The DOI matches its Crossref record; 241 of the 244 references it cites were found in a registry or an index.
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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Items 201–241 of 241
Seeing is not believing: cognitive bias and modelling in collaborative planning
Hoch, C., Zellner, M., Milz, D., Radinsky, J., & Lyons, L. (2015) · Planning Theory & Practice · doi:10.1080/14649357.2015.1045015 · Cited by 25
Vermaat, J. E., Eppink, F. V., van den Bergh, J. C. J. M., Barendregt, A., & van Belle, J. (2004) · Ecological Economics · doi:10.1016/j.ecolecon.2004.06.027 · Cited by 25
SCHIMEL, D. S., Hibbard, K. A., Costa, D., Cox, P. M., & van der LEEUW, S. (2015) · Anthropocene · doi:10.1016/j.ancene.2016.02.001 · Cited by 25
Mixed qualitative-simulation methods
Millington, J. D. A., & Wainwright, J. (2016) · Progress in Human Geography · doi:10.1177/0309132515627021 · Cited by 24
Bitterman, P., & Bennett, D. A. (2016) · Ecology and Society · doi:10.5751/es-08677-210321 · Cited by 24
Jiang, Q., Bregt, A. K., & Kooistra, L. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.10.329 · Cited by 23
National Research Council (2006) · National Academies Press eBooks · doi:10.17226/11699 · Cited by 23
Designing the Distributed Model Integration Framework – DMIF
Belete, G. F., Voinov, A. A., & Morales, J. (2017) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2017.04.003 · Cited by 21
Cost-benefit analysis of riparian protection in an eastern Canadian watershed
Trenholm, R., Lantz, V. A., Martı́nez-Espiñeira, R., & Little, S. (2013) · Journal of Environmental Management · doi:10.1016/j.jenvman.2012.11.039 · Cited by 20
Fu, B., Guillaume, J. H. A., & Jakeman, A. J. (2015) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2015.05.017 · Cited by 19
Happe, K., & Happe, K. (2005) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.24464 · Cited by 19
A Miniature Data Repository on a Raspberry Pi
Samourkasidis, A., & Athanasiadis, I. N. (2016) · Electronics · doi:10.3390/electronics6010001 · Cited by 17
Migration, Intensification, and Diversification as Adaptive Strategies
Bell, A. R., Calvo-Hernandez, C., & Oppenheimer, M. (2019) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.2019a16102 · Cited by 17
Belete, G. F., Voinov, A. A., Arto, I., Dhavala, K. K., Bulavskaya, T., Niamir, L., Moghayer, S., & Filatova, T. (2019) · Energies · doi:10.3390/en12152880 · Cited by 17
Empiricism and Agent-Based Modelling
Smajgl, A., & Barreteau, O. (2013) · Springer eBooks · doi:10.1007/978-1-4614-6134-0_1 · Cited by 16
An agent-based approach to global uncertainty and sensitivity analysis
Harp, D. R., & Vesselinov, V. V. (2011) · Computers & Geosciences · doi:10.1016/j.cageo.2011.06.025 · Cited by 15
Modelling feedbacks between human and natural processes in the land systemPreprint
Robinson, D. T., Vittorio, A. D., Alexander, P. M., et al. (2017) · doi:10.5194/esd-2017-68 · Cited by 15
Self-citationA Temporal Variant‐Invariant Validation Approach for Agent‐based Models of Landscape Dynamics
Bone, C. E., Johnson, B. R., Nielsen‐Pincus, M., Sproles, E. A., & Bolte, J. P. (2013) · Transactions in GIS · doi:10.1111/tgis.12016 · Cited by 14
Scientific data from and for the citizen
Schade, S., Tsinaraki, C., & Roglia, E. (2017) · First Monday · doi:10.5210/fm.v22i8.7842 · Cited by 14
Aguilar, L., Lalith, M., Hori, M., Ichimura, T., & Tanaka, S. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-13191-7_14 · Cited by 13
