School of Environmental Sciences, University of Guelph, Guelph, Canada.
Department of Applied Mathematics, University of Waterloo, Waterloo, Canada.
Philos Trans R Soc Lond B Biol Sci. 2022 Aug 15;377(1857):20210382. doi: 10.1098/rstb.2021.0382. Epub 2022 Jun 27.
Humans and the environment form a single complex system where humans not only influence ecosystems but also react to them. Despite this, there are far fewer coupled human-environment system (CHES) mathematical models than models of uncoupled ecosystems. We argue that these coupled models are essential to understand the impacts of social interventions and their potential to avoid catastrophic environmental events and support sustainable trajectories on multi-decadal timescales. A brief history of CHES modelling is presented, followed by a review spanning recent CHES models of systems including forests and land use, coral reefs and fishing and climate change mitigation. The ability of CHES modelling to capture dynamic two-way feedback confers advantages, such as the ability to represent ecosystem dynamics more realistically at longer timescales, and allowing insights that cannot be generated using ecological models. We discuss examples of such key insights from recent research. However, this strength brings with it challenges of model complexity and tractability, and the need for appropriate data to parameterize and validate CHES models. Finally, we suggest opportunities for CHES models to improve human-environment sustainability in future research spanning topics such as natural disturbances, social structure, social media data, model discovery and early warning signals. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.
人类和环境形成了一个单一的复杂系统,在这个系统中,人类不仅影响生态系统,而且对生态系统也有反应。尽管如此,耦合的人类-环境系统(CHES)数学模型比非耦合生态系统模型要少得多。我们认为,这些耦合模型对于理解社会干预的影响及其避免灾难性环境事件和支持可持续轨迹的潜力至关重要,可持续轨迹的时间跨度可达数十年。本文简要介绍了 CHES 建模的历史,随后对包括森林和土地利用、珊瑚礁和渔业以及气候变化缓解在内的系统的最新 CHES 模型进行了回顾。CHES 建模捕捉动态双向反馈的能力带来了优势,例如能够在更长的时间尺度上更真实地表示生态系统动态,并允许使用生态模型无法生成的见解。我们讨论了最近研究中此类关键见解的示例。然而,这种优势带来了模型复杂性和可处理性的挑战,以及需要适当的数据来参数化和验证 CHES 模型。最后,我们提出了在未来研究中利用 CHES 模型改善人类-环境可持续性的机会,涵盖了自然干扰、社会结构、社交媒体数据、模型发现和预警信号等主题。本文是“生态复杂性和生物圈:未来 30 年”主题特刊的一部分。