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Low scaling of a life history variable: Analysing eutherian gestation periods with and without phylogeny-informed statistics


Clauss, Marcus; Dittmann, Marie T; Müller, Dennis W H; Zerbe, Philipp; Codron, Daryl (2014). Low scaling of a life history variable: Analysing eutherian gestation periods with and without phylogeny-informed statistics. Mammalian Biology - Zeitschrift für Säugetierkunde, 79(1):9-16.

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, M0.18-0.20) as when using Phylogenetic Generalized Least Squares (PGLS, M0.07-0.10), 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 randomized 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.

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, M0.18-0.20) as when using Phylogenetic Generalized Least Squares (PGLS, M0.07-0.10), 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 randomized 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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17 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:05 Vetsuisse Faculty > Veterinary Clinic > Department of Small Animals
05 Vetsuisse Faculty > Veterinary Clinic > Department of Farm Animals
Dewey Decimal Classification:570 Life sciences; biology
630 Agriculture
Date:2014
Deposited On:29 Nov 2013 08:18
Last Modified:30 Oct 2016 06:05
Publisher:Elsevier
ISSN:1616-5047
Publisher DOI:https://doi.org/10.1016/j.mambio.2013.01.002
Permanent URL: https://doi.org/10.5167/uzh-85491

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