Medawar and Hamilton on the selective forces in the evolution of ageing

Both Medawar and Hamilton contributed key ideas to the modern evolutionary theory of ageing. In particular, they both suggested that, in populations with overlapping generations, the force with which selection acts on traits declines with the age at which traits are expressed. This decline would eventually cause ageing to evolve. However, the biological literature diverges on the relationship between Medawar's analysis of the force of selection and Hamilton's. Some authors appear to believe that Hamilton perfected Medawar's insightful, yet ultimately erroneous analysis of this force, while others see Hamilton's analysis as a coherent development of, or the obvious complement to Medawar's. Here, the relationship between the two analyses is revisited. Two things are argued for. First, most of Medawar's alleged errors that Hamilton would had rectified seem not to be there. The origin of these perceived errors appears to be in a misinterpretation of Medawar's writings. Second, the mathematics of Medawar and that of Hamilton show a significant overlap. However, different meanings are attached to the same mathematical expression. Medawar put forth an expression for the selective force on age-specific fitness. Hamilton proposed a full spectrum of selective forces each operating on age-specific fitness components, i.e. mortality and fertility. One of Hamilton's expressions, possibly his most important, is of the same form as Medawar's expression. But Hamilton's selective forces on age-specific fitness components do not add up to yield Medawar's selective force on age-specific fitness. It is concluded that Hamilton's analysis should be considered neither as a correction to Medawar's analysis nor as its obvious complement.

Fur colour in the Arctic fox: genetic architecture and consequences for fitness

Genome-wide association studies provide good opportunities for studying the genetic basis of adaptive traits in wild populations. Yet, previous studies often failed to identify major effect genes. In this study, we used high-density single nucleotide polymorphism and individual fitness data from a wild non-model species. Using a whole-genome approach, we identified the MC1R gene as the sole causal gene underlying Arctic fox Vulpes lagopus fur colour. Further, we showed the adaptive importance of fur colour genotypes through measures of fitness that link ecological and evolutionary processes. We found a tendency for blue foxes that are heterozygous at the fur colour locus to have higher fitness than homozygous white foxes. The effect of genotype on fitness was independent of winter duration but varied with prey availability, with the strongest effect in years of increasing rodent populations. MC1R is located in a genomic region with high gene density, and we discuss the potential for indirect selection through linkage and pleiotropy. Our study shows that whole-genome analyses can be successfully applied to wild species and identify major effect genes underlying adaptive traits. Furthermore, we show how this approach can be used to identify knowledge gaps in our understanding of interactions between ecology and evolution.

Episodes of opposing survival and reproductive selection cause strong fluctuating selection on seasonal migration versus residence

Quantifying temporal variation in sex-specific selection on key ecologically relevant traits, and quantifying how such variation arises through synergistic or opposing components of survival and reproductive selection, is central to understanding eco-evolutionary dynamics, but rarely achieved. Seasonal migration versus residence is one key trait that directly shapes spatio-seasonal population dynamics in spatially and temporally varying environments, but temporal dynamics of sex-specific selection have not been fully quantified. We fitted multi-event capture-recapture models to year-round ring resightings and breeding success data from partially migratory European shags (Phalacrocorax aristotelis) to quantify temporal variation in annual sex-specific selection on seasonal migration versus residence arising through adult survival, reproduction and the combination of both (i.e. annual fitness). We demonstrate episodes of strong and strongly fluctuating selection through annual fitness that were broadly synchronized across females and males. These overall fluctuations arose because strong reproductive selection against migration in several years contrasted with strong survival selection against residence in years with extreme climatic events. These results indicate how substantial phenotypic and genetic variation in migration versus residence could be maintained, and highlight that biologically important fluctuations in selection may not be detected unless both survival selection and reproductive selection are appropriately quantified and combined.

How fitness consequences of early-life conditions vary with age in a long-lived seabird: A Bayesian multivariate analysis of age-specific reproductive values

Evolutionary theory suggests that individuals can benefit from deferring the fitness cost of developing under poor conditions to later in life. Although empirical evidence for delayed fitness costs of poor developmental conditions is abundant, individuals that die prematurely have not often been incorporated when estimating fitness, such that age-specific fitness costs, and therefore the relative importance of delayed fitness costs are actually unknown. We developed a Bayesian statistical framework to estimate age-specific reproductive values in relation to developmental conditions. We applied it to data obtained from a long-term longitudinal study of common terns Sterna hirundo, using sibling rank to describe variation in developmental conditions. Common terns have a maximum of three chicks, and later hatching chicks acquire less food, grow more slowly and have a lower fledging probability than their earlier hatched siblings. We estimated fitness costs in adulthood to constitute c. 45% and 70% of the total fitness costs of hatching third and second, respectively, compared to hatching first. This was due to third-ranked hatchlings experiencing especially high pre-fledging mortality, while second-ranked hatchlings had lower reproductive success in adulthood. Both groups had slightly lower adult survival. There was, however, no evidence for sibling rank-specific rates of senescence. We additionally found years with low fledgling production to be associated with particularly strong pre-fledging selection on sibling rank, and with increased adult survival to the next breeding season. This suggests that adults reduce parental allocation to reproduction in poor years, which disproportionately impacts low-ranked offspring. Interpreting these results, we suggest that selection at the level of the individual offspring for delaying fitness costs is counteracted by selection for parental reduction in brood size when resources are limiting.

