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

Calum Brown, Peter Alexander, Sascha Holzhauer and Mark D. A. Rounsevell

Wiley Interdisciplinary Reviews: Climate Change, 2017, vol. 8, issue 2

Abstract: 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

Date: 2017
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