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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Riggins, F. J., & Mitra, S. (1990) · Choice Reviews Online · doi:10.5860/choice.27-6637 · Cited by 16,590
Mixing Qualitative and Quantitative Methods: Triangulation in Action.
Jick, T. D. (1979) · Administrative Science Quarterly · doi:10.2307/2392366 · Cited by 7,103 · cited 1×
“Mixed methods research can also provide opportunities for triangulation, in which data acquired by one method are compared against data acquired by different methods (Jick, 1979; Midgley et al., 2013).”
MethodThe Problem of Pattern and Scale in Ecology: The Robert H. MacArthur Award Lecture
Levin, S. A. (1992) · Ecology · doi:10.2307/1941447 · Cited by 6,830
Agent-based modeling: Methods and techniques for simulating human systems
Bonabeau, E. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082080899 · Cited by 4,500
Learning from television in young children
Barr, R., & Brito, N. H. (2012) · doi:10.1007/978-1- · Cited by 3,959
Coleman, J. S. 1.-1. (1990) · Cited by 3,463
O’Neill, B. C., Kriegler, E., Ebi, K. L., Kemp-Benedict, E., Riahi, K., Rothman, D. S., van Ruijven, B. J., van Vuuren, D. P., Birkmann, J., Kok, K., et al. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.01.004 · Cited by 3,359
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Doyle, T. (2017) · The Information Society · doi:10.1080/01972243.2017.1354593 · Cited by 3,111
Platt, J. R. (1964) · Science · doi:10.1126/science.146.3642.347 · Cited by 2,907
Catastrophic regime shifts in ecosystems: linking theory to observation
Scheffer, M., & Carpenter, S. R. (2003) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2003.09.002 · Cited by 2,886
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
Multisector Dynamics: Advancing the Science of Complex Adaptive Human‐Earth Systems
Reed, P. M., Hadjimichael, A., Moss, R. H., Brelsford, C. M., Burleyson, C., Cohen, S., Dyreson, A. R., Gold, D., Gupta, R. S., Keller, K. M., et al. (2022) · Earth s Future · doi:10.1029/2021ef002621 · Cited by 128
Jafino, B., Kwakkel, J., & Taebi, B. (2021) · WIREs Climate Change · doi:10.1002/wcc.721 · Cited by 90
Towards a better future for biodiversity and people: Modelling Nature Futures
Kim, H., Peterson, G., Cheung, W. W. L., Ferrier, S., Alkemade, R., Arneth, A., Kuiper, J. J., Okayasu, S., Pereira, L. M., Acosta, L. A., et al. (2023) · Global Environmental Change · doi:10.1016/j.gloenvcha.2023.102681 · Cited by 133
Future Developments in Geographical Agent‐Based Models: Challenges and Opportunities
Heppenstall, A. J., Crooks, A. T., Malleson, N., Manley, E., Ge, J., & Batty, M. (2020) · Geographical Analysis · doi:10.1111/gean.12267 · Cited by 95
Razavi, S., Hannah, D. M., ELSHORBAGY, A. A., Kumar, S. V., Marshall, L. A., SOLOMATINE, D. P., Dezfuli, A., Sadegh, M., & Famiglietti, J. S. (2022) · Hydrological Processes · doi:10.1002/hyp.14596 · Cited by 95
Obringer, R., & Nateghi, R. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.103278 · Cited by 91
Sensitivity analysis: A discipline coming of age
Saltelli, A., Jakeman, A. J., Razavi, S., & Wu, Q. (2021) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2021.105226 · Cited by 91
Zaidi, A. T., Ajibade, S.-S. M., Musa, M., & Bekun, F. V. (2023) · International Journal of Energy Economics and Policy · doi:10.32479/ijeep.14683 · Cited by 79
Aly, E. A., Elsawah, S., & Ryan, M. J. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.130803 · Cited by 72
Incorporating human behaviour into Earth system modelling
Beckage, B., Moore, F. C., & LaCasse, K. M. (2022) · Nature Human Behaviour · doi:10.1038/s41562-022-01478-5 · Cited by 80
Aman, S., Hassan, N. M., Khattak, M. N., Moustafa, M. A., Fakhri, M., & Ahmad, Z. (2021) · Sustainability · doi:10.3390/su132312998 · Cited by 68
An integral approach to address socio-ecological systems sustainability and their uncertainties
Fernández, J. M., Baños-González, I., & Selma, M. Á. E. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.144457 · Cited by 61
Five Questions to Understand Epistemology and Its Influence on Integrative Marine Research
Moon, K., Cvitanovic, C., Blackman, D. A., Scales, I. R., & Browne, N. K. (2021) · Frontiers in Marine Science · doi:10.3389/fmars.2021.574158 · Cited by 60
A Fate Worse Than Warming? Stratospheric Aerosol Injection and Global Catastrophic Risk
Tang, A., & Kemp, L. (2021) · Frontiers in Climate · doi:10.3389/fclim.2021.720312 · Cited by 58
“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).”
