Open AccessSpatial scales of habitat selection decisions: implications for telemetry‐based movement modelling
Author(s) -
BastilleRousseau Guillaume,
Murray Dennis L.,
Schaefer James A.,
Lewis Mark A.,
Mahoney Shane P.,
Potts Jonathan R.
Publication year - 2018
Publication title -
ecography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.973
H-Index - 128
eISSN - 1600-0587
pISSN - 0906-7590
DOI - 10.1111/ecog.02655
Subject(s) - movement (music) , temporal scales , scale (ratio) , artifact (error) , computer science , habitat , spatial ecology , global positioning system , home range , telemetry , temporal resolution , ecology , selection (genetic algorithm) , environmental resource management , range (aeronautics) , geography , remote sensing , environmental science , cartography , artificial intelligence , telecommunications , engineering , biology , philosophy , physics , quantum mechanics , aerospace engineering , aesthetics
Movement influences a myriad of ecological processes operating at multiple spatial and temporal scales. Yet our understanding of animal movement is limited by the resolution of data that can be obtained from individuals. Traditional approaches implicitly assume that movement decisions are made at the spatial and temporal scales of observation, although this scale is typically an artifact of data‐gathering technology rather than biological realism. To address this limitation, we used telemetry‐based movement data for caribou Rangifer tarandus in Newfoundland, Canada, and compared movement decisions estimated at the temporal resolution of GPS relocations (2 h) to a novel model describing directional movement to areas reachable over an extended period. We showed that this newer model is a better predictor of movement decisions by caribou, with decisions made at the scale of ∼2 km, including the strong avoidance of dense coniferous forest, an outcome not detectable at the scale of GPS relocations. These results illustrate the complexity of factors affecting animal movement decisions and the analytical challenges associated with their interpretation. Our novel modelling framework will help support increased accuracy in predictive models of animal space‐use, and thereby aid in determining biologically meaningful scales for collecting movement and habitat data.