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Virus host shifts, where a virus transmits to and infects a novel host species, are a major source of emerging infectious disease. Genetic similarity between eukaryotic host species has been shown to be an important determinant of the outcome of virus host shifts, but it is unclear if this is the case for prokaryotes where anti-virus defences can be transmitted by horizontal gene transfer and evolve rapidly. Here, we measure the susceptibility of 64 strains of Staphylococcaceae bacteria (48 strains of Staphylococcus aureus and 16 non-S. aureus species spanning 2 genera) to the bacteriophage ISP, which is currently under investigation for use in phage therapy. Using three methods-plaque assays, optical density (OD) assays, and quantitative (q)PCR-we find that the host phylogeny explains a large proportion of the variation in susceptibility to ISP across the host panel. These patterns were consistent in models of only S. aureus strains and models with a single representative from each Staphylococcaceae species, suggesting that these phylogenetic effects are conserved both within and among host species. We find positive correlations between susceptibility assessed using OD and qPCR and variable correlations between plaque assays and either OD or qPCR, suggesting that plaque assays alone may be inadequate to assess host range. Furthermore, we demonstrate that the phylogenetic relationships between bacterial hosts can generally be used to predict the susceptibility of bacterial strains to phage infection when the susceptibility of closely related hosts is known, although this approach produced large prediction errors in multiple strains where phylogeny was uninformative. Together, our results demonstrate the ability of bacterial host evolutionary relatedness to explain differences in susceptibility to phage infection, with implications for the development of ISP both as a phage therapy treatment and as an experimental system for the study of virus host shifts., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Walsh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The major frameworks for predicting evolutionary change assume that a phenotype's underlying genetic and environmental components are normally distributed. However, the predictions of these frameworks may no longer hold if distributions are skewed. Despite this, phenotypic skew has never been decomposed, meaning the fundamental assumptions of quantitative genetics remain untested. Here we demonstrate that the substantial phenotypic skew in the body size of juvenile blue tits (Cyanistes caeruleus) is driven by environmental factors. Although skew had little impact on our predictions of selection response in this case, our results highlight the impact of skew on the estimation of inheritance and selection. Specifically, the nonlinear parent-offspring regressions induced by skew, alongside selective disappearance, can strongly bias estimates of heritability. The ubiquity of skew and strong directional selection on juvenile body size imply that heritability is commonly overestimated, which may in part explain the discrepancy between predicted and observed trait evolution., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

The mismatch between when individuals breed and when we think they should breed has been a long-standing problem in evolutionary ecology. Price et al. is a classic theory paper in this field and is mainly cited for its most obvious result: if individuals with high nutritional condition breed early, then the advantage of breeding early may be overestimated when information on nutritional condition is absent. Price at al.'s less obvious result is that individuals, on average, are expected to breed later than the optimum. Here, we provide an explanation of their non-intuitive result in terms of hard selection, and go on to show that neither of their results are expected to hold if the relationship between breeding date and nutrition is allowed to evolve. By introducing the assumption that the advantage of breeding early is greater for individuals in high nutritional condition, we show that their most cited result can be salvaged. However, individuals, on average, are expected to breed earlier than the optimum, not later. More generally, we also show that the hard selection mechanisms that underpin these results have major implications for the evolution of plasticity: when environmental heterogeneity becomes too great, plasticity is selected against, prohibiting the evolution of generalists., (© 2022 The Authors. Evolution Letters published by Wiley Periodicals LLC on behalf of Society for the Study of Evolution (SSE) and European Society for Evolutionary Biology (ESEB).)

