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The status of dynamic quantitative modeling in ecology

William Lauenroth, Indy Burke and 1 other contributor

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    Abstract

    Dynamic quantitative modeling in the broadest sense has been a part of ecology since early in the twentieth century. It began in the form of mathematical population theory and was expanded in midcentury by the addition of systems analysis and ecosystem modeling. Because modeling is an important and productive activity for a scientific discipline, the status of modeling can be used as an indicator of the state of the discipline. Our objective was to evaluate the current state of ecology with respect to dynamic quantitative modeling and to speculate about profitable future directions for incorporation of dynamic quantitative modeling. We evaluated the state of modeling in ecology in two ways. First, we assessed the attitudes of ecologists about quantitative modeling, and second, we evaluated the degree to which quantitative modeling is being used as a research tool in ecology. We assessed the attitudes of ecologists toward quantitative modeling by conducting a survey of a random 20% sample of the membership of the Ecological Society of America. We sent 1,535 e-mail invitations to participate in the survey, and 350 ecologists responded. As a separate analysis we evaluated the degree to which quantitative modeling is currently being used as a research tool in ecology by assessing the frequency and kind of modeling that was published in the journals Ecology and Ecological Applications in 1996,1998, and 2000. We found that ecologists are overwhelmingly supportive of an important role for dynamic quantitative modeling in both past discoveries and future advancement of knowledge. This was true for population, ecophysiological, community, and ecosystem ecologists. By contrast, we discovered that only 17% of the papers published in what are arguably the premier journals in the field employed dynamic quantitative modeling. This difference, representing what individuals say and what is represented in our journals, may be explained by limited availability of training in quantitative modeling. While most ecologists recognize the potential value, relatively few have appropriate training to allow them to make effective use of dynamic quantitative modeling. Our results suggest that an effective way to address this problem is to establish opportunities for relationships between undergraduate and graduate students and ecologists who are using modeling in their research. Our conclusion, conditioned on the limitation of our sample, is that ecologists are ready to make much more effective use of dynamic quantitative modeling than they have in the past. Our major challenge is to decide how to most effectively make the necessary skills available to ecological researchers.