Wind is the primary dispersal vector for the seeds and pollen of many plants. While it is widely assumed that patterns of wind speed and direction could play an important role in structuring gene flow, this idea has remained largely untested at macroecological scales. In this study we reanalyzed over 100 published landscape genetic datasets representing thousands of populations of more than 50 species of trees, in a global test of the role of wind in shaping genetic differentiation and directional gene flow in trees. We used a novel approach to model wind connectivity between population pairs, integrating global data on 30 years of hourly wind conditions with landscape connectivity modeling approaches traditionally used for terrestrial vertebrates. Using a hierarchical modeling framework, we combined these wind connectivity data with genetic connectivity estimates and species dispersal and pollination traits to test for the impact of wind on landscape genetics.
Results/Conclusions
By comparing genetic patterns in wind-dispersed species both to null expectations and to non-wind-dispersed species, we found strong support for the hypothesis that wind has widespread influences on gene flow in trees. Models incorporating wind connectivity statistically outperform models based on just distance; wind connectivity coefficients were consistent with hypothesized effects; and model terms capturing the interaction between wind connectivity and species dispersal biology indicate that wind is a stronger predictor of gene flow in species with greater wind dispersal adaptations. For example, the direction of dominant gene flow and dominant wind flow between population pairs are aligned in nearly two thirds of cases in wind-dispersed species but only half of cases in non-wind-dispersed species. Our results suggest that wind is important in shaping genetic patterns and can be effectively incorporated into landscape genetic models of wind-dispersed organisms, which may help to inform basic ecological questions about dispersal and genetic diversity as well as applications such as conservation genetics and adaptive gene flow under climate change.