Leaf size variations in a dominant desert shrub, Reaumuria soongarica, adapted to heterogeneous environments

The climate in arid Central Asia (ACA) has changed rapidly in recent decades, but the ecological consequences of this are far from clear. To predict the impacts of climate change on ecosystem functioning, greater attention should be given to the relationships between leaf functional traits and environmental heterogeneity. As a dominant constructive shrub widely distributed in ACA, Reaumuria soongarica provided us with an ideal model to understand how leaf functional traits of desert ecosystems responded to the heterogeneous environments of ACA. Here, to determine the influences of genetic and ecological factors, we characterized species-wide variations in leaf traits among 30 wild populations of R. soongarica and 16 populations grown in a common garden. We found that the leaf length, width, and leaf length to width ratio (L/W) of the northern lineage were significantly larger than those of other genetic lineages, and principal component analysis based on the in situ environmental factors distinguished the northern lineage from the other lineages studied. With increasing latitude, leaf length, width, and L/W in the wild populations increased significantly. Leaf length and L/W were negatively correlated with altitude, and first increased and then decreased with increasing mean annual temperature (MAT) and mean annual precipitation (MAP). Stepwise regression analyses further indicated that leaf length variation was mainly affected by latitude. However, leaf width was uncorrelated with altitude, MAT, or MAP. The common garden trial showed that leaf width variation among the eastern populations was caused by both local adaptation and phenotypic plasticity. Our findings suggest that R. soongarica preferentially changes leaf length to adjust leaf size to cope with environmental change. We also reveal phenotypic evidence for ecological speciation of R. soongarica. These results will help us better understand and predict the consequences of climate change for desert ecosystem functioning.