Substrate and climate determine terrestrial litter decomposition

• 成果类型: Article
• 署名作者: Wu, Qiuxia; Ni, Xiangyin; Sun, Xinyao; Chen, Zihao; Hong, Songbai; Berg, Bjoern; Zheng, Mianhai; Chen, Ji; Zhu, Jingjing; Ai, Ling; Zhang, Yichen; Wu, Fuzhong
• 署名单位: Fujian Normal University; Peking University Shenzhen Graduate School (PKU Shenzhen); Peking University; Peking University; Peking University Shenzhen Graduate School (PKU Shenzhen); Ministry of Natural Resources of the People's Republic of China; University of Helsinki; Chinese Academy of Sciences; South China Botanical Garden, CAS; Chinese Academy of Sciences; Institute of Earth Environment, CAS; Peking University
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-9466
• DOI: 10.1073/pnas.2420664122
• 发表日期: 2025-02-18
• 关键词: soil organic-matter; residue decomposition; carbon; MODEL; photodegradation; temperature; EFFICIENCY; biomass; lignin; rates

摘要

Litter decomposition is a fundamental biogeochemical process for carbon flux and nutrient cycling in terrestrial ecosystems, yet the global variation in decomposition rates and their covariations with climate and substrate are not fully understood. Here, we synthesized a global dataset of 6,733 independent observations across six continents to illustrate the climatic and substrate controls over litter decomposi-tion. The average decomposition rates of various litter types ranged from 0.74 to 4.01 y-1 across polar to tropics, showing a large geographical span. Litter substrate and climate directly explained 36 and 30% of the variations in decomposition rates, with the carbon- to- nitrogen ratio identified as the best predictor. In the absence of climate variables, litter substrate can effectively explain the variation, while the model's predictive capacity decreased significantly after litter substrate was excluded. Our synthesis highlights that a fundamental constraint on litter substrate leads to predictable global- scale patterns of terrestrial litter decomposition rates. Integrating litter chemistry parameters should be prioritized for parameter optimization in Earth system models.