初级生产
气候变化
环境科学
降水
土地利用、土地利用的变化和林业
植被(病理学)
持久性(不连续性)
全球变化
生态系统
土地利用
气候学
自然地理学
大气科学
生态学
地理
气象学
生物
医学
地质学
工程类
病理
岩土工程
作者
Xiaojuan Xu,Fusheng Jiao,Huiyu Liu,Haibo Gong,Changxin Zou,Naifeng Lin,Peng Xue,Mingyang Zhang,Kelin Wang
标识
DOI:10.1016/j.scitotenv.2022.155086
摘要
Substantial evidence suggests a widespread increase in global vegetation gross primary production (GPP) since the 1980s. If the increasing trend of GPP remains unchanged in the future, it is considered to be the persistence of increasing GPP. However, it is still unknown whether the vegetation increasing GPP is persistent under the interactive effects of climate change and land use changes in Northwest China. Using the Mann-Kendall and boosted regression tree models, we constructed the relationship between the increasing GPP and environmental variables, and further explored its persistence under the interactions between climate change and land use changes under SSP245 and SSP585 scenarios. The results indicated that: (1) Land use change (8.01%) was the most important variable for the increasing GPP. The surface net solar radiation (6.79%), and maximum temperature of the warmest month (6.78%) were also very important. Moreover, mean temperature of the warmest quarter had strong interactions with mean precipitation of the warmest quarter (9.82%) and land use change (8.24%). (2) Under the SSP245 scenario, the persistence of increasing GPP accounted for 65.06% of the area in 2100, mainly located in Qinghai, Ningxia, and Shaanxi, while it only accounted for 19.50% under the SSP585 scenario. (3) The SSP245 scenario moderate warming leads to a slight ecosystem benefit, with more areas developing an increase in GPP due to climate and land use change factors. On the other hand, under SSP585 scenario, there are widespread losses of increasing GPP, driven largely by climate change, while ecological engineering is conducive to the persistence of increasing GPP in southern Qinghai. The results highlight the importance of the interactive effects of climate change and land use changes for predicting the persistence of vegetation change.
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