Sihui Xin , Zhouyuan Li , Junsong Nong , Jiaxin Wu , Xinwei Zou , Ruijin Wu , Shikui Dong , Rongling Wu , Shaopeng Wang
{"title":"Environmental system dynamics: Current development and applications","authors":"Sihui Xin , Zhouyuan Li , Junsong Nong , Jiaxin Wu , Xinwei Zou , Ruijin Wu , Shikui Dong , Rongling Wu , Shaopeng Wang","doi":"10.1016/j.ecolmodel.2025.111135","DOIUrl":null,"url":null,"abstract":"<div><div>System Dynamics (SD) has emerged as a fundamental and powerful modeling methodology for understanding and simulating the behavior of both natural and social-economic systems. This review explores the historical development, key concepts, and broad applications of SD as a fundamental modeling approach. Tracing its evolution from the its inception since 1960s, the paper outlines the four major phases of SD's growth, from its initial conceptualization, through its methodological refinements, to its widespread application in ecosystems, and socio-economic systems in recent over the half century. The review highlights the development of SD communities across the globe, including the North American school, European clusters, and the growing body of work in China, and the progress in the global collaboration. We discuss and organize the foundational paired concepts of SD, including stock-flow relationships, the structure-behavior paradigm, the cause-effect process, and the loop-feedback paradigm. We summarize the SD modeling workflow protocol in the four stages, as conceptualization, visualization, quantification, and verification. It demonstrates good practices of SD modeling in various ecological contexts, spanning population, community, landscape, and macro-ecosystem levels, while emphasizing the method's adaptability and capacity for spatial modeling. Building on an extensive literature review and bibliometric analysis, the paper synthesizes key progress in SD modeling while offering insights into future perspectives and potential advancements. It concludes by reflecting on SD's ability to address multi-scale, multi-dimensional challenges and its compatibility with emerging novel approaches. Our goal is to bridge SD with contemporary ecological modeling practices by systematically reviewing the theoretical and practical advances of SD. This review provides insights for scholars and practitioners seeking to embed SD approach to the environmental and ecological systems simulation.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"506 ","pages":"Article 111135"},"PeriodicalIF":2.6000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380025001206","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
System Dynamics (SD) has emerged as a fundamental and powerful modeling methodology for understanding and simulating the behavior of both natural and social-economic systems. This review explores the historical development, key concepts, and broad applications of SD as a fundamental modeling approach. Tracing its evolution from the its inception since 1960s, the paper outlines the four major phases of SD's growth, from its initial conceptualization, through its methodological refinements, to its widespread application in ecosystems, and socio-economic systems in recent over the half century. The review highlights the development of SD communities across the globe, including the North American school, European clusters, and the growing body of work in China, and the progress in the global collaboration. We discuss and organize the foundational paired concepts of SD, including stock-flow relationships, the structure-behavior paradigm, the cause-effect process, and the loop-feedback paradigm. We summarize the SD modeling workflow protocol in the four stages, as conceptualization, visualization, quantification, and verification. It demonstrates good practices of SD modeling in various ecological contexts, spanning population, community, landscape, and macro-ecosystem levels, while emphasizing the method's adaptability and capacity for spatial modeling. Building on an extensive literature review and bibliometric analysis, the paper synthesizes key progress in SD modeling while offering insights into future perspectives and potential advancements. It concludes by reflecting on SD's ability to address multi-scale, multi-dimensional challenges and its compatibility with emerging novel approaches. Our goal is to bridge SD with contemporary ecological modeling practices by systematically reviewing the theoretical and practical advances of SD. This review provides insights for scholars and practitioners seeking to embed SD approach to the environmental and ecological systems simulation.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).