Skip to main content
Log in

Using agent-based modelling to simulate social-ecological systems across scales

  • Published:
GeoInformatica Aims and scope Submit manuscript

Abstract

Agent-based modelling (ABM) simulates Social-Ecological-Systems (SESs) based on the decision-making and actions of individual actors or actor groups, their interactions with each other, and with ecosystems. Many ABM studies have focused at the scale of villages, rural landscapes, towns or cities. When considering a geographical, spatially-explicit domain, current ABM architecture is generally not easily translatable to a regional or global context, nor does it acknowledge SESs interactions across scales sufficiently; the model extent is usually determined by pragmatic considerations, which may well cut across dynamical boundaries. With a few exceptions, the internal structure of governments is not included when representing them as agents. This is partly due to the lack of theory about how to represent such as actors, and because they are not static over the time-scales typical for social changes to have significant effects. Moreover, the relevant scale of analysis is often not known a priori, being dynamically determined, and may itself vary with time and circumstances. There is a need for ABM to cross the gap between micro-scale actors and larger-scale environmental, infrastructural and political systems in a way that allows realistic spatial and temporal phenomena to emerge; this is vital for models to be useful for policy analysis in an era when global crises can be triggered by small numbers of micro-level actors. We aim with this thought-piece to suggest conceptual avenues for implementing ABM to simulate SESs across scales, and for using big data from social surveys, remote sensing or other sources for this purpose.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Berkes F, Folke C (1998) Linking social and ecological systems: management practices and social mechanisms for building resilience. Cambridge University Press, Cambridge

    Google Scholar 

  2. Redman CL, Grove JM, Kuby LH (2004) Integrating Social Sciences into the Long-Term Ecological Research (LTER) Network: Social Dimensions of Ecological Change and Ecological Dimensions of Social Change. Ecosystems 7(2):161–171

    Google Scholar 

  3. Folke C, Hahn T, Olsson P, Norberg J (2005) Adaptive Governance of Social-Ecological Systems. Annu Rev Environ Resour 30:441–473

    Google Scholar 

  4. Verburg PH, Dearing JA, Dyke JG, van der Leeuw S, Seitzinger S, Steffen W, Syvitski J (2016) Methods and approaches to modelling in the Anthropocene. Glob Environ Chang 39:328–340

    Google Scholar 

  5. Anderies JM, Janssen MA, Ostrom E (2004) A Framework to Analyze the Robustness of Social-ecological Systems from an Institutional Perspective. Ecol Soc 9(1):18

    Google Scholar 

  6. McGinnis MD, Ostrom E (2014) Social-ecological systems framework: initial changes and continuing challenges. Ecol Soc 19(2):30

    Google Scholar 

  7. Leslie HM, Basurto X, Nenadovic M, Sievanen L, Cavanaugh KC, Cota-Nieto JJ, Erisman BE, Finkbeiner E, Hinojosa-Arango G, Moreno-Báez M, Nagavarapu S, Reddy SM, Sánchez-Rodríguez A, Siegel K, Ulibarria-Valenzuela JJ, Weaver AH, Aburto-Oropeza O (2015) Operationalizing the social-ecological systems framework to assess sustainability. PNAS 112(19):5979–5984

    Google Scholar 

  8. Polhill JG, Filatova T, Schlüter M, Voinov A (2016) Modelling systemic change in coupled socio-environmental systems. Environ Model Softw 75:318–332

    Google Scholar 

  9. Schlüter M, McAllister RRJ, Arlinghaus R, Bunnefeld N, Eisenack K, Hölker F, Milner-Gulland EJ, Müller B, Nicholson E, Quaas M, Stöven M (2012) New horizons for managing the environment: a review of coupled social-ecological systems modeling. Nat Resour Model 25(1):219–272

    Google Scholar 

  10. Virapongse A, Brooks S, Metcalf EC, Zedalis M, Gosz J, Kliskey A, Alessa L (2016) A socio-ecological systems approach for environmental management. J Environ Manag 178:83–91

    Google Scholar 

  11. An L (2012) Modeling human decisions in coupled human and natural systems: Review of agent-based models. Ecol Model 229:25–36

    Google Scholar 

  12. Filatova T, Verburg PH, Parker DC, Stannard CA (2013) Spatial agent-based models for socio-ecological systems: Challenges and prospects. Environ Model Softw 45:1–7

    Google Scholar 

  13. Matthews RB, Gilbert NG, Roach A, Polhill JG, Gotts NM (2007) Agent-based land-use models: a review of applications. Landsc Ecol 22(10):1147–1459

    Google Scholar 

  14. Parker DC, Manson SM, Janssen MA, Hoffmann MJ, Deadman P (2003) Multi-agent systems for the simulation of land-use and land-cover change: A review. Ann Assoc Am Geogr 93(2):314–337

