Socio-Environmental Systems Modelling最新文献

{"title":"Upscaling in socio-environmental systems modelling: Current challenges, promising strategies and insights from ecology","authors":"G. Dressler, J. Groeneveld, Jessica Hetzer, Anja Janischewski, Henning Nolzen, E. Rödig, Nina Schwarz, Franziska Taubert, Jule Thober, Meike Will, T. Williams, S. Wirth, B. Müller","doi":"10.18174/sesmo.18112","DOIUrl":"https://doi.org/10.18174/sesmo.18112","url":null,"abstract":"Sustainability challenges in socio-environmental systems (SES) are inherently multiscale, with global-level changes emerging from socio-environmental processes that operate across different spatial, temporal, and organisational scales. Models of SES therefore need to incorporate multiple scales, which requires sound methodologies for transferring information between scales. Due to the increasing global connectivity of SES, upscaling – increasing the extent or decreasing the resolution of a modelling study – is becoming progressively more important. However, upscaling in SES models has received less attention than in other fields (e.g., ecology or hydrology) and therefore remains a pressing challenge. To advance the understanding of upscaling in SES, we take three steps. First, we review existing upscaling approaches in SES as well as other disciplines. Second, we identify four main challenges that are particularly relevant to upscaling in SES: 1) heterogeneity, 2) interactions, 3) learning and adaptation, and 4) emergent phenomena. Third, we present an approach that facilitates the transfer of existing upscaling methods to SES, using two good practice examples from ecology. To describe and compare these methods, we propose a scheme of five general upscaling strategies. This scheme builds upon and unifies existing schemes and provides a standardised way to classify and represent existing as well as new upscaling methods. We demonstrate how the scheme can help to transparently present upscaling methods and uncover scaling assumptions, as well as to identify limits for the transfer of upscaling methods. We finish by pointing out research avenues on upscaling in SES to address the identified upscaling challenges.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115743863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"18 Politically relevant solar geoengineering scenarios","authors":"A. Lockley, Yangyang Xu, S. Tilmes, M. Sugiyama, D. Rothman, Adrian Hindes","doi":"10.18174/sesmo.18127","DOIUrl":"https://doi.org/10.18174/sesmo.18127","url":null,"abstract":"Solar geoengineering, also known as Solar Radiation Modification (SRM), has been proposed to alter Earth’s radiative balance to reduce the effects of anthropogenic climate change. SRM has been identified as a research priority, as it has been shown to effectively reduce surface temperatures, while substantial uncertainties remain around side effects and impacts. Global modeling studies of SRM have often relied on idealized scenarios to understand the physical processes of interventions and their widespread impacts. These extreme or idealized scenarios are not directly policy-relevant and are often physically implausible (such as imposing global solar reduction to counter the warming of an instantaneous quadrupling of CO2). The climatic and ecological impacts of politically relevant and potentially plausible SRM approaches have rarely been modeled and assessed. Nevertheless, commentators and policymakers often falsely assume that idealized or extreme scenarios are proposed solutions to climate change. This paper proposes 18 scenarios that appear to be broadly plausible from political and Earth System perspectives and encompass futures that could be both warnings or perhaps desirable. We place these scenarios into four groups following broader strategic contexts: (1) Global Management; (2) Regional Emergencies; (3) Coordinated Regional Interventions; and (4) Reactive Global Interventions. For each scenario, relevant model experiments are proposed. Some may be performed with existing setups of global climate models, while others require further specification. Developing and performing these model experiments – and assessing likely resulting impacts on society and ecosystems – would be essential to inform public debate and policymakers on the real-world issues surrounding SRM.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130945467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses","authors":"T. Iwanaga, W. Usher, Jon Herman","doi":"10.18174/sesmo.18155","DOIUrl":"https://doi.org/10.18174/sesmo.18155","url":null,"abstract":"Sensitivity analysis is now considered a standard practice in environmental modeling. Several open-source libraries, such as the Sensitivity Analysis Library (SALib), have been published in the recent past aimed at simplifying the application of sensitivity analyses. Still, there remain issues in software usability and accessibility, as well as a lack of guidance in the interpretation of sensitivity analysis results. This paper describes the changes made and planned to SALib to advance the ease with which modelers may conduct sensitivity analysis and interpret results. We further offer our perspectives from the past 7 years of maintaining SALib for the consideration of those aspiring to launch their own software for sensitivity analysis, develop methodology, or those otherwise interested in becoming involved in a project like SALib. These include the value of a community of practice to foster best practices for sensitivity analysis, the potential for collaboration across different software (for sensitivity analysis) platforms, and the need to specifically support the software development that underpins computational science.