The beak of the other finch: coevolution of genetic covariance structure and developmental modularity during adaptive evolution

Abstract

The link between adaptation and evolutionary change remains the most central and least understood evolutionary problem. Rapid evolution and diversification of avian beaks is a textbook example of such a link, yet the mechanisms that enable beak's precise adaptation and extensive adaptability are poorly understood. Often observed rapid evolutionary change in beaks is particularly puzzling in light of the neo-Darwinian model that necessitates coordinated changes in developmentally distinct precursors and correspondence between functional and genetic modularity, which should preclude evolutionary diversification. I show that during first 19 generations after colonization of a novel environment, house finches (Carpodacus mexicanus) express an array of distinct, but adaptively equivalent beak morphologies-a result of compensatory developmental interactions between beak length and width in accommodating microevolutionary change in beak depth. Directional selection was largely confined to the elimination of extremes formed by these developmental interactions, while long-term stabilizing selection along a single axis-beak depth-was mirrored in the structure of beak's additive genetic covariance. These results emphasize three principal points. First, additive genetic covariance structure may represent a historical record of the most recurrent developmental and functional interactions. Second, adaptive equivalence of beak configurations shields genetic and developmental variation in individual components from depletion by natural selection. Third, compensatory developmental interactions among beak components can generate rapid reorganization of beak morphology under novel conditions and thus greatly facilitate both the evolution of precise adaptation and extensive diversification, thereby linking adaptation and adaptability in this classic example of Darwinian evolution.

Figure 1.

Distinct, but similarly integrated beak morphologies during 19 generations following establishment of house finches in northwestern Montana, USA. Upper drawings illustrate reconfiguration of beak morphology by tpsSuper (v. 1.03) from a consensus position based on displacement of 10 homologous landmarks (black circles in the arrivals group) within each group of generations and is shown for illustration only. Middle graph shows microevolutionary change in standardized (mean = 0, s.d. = 1) beak length (circles, solid line), depth (squares, dashed line) and width (triangles, dotted line) across generations. Lower graph shows integration index (mean ± 1 s.e.) calculated for three beak components as I = [∑(λ_i−1)²/6]^1/2 (Cheverud et al. 1983), where λ_i is an eigenvalue of the correlation matrix of the normalized data (table 1). Statistical significance of the integration coefficient was obtained by resampling, with replacement, of the within-principal component loadings (n = 500).

Figure 2.

Microevolutionary trends in covariance structure of beak morphology illustrate widespread interchangeability and compensatory variation in beak components during microevolutionary change. The CPC analysis of shared covariance structure in (a) males and (b) females during 19 generations after population establishment. Line thickness indicates the hierarchy of shared covariance structure. (c) Eigenanalysis of changes in covariance structure across generations (conventional PC analysis of the covariance matrices of CPC1 scores of each generation). Shown is percentage of variance accounted by the first three eigenvalues across all generations and coefficients of corresponding eigenvectors. Error bars are bootstrapped s.e. (n = 100). High covariation among generations would produce consistently increasing or decreasing PC loadings across generations, while fluctuating PC loadings among generations indicate negative covariation among some generations and might be produced by compensatory growth of different beak components in different generations (table 5).

Figure 3.

Relative difference between the first (λ₁) and the second (λ₂) eigenvalues of additive genetic covariance matrix (G, table 4), phenotypic covariance matrix (P, table 1), matrix of ontogenetic variation (L⁻¹, table 5) and matrix describing adaptive landscape (M, table 3) in Montana house finches over 19 generations after population establishment. Smaller values indicate greater dimensionality of variability. The third eigenvalues were not significant in any of the matrices.

Figure 4.

Overall fitness surface (juvenile postfledging survival) defined by the canonical axes m₁ (variation in beak depth) and m₃ (relative expression of beak length and beak width) (table 3). Dots show average coordinates of m₁, m₃ and survival for each generation (shown by numbers), starting with generation 5. Arrows connect subsequent generations. G matrix orientation (85% along m₁ and 8.7% along m₃) largely coincides with the orientation of M matrix.

Figure 5.

Concordance of G, additive genetic covariance matrix (table 4); P, phenotypic covariance matrix (table 1); L⁻¹, negative inverse covariance matrix of ontogenetic integration (table 5) and M, matrix of multivariate selection (table 3) of beak morphology during 19 generations following population establishment. Drawn are the first (above diagonal) and the second (below diagonal) eigenvectors and the corresponding vector correlations and angles (in degrees) between them. All vectors are drawn the same length for illustration only (see tables 1–5 for actual length in corresponding eigenvalues). Thick lines show overall vectors calculated across all generations; thin lines show within-generation vectors. For L⁻¹ versus G, and P versus G comparisons, within-generation vectors of L⁻¹ and P are compared with the vectors of overall G. For all other comparisons (L⁻¹ versus P, L⁻¹ versus M, and P versus M), vectors are compared within each generation. Brackets show bootstrapped limits (n = 100) within which the vectors are not distinct. Asterisks indicate similarity of overall vector correlations (if thick vectors are within the bracket) or similarity of within-generation vectors (if most of the within-generation vectors are within the bracket).

Figure 6.

Developmental abnormalities in house finch beaks illustrating errors in coordinated growth of beak components. Upper row: (a) normal phenotype, (b) overbite—elongated upper beak (frequency: 14 per 15 000 captures = 0.09%), (c) ‘crossbill’ phenotype (total: 0.11% of which right crossing: 0.08%, left-crossing: 0.03%), (d) ‘shoveler’ phenotype—widened and flattened upper beak (0.02%) and (e) outgrowth/modifications on lower or upper beak (0.23%). Middle row: (f) normal phenotype, (g) overbite, (h–i) ‘crossbill’ phenotype, (j) ‘skimmer’ phenotype—widened and overlapping lower beak (0.01%), (k) both upper and lower beaks are curved in the same direction (0.017%) and (l) ‘shoveler’ phenotype. Lower row: (m) normal phenotype, (n) underbite—longer lower beak (0.12%), (o) right-crossing ‘crossbill’ phenotype, (p) both upper and lower beaks curved in the same direction, (q) ‘skimmer’ phenotype, (r) incomplete right-curving (0.18%) and (s) outgrowth on upper or lower beaks (e.g. pronounced groves, ridges and condensations).