ABSTRACT
Evolutionary adaptation through genetic change requires genetic variation and is a key mechanism enabling species to persist in changing environments. Although a substantial body of work has focused on understanding how and why additive genetic variance (V A) differs among traits within species, we still know little about how they vary among species. Here we make a first attempt at testing for interspecific variation in two complementary measures of V A and the role of phylogeny in shaping this variation. To this end, we performed a phylogenetic comparative analysis using 1822 narrow-sense heritability (h 2) for 68 species of birds and mammals and 378 coefficients of additive genetic variance (CV A) estimates for 23 species. Controlling for within-species variation attributable to estimation method and trait type, we found some interspecific variation in h 2 (~15%) but not CV A. Although suggestive of interspecific variation in the importance of non-(additive) genetic sources of variance, sample sizes were insufficient to test this hypothesis directly. Additionally, although power was low, no phylogenetic signal was detected for either measure. Hence, while this suggests interspecific variation in V A is probably small, our understanding of interspecific variation in the adaptive potential of wild vertebrate populations is currently hampered by data limitations, a scarcity of CV A estimates and a measure of their uncertainty in particular.
ABSTRACT
An individual's lifetime reproductive success (LRS) measures its realized genetic contributions to the next generation, but how well does it predict this over longer periods? Here we use human genealogical data to estimate expected individual genetic contributions (IGC) and quantify the degree to which LRS, relative to other fitness proxies, predicts IGC over longer periods. This allows an identification of the life-history stages that are most important in shaping variation in IGC. We use historical genealogical data from two non-isolated local populations in Switzerland to estimate the stabilized IGC for 2230 individuals approximately 10 generations after they were born. We find that LRS explains 30% less variation in IGC than the best predictor of IGC, the number of grandoffspring. However, albeit less precise than the number of grandoffspring, we show that LRS does provide an unbiased prediction of IGC. Furthermore, it predicts IGC better than lifespan, and accounting for offspring survival to adulthood does not improve the explanatory power. Overall, our findings demonstrate the value of human genealogical data to evolutionary biology and suggest that reproduction-more than lifespan or offspring survival-impacts the long-term genetic contributions of historic humans, even in a population with appreciable migration.