Cell synchronization allows the examination of cell cycle progression. Nocodazole and other microtubule poisons have been used extensively to interfere with microtubule function and arrest cells in mitosis. Since microtubules are important for many cellular functions, alternative cell cycle synchronization techniques independent of microtubule inhibition are also used for synchronizing cells in mitosis. Here we describe using nocodazole, STLC, and combining thymidine block with MG132 to synchronize cells in mitosis. These inhibitors are reversible and mitotic cells can be released into the G1 phase synchronously. These techniques can be applied to both Western blot and timelapse imaging to study mitotic progression., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Rather little is known about the dietary richness and variation of generalist insectivorous species, including birds, due primarily to difficulties in prey identification. Using faecal metabarcoding, we provide the most comprehensive analysis of a passerine's diet to date, identifying the relative magnitudes of biogeographic, habitat and temporal trends in the richness and turnover in diet of Cyanistes caeruleus (blue tit) along a 39 site and 2° latitudinal transect in Scotland. Faecal samples were collected in 2014-2015 from adult birds roosting in nestboxes prior to nest building. DNA was extracted from 793 samples and we amplified COI and 16S minibarcodes. We identified 432 molecular operational taxonomic units that correspond to putative dietary items. Most dietary items were rare, with Lepidoptera being the most abundant and taxon-rich prey order. Here, we present a statistical approach for estimation of gradients and intersample variation in taxonomic richness and turnover using a generalised linear mixed model. We discuss the merits of this approach over existing tools and present methods for model-based estimation of repeatability, taxon richness and Jaccard indices. We found that dietary richness increases significantly as spring advances, but changes little with elevation, latitude or local tree composition. In comparison, dietary composition exhibits significant turnover along temporal and spatial gradients and among sites. Our study shows the promise of faecal metabarcoding for inferring the macroecology of food webs, but we also highlight the challenge posed by contamination and make recommendations of laboratory and statistical practices to minimise its impact on inference., (© 2020 John Wiley & Sons Ltd.)

Most theoretical studies have explored the evolution of plasticity when the environment, and therefore the optimal trait value, varies in time or space. When the environment varies in time and space, we show that genetic adaptation to Markovian temporal fluctuations depends on the between-generation autocorrelation in the environment in exactly the same way that genetic adaptation to spatial fluctuations depends on the probability of philopatry. This is because both measure the correlation in parent-offspring environments and therefore the effectiveness of a genetic response to selection. If the capacity to genetically respond to selection is stronger in one dimension (e.g., space), then plasticity mainly evolves in response to fluctuations in the other dimension (e.g., time). If the relationships between the environments of development and selection are the same in time and space, the evolved plastic response to temporal fluctuations is useful in a spatial context and genetic differentiation in space is reduced. However, if the relationships between the environments of development and selection are different, the optimal level of plasticity is different in the two dimensions. In this case, the plastic response that evolves to cope with temporal fluctuations may actually be maladaptive in space, resulting in the evolution of hyperplasticity or negative plasticity. These effects can be mitigated by spatial genetic differentiation that acts in opposition to plasticity resulting in counter-gradient variation. These results highlight the difficulty of making space-for-time substitutions in empirical work but identify the key parameters that need to be measured in order to test whether space-for-time substitutions are likely to be valid.

Parent and offspring behaviors are expected to act as both the agents and targets of selection. This may generate parent-offspring coadaptation in which parent and offspring behaviors become genetically correlated in a way that increases inclusive fitness. Cross-fostering has been used to study parent-offspring coadaptation, with the prediction that offspring raised by non-relatives, or parents raising non-relatives, should suffer fitness costs. Using long-term data from more than 400 partially crossed broods of blue tits (Cyanistes caeruleus), we show that there is no difference in mass or survival between crossed and non-crossed chicks. However, previous studies for which the evidence for parent-offspring coadaptation is strongest compare chicks from fully crossed broods with those from non-crossed broods. When parent-offspring coadaptation acts at the level of the brood then partial cross-fostering experiments are not expected to show evidence of coadaptation. To test this, we performed an additional experiment (163 broods) in which clutches were either fully crossed, non-crossed, or partially crossed. In agreement with the long-term data, there was no evidence for parent-offspring coadaptation on offspring fitness despite high power. In addition there was no evidence of effects on parental fitness, nor evidence of sibling coadaptation, although the power of these tests was more modest., (© 2018 The Authors Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.)

