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Frontiers in Ecology and Evolution
Article . 2023 . Peer-reviewed
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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

Authors: Hui He; Hui He; Hui Yu; Hui Yu; Ziwei Rong; Yan Yang; Pengshang Li;

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

Abstract

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.

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Keywords

model evaluation, grassland AGB, Ecology, Evolution, remote sensing inversion, climate change, machine learning, Three-River-Source National Park, QH359-425, QH540-549.5

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
gold