收藏设为首页 广告服务联系我们在线留言

干旱区地理 ›› 2024, Vol. 47 ›› Issue (9): 1587-1595.doi: 10.12118/j.issn.1000-6060.2023.555 cstr: 32274.14.ALG2023555

• 区域发展 • 上一篇    下一篇

关中平原城市群生态系统服务时空特征及生态功能区划分

张鑫1(), 张丹2(), 张广森3, 宋玫4   

  1. 1.同济大学建筑与城市规划学院,上海 200092
    2.西安建筑科技大学建筑学院,陕西 西安 710054
    3.青岛市政工程公司,山东 青岛 266555
    4.青岛热电燃气公司,山东 青岛 266555
  • 收稿日期:2023-10-08 修回日期:2023-11-19 出版日期:2024-09-25 发布日期:2024-09-24
  • 通讯作者: 张丹(1997-),女,硕士研究生,主要从事低碳生态理论研究. E-mail: 1546038330@xauat.edu.cn
  • 作者简介:张鑫(1994-),男,博士研究生,主要从事低碳生态理论研究. E-mail: zhangx_qd@tongji.edu.cn
  • 基金资助:
    国家自然基金项目(52078404)

Spatiotemporal characteristics of ecosystem services and ecological function areas in Guanzhong Plain urban agglomeration

ZHANG Xin1(), ZHANG Dan2(), ZHANG Guangsen3, SONG Mei4   

  1. 1. College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    2. School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710054, Shaanxi, China
    3. Qingdao Municipal Engineering Company, Qingdao 266555, Shandong, China
    4. Qingdao Thermal Electricity and Gas Company, Qingdao 266555, Shandong, China
  • Received:2023-10-08 Revised:2023-11-19 Published:2024-09-25 Online:2024-09-24

摘要:

量化区域生态系统服务的时空分布格局,分析权衡/协同关系,识别生态系统服务簇,结合各服务簇内的功能特征,划定生态功能分区,有利于加强区域生态系统管理。以关中平原城市群为例,对2000—2020年的5种生态系统服务进行计算,运用K-means聚类分析对服务簇进行识别,确定主导服务功能并实现生态功能分区的划分。结果表明:(1) 粮食生产量和土壤保持量呈现先增加后减少的趋势;产水量呈现先迅速增加后缓慢增加的趋势;生境质量和碳固持量均呈现较轻幅度的减少趋势。粮食生产量高值区主要集中在研究区中部和东北部;土壤保持量的高值区主要集中在南部和西部;生境质量和碳固持量的高值区主要集中在南部。(2) 粮食生产量与其他服务均呈现权衡关系,土壤保持量与生境质量、土壤保持量与碳固持量、生境质量与碳固持量之间均呈现协同关系,不同服务间相关关系的强弱会随着时间的变化而变化。(3) 生态功能分区识别为粮食主产区、生态保育区、重要城市区和生态均衡区。研究结果对于维持生态系统的平衡和经济的可持续发展至关重要,对于促进关中平原城市群不同生态功能分区的生态系统管理具有指导意义。

关键词: 生态系统服务簇, 权衡, 协同, K-means聚类, 关中平原城市群

Abstract:

This study employs a quantitative approach to analyze the spatiotemporal distribution patterns of five ecosystem services in the Guanzhong Plain urban agglomeration, northwest China from 2000 to 2020. Utilizing K-means clustering analysis, ecosystem service clusters are identified, dominant service functions are determined, and ecological functional zones are delineated based on the functional characteristics within each cluster. Results indicate: (1) Grain production and soil retention exhibit a trend of initial increase followed by a decrease, while water yield demonstrates a rapid increase followed by a slow rise. Habitat quality and carbon sequestration services show a relatively mild decrease. High-value zones for grain production are concentrated in the central and northeastern parts, soil retention in the southern and western areas, and habitat quality and carbon sequestration services in the southern region. (2) Grain production shows a trade-off relationship with other services, while soil retention exhibits synergies with habitat quality and soil retention with carbon sequestration, as well as synergies between habitat quality and carbon sequestration, with varying strengths of inter-service correlations over time. (3) Ecological functional zones are identified as primary grain-producing areas, ecological conservation zones, important urban areas, and ecological balance zones. This study is crucial for maintaining the balance of ecosystems and fostering sustainable economic development, providing guidance for ecosystem management in different functional zones within the Guanzhong Plain urban agglomeration.

Key words: ecosystem service clusters, trade-offs, synergies, K-means clustering, Guanzhong Plain urban agglomeration