Limitations, Challenges, and Solutions to Integrating Carbon Dynamics with Land-Use Models
Evans, T. P., Robinson, D. T., & Schmitt-Harsh, M. (2013) · Cambridge University Press eBooks · doi:10.1017/cbo9780511894824.010 · Cited by 11
Behaviorally Realistic Risk Management
Fischhoff, B. (2014) · Cited by 11
Reconsidering Scale: Using Geographic Information Systems to Support Spatial Planning Conversations
Milz, D., Zellner, M., Hoch, C., Radinsky, J., Pudlock, K., & Lyons, L. (2017) · Planning Practice and Research · doi:10.1080/02697459.2017.1378979 · Cited by 11
Complexity and Uncertainty: Rethinking The Modelling Activity
Brugnach, M., Pahl‐Wostl, C., Lindenschmidt, K. E., Janssen, J., Filatova, T., Mouton, A., Holtz, G., van der Keur, P., & N. Gaber, N. (2008) · Lincoln (University of Nebraska) · Cited by 11
Participatory Complex Systems Modeling for Environmental Planning:
Zellner, M., Lyons, L., Milz, D., Shelley, J., Hoch, C., Massey, D., & Radinsky, J. (2020) · Michigan State University Press eBooks · doi:10.14321/j.ctvz9396g.14 · Cited by 10
Exploring the use of agent-based modelling in mixed methods research
Sætra, H. S. (2017) · Barataria Revista Castellano-Manchega de Ciencias Sociales · doi:10.20932/barataria.v0i22.337 · Cited by 8
Mallavarapu, A., Lyons, L., Shelley, T., Slattery, B., Minor, E., & Zellner, M. (2015) · Journal of Educational Data Mining · doi:10.5281/zenodo.3554669 · Cited by 7
Accounting for the human factor
Gilligan, J. M. (2017) · Nature Climate Change · doi:10.1038/s41558-017-0038-0 · Cited by 7
Natural Resource Management: Contributions of System Dynamics to Research, Policy and Implementation
Lane, D. C., & Kopainsky, B. (2017) · Systems Research and Behavioral Science · doi:10.1002/sres.2461 · Cited by 5
Paget, N., Bonté, B., Barreteau, O., Pigozzi, G., & Maurel, P. (2019) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.2019a16166 · Cited by 5
Impact of diverse behavioral theories on environmental management: Explorations with Daisyworld
Janssen, M. A. (2016) · Winter Simulation Conference · doi:10.1109/wsc.2016.7822217 · Cited by 5
A Model Driven Engineering Framework for Simulation Experiment Management
Chakladar, S. (2016) · Cited by 4
Jakeman, A. J., & Jakeman, J. D. (2018) · Mathematics for industry · doi:10.1007/978-981-10-7811-8_15 · Cited by 4
Uncertainty and Sensitivity in Surface Dynamics Modeling
Kettner, A. J., & Syvitski, J. P. M. (2016) · Computers & Geosciences · doi:10.1016/j.cageo.2016.03.003 · Cited by 3
Milz, D. (2015) · Figshare · Cited by 3
Impact of diverse behavioral theories on environmental management: explorations with daisyworld
Janssen, M. A. (2016) · Winter Simulation Conference · doi:10.5555/3042094.3042308 · Cited by 3
Self-citationClinical Genomics Data Use: Protecting Patients Privacy Rights
Maliapen, M. (2009) · Studies in Ethics Law and Technology · doi:10.2202/1941-6008.1080 · Cited by 2
Hybrid Systems Modelling Aided by Machine Learning with Applications in Healthcare
Elbattah, M. (2018) · ARAN (University of Galway Research Repository) (Ollscoil na Gaillimhe – University of Galway) · doi:10.13025/16000 · Cited by 2
How to Start an Environmental Software Project
Athanasiadis, I. N. (2017) · IFIP advances in information and communication technology · doi:10.1007/978-3-319-89935-0_33 · Cited by 2
Gray, S. A., Voinov, A. A., Bommel, P., Page, C. L., & Olabisi, L. S. (2016) · Agritrop (Cirad) · Cited by 2
Flagged first, then by citations
3 of the 244 references couldn’t be matched to a known paper.
