Environmental forcing and genetic differentiation in subdivided populations

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.