Population Structure And Gene Flow In Solitary Bees: Implications For Their Conservation And Management

Abstract

The study of genetic population structure is a central issue in evolutionary biology because it determines the distributional pattern and amount of genetic variation that is available for evolution within a species. Therefore, species adaptability to environmental change operates within the constraints imposed by population structure. Bees have recently become the focus of conservation concern due to the increasing evidence of population declines worldwide drawing attention to the ecological and economic consequences of pollinator loss. Results from multiple studies have identified three major drivers of bee decline: (1) Environmental stressors, including habitat loss and pesticide exposure; (2) Pests and pathogens; and (3) Loss of genetic diversity. Despite its importance, the levels and distribution of genetic diversity remain poorly understood in bees. Here, I investigate the patterns of genetic diversity in five solitary bee species to understand how climate, crop domestication and landscape features drive changes in bee population demography and genetic structure. I developed de novo genetic markers and spatial models for all species, to determine how populations are structured and connected through gene flow at different geographic scales. I find evidence that changes in climatic conditions, range shifts in host-plants due to crop domestication, and the distribution of suitable nesting sites are important predictors of levels of genetic diversity and population structure in solitary bees. My results reveal that male-biased dispersal may be common in bees and the production of high frequencies of sterile diploid males are not a necessary outcome of populations with low genetic variability. I also provide evidence that drier climates, tillage and low-density of suitable nesting areas may diminish bee population abundance. In summary, I find that investigating patterns of genetic variability in bees using molecular tools provides significant insights into how environmental stressors affected past and current population demography. My results have implications for bee conservation and the effective management of wild bee populations for crop pollination.