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Humans currently spend over 3 billion person-hours per week playing computer games. Most of these games are purely for entertainment, but use of computer games for education has also expanded dramatically. At the same time, experimental games have become a staple of social science research but have depended on relatively small sample sizes and simple, abstract situations, limiting their range and applicability. If only a fraction of the time spent playing computer games could be harnessed for research, it would open up a huge range of new opportunities. We review the use of games in research, education, and entertainment and develop ideas for integrating these three functions around the idea of ecosystem services valuation. This approach to valuation can be seen as a version of choice modeling that allows players to generate their own scenarios taking account of the trade-offs embedded in the game, rather than simply ranking pre-formed scenarios. We outline a prototype game called “Lagom Island” to test the proposition that gaming can be used to reveal the value of ecosystem services. Our prototype provides a potential pathway and functional building blocks for approaching the relatively untapped potential of games in the context of ecosystem services research. [ABSTRACT FROM AUTHOR]

The Integrated History and future of People on Earth (IHOPE) initiative is a global network of researchers and research projects with its International Program Office (IPO) now based at the Stockholm Resilience Center (SRC), Uppsala University, Arizona State University, Portland State University, and the Australian National University. Research linked to IHOPE demonstrates that Earth system changes in the past have been strongly associated with changes in the coupled human–environment system. IHOPE supports integrating knowledge and resources from the biophysical and the social sciences and the humanities to address analytical and interpretive issues associated with coupled human–earth system dynamics. This integration of human history and Earth system history is a timely and important task. Until recently, however, there have been few attempts at such integration. IHOPE will create frameworks that can be used to help achieve this integration. The overarching goal is to produce a rich understanding of the relationships between environmental and human processes over the past millennia. IHOPE recognizes that one major challenge for reaching this goal is developing ‘workable’ terminology that can be accepted by scholars of all disciplines. The specific objectives for IHOPE are to identify slow and rapidly moving features of complex social–ecological systems, on local to continental spatial scales, which induce resilience, stress, or collapse in linked systems of humans in nature. These objectives will be reached by exploring innovative ways of conducting interdisciplinary and transdisciplinary science, including theory, case studies, and integrated modeling. Examples of projects underway to implement this initiative are briefly discussed. [ABSTRACT FROM AUTHOR]

This paper presents results from the MayaSim model, an integrated agent-based, cellular automata, and network model representing the ancient Maya social-ecological system. The model represents the relationship between population growth, agricultural production, soil degradation, climate variability, primary productivity, hydrology, ecosystem services, forest succession, and the stability of trade networks. Agents representing settlements develop and expand within a spatial landscape that changes under climate variation and responds to anthropogenic impacts. The model is able to reproduce spatial patterns and timelines somewhat analogous to that of the ancient Maya, although this proof-of-concept model requires refinement and further archaeological data for calibration. This paper aims to identify candidate features of a resilient versus vulnerable social-ecological system, and employs computer simulation to explore this topic, using the ancient Maya as an example. Complex systems modelling identifies how interconnected variables behave, considering fast-moving variables such as land cover change and trade connections, meso-speed variables such as demographics and climate variability, as well as slow-moving variables such as soil degradation. [ABSTRACT FROM AUTHOR]