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Figuring Out the Human Dimensions of Fisheries: Illuminating Models
Author(s) -
HallArber Madeleine,
Pomeroy Caroline,
Conway Flaxen
Publication year - 2009
Publication title -
marine and coastal fisheries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.664
H-Index - 28
ISSN - 1942-5120
DOI - 10.1577/c09-006.1
Subject(s) - interdependence , context (archaeology) , fisheries management , data science , point (geometry) , computer science , qualitative property , knowledge management , management science , fishery , sociology , fishing , geography , social science , engineering , biology , geometry , mathematics , archaeology , machine learning
Both natural scientists and economists commonly use quantitative data to create models of the systems that interest them and then use these models to inform fisheries management. Other social scientists rely on lengthier, descriptive texts based primarily on qualitative data to assess the human dimensions. To their dismay, fisheries social scientists find that much of their rich narrative with keen insights ends up filling pages that are neither read nor meaningfully integrated into decision‐making in fisheries management. Nevertheless, what all scientists, practitioners, and managers want and need is information that will lead to a better understanding of the ecosystem (comprised of interdependent ecological and human systems) and therefore to fisheries management that benefits the whole system. Based on the belief that only a combination of high‐quality quantitative and qualitative data will provide both the numbers and the context needed for success in ecosystem‐based management, we discuss efforts to present social and cultural information in forms that are more familiar to those who rely on models for a representation of reality in the fisheries context. We point out how the designers of these models (or how we) think the models might be applied to fisheries management, noting how each model attempts to incorporate qualitative data to depict context essential for grounding the more commonly used biological and economic models. We also assess the benefits and limitations of these models, including the constraints on their development and use.

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