Compatible genetic and ecological estimates of dispersal rates in insect (Coenagrion mercuriale: Odonata: Zygoptera) populations: analysis of ‘neighbourhood size’ using a more precise estimator
Article first published online: 5 DEC 2006
DOI: 10.1111/j.1365-294X.2006.03184.x
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How to Cite
WATTS, P. C., ROUSSET, F., SACCHERI, I. J., LEBLOIS, R., KEMP, S. J. and THOMPSON, D. J. (2007), Compatible genetic and ecological estimates of dispersal rates in insect (Coenagrion mercuriale: Odonata: Zygoptera) populations: analysis of ‘neighbourhood size’ using a more precise estimator. Molecular Ecology, 16: 737–751. doi: 10.1111/j.1365-294X.2006.03184.x
Publication History
- Issue published online: 5 FEB 2007
- Article first published online: 5 DEC 2006
- Received 26 August 2006; revision accepted 28 September 2006
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Keywords:
- capture–mark–recapture;
- conservation;
- dispersal;
- isolation by distance;
- spatial genetic structure
Abstract
Genetic and demographic estimates of dispersal are often thought to be inconsistent. In this study, we use the damselfly Coenagrion mercuriale (Odonata: Zygoptera) as a model to evaluate directly the relationship between estimates of dispersal rate measured during capture–mark–recapture fieldwork with those made from the spatial pattern of genetic markers in linear and two-dimensional habitats. We estimate the ‘neighbourhood size’ (Nb) — the product of the mean axial dispersal rate between parent and offspring and the population density — by a previously described technique, here called the regression method. Because C. mercuriale is less philopatric than species investigated previously by the regression method we evaluate a refined estimator that may be more applicable for relatively mobile species. Results from simulations and empirical data sets reveal that the new estimator performs better under most situations, except when dispersal is very localized relative to population density. Analysis of the C. mercuriale data extends previous results which demonstrated that demographic and genetic estimates of Nb by the regression method are equivalent to within a factor of two at local scales where genetic estimates are less affected by habitat heterogeneity, stochastic processes and/or differential selective regimes. The corollary is that with a little insight into a species’ ecology the pattern of spatial genetic structure provides quantitative information on dispersal rates and/or population densities that has real value for conservation management.

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