A statistical framework for modelling migration corridors

Tristan A. Nuñez; Mark A. Hurley; Tabitha A. Graves; Anna C. Ortega; Hall Sawyer; Julien Fattebert; Jerod A. Merkle; Matthew J. Kauffman

doi:10.1111/2041-210x.13969

USGS · 70266792

A statistical framework for modelling migration corridors

Tristan A. Nuñez·Mark A. Hurley·Tabitha A. Graves·Anna C. Ortega·Hall Sawyer·Julien Fattebert·Jerod A. Merkle·Matthew J. Kauffman

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Abstract

1. Management of animal populations requires spatially explicit knowledge of movement corridors, such as those used during seasonal migrations. GPS tracking data allows for mapping of corridors from directly observed movements, providing important insights, but tracking data is absent for many populations. 2. We developed a novel statistical corridor modeling approach that predicts movement corridors from cost-distance movement models fit directly to migration tracking data. Unlike existing predictive approaches, this does not require the ad-hoc transformation of habitat suitability surfaces into resistance surfaces. We tested the ability of the approach to recover parameters used to generate simulated movements. We then used GPS data from three migrating mule deer (Odocoileus hemionus) herds in Idaho and Wyoming to model corridors as a function of elevation, slope, aspect, percent shrub, date of peak green-up, snow-off date, and human footprint. We assessed the predictive ability of the fitted models using validation tracks from the same herd as well as from the other herds. 3. The approach reproduced parameters used to generate the simulated movements, predicted the corridors used by migratory populations, and described the direction, magnitude, and confidence levels of the effects of environmental variables on corridors. The effects environmental variables had on corridors differed depending on the herd. Within-herd validation indicated that fitted corridor models are more accurate at predicting migration corridors than null models, and cross-herd validation indicated that fitted models for some herds accurately predicted the observed migrations of other herds. 4. In addition to the practical benefit of mapping corridors for management, our statistical corridor modeling framework sets the stage for evaluating fundamental questions about the fitness tradeoffs, navigation, learning, fidelity, and movement constraints that influence migratory and other corridor-generating behavior. Models of predictive corridors can inform management and planning for the conservation of migrations across taxa, including the potential restoration of corridors. Our corridor modeling approach is also readily applied to non-migratory animal movements.

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Methods in Ecology and Evolution Article

Source-reported bounding extent: 42.05335013528642° to 45.9008891737889° latitude; -116.51571099773642° to -108.42991483721727° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeX RIS

Tristan A. Nuñez, Mark A. Hurley, Tabitha A. Graves, Anna C. Ortega, Hall Sawyer, Julien Fattebert, Jerod A. Merkle, Matthew J. Kauffman. 2022-09-18. A statistical framework for modelling migration corridors. https://doi.org/10.1111/2041-210x.13969

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