Data from: Spatial variation in leaf nutrient traits of dominant desert riparian plant species in an arid inland river basin of China
Zhang, Xiaolong et al. (2019), Data from: Spatial variation in leaf nutrient traits of dominant desert riparian plant species in an arid inland river basin of China, Dryad, Dataset, https://doi.org/10.5061/dryad.rg25909
Understanding how patterns of leaf nutrient traits respond to groundwater depth is crucial for modeling the nutrient cycling of desert riparian ecosystems and forecasting the responses of ecosystems to global changes. In this study, we measured leaf nutrients along a transect across a groundwater depth gradient in the downstream Heihe River to explore the response of leaf nutrient traits to groundwater depth and soil properties. We found that leaf nutrient traits of dominant species showed different responses to groundwater depth gradients. Leaf C, leaf N, leaf P and leaf K decreased significantly with groundwater depth, whereas patterns of leaf C/N and leaf N/P followed quadratic relationships with groundwater depth. Meanwhile, leaf C/P did not vary significantly along the groundwater depth gradient. Variations in leaf nutrient traits were associated with soil properties (e.g. soil bulk density, soil pH). Groundwater depth and soil pH jointly regulated the variation of leaf nutrient traits, however, groundwater depth explained the variation of leaf nutrient traits better than did soil pH. At the local scale in the typical desert riparian ecosystem, the dominant species was characterized by low leaf C, leaf N and leaf P, but high leaf N/P and leaf C/P, indicating that, desert riparian plants might be more limited by P than N in the growing season. Our observations will help to reveal specific adaptation patterns in relation to the groundwater depth gradient for dominant desert riparian species, provide insights into adaptive trends of leaf nutrient traits, and add information relevant to understanding the adaptive strategies of desert riparian forest vegetation to moisture gradients.