BackgroundUnintended consequences of climate change mitigation for African river basins
Giuliani, M., Lamontagne, J., Hejazi, M. I., Reed, P. M., & Castelletti, A. F. (2022) · Nature Climate Change · doi:10.1038/s41558-021-01262-9 · Cited by 62
How to keep it adequate: A protocol for ensuring validity in agent-based simulation
Troost, C., Huber, R., Bell, A. R., van Delden, H., Filatova, T., Le, Q. B., Lippe, M., Niamir, L., Polhill, G. J., Sun, Z., et al. (2022) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2022.105559 · Cited by 58
Nugroho, S., & Uehara, T. (2023) · Systems · doi:10.3390/systems11110530 · Cited by 52
How to make socio‐environmental modelling more useful to support policy and management?
Will, M., Dressler, G., Kreuer, D., Thulke, H., Grêt-Regamey, A., & Müller, B. (2021) · People and Nature · doi:10.1002/pan3.10207 · Cited by 31
Razavi, S., Duffy, A., Eamen, L., Jakeman, A., Jardine, T., Wheater, H., Hunt, R. J., Maier, H. R., Abdelhamed, M. S., Ghoreishi, M., et al. (2025) · Water Resources Research · doi:10.1029/2024wr038088 · Cited by 44
Chen, M., Lv, G., Zhou, C., Lin, H., Ma, Z., Yue, S., Wen, Y., Zhang, F., Wang, J., Zhu, Z., et al. (2021) · Science China Earth Sciences · doi:10.1007/s11430-020-9759-0 · Cited by 48
Villamayor‐Tomás, S., Oberlack, C., Epstein, G., Partelow, S., Roggero, M., Kellner, E., Tschopp, M., & Cox, M. E. (2020) · Current Opinion in Environmental Sustainability · doi:10.1016/j.cosust.2020.05.002 · Cited by 44
Bi, C., & Little, J. C. (2022) · Sustainable Cities and Society · doi:10.1016/j.scs.2022.103915 · Cited by 46
Wu, W., Eamen, L., Dandy, G. C., Razavi, S., Kuczera, G. A., & Maier, H. R. (2023) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2023.105777 · Cited by 48
Ding, K. J., Gilligan, J. M., Yang, Y. E., Wolski, P., & Hornberger, G. M. (2021) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2021.105573 · Cited by 43
A Serious Board Game to Analyze Socio-Ecological Dynamics towards Collaboration in Agriculture
Alegría, M. E. O., Schütze, N., & Zipper, S. C. (2020) · Sustainability · doi:10.3390/su12135301 · Cited by 42
Schlüter, M., Brelsford, C. M., Ferraro, P. J., Orach, K., Qiu, M., & Smith, M. D. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2215676120 · Cited by 45
Tracing resilience, social dynamics and behavioral change: a review of agent-based flood risk models
Taberna, A., Filatova, T., Roy, D., & Noll, B. (2020) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.2020a17938 · Cited by 45
Participatory Methods for Systems Modeling of Youth Mental Health: Implementation Protocol
Freebairn, L., Occhipinti, J., Song, Y. J. C., Skinner, A., Lawson, K. D., Lee, G. Y., Hockey, S. J., Huntley, S., & Hickie, I. B. (2022) · JMIR Research Protocols · doi:10.2196/32988 · Cited by 44
Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus
Magliocca, N. R. (2020) · Land · doi:10.3390/land9120519 · Cited by 39
Linking model design and application for transdisciplinary approaches in social-ecological systems
