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Governments, businesses, and civil society organizations have diverse policy tools to incentivize adaptation. Policy tools can shape the type and extent of adaptation, and therefore, function either as barriers or enablers for reducing risk and vulnerability. Using data from a systematic review of academic literature on global adaptation responses to climate change (n = 1549 peer-reviewed articles), we categorize the types of policy tools used to shape climate adaptation. We apply qualitative and quantitative analyses to assess the contexts where particular tools are used, along with equity implications for groups targeted by the tools, and the tools’ relationships with transformational adaptation indicators such as the depth, scope, and speed of adaptation. We find diverse types of tools documented across sectors and geographic regions. We also identify a mismatch between the tools that consider equity and those that yield more transformational adaptations. Direct regulations, plans, and capacity building are associated with higher depth and scope of adaptation (thus transformational adaptation), while economic instruments, information provisioning, and networks are not; the latter tools, however, are more likely to target marginalized groups in their design and implementation. We identify multiple research gaps, including a need to assess instrument mixes rather than single tools and to assess adaptations that result from policy implementation. Key policy insights Information-based approaches, networks, and economic instruments are the most frequently documented adaptation policy tools worldwide. Direct regulations, plans, and capacity building are associated with higher depth and scope of adaptation, and thus more transformational adaptation. Capacity building, economic instruments, networks, and information provisioning approaches are more likely to target specific marginalized groups and thus equity challenges. There are many regions and sectors where certain tools are not widely documented (e.g. regulations and plans in Africa and Asia), representing a key research gap.

Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses.

New theoretical agent-based model of population-wide adoption of prosocial common-pool behavior with four parameters (initial percent of adopters, pressure to change behavior, synergy from behavior, and population density); dynamics in behavior, movement, freeriding, and group composition and size; and emergence of multilevel group selection. Theoretical analysis of model's dynamics identified six regions in model's parameter space, in which pressure-synergy combinations lead to different outcomes: extinction, persistence, and full adoption. Simulation results verified the theoretical analysis and demonstrated that increases in density reduce number of pressure-synergy combinations leading to population-wide adoption; initial percent of contributors affects underlying behavior and final outcomes, but not size of regions or transition zones between them; and random movement assists adoption of prosocial common-pool behavior. [ABSTRACT FROM AUTHOR]

Prosocial common-pool behavior – subtractable and non-excludable behavior that benefits others – is essential for the survival of any population of social individuals. The behavior, however, usually carries a cost to those who contribute it, placing them at a disadvantage with respect to those who freeride – those who do not contribute but still benefit. How populations sustain existing or adopt new prosocial common-pool behaviors remains unclear. We introduce a theoretical agent-based model and use it to study the role of social identity in a population’s adoption of such behavior. Social identity is relevant because it influences the behavior of individuals in a group, including their willingness to behave prosocially. Our model simulates the emergence of multiple and dynamic social identities of agents within self-organizing groups. Our simulation results suggest that the role of social identity may depend substantially on the density of the population and the commitment level of population members to their groups; that the relationship between density, commitment, and adoption may be nuanced; that, under lower density levels, mobility between groups may be essential; and that the persistence and adoption of prosocial behavior in a population may be overwhelmingly driven by individuals who are highly committed to their groups. The results caution against the influence of two looming worldwide trends – an increase in population density and a decrease in group commitment. The results suggest that, when combined, these two trends may produce the lowest adoption levels of prosocial behavior, the adverse and population-wide repercussions of which could be catastrophic. Finally, our results suggest that social identity may play a helpful role in offsetting the consequences of these trends, implying a need for further empirical and experimental study of the subject and future consideration of incorporating the role of social identity into policy analysis and design. [ABSTRACT FROM AUTHOR]

This article introduces two tools aimed at improving our understanding of the relationship between human and artificial rationality and helping us identify agents that are false positives or negatives. The first is a framework that systematically exposes where and how discrepancies between human and artificial rationalities can arise. The second is a test that utilises the insight gained from applying the framework in testing the ability of an artificial agent to represent human decision-making. To demonstrate the usefulness of the test, the article describes its application in testing the ability of a set of Individual Evolutionary Learning agents to represent human decision-making in a social psychology experiment, called the Voluntary Contributions Mechanism. In contrast to the results of a prior test that relied on a behaviour-based method, the results of this test show that the ability of these artificial agents to replicate the behaviour of their human counterparts is not a reliable indicator of their ability to represent their decision-making. The article then uses insight from the test to suggest how to improve the ability of Individual Evolutionary Learning agents to represent human decision-making in the Voluntary Contributions Mechanism. [ABSTRACT FROM AUTHOR]