A standardized approach to estimate life history tradeoffs in evolutionary ecology. Issue 2 (16th October 2013)

• Record Type: Journal Article
• Authors: Hamel, Sandra; Yoccoz, Nigel Gilles; Gaillard, Jean‐Michel
• Is Part Of: Oikos. Volume 123:Issue 2(2014)
• Page Start: 151
• Page End: 160
• Publication Date: 2013-10-16
• Subjects: Ecology -- Periodicals; 570
• DOI: 10.1111/j.1600-0706.2013.00819.x
• Languages: English
• ISSNs: 0030-1299

Abstract

<abstract abstract-type="main" xml:lang="en"> <title> <x xml:space="preserve">Abstract</x> </title> <p>As tradeoffs limit the maximum Darwinian fitness individuals can reach, measuring reliably the strength of tradeoffs using appropriate metrics is of prime importance to understand the evolution of traits under constraints. Tradeoffs involving phenotypic traits and fitness components, however, are difficult to quantify in free‐ranging populations because of confounding effects due to environmental variation and individual heterogeneity. Furthermore, although some methods have been used previously to quantify tradeoffs, these methods cannot be applied with respect to binary traits, which are common to describe life histories (e.g. probability of reproduction, nesting success, offspring survival). Here, we demonstrate how to measure reliably the strength of tradeoffs involving binary traits using (auto)correlation estimates obtained from generalized linear (mixed) models. We first propose a standardized approach that accounts for the variation in the nature of the tradeoffs being compared (e.g. continuous/binary traits, repeated/non‐repeated measures), and then apply this method to longitudinal data from two contrasting species of large herbivores. Empirical estimates of tradeoffs varied among traits, and between‐species comparisons suggested that reproductive tradeoffs between successive breeding attempts might only occur in capital breeders. The empirical results we obtained clearly demonstrate that the method we provide allows measuring reliably the strength of tradeoffs under most circumstances, including tradeoffs on binary traits. Our original approach therefore offers an important first step for comparing the strength and, hence, the relative importance of different tradeoffs, and opens the door to a better understanding of the evolution of life history traits in free‐ranging populations.</p> </abstract>