Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Incorporating human behaviour into Earth system modelling

Abstract

Climate change and other challenges to the stability and functioning of natural and managed environmental systems are driven by increasing anthropogenic domination of the Earth. Models to forecast the trajectory of climate change and to identify pathways to sustainability require representation of human behaviour and its feedbacks with the climate system. Social climate models (SCMs) are an emerging class of models that embed human behaviour in climate models. We survey existing SCMs and make recommendations for how to integrate models of human behaviour and climate. We suggest a framework for representing human behaviour that consists of cognition, contagion and a behavioural response. Cognition represents the human processing of information around climate change; contagion represents the spread of information, beliefs and behaviour through social networks; and response is the resultant behaviour or action. This framework allows for biases, habituation and other cognitive processes that shape human perception of climate change as well as the influence of social norms, social learning and other social processes on the spread of information and factors that shape decision-making and behaviour. SCMs move beyond the inclusion of human activities in climate models to the representation of human behaviour that determines the magnitude, sign and character of these activities. The development of SCMs is a challenging but important next step in the evolution of Earth system models.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Traditional climate models and social climate models.

References

  1. Gallagher, R. & Carpenter, B. Human-dominated ecosystems. Science 277, 485 (1997).

    Article  Google Scholar 

  2. Vitousek, P. M., Mooney, H. A., Lubchenco, J. & Melillo, J. M. Human domination of Earth’s ecosystems. Science 277, 494–499 (1997).

    Article  CAS  Google Scholar 

  3. Steffen, W. et al. Planetary boundaries: guiding human development on a changing planet. Science 347, 1259855 (2015).

  4. Geller, E. S. in Psychology and Social Responsibility: Facing Global Challenges (eds Staub, S. & Green, P.) 248–268 (New York Univ. Press, 1992).

  5. Penn, D. J. The evolutionary roots of our environmental problems: toward a Darwinian ecology. Q. Rev. Biol. 78, 275–301 (2003).

    Article  PubMed  Google Scholar 

  6. Ayllón, D. et al. Cross-disciplinary links in environmental systems science: current state and claimed needs identified in a meta-review of process models. Sci. Total Environ. 622–623, 954–973 (2018).

    Article  PubMed  Google Scholar 

  7. Beckage, B. et al. The Earth has humans, so why don’t our climate models? Clim. Change https://doi.org/10.1007/s10584-020-02897-x (2020).

  8. Palmer, P. I. & Smith, M. J. Earth systems: model human adaptation to climate change. Nature 512, 365–366 (2014).

    Article  CAS  PubMed  Google Scholar 

  9. Motesharrei, S. et al. Modeling sustainability: population, inequality, consumption, and bidirectional coupling of the Earth and human systems. Natl Sci. Rev. https://doi.org/10.1093/nsr/nww081 (2016).

  10. Donges, J. F. et al. Closing the loop: reconnecting human dynamics to Earth system science. Anthropocene Rev. 4, 151–157 (2017).

    Article  Google Scholar 

  11. Müller-Hansen, F. et al. Towards representing human behavior and decision making in Earth system models—an overview of techniques and approaches. Earth Syst. Dyn. 8, 977–1007 (2017).

    Article  Google Scholar 

  12. Calvin, K. & Bond-Lamberty, B. Integrated human–Earth system modeling—state of the science and future directions. Environ. Res. Lett. 13, 063006 (2018).

    Article  Google Scholar 

  13. Steffen, W. et al. The emergence and evolution of Earth system science. Nat. Rev. Earth Environ. 1, 54–63 (2020).

    Article  Google Scholar 

  14. Farahbakhsh, I., Bauch, C. T. & Anand, M. Modelling coupled human–environment complexity for the future of the biosphere: strengths, gaps and promising directions. Phil. Trans. R. Soc. B 377, 20210382 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Steffen, W. et al. Trajectories of the Earth system in the Anthropocene. Proc. Natl Acad. Sci. USA 115, 8252–8259 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Shin, Y. A., Lacasse, K., Gross, L. J. & Beckage, B. How coupled is coupled human–natural systems research? Ecol. Soc. 27, art4 (2022).