    Google Scholar 

  15. Balbi S, Giupponi C (2009) Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability. Working Paper Department of Economics, Ca’ Foscari University of Venice, No. 15/WP/2009, ISSN: 1827/336X

  16. Groeneveld J, Müller B, Buchmann CM, Dressler G, Guo C, Hase N, Hoffmann F, John F, Klasseert C, Lauf T, Liebelt V, Nolzen H, Pannicke N, Schulze J, Weise H, Schwarz N (2017) Theoretical foundations of human decision-making in agent-based land use models - A review. Environ Model Softw 87:39–48

    Google Scholar 

  17. Heckbert S, Baynes T, Reeson A (2010) Agent-based modelling in ecological economics. Ann N Y Acad Sci 1185:39–53

    Google Scholar 

  18. Rounsevell MDA, Robinson DT, Murray-Rust D (2012a) From actors to agents in socio-ecological systems models. Philos Trans R Soc B Biol Sci 367:259–269

    Google Scholar 

  19. Schulze J, Müller B, Groeneveld J, Grimm V (2017) Agent-Based Modelling of Social-Ecological Systems: Achievements, Challenges, and a Way Forward. Journal of Artificial Societies and Social Simulation 20(2):8

    Google Scholar 

  20. Gog JL, Pellis L, Wood JLN, McLean AR, Arinaminpathy N, Lloyd-Smith JO (2015) Seven challenges in modeling pathogen dynamics within-host and across scales. Epidemics 10:45–48

    Google Scholar 

  21. Delli Gatti D, Gallegati M, Greenwald B, Russo A, Stiglitz JE (2010) The financial accelerator in an evolving credit network. J Econ Dyn Control 34:1627–1650

    Google Scholar 

  22. Stiglitz JE, Gallegati M (2011) Heterogeneous Interacting Agent Models for Understanding Monetary Economies. East Econ J 37:6–12

    Google Scholar 

  23. Waldrop MM (2018) Free Agents. Science 360:144–147

    Google Scholar 

  24. Kiyono K, Struzik ZR, Yamamoto Y (2006) Criticality and Phase Transitions in Stock-Price Fluctuations. Phys Rev Lett 96:068701

    Google Scholar 

  25. Arneth A, Brown C, Rounsevell MDA (2014) Global models of human decision-making for land-based mitigation and adaptation assessment. Nat Clim Chang 4:550–558

    Google Scholar 

  26. Rounsevell MDA, Pedroli B, Erb K-H, Gramberger M, Busck AG, Haberl H, Kristensen S, Kuemmerle T, Lavorel S, Lindner M, Lotze-Campen H, Metzger MJ, Murray-Rust D, Popp A, Perez-Souba M, Reenberg A, Vadineanu A, Verburg PH, Wolfslehner B (2012b) Challenges for land system science. Land Use Policy 29(4):899–910

    Google Scholar 

  27. Haining R (2003) Spatial Data Analysis: Theory and Practice. Cambridge University Press, Cambridge

    Google Scholar 

  28. Lloyd CD (2014) Exploring spatial scale in Geography. Wiley, Chichester

    Google Scholar 

  29. Marston SA, Jones JP III, Woodward K (2005) Human Geography without Scale. Trans Inst Br Geogr 30:416–432

    Google Scholar 

  30. Montello DR (2001) Scale in Geography. In: Baltes B (ed) Smelser NJ. Elsevier, International Encyclopedia of the Social and Behavioral Sciences, pp 13501–13504

    Google Scholar 

  31. Gibson CC, Ostrom E, Ahn TK (2000) The concept of scale and the human dimensions of global change: a survey. Ecol Econ 32(2):217–239

    Google Scholar 

  32. Cash DW, Adger NW, Berkes F, Garden P, Lebel L, Olsson P, Pritchard L, Young O (2006) Scale and cross-scale dynamics: governance and information in a multilevel world. Ecol Soc 11(2):8

    Google Scholar 

  33. Lebel L, Garden P, Imamura M (2005) The politics of scale, position and place in the management of water resources in the Mekong region. Ecol Soc 10(2):18

    Google Scholar 

  34. Young O (2006) Vertical interplay among scale-dependent environmental and resource regimes. Ecol Soc 11(1):27

    Google Scholar 

  35. Gotts NM, Polhill JG (2006) Simulating Socio-Techno-Ecosystems. Proceedings of the First World Congress on Social Simulation (WCSS 2006), Kyoto University, Kyoto, Japan, 21–25 August 2006, pp 119–126

  36. Hofstede GJ (2018) Mental Activity and Culture: The Elusive Real World. In: Faucher C (ed) Advances in Culturally-Aware Intelligent Systems and in Cross-Cultural Psychological Studies. Springer International Publishing, Cham, pp 143–164

