Abstract
Traditionally, biological times (gestation period, longevity) are proposed to scale to body mass M as M0.25. Although phylogeny-informed statistics have become widespread, it is still sometimes assumed that in datasets comprising a very large number of species, analyses that do not and that do account for phylogeny will yield similar results. Here we show, in a large dataset on gestation period length in eutherian mammals (1214 species from 20 orders), that the allometric scaling exponent is about twice as high using conventional statistics (ordinary least squares OLS, M0.18–020) as when using phylogenetic generalised least squares (PGLS, M007-010), indicating that among closely related taxa, the scaling of gestation is much lower than generally assumed. This matches the well-known absence of scaling among different-sized breeds of domestic animal species, and indicates that changes in M must be more related to changes in development speed rather than development time among closely related species, which has implications for interpreting life history-consequences of insular dwarfism and gigantism. Only when allowing just one species per order (simulated in 100 randomised datasets of n = 20 species across 20 orders) is 0.25 included in the scaling exponent confidence interval in both OLS and PGLS. Differences in scaling at different taxonomic levels in comparative datasets may indicate evolutionary trends where successive taxonomic groups compete by fundamental variation in organismal design not directly linked to changes in M. Allometries then do not necessarily represent universal scaling rules, but snapshots of evolutionary time that depend on diversification and extinction events before the picture was taken. It is either by analysing subsets separately, or by using PGLS in large datasets, that the underlying relationships with M can then be unveiled.
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Clauss, M., Dittmann, M.T., Müller, D.W.H. et al. Low scaling of a life history variable: Analysing eutherian gestation periods with and without phylogeny-informed statistics. Mamm Biol 79, 9–16 (2014). https://doi.org/10.1016/j.mambio.2013.01.002
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DOI: https://doi.org/10.1016/j.mambio.2013.01.002