梁子湖流域生态系统服务簇时空演变及其驱动力

生态文明建设背景下,明确流域生态系统服务及其相互作用关系的演变和驱动机制,对流域国土空间生态保护与可持续发展具有重要意义。以梁子湖流域为例,基于FLUS模型、Pearson相关性分析、自组织映射、地理探测器等方法识别流域2010—2030年土地利用变化情况,揭示流域生态系统服务及其相互作用关系的时空演变规律与驱动因素,并提出基于生态系统服务簇的流域生态空间保护的工作框架。结果发现:(1)2010—2030年,流域土地利用变化情况显著,整体表现为耕地和水体面积减少、林地和建设用地面积增加。(2)3种模拟情景中,仅生态保护情景时流域生态系统服务价值上升,其余均呈现不同程度的下降趋势。(3)流域各项生态系统服务之间存在权衡与协同关系,且协同关系占据主导地位。(4)流域共识别出6种生态系统服务簇,其中以食物生产为主导功能的服务簇面积占比最大;服务簇的识别结果与实际土地利用类型较为一致,但同类用地仍可提供多个具有不同主导服务功能的服务簇。(5)流域生态系统服务簇的分异是自然环境、社会经济与景观格局共同作用的结果,优化景观格局能一定程度上保护流域主导服务功能的稳定。

长江源区生态功能区划与生态系统管理

生态功能区划是近年来我国着力建设的一个新的关于资源与环境管理的框架。首先简要讨论了生态功能区划的性质,指出生态功能区划是基于生态系统的地理框架。与生态区比较,生态功能区强调人文活动对生态系统提供产品和服务能力的影响,并反映人类的价值判断。生态功能区划的最终目的是以生态系统的等级结构和尺度原则为基础,在不同尺度水平上实施“基于生态系统的管理”。以长江源区为例,进行了生态功能区划的实证分析。其基本认识是,按照生态系统的自然边界划分生态系统单元;进行生态系统描述和评价;在确定主导生态功能的基础上划分不同的生态功能区。最后讨论了按照生态系统原理对长江源生态功能分区进行管理和建设。

基于要素-结构-功能的生态功能分区--以大理白族自治州为例

生态功能分区综合反映了区域自然生态功能的特征差异,是自然资源开发和生态环境保护空间差异化管治的重要依据。针对以往生态功能分区分析框架复杂多样、权重设定人为主观等问题,本文以云南省大理白族自治州为例,基于要素-结构-功能系统分析框架,从基底要素-干扰结构-主导服务三方面构建指标体系,运用自组织特征映射(SOFM)神经网络依次进行流域主导生态系统服务分区、基底要素分区、干扰结构分区和生态功能综合分区,最终将大理州划分为4个生态功能区和10个生态功能亚区。不同要素分区对比结果表明,大理州生态功能综合分区主要受主导生态系统服务制约,二者重叠率达79.98%。本研究基于要素-结构-功能分析框架,系统刻画了区域生态系统结构与功能特征及其空间差异,为生态功能分区提供了新的方法指引。

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

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.