Steger, C., Hirsch, S. L., Cosgrove, C. L., Inman, S., Nost, E., Shinbrot, X. A., Thorn, J., Brown, D. G., Grêt‐Regamey, A., Müller, B. H., et al. (2020) · Global Environmental Change · doi:10.1016/j.gloenvcha.2020.102201 · Cited by 44
Kinnebrew, E., Shoffner, E., Farah‐Pérez, A., Mills‐Novoa, M., & Siegel, K. (2020) · Conservation Biology · doi:10.1111/cobi.13642 · Cited by 42
Schwarz, N., Dreßler, G., Frank, K., Jager, W., Janssen, M. A., Müller, B. H., Schlüter, M., Wijermans, N., & Groeneveld, J. (2020) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.2020a16340 · Cited by 40
Little, J. C., Kaaronen, R. O., Hukkinen, J., Xiao, S., Sharpee, T. O., Farid, A. M., Nilchiani, R., & Barton, C. M. (2023) · Environmental Science & Technology · doi:10.1021/acs.est.2c06203 · Cited by 40
Zellner, M. L. (2024) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2024.105063 · Cited by 38
How modelling paradigms affect simulated future land use change
Brown, C., Holman, I. P., & Rounsevell, M. (2021) · Earth System Dynamics · doi:10.5194/esd-12-211-2021 · Cited by 35
Standardizing the factors used in wind farm site suitability models: A review
Wimhurst, J. J., Nsude, C. C., & Greene, J. S. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e15903 · Cited by 33
A Typology for Characterizing Human Action in MultiSector Dynamics Models
Yoon, J., Romero‐Lankao, P., Yang, Y. E., Klassert, C. J. A., Urban, N. M., Kaiser, K. E., Keller, K. M., Yarlagadda, B., Voisin, N., Reed, P. M., et al. (2022) · Earth s Future · doi:10.1029/2021ef002641 · Cited by 35
A new academic impact metric for evaluating geographic simulation models
Xu, K., Chen, M., Kettner, A. J., Barton, C. M., Croke, B., Jakeman, A. J., Ames, D. P., Wang, H., Cuddy, S., Yue, S., et al. (2022) · International Journal of Digital Earth · doi:10.1080/17538947.2022.2138589 · Cited by 29
Amorocho‐Daza, H., Sušnik, J., van der Zaag, P., & Slinger, J. H. (2024) · Ecological Modelling · doi:10.1016/j.ecolmodel.2024.110943 · Cited by 39
AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model
Coronese, M., Occelli, M., Lamperti, F., & Andrea Roventini, B. (2023) · Ecological Economics · doi:10.1016/j.ecolecon.2023.107756 · Cited by 30
Children’s Environmental Health: A Systems Approach for Anticipating Impacts from Chemicals
Hubal, E. A. C., Reif, D. M., Slover, R., Mullikin, A., & Little, J. C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17228337 · Cited by 28
Fotopoulou, E., Mandilara, I., Zafeiropoulos, A., Laspidou, C., Adamos, G., Koundouri, P., & Papavassiliou, S. (2022) · Frontiers in Environmental Science · doi:10.3389/fenvs.2022.1003599 · Cited by 28
García-Álvarez, D., Olmedo, M. T. C., van Delden, H., Mas, J., & Paegelow, M. (2022) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2022.105411 · Cited by 27
Progress in modeling dynamic systems for sustainable development
Selin, N. E., Giang, A., & Clark, W. C. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2216656120 · Cited by 30
The human–technical–environmental systems framework for sustainability analysis
Selin, H., & Selin, N. E. (2022) · Sustainability Science · doi:10.1007/s11625-022-01177-0 · Cited by 28
