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.
CRAFTY also forms part of the LandSyMM sub-national to global scale model of the land system (https://landsymm.earth), and has been coupled with the eco-evolutionary modelling platform ‘RangeShifter’ (through the R package RangeShiftR)
The basic framework is described in Murray-Rust et al. 2014, and the following variations and applications have also been produced:
- Global: CRAFTY-Global; Saxena et al. (in prep.)
- Europe: CRAFTY-EU; Brown et al. (2019, 2021); online interface OSF item
- United Kingdom: CRAFTY-GB; Brown et al. (2022); online interface OSF item
- Scotland CRAFTY-Scotland; Burton et al. (in review)
- Sweden: CRAFTY-Sweden; Blanco et al. (2017a, b)
- Germany: CRAFTY-DE; Winkler et al. (in prep.)
- Brazil: CRAFTY-Brazil; Millington et al. (2021)
- Experimental applications: Brown et al. (2014, 2018)
- Applications to protected areas, rewilding & biodiversity: Synes et al. (2018), Urban et al. (2021), Staccione et al. (2023), Brown et al. (2024)
- Applications on land-based Carbon Dioxide Removal and climate mitigation: Perkins et al. (2023)
- Institutional & AI-based modelling: Holzhauer et al. (2019), Zeng et al. (2024, 2025a, b, c)
- Application to rubber plantation expansion in Yunnan Province, China: Synes et al. (2016)
- Model evaluation: Brown et al. (2023)
Github repositories: https://github.com/CRAFTY-ABM
Documentation: https://www.wiki.ed.ac.uk/display/CRAFTY (legacy)
https://github.com/CRAFTY-ABM/CRAFTY_Documentation (under construction)
Publications:
Alexander, P., Prestele, R., Verburg, P. H., Arneth, A., Baranzelli, C., Batista e Silva, F., … Rounsevell, M. D. A. A. (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
Blanco, V.; Brown, C.; Holzhauer, S.; Vulturius, G.; Rounsevell, M. D. A. The importance of socio-ecological system dynamics in understanding adaptation to global change in the forestry sector 2017. Journal of environmental management, 196, 36–47. doi:10.1016/j.jenvman.2017.02.066
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., Holzhauer, S., Metzger, M. J., Paterson, J. S., & Rounsevell, M. (2018). 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
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, 10, 809-845. https://doi.org/10.5194/esd-10-809-2019
Brown, C.; Holman, I.; Rounsevell, M. How modelling paradigms affect simulated future land use change. 2021. Earth System Dynamics, 12 (1), 211–231. doi:10.5194/esd-12-211-2021
Brown, C.; Seo, B.; Alexander, P.; Burton, V.; Chacón-Montalván, E. A.; Dunford, R.; Merkle, M.; Harrison, P. A.; Prestele, R.; Robinson, E. L.; Rounsevell, M. Agent‐Based Modeling of Alternative Futures in the British Land Use System 2022. Earth’s Future, 10 (11). doi:10.1029/2022EF002905
Brown, C.; Millington, J.; Rounsevell, M. Assessing the quality of land system models: moving from valibration to evaludation 2023. Socio-environmental Systems Modelling, 5, Art.Nr.: 18434. doi:10.18174/sesmo.18434
Brown, C.; Prestele, R.; Rounsevell, M. An assessment of future rewilding potential in the United Kingdom 2024. Conservation Biology, 38 (4), Art.-Nr.: e14276. doi:10.1111/cobi.14276
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
Millington, James D. A., Valeri Katerinchuk, Ramon Felipe Bicudo da Silva, Daniel de Castro Victoria, and Mateus Batistella. 2021. “Modelling Drivers of Brazilian Agricultural Change in a Telecoupled World.” Environmental Modelling & Software, February, 105024. https://doi.org/10.1016/j.envsoft.2021.105024
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
Perkins, O.; Alexander, P.; Arneth, A.; Brown, C.; Millington, J. D. A.; Rounsevell, M. Toward quantification of the feasible potential of land-based carbon dioxide removal 2023. One Earth, 6 (12), 1638–1651. doi:10.1016/j.oneear.2023.11.011
Seo, B., Brown, C., & Rounsevell, M. D. A. (2018). Evaluation and calibration of an agent based land use model using remotely sensed land cover and primary productivity data. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium(pp. 7476–7479). 10.1109/IGARSS.2018.8518023
Staccione, A., Brown, C., Arneth, A., Rounsevell, M., Essenfelder, A.H., Seo, B., Mysiak, J. (2023). Exploring the effects of Protected Area Networks on the European land system. Journal of Environmental Management, 337, 117741 https://doi.org/10.1016/j.jenvman.2023.117741
Synes, N. W.; Brown, C.; Watts, K.; White, S. M.; Gilbert, M. A.; Travis, J. M. J. Emerging Opportunities for Landscape Ecological Modelling. 2016. Current Landscape Ecology Reports, 1 (4), 146–167. doi:10.1007/s40823-016-0016-7
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
Urban, M. C.; Travis, J. M. J.; Zurell, D.; Thompson, P. L.; Synes, N. W.; Scarpa, A.; Peres-Neto, P. R.; Malchow, A.-K.; James, P. M. A.; Gravel, D.; De Meester, L.; Brown, C.; Bocedi, G.; Albert, C. H.; Gonzalez, A.; Hendry, A. P.
Coding for Life: Designing a Platform for Projecting and Protecting Global Biodiversity.
2021. BioScience. doi:10.1093/biosci/biab099
Zeng, Y.; Brown, C.; Byari, M.; Raymond, J.; Schmitt, T.; Rounsevell, M. InsNet-CRAFTY v1.0: Integrating institutional network dynamics powered by large language models with land use change simulation 2024. Copernicus. doi:10.5194/egusphere-2024-2661
Zeng, Y.; Brown, C.; Raymond, J.; Byari, M.; Hotz, R.; Rounsevell, M. Exploring the opportunities and challenges of using large language models to represent institutional agency in land system modelling 2025. Earth System Dynamics, 16 (2), 423–449. doi:10.5194/esd-16-423-2025
Zeng, Y.; Raymond, J.; Brown, C.; Byari, M.; Rounsevell, M. Simulating endogenous institutional behaviour and policy implementation pathways within the land system 2025. Ecological Modelling, 501, Article no: 111032. doi:10.1016/j.ecolmodel.2025.111032
Zeng, Y.; Raymond, J.; Brown, C.; Rounsevell, M. Exploring outcome-driven policymaking on protected areas with an endogenous institutional model 2025. Journal of Cleaner Production, 501, 145262. doi:10.1016/j.jclepro.2025.145262