    Google Scholar 

  37. Foley JA, DeFries R, Asner GP, Barford C, Bonan G, Carpenter SR, Chapin FS, Coe MT, Daily GC, Gibbs HK, Helkowski JH, Holloway T, Howard EA, Kucharik CJ, Monfreda C, Patz JA, Prentice IC, Ramankutty N, Snyder PK (2005) Global consequences of land use. Science 309(5734):570–574

    Google Scholar 

  38. Schlüter M, Baeza A, Dressler G, Frank K, Groeneveld J, Jager W, Jansse MA, McAllister RRJ, Müller B, Orach K, Schwarz N, Wijermans N (2017) A framework for mapping and comparing behavioural theories in models of social-ecological systems. Ecol Econ 131:21–35

    Google Scholar 

  39. Hofstede GJ (2017) GRASP agents: social first, intelligent later. AI & Soc:1–9

  40. Carpenter SR, Mooney HA, Agard J, Capistrano D, DeFries RS, Díaz S, Dietz T, Duraiappah AK, Oteng-Yeboah A, Pereira HM, Perrings C, Reid WV, Sarukhan J, Scholes RJ, Whyte A (2009) Science for managing ecosystem services: Beyond the Millennium Ecosystem Assessment. Proc Natl Acad Sci 106(5):1305–1312

    Google Scholar 

  41. Müller D, Munroe DK (2014) Current and Future Challenges in Land-Use Science. Journal of Land Use Science 9(2):133–142

    Google Scholar 

  42. Colander D (2006) Post Walrasian Macroeconomics: Beyond the Dynamic Stochastic General Equilibrium Model. Cambridge University Press, New York

    Google Scholar 

  43. Sonnenschein H (1972) Market Excess Demand Functions. Econometrica 40(3):549–563

    Google Scholar 

  44. Debreu G (1974) Excess Demand Functions. J Math Econ 1(1):15–23

    Google Scholar 

  45. Kirman AP (1992) Whom or What Does the Representative Individual Represent? J Econ Perspect 6(2):117–136

    Google Scholar 

  46. Balke T, Gilbert N (2014) How Do Agents Make Decisions? A Survey. Journal of Artificial Societies and Social Simulation 17(4):13

    Google Scholar 

  47. Epstein JM, Axtell RL (1996) Growing Artificial Societies: Social Science from the Bottom Up. Press, The MIT

    Google Scholar 

  48. Tesfatsion L, Judd KL (2006) Handbook of Computational Economics. Vol. 2, Agent-Based Computational Economics. Elsevier, Amsterdam

  49. LeBaron B, Tesfatsion L (2008) Modeling Macroeconomies as Open-Ended Dynamic Systems of Interacting Agents. Am Econ Rev 98(2):246–250

    Google Scholar 

  50. Raberto M, Teglio A, Cincotti S (2012) Debt Deleveraging and Business Cycles. An Agent-Based Perspective. Economics: The Open-Access, Open-Assessment E-Journal https://doi.org/10.5018/economics-ejournal.ja.2012-27

  51. Delli Gatti D, Di Guilmi C, Gaffeo E, Giulioni G, Gallegati M, Palestrini A (2005) A new approach to business fluctuations: heterogeneous interacting agents, scaling laws and financial fragility. J Econ Behav Organ 56(4):489–512

    Google Scholar 

  52. Farmer JD, Hepburn C, Mealy P, Teytelboym A (2015) A Third Wave in the Economics of Climate Change. Environ Resour Econ 62(2):329–357

    Google Scholar 

  53. Lamperti F, Dosi G, Napoletano M, Roventini A, Sapio A (2017a) Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-Based Integrated Assessment Model LEM Working Paper Series. Available at SSRN: https://www.ssrn.com/abstract=2944328 or https://doi.org/10.2139/ssrn.2944328

  54. Lustick IS, Alcorn B, Garces M, Ruvinsky A (2012) From theory to simulation: the dynamic political hierarchy in country virtualisation models. Journal of Experimental & Theoretical Artificial Intelligence 24(3):279–299

    Google Scholar 

  55. Natalini D, Bravo G, Jones AW (2017) Global food security and food riots–an agent-based modelling approach. Food Security:1–21. https://doi.org/10.1007/s12571-017-0693-z.

