Demographic inference for spatially heterogeneous populations using long shared haplotypes.

Area of Science:

• Population genetics
• Mathematical modeling
• Spatial ecology

Background:

• Understanding population structure and history is crucial in ecology and evolution.
• Spatial heterogeneity in dispersal and population density significantly impacts genetic diversity and ancestry.
• Previous models often simplify spatial dynamics, limiting their application in complex habitats.

Purpose of the Study:

• To introduce a modified spatial Λ-Fleming-Viot process for modeling population ancestry in a two-region habitat with a discontinuity.
• To derive an analytical formula for expected shared haplotype segments based on sampling locations.
• To develop a method for inferring population dispersal and density parameters.

Main Methods:

• Utilized a modified spatial Λ-Fleming-Viot process.
• Derived an analytical formula for expected shared haplotype segments.
• Employed a composite likelihood approach for parameter inference.
• Validated the method using simulated datasets.

Main Results:

• An analytical formula for expected shared haplotype segments was derived.
• The formula depends on sampling locations and involves the transition density of a skew diffusion.
• The composite likelihood approach demonstrated efficiency in inferring dispersal and density parameters.
• Simulations confirmed the method's effectiveness across various scenarios.

Conclusions:

• The modified spatial Λ-Fleming-Viot process provides a robust framework for studying population ancestry in heterogeneous environments.
• The derived formula and inference method are valuable tools for ecological and evolutionary research.
• This approach enhances our ability to understand the impact of spatial discontinuities on population genetic structure.