Literature DB >> 30506304

Hourly movement decisions indicate how a large carnivore inhabits developed landscapes.

Michael J Evans1, Jason E Hawley2, Paul W Rego2, Tracy A G Rittenhouse3.   

Abstract

The ecology of wildlife living in proximity to humans often differs from that in more natural places. Animals may perceive anthropogenic features and people as threats, exhibiting avoidance behavior, or may acclimate to human activities. As development expands globally, changes in the ecology of species in response to human phenomena may determine whether animals persist in these changing environments. We hypothesize that American black bears (Ursus americanus) persist within developed areas by effectively avoiding risky landscape features. We test this by quantifying changes in the movements of adult females from a population living within exurban and suburban development. We collected hourly GPS data from 23 individuals from 2012 to 2014 and used step-selection functions to estimate selection for anthropogenic features. Females were more avoidant of roads and highways when with cubs than without and were more responsive to increased traffic volume. As bears occupied greater housing densities, selection for housing increased, while avoidance of roads and responsiveness to traffic increased. Behavioral flexibility allowed bears in highly developed areas to alter selection and avoidance for anthropogenic features seasonally. These findings support the hypothesis that black bears perceive human activity as risky, and effectively avoid these risks while inhabiting developed areas. We document a high amount of individual variation in selection of anthropogenic features within the study population. Our findings suggest that initially, wildlife can successfully inhabit developed landscapes by effectively avoiding human activity. However, variation among individuals provides the capacity for population-level shifts in behavior over time.

Entities:  

Keywords:  Adaptation; Functional response; Movement behavior; Risk avoidance; Selection; Urban

Mesh:

Year:  2018        PMID: 30506304     DOI: 10.1007/s00442-018-4307-z

Source DB:  PubMed          Journal:  Oecologia        ISSN: 0029-8549            Impact factor:   3.225


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