  56. Ferrier S, Ninan KN, Leadly P, Alkemade R, Acosta LA, Akçakaya HR, Brotons L, Cheung WWL, Christensen V, Harhash KA, Kabubo-Mariara J, Lundquist C, Obersteiner M., Pereira HM, Peterson G, Pichs-Madruga R, Ravindranath N, Rondinini C, Wintle BA (2016) IPBES (2016): The methodological assessment report on scenarios and models of biodiversity and ecosystem services. Secretariat of the Intergovernmental. Science-Policy Platform on Biodiversity and Ecosystem Services, Bonn, Germany

  57. Gilbert N, Ahrweiler P, Barbrook-Johnson P, Narasimhan KP, Wilkinson H (2018) Computational Modelling of Public Policy: Reflections on Practice. Journal of Artificial Societies and Social Simulation 21(1):14

    Google Scholar 

  58. Janssen MA, Walker BH, Langridge J, Abel N (2000) An adaptive agent model for analysing co-evolution of management and policies in a complex rangeland system. Ecol Model 131(2–3):249–268

    Google Scholar 

  59. Gross JE, McAllister RJJ, Abel N, Stafford Smith DM, Maru Y (2006) Australian rangelands as complex adaptive systems: A conceptual model and preliminary results. Environ Model Softw 21(9):1264–1272

    Google Scholar 

  60. Cioffi-Revilla C, Rouleau M (2010) MASON RebeLand: An agent-based model of Politics, Environment, and Insurgency. Int Stud Rev 12(1):31–52

    Google Scholar 

  61. Gerst MD, Wang P, Roventini A, Fagiolo G, Dosi G, Howarth RB, Borsuk ME (2013) Agent-based modelling of climate policy: An introduction to the ENGAGE multi-level model framework. Environ Model Softw 44:62–75

    Google Scholar 

  62. Greeven S, Kraan O, Chappin EJL, Kwakkel JH (2016) The Emergence of Climate Change Mitigation Action by Society: An Agent-based Scenario Discovery Study. Journal of Artificial Societies and Social Simulation 19(3):9

    Google Scholar 

  63. Dubbelboer J, Nikolic I, Jenkins K, Hall J (2017) An Agent-based Model of Flood Risk and Insurance. Journal of Artificial Societies and Social Simulation 20(1):6

    Google Scholar 

  64. Muis J (2010) Simulating Political Stability and Change in the Netherlands (1998–2010): an Agent-Based Model of Party Competition with Media Effects Empirically Tested. Journal of Artificial Societies and Social Simulation 13(2):4

    Google Scholar 

  65. Brondizio ES, Ostrom E, Young OR (2009) Connectivity and the Governance of Multilevel Social-Ecological Systems. Annu Rev Environ Resour 34:253–278

    Google Scholar 

  66. Ostrom E (2009) A general framework for analyzing sustainability of social-ecological systems. Science 325(5939):419–422

    Google Scholar 

  67. Armitage DR, Plummer R, Berkes F, Arthur RI, Charles AT, Davidson-Hunt IJ, Diduck AP, Doubleday NC, Johnson DS, Marschke M, McConney P, Pinkerton EW, Wollenberg EK (2009) Adaptive co-management for social-ecological complexity. Front Ecol Environ 7(2):95–102

    Google Scholar 

  68. Grimm V, Ayllón D, Railsback SF (2017) Next-generation Individual-Based Models Integrate Biodiversity and Ecosystems: Yes We Can and Yes We Must. Ecosystems 20(2):229–236

    Google Scholar 

  69. Luus KA, Robinson DT, Deadman PJ (2013) Representing ecological processes in agent-based models of land use and cover change. J Land Use Sci 8(2):175–198

    Google Scholar 

  70. Huigen MGA (2004) First principles of the MameLuke multi-actor modelling framework for land use change, illustrated with a Philippine case study. J Environ Manag 72(1–2):5–21

    Google Scholar 

  71. Bakker MM, Govers G, Kosmas C, Vanacker V, van Oost K, Rounsevell MDA (2005) Soil Erosion as a Driver of Land-Use Change. Agric Ecosyst Environ 105(3):467–481

    Google Scholar 

  72. Eichner T, Pethig R (2005) Ecosystem and Economy: An Integrated Dynamic General Equilibrium Approach. J Econ 85(3):213–249

    Google Scholar 

  73. Lindkvist E, Basurto X, Schlüter M (2017) Micro-level explanations for emergent patterns of self-governance arrangements in small-scale fisheries—A modeling approach. PLoS One 12(4):e0175532. https://doi.org/10.1371/journal.pone.0175532

    Google Scholar 

  74. Martin R, Schlüter M (2015) Combining system dynamics and agent-based modeling to analyze social-ecological interactions – an example from modeling restoration of a shallow lake. Frontiers in Environmental Science 3:66

    Google Scholar 

  75. Manson SM (2005) Agent-based modeling and genetic programming for modeling land change in the Southern Yucatán Peninsular Region of Mexico. Agric Ecosyst Environ 111(1–4):47–62

