Literature DB >> 24605792

A plea for simultaneously considering matrix quality and local environmental conditions when analysing landscape impacts on effective dispersal.

Femke J Pflüger1, Niko Balkenhol.   

Abstract

Landscape genetics has tremendous potential for enhancing our understanding about landscape effects on effective dispersal and resulting genetic structures. However, the vast majority of landscape genetic studies focus on effects of the landscape among sampling locations on dispersal (i.e. matrix quality), while effects of local environmental conditions are rather neglected. Such local environmental conditions include patch size, habitat type or resource availability and are commonly used in (meta-) population ecology and population genetics. In our opinion, landscape genetic studies would greatly benefit from simultaneously incorporating both matrix quality and local environmental conditions when assessing landscape effects on effective dispersal. To illustrate this point, we first outline the various ways in which environmental heterogeneity can influence different stages of the dispersal process. We then propose a three-step approach for assessing local and matrix effects on effective dispersal and review how both types of effects can be considered in landscape genetic analyses. Using simulated data, we show that it is possible to correctly disentangle the relative importance of matrix quality vs. local environmental conditions for effective dispersal. We argue that differentiating local and matrix effects in such a way is crucial for predicting future species distribution and persistence, and for optimal conservation decisions that are based on landscape genetics. In sum, we think it is timely to move beyond purely statistical, pattern-oriented analyses in landscape genetics and towards process-oriented approaches that consider the full range of possible landscape effects on dispersal behaviour and resulting gene flow.
© 2014 John Wiley & Sons Ltd.

Keywords:  behavioural mechanisms; carrying capacity; effective distance; habitat (dis-) similarity; landscape connectivity; metapopulation connectivity index

Mesh:

Year:  2014        PMID: 24605792     DOI: 10.1111/mec.12712

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


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