Towards representing human behavior and decision making in Earth system models – an overview of techniques and approaches

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

doi:10.5194/esd-8-977-2017

Cited by 77 publications

(89 citation statements)

References 189 publications

(176 reference statements)

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“…In order to move towards these goals, we have developed CRAFTY-EU, a continental-scale, agent-based model of the European land system based on the CRAFTY modelling framework (Murray-Rust et al, 2014). We describe the design, calibration and evaluation of this model before using it to explore future developments in Europe's land system under a range of climatic and socio-economic scenarios.…”

Section: Introductionmentioning

confidence: 99%

Societal breakdown as an emergent property of large-scale behavioural models of land use change

2019

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Abstract. Human land use has placed enormous pressure on natural resources and ecosystems worldwide and may even prompt socio-ecological collapses under some circumstances. Efforts to avoid such collapses are hampered by a lack of knowledge about when they may occur and how they may be prevented. Computational models that illuminate potential future developments in the land system are invaluable tools in this context. While such models are widely used to project biophysical changes, they are currently less able to explore the social dynamics that will be key aspects of future global change. As a result, strategies for navigating a hazardous future may suffer from “blind spots” at which individual, social and political behaviours divert the land system away from predicted pathways. We apply CRAFTY-EU, an agent-based model of the European land system, in order to investigate the effects of human behavioural aspects of land management at the continental scale. We explore a range of potential futures using climatic and socio-economic scenarios and present a coherent set of cross-sectoral projections without imposed equilibria or optimisation. These projections include various behavioural responses to scenarios including non-economic motivations, aversion to change and heterogeneity in decision-making. We find that social factors and behavioural responses have dramatic impacts on simulated dynamics and can contribute to a breakdown of the land system's essential functions in which shortfalls in food production of up to 56 % emerge. These impacts are largely distinct from, and at least as large as, those of projected climatic change. We conclude that the socio-economic aspects of future scenarios require far more detailed and varied treatment. In particular, deviation from simple economic rationality at individual and aggregate scales may profoundly alter the nature of land system development and the achievability of policy goals.

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Section: Introductionmentioning

confidence: 99%

Societal breakdown as an emergent property of large-scale behavioural models of land use change

2019

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“…As a result, the human behavior incorporated in coupled SES models is often rudimentary compared to the state of the art in social science modeling, and as such out of touch with current social theory. Recent reviews on approaches to represent the social dimension in SES models discuss this problem in detail (Müller-Hansen et al, 2017;Schlüter et al, 2017).…”

Section: 6mentioning

confidence: 99%

Eight grand challenges in socio-environmental systems modeling

Elsawah

Filatova

Jakeman

et al. 2020

SESMO

130

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Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices.

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“…Critically, all stakeholders involved in resource conservation are constrained in their decision‐making; managing and using resources takes effort (e.g. time or money), and effort expended in developing or enforcing one policy (for managers) or performing one action (for users) will be effort not expendable elsewhere (Milner‐Gulland, ; Müller‐Hansen et al., ; Schlüter et al., ). In finding strategies, GMSE models this trade‐off by setting a fixed budget for managers and users.…”

Section: Genetic Algorithmmentioning

confidence: 99%

GMSE: An r package for generalised management strategy evaluation

et al. 2018

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Management strategy evaluation (MSE) is a powerful tool for simulating all key aspects of natural resource management under conditions of uncertainty. We present the r package generalised management strategy evaluation (GMSE), which applies genetic algorithms to provide a generalised tool for simulating adaptive decision‐making management scenarios between stakeholders with competing objectives under complex social‐ecological interactions and uncertainty. GMSE models can be agent‐based and spatially explicit, incorporating a high degree of realism through mechanistic modelling of links and feedbacks among stakeholders and with the ecosystem; additionally, user‐defined sub‐models can also be incorporated as functions into the broader GMSE framework. We show how GMSE simulates a social‐ecological system using the example of an adaptively managed waterfowl population on an agricultural landscape; simulated waterfowl exploit agricultural land, causing conflict between conservation interests and the interest of food producers maximising their crop yield. The r package GMSE is open source under GNU Public License; source code and documents are freely available on GitHub.

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Towards representing human behavior and decision making in Earth system models – an overview of techniques and approaches

Cited by 77 publications

References 189 publications

Societal breakdown as an emergent property of large-scale behavioural models of land use change

Societal breakdown as an emergent property of large-scale behavioural models of land use change

Eight grand challenges in socio-environmental systems modeling

GMSE: An r package for generalised management strategy evaluation

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