长三角城市群地区生态系统服务价值时空演变及驱动因素研究

doi:10.19741/j.issn.1673-4831.2022.0403

摘要/Abstract

摘要： 城市生态福祉问题日益受到关注,探索城市群生态系统服务价值(ESV)驱动效应对于提升城市生态福祉和人居环境健康具有重要借鉴意义。以长江三角洲城市群(长三角城市群)27个城市为研究对象,采用随机森林(RF)和结构方程模型(SEM)方法探究人为活动和自然条件2个方面10项指标对ESV的驱动特征及驱动路径演化特征。结果表明,(1)2000-2020年长三角城市群总体ESV出现先下降后上升的变化趋势,体现出重点湖泊、湿地和水系ESV最高,南部丘陵次之,北部农田再次之,都市群建成区最低的空间分布格局。(2)长三角城市群ESV呈较强的空间聚集模式,其中,2000-2020年扬州、泰州和盐城市接壤地区,盐城和南通市滨海湿地,常州、无锡、苏州和湖州市接壤地区以及南京和马鞍山市接壤地区ESV上升热点效应非常显著。(3)长三角城市群地区水域面积对ESV驱动影响的重要程度高于其他影响因素;SEM分析结果显示,驱动因素通过直接间接方式对2000、2010、2020年ESV以及2000-2020年ESV变化的解释程度总体上分别为85%、84%、83%和72%。长三角ESV空间聚集冷热点演变过程从侧面反映了长三角城市群城市化演变过程;水域面积对ESV的直接驱动效果非常显著;林地面积除对ESV的直接驱动外,对ESV的间接驱动也是重要路径。建议综合考虑各项指标的直接和间接因果驱动效应,从城市群一体化发展的角度提升城市生态系统服务价值。

关键词: 生态系统服务价值, 驱动机制, 结构方程模型, 城市群地区

Abstract: Urban ecological well-being is increasingly concerned these years. Exploring the driving effect of ecosystem service value (ESV) of urban agglomerations has essential reference significance for improving urban ecological well-being and human settlement health. Taking 27 cities in the Yangtze River Delta Urban Agglomeration (YRDUA) as the research object, the driving characteristics and driving path evolution characteristics of 10 indicators of human activities and natural conditions on ESV were explored by using random forest (RF) and structural equation model (SEM). The results show that: (1)During 2000-2020, the overall ESV of the YRDUA decreased first and then increased. Its spatial distribution pattern show that: the highest in key lakes, wetlands, and water systems, followed by hills in the south, farmland in the north, and the lowest in the built-up area of the urban agglomeration. (2) There is a strong spatial aggregation mode of ESV in the YRDUA. For example, during 2000-2020, the hot spot effect of ESV had risen remarkably in the contiguous areas of Yangzhou-Taizhou-Yancheng, Changzhou-Wuxi-Suzhou-Huzhou and Ma'anshan-Nanjing, and in the coastal wetland of Yancheng-Nantoug was very remarkable. (3) The driving influence of water area in the YRDUA on ESV is greater than other factors. SEM shows that the driving factors explain the changes of the ESV in 2000, 2010, 2020, and 2000-2020 through direct and indirect means in different degrees of 85%, 84%, 83%, and 72%, respectively. It is found that the changing process of cold and hot spots of ESV spatial aggregation in the YRDUA reflects the evolution characteristics of urbanization in this area from the side, the water area drives ESV in a very significant and direct way. In addition to the direct way, forest land area drives ESV through an importantly indirect path. It is suggested to consider the direct and indirect driving effects of all factors comprehensively and improve the ESV of urban ecosystem from the perspective of integrated development of urban agglomerations.

Key words: ecosystem service value, driving mechanism, structural equation model, urbdan agglomeration area

中图分类号:

马伟波, 杨帆, 王楠, 赵立君, 谭琨, 张孝飞, 张龙江, 李海东. 长三角城市群地区生态系统服务价值时空演变及驱动因素研究[J]. 生态与农村环境学报, 2022, 38(11): 1365-1376.

MA Wei-bo, YANG Fan, WANG Nan, ZHAO Li-jun, TAN Kun, ZHANG Xiao-fei, ZHANG Long-jiang, LI Hai-dong. Study on Spatial-temporal Evolution and Driving Factors of Ecosystem Service Value in the Yangtze River Delta Urban Agglomerations[J]. Journal of Ecology and Rural Environment, 2022, 38(11): 1365-1376.

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