中国重点生态修复城市(赣州)生态系统服务供需关系及分区管理的多尺度分析

IF 4.8 2区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Qiyou Wang, Tong Li, Qiang Liao, Deer Liu
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引用次数: 0

摘要

随着经济社会的快速发展,决策者需要深入了解可持续生态系统管理在实际应用中的作用,这对生态系统的可持续发展至关重要。理解生态系统供给与社会需求之间的关系,是克服人类与生态系统之间矛盾的关键,也是成功实现生态恢复和区域健康发展的关键。然而,目前针对重点生态修复区生态系统服务供需关系的多尺度、多方法研究还比较缺乏。本研究选取典型的生态屏障(即中国南方的赣州市)作为研究区域,以 2020 年为研究时点,在像素点、乡镇和县域尺度上调查了包括产水量(WY)、固碳(CS)、作物产量(CP)、土壤保持(SR)和娱乐服务(RE)在内的五种生态系统服务(ES)。在多个尺度下,对生态系统服务供给进行了平衡与协调分析,并利用耦合协调度(CD)、匹配度(MD)和供需比(SDR)对供需关系进行了定量分析。最后,根据乡镇尺度的 MD,将赣州市划分为四个区域:高需求区、低需求区、低供应区和高供应区。结果表明,在像素尺度上,CP 与 CS 之间存在权衡关系,而在其他尺度上,ES 之间没有权衡关系。赣州市各区县的供需关系极不协调,存在明显的空间错配。CD 值较高的区域位于崇义县和龙南县,而 SDR 值较低的区域位于人口和 GDP 相对较高的章贡区。赣州市以乡镇为单位的 MD 划分结果显示,17 个乡镇被划分为高需求区(主要分布在城区),23 个乡镇被划分为低需求区(主要分布在郊区);77 个乡镇被划分为低供给区,167 个乡镇被划分为高供给区,主要分布在林区。本研究为区域生态空间规划提供了指导,加深了对生态服务设施管理的理解,为决策者规划未来的生态修复提供了更客观的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multi-scale Analysis of Supply–Demand Relationship of Ecosystem Services and Zoning Management in a Key Ecological-Restoration City (Ganzhou) of China

Multi-scale Analysis of Supply–Demand Relationship of Ecosystem Services and Zoning Management in a Key Ecological-Restoration City (Ganzhou) of China

With the rapid development of economy and society, decision-makers need a deep understanding of the role of sustainable ecosystem management in practical application, which is crucial to the sustainable development of ecosystems. Understanding the relationship between ecosystem supply and social demand is key in overcoming the contradiction between humans and the ecosystem, as well as achieving successful ecological restoration and healthy regional development. However, there is still a lack of multi-scale and multi-method research on the supply–demand relationship of ecosystem services for key ecological-restoration zone. In this study, a typical ecological barrier (i.e., Ganzhou City of southern China) was selected as the research area, and five ecosystem services (ESs) including water yield (WY), carbon sequestration (CS), crop production (CP), soil retention (SR) and recreation service (RE) were investigated at the pixel, township and county scale in 2020. The balance and coordination analysis of ESs supply and the quantitative analysis of the supply–demand relationship (using the coupling coordination degree (CD), matching degree (MD), and supply–demand ratio (SDR)) were executed under multiple scales. Finally, based on the MD at the township scale, Ganzhou City was divided into four areas: high-demand, low-demand, low-supply and high-supply areas. The results reveal a trade-off relationship between CP and CS at the pixel scale, with no trade-off relationships observed among the ESs at the other scales. The supply–demand relationships of different districts and counties in Ganzhou City are highly uncoordinated, with distinct spatial mismatching. Areas with high CD values are located in Chongyi County and Longnan County, while the low/value SDR area is located in Zhanggong District, with a relatively high population and GDP. The results of MD division based on township level in Ganzhou City show 17 townships are classified as high-demand areas (mainly in urban areas) and 23 townships are classified as low-demand areas (mainly in the suburbs); 77 townships are classified as low-supply areas and 167 townships are classified as high-supply areas, which are mainly distributed in forest areas. This study provides guide for regional ecological space planning, enhances the understanding of ESs management, and provides a more objective reference for decision makers to plan future ecological restoration.

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来源期刊
Natural Resources Research
Natural Resources Research Environmental Science-General Environmental Science
CiteScore
11.90
自引率
11.10%
发文量
151
期刊介绍: This journal publishes quantitative studies of natural (mainly but not limited to mineral) resources exploration, evaluation and exploitation, including environmental and risk-related aspects. Typical articles use geoscientific data or analyses to assess, test, or compare resource-related aspects. NRR covers a wide variety of resources including minerals, coal, hydrocarbon, geothermal, water, and vegetation. Case studies are welcome.
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