    Article  Google Scholar 

  17. Hausfather, Z. & Peters, G. P. Emissions—the ‘business as usual’ story is misleading. Nature 577, 618–620 (2020).

    Article  CAS  PubMed  Google Scholar 

  18. Burgess, M. G., Ritchie, J., Shapland, J. & Pielke, R. IPCC baseline scenarios have over-projected CO2 emissions and economic growth. Environ. Res. Lett. 16, 014016 (2021).

    Article  CAS  Google Scholar 

  19. Hausfather, Z. & Moore, F. C. Net-zero commitments could limit warming to below 2 °C. Nature 604, 247–248 (2022).

    Article  CAS  PubMed  Google Scholar 

  20. Beckage, B. et al. Linking models of human behaviour and climate alters projected climate change. Nat. Clim. Change 8, 79–84 (2018).

    Article  Google Scholar 

  21. Moore, F. C. et al. Determinants of emissions pathways in the coupled climate–social system. Nature 603, 103–111 (2022).

    Article  CAS  PubMed  Google Scholar 

  22. Rennert, K. et al. The social cost of carbon: advances in long-term probabilistic projections of population, GDP, emissions, and discount rates. Brook. Pap. Econ. Act. 2021, 223–305 (2022).

    Article  Google Scholar 

  23. Stewart, I. Do Dice Play God? The Mathematics of Uncertainty (Hachette, 2019).

  24. Jusup, M. et al. Social physics. Phys. Rep. 948, 1–148 (2022).

    Article  Google Scholar 

  25. Wolfram, S. A New Kind of Science (Mathematica, 2002).

  26. Beckage, B., Gross, L. J. & Kauffman, S. The limits to prediction in ecological systems. Ecosphere 2, 1–12 (2011).

    Article  Google Scholar 

  27. Flack, J. C. Coarse-graining as a downward causation mechanism. Phil. Trans. R. Soc. A 375, 20160338 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Riahi, K. et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Article  Google Scholar 

  29. Weyant, J. Some contributions of integrated assessment models of global climate change. Rev. Environ. Econ. Policy 11, 115–137 (2017).

    Article  Google Scholar 

  30. Mendelsohn, R. Efficient adaptation to climate change. Climatic Change 45, 583–600 (2000).

    Article  Google Scholar 

  31. Diaz, D. B. Estimating global damages from sea level rise with the Coastal Impact and Adaptation Model (CIAM). Climatic Change 137, 143–156 (2016).

    Article  Google Scholar 

  32. Benveniste, H., Oppenheimer, M. & Fleurbaey, M. Effect of border policy on exposure and vulnerability to climate change. Proc. Natl Acad. Sci. USA 117, 26692–26702 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Schneider, S. H., Easterling, W. E. & Mearns, L. O. Adaptation: sensitivity to natural variability, agent assumptions and dynamic climate changes. Clim. Change 45, 203–221 (2000).

    Article  Google Scholar 

  34. Melillo, J. M., Prentice, I. C., Farquhar, G. D., Schulze, E. D. & Sala, O. E. in Climate Change 1995: The Science of Climate Change (eds Houghton, J. T. et al.) 445–481 (IPCC, Cambridge Univ. Press, 1996).

  35. Melillo, J. M. et al. Soil warming and carbon-cycle feedbacks to the climate system. Science 298, 2173–2176 (2002).

    Article  CAS  PubMed  Google Scholar 

  36. Rial, J. A. et al. Nonlinearities, feedbacks and critical thresholds within the Earth’s climate system. Climatic Change 65, 11–38 (2004).

    Article  Google Scholar 

  37. Stephens, G. L. Cloud feedbacks in the climate system: a critical review. J. Clim. 18, 237–273 (2005).

    Article  Google Scholar 

  38. Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).

    Article  CAS  PubMed  Google Scholar 

  39. Arneth, A. et al. Terrestrial biogeochemical feedbacks in the climate system. Nat. Geosci. 3, 525–532 (2010).

    Article  CAS  Google Scholar 

  40. Bonan, G. B. & Doney, S. C. Climate, ecosystems, and planetary futures: the challenge to predict life in Earth system models. Science 359, eaam8328 (2018).

