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揭示社会生态互动中的杠杆作用和阻碍因素:以黄河流域农业生产为例。

Uncovering leveraging and hindering factors in socio-ecological interactions: Agricultural production in the Yellow River Basin as an example.

机构信息

State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China.

State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China.

出版信息

J Environ Manage. 2024 Sep;368:122197. doi: 10.1016/j.jenvman.2024.122197. Epub 2024 Aug 13.

Abstract

Agricultural production and sustainable human livelihoods in large river basins are threatened by climate change, human activities, and resource constraints. However, due to the complexity of socio-ecological interactions and agricultural sustainability, current studies are still limited by a priori knowledge and systematic analyses, as well as by the lack of quantification and identification of key factors and valuable pathway structures for agricultural production activities. Here, we combined observation-based causal inference and network analysis to quantify and assess the complex interactions in agricultural production in the Yellow River Basin (YRB) based on data from 12 factors relevant to agriculture over 40 years. We quantitatively assessed the leveraging and hindering roles of the factors in the interacting network system and provided managers with optimization priorities and possible causal pathways to achieve sustainable agriculture in the basin. For example, the fruit yield and income of rural households were identified as leveraging factors that positively affect the agricultural economy. Groundwater was seen as a hindering factor in dampening the negative impacts of the system, highlighting the importance of preventing groundwater depletion. Moreover, the findings suggest that spatially diverse causal interaction structures exist in the YRB and have shaped a variety of distinctive agricultural development modes. Our research ideas and results highlight both systemic considerations and the amplifying or dampening role of factors in interaction pathways, providing valuable quantitative insights into the management and intervention of sustainable agriculture in large river basins. Owing to replaceable and extensible network models, the methodology has the potential to be utilized in a variety of study areas and topics with complex socio-ecological interactions.

摘要

农业生产和人类的可持续生计在大河流域受到气候变化、人类活动和资源限制的威胁。然而,由于社会-生态相互作用和农业可持续性的复杂性,当前的研究仍然受到先验知识和系统分析的限制,也缺乏对农业生产活动的关键因素和有价值的路径结构的量化和识别。在这里,我们结合基于观测的因果推理和网络分析,利用 40 多年来与农业相关的 12 个因素的数据,对黄河流域(YRB)的农业生产中的复杂相互作用进行了量化和评估。我们定量评估了这些因素在相互作用网络系统中的促进和阻碍作用,并为管理者提供了优化优先级和可能的因果路径,以实现流域内的可持续农业。例如,农村家庭的水果产量和收入被确定为促进农业经济的促进因素。地下水被视为阻碍系统负面影响的因素,突出了防止地下水枯竭的重要性。此外,研究结果表明,黄河流域存在空间上多样化的因果相互作用结构,形成了多种独特的农业发展模式。我们的研究思路和结果既强调了系统的考虑因素,又强调了因素在相互作用路径中的放大或抑制作用,为大河流域可持续农业的管理和干预提供了有价值的定量见解。由于可替换和可扩展的网络模型,该方法有可能在具有复杂社会-生态相互作用的各种研究领域和主题中得到应用。

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