Genetic variance–covariance matrices: A critique of the evolutionary quantitative genetics research program [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Biology and Philosophy 21 (1):1-23 (2006)
This paper outlines a critique of the use of the genetic variance–covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations – contrary to what assumed by most practicing biologists. I suggest that the search for a general solution to the difficult problem of identifying causal structures given observed correlation’s has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners.
|Keywords||quantitative genetics evolutionary theory G-matrices|
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Massimo Pigliucci (2012). On the Different Ways of ‘‘Doing Theory’’ in Biology. Biological Theory 7 (4):DOI 10.1007/s13752-012-0047-1.
Massimo Pigliucci (2010). Okasha's Evolution and the Levels of Selection: Toward a Broader Conception of Theoretical Biology. [REVIEW] Biology and Philosophy 25 (3):405-415.
Massimo Pigliucci (2008). The Proper Role of Population Genetics in Modern Evolutionary Theory. Biological Theory 3 (4):316-324.
Massimo Pigliucci (2009). Samir Okasha: Evolution and the Levels of Selection. Biology and Philosophy 24 (4):551-560.
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