Michael B. Morrissey

DIRECTIONAL SELECTION IN TEMPORALLY REPLICATED STUDIES IS REMARKABLY CONSISTENT

Temporal variation in selection is a fundamental determinant of evolutionary outcomes. A recent paper presented a synthetic analysis of temporal variation in selection in natural populations. The authors concluded that there is substantial variation in the strength and direction of selection over time, but acknowledged that sampling error would result in estimates of selection that were more variable than the true values. We reanalyze their dataset using techniques that account for the necessary effect of sampling error to inflate apparent levels of variation and show that directional selection is remarkably constant over time, both in magnitude and direction. Thus we cannot claim that the available data support the existence of substantial temporal heterogeneity in selection. Nonetheless, we conject that temporal variation in selection could be important, but that there are good reasons why it may not appear in the available data. These new analyses highlight the importance of applying techniques that estimate parameters of the distribution of selection, rather than parameters of the distribution of estimated selection (which will reflect both sampling error and “real” variation in selection); indeed, despite availability of methods for the former, focus on the latter has been common in synthetic reviews of the aspects of selection in nature, and can lead to serious misinterpretations.

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.

The spatial patterns of directional phenotypic selection.

Local adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection.

pedantics: an r package for pedigree‐based genetic simulation and pedigree manipulation, characterization and viewing

Analyses of pedigrees and pedigree‐derived parameters (e.g. relatedness and fitness) provide some of the most informative types of studies in evolutionary biology. The r package pedantics implements tools to facilitate power and sensitivity analyses of pedigree‐related studies of natural populations. Functions are available to permute pedigree data in various ways with the goal of mimicking patterns of pedigree errors and missingness that occur in studies of natural populations. Another set of functions simulates genetic and phenotypic data based on arbitrary pedigrees. Finally, functions are also available with which visual and numerical representations of pedigree structure can be generated.

The maintenance of genetic variation due to asymmetric gene flow in dendritic metapopulations.

Dendritic landscapes can have ecological properties that differ importantly from simpler spatial arrangements of habitats. Most dendritic landscapes are structured by elevation, and therefore, migration is likely to be directionally biased. While the population‐genetic consequences of both dendritic landscape arrangements and asymmetric migration have begun to be studied, these processes have not been considered together. Simple conceptual models predict that if migration into branch (headwater) populations is limited, such populations can act as reservoirs for potentially unique alleles. As a consequence of the fact that dendritic landscapes have, by definition, more branches than internal habitat patches, this process may lead to the maintenance of higher overall genetic diversities in metapopulations inhabiting dendritic networks where migration is directionally biased. Here we begin to address the generality of these simple predictions using genetic models and a review of empirical literature. We show, for a range of demographic parameters, that dendritic systems with asymmetric migration can maintain levels of genetic variation that are very different, sometimes very elevated, compared with more classical models of geographical population structure. Furthermore, predicted patterns of genetic variation within metapopulations—that is, stepwise increases in genetic diversity at nodes—do occur in some empirical data.

Indirect genetics effects and evolutionary constraint: an analysis of social dominance in red deer, Cervus elaphus.

By determining access to limited resources, social dominance is often an important determinant of fitness. Thus, if heritable, standard theory predicts mean dominance should evolve. However, dominance is usually inferred from the tendency to win contests, and given one winner and one loser in any dyadic contest, the mean proportion won will always equal 0.5. Here, we argue that the apparent conflict between quantitative genetic theory and common sense is resolved by recognition of indirect genetic effects (IGEs). We estimate selection on, and genetic (co)variance structures for, social dominance, in a wild population of red deer Cervus elaphus, on the Scottish island of Rum. While dominance is heritable and positively correlated with lifetime fitness, contest outcomes depend as much on the genes carried by an opponent as on the genotype of a focal individual. We show how this dependency imposes an absolute evolutionary constraint on the phenotypic mean, thus reconciling theoretical predictions with common sense. More generally, we argue that IGEs likely provide a widespread but poorly recognized source of evolutionary constraint for traits influenced by competition.

