Scale of effect of landscape patterns on resource selection by bobcats (Lynx rufus) in a multi-use rangeland system

Context

There is a growing appreciation that wildlife behavioral responses to environmental conditions are scale-dependent and that identifying the scale where the effect of an environmental variable on a behavior is the strongest (i.e., scale of effect) can reveal how animals perceive and respond to their environment. In South Texas, brush management often optimizes agricultural and wildlife management objectives through the precise interspersion of vegetation types creating novel environments which likely affect animal behavior at multiple scales. There is a lack of understanding of how and at what scales this management regime and associated landscape patterns influence wildlife.

Objectives

Our objective was to examine the scale at which landscape patterns had the strongest effect on wildlife behavior. Bobcats (Lynx rufus) our model species, are one of the largest obligated carnivores in the system, and have strong associations with vegetation structure and prey density, two aspects likely to influenced by landscape patterns. We conducted a multiscale resource selection analysis to identify the characteristic scale where landscape patterns had the strongest effect on resource selection.

Methods

We examined resource selection within the home range for 9 bobcats monitored from 2021 to 2022 by fitting resource selection functions which included variables representing landcover, water, energy infrastructure, and landscape metrics (edge density, patch density, and contagion). We fit models using landscape metrics calculated at 10 different scales and compared model performance to identify the scale of effect of landscape metrics on resource selection.

Results

The scale of effect of landscape metrics occurred at finer scales. The characteristic scale for edge density and patch density was 30 m (the finest scale examined), and the characteristic scale for contagion occurred at 100 m. Bobcats avoided locations with high woody patch density and selected for greater woody edge density and contagion. Bobcats selected areas closer to woody vegetation and water bodies while avoiding herbaceous cover and energy development infrastructure.

Conclusions

A key step in understanding the effect of human development and associated landscape patterns on animal behavior is the identifying the scale of effect. We found support for our hypothesis that resource selection would be most strongly affected by landscape configuration at finer scales. Our study demonstrates the importance of cross-scale comparisons when examining the effects of landscape attributes on animal behavior.