Host shifts-where a pathogen jumps between different host species-are an important source of emerging infectious disease. With on-going climate change there is an increasing need to understand the effect changes in temperature may have on emerging infectious disease. We investigated whether species' susceptibilities change with temperature and ask if susceptibility is greatest at different temperatures in different species. We infected 45 species of Drosophilidae with an RNA virus and measured how viral load changes with temperature. We found the host phylogeny explained a large proportion of the variation in viral load at each temperature, with strong phylogenetic correlations between viral loads across temperature. The variance in viral load increased with temperature, while the mean viral load did not. This suggests that as temperature increases the most susceptible species become more susceptible, and the least susceptible less so. We found no significant relationship between a species' susceptibility across temperatures, and proxies for thermal optima (critical thermal maximum and minimum or basal metabolic rate). These results suggest that whilst the rank order of species susceptibilities may remain the same with changes in temperature, some species may become more susceptible to a novel pathogen, and others less so., Competing Interests: The authors have declared that no competing interests exist.

Conflict between organisms can lead to a reciprocal adaptation that manifests as an increased evolutionary rate in genes mediating the conflict. This adaptive signature has been observed in RNA-interference (RNAi) pathway genes involved in the suppression of viruses and transposable elements in Drosophila melanogaster , suggesting that a subset of Drosophila RNAi genes may be locked in an arms race with these parasites. However, it is not known whether rapid evolution of RNAi genes is a general phenomenon across invertebrates, or which RNAi genes generally evolve adaptively. Here we use population genomic data from eight invertebrate species to infer rates of adaptive sequence evolution, and to test for past and ongoing selective sweeps in RNAi genes. We assess rates of adaptive protein evolution across species using a formal meta-analytic framework to combine data across species and by implementing a multispecies generalized linear mixed model of mutation counts. Across species, we find that RNAi genes display a greater rate of adaptive protein substitution than other genes, and that this is primarily mediated by positive selection acting on the genes most likely to defend against viruses and transposable elements. In contrast, evidence for recent selective sweeps is broadly spread across functional classes of RNAi genes and differs substantially among species. Finally, we identify genes that exhibit elevated adaptive evolution across the analyzed insect species, perhaps due to concurrent parasite-mediated arms races., (Copyright © 2018 Palmer et al.)

One consequence of rising spring temperatures is that the optimum timing of key life-history events may advance. Where this is the case, a population's fate may depend on the degree to which it is able to track a change in the optimum timing either via plasticity or via adaptation. Estimating the effect that temperature change will have on optimum timing using standard approaches is logistically challenging, with the result that very few estimates of this important parameter exist. Here we adopt an alternative statistical method that substitutes space for time to estimate the temperature sensitivity of the optimum timing of 22 plant species based on >200 000 spatiotemporal phenological observations from across the United Kingdom. We find that first leafing and flowering dates are sensitive to forcing (spring) temperatures, with optimum timing advancing by an average of 3 days °C -1 and plastic responses to forcing between -3 and -8 days °C -1 . Chilling (autumn/winter) temperatures and photoperiod tend to be important cues for species with early and late phenology, respectively. For most species, we find that plasticity is adaptive, and for seven species, plasticity is sufficient to track geographic variation in the optimum phenology. For four species, we find that plasticity is significantly steeper than the optimum slope that we estimate between forcing temperature and phenology, and we examine possible explanations for this countergradient pattern, including local adaptation., (© 2017 The Authors Global Change Biology Published by John Wiley & Sons Ltd.)