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124807489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a global behavioural model of anthropogenic fire: The spatiotemporal distribution of land-fire systems","authors":"Oliver Perkins, Sarah Matej, K. Erb, J. Millington","doi":"10.18174/sesmo.18130","DOIUrl":"https://doi.org/10.18174/sesmo.18130","url":null,"abstract":"Landscape fire regimes are created through socio-ecological processes, yet in current global models the representation of anthropogenic impacts on fire regimes is restricted to simplistic functions derived from coarse measures such as GDP and population density. As a result, fire-enabled dynamic global vegetation models (DGVMs) have limited ability to reproduce observed patterns of fire, and limited prognostic value. At the heart of this challenge is a failure to represent human agency and decision-making related to fire. This paper outlines progress towards a global behavioural model that captures the categorical differences in human fire use and management that arise from diverse land use objectives under varying socio-ecological contexts. We present a modelled global spatiotemporal distribution of what we term ‘land-fire systems’ (LFSs), a classification that combines land use systems and anthropogenic fire regimes. Our model simulates competition between LFSs with a novel bootstrapped classification tree approach that performs favourably against reference multinomial regressions. We evaluate model outputs with the human appropriation of net primary production (HANPP) framework and find good overall agreement. We discuss limitations to our methods, as well as remaining challenges to the integration of behavioural modelling in DGVMs and associated model-intercomparison protocols.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131033853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perspectives on confronting issues of scale in systems modeling","authors":"T. Iwanaga, Patrick Steinmann, Amir Sadoddin, Derek Robinson, Val Snow, V. Grimm, Hsiao-Hsuan Wang","doi":"10.18174/sesmo.18156","DOIUrl":"https://doi.org/10.18174/sesmo.18156","url":null,"abstract":"Issues of scale pervade every aspect of socio-environmental systems (SES) modeling. They can stem from the context of both the modeling process, and the purpose of the integrated model. A webinar hosted by the National Socio-Environmental Synthesis Center (SESYNC), The Integrated Assessment Society (TIAS) and the journal Socio-Environmental Systems Modelling (SESMO) explored how model stakeholders can address issues of scale. Four key considerations were raised: (1) being aware of our influence on the modeling pathway, and developing a shared language to overcome cross-disciplinary communication barriers; (2) that localized effects may aggregate to influence behavior at larger scales, necessitating the consideration of multiple scales; (3) that these effects are “patterns” that can be elicited to capture understanding of a system (of systems); and (4) recognition that the scales must be relevant to the involved stakeholders and decision makers. Key references in these four areas of consideration are presented to complement the discussion of confronting scale as a grand challenge in socio-environmental modeling. By considering these aspects within the integrated modeling process, we are better able to confront the issues of scale in socio-environmental modeling.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114843153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RICE50+: DICE model at country and regional level","authors":"Paolo Gazzotti","doi":"10.18174/sesmo.18038","DOIUrl":"https://doi.org/10.18174/sesmo.18038","url":null,"abstract":"Benefit-cost Integrated Assessment Models (IAMs) have been largely used for optimal policies and mitigation pathways countering climate change. However, the available models are relatively limited in the representation of regional heterogeneity. This is despite strong evidence of significant variation of local mitigation costs and benefits, institutional capacity, environmental and economic priorities. Here, I introduce RICE50+, a benefit-cost optimizing IAM with more than 50 independently deciding regions or countries. Its core foundation is the DICE model, improved with several original contributions. These include new calibrations on actual mitigation cost data, full integration of recent empirically based impact functions, alternative socioeconomic reference projections as well as normative preferences, including welfare specifications explicitly featuring inequality aversion. Due to its high level of regional detail, the model can support researchers in better investigating the role of heterogeneity in international cooperation, cross-country inequalities, and climate change impacts under a variety of mitigation pathways and scenarios.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128715366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergising decision making and interventions across human health and environment: concepts for designing a model for infectious diseases","authors":"J. Stanhope, H. Mayfield, J. Guillaume, O. Sahin, P. Weinstein, C. Lau","doi":"10.18174/sesmo.18126","DOIUrl":"https://doi.org/10.18174/sesmo.18126","url":null,"abstract":"The impact of environmental factors on human health outcomes is well established. It is therefore not surprising that interventions aimed at improving human health are often environmental-based, such as restoring riparian vegetation for flood mitigation, with a view to reducing associated infectious disease transmission. Yet the risks and benefits of these interventions on the environment itself are rarely measured, or weighed up against potential health gains. One of the challenges with such an evaluation is the requirement for cross-sectoral support from decision makers in both the health and environmental sectors. To facilitate this support, cross-sectoral models are required that simultaneously estimate the impact of proposed environmental interventions on both sectors. Despite their obvious value, a systematic search of the peer-reviewed literature did not identify any model that concurrently models the impact of environmental intervention on both environmental and human infectious disease related outcomes. In this paper, we conceptually explore potential approaches for designing such a model, using leptospirosis as a case study to highlight the various data sources, spatial scales, temporal scales and required system behaviour that would need to be integrated for a cross-sectoral model of this complexity. By comparing these system requirements against the strengths and limitations of individual modelling techniques, we demonstrate the potential benefits of a hybrid-ensemble approach that uses component models from different frameworks.  