Alastair J. Wilson

The evolutionary ecology of individual phenotypic plasticity in wild populations

The ability of individual organisms to alter morphological and life‐history traits in response to the conditions they experience is an example of phenotypic plasticity which is fundamental to any populations ability to deal with short‐term environmental change. We currently know little about the prevalence, and evolutionary and ecological causes and consequences of variation in life history plasticity in the wild. Here we outline an analytical framework, utilizing the reaction norm concept and random regression statistical models, to assess the between‐individual variation in life history plasticity that may underlie population level responses to the environment at both phenotypic and genetic levels. We discuss applications of this framework to date in wild vertebrate populations, and illustrate how natural selection and ecological constraint may alter a populations response to the environment through their effects at the individual level. Finally, we present future directions and challenges for research into individual plasticity.

An ecologist's guide to the animal model.

1. Efforts to understand the links between evolutionary and ecological dynamics hinge on our ability to measure and understand how genes influence phenotypes, fitness and population dynamics. Quantitative genetics provides a range of theoretical and empirical tools with which to achieve this when the relatedness between individuals within a population is known. 2. A number of recent studies have used a type of mixed-effects model, known as the animal model, to estimate the genetic component of phenotypic variation using data collected in the field. Here, we provide a practical guide for ecologists interested in exploring the potential to apply this quantitative genetic method in their research. 3. We begin by outlining, in simple terms, key concepts in quantitative genetics and how an animal model estimates relevant quantitative genetic parameters, such as heritabilities or genetic correlations. 4. We then provide three detailed example tutorials, for implementation in a variety of software packages, for some basic applications of the animal model. We discuss several important statistical issues relating to best practice when fitting different kinds of mixed models. 5. We conclude by briefly summarizing more complex applications of the animal model, and by highlighting key pitfalls and dangers for the researcher wanting to begin using quantitative genetic tools to address ecological and evolutionary questions.

The misuse of BLUP in ecology and evolution.

Best linear unbiased prediction (BLUP) is a method for obtaining point estimates of a random effect in a mixed effect model. Over the past decade it has been used extensively in ecology and evolutionary biology to predict individual breeding values and reaction norms. These predictions have been used to infer natural selection, evolutionary change, spatial‐genetic patterns, individual reaction norms, and frailties. In this article we show analytically and through simulation and example why BLUP often gives anticonservative and biased estimates of evolutionary and ecological parameters. Although some concerns with BLUP methodology have been voiced before, the scale and breadth of the problems have probably not been widely appreciated. Bias arises because BLUPs are often used to estimate effects that are not explicitly accounted for in the model used to make the predictions. In these cases, predicted breeding values will often say more about phenotypic patterns than the genetic patterns of interest. An additional problem is that BLUPs are point estimates of quantities that are usually known with little certainty. Failure to account for this uncertainty in subsequent tests can lead to both bias and extreme anticonservatism. We demonstrate that restricted maximum likelihood and Bayesian solutions exist for these problems and show how unbiased and powerful tests can be derived that adequately quantify uncertainty. Of particular utility is a new test for detecting evolutionary change that not only accounts for prediction error in breeding values but also accounts for drift. To illustrate the problem, we apply these tests to long‐term data on the Soay sheep (Ovis aries) and the great tit (Parus major) and show that previously reported temporal trends in breeding values are not supported.

Environmental coupling of selection and heritability limits evolution

There has recently been great interest in applying theoretical quantitative genetic models to empirical studies of evolution in wild populations. However, while classical models assume environmental constancy, most natural populations exist in variable environments. Here, we applied a novel analytical technique to a long-term study of birthweight in wild sheep and examined, for the first time, how variation in environmental quality simultaneously influences the strength of natural selection and the genetic basis of trait variability. In addition to demonstrating that selection and genetic variance vary dramatically across environments, our results show that environmental heterogeneity induces a negative correlation between these two parameters. Harsh environmental conditions were associated with strong selection for increased birthweight but low genetic variance, and vice versa. Consequently, the potential for microevolution in this population is constrained by either a lack of heritable variation (in poor environments) or by a reduced strength of selection (in good environments). More generally, environmental dependence of this nature may act to limit rates of evolution, maintain genetic variance, and favour phenotypic stasis in many natural systems. Assumptions of environmental constancy are likely to be violated in natural systems, and failure to acknowledge this may generate highly misleading expectations for phenotypic microevolution.

SEX-SPECIFIC GENETIC VARIANCE AND THE EVOLUTION OF SEXUAL DIMORPHISM: A SYSTEMATIC REVIEW OF CROSS-SEX GENETIC CORRELATIONS

The independent evolution of the sexes may often be constrained if male and female homologous traits share a similar genetic architecture. Thus, cross‐sex genetic covariance is assumed to play a key role in the evolution of sexual dimorphism (SD) with consequent impacts on sexual selection, population dynamics, and speciation processes. We compiled cross‐sex genetic correlations (rMF) estimates from 114 sources to assess the extent to which the evolution of SD is typically constrained and test several specific hypotheses. First, we tested if rMF differed among trait types and especially between fitness components and other traits. We also tested the theoretical prediction of a negative relationship between rMF and SD based on the expectation that increases in SD should be facilitated by sex‐specific genetic variance. We show that rMF is usually large and positive but that it is typically smaller for fitness components. This demonstrates that the evolution of SD is typically genetically constrained and that sex‐specific selection coefficients may often be opposite in sign due to sub‐optimal levels of SD. Most importantly, we confirm that sex‐specific genetic variance is an important contributor to the evolution of SD by validating the prediction of a negative correlation between rMF and SD.

