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| DOI | 10.1016/j.jnc.2024.126583 |
| Modeling multi-scale relationships between wilderness area changes and potential drivers: Evidence from the southeast coastal area of China | |
| 发表日期 | 2024 |
| ISSN | 1617-1381 |
| EISSN | 1618-1093 |
| 起始页码 | 78 |
| 卷号 | 78 |
| 英文摘要 | An understanding of the trends and causes of wilderness change is critical in supporting wilderness conservation. However, quantitative measurement of the driving mechanisms of wilderness area changes with incorporation of spatial heterogeneity remains a challenge. An integrated wilderness mapping method was employed in this study, with Fujian Province, one of China's first Ecological Civilization Pilot Areas, serving as a case study, to identify the recent spatial distribution and the land-use change matrix of wilderness area changes in the densely populated southeast coastal regions of China. We investigated the potential drivers of changes in wilderness areas from three perspectives: anthropogenic activities and socioeconomics, natural environment, and protected areas management policies, and captured spatial variations using a Multi-Scale Geographically Weighted Regression model (MGWR). The area and quality of wilderness areas showed a decreasing trend from 2000 to 2020, with area decreasing by an average 3.63% annually and wilderness degradation being especially severe from 2010 to 2020. The loss of wilderness areas is influenced by multiple drivers, and under the influence of spatial heterogeneity, different drivers on wilderness areas have a cross-scale spatial character. Human activities and economic development are dominant in driving wilderness degradation and can exert pressure at a large scale. Protected areas may mitigate wilderness loss in the region, but wilderness near protected areas may face greater threats. Natural factors such as vegetation, precipitation and elevation have ambivalent effects, and in some area's climate change may interact with human activities to exacerbate wilderness loss. Compared with global regression and geographically weighted regression models, MGWR produces more realistic results in modeling the relationship between wilderness area changes and potential drivers. This study provides a new perspective for wilderness research, reveals the complex mechanisms of change in wilderness areas, and provides important guidance for global wilderness conservation efforts as well as a reference point for exploring the synergistic interaction between economic development and natural conservation in the densely populated southeast coastal regions of China. |
| 英文关键词 | Wilderness conservation; Wilderness mapping; Spatial heterogeneity; Multi -scale geographically weighted regression; Fujian Province |
| 语种 | 英语 |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| WOS类目 | Biodiversity Conservation ; Ecology |
| WOS记录号 | WOS:001210006800001 |
| 来源期刊 | JOURNAL FOR NATURE CONSERVATION
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| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/291464 |
| 作者单位 | Fujian Agriculture & Forestry University; Tsinghua University; Tsinghua University |
| 推荐引用方式 GB/T 7714 | . Modeling multi-scale relationships between wilderness area changes and potential drivers: Evidence from the southeast coastal area of China[J],2024,78. |
| APA | (2024).Modeling multi-scale relationships between wilderness area changes and potential drivers: Evidence from the southeast coastal area of China.JOURNAL FOR NATURE CONSERVATION,78. |
| MLA | "Modeling multi-scale relationships between wilderness area changes and potential drivers: Evidence from the southeast coastal area of China".JOURNAL FOR NATURE CONSERVATION 78(2024). |
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