气候变化领域集成服务门户(CCPortal): Estimation of grassland aboveground biomass and its response to climate changes based on remote sensing inversion in Three-River-Source National Park, Tibet Plateau, China

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DOI	10.3389/fevo.2023.1326980
	Estimation of grassland aboveground biomass and its response to climate changes based on remote sensing inversion in Three-River-Source National Park, Tibet Plateau, China
	He, Hui; Yu, Hui; Rong, Ziwei; Yang, Yan; Li, Pengshang
发表日期	2023
ISSN	2296-701X
卷号	11
英文摘要	Three-River-Source (TRS) National Park stands as one of China's earliest established national parks, dedicated to significant ecological responsibilities that include conserving soil and water resources in the Tibetan Plateau region. Research on climate change's influence on the TRS region's grasslands is of great significance in our efforts to comprehend and conserve the grassland ecosystem. The most effective random forest (RF) model was chosen to invert the aboveground biomass (AGB) of grassland in the previous 6 years (2015-2020) and predict the grassland AGB in the following 20 years (2021-2040) by comparing linear regression and multivariate nonlinear regression models such as RF, support vector machine, decision tree, and artificial neural network. A Theil-Sen median trend analysis and a Mann-Kendal test were then used to examine the trends of grassland AGB. The results showed that (1) RF outperformed other models in estimating grassland AGB, with a test set decision coefficient of multiple determination (R2) of 0.722, a root mean square error of 42.596 g/m2, and a mean absolute error of 35.619 g/m2; (2) over 6 years, the grassland AGB in TRS National Park had a spatial trend of a steady rise from the northwest to the southeast. The average annual grassland AGB was 247.333 g/m2, with averages of 44.836 g/m2, 92.601 g/m2, and 120.217 g/m2 in the Yangtze River, Yellow River, and Lancang River source parks respectively. The trend of the grassland AGB was primarily stabilized and slightly recovered, with a small portion of the slightly deteriorated areas; (3) climate change significantly affected grassland AGB, and when temperature and precipitation conditions were adequate, grassland AGB values increased with temperature and precipitation. In the scenarios of ssp119, ssp245, and ssp585, grassland AGB is projected to exhibit a dynamic upward trend over the next 20 years. Global warming is expected to boost grassland AGB. Comprehensive measures are essential to maintain grassland health and ensure a positive impact on global carbon and ecological balance. The study's findings hold great importance for the ecological security of the TRS region and contribute to our global understanding of sustainable grassland development.
关键词	climate change grassland AGB machine learning model evaluation remote sensing inversion Three-River-Source National Park
WOS研究方向	Ecology
WOS记录号	WOS:001122668300001
来源期刊	FRONTIERS IN ECOLOGY AND EVOLUTION
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/283566
作者单位	Chinese Academy of Sciences; Institute of Mountain Hazards & Environment, CAS; Chongqing Jiaotong University; Ministry of Natural Resources of the People's Republic of China; Shandong Jianzhu University
推荐引用方式 GB/T 7714	He, Hui,Yu, Hui,Rong, Ziwei,et al. Estimation of grassland aboveground biomass and its response to climate changes based on remote sensing inversion in Three-River-Source National Park, Tibet Plateau, China[J],2023,11.
APA	He, Hui,Yu, Hui,Rong, Ziwei,Yang, Yan,&Li, Pengshang.(2023).Estimation of grassland aboveground biomass and its response to climate changes based on remote sensing inversion in Three-River-Source National Park, Tibet Plateau, China.FRONTIERS IN ECOLOGY AND EVOLUTION,11.
MLA	He, Hui,et al."Estimation of grassland aboveground biomass and its response to climate changes based on remote sensing inversion in Three-River-Source National Park, Tibet Plateau, China".FRONTIERS IN ECOLOGY AND EVOLUTION 11(2023).