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
{"title":"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","authors":"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","doi":"10.36334/modsim.2023.matthews","DOIUrl":null,"url":null,"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.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cross-scale analysis of social-ecological systems: Policy options appraisal for delivering NetZero and other environmental objectives in Scotland\",\"authors\":\"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\",\"doi\":\"10.36334/modsim.2023.matthews\",\"DOIUrl\":null,\"url\":null,\"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. 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Cross-scale analysis of social-ecological systems: Policy options appraisal for delivering NetZero and other environmental objectives in Scotland
: 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.