Pedigree-Based Estimation of Reproductive Value

How successful an individual or cohort is, in terms of their genetic contribution to the future population, is encapsulated in the concept of reproductive value, and is crucial for understanding selection and evolution. Long-term studies of pedigreed populations offer the opportunity to estimate reproductive values directly. However, the degree to which genetic contributions, as defined by a pedigree, may converge on their long-run values within the time frames of available data sets, such that they may be interpreted as estimates of reproductive value, is unclear. We develop a system for pedigree-based calculation of the expected genetic representation that both individuals and cohorts make to the population in the years following their birth. We apply this system to inference of individual and cohort reproductive values in Soay sheep (Ovis aries) from St Kilda, Outer Hebrides. We observe that these genetic contributions appear to become relatively stable within modest time frames. As such, it may be reasonable to consider pedigree-based calculations of genetic contributions to future generations as estimates of reproductive value. This approach and the knowledge that the estimates can stabilize within decades should offer new opportunities to analyze data from pedigreed wild populations, which will be of value to many fields within evolutionary biology and demography.

Fluctuations in lifetime selection in an autocorrelated environment

Most natural environments vary stochastically and are temporally autocorrelated. Previous theory investigating the effects of environmental autocorrelation on evolution mostly assumed that total fitness resulted from a single selection episode. Yet organisms are likely to experience selection repeatedly along their life, in response to possibly different environmental states. We model the evolution of a quantitative trait in organisms with non-overlapping generations undergoing several episodes of selection in a randomly fluctuating and autocorrelated environment. We show that the evolutionary dynamics depends not directly on fluctuations of the environment, but instead on those of an effective phenotypic optimum that integrates the effects of all selection episodes within each generation. The variance and autocorrelation of the integrated optimum shape the variance and predictability of selection, with substantial qualitative and quantitative deviations from previous predictions considering a single selection episode per generation. We also investigate the consequence of multiple selection episodes per generation on population load. In particular, we identify a new load resulting from within-generation fluctuating selection, generating the death of individuals without significance for the evolutionary dynamics. Our study emphasizes how taking into account fluctuating selection within lifetime unravels new properties of evolutionary dynamics, with crucial implications notably with respect to responses to global changes.

Stabilizing selection and adaptive evolution in a combination of two traits in an arctic ungulate

Stabilizing selection is thought to be common in wild populations and act as one of the main evolutionary mechanisms, which constrain phenotypic variation. When multiple traits interact to create a combined phenotype, correlational selection may be an important process driving adaptive evolution. Here, we report on phenotypic selection and evolutionary changes in two natal traits in a semidomestic population of reindeer (Rangifer tarandus) in northern Finland. The population has been closely monitored since 1969, and detailed data have been collected on individuals since they were born. Over the length of the study period (1969-2015), we found directional and stabilizing selection toward a combination of earlier birth date and heavier birth mass with an intermediate optimum along the major axis of the selection surface. In addition, we demonstrate significant changes in mean traits toward earlier birth date and heavier birth mass, with corresponding genetic changes in breeding values during the study period. Our results demonstrate evolutionary changes in a combination of two traits, which agree closely with estimated patterns of phenotypic selection. Knowledge of the selective surface for combinations of genetically correlated traits are vital to predict how population mean phenotypes and fitness are affected when environments change.

Selective Sweep at a QTL in a Randomly Fluctuating Environment

Adaptation is mediated by phenotypic traits that are often near continuous, and undergo selective pressures that may change with the environment. The dynamics of allelic frequencies at underlying quantitative trait loci (QTL) depend on their own phenotypic effects, but also possibly on other polymorphic loci affecting the same trait, and on environmental change driving phenotypic selection. Most environments include a substantial component of random noise, characterized both by its magnitude and its temporal autocorrelation, which sets the timescale of environmental predictability. I investigate the dynamics of a mutation affecting a quantitative trait in an autocorrelated stochastic environment that causes random fluctuations of an optimum phenotype. The trait under selection may also exhibit background polygenic variance caused by many polymorphic loci of small effects elsewhere in the genome. In addition, the mutation at the QTL may affect phenotypic plasticity, the phenotypic response of given genotype to its environment of development or expression. Stochastic environmental fluctuations increase the variance of the evolutionary process, with consequences for the probability of a complete sweep at the QTL. Background polygenic variation critically alters this process, by setting an upper limit to stochastic variance of population genetics at the QTL. For a plasticity QTL, stochastic fluctuations also influences the expected selection coefficient, and alleles with the same expected trajectory can have very different stochastic variances. Finally, a mutation may be favored through its effect on plasticity despite causing a systematic mismatch with optimum, which is compensated by evolution of the mean background phenotype.

