Environmental system dynamics: Current development and applications

• This paper provided an examination of international and historical perspectives on system dynamics modeling, with its evolution over time and regions. • We systematically summarized field development and practices in both Western and Eastern societies, based on literature from English and Chinese sources. • The comparative pairing of key concepts in system dynamics were demonstrated to highlight the multi-faceted nature of the modeling method. 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.