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Predicting dispersal distance in mammals: a trait-based approach
Sarah Whitmee1, C David L Orme
1Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, Berkshire, SL5 7PY, UK. s.whitmee07@imperial.ac.uk
The Journal of Animal Ecology
|August 29, 2012
Summary
Estimating mammal dispersal distances is crucial for understanding ecological processes. This study identifies key life-history traits like home range, geographic range, and body mass that predict dispersal, aiding conservation efforts in data-scarce regions.
Area of Science:
- Ecology
- Evolutionary Biology
- Zoology
Background:
- Dispersal is a key ecological and evolutionary process.
- Quantitative data on dispersal distance are scarce, hindering understanding of population responses to climate change.
- Cross-species correlative approaches can identify dispersal predictors.
Purpose of the Study:
- To compile a dataset of mammal natal dispersal distances.
- To test life-history predictors of dispersal distance in mammals.
- To examine the phylogenetic signal in dispersal distance.
Main Methods:
- Compilation of a novel dataset on natal dispersal distances for mammals.
- Statistical modeling to identify predictors of dispersal distance, accounting for phylogeny.
- Cross-validation of predictive models.
Main Results:
- Dispersal distances in mammals exhibit strong phylogenetic signals.
- Home range area, geographic range size, and body mass were identified as key predictors of dispersal distance.
- Models demonstrated high explanatory power, suggesting predictability even with limited data.
Conclusions:
- Dispersal distance in mammals can be estimated using limited data and key life-history traits.
- The identified predictors (home range, geographic range, body mass) can be used to predict dispersal for species lacking empirical data.
- This approach aids in understanding population dynamics and informing conservation strategies.
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