资源与生态学报

资源与生态学报

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基于动态视角的生态空间识别及其生态系统服务功能时空变化模拟：以四川省邛崃市为例

  

  1. 1. 四川农业大学资源学院，四川成都 611130；
    2.     自然资源部耕地资源调查监测与保护利用重点实验室，四川成都 611130
  • 收稿日期:2021-05-08 修回日期:2021-09-13 接受日期:2021-09-30

Delimiting Ecological Space and Simulating Spatial-temporal Changes in Its Ecosystem Service Functions based on a Dynamic Perspective: Case Study on Qionglai City of Sichuan Province, China

  1. 1. College of Resources, Sichuan Agricultural University, Chengdu 611130, China;

    2. Key Laboratory of Investigation and Monitoring, Protection and Utilization for Cultivated Land Resources,Ministry of Natural Resources, Chengdu 61130, China

  • Received:2021-05-08 Revised:2021-09-13 Accepted:2021-09-30
  • Supported by:
    The Sichuan Science and Technology Program (2020YFS0335, 2021YFH0121); The National College Students’ Innovative Entrepreneurial Training Plan Program of Sichuan Agricultural University (202110626038); The Double Support Program Project of Discipline Construction of Sichuan Agricultural University of China (2018, 2019, 2020).

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摘要： 科学识别生态空间、合理预测主导生态系统服务功能时空变化趋势，是构建国土空间生态保护格局的基础，具有重要的理论意义和应用价值。目前，生态空间识别、功能分区和格局重构大多数以当前生态系统服务功能及其结构信息为参照，忽略了生态系统服务综合功能和主导生态系统服务功能的时空动态性，对未来生态空间主导生态系统服务功能变化模拟不重视，一定程度上影响了生态空间保护格局构建的合理性。本研究提出了一种基于生态系统服务功能动态变化特征的生态空间划定方法，实现了邛崃市生态空间范围识别，解决了当前研究忽略生态系统服务功能时空动态性的问题。在此基础上，研究还应用Markov-CA模型，集成主导生态系统服务功能时空变化特征，实现了2025年邛崃市生态空间主导生态系统服务功能时空变化模拟，为生态空间变化模拟寻找到了合适的方法，也为合理构建生态空间保护格局提供了基础支撑。研究发现邛崃市生态系统服务综合功能量及其年际变化率呈现出明显的动态性，这一发现证实我们在识别生态空间时考虑生态系统服务功能动态特性的必要性。应用本文提出的生态空间识别方法确定邛崃市生态空间面积为98307 ha，与地方生态文明建设规划中确定的相应生态空间范围基本一致，证实了立足于生态系统服务功能动态特性的生态空间划定方法的可靠性。研究结果还表明：2003—2019年，邛崃市主导生态系统服务功能表现出较强的非平稳性，这说明我们应当在生态空间保护格局构建中充分考虑主导生态系统服务功能动态性对未来生态空间功能格局的影响。Markov-CA模型高精度实现了邛崃市主导生态系统服务功能时空变化模拟，Kappa系数达到0.95以上，说明应用该模型模拟未来主导生态系统服务功能空间格局是可行的。模拟结果显示，2019—2025年，受生态系统服务功能非平稳性影响，邛崃市主导生态系统服务功能仍将发生相互转换，预计到2025年，生态空间仍然会保持初级产品生产、气候调节、水文调节三大主导生态系统服务功能，但面积将会发生变化，分别为32793 ha、52490 ha、13024 ha。研究可以为生态保护红线划定、生态功能分区和生态空间保护格局构建提供科学参考。

关键词: font-family:楷体_GB2312, font-size:9pt, ">生态空间；主导生态系统服务功能；动态性；时空变化模拟；font-family:", Times New Roman", ,", serif", font-size:9pt, ">Markov-CAfont-family:楷体_GB2312, font-size:9pt, ">模型

Abstract: Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions (ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai city and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai city’s ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai city show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai city represented strong non-stationary characteristics during 2003-2019, which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019-2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.

Key words: ecological space, dominant ecosystem service functions (ESFs), dynamicity; spatial-temporal change simulation, Markov-CA model