Abstract:
Most social-ecological issues of great importance to human well-being, such as climate change, biodiversity loss, and overexploitation of natural resources are embedded within coupled human and natural systems. Problem-solving and decision-making in these complex systems is difficult. Understanding these issues requires identifying nonlinearities, feedback loops, and integrating different forms of knowledge to create socio-ecological models that allow various decision-makers to better communicate the dynamics of these issues in an effort to make equitable decisions for sustainability. However, creating such models is challenging. Model building too often lags behind conservation decision-making needs because of gaps in scientific knowledge about how these systems are structured, problems with data scarcity, and the challenges in working across different disciplines and with different stakeholder communities. In this talk I outline several emerging ‘Collective Intelligence’ (CI) approaches (e.g., participatory modeling, wisdom of crowds, swarm intelligence) that engage diverse stakeholders and scientists to better understand the nature of complex environmental problems given different conservation data goals (estimating populations and harvesting pressure locally, modeling social and ecological linkages, and estimating uncertain climate change impacts regionally) in a quick but robust manner. Using three empirical fishery case studies I will demonstrate how technological approaches to harnessing the CI of large groups is an efficient way to improve computational model building, increase model validity and better support participatory forms of environmental governance and decision-making.
Bio: Dr. Steven Gray is Professor in the Department of Community Sustainability at Michigan State University. His research focuses on socio-environmental modeling and understanding how individuals and groups make decisions about complex social-ecological systems. He is the lead editor on the book, Environmental Modeling with Stakeholders: Methods, Theories and Applications and lead developer of the participatory modeling software, Mental Modeler. He received his undergraduate degree from the University of Texas at Austin in Anthropology, MS in Geography from Texas State University, and PhD in Ecology and Evolution from Rutgers University.