https://sesmo.org/issue/feed Socio-Environmental Systems Modelling 2020-05-14T17:23:08+02:00 Ioannis N. Athanasiadis ioannis.athanasiadis@wur.nl Open Journal Systems <p><em>SESMO seeks to transform society and socio-environmental decision making through model-based research that integrates multiple issues, domain expertise and interest groups&nbsp;</em></p> https://sesmo.org/article/view/16226 Eight grand challenges in socio-environmental systems modeling 2019-11-05T10:17:54+01:00 Sondoss Elsawah s.elsawah@unsw.edu.au Tatiana Filatova vieenigme@gmail.com Anthony J. Jakeman tony.jakeman@anu.edu.au Albert J. Kettner albert.kettner@gmail.com Moira L. Zellner mzellner@uic.edu Ioannis N. Athanasiadis ioannis.athanasiadis@wur.nl Serena H. Hamilton s.hamilton@ecu.edu.au Robert L. Axtell rax222@gmu.edu Daniel G. Brown danbro@uw.edu Jonathan M. Gilligan jonathan.gilligan@vanderbilt.edu Marco A. Janssen Marco.Janssen@asu.edu Derek T. Robinson derekthomasrobinson@gmail.com Julie Rozenberg jrozenberg@worldbank.org Isaac I. T. Ullah isaaciullah@gmail.com Steve J. Lade steven.lade@su.se <p style="margin: 0px 0px 10.66px; border: medium;"><span style="margin: 0px; color: black; font-size: 12pt;" lang="EN-US">Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices.</span></p> 2020-01-01T00:00:00+01:00 Copyright (c) 2020 Sondoss Elsawah, Tatiana Filatova, Anthony J. Jakeman, Albert J. Kettner, Moira L. Zellner, Ioannis N. Athanasiadis, Serena H. Hamilton, Robert L. Axtell, Daniel G. Brown, Jonathan M. Gilligan, Marco A. Janssen, Derek T. Robinson, Julie Rozenberg, Isaac I. T. Ullah, Steve J. Lade https://sesmo.org/article/view/16312 Contrasting stakeholder and scientist conceptual models of food-energy-water systems: a case study in Magic Valley, Southern Idaho 2019-10-22T15:10:08+02:00 Grace B. Villamor gracev@uni-bonn.de David L. Griffith griffith@uidaho.edu Andrew Kliskey akliskey@uidaho.edu Lilian Alessa alessa@uidaho.edu <p>One of the factors for the success of simulation studies is close collaboration with stakeholders in developing a conceptual model. Conceptual models are a useful tool for communicating and understanding how real systems work. However, models or frameworks that are not aligned with the perceptions and understanding of local stakeholders can induce uncertainties in the model outcomes. We focus on two sources of epistemic uncertainty in building conceptual models of food-energy-water systems (FEWS): (1) context and framing; and (2) model structure uncertainty. To address these uncertainties, we co-produced a FEWS conceptual model with key stakeholders using the Actor-Resources-Dynamics-Interaction (ARDI) method. The method was adopted to specifically integrate public (and local) knowledge of stakeholders in the Magic Valley region of Southern Idaho into a FEWS model. We first used the ARDI method with scientists and modellers (from various disciplines) conducting research in the system, and then repeated the process with local stakeholders. We compared results from the two cohorts and refined the conceptual model to align with local stakeholders’ understanding of the FEWS. This co-development of a conceptual model with local stakeholders ensured the incorporation of different perspectives and types of knowledge of key actors within the socio-ecological systems models.</p> 2019-10-22T00:00:00+02:00 Copyright (c) 2019 Grace Villamor, David L Griffith, Andrew Kliskey, Lilian Alessa https://sesmo.org/article/view/16325 Combining social network analysis and agent-based modelling to explore dynamics of human interaction: A review 2020-03-18T10:33:39+01:00 Meike Will meike.will@ufz.de Jürgen Groeneveld juergen.groeneveld@tu-dresden.de Karin Frank karin.frank@ufz.de Birgit Müller birgit.mueller@ufz.de <p>Agent-based modelling (ABM) and social network analysis (SNA) are both valuable tools for exploring the impact of human interactions on a broad range of social and ecological patterns. Integrating these approaches offers unique opportunities to gain insights into human behaviour that neither the evaluation of social networks nor agent-based models alone can provide. There are many intriguing examples that demonstrate this potential, for instance in epidemiology, marketing or social dynamics. Based on an extensive literature review, we provide an overview on coupling ABM with SNA and evaluating the integrated approach. Building on this, we identify current shortcomings in the combination of the two methods. The greatest room for improvement is found with regard to (i) the consideration of the concept of social integration through networks, (ii) an increased use of the co-evolutionary character of social networks and embedded agents, and (iii) a systematic and quantitative model analysis focusing on the causal relationship between the agents and the network. Furthermore, we highlight the importance of a comprehensive and clearly structured model conceptualization and documentation. We synthesize our findings in guidelines that contain the main aspects to consider when integrating social networks into agent-based models.