What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA.

ABSTRACT: Modelling population connectivity is central to biodiversity conservation and often relies on resistance surfaces reflecting multi-generational gene flow. ResistanceGA (RGA) is a common optimization framework for parameterizing these surfaces by maximizing the fit between genetic distances and cost distances using maximum likelihood population effect models. As the reliability of this framework has rarely been studied, we investigated the conditions maximizing its accuracy for both prediction and interpretation of landscape features' permeability. We ran demo-genetic simulations in contrasted landscapes for species with distinct dispersal capacities and specialization levels, using corresponding reference cost scenarios. We then optimized resistance surfaces from the simulated genetic dist

SUBMITTER: Daniel A 

PROVIDER: S-EPMC11646299 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature