Huang Ying, Kang Ao, Gao Dewu, Li Jin, Zhang Hao, Yan Mengyang, Gan Xiaoyu, Zhou Bo
Art College of Chinese & Asean Arts, School of Fine Arts and Design, Chengdu University, Chengdu, 610106, China.
College of Architecture and Environment, Sichuan University, Chengdu, 610064, China.
Environ Manage. 2025 Aug;75(8):1994-2009. doi: 10.1007/s00267-025-02171-9. Epub 2025 Apr 22.
The driving mechanisms of ecosystem services (ESs) involve two aspects: the effects of environmental factors (e.g., precipitation and slope) on ESs and the effects of trade-offs/synergies on ESs. Clarifying the complex causal relationships between environmental factors and ESs is essential for decision-makers to formulate ES management. However, existing studies have focused more on identifying the main drivers of ESs without adequately exploring the direct and indirect effects of environmental factors on ESs, especially those based on the interactions between environmental factors and trade-offs/synergies on ESs. In this study, we proposed an integrated approach of trade-offs/synergies and interactions to quantify the direct and indirect effects of environmental factors on ESs by differentiating between the effects of trade-offs/synergies on ESs and the effects of environmental factors on ESs. Three typical ESs, net primary productivity (NPP), soil conservation (SC), and water yield (WY), were estimated in Sichuan Province from 2000-2020. The trade-offs/synergies between ES pairs were subsequently explored using correlation analysis and the geographically weighted regression (GWR) model. The interactions between environmental factors and ESs were verified and separated utilizing the Geodetector model and partial correlation analysis. Finally, the direct and indirect effects of environmental factors on ESs were measured through the bootstrap method. The results revealed that (1) from 2000-2020, three ESs exhibited significant spatial heterogeneity in Sichuan Province. (2) Complex trade-offs and synergies among these ESs were apparent at the provincial scale, characterized by distinct spatial heterogeneity. (3) DEM, temperature, precipitation, and relative humidity were the dominant factors affecting the spatial heterogeneity of ESs. Notably, the interactions involving environmental factors and ESs demonstrated more robust explanatory power for ESs and their trade-offs/synergies than individual drivers did. (4) DEM and temperature had significant direct and indirect effects on ESs when NPP and WY served as the mediating variables, and these mediating variables contributed significantly to the total effect. The integrated trade-offs/synergies and interactions approach deepens our understanding of ES mechanisms and provides a theoretical basis and reference for decision-making, rather than blindly pursuing the maximization of a particular service at the expense of others.
生态系统服务(ESs)的驱动机制涉及两个方面:环境因素(如降水和坡度)对生态系统服务的影响以及权衡/协同作用对生态系统服务的影响。厘清环境因素与生态系统服务之间复杂的因果关系,对于决策者制定生态系统服务管理至关重要。然而,现有研究更多地集中在识别生态系统服务的主要驱动因素上,而没有充分探究环境因素对生态系统服务的直接和间接影响,尤其是基于环境因素与生态系统服务的权衡/协同作用之间相互作用的影响。在本研究中,我们提出了一种权衡/协同作用与相互作用的综合方法,通过区分权衡/协同作用对生态系统服务的影响和环境因素对生态系统服务的影响,来量化环境因素对生态系统服务的直接和间接影响。对四川省2000 - 2020年的三种典型生态系统服务,即净初级生产力(NPP)、土壤保持(SC)和产水量(WY)进行了估算。随后利用相关性分析和地理加权回归(GWR)模型探究了生态系统服务对之间的权衡/协同作用。利用地理探测器模型和偏相关分析验证并分离了环境因素与生态系统服务之间的相互作用。最后,通过自助法测量了环境因素对生态系统服务的直接和间接影响。结果表明:(1)2000 - 2020年,四川省三种生态系统服务呈现出显著的空间异质性。(2)这些生态系统服务之间复杂的权衡和协同作用在省级尺度上很明显,具有明显的空间异质性。(3)数字高程模型(DEM)、温度、降水和相对湿度是影响生态系统服务空间异质性的主要因素。值得注意的是,与单个驱动因素相比,涉及环境因素与生态系统服务的相互作用对生态系统服务及其权衡/协同作用具有更强的解释力。(4)当以净初级生产力和产水量作为中介变量时,数字高程模型和温度对生态系统服务有显著的直接和间接影响,且这些中介变量对总效应有显著贡献。权衡/协同作用与相互作用的综合方法加深了我们对生态系统服务机制的理解,为决策提供了理论依据和参考,而不是盲目追求某一种服务的最大化而以牺牲其他服务为代价。