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Revealing subtle vegetation productivity dynamics in China via a reference-based framework

文献类型：期刊论文

作者Zhang, Shuyi4; Ci, Mengyao4; Zhang, Rui4; Tang, Hanxin4; Jin, Ziwen4; Zeng, Ke4; Wang, Yue4; Zhang, Jiarui3; Niu, Aoying4; Deng, Jie4
刊名GISCIENCE & REMOTE SENSING
出版日期2026-12-31
卷号63期号:1页码:2617775
关键词Reference-based gross primary production long-term dynamics ecological zones human activity zones
ISSN号1548-1603
DOI10.1080/15481603.2026.2617775
产权排序3
文献子类Article
英文摘要Vegetation productivity exhibits substantial spatiotemporal heterogeneity under the combined influence of climate change and anthropogenic disturbance. However, conventional long-term assessments focus on absolute changes, neglecting ecological heterogeneity and climatic confounding, thus limiting their utility for ecosystem management. From ecological and human activity perspectives, we established a reference-based framework using undisturbed ecosystems as ecological baselines, to detect subtle vegetation productivity dynamics across China between 2000 and 2020, capturing deviations between observed and reference productivity. The results showed that the RBRA significantly improved the detection of productivity declines, identifying a decline-affected area in China 39 percentage points larger than that of the CAA, particularly in temperate humid zones and northern regions with high human activity. By combining RBRA and CAA, four vegetation productivity change categories (sustained improvement, potential improvement, latent degradation, and sustained degradation) were identified. At the ecological zone level, the Tibetan Plateau emerged as the primary hotspot of relative decline (80.41%), while over 50% of the humid south-central region achieved sustained improvement. At the human activity zone level, high-intensity zones exhibited over 42% latent degradation, whereas low-intensity areas were dominated by sustained improvement (48-61%). Attribution analysis revealed that while climatic constraints remained the dominant drivers of vegetation productivity change, degradation risks driven by land-use change and economic expansion were more clearly captured by the RBRA framework, particularly in vulnerable and human-impacted regions. Overall, the reference-based framework enhances sensitivity to subtle vegetation change signals and provides a robust scientific basis for targeted conservation and adaptive ecosystem management.
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WOS关键词URBANIZATION ; DEGRADATION ; PATTERNS ; DATASET
WOS研究方向Physical Geography ; Remote Sensing
语种英语
WOS记录号WOS:001666628900001
出版者TAYLOR & FRANCIS LTD
源URL[http://ir.igsnrr.ac.cn/handle/311030/219690]  
专题生态系统网络观测与模拟院重点实验室_外文论文
通讯作者He, Honglin; Liu, Min
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China;
2.Inst Ecochongming IEC, Shanghai, Peoples R China
3.Shanghai TingYing Environm Technol Co LTD, Shanghai, Peoples R China;
4.East China Normal Univ, Global Inst Urban & Reg Sustainabil, Sch Ecol & Environm Sci, Zhejiang Zhoushan Isl Ecosyst Observat & Res Stn, Shanghai, Peoples R China;
推荐引用方式
GB/T 7714		 Zhang, Shuyi,Ci, Mengyao,Zhang, Rui,et al. Revealing subtle vegetation productivity dynamics in China via a reference-based framework[J]. GISCIENCE & REMOTE SENSING,2026,63(1):2617775.
APA Zhang, Shuyi.,Ci, Mengyao.,Zhang, Rui.,Tang, Hanxin.,Jin, Ziwen.,...&Liu, Min.(2026).Revealing subtle vegetation productivity dynamics in China via a reference-based framework.GISCIENCE & REMOTE SENSING,63(1),2617775.
MLA Zhang, Shuyi,et al."Revealing subtle vegetation productivity dynamics in China via a reference-based framework".GISCIENCE & REMOTE SENSING 63.1(2026):2617775.

入库方式： OAI收割

来源：地理科学与资源研究所

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