Genetic and Habitat Rescue Improve Population Viability in Self‐Incompatible Plants

ABSTRACT Habitat fragmentation and the acceleration of environmental change threaten the survival of many plant species. The problem is especially pronounced for plant species with self‐incompatibility mating systems, which are obligate outcrossers, thus requiring high mate availability to persist. In such situations, plant populations suffering decreased fitness could be rescued by: (a) improving local habitat conditions (habitat rescue), (b) increasing the number of individuals (demographic rescue), or (c) introducing new genetic variation (genetic rescue). In this study, we used a spatially and genetically explicit individual‐based model to approximate the demography of a small (N = 250) isolated self‐incompatible population using a timescale of 500 years. Using this model, we quantified the effectiveness of the different types of rescues described above, singly and in combination. Our results show that individual genetic rescue is the most effective type of rescue with respect to improving fitness and population viability. However, we found that introducing a high number of individuals (N > 30) to a small population (N = 50) at the brink of extinction through demographic rescue can also have a positive effect on viability, improving average fitness by 55% compared to introducing a low number of individuals (N = 10) over a long timescale (> 500 years). By itself, habitat rescue showed the lowest effects on viability. However, combining genetic and habitat rescue provided the best results overall, increasing both persistence (> 30%) and mate availability (> 50%). Interestingly, we found that the addition of even a small number of new S alleles (20%) can be highly beneficial to increase mate availability and persistence. We conclude that genetic rescue through the introduction of new S alleles and an increase in habitat suitability is the best management strategy to improve mate availability and population viability of small isolated SI plant populations to overcome the effects of demographic stochasticity and positive density dependence.