There is abundant evidence in many taxa for positive directional selection on body size, and yet little evidence for microevolutionary change. In many species, variation in body size is partly determined by the actions of parents, so a proposed explanation for stasis is the presence of a negative genetic correlation between direct and parental effects. Consequently, selecting genes for increased body size would result in a correlated decline in parental effects, reducing body size in the following generation. We show that these arguments implicitly assume that parental care is cost free, and that including a cost alters the predicted genetic architectures needed to explain stasis. Using a large cross-fostered population of blue tits, we estimate direct selection on parental effects for body mass, and show it is negative. Negative selection is consistent with a cost to parental care, mainly acting through a reduction in current fecundity rather than survival. Under these conditions, evolutionary stasis is possible for moderately negative genetic correlations between direct and parental effects. This is in contrast to the implausibly extreme correlations needed when care is assumed to be cost-free. Thus, we highlight the importance of accounting correctly for complete selection acting on traits across generations., (© 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.)

Projecting the fates of populations under climate change is one of global change biology's foremost challenges. Here, we seek to identify the contributions that temperature-mediated local adaptation and plasticity make to spatial variation in nesting phenology, a phenotypic trait showing strong responses to warming. We apply a mixed modeling framework to a Britain-wide spatiotemporal dataset comprising >100 000 records of first egg dates from four single-brooded passerine bird species. The average temperature during a specific time period (sliding window) strongly predicts spatiotemporal variation in lay date. All four species exhibit phenological plasticity, advancing lay date by 2-5 days °C(-1) . The initiation of this sliding window is delayed further north, which may be a response to a photoperiod threshold. Using clinal trends in phenology and temperature, we are able to estimate the temperature sensitivity of selection on lay date (B), but our estimates are highly sensitive to the temporal position of the sliding window. If the sliding window is of fixed duration with a start date determined by photoperiod, we find B is tracked by phenotypic plasticity. If, instead, we allow the start and duration of the sliding window to change with latitude, we find plasticity does not track B, although in this case, at odds with theoretical expectations, our estimates of B differ across latitude vs. longitude. We argue that a model combining photoperiod and mean temperature is most consistent with current understanding of phenological cues in passerines, the results from which suggest that each species could respond to projected increases in spring temperatures through plasticity alone. However, our estimates of B require further validation., (© 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)

To make progress scientists need to know what other researchers have found and how they found it. However, transparency is often insufficient across much of ecology and evolution. Researchers often fail to report results and methods in detail sufficient to permit interpretation and meta-analysis, and many results go entirely unreported. Further, these unreported results are often a biased subset. Thus the conclusions we can draw from the published literature are themselves often biased and sometimes might be entirely incorrect. Fortunately there is a movement across empirical disciplines, and now within ecology and evolution, to shape editorial policies to better promote transparency. This can be done by either requiring more disclosure by scientists or by developing incentives to encourage disclosure., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The distribution of phenotypes in space will be a compromise between adaptive plasticity and local adaptation increasing the fit of phenotypes to local conditions and gene flow reducing that fit. Theoretical models on the evolution of quantitative characters on spatially explicit landscapes have only considered scenarios where optimum trait values change as deterministic functions of space. Here, these models are extended to include stochastic spatially autocorrelated aspects to the environment, and consequently the optimal phenotype. Under these conditions, the regression of phenotype on the environmental variable becomes steeper as the spatial scale on which populations are sampled becomes larger. Under certain deterministic models - such as linear clines - the regression is constant. The way in which the regression changes with spatial scale is informative about the degree of phenotypic plasticity, the relative scale of effective gene flow and the environmental dependency of selection. Connections to temporal models are discussed., (© 2016 John Wiley & Sons Ltd/CNRS.)

Estimates of molecular genetic variation are often used as a cheap and simple surrogate for a population's adaptive potential, yet empirical evidence suggests they are unlikely to be a valid proxy. However, this evidence is based on molecular genetic variation poorly predicting estimates of adaptive potential rather than how well it predicts true values. As a consequence, the relationship has been systematically underestimated and the precision with which it could be measured severely overstated. By collating a large database, and using suitable statistical methods, we obtain a 95% upper bound of 0.26 for the proportion of variance in quantitative genetic variation explained by molecular diversity. The relationship is probably too weak to be useful, but this conclusion must be taken as provisional: less noisy estimates of quantitative genetic variation are required. In contrast, and perhaps surprisingly, current sampling strategies appear sufficient for characterising a population's molecular genetic variation at comparable markers., (© 2015 John Wiley & Sons Ltd/CNRS.)

