Movement Ecology | |
Spatio–temporal hotspots of satellite–tracked arctic foxes reveal a large detection range in a mammalian predator | |
Dominique Berteaux1  Joël Bêty1  Sandra Lai1  | |
[1] Canada Research Chair on Northern Biodiversity, Centre for Northern Studies and Quebec Center for Biodiversity Science, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski G5L 3A1, QC, Canada | |
关键词: Dynamic Brownian bridge movement model; Scavenging; Detection range; Spatio–temporal hotspots; Sea ice; Vulpes lagopus; Argos satellite tracking; | |
Others : 1233239 DOI : 10.1186/s40462-015-0065-2 |
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received in 2015-03-27, accepted in 2015-10-13, 发布年份 2015 |
【 摘 要 】
Background
The scale at which animals perceive their environment is a strong fitness determinant, yet few empirical estimates of animal detection ranges exist, especially in mammalian predators. Using daily Argos satellite tracking of 26 adult arctic foxes (Vulpes lagopus) during a single winter in the High Canadian Arctic, we investigated the detection range of arctic foxes by detecting hotspots of fox activity on the sea ice.
Results
While maintaining territories in the tundra, these solitary foragers occasionally used the sea ice where they sometimes formed spatio–temporal hotspots, likely scavenging on marine mammal carcasses. We detected 35 movements by 13 individuals forming five hotspots. Foxes often traveled more than 10 km, and up to 40 km, to reach hotspots, which lasted one–two weeks and could gather up to 12 individuals. The likelihood of a fox joining a hotspot was neither influenced by its distance from the hotspot nor by the distance of its home range to the coast.
Conclusions
Observed traveling distances may indicate a high detection range in arctic foxes, and our results suggest their ability to detect food sources on the sea ice from their terrestrial home range. While revealing a wide knowledge gap regarding resource detection abilities in mammalian predators, our study provides estimates of detection range useful for interpreting and modeling animal movements. It also allows a better understanding of foraging behavior and navigation capacity in terrestrial predators.
【 授权许可】
2015 Lai et al.
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