Maternal genetic effects set the potential for evolution in a free-living vertebrate population

Heritable maternal effects have important consequences for the evolutionary dynamics of phenotypic traits under selection, but have only rarely been tested for or quantified in evolutionary studies. Here we estimate maternal effects on early‐life traits in a feral population of Soay sheep (Ovis aries) from St Kilda, Scotland. We then partition the maternal effects into genetic and environmental components to obtain the first direct estimates of maternal genetic effects in a free‐living population, and furthermore test for covariance between direct and maternal genetic effects. Using an animal model approach, direct heritabilities (h2) were low but maternal genetic effects (m2) represented a relatively large proportion of the total phenotypic variance for each trait (birth weight m2 = 0.119, birth date m2 = 0.197, natal litter size m2 = 0.211). A negative correlation between direct and maternal genetic effects was estimated for each trait, but was only statistically significant for natal litter size (ram = −0.714). Total heritabilities (incorporating variance from heritable maternal effects and the direct‐maternal genetic covariance) were significant for birth weight and birth date but not for natal litter size. Inadequately specified models greatly overestimated additive genetic variance and hence direct h2 (by a factor of up to 6.45 in the case of birth date). We conclude that failure to model heritable maternal variance can result in over‐ or under‐estimation of the potential for traits to respond to selection, and advocate an increased effort to explicitly measure maternal genetic effects in evolutionary studies.

CONTRASTING PATTERNS OF PHENOTYPIC PLASTICITY IN REPRODUCTIVE TRAITS IN TWO GREAT TIT (PARUS MAJOR) POPULATIONS

Phenotypic plasticity is an important mechanism via which populations can respond to changing environmental conditions, but we know very little about how natural populations vary with respect to plasticity. Here we use random‐regression animal models to understand the multivariate phenotypic and genetic patterns of plasticity variation in two key life‐history traits, laying date and clutch size, using data from long‐term studies of great tits in The Netherlands (Hoge Veluwe [HV]) and UK (Wytham Woods [WW]). We show that, while population‐level responses of laying date and clutch size to temperature were similar in the two populations, between‐individual variation in plasticity differed markedly. Both populations showed significant variation in phenotypic plasticity (IxE) for laying date, but IxE was significantly higher in HV than in WW. There were no significant genotype‐by‐environment interactions (GxE) for laying date, yet differences in GxE were marginally nonsignificant between HV and WW. For clutch size, we only found significant IxE and GxE in WW but no significant difference between populations. From a multivariate perspective, plasticity in laying date was not correlated with plasticity in clutch size in either population. Our results suggest that generalizations about the form and cause of any response to changing environmental conditions across populations may be difficult.

The danger of applying the breeder's equation in observational studies of natural populations

The breeders equation, which predicts evolutionary change when a phenotypic covariance exists between a heritable trait and fitness, has provided a key conceptual framework for studies of adaptive microevolution in nature. However, its application requires strong assumptions to be made about the causation of fitness variation. In its univariate form, the breeders equation assumes that the trait of interest is not correlated with other traits having causal effects on fitness. In its multivariate form, the validity of predicted change rests on the assumption that all such correlated traits have been measured and incorporated into the analysis. Here, we (i) highlight why these assumptions are likely to be seriously violated in studies of natural, rather than artificial, selection and (ii) advocate wider use of the Robertson–Price identity as a more robust, and less assumption‐laden, alternative to the breeders equation for applications in evolutionary ecology.

Ontogeny of Additive and Maternal Genetic Effects: Lessons from Domestic Mammals

Evolution of size and growth depends on heritable variation arising from additive and maternal genetic effects. Levels of heritable (and nonheritable) variation might change over ontogeny, increasing through “variance compounding” or decreasing through “compensatory growth.” We test for these processes using a meta‐analysis of age‐specific weight traits in domestic ungulates. Generally, mean standardized variance components decrease with age, consistent with compensatory growth. Phenotypic convergence among adult sheep occurs through decreasing environmental and maternal genetic variation. Maternal variation similarly declines in cattle. Maternal genetic effects are thus reduced with age (both in absolute and relative terms). Significant trends in heritability (decreasing in cattle, increasing in sheep) result from declining maternal and environmental components rather than from changing additive variation. There was no evidence for increasing standardized variance components. Any compounding must therefore be masked by more important compensatory processes. While extrapolation of these patterns to processes in natural population is difficult, our results highlight the inadequacy of assuming constancy in genetic parameters over ontogeny. Negative covariance between direct and maternal genetic effects was common. Negative correlations with additive and maternal genetic variances indicate that antagonistic pleiotropy (between additive and maternal genetic effects) may maintain genetic variance and limit responses to selection.

Why h2 does not always equal VA/VP?

Over the last decade, there has been a rapid growth in the application of quantitative genetic techniques to evolutionary studies of natural populations. Whereas this work yields enormous insight into evolutionary processes in the wild, the use of modelling techniques and strategies adopted from animal breeders means that estimates of trait heritabilities (h2) are highly vulnerable to misinterpretation. Specifically, when estimated using animal models, h2 will not generally be comparable across studies and must be interpreted as being conditioned on any fixed effects included in the model. Failure to realize the model dependency of published h2 estimates will give a very misleading, and in most cases upwardly biased, impression of the potential for trait evolution.