    Article  PubMed  Google Scholar 

  41. O’Neill, B. C. et al. The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob. Environ. Change 42, 169–180 (2017).

    Article  Google Scholar 

  42. Hawkins, E. & Sutton, R. The potential to narrow uncertainty in regional climate predictions. Bull. Am. Meteorol. Soc. 90, 1095–1108 (2009).

    Article  Google Scholar 

  43. Lehner, F. et al. Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6. Earth Syst. Dyn. 11, 491–508 (2020).

    Article  Google Scholar 

  44. Haer, T., Botzen, W. J. W. & Aerts, J. C. J. H. The effectiveness of flood risk communication strategies and the influence of social networks—insights from an agent-based model. Environ. Sci. Policy 60, 44–52 (2016).

    Article  Google Scholar 

  45. Orlov, A. et al. Global economic responses to heat stress impacts on worker productivity in crop production. Econ. Disasters Clim. Change 5, 367–390 (2021).

    Article  Google Scholar 

  46. Oppenheimer, M. Climate Change impacts: accounting for the human response. Clim. Change 117, 439–449 (2013).

    Article  Google Scholar 

  47. Gawith, D., Hodge, I., Morgan, F. & Daigneault, A. Climate change costs more than we think because people adapt less than we assume. Ecol. Econ. 173, 106636 (2020).

    Article  Google Scholar 

  48. Kelly Letcher, R. A. et al. Selecting among five common modelling approaches for integrated environmental assessment and management. Environ. Model. Softw. 47, 159–181 (2013).

    Article  Google Scholar 

  49. Verburg, P. H. et al. Methods and approaches to modelling the Anthropocene. Glob. Environ. Change 39, 328–340 (2016).

    Article  Google Scholar 

  50. Robinson, D. T. et al. Modelling feedbacks between human and natural processes in the land system. Earth Syst. Dyn. 9, 895–914 (2018).

    Article  Google Scholar 

  51. Iwanaga, T. et al. Socio-technical scales in socio-environmental modeling: managing a system-of-systems modeling approach. Environ. Model. Softw. 135, 104885 (2021).

    Article  PubMed  Google Scholar 

  52. Sterman, J. et al. Climate interactive: the C-ROADS climate policy model. Syst. Dyn. Rev. 28, 295–305 (2012).

    Article  Google Scholar 

  53. Nordhaus, W. Evolution of modeling of the economics of global warming: changes in the DICE model, 1992-2017. Clim. Change 148, 623–640 (2018).

    Article  Google Scholar 

  54. Bury, T. M., Bauch, C. T. & Anand, M. Charting pathways to climate change mitigation in a coupled socio-climate model. PLoS Comput. Biol. 15, e1007000 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Gazzotti, P. et al. Persistent inequality in economically optimal climate policies. Nat. Commun. 12, 3421 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ricke, K. L. & Caldeira, K. Natural climate variability and future climate policy. Nat. Clim. Change 4, 333–338 (2014).

    Article  Google Scholar 

  57. Howe, P. D., Markowitz, E. M., Lee, T. M., Ko, C.-Y. & Leiserowitz, A. Global perceptions of local temperature change. Nat. Clim. Change 3, 352–356 (2013).

    Article  Google Scholar 

  58. Howe, P. D., Boudet, H., Leiserowitz, A. & Maibach, E. W. Mapping the shadow of experience of extreme weather events. Clim. Change 127, 381–389 (2014).

    Article  Google Scholar 

  59. Sisco, M. R., Bosetti, V. & Weber, E. U. When do extreme weather events generate attention to climate change? Clim. Change 143, 227–241 (2017).

    Article  Google Scholar 

  60. Collins, W. D. et al. The integrated Earth system model version 1: formulation and functionality. Geosci. Model Dev. 8, 2203–2219 (2015).

    Article  Google Scholar 

  61. Stott, P. A. et al. External control of 20th century temperature by natural and anthropogenic forcings. Science 290, 2133–2137 (2000).

