Background/Question/Methods: Threatened populations are usually small and have low genetic diversity, which can reduce their fitness and increase extinction risk. With increasing evidence for the role of genetic problems in population extinction, conservation practitioners have also increasingly started to consider inbreeding depression (ID) when estimating minimum viable population (MVP) sizes. However, in addition to ID, small populations face other genetic problems such as mutation accumulation (MA) and loss of genetic diversity through genetic drift that are usually factored into extinction risk assessments only via verbal arguments. Thus, how the various genetic problems interact remains unknown. We developed deterministic and stochastic eco-evolutionary quantitative models that track both population size and levels of genetic diversity. Our models assume a biallelic multilocus genome whose loci can be under either a single or interacting genetic forces. In addition to ID and MA, we also considered three forms of balancing selection. We defined a MVP to be the lowest population size that avoids an eco-evolutionary extinction vortex and maintains a positive long-term per-capita growth rate in deterministic models or achieves 100\% survival probability for stochastic models after a time sufficient for mutation-selection-drift equilibrium to establish. Results/Conclusions: Our results show that MVP size decreases rapidly with increasing symmetric mutation rates for populations whose genomes are only under balancing selection while with populations whose genomes are under ID and MA, the MVP size increased rapidly. MVP sizes also increase rapidly with increasing number of loci with the same or different selection mechanism until a point is reached at which even arbitrarily large populations cannot survive anymore. However, when keeping the number of loci constant, the observed MVP size is dominated by the mechanism which when in isolation yields the smallest MVP estimate. Thus, to improve MVP estimates there is need for more empirical studies to reveal how different genetic problems interact in the genome.
