Model-Based Synthesis of Locally Contingent Responses to Global Market Signals

Magliocca, Nicholas R.

doi:10.3390/land4030807

Cited by 7 publications

(6 citation statements)

References 71 publications

(155 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3,10,41,96,116 This often involves simple models that can illuminate areas of uncertainty or potential developments that were previously unrecognized. 11,22,51,86,117 Obvious and achievable contributions here include assessments of the role of diffusion in attitudes, knowledge, or uptake of novel practices, 46,98 the potential for particular aspects of local knowledge to alter the impacts of global drivers of change, 58,79,118,119 and the effects of changes in ecosystem service provision on societal and individual decision-making. 56,58,117 More comprehensive analyses face the challenge of incorporating social and ecological systems dynamics more fully.…”

Section: Discussionmentioning

confidence: 99%

Behavioral models of climate change adaptation and mitigation in land‐based sectors

Brown

Alexander

Holzhauer

et al. 2017

WIREs Climate Change

View full text Add to dashboard Cite

Models of the land system are essential to our understanding of the magnitude and impacts of climate change. These models are required to represent a large number of processes in different sectors, but face particular challenges in describing the individual and social behaviors that underpin climate change mitigation and adaptation. We assess descriptions of these behaviors in existing models, their commonalities and differences, and the uses to which they have been put. We find that behavioral models have a distinct and important role to play in climate research, but that they currently suffer from being strongly sectoral in nature, with agricultural models being the most common and behaviorally rich. There are also clear convergences, with economic‐based decision‐making remaining dominant and behaviors such as diffusion, interaction, anticipation, or learning remaining relatively neglected. Active climate change is also rarely modeled, with adaptation and mitigation generally represented as responses to economic drivers under static climatic conditions. Furthermore, dynamic behaviors, objectives, or decision‐making processes are almost entirely absent, despite their clear relevance to climate change responses. We conclude that models have been more successful in the identification of important processes than in their implementation and that, while some behavioral processes may remain impossible to model, behavioral models of adaptation and mitigation in land‐based sectors have substantial unexplored potential. We suggest that greater attention be paid to the cumulative coverage of models in this field, and that improvements in the representation of certain key behaviors be prioritized. WIREs Clim Change 2017, 8:e448. doi: 10.1002/wcc.448 This article is categorized under: Assessing Impacts of Climate Change > Representing Uncertainty

show abstract

Section: Discussionmentioning

confidence: 99%

Behavioral models of climate change adaptation and mitigation in land‐based sectors

Brown

Alexander

Holzhauer

et al. 2017

WIREs Climate Change

View full text Add to dashboard Cite

show abstract

“…national-continental) scales hold promise for the unification of existing areas of knowledge (e.g. van Asselen and Verburg 2013 ; Magliocca 2015 ; Blanco et al 2017 ), as well as allowing modelling at scales more congruent with real-world adaptation processes and effects. In particular, the inclusion of specific adaptation actors and land or water systems that operate across regional scales is a necessary step forward.…”

Section: Discussionmentioning

confidence: 99%

Improving the representation of adaptation in climate change impact models

et al. 2018

View full text Add to dashboard Cite

Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.Electronic supplementary materialThe online version of this article (10.1007/s10113-018-1328-4) contains supplementary material, which is available to authorized users.

show abstract

“…Throughout each simulation, land use maps, numbers of agents in each AFT, ecosystem service production levels and fragmentation indices (fractal dimensions) were recorded. Fractal dimension (Mandelbrot, 1983) was used to capture the patch sizes of each land use, with higher values indicating more complex patterns, and was compared on the basis of relative change from the baseline year using the R package SDMTools (Vanderwal et al, 2014).…”

Section: Simulation Schedulementioning

confidence: 99%

“…Alternative, well-supported conceptualisations of the human land use system are available, and some have been formalised in agent-based or behavioural models that focus on individual-level decisions from which system properties emerge (e.g. Arneth et al, 2014;Brown et al, 2016bBrown et al, , 2017Fagiolo and Roventini, 2017;Magliocca, 2015;Rounsevell et al, 2012b). To date, these models have been limited in scope, mainly operating only in specific contexts or over small geographical areas (e.g.…”

Section: Introductionmentioning

confidence: 99%

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

2019

View full text Add to dashboard Cite

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.

show abstract

Model-Based Synthesis of Locally Contingent Responses to Global Market Signals

Cited by 7 publications

References 71 publications

Behavioral models of climate change adaptation and mitigation in land‐based sectors

Behavioral models of climate change adaptation and mitigation in land‐based sectors

Improving the representation of adaptation in climate change impact models

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

Contact Info

Product

Resources

About