Evol Ecol Res 10: 1-9 (2008)     Full PDF if your library subscribes.

Environmental forcing and genetic differentiation in subdivided populations

Esa Ranta,1* Veijo Kaitala,1 Mats Björklund,2 Per Lundberg,3 Lars A. Bach3 and Nils Chr. Stenseth4

1Integrative Ecology Unit, Department of Biological and Environmental Sciences, University of Helsinki, PO Box 65 (Viikinkaari 1), FIN-00014 Helsinki, Finland, 2Animal Ecology/Department of Ecology and Evolution, Evolutionary Biology Centre (EBC), Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden, 3Department of Theoretical Ecology, Ecology Building, Lund University, SE-22362 Lund, Sweden and  4Centre of Ecological and Evolutionary Synthesis (CEES), Department of Biology, University of Oslo, PO Box 1050 Blindern, N-0316 Oslo, Norway

Author to whom all correspondence should be addressed.
e-mail: esa.ranta@helsinki.fi


Questions: How will genetic differentiation and genetic drift in spatially structured populations be affected by different classes of autocorrelated environmental noise? How does dispersal interact with fluctuations generated from the demographic and environmental forcing in shaping the neutral genetic patterns?

Model and key assumptions: Populations are regulated locally by density-dependent feedback including demographic stochasticity but they are also here forced by environmental noise (white, red, and blue noise corresponding to random, positive, and negative autocorrelation respectively). Spatial structure consists of a looped string of populations connected by dispersal and each with a predefined carrying capacity (one-dimensional stepping stone structure).

Method: Simulations initialized by randomly distributing individuals, and thus genotypes, in space (no fitness differences, no mutation, no recombination, no selection).

Conclusions: In an unpredictable way, red noise reinforces the genetic differentiation among populations more than white or blue noise. Dispersal appears unable to dilute the differentiation effect of positively autocorrelated forcing. In modelling the effect of environmental stochasticity, details about the type of environmental noise are of paramount importance for the results and their biological and management implications.

Keywords: climate change, drift, environmental noise, genetic differentiation, population dynamics.

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