede movement of individuals and has been widely used to identify corridors, but its accuracy is rarely validated against empirical data.ObjectivesWe evaluated SCM’s ability to identify suitable habitat and corridors for onagers (Equus hemionus onager) through a comparison with functional connectivity (i.e., actual movement of individuals) using satellite tracking data.MethodsWe used MaxEnt to predict suitable habitat and evaluated the ability of three SCM approaches: circuit theory, factorial least cost path, and landscape corridors approaches to identify corridors. The performance of the three SCM approaches was validated against independently collected GPS telemetry data.ResultsOnagers selected water sources and dense vegetation while avoiding areas grazed intensely by livestock. The three approaches to SCMs identified similar movement corridors, which were interrupted by roads, affecting major high-flow movement corridors. The SCMs overlapped with functional connectivity by about 21%.ConclusionMovement corridors derived from SCMs did not align with the locations or intensity of corridors identified using the functional connectivity model. This finding suggests that SCMs might have a tendency to overestimate landscape resistance in areas with low habitat suitability. Therefore, SCM may not adequately capture individual decisions about habitat selection and movement. To protect corridors linking suitable habitat, data on functional connectivity (i.e., telemetry data) can be coupled with SCM to better understand habitat selection and movements of populations as a consequence of landscape features.