What is the purpose of a genetic variance-covariance matrix, or G matrix, in trait evolution studies?

• A. To measure environmental variance alone.
• B. To quantify gene expression patterns.
• C. To summarize additive genetic variances and covariances among traits; it predicts how multiple traits will respond to selection.
• D. To identify ecological niches.

Answer: (C)

The key idea here is that the G matrix summarizes how traits are linked at the genetic level. Its diagonal entries are the additive genetic variances for each trait, and the off-diagonal entries are the additive genetic covariances between trait pairs. This structure matters because when selection acts on a suite of traits, the response isn’t just for each trait in isolation—the genetic correlations cause traits to change together. Mathematically, the expected change in trait means under selection is given by Δz = Gβ, where β is the vector of selection gradients. So, the G matrix lets us predict both how much each trait can evolve and how evolution in one trait might pull others along, revealing potential constraints or facilitation on mult trait evolution. It’s distinct from environmental variance, which is about non-genetic variation, and from gene-expression data or niche identification, which are different concepts.