Comparative Quantitative Genetics: Evolution of the G Matrix

Trends in Ecology and Evolution 17 (7):320-327 (2002)
  Copy   BIBTEX

Abstract

Quantitative genetics provides one of the most promising frameworks with which to unify the fields of macroevolution and microevolution. The genetic variance–covariance matrix (G) is crucial to quantitative genetic predictions about macroevolution. In spite of years of study, we still know little about how G evolves. Recent studies have been applying an increasingly phylogenetic perspective and more sophisticated statistical techniques to address G matrix evolution. We propose that a new field, comparative quantitative genetics, has emerged. Here we summarize what is known about several key questions in the field and compare the strengths and weaknesses of the many statistical and conceptual approaches now being employed. Past studies have made it clear that the key question is no longer whether G evolves but rather how fast and in what manner. We highlight the most promising future directions for this emerging field.

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 100,774

External links

  • This entry has no external links. Add one.
Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Evolution of phenotypic plasticity: where are we going now?Massimo Pigliucci - 2005 - Trends in Ecology and Evolution 20 (9):481-486.
Genotype–phenotype mapping and the end of the ‘genes as blueprint’ metaphor.Massimo Pigliucci - 2010 - Philosophical Transactions Royal Society B 365:557–566.
From heritability to probability.Omri Tal - 2009 - Biology and Philosophy 24 (1):81-105.

Analytics

Added to PP
2010-04-27

Downloads
0

6 months
0

Historical graph of downloads

Sorry, there are not enough data points to plot this chart.
How can I increase my downloads?

Author Profiles

References found in this work

No references found.

Add more references