From static to predictive indicators: Construction of China's spatiotemporal risk zoning index for land use changes ecological risks
文献类型：期刊论文
| 作者 | Zhang, Xuyang2,3; Song, Wei1,3 |
| 刊名 | ECOLOGICAL INDICATORS
 |
| 出版日期 | 2025-10-01 |
| 卷号 | 179页码:114154 |
| 关键词 | Land use change InVEST model LCM model Ecological risk composite index Ecological risk zoning China |
| ISSN号 | 1470-160X |
| DOI | 10.1016/j.ecolind.2025.114154 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | The synergistic interactions between global climate change and anthropogenic activities have amplified the compound stress effects of land-use disturbances on ecosystems, precipitating a substantial escalation in ecological risks (ER). Nevertheless, contemporary assessment frameworks exhibit significant shortcomings in addressing these multidimensional stress dynamics. Prevailing ecological zoning methodologies predominantly employ static evaluation paradigms, which fail to adequately elucidate the spatiotemporal evolution patterns and prospective trajectories of land-use transformations and associated ecosystem services (ESs). These methodological constraints not only impede practical implementation in ER governance but have also perpetuated a critical knowledge gap in spatial partitioning research concerning ER stemming from land-use modifications. To address these challenges, this study pioneers the development of an integrated ecological risk comprehensive index of land use changes (ERCILUC), coupled with the creation of a hierarchical spatial zoning architecture incorporating national-scale, physiographic regionalization, and administrative jurisdictional dimensions. This methodological advancement facilitates the inaugural systematic spatial delineation of ER gradations associated with land use changes (LUC) across China's territorial expanse. The results indicate that: (1) The ERCILUC in China (mean value 4.97 %) demonstrates distinct spatial differentiation characteristics with higher values concentrated in northeastern and southwestern regions, contrasting with lower values in western areas; (2) ER levels exhibit a predominance of low-risk zones (92.99 %), followed by moderate-risk (4.12 %) and high-risk areas (2.89 %); (3) A three-tiered ER zoning system has been established across national-geographic partitionadministrative boundary levels, comprising 5 primary zones, 15 secondary zones, and 45 tertiary zones. The ER zoning framework developed in this study transcends the spatiotemporal scale limitations inherent in conventional research approaches. Through innovative dynamic prediction capabilities, it facilitates the transition from static assessment to dynamic monitoring in ER management, providing scientific foundations and theoretical guidance for ecological functional zoning, coordinated territorial spatial protection, and global risk prevention strategies. |
| URL标识 | 查看原文 |
| WOS关键词 | ECOSYSTEM SERVICES ; HEALTH ; IMPACT |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001584544800001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217503]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Song, Wei |
| 作者单位 | 1.Hebei Collaborat Innovat Ctr Urban Rural Integrat, Shijiazhuang 050061, Peoples R China 2.Anhui Univ Sci & Technol, Sch Earth & Environm, Huainan 232001, Peoples R China; 3.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zhang, Xuyang,Song, Wei. From static to predictive indicators: Construction of China's spatiotemporal risk zoning index for land use changes ecological risks[J]. ECOLOGICAL INDICATORS,2025,179:114154. |
| APA | Zhang, Xuyang,&Song, Wei.(2025).From static to predictive indicators: Construction of China's spatiotemporal risk zoning index for land use changes ecological risks.ECOLOGICAL INDICATORS,179,114154. |
| MLA | Zhang, Xuyang,et al."From static to predictive indicators: Construction of China's spatiotemporal risk zoning index for land use changes ecological risks".ECOLOGICAL INDICATORS 179(2025):114154. |
入库方式： OAI收割
来源：地理科学与资源研究所
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