Wimhurst, J. J., Greene, J. S., & Koch, J. (2023) · Applied Energy · doi:10.1016/j.apenergy.2023.121880 · Cited by 26
Bartkowski, B., Beckmann, M., Drechsler, M., Kaim, A., Liebelt, V., Müller, B. H., Witing, F., & Strauch, M. (2020) · Frontiers in Environmental Science · doi:10.3389/fenvs.2020.00103 · Cited by 30
Zhang, J., Yang, Y. E., Li, H., & Shittu, E. (2021) · Journal of Water Resources Planning and Management · doi:10.1061/(asce)wr.1943-5452.0001461 · Cited by 25
Grêt‐Regamey, A., & Fagerholm, N. (2023) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2023.104978 · Cited by 29
Iwanaga, T., Partington, D., Ticehurst, J. L., Croke, B., & Jakeman, A. J. (2020) · Journal of Hydrology Regional Studies · doi:10.1016/j.ejrh.2020.100669 · Cited by 25
From situated knowledges to situated modelling: a relational framework for simulation modelling
Klein, A., Unverzagt, K., Alba, R., Donges, J. F., Hertz, T., Krueger, T., Lindkvist, E., Martin, R., Niewöhner, J., Prawitz, H., et al. (2024) · Ecosystems and People · doi:10.1080/26395916.2024.2361706 · Cited by 40
How can social–ecological system models simulate the emergence of social–ecological crises?
Brown, C., & Rounsevell, M. (2020) · People and Nature · doi:10.1002/pan3.10167 · Cited by 26
Brugière, A., Nguyen-Ngoc, D., & Drogoul, A. (2022) · Frontiers in Applied Mathematics and Statistics · doi:10.3389/fams.2022.1020353 · Cited by 29
Wang, H., & Grant, W. E. (2020) · Ecological Modelling · doi:10.1016/j.ecolmodel.2020.109403 · Cited by 23
Visualization of causation in social-ecological systems
Banitz, T., Hertz, T., Johansson, L., Lindkvist, E. A. L., Martínez-Peña, R., Radosavljevic, S., Schlüter, M., Wennberg, K., Ylikoski, P., & Grimm, V. (2022) · Ecology and Society · doi:10.5751/es-13030-270131 · Cited by 11
Learning across disciplines in socio-environmental problem framing
Pennington, D. D., Vincent, S. G., Gosselin, D. C., & Thompson, K. (2021) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.2021a17895 · Cited by 22
Towards a better future for biodiversity and people: modelling Nature FuturesPreprint
Kim, H., Peterson, G., Cheung, W. W. L., Ferrier, S., Alkemade, R., Arneth, A., Kuiper, J. J., Okayasu, S., Pereira, L. M., Acosta, L. A., et al. (2021) · Global Environmental Change · doi:10.31235/osf.io/93sqp · Cited by 22
Towards principles and policy levers for advancing living shorelines
Jones, S., & Pippin, J. S. (2022) · Journal of Environmental Management · doi:10.1016/j.jenvman.2022.114695 · Cited by 21
Perkins, O., Matej, S., Erb, K., & Millington, J. D. A. (2022) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.18130 · Cited by 24
Disasters collide at the intersection of extreme weather and infectious diseases
Drake, J. M., Marty, É., Gandhi, K. J. K., Welch‐Devine, M., Bledsoe, B. P., Shepherd, J. M., Seymour, L., Fortuin, C. C., & Montes, C. R. (2023) · Ecology Letters · doi:10.1111/ele.14188 · Cited by 21
A Web-based geo-simulation approach integrating knowledge graph and model-services
