Unifying Life‐History Analyses for Inference of Fitness and Population Growth

Abstract

The lifetime fitnesses of individuals comprising a population determine its numerical dynamics, and genetic variation in fitness results in evolutionary change. The dual importance of individual fitness is well understood, but empirical fitness records generally generally violate the assumptions of standard statistical approaches. This problem has plagued comprehensive study of fitness and impeded empirical study of the link between numerical and genetic dynamics of populations. Recently developed aster models address this problem by explicitly modeling the dependence of later expressed components of fitness (e.g. fecundity) on those expressed earlier (e.g. survival to reproduce). Moreover, aster models employ different sampling distributions for components of fitness, as appropriate (e.g. binomial for survival over a given interval and Poisson for fecundity). The analysis is conducted by maximum likelihood, and the resulting compound distributions for lifetime fitness closely approximate the observed data. We illustrate the breadth of aster's utility with three examples demonstrating estimation of the finite rate of increase, comparison of mean fitness among genotypic groups, and phenotypic selection analysis. Aster models offer a unified approach to address the breadth of questions in evolution and ecology for which life history data are gathered.

Evolutionary rescue beyond the models

“…These aspects of fitness have impeded (though not prevented) its evaluation. Aster modelling [36] was developed to enable precise estimation of mean absolute fitness, with statistical power for conclusive inference about population decline [33] by explicitly modelling the compound nature of lifetime fitness. Even so, because environmental variation over years can be substantial [37], assessment of population decline would appropriately consider multiple cohorts ( [38] is a rare example).…”

“…Fitness components were measured for individual plants, and these were used to estimate multivariate patterns of selection on leaf number, leaf thickness and reproductive stage at each field site. These data have been re-analysed using aster models [36,49]. This experiment also yielded estimates of additive-genetic variances and co-variances among the three focal plant traits within each field site and covariation in trait expression among the sites [43], indicating the potential for adaptive evolution in response to the novel environmental conditions.…”

Introduction beyond a species range: a relationship between population origin, adaptive potential and plant performance

“…The performance of plants of different origins at Beer Sheva location was compared using aster modeling of individual and group lifetime fitness (Geyer et al, 2007;Shaw et al, 2008) as implemented in R (R Development Core Team, 2009). The life-history stages that we modeled, and their statistical distributions, for the first year assessment were early-season seed germination (Bernoulli), whether a plant reproduced or not (Bernoulli) and total seeds per plant (Poisson).…”

“…The RP values of plants of different origins in the introduction year were analyzed over plots by one-sample t-test. Similarly, the observed proportions of seeds of different origins in plots at 4 years after introduction were at first subtracted from those expected under no selective advantage (that is, equal for all accessions) and then analyzed over plots by one-sample t-test.The performance of plants of different origins at Beer Sheva location was compared using aster modeling of individual and group lifetime fitness (Geyer et al, 2007;Shaw et al, 2008) as implemented in R (R Development Core Team, 2009). The life-history stages that we modeled, and their statistical distributions, for the first year assessment were early-season seed germination (Bernoulli), whether a plant reproduced or not (Bernoulli) and total seeds per plant (Poisson).…”

Three Sequenced Legume Genomes and Many Crop Species: Rich Opportunities for Translational Genomics

“…The leguminous tree honey locust (Gleditsia triacanthos) is being used as a model for studying rhizobia in a nonnodulating but nitrogen-fixing species (Lee and Hirsch, 2006). The nodulating prairie legume partridge pea (Chamaecrista fasciculata) is being studied both as a model of ecological adaptation to climate change (Shaw et al, 2008) and of floral structure (Tucker, 2003), and to help determine timing of polyploidy early in the legumes (Singer et al, 2009). …”