[Differences and drivers of leaf stable carbon and nitrogen isotope in herbs under different vegetation types on the eastern Qinghai-Tibet Plateau].

Ying Yong Sheng Tai Xue Bao

Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China.

Published: April 2024

The natural abundance of stable carbon and nitrogen isotopes (δC and δN) in leaves can provide comprehensive information on the physiological and ecological processes of plants and has been widely used in ecological research. However, recent studies on leaf δC and δN have focused mainly on woody species, few studies have been conducted on herbs in different vegetation types, and their differences and driving factors are still unclear. In this study, we focused on the herbs in subalpine coniferous forests, alpine shrublands, and alpine mea-dows on the eastern Qinghai-Tibet Plateau, and investigated the differences in leaf δC and δN of herbs and the driving factors. The results showed that there were significant differences in leaf δC and δN values of herbs among different vegetation types, with the highest δC and δN values in alpine meadows, followed by alpine shrublands, and the lowest in subalpine coniferous forests. Using variation partitioning analysis, we revealed that differences in leaf δC and δN of herbs among various vegetation types were driven by both leaf functional traits and climate factors, with the contribution of leaf functional traits being relatively higher than that of climate factors. Hierarchical partitioning results indicated that mean annual temperature (MAT), chlorophyll content index, leaf nitrogen content per unit area (N), and leaf mass per area were the main drivers of leaf δC variations of herbs across different vegetation types, while the relative importance of N and MAT for variation in leaf δN of herbs was much higher than those other variables. There was a strong coupling relationship between leaf δC and δN as indicated by the result of the ordinary least squares regression. Our findings could provide new insights into understanding the key drivers of leaf δC and δN variations in herbs across different vegetation types.

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Source
http://dx.doi.org/10.13287/j.1001-9332.202404.013DOI Listing

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