| 黄土高原生态系统健康时空演变及其驱动因素分析 |
| 摘要点击 155 全文点击 8 投稿时间：2024-07-13 修订日期：2024-08-30 |
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| 中文关键词 生态系统健康 压力-状态-响应（PSR）框架 驱动因素 时空地理加权回归（GTWR）模型 黄土高原 |
| 英文关键词 ecosystem health pressure-state-response（PSR）framework driving factor spatial-temporal geographically weighted regression （GTWR） model Loess Plateau |
| DOI 10.13227/j.hjkx.20250747 |
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| 中文摘要 |
| 明确区域生态系统的健康状况及其驱动因素对于推动可持续发展具有重要意义. 基于“压力-状态-响应（PSR）”框架，评估了2000年、2005年、2010年、2015年和2020年黄土高原生态系统健康水平，并利用时空地理加权回归（GTWR）模型进一步识别了影响生态系统健康水平的主要驱动因素. 结果表明：①研究期间内黄土高原生态系统健康水平呈波动上升的趋势，其值由2000年的0.452上升到2020年的0.464，生态系统健康水平较好的区域主要分布在其中部和东北部地区，其值普遍高于0.45，生态系统健康水平较差的区域主要分布在其西北和东南部分区域，其值多低于0.40；②从空间聚集特征来看，黄土高原生态系统健康水平呈现显著的空间聚集特征，“H-H聚集”主要位于黄土高原中部、西部和东北部的西宁、延安、太原和天水等市； ③驱动因素分析表明，坡度、年均气温、建设用地比例和土地利用强度为影响黄土高原生态系统健康的主导因子，其中坡度主要表现为正向驱动作用，年均气温、建设用地比例和土地利用强度主要表现为负向驱动作用. 研究结果能够为黄土高原生态保护和可持续发展政策的制定提供理论依据. |
| 英文摘要 |
| The clarification of health status of a regional ecosystems and their driving factors is of great significance for promoting sustainable development. Based on the “pressure-state-response （PSR）” framework， the ecosystem health levels of the Loess Plateau were evaluated for the years 2000， 2005， 2010， 2015， and 2020， and the main driving factors affecting ecosystem health levels were further identified by using the spatial-temporal geographically weighted regression （GTWR） model. The following results were obtained： ① During the study period， the ecosystem health level of the Loess Plateau fluctuated upward， with the value increasing from 0.452 in 2000 to 0.464 in 2020. Areas with good ecosystem health levels were mostly distributed in the central and northeastern regions， with values greater than 0.45. Areas with poor ecosystem health levels were mostly distributed in the northwest and southeast regions， with values lower than 0.40. ② From the perspective of spatial aggregation characteristics， the ecosystem health level of the Loess Plateau exhibited significant spatial aggregation.“H-H aggregations”were mostly located in the central， western， and northeastern parts of the Loess Plateau， such as Xining， Yan'an， Taiyuan， and Tianshui. ③ The analysis of driving factors showed that the slope， annual average temperature， proportion of construction land， and land use intensity were the dominant factors affecting the ecosystem health of the Loess Plateau. Slope mainly drove positively， whereas annual average temperature， proportion of construction land， and land use intensity mainly drove negatively. Our results can provide a theoretical basis for the formulation of ecological protection and sustainable development policies on the Loess Plateau. |
