Spatial and temporal distribution of ecosystem services and trade-offs in the Yangtze River Delta
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摘要:研究目的
生态系统服务关系人类福祉，生态系统服务的可持续供给可为区域生态安全和可持续发展提供保障。
研究方法基于InVEST模型，结合土地利用类型、归一化植被指数（Normalized Differnce Vegetation Index, NDVI）和气象数据，分析1990—2020年长江三角洲地区植被净初级生产力（Net Primary Productivity, NPP）、土壤保持、生境质量和碳储量4种重要生态系统服务功能的时空分布特征，并识别其热点区域。采用相关系数法，分析长江三角洲地区不同生态系统服务功能与土地利用类型之间的权衡/协同关系。
研究结果结果表明：①长江三角洲地区的生态系统服务功能具有明显空间异质性，生境质量、水土保持和碳储量呈现出西南高、东北低的空间格局，且生境质量和碳储量的高值沿江分布。1990—2020年，生境质量与碳储量多数提升；土壤保持和植被净初级生产力整体呈现下降趋势，但东部地区有所提高。②1990—2020年，3类热点区（热点区、显著热点区、极显著热点区）所占面积无显著变化，集中分布在西南地区，具有明显的地带性。③土壤保持、碳储量、生境质量之间主要为协同关系，而NPP与碳储量、生境质量、土壤保持主要为权衡关系。为确保当地生态系统的可持续管理，在空间规划中应考虑生态系统服务之间的相互联系，尽量减少权衡效应，提高协同效应。
结论本次研究聚焦于长江三角洲区域，基于ArcGIS和Geoda，通过整合遥感数据、地理信息数据、社会经济数据等多源数据集，对长三角地区的4项关键生态系统服务（固碳能力、土壤保持、生境质量和植被净初级生产力）进行了全面评估，系统地揭示了长三角地区在格网县域尺度上的生态系统服务空间格局特征，为深入理解和优化该区域的生态系统服务提供了重要依据。
Abstract:ObjectiveValuation of ecosystem services is critical to the sustainable development of a region and human well−being.
MethodsTaking the Yangtze River Delta as the study area, we analysed the spatial and temporal distribution characteristics of four important ecosystem service functions, namely, net primary productivity (NPP) of vegetation, soil retention, habitat quality and carbon storage, in the Yangtze River Delta region from 1990 to 2020, based on the InVEST model and combining the land use types, normalised difference vegetation index (NDVI) and meteorological data. The spatial and temporal distribution characteristics of four important ecosystem services, namely vegetation net primary productivity (NPP), soil conservation, habitat quality and carbon storage, were analysed from 1990 to 2020, and hotspot areas for the four ecosystem services were identified. The correlation coefficient method was used to analyze the relationship between various ecosystem functions and land use types in the Yangtze River Delta region.
ResultsThe results show that: ① the ecosystem service functions in the Yangtze River Delta region are spatially heterogeneous, with habitat quality, soil and water conservation and carbon storage showing a spatial pattern of "high in the southwest and low in the northeast", while the high values of habitat quality and carbon storage are distributed along the river. During the period 1990−2020, habitat quality and carbon storage services show a trend of "overall increase − local decrease", while soil conservation and vegetation net primary productivity services show a trend of "overall decrease − local increase". ② The area occupied by the three types of hotspots (hotspots, significant hotspots and very significant hotspots) in the Yangtze River Delta does not change significantly, and the distribution is obviously zonal, concentrated in the southwest. ③ In the Yangtze River Delta, there is a synergistic relationship between soil conservation, carbon storage and habitat, and NPP is a trade−off with carbon storage, habitat quality and soil conservation; among the seven land use types, NPP and soil conservation have a trade−off relationship. The trade−off/synergistic relationship between NPP and soil conservation is consistent with the Yangtze River Delta region. To ensure the sustainable management of local ecosystems, it is necessary to consider the interrelationships among ecosystem services in spatial planning to minimise trade−offs and enhance synergies.
ConclusionsThis study focused on the Yangtze River Delta region and comprehensively evaluated four key ecosystem services (carbon storage, soil retention, habitat quality and net primary productivity of vegetation) in the Yangtze River Delta region through integrating multi−source datasets such as remote sensing data, geographical information data and socio−economic data, based on ArcGIS and Geoda. It systematically revealed the spatial pattern characteristics of ecosystem services in the Yangtze River Delta region on the grid−county scale, providing an important basis for in-depth understanding and optimizing the ecosystem services in this region.