By combining the strengths of the different techniques to tackle this wicked problem, such a modelling approach supports the prioritisation of environmental interventions that optimise the overall benefit by considering impacts on both human health and the environment.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129421205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Containerization for creating reusable model code","authors":"Manuela Vanegas Ferro, Allen Lee, C. Pritchard, C. Barton, M. Janssen","doi":"10.18174/sesmo.18074","DOIUrl":"https://doi.org/10.18174/sesmo.18074","url":null,"abstract":"Will you be able to run your computational models in the future? Even with well-documented code, this can be difficult due to changes in the software frameworks and operating systems that your code was built on. In this paper we discuss the use of containers to preserve code and their software dependencies to reproduce simulation results in the future. Containers are standalone lightweight packages of the original model software and their dependencies that can be run independent of the platform. As such they are suitable for reuse and sharing results. However, the use of containers is rare in the field of modeling social-environmental systems. We provide an introduction to the basic principles of containerization, argue why it would be beneficial if this tool became common practice in the field, describe a conceptual walkthrough to the process of containerizing a model, and reflect on near future directions of containerization workflows.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124199273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding smallholder farmer decision making in forest land restoration using agent-based modeling","authors":"Vianny Ahimbisibwe, J. Groeneveld, Melvin Lippe, S. Tumwebaze, E. Auch, Uta Berger","doi":"10.18174/sesmo.2021a18036","DOIUrl":"https://doi.org/10.18174/sesmo.2021a18036","url":null,"abstract":"Success of forest restoration at farm level depends on the farmer´s decision-making and the constraints to farmers’ actions. There is a gap between the intentions and the actual behavior towards restoration in Sub-Saharan Africa and the Global South. To understand this discrepancy, our study uses empirical household survey data to design and parameterize an agent-based model. WEEM (Woodlot Establishment and Expansion Model) has been designed based on household socio-demographics and projects the temporal dynamics of woodlot numbers in Uganda. The study contributes to a mechanistic understanding of what determines the current gap between farmer’s intention and actual behavior. Results reveal that an increase in knowledge of the current forest policies laws and regulations (PLRs) from 18% to 50% and to 100% reduces the average number of woodlots by 18% and 79% respectively. Lack of labor reduces the number of woodlots by 80%. Increased labor requirement from 4 to 8 and to 12 man-days, reduces the number of woodlots by 26% and 61% respectively. WEEM indicates that absence of household labor and de facto misconception of PLRs “perceived tenure insecurity” constrains the actual behavior of farmers. We recommend forest PLRs to provide full rights of use and ownership of trees established on private farmland. Tree fund in the case of Uganda should be operationalized to address the transaction costs and  to achieve the long-term targets of forest land restoration.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127836097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An agent-based model to support community forest management and non-timber forest product harvesting in northern Thailand","authors":"Wuthiwong Wimolsakcharoen, P. Dumrongrojwatthana, C. Page, François Bousquet, G. Trébuil","doi":"10.18174/SESMO.2021A17894","DOIUrl":"https://doi.org/10.18174/SESMO.2021A17894","url":null,"abstract":"Agent-based models are popular in common-pool resource management to represent complex systems and stimulate collective action and management, where they are used to evaluate scenarios of stakeholders’ choice in participatory simulations. We developed the “CoComForest” (COllaborative COMmunity FOREST management) model to support community forest management (CFM) and non-timber forest product (NTFP) harvesting in Nan Province, northern Thailand. The model was used as a computer-based role-playing game to support sharing of perceptions and knowledge among stakeholders, and in participatory simulations to explore future CFM scenarios. The Unified Modelling Language was used to build the conceptual model, subsequently implemented under the CORMAS (COmmon-pool Resource and Multi-Agent System) simulation platform. Several tests were conducted in the laboratory for verification and calibration before using this tool with 21 diverse stakeholders during a field workshop. Three different participatory gaming and simulation sessions were organized. The first one focused on the co-validation of the model with participants. They accepted most of the model functionalities and the scheduling of the rounds of play. The model was used in the subsequent two sessions to simulate the scenarios of firebreak establishment and introduction of outsiders intensively harvesting NTFPs, respectively. The results showed that the intensive harvesting practices of outsiders accelerated the depletion of resources, whereas the prevention of wildfire by establishing firebreaks could increase the resource availability in the landscape. The debriefing session at the end of the workshop focused on the analysis of simulation results and the relationships between the players’ decision-making and their actual circumstances. Individual in-depth interviews conducted after the workshop helped to evaluate the use of this model with local stakeholders. Most participants considered the model as a useful common representation of the system they manage collectively. Its use in participatory simulations facilitated communication among the stakeholders searching for an adapted and acceptable collective action plan to improve CFM at the sub-district level in order to prevent the overharvesting of NTFPs by outsiders.","PeriodicalId":166291,"journal":{"name":"Socio-Environmental Systems Modelling","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129030120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}