Whenever allele frequencies are unequal, nonadditive gene action contributes to additive genetic variance and therefore the resemblance between parents and offspring. The reason for this has not been easy to understand. Here, we present a new single-locus decomposition of additive genetic variance that may give greater intuition about this important result. We show that the contribution of dominant gene action to parent-offspring resemblance only depends on the degree to which the heterozygosity of parents and offspring covary. Thus, dominant gene action only contributes to additive genetic variance when heterozygosity is heritable. Under most circumstances this is the case because individuals with rare alleles are more likely to be heterozygous, and because they pass rare alleles to their offspring they also tend to have heterozygous offspring. When segregating alleles are at equal frequency there are no rare alleles, the heterozygosities of parents and offspring are uncorrelated and dominant gene action does not contribute to additive genetic variance., (© 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.)

Quantitative genetic analysis is often fundamental for understanding evolutionary processes in wild populations. Avian populations provide a model system due to the relative ease of inferring relatedness among individuals through observation. However, extra-pair paternity (EPP) creates erroneous links within the social pedigree. Previous work has suggested this causes minor underestimation of heritability if paternal misassignment is random and hence not influenced by the trait being studied. Nevertheless, much literature suggests numerous traits are associated with EPP and the accuracy of heritability estimates for such traits remains unexplored. We show analytically how nonrandom pedigree errors can influence heritability estimates. Then, combining empirical data from a large great tit (Parus major) pedigree with simulations, we assess how heritability estimates derived from social pedigrees change depending on the mode of the relationship between EPP and the focal trait. We show that the magnitude of the underestimation is typically small (<15%). Hence, our analyses suggest that quantitative genetic inference from pedigrees derived from observations of social relationships is relatively robust; our approach also provides a widely applicable method for assessing the consequences of nonrandom EPP., (© 2015 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.)

Emerging infectious diseases are often the result of a host shift, where the pathogen originates from a different host species. Virulence--the harm a pathogen does to its host-can be extremely high following a host shift (for example Ebola, HIV, and SARs), while other host shifts may go undetected as they cause few symptoms in the new host. Here we examine how virulence varies across host species by carrying out a large cross infection experiment using 48 species of Drosophilidae and an RNA virus. Host shifts resulted in dramatic variation in virulence, with benign infections in some species and rapid death in others. The change in virulence was highly predictable from the host phylogeny, with hosts clustering together in distinct clades displaying high or low virulence. High levels of virulence are associated with high viral loads, and this may determine the transmission rate of the virus.

Disease progression in HIV-infected individuals varies greatly, and while the environmental and host factors influencing this variation have been widely investigated, the viral contribution to variation in set-point viral load, a predictor of disease progression, is less clear. Previous studies, using transmission-pairs and analysis of phylogenetic signal in small numbers of individuals, have produced a wide range of viral genetic effect estimates. Here we present a novel application of a population-scale method based in quantitative genetics to estimate the viral genetic effect on set-point viral load in the UK subtype B HIV-1 epidemic, based on a very large data set. Analyzing the initial viral load and associated pol sequence, both taken before anti-retroviral therapy, of 8,483 patients, we estimate the proportion of variance in viral load explained by viral genetic effects to be 5.7% (CI 2.8-8.6%). We also estimated the change in viral load over time due to selection on the virus and environmental effects to be a decline of 0.05 log10 copies/mL/year, in contrast to recent studies which suggested a reported small increase in viral load over the last 20 years might be due to evolutionary changes in the virus. Our results suggest that in the UK epidemic, subtype B has a small but significant viral genetic effect on viral load. By allowing the analysis of large sample sizes, we expect our approach to be applicable to the estimation of the genetic contribution to traits in many organisms.