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Keywords:
- ecosystem services /
- InVEST model /
- trade−off and coordination /
- Yangtze River Delta
创新点分析了1990—2020年长江三角洲地区4种重要生态系统服务功能的时空分布特征及权衡/协同关系，为长江三角洲生态系统服务的动态变化提供科学依据，并有助于制定区域可持续管理政策。
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图 1 长江三角洲区位图
a—长江三角洲地理位置（基于自然资源部标准地图服务网站GS(2021)7160号的标准地图绘制底图边界无修改，后图同）；b—长江三角洲高程分布；c—长江三角洲各省市土地利用类型分布
Figure 1. Location of Yangtze River Delta
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图 3 7种土地利用类型的4种生态系统服务分布风向玫瑰图
Figure 3. Wind rose map of the distribution of four ecosystem services for seven land use types
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图 4 长江三角洲4类典型生态系统服务冷热点空间分布图
Figure 4. Yangtze River Delta’s spatial mapping of thermal anomalies for four characteristic ecosystem services
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图 5 长江三角洲4种主要生态系统服务的双变量局部空间自相关性和集聚分布图
Figure 5. Two-dimensional local spatial autocorrelation and cluster distribution of four important ecosystem services in the Yangtze River Delta
表 1 数据来源与描述
Table 1 Data source and description
数据类型 数据名称 数据来源 空间分辨率 相关用途 遥感数据 土地利用/覆被数据集：Landsat 8 中国科学院资源环境科学与数据中心
(https://www.resdc.cn/)30 m 土地利用类型 夜间灯光数据集：NPP-VIRS 500 m 生境质量需求 高程数据（DEM）
集：SRTM250 m 土壤保持供给与需求
（地形因子）初级净生产力数据（NPP）集：MOD17A3 https://ladsweb.modaps.eosdis.nasa.gov/ 500 m 归一化植被指数集：MOD13Q1
(NDVI)250 m 人口数据 https://www.worldpop.org/ 1 km 固碳需求 土壤数据 土壤有机质、土壤质地等 HWSD土壤数据库(http://data.tpdc.ac.cn/zh-hans/) 1∶ 1000000 土壤保持供给与需求 气候数据 逐月降水量 中国科学院资源环境科学与数据中心
(https://wwwresdc.cn)；
国家青藏高原科学数据中心
(https://data.tpdc.ac.cn/home)1 km 土壤保持供给与需求 二氧化碳排放量 市域尺度 固碳需求 社会经济数据 生物物理表和威胁因素 CHRED 3.0数据库 生境质量供给 其他数据 文献和InVEST用户指南 
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表 2 长江三角洲各项生态系统服务冷热点空间分布范围及面积占比
Table 2 The proportion of the cold and hot spots ecosystem services in Yangtze River Delta
生态系统服务 1990年热点区（热点、显著热点和极显著热点）占比/% 1990年冷点区（冷点、显著冷点和极显著冷点）占比/% 2020年热点区（热点、显著热点和极显著热点）占比/% 2020年冷点区（冷点、显著冷点和极显著冷点）占比/% 生境
质量11.409 0 11.107 0 土壤
保持19.045 1.886 13.314 0 碳储量 13.340 6.187 13.340 6.187 NPP 2.895 2.133 7.415 3.059
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表 3 生态系统服务主成分分析
Table 3 Principal component analysis of ecosystem services
生态系统服务 1990年 2000年 2010年 2020年 成分1 成分2 成分1 成分2 成分1 成分2 成分1 成分2 碳储量 0.721 0.688 0.789 0.608 0.794 0.602 0.804 0.589 生境质量 −0.723 0.691 −0.789 0.612 −0.793 0.607 −0.802 0.594 土壤保持 −0.997 0.061 −0.995 0.088 −0.995 0.091 −0.995 0.098 NPP 0.999 −0.021 0.999 −0.018 0.999 −0.018 0.999 −0.017 解释方差/% 92.084 6.392 85.651 12.714 85.160 13.234 85.071 13.312
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