    Article  CAS  PubMed  Google Scholar 

  62. Stern, D. I. & Kaufmann, R. K. Anthropogenic and natural causes of climate change. Clim. Change 122, 257–269 (2014).

    Article  Google Scholar 

  63. Carmichael, G. R. et al. Asian aerosols: current and year 2030 distributions and implications to human health and regional climate change. Environ. Sci. Technol. 43, 5811–5817 (2009).

    Article  CAS  PubMed  Google Scholar 

  64. Schlüter, M. et al. A framework for mapping and comparing behavioural theories in models of social–ecological systems. Ecol. Econ. 131, 21–35 (2017).

    Article  Google Scholar 

  65. Eyster, H. N., Satterfield, T. & Chan, K. M. A. Why people do what they do: an interdisciplinary synthesis of human action theories. Annu. Rev. Environ. Resour. 47, 725–751 (2022).

    Article  Google Scholar 

  66. Jager, W. Enhancing the Realism of Simulation (EROS): on implementing and developing psychological theory in social simulation. J. Artif. Soc. Soc. Simul. 20, 14 (2017).

    Article  Google Scholar 

  67. Muelder, H. & Filatova, T. One theory—many formalizations: testing different code implementations of the theory of planned behaviour in energy agent-based models. J. Artif. Soc. Soc. Simul. 4, 5 (2018).

  68. Brown, C. & Rounsevell, M. How can social–ecological system models simulate the emergence of social–ecological crises? People Nat. 3, 88–103 (2021).

    Article  Google Scholar 

  69. Bayne, T. et al. What is cognition? Curr. Biol. 29, R608–R615 (2019).

    Article  CAS  PubMed  Google Scholar 

  70. Young, H. P. Innovation diffusion in heterogeneous populations: contagion, social influence, and social learning. Am. Econ. Rev. 99, 1899–1924 (2009).

    Article  Google Scholar 

  71. Nordhaus, W. Climate change: the ultimate challenge for economics. Am. Econ. Rev. 109, 1991–2014 (2019).

    Article  Google Scholar 

  72. Hawkins, E. & Sutton, R. The potential to narrow uncertainty in projections of regional precipitation change. Clim. Dyn. 37, 407–418 (2011).

    Article  Google Scholar 

  73. Goldberg, M. H., Linden, S., van der, Leiserowitz, A. & Maibach, E. Perceived social consensus can reduce ideological biases on climate change. Environ. Behav. https://doi.org/10.1177/0013916519853302 (2019).

  74. Kim, S. C., Pei, D., Kotcher, J. E. & Myers, T. A. Predicting responses to climate change health impact messages from political ideology and health status: cognitive appraisals and emotional reactions as mediators. Environ. Behav. 53, 1095–1117 (2021).

    Article  Google Scholar 

  75. Swim, J. et al. Psychology and Global Climate Change: Addressing a Multi-faceted Phenomenon and Set of Challenges (American Psychological Association, 2011).

  76. Murphy, R. The Fossil-Fuelled Climate Crisis: Foresight or Discounting Danger? (Springer International, 2021).

  77. Hoffman, A. J. How Culture Shapes the Climate Change Debate (Stanford Univ. Press, 2015).

  78. Schelling, T. C. Micromotives and Macrobehavior (WW Norton, 2006).

  79. Williams, H. T. P., McMurray, J. R., Kurz, T. & Hugo Lambert, F. Network analysis reveals open forums and echo chambers in social media discussions of climate change. Glob. Environ. Change 32, 126–138 (2015).

    Article  Google Scholar 

  80. Farrell, J. Network structure and influence of the climate change counter-movement. Nat. Clim. Change 6, 370–374 (2016).

    Article  Google Scholar 

  81. Otto, I. M. et al. Social tipping dynamics for stabilizing Earth’s climate by 2050. Proc. Natl Acad. Sci. USA 117, 2354–2365 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Nordhaus, W. Climate clubs: overcoming free-riding in international climate policy. Am. Econ. Rev. 105, 1339–1370 (2015).

    Article  Google Scholar 

  83. Kotchen, M. J. Which social cost of carbon? A theoretical perspective. J. Assoc. Environ. Resour. Econ. 5, 673–694 (2018).

