初级生产
环境科学
生物地球化学循环
大气科学
生产力
天蓬
叶面积指数
间接影响
植被(病理学)
全球变化
气候变化
全球变暖
生态系统
生态学
化学
环境化学
生物
医学
宏观经济学
病理
政治学
法学
经济
地质学
作者
Yue Chen,Zaichun Zhu,Weiqing Zhao,Muyi Li,Sen Cao,Yaoyao Zheng,Feng Tian,Ranga B. Myneni
标识
DOI:10.1088/1748-9326/ad107f
摘要
Abstract Gross primary productivity (GPP) is jointly controlled by the structural and physiological properties of the vegetation canopy and the changing environment. Recent studies showed notable changes in global GPP during recent decades and attributed it to dramatic environmental changes. Environmental changes can affect GPP by altering not only the biogeochemical characteristics of the photosynthesis system (direct effects) but also the structure of the vegetation canopy (indirect effects). However, comprehensively quantifying the multi-pathway effects of environmental change on GPP is currently challenging. We proposed a framework to analyse the changes in global GPP by combining a nested machine-learning model and a theoretical photosynthesis model. We quantified the direct and indirect effects of changes in key environmental factors (atmospheric CO 2 concentration, temperature, solar radiation, vapour pressure deficit (VPD), and soil moisture (SM)) on global GPP from 1982 to 2020. The results showed that direct and indirect absolute contributions of environmental changes on global GPP were 0.2819 Pg C yr −2 and 0.1078 Pg C yr −2. Direct and indirect effects for single environmental factors accounted for 1.36%–51.96% and 0.56%–18.37% of the total environmental effect. Among the direct effects, the positive contribution of elevated CO 2 concentration on GPP was the highest; and warming-induced GPP increase counteracted the negative effects. There was also a notable indirect effect, mainly through the influence of the leaf area index. In particular, the rising VPD and declining SM negatively impacted GPP more through the indirect pathway rather than the direct pathway, but not sufficient to offset the boost of warming over the past four decades. We provide new insights for understanding the effects of environmental changes on vegetation photosynthesis, which could help modelling and projection of the global carbon cycle in the context of dramatic global environmental change.
科研通智能强力驱动
Strongly Powered by AbleSci AI