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A plea for simultaneously considering matrix quality and local environmental conditions when analysing landscape impacts on effective dispersal
Author(s) -
Pflüger Femke J.,
Balkenhol Niko
Publication year - 2014
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.12712
Subject(s) - biological dispersal , ecology , population , landscape connectivity , biology , environmental quality , habitat , environmental resource management , environmental science , demography , sociology
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.