Dataset of Rapid adaptive responses of rosette-type macrophyte Vallisneria natans juveniles to varying water depths: The role of leaf trait plasticity
Cite this dataset
Gao, Yuxuan (2022). Dataset of Rapid adaptive responses of rosette-type macrophyte Vallisneria natans juveniles to varying water depths: The role of leaf trait plasticity [Dataset]. Dryad. https://doi.org/10.5061/dryad.1g1jwstx5
Rosette-type submerged macrophytes are widely distributed across a range of water depths in shallow lakes and play a key role in maintaining ecosystem structures and functions. However, little is known about the rapid adaptive responses of such macrophytes to variations in water depth, especially at the juvenile stage. Here, we conducted a short term in situ mesocosm experiment, in which the juveniles of Vallisneria natans were exposed to a water depth gradient ranging from 20 to 360 cm. Twenty-two leaf-related traits were examined after four weeks of growth in a shallow lake. Most (18) traits of V. natans generally showed high plasticity in relation to water depth. Specifically, juveniles allocated more biomass to leaves, and had higher specific leaf area, leaf length to width ratio, chlorophyll content, and carotenoids content in deep waters, displaying trait syndrome associated with high resource acquisition. In contrast, V. natans juveniles in shallow waters had higher leaf dry matter content, leaf soluble carbohydrate content, carotenoids per unit chlorophyll, and peroxidase activity, pertaining to resource conservation. Notably, underwater light intensity was found to be the key factor explaining the trait plasticity along the water depth gradient, and 1.30 mol photons m–2 d–1 (at 270 cm) could be the optimal irradience level based on the total biomass of V. natans juveniles. The present study highlights the significance of leaf trait plasticity for rosette-type macrophytes in response to variations in water depth, and sheds new light on the differences between trade-offs in deep- and shallow-water areas.
National Natural Science Foundation of China, Award: 41971043