Transdisciplinary Climate Research to Support Decision Making

• Main Author: Ferguson, Daniel B.
• Other Authors: Woodhouse, Connie
• Language: en_US
• Published: The University of Arizona. 2015
• Subjects: Geography
• Online Access: http://hdl.handle.net/10150/556812

Climate research holds great promise for helping societies around the world adapt to what are likely to be dramatic changes in social-ecological systems in the 21st century. The climate research community has made enormous strides forward over the last 30 years in understanding how the climate system operates, the primary drivers of change, the complex interactions between humans and their landscapes, and the ways that people make decisions and utilize new information. The pace of that progress, though, has not been matched by use of all this new knowledge in climate-relevant decision processes. The work presented in this dissertation addresses this mismatch and starts with the assumption that one of the fundamental barriers between the research that we carry out and the research that gets utilized in society is the prevalence of a disconnect between scientists and those who could use scientific information. The central question that links the three articles that make up the substantive contribution of this dissertation is: how can scientists and other experts in society more successfully collaborate to develop the kinds of transgressive knowledge necessary to address complex, climate-related problems? The articles address this question by exploring and adding to theoretical insights about this disconnect (Appendix 1), describing findings from the practice of research meant to address a pressing climate-related problem (Appendix 2), and reviewing lessons we have learned from work to evaluate use-inspired, engaged climate research (Appendix 3). Each article offers specific insights and results, but collectively this work demonstrates the value and importance of transdisciplinary research that fosters integration of different kinds of knowledge to address highly complex problems.