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基于生态系统服务簇的山东省黄河流域分区管控

Zoning management and control for the Yellow River Basin in Shandong Province of China using ecosystem service bundles

  • 摘要: 黄河流域重大国家战略背景下山东段生态系统破碎化、生物多样性下降等问题依旧显著,如何开展生态保护分区分类管控,是提升区域生态系统服务的关键。该研究首先利用InVEST模型,对2002—2022年山东省沿黄9市77个区县水源涵养、碳存储、土壤保持、生境质量4项重要生态系统服务进行评估;其次,运用自组织神经网络映射模型进行聚类分析,识别生态系统服务簇;并通过面板数据计量经济模型解释生态系统服务簇的驱动因素,进而提出有针对性的山东省黄河流域的生态分区管控策略。结果表明:1)水源涵养呈现鲁中山区—黄河流域干流两岸地区—鲁西平原渐递减的阶梯式空间分布特征,鲁中山区的降水明显高于其他地区;碳存储呈现山区高,平原低的态势;土壤保持量呈现鲁中山区-鲁西平原-黄河三角洲逐级递减的阶梯式空间分布特征。鲁中山区、黄河三角洲、东平湖和南四湖的生境质量最高,城镇聚集区的生境质量最低。2)根据生态系统服务的空间分布特征,采用自组织神经网络将山东省黄河流域的77个区县划分为四类簇:生态协调簇、水源保护簇、生态发展簇和城市发展簇。3)基于生态系统服务簇进行驱动因素分析,气温、降水、人口、土地利用强度等对生态系统服务簇转化有不同程度的影响。4)根据生态系统服务簇的聚类识别,将77个区县划分为6大片区:水源保护区、核心保护区、优势服务区、生态提升区、重点保护区和生态农业区,并从生态保护和高质量发展两个方面提出差异化管控策略。研究提出的分区管控路径可助力山东省国土空间生态修复和空间格局优化及碎片化管理。

     

    Abstract: Ecosystem fragmentation and biodiversity are declining in the sections of the Yellow River Basin in Shandong Province. It is often required for the zoning-based ecological conservation with categorical controls, in order to enhance the regional ecosystem services. In this study, the InVEST model was first employed to evaluate four key ecosystem services (ES): water yield, carbon storage, soil conservation, and habitat quality, over 77 counties in nine cities adjacent to the Yellow River in Shandong Province from 2002 to 2022. Subsequently, a self-organizing feature mapping (SOFM) model with a conventional K-means cluster was utilized for the cluster analysis. The ecosystem service bundles were then identified to validate the clustering of ecosystem service bundles. Finally, an econometric model of the panel data was applied to interpret the driving factors of the ecosystem service bundles (ESB). And the driving factors of four ecosystem services were adopted as fixed effects models (FEM) in econometrics, while random effects models (REM) were employed for the ESB-driven analysis. Furthermore, targeted ecological zoning control strategies for the Yellow River Basin in Shandong Province are proposed.The results revealed: 1) Spatiotemporal distribution. Water yield exhibited a stepped spatial gradient with the decrease from the central mountainous area to the main channel, and further to the western Shandong plain. Precipitation in the central mountainous region was significantly higher than in the rest areas. Carbon storage shared the higher values in the mountainous areas, whereas the lower values were found in the plains. Soil conservation displayed a hierarchical decline from the central mountainous area to the western plain and the Yellow River Delta. Habitat quality was highest in the central mountainous area, the Yellow River Delta, Dongping Lake, and Nansi Lake. While the urban agglomerations exhibited the lowest habitat quality. In terms of time span, the water yield capacity increased by 0.3% in 2022, compared with the 2002–2022 average. The carbon storage capacity decreased by 4.5% annually, compared with 2022; The soil conservation capacity was twice in 2022 as much was in 2002. The habitat quality remained largely unchanged with a 0.2% increase since 2002. 2) Ecosystem service bundles identification. According to the spatial distribution patterns of ecosystem services, the SOFM classified the 77 counties into four ESBs: ecological coordination, water conservation, ecological development, and urban development bundle. The urban development bundles evolved into the ecological ones, while purely urban development bundles decreased markedly in 2002-2007. Only a little significant change occurred in 2007-2012. Furthermore, the ecological development bundles decreased significantly, while the urban development bundles increased substantially in 2012-2017. Ecological development bundles increased markedly, whereas the urban development bundles decreased noticeably in 2017-2022. 3) Driving factors. Driving mechanisms indicated that the temperature, precipitation, population, and land development intensity exerted varying degrees on the ecosystem service bundles. Among them, there were significant negative effects of the temperature and land development intensity on the ESB changes. While the precipitation and population shared the positive effects. There was a significant variation in the dominant influencing factors on the different ecosystem service bundles. Therefore, the ecological measures should be implemented to tailor to the local conditions of each ecological functional zoning. 4) Zoning strategies. 77 counties were divided into six major zones: water conservation, core protection, dominant service, ecological enhancement, key protection, and ecological agriculture zone. Different strategies were proposed from the perspectives of ecological conservation and high-quality development. The zoning framework can provide the scientific support to mitigate the fragmentation for the spatial patterns optimization and ecological restoration in Shandong Province. Great contributions can also be achieved for the coordinated development of the ecological protection and socio-economic goals for the Yellow River Basin. Four types of ecosystem service bundles and the six major zoning schemes can be directly applied to the rest provinces within the Yellow River Basin, as well as to the major river systems across China. The spatially differentiated applicability and dissemination can also provide precise guidance for the decision-making on the regional production.

     

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