    Google Scholar 

  76. Gaube V, Kaiser C, Wildenberg M, Adensam H, Fleissner P, Kobler J, Lutz J, Schaumberger A, Schaumberger J, Smetschka B, Wolf A, Richter A, Haberl H (2009) Combining agent-based and stock-flow modelling approaches in a participative analysis of the integrated land system in Reichraming, Austria. Landsc Ecol 24(9):1149–1165

    Google Scholar 

  77. Bagstad KJ, Johnson GW, Voigt B, Villa F (2013) Spatial dynamics of ecosystem service flows: A comprehensive approach to quantifying actual services. Ecosyst Serv 4:117–125

    Google Scholar 

  78. Bithell M, Brasington J (2009) Coupling Agent-based models of subsistence farming with individual-based forest models and dynamic models of water distribution. Environ Model Softw 24(2):173–190

    Google Scholar 

  79. Guillem EE, Murray-Rust D, Robinson DT, Barnes A, Rounsevell MDA (2015) Modelling farmer decision-making to anticipate tradeoffs between provisioning ecosystem services and biodiversity. Agric Syst 137:12–23

    Google Scholar 

  80. Bonan GB, Doney SC (2018) Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models. Science 359(6375), eaam8328. https://doi.org/10.1126/science.aam8328

  81. Purves D, Scharlemann JPW, Harfoot M, Newbold T, Tittensor DP, Hutton J, Emmott S (2013) Ecosystems: Time to model all life on earth. Nature 493:295–297

    Google Scholar 

  82. Evans MR, Bithell M, Cornell SJ, Dall SRX, Díaz S, Emmott S, Ernande B, Grimm V, Hodgson DJ, Lewis SL, Mace GM, Morecroft M, Moustakas A, Murphy E, Newbold T, Norris KJ, Petchey O, Smith M, Travis JMJ, Benton TG (2013) Predictive systems ecology. Proc R Soc B 280:20131452. https://doi.org/10.1098/rspb.2013.1452

    Google Scholar 

  83. Harfoot MBJ, Newbold T, Tittensor DP, Emmott S, Hutton J, Lyutsarev V, Smith MJ, Scharlemann JPW, Purves DW (2014) Emergent Global Patterns of Ecosystem Structure and Function from a Mechanistic General Ecosystem Model. PLoS Biol 12(4):e1001841. https://doi.org/10.1371/journal.pbio.1001841

    Google Scholar 

  84. Titeux N, Henle K, Mihoub J-B, Regos A, Geijzendorffer IR, Cramer W, Verburg PH, Brotons L (2016) Biodiversity scenarios neglect future land-use changes. Glob Chang Biol 22:2505–2515

    Google Scholar 

  85. van Dam KH, Nikolic I, Lukszo Z (2013) Agent-based modelling of Socio-Technical Systems. Agent-Based Social Systems 9, Springer

  86. Barber CP, Cochrane MA, Souza CN Jr, Laurance WF (2014) Roads, deforestation and the mitigating effect of protected areas in the Amazon. Biol Conserv 177:203–209

    Google Scholar 

  87. Millington JDA, Xiong H, Peterson S, Woods J (2017) Integrating Modelling approaches for Understanding Telecoupling: Global Food Trade and Local Land Use. Land 6(3):56

    Google Scholar 

  88. Parker DC, Hessl A, Davis SC (2008) Complexity, land-use modeling, and the human dimension: Fundamental challenges for mapping unknown outcome spaces. Geoforum 39(2):789–804

    Google Scholar 

  89. Pacilly FCA, Hofstede GJ, van Bueren ETL, Kessel GJT, Groot JCJ (2018) Simulating crop-disease interactions in agricultural landscapes to analyse the effectiveness of host resistance in disease control: The case of potato late blight. Ecol Model 378:1–12

    Google Scholar 

  90. FCA Pacilly (2018) Social-ecological modelling of potato late blight. Managing crop resistance in disease. PhD Thesis, Wageningen University, 175p

  91. Voinov A, Shugart HH (2013) ‘Integronsters’, integral and integrated modeling. Environ Model Softw 39:149–158

    Google Scholar 

  92. Wolf S, Hinkel J, Hallier M, Bisaro A, Lincke D, Ionescu C, Klein RJT (2013) Clarifying vulnerability definitions and assessments using formalisation. International Journal of Climate Change Strategies and Management 5:54–70

    Google Scholar 

  93. Axelrod R (2006) Agent-based modeling as a bridge between disciplines. In: Tesfatsion L, Judd KL (eds) Handbook of Computational Economics, Elsevier, Vol, vol 2, pp 1565–1584

    Google Scholar 

  94. Polhill JG, Gotts NM (2009) Ontologies for transparent integrated human-natural system modelling. Landsc Ecol 24:1255–1267