    Google Scholar 

  84. Hamilton, M. & Lubell, M. Collaborative governance of climate change adaptation across spatial and institutional scales. Policy Stud. J. 46, 222–247 (2018).

    Article  Google Scholar 

  85. Lubell, M. & Morrison, T. H. Institutional navigation for polycentric sustainability governance. Nat. Sustain. 4, 664–671 (2021).

    Article  Google Scholar 

  86. Pankratz, N. M. C. & Schiller, C. Climate change and adaptation in global supply-chain networks. SSRN Electron. J. https://doi.org/10.2139/ssrn.3475416 (2019).

  87. Baldos, U. L. C., Hertel, T. W. & Moore, F. C. Understanding the spatial distribution of welfare impacts of global warming on agriculture and its drivers. Am. J. Agric. Econ. 101, 1455–1472 (2019).

    Article  Google Scholar 

  88. Kraan, O., Kramer, G. J., van der Lei, T. & Huppes, G. in Advances in Social Simulation 2015 (eds Jager, W. et al.) Vol. 528, 207–216 (Springer International, 2017).

  89. Mercure, J.-F., Lam, A., Billington, S. & Pollitt, H. Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 °C. Clim. Change 151, 109–129 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Eker, S., Reese, G. & Obersteiner, M. Modelling the drivers of a widespread shift to sustainable diets. Nat. Sustain. 2, 725–735 (2019).

  91. Brown, C., Seo, B. & Rounsevell, M. Societal breakdown as an emergent property of large-scale behavioural models of land use change. Earth Syst. Dyn. 10, 809–845 (2019).

    Article  Google Scholar 

  92. Hassani-Mahmooei, B. & Parris, B. W. Climate change and internal migration patterns in Bangladesh: an agent-based model. Environ. Dev. Econ. 17, 763–780 (2012).

    Article  Google Scholar 

  93. McNamara, D. E. & Keeler, A. A coupled physical and economic model of the response of coastal real estate to climate risk. Nat. Clim. Change 3, 559–562 (2013).

    Article  Google Scholar 

  94. Konc, T., Drews, S., Savin, I. & van den Bergh, J. C. J. M. Co-dynamics of climate policy stringency and public support. Glob. Environ. Change 74, 102528 (2022).

    Article  Google Scholar 

  95. Howard, P. & Livermore, M. A. Sociopolitical feedbacks and climate change. Harv. Environ. Law Rev. 43, 119–174 (2019).

    Google Scholar 

  96. Tavoni, A., Dannenberg, A., Kallis, G. & Löschel, A. Inequality, communication, and the avoidance of disastrous climate change in a public goods game. Proc. Natl Acad. Sci. USA 108, 11825–11829 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Pettifor, H., Wilson, C., McCollum, D. & Edelenbosch, O. Y. Modelling social influence and cultural variation in global low-carbon vehicle transitions. Glob. Environ. Change 47, 76–87 (2017).

    Article  Google Scholar 

  98. Lamperti, F., Dosi, G., Napoletano, M., Roventini, A. & Sapio, A. Climate change and green transitions in an agent-based integrated assessment model. Technol. Forecast. Soc. Change 153, 119806 (2020).

    Article  Google Scholar 

  99. Gouel, C. & Laborde, D. The crucial role of domestic and international market-mediated adaptation to climate change. J. Environ. Econ. Manage. 106, 102408 (2021).

    Article  Google Scholar 

  100. Bakkensen, L. A. & Barrage, L. Going underwater? Flood risk belief heterogeneity and coastal home price dynamics. Rev. Financ. Stud. 35, 3666–3709 (2022).

    Article  Google Scholar 

  101. Berrang-Ford, L. et al. A systematic global stocktake of evidence on human adaptation to climate change. Nat. Clim. Change 11, 989–1000 (2021).

    Article  Google Scholar 

  102. Sloat, L. L. et al. Climate adaptation by crop migration. Nat. Commun. 11, 1243 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Menzel, A. et al. Climate change fingerprints in recent European plant phenology. Glob. Change Biol. 26, 2599–2612 (2020).