Li, H., Zhang, C., Xiao, Z., Chen, M., Lu, D., & Liu, S. (2021) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2021.105160 · Cited by 20
Health and equity implications of individual adaptation to air pollution in a changing climate
Sparks, M. S., Farahbakhsh, I., Anand, M., Bauch, C. T., Conlon, K. C., East, J. D., Li, T., Lickley, M. J., Garcia–Menendez, F., Monier, E., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2215685121 · Cited by 19
Lin, C., Yang, Y. E., Malek, K., & Adam, J. C. (2022) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2022.105451 · Cited by 20
Past, Present, and Future of Complex Systems Theory in Archaeology
Davis, D. S. (2023) · Journal of Archaeological Research · doi:10.1007/s10814-023-09193-z · Cited by 18
Bruno, J. E., Fernández‐Giménez, M. E., & Balgopal, M. M. (2021) · Ecology and Society · doi:10.5751/es-12754-260427 · Cited by 17
An open-source platform for geospatial participatory modeling in the cloud
White, C. T., Petrášová, A., Petráš, V., Tateosian, L. G., Vukomanovic, J., Mitášová, H., & Meentemeyer, R. K. (2023) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2023.105767 · Cited by 19
Lin, C., & Yang, Y. E. (2022) · Earth s Future · doi:10.1029/2021ef002403 · Cited by 17
Modelling forests as social-ecological systems: A systematic comparison of agent-based approaches
Ekström, H., Droste, N., & Brady, M. (2024) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2024.105998 · Cited by 18
Wang, H., van Voorn, G. V., Grant, W., Zare, F., Giupponi, C., Steinmann, P., Müller, B., Elsawah, S., van Delden, H., Athanasiadis, I., et al. (2023) · Socio-Environmental Systems Modelling · doi:10.18174/sesmo.18563 · Cited by 24
Navigating causal reasoning in sustainability science
Schlüter, M., Hertz, T., García, M. M., Banitz, T., Grimm, V., Johansson, L., Lindkvist, E., Peña, R. M., Radosavljevic, S., Wennberg, K. J., et al. (2024) · AMBIO · doi:10.1007/s13280-024-02047-y · Cited by 15
van Valkengoed, A. M., Perlaviciute, G., & Steg, L. (2025) · Environmental Research Communications · doi:10.1088/2515-7620/adb9bf · Cited by 19
Magliocca, N. R., Price, A. N., Mitchell, P., Curtin, K. M., Hudnall, M., & McSweeney, K. (2022) · IISE Transactions · doi:10.1080/24725854.2022.2123998 · Cited by 15
Aly, E. A., Elsawah, S., & Ryan, M. J. (2022) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2022.105360 · Cited by 14
18 Politically relevant solar geoengineering scenarios
Lockley, A. J., Xu, Y., Tilmes, S., Sugiyama, M., Rothman, D. S., & Hindes, A. (2022) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.18127 · Cited by 16
Nel, D., & Taeihagh, A. (2024) · Policy Sciences · doi:10.1007/s11077-024-09531-y · Cited by 14
Systems engineering applied to urban planning and development: A review and research agenda
Reid, J. B., & Wood, D. R. (2022) · Systems Engineering · doi:10.1002/sys.21642 · Cited by 13
The water energy food nexus: A multi-objective optimization tool
Mansour, F., Al‐Hindi, M., Najm, M. R. A., & Yassine, A. (2024) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2024.108718 · Cited by 13
Leadership in participatory modelling – Is there a need for it?
