Collaboration Across Boundaries: Reflections on Studying the Sustainability of the Mississippi River Delta as a Coupled Natural-Human System
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We report in this chapter our experience in collaboration across boundaries from working on an interdisciplinary project funded by the National Science Foundation under the Dynamics of Coupled Natural-Human Systems program. The project investigates the sustainability of the Mississippi River Delta (MRD), which is considered one of the most vulnerable coastal zones in the continental United States and the world. Our overarching research question is: will the MRD reach a tipping point that would make it difficult to sustain in the future? The project consists of seven components, each led by investigators from disciplines including hydrology, sedimentology, ecology, geography, political science, economics, and finance. We conducted a survey of the team members to obtain their opinions on the challenges, benefits, and suggestions for improvement regarding collaboration across disciplinary boundaries. The results provide insights into the development of best practice for collaboration across boundaries. Survey results suggest that a successful interdisciplinary project would need a detailed research plan with timelines and expected results stated, and the plan would need to be followed through. Finding collaborators who have similar priorities, can deliver the results on time, and continue engagement in the research is difficult, but the reward in making it happen is gratifying because it will ultimately be beneficial to advancing the science and practice of sustaining complex natural-human systems.
author list (cited authors)
Lam, N., Xu, Y. J., Pace, R. K., Liu, K., Qiang, Y. i., Narra, S., ... Mihunov, V.
complete list of authors
Lam, Nina S-N||Xu, Y Jun||Pace, R Kelley||Liu, Kam-biu||Qiang, Yi||Narra, Siddhartha||Bianchette, Thomas A||Cai, Heng||Zou, Lei||Li, Kenan||Joshi, Sanjeev||Mihunov, Volodymyr
editor list (cited editors)
Collaboration Across Boundaries for Social-Ecological Systems Science