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Landscape Ecology

, Volume 23, Issue 5, pp 603–614 | Cite as

Inferring the effects of landscape structure on roe deer (Capreolus capreolus) movements using a step selection function

  • Aurélie Coulon
  • Nicolas Morellet
  • Michel Goulard
  • Bruno Cargnelutti
  • Jean-Marc Angibault
  • A. J. Mark Hewison
Research Article

Abstract

In this study, we sought to understand how landscape structure affects roe deer movements within their home-range in a heterogeneous and fragmented agricultural system of south-western France. We analysed the movements of 20 roe deer fitted with GPS collars which recorded their locations every 2–6 h over several months (mean = 9 months). Based on empirical observations and previous studies of roe deer habitat use, we hypothesised that roe deer should avoid buildings and roads, move preferentially along valley bottoms and through the more wooded areas of the landscape. To test these hypotheses we paired each observed movement step with 10 random ones. Using conditional logistic regression, we modelled a step selection function, which represents the probability of selecting a given step as a function of these landscape variables. The selected model indicated that movements were influenced by all the tested landscape features, but not always in the predicted direction: our results suggested that roe deer tend to avoid buildings, roads, valley bottoms and possibly the more wooded areas (although the latter result should be interpreted with caution, as it may be influenced by a bias in the rate of GPS fix acquisition in woods). The distances to buildings and to roads were the most influential variables in the model, suggesting that the avoidance of potential sources of disturbance may be a key factor in determining ranging behaviour of roe deer in human dominated landscapes.

Keywords

Connectivity GPS Fragmentation Buildings Roads Topography Woodland SSF Ungulate 

Notes

Acknowledgements

We thank all the volunteers who participated in the roe deer captures. We also thank Sylvie Ladet for help with the use of the GIS software. We thank the BK group of the Cornell Lab of Ornithology and two anonymous reviewers for their helpful comments on the ms. Aurélie Coulon was supported by a Ph.D. grant from INRA, the Fédération Régionale des Chasseurs de Midi-Pyrénées and the Fédération Départementale des Chasseurs de la Haute-Garonne.

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Aurélie Coulon
    • 1
    • 2
  • Nicolas Morellet
    • 1
  • Michel Goulard
    • 3
  • Bruno Cargnelutti
    • 1
  • Jean-Marc Angibault
    • 1
  • A. J. Mark Hewison
    • 1
  1. 1.INRA, Behavior and Ecology of WildlifeCastanetFrance
  2. 2.Fuller Evolutionary Biology ProgramCornell Lab of OrnithologyIthacaUSA
  3. 3.INRA, UR 875, Biometry and Artificial IntelligenceCastanetFrance

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