    Google Scholar 

  95. Janssen S, Andersen E, Athanasiadis IN, van Ittersum M (2008) An European database for integrated assessment and modeling of agricultural systems. In: Sànchez-Marrè M, Béjar J, Comas J, Rizzoli A, Guariso G (eds) Proceedings of the 4th Biennial Meeting of the International Environmental Modeling and Software Society (iEMSs). Barcelona, Spain, pp 719–726

    Google Scholar 

  96. Bosch J (2014) Continuous software engineering. Springer International Publishing

  97. Herbsleb JD (2007) Global Software Engineering: The Future of Socio-technical co-ordination. Future of Software Engineering, 188–198, IEEE Computer Society

  98. Parker J, Epstein JM (2011) A distributed Platform for Global-Scale Agent-Based Models of Disease Transmission. ACM Transactions on Modeling and Computer Simulation 22(1):1–25

    Google Scholar 

  99. Parry HR, Bithell M (2012) Large scale agent-based modelling: A review and guidelines for model scaling. In: Heppenstall AJ, Crooks AT, See LM, Batty M (eds) Agent-based models of Geographical Systems. Springer, Dordrecht, pp 271–308

    Google Scholar 

  100. Smajgl A, Brown DG, Valbuena D, Huigen MGA (2011) Empirical characterisation of agent behaviours in socio-ecological systems. Environ Model Softw 26(7):837–844

    Google Scholar 

  101. Müller-Hansen F, Schlüter M, Mäs M, Donges JF, Kolb JJ, Thonicke K, Heitzig J (2017) Towards representing human behavior and decision making in Earth System models – an overview of techniques and approaches. Earth System Dynamics 8:977–1007

    Google Scholar 

  102. Kitchin R (2013) Big data and human geography: Opportunities, challenges and risks. Dialogues in Human Geography 3(3):262–267

    Google Scholar 

  103. Yang C, Huang Q, Li Z, Liu K, Hu F (2017) Big Data and cloud computing: innovation opportunities and challenges. International Journal of Digital Earth 10(1):13–53

    Google Scholar 

  104. Ward JA, Evans AJ, Malleson NS (2016) Dynamic calibration of agent-based models using data assimilation. R Soc Open Sci 3(4):150703

    Google Scholar 

  105. Lee J-S, Filatova T, Ligmann-Zielinska A, Hassani-Mahmooei B, Stonedahl F, Lorscheid I, Voinov A, Polhill G, Sun Z, Parker DC (2015) The complexities of Agent-Based modeling output analysis. Journal of Artificial Societies and Social Simulation 18(4):4

    Google Scholar 

  106. Lamperti F, Roventini A, Sani A (2018) Agent-based model calibration using machine learning surrogates. J Econ Dyn Control 90:366–389

    Google Scholar 

  107. Kattwinkel M, Reichert P (2017) Bayesian parameter inference for individual-based models using a Particle Markov Chain Monte Carlo Method. Environ Model Softw 87:110–119

    Google Scholar 

  108. Grimm V, Revilla E, Berger U, Jeltsch F, Mooij WM, Railsback SF, Thulke HH, Weiner J, Wiegand T, DeAngelis DL (2005) Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310:987–991

    Google Scholar 

  109. Barrett C, Eubank S, Marathe A, Marathe M, Swarup S (2015) Synthetic information environments for policy informatics: a distributed cognition perspective. In: Johnston EW (ed) Governance in the Information Era: Theory and Practice of Policy Informatics. Routledge, New York, pp 267–284

    Google Scholar 

  110. Schulz K, Seppelt R, Zehe E, Vogel HJ, Attinger S (2006) Importance of spatial structures in advancing hydrological sciences. Water Resources Research 42:W03S03

  111. Saari DG (2010) Aggregation and multilevel design for systems: Finding guidelines. J Mech Des 132(8):081006

    Google Scholar 

  112. Evans TP, Kelley H (2004) Multi-scale analysis of a household level agent-based model of land cover change. J Environ Manag 72(1–2):57–72

    Google Scholar 

  113. Galan JM, Izquierdo LR (2005) Appearances can be deceiving: Lessons learned re-implementing Axelrod's 'Evolutionary approach to norms'. Journal of Artificial Societies and Social Simulation 8(3):2

    Google Scholar 

  114. Edwards M, Huet S, Goreaud F, Deffuant G (2003) Comparing an individual-based model of behaviour diffusion with its mean field aggregate approximation. Journal of Artificial Societies and Social Simulation 6(4):9

    Google Scholar 

  115. Huet S, Edwards M, Deffuant G (2007) Taking into Account the Variations of Neighbourhood Sizes in the Mean-Field Approximation of the Threshold Model on a Random Network. Journal of Artificial Societies and Social Simulation 10(1):10

    Google Scholar 

  116. Pagel J, Fritzsch K, Biedermann R, Schröder B (2008) Annual plants under cyclic disturbance regime: better understanding through model aggregation. Ecol Appl 18:2000–2015