Hämäläinen, R. P., Miliszewska, I., & Voinov, A. A. (2020) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2020.104834 · Cited by 14
Modelling Domestic Water Use in Metropolitan Areas Using Socio-Cognitive Agents
Perelló-Moragues, A., Manel Poch, A., Saurı́, D., Popartan, L. A., & Pablo Noriega, A. (2021) · Water · doi:10.3390/w13081024 · Cited by 13
Antosz, P., Bharwani, S., Borit, M., & Edmonds, B. (2022) · International Journal of Social Research Methodology · doi:10.1080/13645579.2022.2052651 · Cited by 12
Loblay, V., Freebairn, L., & Occhipinti, J. (2023) · Health Research Policy and Systems · doi:10.1186/s12961-023-01069-4 · Cited by 15
Developing shared qualitative models for complex systems
Moon, K., & Browne, N. K. (2020) · Conservation Biology · doi:10.1111/cobi.13632 · Cited by 12
Spatially Explicit Fuzzy Cognitive Mapping for Participatory Modeling of Stormwater Management
White, C. T., Mitášová, H., BenDor, T. K., Foy, K. C., Pala, O., Vukomanovic, J., & Meentemeyer, R. K. (2021) · Land · doi:10.3390/land10111114 · Cited by 16
Zare, F., Jakeman, A. J., Elsawah, S., & Guillaume, J. H. A. (2024) · Ecological Modelling · doi:10.1016/j.ecolmodel.2024.110719 · Cited by 15
Eitzel, M. V., Solera, J., Wilson, K. B., Neves, K., Fisher, A. C., Veski, A., Omoju, O. E., Ndlovu, A. M., & Hove, E. M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0237638 · Cited by 14
Gonzalez-Redin, J., Polhill, G. J., Dawson, T. P., Hill, R., & Gordon, I. J. (2019) · AMBIO · doi:10.1007/s13280-019-01286-8 · Cited by 11
Representing driver-response complexity in ecosystems using an improved conceptual model
Bentley, C., & Anandhi, A. (2020) · Ecological Modelling · doi:10.1016/j.ecolmodel.2020.109320 · Cited by 11
A new agent-based model provides insight into deep uncertainty faced in simulated forest management
Sotnik, G., Cassell, B. A., Duveneck, M. J., & Scheller, R. M. (2021) · Landscape Ecology · doi:10.1007/s10980-021-01324-5 · Cited by 11
Martínez‐López, J., Albaladejo, J., & de Vente, J. (2024) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2024.106061 · Cited by 10
The portal of OpenGMS: Bridging the contributors and users of geographic simulation resources
Xu, K., Chen, M., Yue, S., Zhang, F., Wang, J., Wen, Y., & Lü, G. (2024) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2024.106142 · Cited by 10
Scenario Storyline Discovery for Planning in Multi‐Actor Human‐Natural Systems Confronting Change
Hadjimichael, A., Reed, P., Quinn, J., Vernon, C. R., & Thurber, T. B. (2024) · Earth's Future · doi:10.1029/2023ef004252 · Cited by 10
Improving the Interpretation of Data-Driven Water Consumption Models via the Use of Social Norms
Obringer, R., Nateghi, R., Ma, Z., & Kumar, R. (2022) · Journal of Water Resources Planning and Management · doi:10.1061/(asce)wr.1943-5452.0001611 · Cited by 11
Interpolating resident attitudes toward exurban roadside forest management
DiFalco, S., Morzillo, A., & Ghosh, D. (2022) · Landscape Ecology · doi:10.1007/s10980-022-01537-2 · Cited by 8
Merino-Benítez, T., Bojórquez-Tapia, L. A., Miquelajauregui, Y., & Batllori-Sampedro, E. (2024) · Frontiers in Climate · doi:10.3389/fclim.2024.1331945 · Cited by 9
Knowledge sources, narratives, and living in social-ecological systems
Cockerill, K., Glynn, P. D., Cerrutti, E. S., & Little, J. C. (2024) · Mitigation and Adaptation Strategies for Global Change · doi:10.1007/s11027-024-10151-3 · Cited by 12
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
