Interdisciplinary collaborations are increasingly common in many areas of science, but particularly in fields involved with environmental problems. This is because problems related to human interactions with the environment typically contain numerous parameters, reflect extensive human alterations of ecosystems, require understanding of physical–biological interactions at multiple spatial and temporal scales, and involve economic and social capital. Distilling useful scientific information in collaborative interactions is a challenge, as is the transfer of this information to others, including scientists, stakeholders, resource managers, policymakers, and the public. While this problem has been recognized by historians and philosophers of science, it has rarely been recognized and openly discussed by scientists themselves (but see NAS 1986). The participation of individuals from a diverse set of scientific disciplines has the potential to enhance the success of problem solving (USGS/ESA 1998). However, obstacles often arise in collaborative efforts for several well-known reasons. First, it is often difficult to find a common language because of disciplinary specialization (Wear 1999, Sarewitz et al. 2000). Second, existing scientific knowledge (theories, models, etc.) may reflect a historical scientific and sociopolitical context that may make it ill suited to address current environmental problems and questions (see, for example, Ford 2000, NSB 2000). Third, collaborations involving multiple disciplines may create difficulties owing to mismatches in space and time scales, in forms of knowledge (e.g., qualitative versus quantitative), and in levels of precision and accuracy (see, for example, Herrick 2000). Fourth, scientists are partly conditioned by nonscientific values. A social fabric may dictate scientists' worldviews, lead them to favor certain assumptions over others, and underlie the way they study ecosystems (Boyd et al. 1991).
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Benda et al. (2002) studied this question.
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