    Google Scholar 

  117. Martin R, Thomas SA (2016) Analyzing regime shifts in agent-based models with equation-free analysis. In: Sauvage S, Sánchez-Pérez JM, Rizzoli AE (eds) 8th International Congress on Environmental Modelling and Software. Toulouse, France, pp 494–502

    Google Scholar 

  118. Zou Y, Fonoberov VA, Fonoberova M, Mezic I, Kevrekidis IG (2012) Model reduction for agent-based social simulation: Coarse-graining a civil violence model. Physical Rev E Stat Nonlin Soft Matter Phys 85:066106

    Google Scholar 

  119. Banisch S (2016) Markov chain aggregation for agent-based models. Springer International Publishing

  120. Hallier M, Hartmann C (2016) Constructing Markov state models of reduced complexity from agent-based simulation data. Social Simulation Conference 2016, Rome, Italy

  121. Niedbalski JS, Deng K Mehta PG, Meyn S (2008) Model reduction for reduced order estimation in traffic models. Proceedings American Control Conference 2008, Seattle, USA

  122. Costanza R (1989) Model goodness of fit: A multiple resolution procedure. Ecol Model 47(3–4):199–215

    Google Scholar 

  123. Pontius RG Jr, Boersma W, Castella J-C, Clarke K, de Nijs T, Dietzel C, Dua Z, Fotsing E, Goldstein N, Kok K, Koomen E, Lippitt CD, McConnell W, Sood AM, Pijanowski B, Pithadia S, Sweeney S, Trung TN, Veldkamp AT, Verburg PH (2008) Comparing the input, output, and validation maps for several models of land change. Ann Reg Sci 42(1):11–37

    Google Scholar 

  124. Magliocca NR, van Vliet J, Brown C, Evans TP, Houet T, Messerli P, Messina JP, Nicholas KA, Ornetsmüller C, Sagebiel J, Schweizer V, Verburg PH, Yu Q (2015) From meta-studies to modeling: Using synthesis knowledge to build broadly applicable process-based land change models. Environ Model Softw 72:10–20

    Google Scholar 

  125. Deodhar S, Bisset K, Chen J, Barrett C, Wilson M Marathe M (2015) EpiCaster: An Integrated Web Application For Situation Assessment and Forecasting of Global Epidemics. Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics.

  126. Adger WN, Arnell NW, Tompkins EL (2005a) Successful adaptation to climate change across scales. Glob Environ Chang 15(2):77–86

    Google Scholar 

  127. Balbi S, Giupponi C, Perez P, Alberti M (2013) A spatial agent-based model for assessing strategies of adaptation to climate and tourism demand changes in an alpine tourism destination. Environ Model Softw 45:29–51

    Google Scholar 

  128. Cohen A, McCarthy J (2014) Reviewing rescaling: Strengthening the case for environmental considerations. Prog Hum Geogr 39(1):3–25

    Google Scholar 

  129. Adger WN, Brown K, Tompkins EL (2005b) The Political Economy of Cross-Scale Networks in Resource Co-Management. Ecol Soc 10(2):9

    Google Scholar 

  130. Janssen M, de Vries B (1998) The battle of perspectives: a multi-agent model with adaptive responses to climate change. Ecol Econ 26(1):43–65

    Google Scholar 

  131. Stern N (2016) Current climate models are grossly misleading. Nature 530:407–409

    Google Scholar 

  132. Wiedmann T, Lenzen M (2018) Environmental and social footprints of international trade. Nat Geosci 11:314–321

    Google Scholar 

  133. Janssen MA, Alessa LN, Barton M, Bergin S, Lee A (2008) Towards a Community Framework for Agent-Based Modelling. Journal of Artificial Societies and Social Simulation 11(2):6

    Google Scholar 

  134. Rollins ND, Barton CM, Bergin S, Janssen MA, Lee A (2014) A Computational Model Library for publishing model documentation and code. Environ Model Softw 61:59–64

    Google Scholar 

  135. Collier N, North M (2012) Repast HPC: A Platform for Large-Scale Agent-Based Modeling; in: Dubitzky W., Kurowski K, Schott B (Eds.) Large-Scale Computing, 202p

  136. Vervoort JM, Rutting L, Kok K, Hermans FLP, Veldkamp T, Bregt AK, van Lammeren R (2012) Exploring dimensions, scales, and cross-scale dynamics from the perspectives of change agents in social–ecological systems. Ecol Soc 17(4):24

    Google Scholar 

  137. Smajgl A (2010) Challenging beliefs through multi-level participatory modelling in Indonesia. Environ Model Softw 25(11):1470–1476

