CN 11-5366/S     ISSN 1673-1530
“风景园林,不只是一本期刊。”

上海市城乡林水复合生态系统类型识别与修复潜力

Identification and Restoration Potential of Urban-Rural Forest-Water Composite Ecosystems

  • 摘要:
    目的 上海作为水网密集型城市,长期面临林水空间利用矛盾突出、生态系统功能协同不足、缺乏水绿一体化建设评估标准等问题,制约了生态系统服务能力的提升与蓝绿空间一体化建设的推进。为回应当前“林水复合·水绿融合”建设的迫切需求,须构建面向城乡生态修复的林水复合区域系统识别思路,以支撑不同类型区域的生态修复潜力评估。
    方法 利用上海市2021—2023年的高时空分辨率影像数据,提出并应用一套林水复合区域分类与识别方法,划分生态融合区、基础林水交界区和待恢复水林区三种类型,结合季节和月度动态指标评估地表植被覆盖及淹水状况,开发针对性评估林水复合生态系统修复潜力的标准化方法。
    结果 1)3类林水复合区域在空间分布上呈现显著差异,生态融合区、基础林水交界区和待恢复水林区的总面积分别为128.90、447.54和25.56 km2,占上海市水体总面积的19%、66%和4%。2)不同林水复合类型区域表现出差异化的动态特征,待恢复水林区表现出最高的动态性,生态融合区次之,基础林水交界区保持相对稳定。3)空间分布上,3类林水复合区域呈现显著的城乡异质性,远郊地区保有更多适宜营建和修复的土地资源,而中心城区虽紧邻主干河流,但因硬质驳岸等原因,林水复合程度明显较低。
    结论 构建的面向城市生态修复的林水复合区域分类与识别体系,揭示了上海市不同区域的生态格局特征和演变机制,为精准施策提供了依据。该研究方法具有良好的通用性,可为其他水网密集型城市的生态空间规划与林水系统优化提供借鉴路径。

     

    Abstract:
    Objective Shanghai, a densely populated megacity with a dense water network, faces challenges such as fragmented forest – water configurations, weak coordination among ecosystem functions, and the lack of standardized frameworks for integrated blue – green spatial planning. These issues constrain ecological capacity and urban planning effectiveness. In response to the urgent need for promoting “forest – water composition” and “water–green integration” as key directions in ecological spatial governance, this study proposes a technical framework for identifying forest–water composite zones and evaluating their restoration potential, aiming to provide spatially explicit ecological management and restoration strategies.
    Methods Taking Shanghai as a case study with its complex hydrological background and dynamic land use, this study uses high resolution satellite images from 2021 to 2023 were processed on the Google Earth Engine platform. Forests and water bodies were extracted using Sentinel-derived Dynamic World land cover products and spectral indices (EVI, NDVI, MNDWI, and LSWI). Seasonal water extent was delineated from maximum water distribution between April and September (2021-2023) to capture hydrological dynamics. A multi-step classification and evaluation system was constructed. Water–forest adjacency was quantified using a spatial adjacency index (shared perimeter over total water perimeter), and water body complexity was measured through the perimeter–area ratio. Dynamic characteristics of vegetation and water cover were calculated at monthly and seasonal scales to establish the seasonal (Is) and monthly (Im) dynamic indices. Based on spatial proximity and temporal variability, forest–water composite zones were classified into three categories: 1) Ecological integration zones (adjacent with sedimentation), 2) basic forest–water interface ( adjacent but weak dynamics); 3) water – forest zones to be restored (sedimentation but lacking forested edges). Spatial patterns are analyzed using Getis-Ord Gi* statistics and nearest neighbor analysis. Restoration potential is assessed through dynamic indicators, spatial adjacency, and available surrounding land.
    Results  The results reveal distinct spatial differentiation. The ecological integration zones, basic forest – water interface zones, and water – forest zones to be restored respectively occupy an area of 128.90 km², 447.54 km², and 25.56 km², representing 19%, 66% and 4% of Shanghai's total water area. Ecological integration zones are primarily distributed in outer districts such as Qingpu and Chongming, corresponding to sediment-rich lakes and wide rivers with forest margins. Basic forest – water interface zones are more evenly spread but concentrated in central districts (e.g., Huangpu, Yangpu, Xuhui), where adjacency exists but dynamic transformation is minimal due to shoreline hardening. Water – forest zones to be restored are typically located at the margins of open water and disturbed lands, including abandoned ponds and silted tributaries. Dynamic analysis shows the highest ecological fluctuation in zones to be restored (Is= 0.41; Im= 0.26), suggesting strong seasonal responsiveness and vulnerability; ecological integration zones exhibit moderate variability (Is= 0.30; Im= 0.15), indicating stable connectivity with restoration potential; basic forest – water interface zone remain largely static (Is= 0.04; Im= 0.01), often due to artificial modification. Urban – rural gradient analysis reveals significant heterogeneity. Suburban districts such as Songjiang and Jiading host larger composite patches, with significant clustering ( p < 0.01), implying high restoration opportunities. In contrast, central areas show fragmented, random distributied patches. Statistical tests confirm no significant relationship between forest – water composite level and water area or shape complexity ( p > 0.05), indicating that composite potential is primarily driven by anthropogenic regulation and policy interventions rather than natural morphology.
    Conclusion This research establishes a standardized, scalable classification and evaluation framework for forest – water composite ecosystems, applicable to complex urban landscapes. Through spatial disaggregation and dynamic assessment, the research uncovers the multi-scalar heterogeneity and ecological transformation patterns of Shanghai’s forest – water systems, enabling precise zoning, targeted restoration, and evidence-based planning. The research further proposes a governance model based on “core – corridor – reserve” spatial logic: Preserving ecological integration zones as biodiversity-rich ecological cores, enhancing basic forest – water interface zones as green – blue corridors, and prioritizing water – forest zones to be restored through adaptive restoration tailored to hydrological and vegetative feedbacks. In central urban areas, vertical ecological integration technologies (e.g., sponge structures, terrace planting) are recommended to overcome spatial constraints, whereas in suburban districts, horizontal corridor expansion is prioritized. The proposed methodological system responds to the urgent need for spatially explicit, process-informed planning tools in water-rich, development-intensive cities. By integrating structural and dynamic metrics, this framework advances understanding of composite ecosystem resilience and provides a practical toolset for restoration prioritization under future climate and land use scenarios. The findings have broader implications for ecological governance in deltaic and river-network cities, offering a transferrable reference for implementing synergistic blue – green infrastructure strategies.

     

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