RESUMO
The vertical structural complexity (VSC) of plant communities reflects the occupancy of spatial niches and is closely related to resource utilization and environmental adaptation. However, understanding the large-scale spatial pattern of VSC and its underlying mechanisms remains limited. Here, we systematically investigate 2013 plant communities through grid sampling on the Tibetan Plateau. VSC is quantified as the maximum plant height within a plot (Height-max), coefficient of variation of plant height (Height-var), and Shannon evenness of plant height (Height-even). Precipitation dominates the spatial variation in VSC in forests and shrublands, supporting the classic physiological tolerance hypothesis. In contrast, for alpine meadows, steppes, and desert grasslands in extreme environments, non-resource limiting factors (e.g., wide diurnal temperature ranges and strong winds) dominate VSC variation. Generally, with the shifting of climate from favorable to extreme, the effect of resource availability gradually decreases, but the effect of non-resource limiting factors gradually increases, and that the physiological tolerance hypothesis only applicable in favorable conditions. With the help of machine learning models, maps of VSC at 1-km resolution are produced for the Tibetan Plateau. Our findings and maps of VSC provide insights into macroecological studies, especially for adaptation mechanisms and model optimization.
Assuntos
Mudança Climática , Clima , Tibet , Temperatura , PlantasRESUMO
Nitrogen (N) is an important element for most terrestrial ecosystems; its variation among different plant organs, and allocation mechanisms are the basis for the structural stability and functional optimization of natural plant communities. The nature of spatial variations of N and its allocation mechanisms in plants in the Tibetan Plateau-known as the world's third pole-have not been reported on a large scale. In this study, we consistently investigated the N content in different organs of plants in 1564 natural community plots in Tibet Plateau, using a standard spatial-grid sampling setup. On average, the N content was estimated to be 19.21, 4.12, 1.14, and 10.86 mg g-1 in the leaf, branch, trunk, and root, respectively, with small spatial variations. Among organs in communities, leaves were the most active, and had the highest N content, independent of the spatial location; as for vegetation type, communities dominated by herbaceous plants had higher N content than those dominated by woody plants. Furthermore, the allocation of N among different plant organs was allometric, and not significantly influenced by vegetation types and environmental factors; the homeostasis of N was also not affected much by the environment, and varied among the plant organs. In addition, the N allocation strategy within Tibet Plateau for different plant organs was observed to be consistent with that in China. Our findings systematically explore for the first time, the spatial variations in N and allometric mechanisms in natural plant communities in Tibet Plateau and establish a spatial-parameters database to optimize N cycle models.