Black‐tailed deer seasonal habitat selection: accounting for missing global positioning system fixes. Issue 8 (6th September 2022)

• Record Type: Journal Article
• Authors: Vales, David J.; Nielson, Ryan M.; Middleton, Michael P.
• Is Part Of: Journal of wildlife management. Volume 86:Issue 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-09-06
• Subjects: activity -- bias -- black‐tailed deer -- fix success -- GPS -- habitat selection -- iSSF -- model evaluation -- Odocoileus hemionus columbianus -- Washington State; Wildlife management -- Periodicals; Zoology -- Periodicals; 333.954
• DOI: 10.1002/jwmg.22305
• Languages: English
• ISSNs: 0022-541X

Abstract

Abstract: Quantitative models of black‐tailed deer ( Odocoileus hemionus columbianus ) habitat selection do not exist for Pacific Northwest landscapes but are needed to make predictions of how deer respond to timber harvest. We developed models to estimate habitat selection by black‐tailed deer within seasonal home ranges in the west‐central Cascade Mountains, Washington, USA, from 2008–2019. Even with moderately high global positioning system (GPS) fix success within summer and winter (both averages ≥0.87), we were concerned about landscape or vegetation characteristics causing fix success failure that would bias estimates of habitat selection. Year of GPS‐collar production, deer activity, and diel period (night, day, crepuscular) were associated with fix success. The odds of acquiring a fix were 2.53 times greater when the deer were inactive compared to active, and this difference was greater for those deer with higher average percent canopy cover within their home range. These relationships only explained a portion of the variation in the data and did not negate concerns about the effects of missing locations when estimating habitat selection, so we estimated deer habitat selection within summer and winter using an integrated step selection function (iSSF) and a probability of detection integrated step selection function (PDiSSF). The iSSF ignored missing fixes; the PDiSSF accounted for GPS fix failure due to the landscape and vegetation conditions. Covariates in the final summer PDiSSF included step length, an index of forage biomass, distance to cover‐forage edge, and distance to road. The winter model was similar but did not include forage biomass. We modeled the probability of detection in the PDiSSF as a function of canopy cover in both seasonal models. The standard iSSF resulted in estimates of stronger selection for areas with higher biomass, presumably because fix success was higher in these more open areas. Predictions of habitat selection from the final PDiSSF summer model evaluated well with independent data from a nearby study area. Evaluation of the final winter model was less promising. Ignoring missing GPS locations, even with an average fix success as high as 87%, would have led to different predictions of habitat selection by black‐tailed deer. We recommend that researchers consider the effect of habitat‐induced bias in fix success on the accuracy of estimates of habitat selection and consider using the PDiSSF to remove bias related to missing fixes. Abstract : We developed black‐tailed deer seasonal step selection functions in western Washington, USA, that accounted for missing global positioning system (GPS) fixes and documented differences that would have occurred if missing data were ignored. Model coefficients were significantly different between models developed with and without consideration for missing fixes. Models that accounted for missing data using canopy cover as a probability of detection covariate evaluated well with independent data, and simulations demonstrated potential bias that would have resulted from neglecting missing animal locations.