Incorporating Movement Behavior and Barriers to Improve Kernel Home Range Space Use Estimates

摘要: Kernel-based utilization distribution (UD) estimates are powerful tools to investigate home range space use and resource selection in many vertebrate species. By ignoring local movement information provided by the serial correlation between successive locations constraints imposed obvious boundaries, classical kernel method results loosely estimated UDs that tend overflow into never-visited areas eventually possibly biased of habitat selection. We improved biological relevance incorporating both (and activity) boundary constraints.