李帆, 贾夏, 赵永华, 奥勇, 韩磊, 刘钊, 丁诗雨. 基于DPSIR模型的黄土高原生态敏感性演变格局及驱动力分析[J]. 农业工程学报, 2023, 39(9): 241-251. DOI: 10.11975/j.issn.1002-6819.202211239
    引用本文: 李帆, 贾夏, 赵永华, 奥勇, 韩磊, 刘钊, 丁诗雨. 基于DPSIR模型的黄土高原生态敏感性演变格局及驱动力分析[J]. 农业工程学报, 2023, 39(9): 241-251. DOI: 10.11975/j.issn.1002-6819.202211239
    LI Fan, JIA Xia, ZHAO Yonghua, AO Yong, HAN Lei, LIU Zhao, DING Shiyu. Evolutionary pattern and driving forces of ecological sensitivity in the Loess Plateau using DPSIR model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(9): 241-251. DOI: 10.11975/j.issn.1002-6819.202211239
    Citation: LI Fan, JIA Xia, ZHAO Yonghua, AO Yong, HAN Lei, LIU Zhao, DING Shiyu. Evolutionary pattern and driving forces of ecological sensitivity in the Loess Plateau using DPSIR model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(9): 241-251. DOI: 10.11975/j.issn.1002-6819.202211239

    基于DPSIR模型的黄土高原生态敏感性演变格局及驱动力分析

    Evolutionary pattern and driving forces of ecological sensitivity in the Loess Plateau using DPSIR model

    • 摘要: 摸清生态系统敏感性时空演变格局,对其驱动因素及未来发展趋势进行探测是修复和提高生态系统稳定性的重要内容。黄土高原是世界上水土流失最严重和生态环境最脆弱的地区之一,探究该地区生态敏感性时空演变特征及驱动因素,科学划分生态敏感性治理分区对于促进国家生态文明建设具有重要意义。基于“驱动-压力-状态-影响-响应”(driving-pressure-state-impact-response,DPSIR)框架,耦合空间距离指数和全排列多边形图示指标法构建生态敏感性指标体系,使用地理信息演变图谱和地理探测器研究黄土高原2000—2020年5个时间点生态敏感性时空格局和驱动力,最终划分生态敏感性治理分区。结果表明:1)研究期内黄土高原生态敏感性表现为西北高、东南低的分布特征,时间上先增加后下降。2)研究期内黄土高原生态敏感性转移类型以波动稳定型为主,生态改善区面积占比最大(35.17%),变化0次和1次的面积占比62.06%,生态环境演变稳定向好。3)生态敏感性的各驱动因素中,NDVI和降水量以及两者与其他因子的交互作用对于黄土高原生态敏感性具有明显的驱动作用。4)2030年低度敏感将成为黄土高原的主要敏感类型;沙地和农灌区以及黄土高塬沟壑区的中西部是生态敏感性治理的重点地区。整体来看,黄土高原生态环境有所好转,生态治理措施取得了积极成效,该研究可为黄土高原生态治理及高质量发展提供参考。

       

      Abstract: The temporal and spatial evolution pattern of ecosystem sensitivity has been one of the most important components to restore and improve ecosystem stability, together with the driving factors and future development trends. The Loess Plateau is one of the typical areas with the most severe soil erosion in the world. Alternatively, the implementation of the "Grain for Green" project in 1999 has significantly improved the ecological environment. It is a high demand to examine the suitability of ecological governance measures using the temporal and spatial evolution characteristics of ecological sensitivity in the Loess Plateau over the past 20 years. In this study, an ecological sensitivity index system was constructed to couple the spatial distance index and the entire array-polygon indicator under the Driving-Pressure-State-Impact-Response framework. The temporal and spatial patterns and their driving forces of ecological sensitivity were investigated at five-time points from 2000 to 2020 in the Loess Plateau using a geographic information evolution map and a geographic detector. The CA-Markov model was used to simulate the ecological sensitivity for ecological zoning in 2030. The results showed that: 1) Spatially, the ecological sensitivity of the Loess Plateau exhibited a distribution pattern of high in the northwest and low in the southeast, with the high sensitivity types decreasing towards the southeast direction and the aggregation weakening, while the low sensitivity types increased towards the northwest direction, but the aggregation strengthened at the original position. Temporally, there was a varying trend of first increasing and then decreasing. 2) The ecological sensitivity transfer types were mainly fluctuating stability. In individual sensitivity types, the insensitive transfer type was mainly stability, while the low, moderate, and severe sensitive transfer types were mainly fluctuating stability, and the extremely sensitive transfer type was mainly reduction. The largest area proportion of the ecological improvement zone (35.17%) was mainly distributed in the western part of the Loess Plateau. The areas with 0 and 1 changes accounted for 62.06%, indicating a stable and improving trend in the ecological environment. 3) The most significant effect of the natural factors on the ecological sensitivity among the driving factors. The NDVI, precipitation, and their interaction posed a significant driving effect on ecological sensitivity. 4) The ecological sensitivity can be expected as the distribution pattern of high in the northwest and low in the southeast in 2030, where the low sensitivity will be the main sensitive type. The key areas of ecological protection were obtained as the sandy land, agricultural irrigation region, and the mid-west of the loess sorghum gully region. Overall, the ecological environment of the Loess Plateau has improved after the ecological governance measures. This study can provide a strong reference for the ecological environment and high-quality development in the Loess Plateau.

       

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