Linking model design and application for transdisciplinary approaches in social-ecological systems
Linking model design and application for transdisciplinary approaches in social-ecological systems
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将社会生态系统中跨学科方法的模型设计和应用联系起来
DOI：
10.1016/j.gloenvcha.2020.102201
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Müller, Birgit
中科院分区：
文献类型：
--
作者：
Steger, Cara;Hirsch, Shana;Cosgrove, Chris;Inman, Sarah;Nost, Eric;Shinbrot, Xoco;Thorn, Jessica P.R.;Brown, Daniel G.;Grêt-Regamey, Adrienne;Müller, Birgit
随着全球环境变化的持续加速和加剧，科学和社会正在转向跨学科方法，以促进向可持续性的过渡。建模越来越多地被用作一种技术工具，以提高我们对社会生态系统（SES）的理解，鼓励合作和学习，并促进决策。这项研究提高了我们对如何设计和应用SES模型来应对日益严峻的全球环境变化挑战的理解，以山脉为代表系统。我们分析了74篇描述山地SES动态模型的同行评议论文，并根据模型目的、数据和模型类型、利益相关者参与程度、空间程度/分辨率等特征对其进行了评价。在我们的分析中，略多于一半的模型是参与性的，但只有21.6%的论文显示与决策者有任何直接的联系。我们发现，SES模型往往不足以代表社会数据集，很少纳入人种学数据。与利益相关者多样性缺失或未处理利益相关者多样性的情况相比，利益相关者多样性较高的条件下的建模工作往往具有更高的决策支持率。我们通过适当技术的镜头讨论我们的结果，借鉴了科学与技术研究中的边界对象和标量设备的概念。我们提出了四个指导原则，以促进SES模型作为适合跨学科应用的技术的发展：(1)增加SES模型设计和应用中利益相关者的多样性，以改善协作；(2)通过整合不同的知识和数据类型来平衡利益相关者之间的权力动态；(3)促进模型设计的灵活性；(4)弥补决策支持、学习和沟通方面的差距。创建适合跨学科应用的SES模型将需要先进的规划，增加对多样化数据和知识作用的资助和关注，以及加强跨学科的伙伴关系。高度情境化的参与式模型包含了数据和行动者的多样性，似乎有望为世界上最紧迫的环境挑战做出重大贡献。
As global environmental change continues to accelerate and intensify, science and society are turning to transdisciplinary approaches to facilitate transitions to sustainability. Modeling is increasingly used as a technological tool to improve our understanding of social-ecological systems (SES), encourage collaboration and learning, and facilitate decision-making. This study improves our understanding of how SES models are designed and applied to address the rising challenges of global environmental change, using mountains as a representative system. We analyzed 74 peer-reviewed papers describing dynamic models of mountain SES, evaluating them according to characteristics such as the model purpose, data and model type, level of stakeholder involvement, and spatial extent/resolution. Slightly more than half the models in our analysis were participatory, yet only 21.6% of papers demonstrated any direct outreach to decision makers. We found that SES models tend to under-represent social datasets, with ethnographic data rarely incorporated. Modeling efforts in conditions of higher stakeholder diversity tend to have higher rates of decision support compared to situations where stakeholder diversity is absent or not addressed. We discuss our results through the lens of appropriate technology, drawing on the concepts of boundary objects and scalar devices from Science and Technology Studies. We propose four guiding principles to facilitate the development of SES models as appropriate technology for transdisciplinary applications: (1) increase diversity of stakeholders in SES model design and application for improved collaboration; (2) balance power dynamics among stakeholders by incorporating diverse knowledge and data types; (3) promote flexibility in model design; and (4) bridge gaps in decision support, learning, and communication. Creating SES models that are appropriate technology for transdisciplinary applications will require advanced planning, increased funding for and attention to the role of diverse data and knowledge, and stronger partnerships across disciplinary divides. Highly contextualized participatory modeling that embraces diversity in both data and actors appears poised to make strong contributions to the world’s most pressing environmental challenges.
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