Physiological Changes in Largemouth Bass Caused by Live-Release Angling Tournaments in Southeastern Ontario

Abstract Several largemouth bass Micropterus salmoides tournaments in Ontario were visited in the summers of 1999 and 2000 to examine the physiological changes that occur in largemouth bass as a result of tournament procedures. Physiological variables were compared among tournament-caught largemouth bass, resting laboratory controls, and angled controls. The plasma cortisol and glucose concentrations and plasma osmolarity in tournament-caught largemouth bass sampled within 5 min following the weigh-in were significantly greater than those in both control groups. Tournament-caught fish also exhibited ionic disturbances that involved increases in plasma sodium and potassium concentrations, but there were no significant changes in the levels of plasma chloride. Large changes in the metabolic status of largemouth bass sampled following the weigh-in included major reductions in the muscle energy stores phosphocreatine, adenosine triphosphate, and glycogen and large increases in muscle and plasma lactate concen...

Pharmacogenomic agreement between two cancer cell line data sets

Large cancer cell line collections broadly capture the genomic diversity of human cancers and provide valuable insight into anti-cancer drug response. Here we show substantial agreement and biological consilience between drug sensitivity measurements and their associated genomic predictors from two publicly available large-scale pharmacogenomics resources: The Cancer Cell Line Encyclopedia and the Genomics of Drug Sensitivity in Cancer databases.

The Prediction of Adaptive Evolution: Empirical Application of the Secondary Theorem of Selection and Comparison to the Breeder's Equation

Adaptive evolution occurs when fitness covaries with genetic merit for a trait (or traits). The breeder’s equation (BE), in both its univariate and multivariate forms, allows us to predict this process by combining estimates of selection on phenotype with estimates of genetic (co)variation. However, predictions are only valid if all factors causal for trait‐fitness covariance are measured. Although this requirement will rarely (if ever) be met in practice, it can be avoided by applying Robertson’s secondary theorem of selection (STS). The STS predicts evolution by directly estimating the genetic basis of trait‐fitness covariation without any explicit model of selection. Here we apply the BE and STS to four morphological traits measured in Soay sheep (Ovis aries) from St. Kilda. Despite apparently positive selection on heritable size traits, sheep are not getting larger. However, although the BE predicts increasing size, the STS does not, which is a discrepancy that suggests unmeasured factors are upwardly biasing our estimates of selection on phenotype. We suggest this is likely to be a general issue, and that wider application of the STS could offer at least a partial resolution to the common discrepancy between naive expectations and observed trait dynamics in natural populations.

A framework for power and sensitivity analyses for quantitative genetic studies of natural populations, and case studies in Soay sheep (Ovis aries)

Studies of the quantitative genetics of natural populations have contributed greatly to evolutionary biology in recent years. However, while pedigree data required are often uncertain (i.e. incomplete and partly erroneous) and limited, means to evaluate the effects of such uncertainties have not been developed. We have therefore developed a general framework for power and sensitivity analyses of such studies. We propose that researchers first generate a set of pedigree data that they wish to use in a quantitative genetic study, as well as data regarding errors that occur in that pedigree. This pedigree is then permuted using the data regarding errors to generate hypothetical ‘true’ and ‘assumed’ pedigrees that differ so as to mimic pedigree errors that might occur in the study system under consideration. Phenotypic data are then simulated across the true pedigree (according to user‐defined genetic and environmental covariance structures), before being analysed with standard quantitative genetic techniques in conjunction with the ‘assumed’ pedigree data. To illustrate this approach, we conducted power and sensitivity analyses in a well‐known study of Soay sheep (Ovis aries). We found that, although the estimation of simple genetic (co)variance structures is fairly robust to pedigree errors, some potentially serious biases were detected under more complex scenarios involving maternal effects. Power analyses also showed that this study system provides high power to detect heritabilities as low as about 0.09. Given this range of results, we suggest that such power and sensitivity analyses could greatly complement empirical studies, and we provide the computer program pedantics to aid in their application.