    Google Scholar 

  138. Mazzega P, Therond O, Debril T, March H, Sibertin-Blanc C, Lardy R, Sant’Ana D (2014) Critical Multi-level Governance Issues of Integrated Modelling: An Example of Low-Water Management in the Adour-Garonne Basin (France). J Hydrol 519:2515–2526

    Google Scholar 

  139. Castella J-C (2009) Assessing the role of learning devices and geovisualisation tools for collective action in natural resource management: Experiences from Vietnam. J Environ Manag 90(2):1313–1319

    Google Scholar 

  140. d'Aquino P, Bah A (2014) Multi-level participatory design of land use policies in African drylands: A method to embed adaptability skills of drylands societies in a policy framework. J Environ Manag 132:207–219

    Google Scholar 

  141. Delmotte S, Barbier J-M, Mouret J-C, Le Page C, Wery J, Chauvelon P, Sandoz A, Lopez-Ridaura S (2016) Participatory integrated assessment of scenarios for organic farming at different scales in Camargue, France. Agric Syst 143:147–158

    Google Scholar 

  142. Lippe M, Hilger T, Sudchalee S, Wechpibal N, Jintrawet A, Cadisch G (2017) Simulating stakeholder-based land-use change scenarios and their implication on Above-Ground Carbon and environmental management in Northern Thailand. Land 6(4):85

    Google Scholar 

  143. Barnaud C, Van Paassen A (2013) Equity, Power Games, and Legitimacy: Dilemmas of Participatory Natural Resource Management. Ecol Soc 18(2):21

    Google Scholar 

  144. Janssen MA (2017) The Practice of Archiving Model Code of Agent-Based Models. Journal of Artificial Societies and Social Simulation 20(1):1–2

    Google Scholar 

  145. Lippe M, Thai Minh T, Neef A, Hilger T, Hoffmann V, Lam NT, Cadisch G (2011) Building on qualitative datasets and participatory process to simulate land use change in a mountain watershed of Northwest Vietnam. Environ Model Softw 26(12):1454–1466

    Google Scholar 

  146. Le Page C, Perrotton A (2017) KILT: A Modelling Approach Based on Participatory Agent-Based Simulation of Stylized Socio-Ecosystems to Stimulate Social Learning with Local Stakeholders. In: Sukthankar G, Rodriguez-Aguilar JA (eds) Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops. Visionary Papers. Springer, Cham, pp 31–44

    Google Scholar 

  147. Allen CR, Fontaine JJ, Pope KL, Garmestani AS (2011) Adaptive management for a turbulent future. J Environ Manag 92(5):1339–1345

    Google Scholar 

  148. Le Page C, Bobo KS, Kamgaing OWT, Ngahane FB, Waltert M (2015) Interactive simulations with a stylized scale model to codesign with villagers an agent-based model of bushmeat hunting in the periphery of Korup National Park (Cameroon). Journal of Artificial Societies and Social Simulation 18(1):8

    Google Scholar 

  149. Voinov A, Bousquet F (2010) Modelling with stakeholders. Environ Model Softw 25(11):1268–1281

    Google Scholar 

  150. Johnson PG (2015) Agent-based models as “interested amateurs”. Land 4(2):281–299

    Google Scholar 

  151. Lee DB Jr (1973) Requiem for large-scale models. J Am Inst Plann 39(3):163–178

    Google Scholar 

  152. Lee DB (1994) Retrospective on large scale urban models. J Am Plan Assoc 60:35–40

    Google Scholar 

Download references

Acknowledgements

This paper originated from discussions during the Lorentz Center workshop ‘Cross-Scale Resilience in Socio-Ecological Simulations’ in Leiden 1–4 May 2017. The authors would like to thank in particular Géraldine Abrami, Bruce Edmonds, Eline de Jong, Gary Polhill and Nanda Wijermans for organising the workshop, and the Lorentz Center for hosting and providing financial support. Maja Schlüter acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 682472 – MUSES). The input of Pete Smith contributes to the DEVIL project [NE/M021327/1]. Kevin Thellmann acknowledges funding from the Water-People-Agriculture Research Training Group funded by the Anton & Petra Ehrmann-Stiftung. Nick Gotts acknowledges help from the Centre for Policy Modelling, Manchester Metropolitan University Business School, where he is a visiting fellow. Melvin Lippe acknowledges funding form the German Federal Ministry of Food and Agriculture due to a decision by the German Bundestag through the LaForeT Policies project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Melvin Lippe.

Additional information

Publisher’s Note

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

Publisher’s Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lippe, M., Bithell, M., Gotts, N. et al. Using agent-based modelling to simulate social-ecological systems across scales. Geoinformatica 23, 269–298 (2019). https://doi.org/10.1007/s10707-018-00337-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10707-018-00337-8

Keywords

Navigation