Predicting dispersal distance in mammals: a trait-based approach
Article first published online: 23 AUG 2012
© 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society
Journal of Animal Ecology
Volume 82, Issue 1, pages 211–221, January 2013
How to Cite
Whitmee, S., Orme, C. D. L. (2013), Predicting dispersal distance in mammals: a trait-based approach. Journal of Animal Ecology, 82: 211–221. doi: 10.1111/j.1365-2656.2012.02030.x
- Issue published online: 17 JAN 2013
- Article first published online: 23 AUG 2012
- Manuscript Accepted: 16 JUL 2012
- Manuscript Received: 7 DEC 2011
- climate change;
- comparative biology;
- life history;
- Dispersal is one of the principal mechanisms influencing ecological and evolutionary processes but quantitative empirical data are unfortunately scarce. As dispersal is likely to influence population responses to climate change, whether by adaptation or by migration, there is an urgent need to obtain estimates of dispersal distance.
- Cross-species correlative approaches identifying predictors of dispersal distance can provide much-needed insights into this data-scarce area. Here, we describe the compilation of a new data set of natal dispersal distances and use it to test life-history predictors of dispersal distance in mammals and examine the strength of the phylogenetic signal in dispersal distance.
- We find that both maximum and median dispersal distances have strong phylogenetic signals. No single model performs best in describing either maximum or median dispersal distances when phylogeny is taken into account but many models show high explanatory power, suggesting that dispersal distance per generation can be estimated for mammals with comparatively little data availability.
- Home range area, geographic range size and body mass are identified as the most important terms across models. Cross-validation of models supports the ability of these variables to predict dispersal distances, suggesting that models may be extended to species where dispersal distance is unknown.