C:N:P stoichiometry in terrestrial ecosystems in China

生物群落 陆地生态系统 生态系统 生态化学计量学 生物量(生态学) 垃圾箱 环境科学 生态学 自行车 森林生态学 生产力 营养循环 环境化学 化学 地理 林业 生物 宏观经济学 经济 有机化学
作者
Jiahui Zhang,Mingxu Li,Li Xu,Jianxing Zhu,Guanhua Dai,Nianpeng He
出处
期刊:Science of The Total Environment [Elsevier]
卷期号:795: 148849-148849 被引量:100
标识
DOI:10.1016/j.scitotenv.2021.148849
摘要

Ecological stoichiometry is an efficient tool for exploring the balance and cycling of coupled elements (e.g., carbon [C], nitrogen [N], and phosphorus [P]). Therefore, C:N:P ratios are essential input parameters in most ecological models of productivity or C cycling. However, previous C:N:P ratios estimated using the species arithmetic means exhibit high uncertainty when used as direct model parameters. In this study, we comprehensively calculated C:N:P ratios from organs to ecosystems for 66 typical natural ecosystems in China (e.g., forests, grasslands, and deserts) using the community biomass-weighted mean (CWM), with the consistently measured element data of 3229 site-species combination. The C:N:P ratios were 427:19:1, 885:13:1, 9549:33:1, and 797:18:1 in the leaves, branches, trunks, and roots of terrestrial ecosystems, respectively. Furthermore, the ratios were 91:4:1, 919:17:1, 1121:25:1, and 55:4:1 in ecosystems, plant communities, litter, and soils, respectively. Significant differences were observed in C:N:P ratios among different ecosystem types and biomes, with generally higher ratios in forests. Moreover, the latitudinal patterns of C:N ratios exhibited no obvious trends, whereas both C:P and N:P ratios decreased significantly with increasing latitude, especially in forests. Environmental conditions explained 15.4–86.6% of the spatial variation of C:N:P ratios from organs to ecosystems. In summary, this study systematically demonstrates the variations in biome-scale C:N:P stoichiometry in terrestrial ecosystems, as well as their influencing factors, using the CWM. More importantly, this study provides a systematic dataset of C:N:P ratios from plot to biome scale that can be used to improve relevant ecological models.
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