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. 2006 Nov 1;40(21):6547-54.
doi: 10.1021/es061030q.

Evaluation of the current state of mechanistic aquatic biogeochemical modeling: citation analysis and future perspectives

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Evaluation of the current state of mechanistic aquatic biogeochemical modeling: citation analysis and future perspectives

George B Arhonditsis et al. Environ Sci Technol. .

Abstract

We examined the factors that determine the citations of 153 mechanistic aquatic biogeochemical modeling papers published from 1990 to 2002. Our analysis provides overwhelming evidence that ocean modeling is a dynamic area of the current modeling practice. Models developed to gain insight into the ocean carbon cycle/marine biogeochemistry are most highly cited, the produced knowledge is exported to other cognitive disciplines, and oceanic modelers are less reluctant to embrace technical advances (e.g., assimilation schemes) and more critically increase model complexity. Contrary to our predictions, model application for environmental management issues on a local scale seems to have languished; the pertinent papers comprise a smaller portion of the published modeling literature and receive lower citations. Given the critical planning information that these models aim to provide, we hypothesize that the latter finding probably stems from conceptual weaknesses, methodological omissions, and an evident lack of haste from modelers to adopt new ideas in their repertoire when addressing environmental management issues. We also highlight the lack of significant association between citation frequency and model complexity, model performance, implementation of conventional methodological steps during model development (e.g., validation, sensitivity analysis), number of authors, and country of affiliation. While these results cast doubt on the rationale of the current modeling practice, the fact that the Fasham et al. (1990) paper has received over 400 citations probably dictates what should be done from the modeling community to meet the practical need for attractive and powerful modeling tools.

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