, Volume 5, Issue 4, pp 376-384

First online:

Ten Heuristics for Interdisciplinary Modeling Projects

  • Craig R. NicolsonAffiliated withDepartment of Natural Resources Conservation, University of Massachusetts, Box 34210, Amherst, Massachusetts 01003-4210, USA
  • , Anthony M. StarfieldAffiliated withDepartment of Ecology, Evolution and Behavior, University of Minnesota, 1987 Upper Buford Circle, St Paul, Minnesota 55018, USA
  • , Gary P. KofinasAffiliated withInstitute of Arctic Studies, Dartmouth College, 6214 Fairchild, Hanover, New Hampshire 03755, USA
  • , John A. KruseAffiliated withInstitute of Social and Economic Research, University of Alaska–Anchorage, 3211 Providence Drive, Anchorage, Alaska 99508, USA

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Complex environmental and ecological problems require collaborative, interdisciplinary efforts. A common approach to integrating disciplinary perspectives on these problems is to develop simulation models in which the linkages between system components are explicitly represented. There is, however, little guidance in the literature on how such models should be developed through collaborative teamwork. In this paper, we offer a set of heuristics (rules of thumb) that address a range of challenges associated with this enterprise, including the selection of team members, negotiating a consensus view of the research problem, prototyping and refining models, the role of sensitivity analysis, and the importance of team communication. These heuristics arose from a comparison of our experiences with several interdisciplinary modeling projects. We use one such experience—a project in which natural scientists, social scientists, and local residents came together to investigate the sustainability of small indigenous communities in the Arctic—to illustrate the heuristics.

Key Words: interdisciplinary; modeling; ecosystem; collaboration; sustainability; Arctic; integrated assessment; teamwork.