Research works printed but not linked: 8
- Brown, D.G., Robinson, D.T., French, N.H.F., and B.C. Reed (eds), in Land use and the carbon cycle: Advances in Integrated Science, Management, and Policy. Cambridge University Press. Pp. 178-208.
- Ferson, S., & Sentz, K. (2016). Epistemic Uncertainty in Agent-based Modeling. In S. Freitag, R. L. Muhanna, & R. L. Mullen (Eds.), Proceedings of the 7th International Workshop of Reliable Engineering Computing: Computing with Polymorphic Uncertain Data (pp. 65-82).
- Jordan, R., Gray, S., Zellner, M., Glynn, P., Voinov, A., Hedelin, B., Sterling, E., Leong, K., Schmitt Olabisi, L., Hubacek, K., Bommel, P., BenDor, T., Jetter, A., Laursen, B., Singer, A., Giabbanelli, P., Kolagani, N., Basco Carrera, L., & Jenni, K. (2018). 12 Questions for the participatory modeling community. Earth's Future, 6(8), 1046-1057.
- Mingers, J. (2006). Philosphical foundations: critical realism. In: Mingers, J. Realising system thinking: knowledge and action in management science. Springer. pp. 11-31.
- Rasmussen, C.E., & Williams, C.K.I (2006). Gaussian Processes for Machine Learning, the MIT Press, ISBN 026218253X. http://www.gaussianprocess.org/gpml.
- Rounsevell, M. et al. (2016) Linking Earth System Dynamics and Social System Modeling. Report of the Computational Human and Earth Systems Science (CHESS) group from the Workshop: 'Linking Earth System Dynamics and Social System Modeling', 23-25 May 2016, Boulder, Colorado, USA. Retrieved from: https://csdms.colorado.edu/wiki/CHESS on August 6th, 2018.
- Schmolke, A., Thorbek, P., DeAngelis, D.L., Grimm, V. (2010). Ecological modelling supporting environmental decision making: a strategy for the future. Trends in Ecology & Evolution 25 (8), 479-486.
- Sætra, H.S., 2017. Exploring the use of agent-based modelling in mixed methods research. Barataria. Revista Castellano- Manchega de Ciencias Sociales, 22, 15-31. https://doi.org/10.20932/barataria.v0i22.337. · DOI
Cited by
Sorted by citations
The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support
Razavi, S., Jakeman, A. J., Saltelli, A., Prieur, C., Iooss, B., Borgonovo, E., Plischke, E., Piano, S. L., Iwanaga, T., Becker, W., et al. (2020) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2020.104954 · Cited by 703
Foundations of complexity economics
Arthur, W. B. (2021) · Nature Reviews Physics · doi:10.1038/s42254-020-00273-3 · Cited by 362
Chen, M., Voinov, A. A., Ames, D. P., Kettner, A. J., Goodall, J. L., Jakeman, A. J., Barton, C. M., Harpham, Q., Cuddy, S., DeLuca, C., et al. (2020) · Earth-Science Reviews · doi:10.1016/j.earscirev.2020.103223 · Cited by 138
Elsawah, S., Hamilton, S. H., Jakeman, A. J., Rothman, D. S., Schweizer, V. J., Trutnevyte, E., Carlsen, H., Drakes, C., Frame, B., Fu, B., et al. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.138393 · Cited by 145
Coastal and Marine Socio-Ecological Systems: A Systematic Review of the Literature
Refulio-Coronado, S., LaCasse, K. M., Dalton, T. M., Humphries, A. T., Basu, S., Uchida, H., & Uchida, E. (2021) · Frontiers in Marine Science · doi:10.3389/fmars.2021.648006 · Cited by 149
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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