Isolation by distance in a continuous population under stochastic demographic fluctuations.

Area of Science:

• Population Genetics
• Ecology
• Evolutionary Biology

Background:

• Natural populations exhibit non-uniform spatial and temporal density.
• Existing models struggle to describe genetic structuring with demographic heterogeneity and local gene movement correlations.
• Isolation by distance models face analytical challenges in continuous populations with varying densities.

Purpose of the Study:

• To formulate exact recursions for identity probabilities in continuous populations.
• To define effective dispersal and effective density generalizing lattice models.
• To assess these effective parameters in a heterogeneous, dynamic plant population.

Main Methods:

• Formulation of exact recursions for probabilities of identity.
• Deduction of effective dispersal and effective density definitions.
• Simulations comparing demographic and genetic pattern-derived parameter estimates.
• Analysis of spatio-temporal density correlations and dispersal kurtosis effects.

Main Results:

• Effective dispersal and effective density generalize previous findings.
• Increasing spatio-temporal density correlations reduce the product of effective parameters.
• Dispersal kurtosis affects sensitivity to density fluctuations but not the relationship between the product and genetic structure statistic a(r).
• Observed census density and dispersal rate overestimate effective dispersal in aggregated habitats.

Conclusions:

• The new effective parameters provide a robust framework for understanding spatial genetic structure in continuous populations.
• Demographic heterogeneities significantly impact genetic structuring, requiring advanced modeling approaches.
• Standard estimators of population genetic parameters can be heavily biased in spatially aggregated populations.