Modeling minimum viable population size with multiple genetic problems of small populations

Area of Science:

• Conservation genetics
• Population viability analysis
• Ecoevolutionary dynamics

Background:

• Species persistence relies on defining minimum viable population (MVP) sizes.
• Genetic factors, including deleterious mutations and inbreeding depression, critically influence extinction risk.
• Current MVP estimates often do not fully integrate complex genetic interactions.

Purpose of the Study:

• Develop methods to incorporate genetic issues beyond inbreeding depression into MVP calculations.
• Quantify the impact of interacting genetic problems on MVP size.
• Reduce arbitrariness in time and persistence probability thresholds for MVP analyses.

Main Methods:

• Developed ecoevolutionary quantitative models to simulate population size and genetic diversity.
• Modeled a biallelic multilocus genome under mutation-selection-drift balance and balancing selection.
• Defined MVP as the minimum population size avoiding an ecoevolutionary extinction vortex.

Main Results:

• MVP size decreased with increased mutation rates under balancing selection.
• MVP size increased substantially with mutation-selection-drift balance and increasing numbers of affected loci.
• Interactions between genetic problems did not consistently elevate MVP size for a fixed number of loci.

Conclusions:

• MVP estimates must integrate diverse genetic forces and their interactions.
• Complex genetic architectures can necessitate significantly larger population sizes for viability.
• Further empirical research is crucial to understand in-genome genetic process interactions.