    Article  Google Scholar 

  104. Hino, M., Field, C. B. & Mach, K. J. Managed retreat as a response to natural hazard risk. Nat. Clim. Change 7, 364–370 (2017).

    Article  Google Scholar 

  105. Rode, A. et al. Estimating a social cost of carbon for global energy consumption. Nature 598, 308–314 (2021).

    Article  CAS  PubMed  Google Scholar 

  106. van Ginkel, K. C. H. et al. Climate change induced socio-economic tipping points: review and stakeholder consultation for policy relevant research. Environ. Res. Lett. 15, 023001 (2020).

    Article  Google Scholar 

  107. Chase-Dunn, C. & Lerro, B. Social Change: Globalization from the Stone Age to the Present (Routledge, 2016).

  108. Matsumoto, K. Climate change impacts on socioeconomic activities through labor productivity changes considering interactions between socioeconomic and climate systems. J. Clean. Prod. 216, 528–541 (2019).

    Article  Google Scholar 

  109. Rounsevell, M. D. A., Robinson, D. T. & Murray-Rust, D. From actors to agents in socio-ecological systems models. Phil. Trans. R. Soc. B 367, 259–269 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Edelenbosch, O. Y., McCollum, D. L., Pettifor, H., Wilson, C. & van Vuuren, D. P. Interactions between social learning and technological learning in electric vehicle futures. Environ. Res. Lett. 13, 124004 (2018).

    Article  Google Scholar 

  111. Menard, J., Bury, T. M., Bauch, C. T. & Anand, M. When conflicts get heated, so does the planet: coupled social–climate dynamics under inequality. Proc. R. Soc. B 288, 20211357 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Konc, T., Savin, I. & van den Bergh, J. C. J. M. The social multiplier of environmental policy: application to carbon taxation. J. Environ. Econ. Manage. 105, 102396 (2021).

    Article  Google Scholar 

  113. Rosenbloom, D., Meadowcroft, J. & Cashore, B. Stability and climate policy? Harnessing insights on path dependence, policy feedback, and transition pathways. Energy Res. Soc. Sci. 50, 168–178 (2019).

    Article  Google Scholar 

  114. Rao, N. D. Distributional impacts of climate change mitigation in Indian electricity: the influence of governance. Energy Policy 61, 1344–1356 (2013).

    Article  Google Scholar 

  115. Vandyck, T., Keramidas, K., Tchung-Ming, S., Weitzel, M. & Van Dingenen, R. Quantifying air quality co-benefits of climate policy across sectors and regions. Clim. Change 163, 1501–1517 (2020).

    Article  CAS  Google Scholar 

  116. Fussel, H.-M. How inequitable is the global distribution of responsibility, capability, and vulnerability to climate change: a comprehensive indicator-based assessment. Glob. Environ. Change 20, 597–611 (2010).

    Article  Google Scholar 

  117. IPCC Climate Change 2022: Impacts, Adaptation and Vulnerability (eds Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).

  118. Stanton, E. A., Ackerman, F. & Kartha, S. Inside the integrated assessment models: four issues in climate economics. Clim. Dev. 1, 166–184 (2009).

    Article  Google Scholar 

  119. Jafino, B. A., Kwakkel, J. H. & Taebi, B. Enabling assessment of distributive justice through models for climate change planning: a review of recent advances and a research agenda. WIREs Clim. Change 12, e721 (2021).

  120. Ciullo, A., Kwakkel, J. H., De Bruijn, K. M., Doorn, N. & Klijn, F. Efficient or fair? Operationalizing ethical principles in flood risk management: a case study on the Dutch–German Rhine. Risk Anal. 40, 1844–1862 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  121. Thornton, P. K., Jones, P. G., Alagarswamy, G., Andresen, J. & Herrero, M. Adapting to climate change: agricultural system and household impacts in East Africa. Agric. Syst. 103, 73–82 (2010).

