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• Neglecting key interactions can lead to incorrect assessments and potentially inadequate alleviation strategies. • Cross-level interactions can reinforce or mitigate poverty traps. • Fractal traps are one of several types of traps in multi-level systems. Recent research has demonstrated the multidimensional nature of poverty and the multi-level organization of social-ecological systems that display poverty traps. The traps on these different levels can reinforce each other, and therefore multi-level traps pose particular challenges for poverty alleviation. Yet, poverty trap models rarely consider more than one level of organization and only a few attributes of the system at each level. These limitations constrain our understanding of the mechanisms that generate poverty traps and may hinder or even mislead development efforts. Here, we present a series of two-level dynamical system models of poverty traps and use these models to investigate the combined influences of biophysical and economic factors, farmers' habits and community decisions on creating and alleviating persistent poverty. Our results indicate that neglecting key interactions can lead to incorrect assessments and potentially inadequate alleviation strategies. Moreover, we obtain necessary conditions for the existence of fractal poverty traps, and show that (i) cross-level interactions can open possibilities for escaping from poverty, (ii) that farmers' behavioral changes may create or impede a way out of poverty, and (iii) that the effectiveness of development interventions depends on the combined influences of biophysical and economic dynamics, farmers' behavior and community spending on agricultural and social activities. [ABSTRACT FROM AUTHOR]

Preparing students for their future and qualifying them to enter public life is the essential role of the public-school system. As such, an understanding of climate science ought to be an essential – and significant – component of that preparation. This research proposes a novel pathway to teach climate science via a 3D interactive digital game and examines the potential of 12–13-year olds as a prepatent group for climate science interventions. After playing a proof-of-concept climate science game that covers the physical causes and mechanisms of climate change, 401 students in Austria and Australia were tested with a climate literacy questionnaire. Our results indicate that climate literacy can be improved in this age group via the digital game. In addition, we found further evidence of established climate science 'knowledge domains' in this age group that form a natural 'increased levels of complexity' scaffold that can be used to design curricula such as that in the digital game. These four 'knowledge domains' are (in brief): Earth in the solar system; gravity and its effect on the atmosphere; albedo and solar radiation, and; greenhouse gases and their warming potential. • 3D interactive digital games allow students to 'see' how the climate system works which may improve learning outcomes. • 3D interactive environments allow students to explore worrisome issues in an abstract, non-threatening learning environment. • A world-first climate literacy framework based on tested learning outcomes and knowledge domains in 12–13-year-olds. • A world-first strategy to circumvent worldview bias by targeting early adolescents prior to worldview development. • This approach avoids worldview biasing, misinformation and confusion amongst teachers. [ABSTRACT FROM AUTHOR]

As conservation biology has matured, its scope has expanded from a primarily ecological focus to recognition that nearly all conservation problems involve people. At the same time, conservation actions have been increasingly informed by ever more sophisticated quantitative models. These models have focused primarily on ecological and geographic elements of conservation problems, such as mark-recapture methods, predicting species occurrences, and optimizing the placement of protected areas. There are many off-the-shelf ecological models for conservation managers to draw upon, but very few that describe human-nature interactions in a generalizable manner. We address this gap by proposing a minimalistic modeling framework for human-nature interactions, combining well-established ideas in economics and social sciences (grounded in Ostrom's social-ecological systems framework) and accepted ecological models. Our approach begins with a systems breakdown consisting of an ecosystem, resource users, public infrastructure, and infrastructure providers; and interactions between these system elements, which bring together the biophysical context, the relevant attributes of the human society, and the rules (institutions, such as protected areas) currently in use. We briefly review the different disciplinary building blocks that the framework could incorporate and then illustrate our approach with two examples: a detailed analysis of the social-ecological dynamics involved in managing South African protected areas and a more theoretical analysis of a general system. We conclude with further discussion of the urgent need in conservation biology for models that are genuinely designed to capture the complexities of human socioeconomic behavior, rather than the more typical approach of trying to adapt an ecological model or a stochastic process to simulate human agency and decision-making. Our framework offers a relatively simple but highly versatile way of specifying social-ecological models that will help conservation biologists better represent critical linkages between social and ecological processes when modeling social-ecological dynamics. • A framework for conceptualizing and modeling social-ecological systems is presented. • Supporting modeling 'building blocks' are presented for conservation problems. • Application of the framework is illustrated for two conservation problems. • Utility of the framework for improving conservation outcomes is discussed. [ABSTRACT FROM AUTHOR]