Integrating viability and fecundity selection to illuminate the adaptive nature of genetic clines

Genetically based trait variation across environmental gradients can reflect adaptation to local environments. However, natural populations that appear well-adapted often exhibit directional, not stabilizing, selection on ecologically relevant traits. Temporal variation in the direction of selection could lead to stabilizing selection across multiple episodes of selection, which might be overlooked in short-term studies that evaluate relationships of traits and fitness under only one set of conditions. Furthermore, nonrandom mortality prior to trait expression can bias inferences about trait evolution if viability selection opposes fecundity selection. Here, we leveraged fitness and trait data to test whether phenotypic clines are genetically based and adaptive, whether temporal variation in climate imposes stabilizing selection, and whether viability selection acts on adult phenotypes. We monitored transplants of the subalpine perennial forb, Boechera stricta (Brassicaceae), in common gardens at two elevations over 2-3 years that differed in drought intensity. We quantified viability, and fecundity fitness components for four heritable traits: specific leaf area, integrated water-use efficiency, height at first flower, and flowering phenology. Our results indicate that genetic clines are maintained by selection, but their expression is context dependent, as they do not emerge in all environments. Moreover, selection varied spatially and temporally. Stabilizing selection was most pronounced when we integrated data across years. Finally, viability selection prior to trait expression targeted adult phenotypes (age and size at flowering). Indeed, viability selection for delayed flowering opposed fecundity selection for accelerated flowering; this result demonstrates that neglecting to account for viability selection could lead to inaccurate conclusions that populations are maladapted. Our results suggest that reconciling clinal trait variation with selection requires data collected across multiple spatial scales, time frames, and life-history stages.

: Probabilistic Population Projections

We describe bayesPop, an R package for producing probabilistic population projections for all countries. This uses probabilistic projections of total fertility and life expectancy generated by Bayesian hierarchical models. It produces a sample from the joint posterior predictive distribution of future age- and sex-specific population counts, fertility rates and mortality rates, as well as future numbers of births and deaths. It provides graphical ways of summarizing this information, including trajectory plots and various kinds of probabilistic population pyramids. An expression language is introduced which allows the user to produce the predictive distribution of a wide variety of derived population quantities, such as the median age or the old age dependency ratio. The package produces aggregated projections for sets of countries, such as UN regions or trading blocs. The methodology has been used by the United Nations to produce their most recent official population projections for all countries, published in the World Population Prospects.

Harvest-induced phenotypic selection in an island population of moose, Alces alces

Empirical evidence strongly indicates that human exploitation has frequently led to rapid evolutionary changes in wild populations, yet the mechanisms involved are often poorly understood. Here, we applied a recently developed demographic framework for analyzing selection to data from a 20-year study of a wild population of moose, Alces alces. In this population, a genetic pedigree has been established all the way back to founders. We demonstrate harvest-induced directional selection for delayed birth dates in males and reduced body mass as calf in females. During the study period, birth date was delayed by 0.81 days per year for both sexes, whereas no significant changes occurred in calf body mass. Quantitative genetic analyses indicated that both traits harbored significant additive genetic variance. These results show that selective harvesting can induce strong selection that oppose natural selection. This may cause evolution of less favorable phenotypes that become maladaptive once harvesting ceases.

Diffraction-geometry refinement in the DIALS framework

A comprehensive description of the methods used within the DIALS framework for diffraction-geometry refinement using predicted reflection centroids is given. Examples of the advanced features of the software are provided.

Rapid data collection and modern computing resources provide the opportunity to revisit the task of optimizing the model of diffraction geometry prior to integration. A comprehensive description is given of new software that builds upon established methods by performing a single global refinement procedure, utilizing a smoothly varying model of the crystal lattice where appropriate. This global refinement technique extends to multiple data sets, providing useful constraints to handle the problem of correlated parameters, particularly for small wedges of data. Examples of advanced uses of the software are given and the design is explained in detail, with particular emphasis on the flexibility and extensibility it entails.

Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations.

Estimating phenotypic selection in age-structured populations by removing transient fluctuations

An extension of the selection differential in the Robertson-Price equation for the mean phenotype in an age-structured population is provided. Temporal changes in the mean phenotype caused by transient fluctuations in the age-distribution and variation in mean phenotype among age classes, which can mistakenly be interpreted as selection, will disappear if reproductive value weighting is applied. Changes in any weighted mean phenotype in an age-structured population may be decomposed into between- and within-age class components. Using reproductive value weighting the between-age class component becomes pure noise, generated by previous genetic drift or fluctuating selection. This component, which we call transient quasi-selection, can therefore be omitted when estimating age-specific selection on fecundity or viability within age classes. The final response can be computed at the time of selection, but can not be observed until lifetime reproduction is realized unless the heritability is one. The generality of these results is illustrated further by our derivation of the selection differential for the continuous time age-structured model with general age-dependent weights. A simple simulation example as well as estimation of selection components in a house sparrow population illustrates the applicability of the theory to analyze selection on the mean phenotype in fluctuating age-structured populations.