    Article  Google Scholar 

  122. Dennig, F., Budolfson, M. B., Fleurbaey, M., Siebert, A. & Socolow, R. H. Inequality, climate impacts on the future poor, and carbon prices. Proc. Natl Acad. Sci. USA 112, 15827–15832 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Sonja, K. & Harald, W. Building equity in: strategies for integrating equity into modelling for a 1.5 °C world. Phil. Trans. R. Soc. A 376, 20160461 (2018).

    Article  Google Scholar 

  124. Peng, W. et al. Climate policy models need to get real about people — here’s how. Nature 594, 174–176 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Nordhaus, W. D. Revisiting the social cost of carbon. Proc. Natl Acad. Sci. USA 114, 1518–1523 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Cai, Y. & Lontzek, T. S. The social cost of carbon with economic and climate risks. J. Polit. Econ. 127, 2684–2734 (2019).

    Article  Google Scholar 

  127. Kotlikoff, L., Kubler, F., Polbin, A., Sachs, J. & Scheidegger, S. Making carbon taxation a generational win win. Int. Econ. Rev. 62, 3–46 (2021).

    Article  Google Scholar 

  128. Kotlikoff, L., Kübler, F., Polbin, A. & Scheidegger, S. Economists have needlessly produced a climate war. VoxEU (27 October 2021).

  129. Elsawah, S. et al. Eight grand challenges in socio-environmental systems modeling. Socio-environ. Syst. Model. 2, 16226 (2020).

    Google Scholar 

  130. Kalkuhl, M. & Wenz, L. The impact of climate conditions on economic production: evidence from a global panel of regions. J. Environ. Econ. Manage. 103, 102360 (2020).

    Article  Google Scholar 

  131. Carleton, T. et al. Valuing the global mortality consequences of climate change accounting for adaptation costs and benefits. Q. J. Econ. https://doi.org/10.1093/qje/qjac020 (2022).

  132. Baylis, P. et al. Weather impacts expressed sentiment. PLoS ONE 13, e0195750 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  133. Baylis, P. Temperature and temperament: evidence from Twitter. J. Public Econ. 184, 104161 (2020).

    Article  Google Scholar 

  134. Lu, X. et al. Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen. Clim. Change 138, 505–519 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  135. Weill, J. A., Stigler, M., Deschenes, O. & Springborn, M. R. Social distancing responses to COVID-19 emergency declarations strongly differentiated by income. Proc. Natl Acad. Sci. USA 117, 19658–19660 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Burke, M. et al. Exposures and behavioural responses to wildfire smoke. Nat. Hum. Behav. https://doi.org/10.1038/s41562-022-01396-6 (2022).

  137. Callaghan, M. et al. Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies. Nat. Clim. Change 11, 966–972 (2021).

    Article  Google Scholar 

  138. Jean, N. et al. Combining satellite imagery and machine learning to predict poverty. Science 353, 790–794 (2016).

    Article  CAS  PubMed  Google Scholar 

  139. Winkelmann, R. et al. Social tipping processes towards climate action: a conceptual framework. Ecol. Econ. 192, 107242 (2022).

    Article  Google Scholar 

  140. Eker, S. & Wilson, C. System Dynamics of Social Tipping Processes (International Institute for Applied Systems Analysis, 2022).

  141. Maslin, M. Ecological versus climatic thresholds. Science 306, 2197–2198 (2004).

    Article  CAS  PubMed  Google Scholar 

  142. Rietkerk, M., Dekker, S. C., de Ruiter, P. C. & van de Koppel, J. Self-organized patchiness and catastrophic shifts in ecosystems. Science 305, 1926–1929 (2004).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work resulted from a working group supported by the National Socio-environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation (NSF) grant no. DBI-1052875. B.B. was supported in part by NASA grant no. 80NSSC20M0122 and by USDA National Institute of Food and Agriculture Hatch project no. 1025208. We thank D. Visioni for suggestions that improved Fig. 1.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Brian Beckage.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Human Behaviour thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Beckage, B., Moore, F.C. & Lacasse, K. Incorporating human behaviour into Earth system modelling. Nat Hum Behav 6, 1493–1502 (2022). https://doi.org/10.1038/s41562-022-01478-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-022-01478-5

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing