.png){kind=icon}
.png){kind=icon}
Return
A statistical framework for modelling migration corridors
.png){kind=icon}
OA
AI
DOI：10.1111/2041-210X.13969.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Management of animal populations requires spatially explicit knowledge of movement corridors, such as those used during seasonal migrations. Global Positioning System (GPS) tracking data allow for mapping of corridors from directly observed movements, but such tracking data are absent for many populations. We developed a novel statistical corridor modelling approach that predicts movement corridors from cost-distance 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. 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. 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. In addition to the practical benefit of mapping corridors for management, our statistical corridor modelling framework sets the stage for evaluating fundamental questions about the fitness trade-offs, navigation, learning, fidelity and movement constraints that influence migratory and other corridor-generating behaviour. Models of predictive corridors can inform management and planning for the conservation of migrations across taxa, including the potential restoration of corridors. Our corridor modelling approach is also readily applied to non-migratory animal movements.
Keywords:
corridor ecology
corridor prediction
cost-distance modelling
maximum likelihood
migration ecology
movement ecology
optimization
statistical corridor modelling
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.2
Papers:
2.9K
Citations:
2.9W