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KIT – The Research University in the Helmholtz Association
INSTITUTE OF METEOROLOGY AND CLIMATE RESEARCH, ATMOSPHERIC ENVIRONMENTAL RESEARCH, IMK-IFU
www.imk-ifu.kit.edu
Process-based modelling of socio-ecological systems
Calum Brown
Land Use Change Research Group
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group2 Calum Brown20.09.2018
Source: Department for International Trade
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group3
UK consumption patterns drive global land use change
Calum Brown20.09.2018
de Ruiter H, Macdiarmid JI, Matthews RB, Kastner T, Smith P. 2016 Global cropland and greenhouse gas impacts of UK food supply are increasingly located overseas. J. R. Soc. Interface 13: 20151001.
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group4
Fuchs, R., et al. (2015). Gross changes in reconstructions of historic land cover/use for Europe between 1900 and 2010. Global Change Biology 21, 1
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group5
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group6 Calum Brown20.09.2018
Domestic livestock production exceeds ‘safe
operating space’ for greenhouse gas emissions,
biodiversity loss and nutrient flows
Buckwell, A. and Nadeu, E. 2018. What is the Safe Operating Space for EU Livestock? RISE Foundation, Brussels.
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group7 Calum Brown
Climate impacts
20.09.2018
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group8
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group9
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group10 Calum Brown
Behavioural process examples - diffusion
20.09.2018
Alexander, P., Moran, D., Rounsevell, M. & Smith, P. Modelling the perennial energy crop market: the role of spatial diffusion. J. R. Soc. Interface 10, (2013)
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group11 Calum Brown
Land system change – diffusion of innovations
20.09.2018
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group12 Calum Brown
Climate change adaptation
20.09.2018
Vulturius, G., André, K., Swartling, Å, Brown, C., Rounsevell, M., Blanco, V. (2018). Explaining engagement with climate change adaptation among forest owners in Sweden, Regional Environmental Change
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group13 Calum Brown
Modelling socio-ecological systems
• Land system models must take account of human behaviour
• Makes accurate prediction impossible, and uncertainty analysis essential
• Validation should not be a process of (over-) fitting to historical observations;
ability to produce range of ‘counter-factuals’ crucial to model validity
• Under novel social, economic and climatic conditions, we can‘t use the past
as a guide to the future
• Also account for interactions with complex ecological systems; feedback
dynamics
20.09.2018
Brown et al. 2016, Modeling Earth Systems and Environment
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group14 Calum Brown
Modelling climate change adaptation
20.09.2018
Brown, C., Alexander, P., Holzhauer, S., Rounsevell, M. (2017). Behavioural models of climate change adaptation and mitigation in land-based sectors. WIREs Climate Change, e448. doi: 10.1002/wcc.448
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group15 Calum Brown
Modelling climate change adaptation
20.09.2018
Brown, C., Alexander, P., Holzhauer, S., Rounsevell, M. (2017). Behavioural models of climate change adaptation and mitigation in land-based sectors. WIREs Climate Change, e448. doi: 10.1002/wcc.448
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group16 Calum Brown
Model validation and uncertainty analysis
20.09.2018
Brown, C., Alexander, P., Holzhauer, S., Rounsevell, M. (2017). Behavioural models of climate change adaptation and mitigation in land-based sectors. WIREs Climate Change, e448. doi: 10.1002/wcc.448
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group17 Calum Brown
Science-policy gaps
20.09.2018
Winkler, K., Scown, M., Nicholas, K. (2018). A classification to align social-ecological land systems research with policyin Europe. Land Use Policy, 79.
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group18
Jongman RHG, Bouwma IM, Van Doorn A (2006) Indicative map of the pan-European ecological network in Western Europe. Technical Background Document. Alterra Report 1429
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group19
Impacts on biodiversity
Hallman et al. 2017, More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS One
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group20
Impacts on biodiversity
IPCC ‘A2a’ scenario, 2080
Balint et al. (2011). Cryptic biodiversity loss linked to global climate change. Nature Climate Change 1, 313-318
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group21
WrEN project106 secondary and 27 ancient woodland sites:
• vascular plants - 177 species;
• lichens - 172 species,
• bryophytes - 77 species
• small mammals - 15,000 trap nights, 1700 individuals, 4 species
• bats - 1700 hours of acoustic recording, 6 species/genera
• birds - 8000 records of 59 species
• spiders - 4000 individuals, 103 species
• beetles - 30,000 individuals, 130 species
• craneflies - 5000 individuals, 104 species
• hoverflies - 1300 individuals, 63 species
• moths - 11,289 individuals, 257 species
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group22
Process-based modelling
• Agent/individual-based modelling
• Focus on individual-level behaviour & interactions
• Stochastic, non-equilibrium, path-dependent
• Capable of producing a wide range of outcomes
• Increasingly computationally efficient and scaleable
• Share a basic architecture that allows for model coupling
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group23
‘Competition for resources between Agent
Functional Types (CRAFTY) model
• Allow modelled land managers to
compete for land on the basis of
the ecosystem services they
provide to society
• Includes economic and non-
economic motivations
• Supply ≠ demand
RCP 2.6 – SSP1
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group24 Calum Brown
European modelling: CRAFTY-EU
20.09.2018
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group25 Calum Brown
European modelling: CRAFTY-EU
20.09.2018
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group26 Calum Brown
European modelling: CRAFTY-EU
20.09.2018
Agent type
Intensive arable
Extensive arable
Intensive pasture
Extensive pasture
Very extensive pasture
Intensive agro-forestry mosaic
Extensive agro-forestry mosaic
Managed forest
Unmanaged forest
Marginal multifunctional
Unmanaged land
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group27 Calum Brown
European modelling: CRAFTY-EU
20.09.2018
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group28
(Carine Petit, thèse de doctorat, UCL, 2001)
Calum Brown
Historical parallels
20.09.2018
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group29
RangeShifter
Species’ eco-evolutionary
responses to environmental
change
Represents dispersal,
reproduction and genetic
change
Can be run on dynamic
(modelled) landscapes to
assess future ecological change
Bocedi et al 2014, RangeShifter: a platform for modelling spatial eco‐evolutionary dynamics and species' responses to environmental changes,Methods in Ecology and Evolution
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group30 Calum Brown
Model integration
• CRAFTY-Rangeshifter coupling to investigate pollinator
population dynamics in agricultural landscape
20.09.2018
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group31
Madingley
‘next-generation’ model of
ecosystems and biodiversity
Cohort-based ecological dynamics
within terrestrial and marine
environments
Modelled ecosystems respond to
Human Appropriation of Net Primary
Productivity (HANPP)
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group32 Calum Brown20.09.2018
Model integration
Institute of Meteorology and Climate Research, IMK-IFU, Land Use Change Research Group33 Calum Brown
Challenges
20.09.2018
• ‘Micro’ processes can have macro consequences…
• but understanding of basic processes still needs to be translated into large-scale
models
• We need computationally efficient methods for modelling and model evaluation
• Uncertainty must be explored and communicated
• Diversity of modelling approaches needed
• Find balance between process accuracy and large-scale approximation
• Better reflect policy-relevant outcomes
KIT – The Research University in the Helmholtz Association
INSTITUTE OF METEOROLOGY AND CLIMATE RESEARCH, ATMOSPHERIC ENVIRONMENTAL RESEARCH, IMK-IFU
www.imk-ifu.kit.edu
Thank you
