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Eight grand challenges in socio-environmental systems modeling
Open accessAbstract
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.
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“Modeling, regardless of improvements, may simply be incapable of capturing rare tipping-points and is not intended to accurately predict or foresee non-rational political dynamics (Elsawah et al., 2020).”
From A Fate Worse Than Warming? Stratospheric Aerosol Injection and Global Catastrophic Risk (2021) · cites this paper as Elsawah et al., 2020
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Metadata
- Authors
- Elsawah, S., Filatova, T., Jakeman, A. J., Kettner, A. J., Zellner, M. L., Athanasiadis, I. N., Hamilton, S. H., Axtell, R. L., Brown, D. G., Gilligan, J. M., Janssen, M. A., Robinson, D. T., Rozenberg, J., Ullah, I. I. T., & Lade, S. J.
- Affiliations
- UNSW Sydney (AU)
- University of Twente (NL)
- Australian National University (AU)
- University of Illinois Chicago (US)
- Wageningen University & Research (NL)
- Edith Cowan University (AU)
- George Mason University (US)
- University of Washington (US)
- Vanderbilt University (US)
- Arizona State University (US)
- University of Waterloo (CA)
- World Bank (US)
- San Diego State University (US)
- ORCID
- Venue
- Socio-Environmental Systems Modelling
- Publisher
- Wageningen University and Research
- Published
- 2020-01-01
- Volume
- 2
- Pages
- 16226
- ISSN
- 2663-3027 (ISSN-L)
- OpenAlex
- W2970509049
- Cited by
- 205
- References
- 244
- Citations by year
- 2026: 17 · 2025: 26 · 2024: 32 · 2023: 38 · 2022: 35 · 2021: 31 · 2020: 25
- FWCI
- 16.40
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Socio-Environmental Systems Modeling (publishedVersion, other-oa)
- Socio-Environmental Systems Modeling (acceptedVersion, cc-by-nc)
- OPUS - Open Publications of UTS Scholars (University of Technology Sydney) (submittedVersion, other-oa)
- University of Twente Research Information (submittedVersion, other-oa)
- ANU Open Research (Australian National University) (submittedVersion, cc-by-nc)
- University of Twente Research Information (submittedVersion, cc-by-nc)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by-nc)
- Funders
- National Science Foundation (1052875, 0621695)
- National Socio-Environmental Synthesis Center (1052875, DBI—1052875)
- Svenska Forskningsrådet Formas (2014-589)
- Vetenskapsrådet
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Complex Systems and Decision Making
- Physical Sciences › Environmental Science › Global and Planetary Change › Sustainability and Climate Change Governance
- Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
- Keywords
- societal challenges, uncertainty analysis, scaling, qualitative-quantitative integration, policy adoption, structural change, human dimension, new data sources, stakeholder engagement, social learning, decision support
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