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Spatial Heterogeneity and Driving Mechanisms of Carbon Storage on the Chinese Loess Plateau

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Résumé fourni par la source

The Chinese Loess Plateau is a vast semi-arid landscape that has experienced substantial vegetation recovery through afforestation since the late twentieth century, altering the regional carbon cycle and contributing to China’s carbon neutrality efforts. However, large-scale quantification of carbon storage (CS) remains challenging in this heterogeneous and erosion-prone landscape. In this study, the PLUS land-use simulation model was coupled with an InVEST-based carbon storage accounting framework, and multi-source remote sensing and field survey data were integrated to quantify historical carbon storage from 1980 to 2020 and predict carbon storage in 2040 under three future land-use scenarios: natural development (ND), cultivated land protection (CLP), and ecological protection (EP). The results showed that NDVI exhibited a distinct southeast-to-northwest gradient, with peak values (>0.8) in the southeastern tablelands, where CS reached 10.27 ± 4.20 kg C m−2. Carbon storage increased from 1980 to 2020, primarily due to afforestation, with higher CS in the humid southeastern plateau and lower CS in the arid northwest. Scenario simulation showed that CS maintained a baseline level of 7.07 ± 3.81 kg C m−2 under the ND scenario, increased slightly to 7.08 ± 3.77 kg C m−2 under the CLP scenario, and reached the highest value of 7.10 ± 3.80 kg C m−2 under the EP scenario. SEM-based mechanism analysis indicated that topography exerted the strongest direct influence on CS, followed by vegetation, climate, and socioeconomic factors. These findings suggest that water availability and topographic constraints strongly regulate CS in semi-arid regions, while land-use policy can still modify CS through scenario-dependent land-use change.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Spatial Heterogeneity and Driving Mechanisms of Carbon Storage on the Chinese Loess Plateau
Date Crossref
06/08/2026
Éditeur
MDPI AG
Type
journal-article

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Institutions déclarées

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Sujets associés

Remote Sensing in AgricultureLand Use and Ecosystem ServicesPlant Water Relations and Carbon Dynamics

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