Cytochrome b divergence between avian sister species is linked to generation length and body mass

Abstract

It is increasingly realised that the molecular clock does not tick at a constant rate. Rather, mitochondrial mutation rates are influenced by factors such as generation length and body mass. This has implications for the use of genetic data in species delimitation. It could be that speciation, as recognised by avian taxonomists, is associated with a certain minimum genetic distance between sister taxa, in which case we would predict no difference in the cytochrome b divergence of sister taxa according to the species' body size or generation time. Alternatively, if what taxonomists recognise as speciation has tended to be associated with the passage of a minimum amount of time since divergence, then there might be less genetic divergence between sister taxa with slower mutation rates, namely those that are heavier and/or with longer generation times. After excluding non-flying species, we analysed a database of over 600 avian sister species pairs, and found that species pairs with longer generation lengths (which tend to be the larger species) showed less cytochrome b divergence. This finding cautions against using any simple unitary criterion of genetic divergence to delimit species.

Figure 1. Scatterplot of the effect of the percentage difference in species' mass in each pair ( = (absolute difference in mass/mass of the heavier species)*100) on the cyt b divergence.

There is a significant positive relationship (linear model – y = 0.1948+0.00075x, adjusted R² = 0.015, F _1,548 = 9.29, p = 0.002).

Figure 2. Scatterplot of the effect of generation time of species pairs on the cyt b divergence.

There is a significant negative relationship (linear model – y = 0.2239–0.0026x, adjusted R² = 0.017, F _1,622 = 11.67, p<0.001).

Figure 3. Scatterplot of the effect of the average mass of a species pair on the cyt b divergence, excluding all flightless species.

There is a significant negative correlation between the variables (linear model – y = 0.2118 - 0.000011x, adjusted R² = 0.017, F _1,622 = 12.00, p<0.001).