Cross-scale analysis of social-ecological systems: Policy options appraisal for delivering NetZero and other environmental objectives in Scotland

K. Matthews, K. Blackstock, H. Wardell-Johnson, D. Miller, M. Tavana, S. Thomson, A. Moxey, R. Nielson, N. Baggaley, K. Loades, E. Paterson, R. Pakeman, C. Hawes, J. Stockan, M. Stutter, S. Addy, M. Wilkinson
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Conducting policy-options appraisals is increasingly seen as a transdisciplinary research-policy endeavour with researchers engaging policy actors in an extended peer community (post-normal science). This paper presents a case study of analysis undertaken with researchers, policy analysts, policy makers and other stakeholders to support decisions on how to implement future agriculture support in Scotland, so that the policy programme better delivers across social, economic and environmental objectives. The key change being considered in the future agricultural support programme is Enhanced Conditionality (EC) where the level of financial support provided to farm-businesses will depend on their undertaking agri-environmental measures that deliver against the key priorities of reducing greenhouse gas emissions and reversing biodiversity losses. The paper outlines the policy context within which the EC options appraisal takes place – highlighting how EC is a crucial component in making the wider suite of policy measures work. The transdisciplinary approach, Quantitative Story Telling (QST) is presented, emerging from decision support, participatory research, and post-normal science for policy domains. The stages of QST highlight the importance of analysis that underpins any quantification (decision on how issues are framed and what it included in the analysis) and the expectation that research outputs with be deliberated on with, and interpreted from, stakeholder perspectives. The project specific analyses are outlined, combining top-down options appraisal of how macro-policy decisions could constrain EC and bottom-up analysis of potential uptake and effectiveness of EC measures, undertaken in inter-disciplinary workshops with domain experts from biodiversity, soils and waters. The paper highlights challenges for implementation and evaluation at meso-scale with interactions between farm-businesses and catchment, landscape and regional objectives. The conclusions of the analysis, in policy terms, are that EC presents an opportunity to significantly realign how agricultural land management is conducted in Scotland, so that it is more effective in delivering climate change and biodiversity objectives, but there are formidable challenges in resolving the policy “sudoku”. Meso-scale issues are likely to mean the need to integrate alternative modelling paradigms such as spatial, empirical agent-based modelling (ABM) into policy option appraisals. By taking multi-scale, social-ecological systems perspectives on EC it has been possible to identify key policy decisions at a range of scales on which the success of EC will depend, to have a realistic understanding of how effective the EC measures might be in heterogenous Scottish environments and what are the likely barriers to uptake. The analysis also highlighted where outcomes of the policy change are likely to be challenging to monitor-evaluate; and where there are dependencies between farm-businesses that mean EC measures need to be supplemented with mechanisms that (1) promote cooperation between land managers and (2) identify and respond to agreed local priorities. The value of the participatory QST process was in making sure the analyses being undertaken were salient and the outputs seen as credible – but the challenges of interpreting necessarily complex outputs remain. 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Abstract

