Incorporating movement patterns to discern habitat selection: black bears as a case study

Abstract

Context Animals’ use of space and habitat selection emerges from their movement patterns, which are, in turn, determined by their behavioural or physiological states and extrinsic factors. Aim The aims of the present study were to investigate animal movement and incorporate the movement patterns into habitat selection analyses using Global Positioning System (GPS) location data from 16 black bears (Ursus americanus) in a fragmented area of Florida, USA. Methods Hidden Markov models (HMMs) were used to discern the movement patterns of the bears. These results were then used in step-selection functions (SSFs) to evaluate habitat selection patterns and the factors influencing these patterns. Key results HMMs revealed that black bear movement patterns are best described by three behavioural states: (1) resting (very short step-lengths and large turning angles); (2) encamped (moderate step-lengths and large turning angles); and (3) exploratory (long step-lengths and small turning angles). Bears selected for forested wetlands and marsh wetlands more than any other land cover type, and generally avoided urban areas in all seasons and when in encamped and exploratory behavioural states. Bears also chose to move to locations farther away from major roads. Conclusions Because habitat selection is influenced by how animals move within landscapes, it is essential to consider animals’ movement patterns when making inferences about habitat selection. The present study achieves this goal by using HMMs to first discern black bear movement patterns and associated parameters, and by using these results in SSFs to investigate habitat selection patterns. Thus, the methodological framework developed in this study effectively incorporates state-specific movement patterns while making inferences regarding habitat selection. The unified methodological approach employed here will contribute to an improved understanding of animal ecology as well as informed management decisions. Implications Conservation plans focused on preserving forested wetlands would benefit bears by not only providing habitat for resting and foraging, but also by providing connectivity through fragmented landscapes. Additionally, the framework could be applied to species that follow annual cycles and may provide a tool for investigating how animals are using dispersal corridors.

Behavioral state resource selection in invasive wild pigs in the Southeastern United States

“…Based on the results of our HMM analyses, we distinguished three biologically relevant behavioral states generally based on patterns in the movement characteristics of wild pigs (i.e., resting, foraging, traveling). Previous studies have identified similar patterns for other species 11 , 37 , 55 ; however, behavioral states associated with movement characteristics may be assigned differently depending on prior knowledge of different animal species and fix rate at which GPS data were collected. Specifically, the interpretation of a behavioral state associated with short to intermediate step-lengths (what we defined as foraging) may differ among species.…”

“…Specifically, the interpretation of a behavioral state associated with short to intermediate step-lengths (what we defined as foraging) may differ among species. For example, this category of behavior was defined as “locally active at the kill site” for wolves 56 , “moderately active” for Florida panthers 57 , and “encamped” for American black bears 55 . However, for caribou, this intermediate behavioral state was assigned as “foraging” and was associated with a foraging behavior for black bears as well 11 , 55 .…”

Novel step selection analyses on energy landscapes reveal how linear features alter migrations of soaring birds

“…An important question, here, is how an eagle might balance scavenging road-killed carrion with the risk of vehicle collision across different behavioral or physiological states. State-specific selection in SSFs is an active area of analytical development (Hooten et al, 2014; Avgar et al, 2016; Hooten et al, 2017; Karelus et al, 2019; Scharf et al, 2019), and while our SSF did not explicitly incorporate behaviorally-specific selection into its framework, we were still able to infer behavior-specific use of linear features and habitat plus seasonal variation in those patterns (Figs. 4-6).…”

Novel step selection analyses on energy landscapes reveal how linear features alter migrations of soaring birds

“…An important question here is how an eagle might balance scavenging road-killed carrion with the risk of vehicle collision across different behavioural or physiological states. State-specific selection in SSFs is an active area of analytical development (Avgar et al, 2016;Hooten et al, 2014Hooten et al, , 2017Karelus et al, 2019;Scharf et al, 2019), and while the el-SSF did not explicitly incorporate behaviourally specific selection into its framework, we were still able to infer behaviour-specific use of linear features and habitat plus seasonal variation in those patterns (Figures 4-6). While progress is being made (e.g.…”