摘要
Non-photosynthetic vegetation (NPV), comprising dead branches, fallen leaves, senescent stems, and plant residues, plays a critical role in regulating terrestrial carbon dynamics. However, conventional carbon models and remote sensing products frequently misclassify NPV as bare soil (BS), resulting in systematic underestimation of organic matter transfer, soil respiration, and soil carbon sink along climatic gradients. This misclassification introduces structural biases into carbon fluxes modeling and impedes accurate quantification of vegetation-soil carbon feedbacks. Here, we generated annual maximum NPV coverage (fNPV) products for China at a 300 m spatial resolution for the period 2016–2024 by integrating Sentinel imagery with field observations. To better characterize ecosystem-level carbon fluxes, we propose a novel ecosystem carbon exchange flux (ECEF) index that integrates NPV, photosynthetic vegetation (PV), and BS. Nationally, the average annual fNPV was 0.3679, with an annual increase of 0.0014 yr−1. The highest values were observed in semi-arid to sub-humid regions (Rs), reaching 0.4235 with an annual increase of 0.0075 yr−1. Boosted regression tree analysis identified quarterly temperature and precipitation as dominant climatic drivers, explaining 19.38% and 15.22% of the variance in fNPV, respectively. Carbon sink strength varied along climate gradients, with ECEF values of 0.95 in humid regions and −0.47 in arid regions. Spatial analysis revealed a strong inverse correlation between ECEF and net ecosystem exchange (NEE) (Pearson’s r=−0.68, p<0.05, R2=0.46), supporting ECEF as a robust framework for estimating carbon fluxes across climatic regions. This model-based proxy provides a scalable approach for assessing ecosystem carbon dynamics in regions where direct flux measurements are sparse or unavailable. These findings emphasize the ecological significance of NPV in the terrestrial carbon cycle and underscore its essential role in improving carbon flux estimates under accelerating climate change.
| 源语言 | 英语 |
|---|---|
| 页(从-至) | 151-168 |
| 页数 | 18 |
| 期刊 | Science China Earth Sciences |
| 卷 | 69 |
| 期 | 1 |
| DOI | |
| 出版状态 | 已出版 - 1月 2026 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 13 气候行动
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可持续发展目标 15 陆地生物
指纹
探究 'Spatiotemporal dynamics of non-photosynthetic vegetation across China and their implications for carbon fluxes along climate gradients' 的科研主题。它们共同构成独一无二的指纹。引用此
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