: Public policy confronts complex, contested, wicked problems such as climate and biodiversity crises with challenges of how issues are framed, analysed, codified, and interpreted. Social-ecological systems provide an analytical framework that couples the biosphere and technosphere, recognising biophysical limits and emphasising the importance of critical reflection within policy decision-making. Conducting policy-options appraisals is increasingly seen as a transdisciplinary research-policy endeavour with researchers engaging policy actors in an extended peer community (post-normal science). This paper presents a case study of analysis undertaken with researchers, policy analysts, policy makers and other stakeholders to support decisions on how to implement future agriculture support in Scotland, so that the policy programme better delivers across social, economic and environmental objectives. The key change being considered in the future agricultural support programme is Enhanced Conditionality (EC) where the level of financial support provided to farm-businesses will depend on their undertaking agri-environmental measures that deliver against the key priorities of reducing greenhouse gas emissions and reversing biodiversity losses. The paper outlines the policy context within which the EC options appraisal takes place – highlighting how EC is a crucial component in making the wider suite of policy measures work. The transdisciplinary approach, Quantitative Story Telling (QST) is presented, emerging from decision support, participatory research, and post-normal science for policy domains. The stages of QST highlight the importance of analysis that underpins any quantification (decision on how issues are framed and what it included in the analysis) and the expectation that research outputs with be deliberated on with, and interpreted from, stakeholder perspectives. The project specific analyses are outlined, combining top-down options appraisal of how macro-policy decisions could constrain EC and bottom-up analysis of potential uptake and effectiveness of EC measures, undertaken in inter-disciplinary workshops with domain experts from biodiversity, soils and waters. The paper highlights challenges for implementation and evaluation at meso-scale with interactions between farm-businesses and catchment, landscape and regional objectives. The conclusions of the analysis, in policy terms, are that EC presents an opportunity to significantly realign how agricultural land management is conducted in Scotland, so that it is more effective in delivering climate change and biodiversity objectives, but there are formidable challenges in resolving the policy “sudoku”. Meso-scale issues are likely to mean the need to integrate alternative modelling paradigms such as spatial, empirical agent-based modelling (ABM) into policy option appraisals. By taking multi-scale, social-ecological systems perspectives on EC it has been possible to identify key policy decisions at a range of scales on which the success of EC will depend, to have a realistic understanding of how effective the EC measures might be in heterogenous Scottish environments and what are the likely barriers to uptake. The analysis also highlighted where outcomes of the policy change are likely to be challenging to monitor-evaluate; and where there are dependencies between farm-businesses that mean EC measures need to be supplemented with mechanisms that (1) promote cooperation between land managers and (2) identify and respond to agreed local priorities. The value of the participatory QST process was in making sure the analyses being undertaken were salient and the outputs seen as credible – but the challenges of interpreting necessarily complex outputs remain. The greatest value of QST may be that it provides a structured way to navigate complexity with policy makers rather than seeking to control or eliminate it.
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社会生态系统的跨尺度分析:在苏格兰实现NetZero和其他环境目标的政策选择评估
公共政策面临着复杂的、有争议的、邪恶的问题,如气候和生物多样性危机,以及如何构建、分析、编纂和解释这些问题的挑战。社会生态系统提供了一个分析框架,将生物圈和技术圈结合起来,认识到生物物理的限制,并强调在决策过程中进行批判性反思的重要性。开展政策选择评估越来越被视为一项跨学科的研究政策工作,研究人员与扩大的同行社区(后常态科学)中的政策行为者进行接触。本文介绍了与研究人员、政策分析师、政策制定者和其他利益相关者一起进行的分析案例研究,以支持如何在苏格兰实施未来农业支持的决策,从而使政策方案更好地实现社会、经济和环境目标。在未来的农业支持计划中,正在考虑的关键变化是提高条件(EC),即向农场企业提供的财政支持水平将取决于它们是否采取了农业环境措施,这些措施将有助于减少温室气体排放和扭转生物多样性丧失的关键优先事项。该文件概述了进行EC选择评估的政策背景,强调了EC如何成为使更广泛的政策措施发挥作用的关键组成部分。提出了跨学科的方法,定量故事讲述(QST),从决策支持,参与性研究和政策领域的后常态科学中出现。QST的各个阶段强调了分析的重要性,这是任何量化的基础(决定问题是如何构建的,以及分析中包括什么),以及对研究成果进行审议的期望,并从利益相关者的角度进行解释。在与生物多样性、土壤和水领域专家的跨学科研讨会上,概述了项目的具体分析,结合对宏观政策决定如何限制生态环境的自上而下的选择评估和对生态环境措施的潜在吸收和有效性的自下而上的分析。本文强调了在中尺度实施和评估的挑战,以及农场企业与流域、景观和区域目标之间的相互作用。在政策方面,分析的结论是,EC提供了一个机会,可以显着重新调整苏格兰的农业用地管理方式,以便更有效地实现气候变化和生物多样性目标,但在解决政策“数独”方面存在巨大挑战。中尺度问题可能意味着需要将空间、经验主体建模(ABM)等替代建模范式整合到政策选择评估中。通过对欧共体采取多尺度、社会生态系统的观点,有可能确定欧共体成功所依赖的一系列尺度上的关键政策决定,对欧共体措施在苏格兰异质环境中的有效性有一个现实的理解,以及采取欧共体措施的可能障碍是什么。分析还强调了政策变化的结果可能难以监测和评估的地方;以及在农场和企业之间存在依赖关系的地方,这意味着欧共体措施需要辅以以下机制:(1)促进土地管理者之间的合作;(2)确定和响应商定的地方优先事项。参与性QST过程的价值在于确保正在进行的分析是突出的,产出是可信的——但解释必然复杂的产出的挑战仍然存在。QST的最大价值可能是它提供了一种结构化的方法来与政策制定者一起导航复杂性,而不是寻求控制或消除复杂性。
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