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The predator activity landscape predicts the anti‐predator behavior and distribution of prey in a tundra community

Cite this dataset

Clermont, Jeanne et al. (2021). The predator activity landscape predicts the anti‐predator behavior and distribution of prey in a tundra community [Dataset]. Dryad.


Predation shapes communities through consumptive and non-consumptive effects. In the latter case, prey respond to perceived predation risk through proactive or reactive risk management strategies occurring at different spatial and temporal scales. The predator-prey space race and landscape of fear concepts are useful to better understand how predation risk affects prey behavioral decisions and distribution. We assessed predation-risk effects in a terrestrial Arctic community, where the arctic fox is the main predator of ground-nesting birds. Using high frequency GPS data, we estimated a predator activity landscape corresponding to fox space use patterns, and validated with an artificial prey experiment that this predator activity landscape correlated with the predation risk landscape. We then investigated the effects of the fox activity landscape on multiple prey species, by assessing the anti-predator behavior of a main prey (snow goose) actively searched for by foxes, and the nest distribution of several incidental prey species. We first found that snow geese showed a stronger level of nest defense in areas highly used by foxes, possibly responding with a reactive strategy to variation in predation risk. Then, nests of incidental prey reproducing in habitats easily accessed by foxes had a lower probability of occurrence in areas highly used by foxes, suggesting these birds may use a proactive risk management strategy by shifting their distribution away from risky areas. For incidental prey species nesting in microhabitat refuges difficult to access by foxes, probability of nest occurrence was independent of predation risk in the surrounding area, as they avoid risk at a finer spatial scale. By tracking all individuals of the dominant predator species in our study area, we demonstrated the value of using predator space use patterns to infer spatial variation in predation risk. Overall, we highlight the diversity of risk management strategies in prey sharing a common predator, hence refining our understanding of the mechanisms driving species distribution and community structure.


The datasets (articificial prey experiment, goose behavior and bird nest distribution) provided here contain raw data used in the models presented in the article "The predator activity landscape predicts the anti-predator behavior and distribution of prey in a tundra community". They were used to model the effect of fox activity landscape (intensity of fox space use) on the probability of predation of bait (using and artificial prey experiment), goose nest defense behavior and bird nest distribution. Refer to the article for more details on each analysis. Arctic fox GPS data are available through the Movebank Data Repository at Berteaux, D. 2020, Arctic fox Bylot-GPS tracking, Movebank Study ID 1241071371. Shapefiles of our study site (e.g. polygons of ponds and lakes and islet locations) can be made available upon request.

Usage notes

The README file contains column descriptions. General information for the analyses are presented in the article.


Natural Sciences and Engineering Research Council of Canada, Award: RGPIN‐2019‐05292