</p> 2020-02-28T00:00:00+01:00 Copyright (c) 2020 Meike Will, Jürgen Groeneveld, Karin Frank, Birgit Müller https://sesmo.org/article/view/16227 A bricolage-style exploratory scenario analysis to manage uncertainty in socio-environmental systems modeling: investigating integrated water management options 2020-03-17T16:42:32+01:00 Baihua Fu baihua.fu@anu.edu.au Joseph H.A. Guillaume joseph.guillaume@aalto.fi Anthony J. Jakeman Tony.Jakeman@anu.edu.au Michael J. Asher michael.asher@anu.edu.au <p>Exploratory analysis, while useful in assessing the implications of model assumptions under large uncertainty, is considered at best a semi-structured activity. There is no algorithmic way for performing exploratory analysis and the existing canonical techniques have their own limitations. To overcome this, we advocate a bricolage-style exploratory scenario analysis, which can be crafted by pragmatically and strategically combining different methods and practices. Our argument is illustrated using a case study in integrated water management in the Murray-Darling Basin, Australia. Scenario ensembles are generated to investigate potential policy innovations, climate and crop market conditions, as well as the effects of uncertainties in model components and parameters. Visualizations, regression trees and marginal effect analyses are exploited to make sense of the ensemble of scenarios. The analysis includes identifying patterns within a scenario ensemble, by visualizing initial hypotheses that are informed by prior knowledge, as well as by visualizing new hypotheses based on identified influential variables. Context-specific relationships are explored by analyzing which values of drivers and management options influence outcomes. Synthesis is achieved by identifying context-specific solutions to consider as part of policy design. The process of analysis is cast as a process of finding patterns and formulating questions within the ensemble of scenarios that merit further examination, allowing end-users to make the decision as to what underlying assumptions should be accepted, and whether uncertainties have been sufficiently explored. This approach is especially advantageous when the precise intentions of management are still subject to deliberations. By describing the reasoning and steps behind a bricolage-style exploratory analysis, we hope to raise awareness of the value of sharing this kind of (common but not often documented) analysis process, and motivate further work to improve sharing of know-how about bricolage in practice.</p> 2020-03-17T02:51:12+01:00 Copyright (c) 2020 Baihua Fu, Joseph H.A. Guillaume, Anthony J Jakeman, Michael J. Asher https://sesmo.org/article/view/16343 Fuzzy cognitive mapping of Baltic Archipelago Sea food webs reveals no cliqued views of the system structure between stakeholder groups 2020-05-14T17:23:08+02:00 Laura Uusitalo Laura.Uusitalo@ymparisto.fi Susanna Jernberg susanna.jernberg@ymparisto.fi Patrik Korn patrik.korn@kolumbus.fi Riikka Puntila-Dodd riikka.puntila@ymparisto.fi Annaliina Skyttä annaliinakoskinen@gmail.com Suvi Vikström suvi.vikstrom@ymparisto.fi <p>Incorporating stakeholder views is a key element in successful environmental management, particularly if the managed system delivers cultural and provisioning ecosystem services directly to the stakeholders, or if there are conflicting views about the ecosystem functioning or its optimal management. One such system is the Archipelago Sea in the Southwestern coast of Finland. It is an area with high biodiversity, offering a range of ecosystem services, from regulating services to provisioning and cultural services. Furthermore, it is subjected to a variety of human activities ranging from eutrophication and marine transport to fishing. The management of the area is also a topic of debate, including discussions of minimum landing size of fish, seal hunting quotas, and the role of cormorants in the ecosystem. Fuzzy cognitive mapping&nbsp; offers a method to evaluate and quantitatively compare different actors’ views on ecosystem structure. The models can be compared quantitatively and simulated to illustrate how they respond to various pressure scenarios. This may reveal differences in the perceptions about what are the important interactions in the ecosystem, and how the system would respond to management measures, potentially explaining differing opinions about the best management strategy. In this work, 30 stakeholders, including policy makers, scientists, eNGOs, fisheries, and recreational users created fuzzy cognitive maps (FCMs) of the Archipelago Sea food web. We found that despite the debate about the management of the area, the stakeholders’ views about the food web structure were not clustered based on the stakeholder group, i.e. the different stakeholder groups did not have distinct ideas about the ecosystem structure. The FCM complexity did not show a pattern based on the stakeholder group either. While the general pattern of the FCMs indicated a shared view of the food web structure across most respondents, there was one map from the recreational group that stood out. The exact setup of the models varied. Across all maps, cod, perch, fishing, zooplankton, and herring were the variables having most links with the other variables.&nbsp; The simulated ecosystem responses indicated that fishing was seen as a key factor affecting food web components, while increases of salinity and oxygen levels have a positive impact on multiple ecosystem components. The value of the approach is to enable a two-way discussion about the food webs and how management of pressures may impact the components.</p> 2020-05-14T00:00:00+02:00 Copyright (c) 2020 Laura Uusitalo, Susanna Jernberg, Patrik Korn, Riikka Puntila-Dodd, Annaliina Skyttä, Suvi Vikström