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Competition for Resources between Agent Functional Types (CRAFTY)

CRAFTY is a large-scale agent-based modelling (ABM) framework for the simulation of land use change. It is designed to allow efficient but powerful simulation of a wide range of land uses across large geographical extents, based on the decision-making of simulated land managers who generate a variety of ecosystem services. It is fully open-source and can be used without the need for any programming.

The basic framework is described in Murray-Rust et al. 2014, and the following variations and applications have also been produced:

  • CRAFTY-Sweden: Blanco et al. (2017)
  • CRAFTY-EU: Brown et al. (2019)
  • Institutional modelling: Holzhauer et al. (2019)

Model webpage: https://landchange.earth/CRAFTY

Model repository: https://bitbucket.org/geoslurg/crafty_cobra

Model wiki: https://bitbucket.org/geoslurg/crafty_wiki/wiki/Home

Publications:

  • Holzhauer, S., Brown, C., & Rounsevell, M. (2019). Modelling dynamic effects of multi-scale institutions on land use change. Regional Environmental Change, 19(3), 733–746. https://doi.org/10.1007/s10113-018-1424-5
  • Brown, C., Seo, B., & Rounsevell, M. (2019). Societal breakdown as an emergent property of large-scale behavioural models of land use change. Earth System Dynamics Discussions, (May), 1–49. https://doi.org/10.5194/esd-2019-24
  • Synes, N., Brown, C., Palmer, S., Bocedi, G., Osborne, P. E., Watts, K., … Travis, J. (2018). Coupled land use and ecological models reveal emergence and feedbacks in socio-ecological systems. Ecography. https://doi.org/10.1111/ecog.04039
  • Seo, B., Brown, C., & Rounsevell, M. D. A. (2018). EVALUATION AND CALIBRATION OF AN AGENT BASED LAND USE MODEL USING ta. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium(pp. 7476–7479).
  • Alexander et al. (2017). Assessing uncertainties in land cover projections. Global Change Biology, 23(2), 767–781. https://doi.org/10.1111/gcb.13447
  • Blanco, V., Holzhauer, S., Brown, C., Lagergren, F., Vulturius, G., Lindeskog, M., & Rounsevell, M. D. A. (2017). The effect of forest owner decision-making, climatic change and societal demands on land-use change and ecosystem service provision in Sweden. Ecosystem Services, 23(December 2016), 174–208. https://doi.org/10.1016/j.ecoser.2016.12.003
  • Holman et al. (2017). Modelling Climate Change Impacts, Adaptation and Vulnerability in Europe, Deliverable D3B.2, 1–100.
  • Brown, C., Holzhauer, S., Metzger, M. J., Paterson, J. S., & Rounsevell, M. (2016). Land managers’ behaviours modulate pathways to visions of future land systems. Regional Environmental Change, 1–15. https://doi.org/10.1007/s10113-016-0999-y
  • Murray-Rust, D., Brown, C., van Vliet, J., Alam, S. J., Robinson, D. T., Verburg, P. H., & Rounsevell, M. (2014). Combining agent functional types, capitals and services to model land use dynamics. Environmental Modelling and Software, 59, 187–201. https://doi.org/10.1016/j.envsoft.2014.05.019
  • Brown, C., Murray-Rust, D., Van Vliet, J., Alam, S. J., Verburg, P. H., & Rounsevell, M. D. (2014). Experiments in globalisation, food security and land use decision making. PLoS ONE, 9(12), 1–24. https://doi.org/10.1371/journal.pone.0114213
  • Brown, C., Murray-Rust, D., van Vliet, J., Alam, S. J., Verburg, P. H., & Rounsevell, M. D. (2014). Globalisation, Regionalisation and Behavioural Responses of Land Use Agents. In S. J. Alam & H. V. D. Parunak (Eds.), Multi-Agent-Based Simulation XIV(pp. 101–114). Berlin, Heidelberg: Springer Berlin Heidelberg.