The evolution of traits involved in ecological interactions such as predator-prey, host-parasite, and plant-pollinator interactions, are likely to be shaped by the phylogenetic history of both parties. We develop generalized linear mixed-effects models (GLMM) that estimate the effect of both parties' phylogenetic history on trait evolution, both in isolation but also in terms of how the two histories interact. Using data on the incidence and abundance of 206 flea species on 121 mammal species, we illustrate our method and compare it to previously used methods for detecting host-parasite coevolution. At large spatial scales we find that the phylogenetic interaction effect was substantial, indicating that related parasite species were more likely to be found on related host species. At smaller spatial scales, and when sampling effort was not controlled for, phylogenetic effects on the number and types of parasite species harbored by hosts were found to dominate. We go on to show that in situations where these additional phylogenetic effects exist, then previous methods have very high Type I error rates when testing for the phylogenetic interaction. Our GLMM method represents a robust and reliable approach to quantify the phylogenetic effects of traits determined by, or defined by, ecological interactions and has the advantage that it can easily be extended and interpreted in a broader context than existing permutation tests.

Facultative or "secondary" symbionts are common in eukaryotes, particularly insects. While not essential for host survival, they often provide significant fitness benefits. It has been hypothesized that secondary symbionts form a "horizontal gene pool" shuttling adaptive genes among host lineages in an analogous manner to plasmids and other mobile genetic elements in bacteria. However, we do not know whether the distributions of symbionts across host populations reflect random acquisitions followed by vertical inheritance or whether the associations have occurred repeatedly in a manner consistent with a dynamic horizontal gene pool. Here we explore these questions using the phylogenetic and ecological distributions of secondary symbionts carried by 1,104 pea aphids, Acyrthosiphon pisum. We find that not only is horizontal transfer common, but it is also associated with aphid lineages colonizing new ecological niches, including novel plant species and climatic regions. Moreover, aphids that share the same ecologies worldwide have independently acquired related symbiont genotypes, suggesting significant involvement of symbionts in their host's adaptation to different niches. We conclude that the secondary symbiont community forms a horizontal gene pool that influences the adaptation and distribution of their insect hosts. These findings highlight the importance of symbiotic microorganisms in the radiation of eukaryotes., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Cross-fostering experiments are widely used by quantitative geneticists to study genetics and by behavioral ecologists to study the effects of prenatal investment. Generally, the effects of genes and prenatal investment are confounded and the interpretation given to such experiments is largely dependent on the interests of the researcher. Using a large-scale well-controlled experiment on a wild population of blue tits (Cyanistes caeruleus), we are able to partition variation in body mass across ontogeny into the effects of genes and the effects of between-clutch variation in egg characteristics. We show that although egg effects are important early in ontogeny they quickly dissipate, suggesting that the genetic interpretation of cross-fostering experiments may be preferable for many types of trait. However, the heritability of body mass is smaller than has previously been reported. Our results suggest that this is due to a combination of controlling postnatal environmental effects more carefully and accounting for viability selection operating early in ontogeny., (© 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.)

The relative age of an individual's siblings is a major cause of fitness variation in many species. In Blue tits (Cyanistes caeruleus), we show that age hierarchies are predominantly caused by incubation preclutch completion, such that last laid eggs hatch later than early laid eggs. However, after statistically controlling for incubation behavior late laid eggs are shown to hatch more quickly than early laid eggs reducing the amount of asynchrony. By experimentally switching early and late laid eggs between nests on the day they were laid, we controlled for the effect of differential incubation and found that the faster hatching times of late laid eggs remains. Chicks that hatched earlier were heavier and had higher probability of fledgling, and chicks that hatched from experimental eggs had patterns of growth and survival consistent with this. Egg mass explained a small part of this variation, but the remainder must be due to egg composition. These results are consistent with the idea that intrinsic differences between eggs across the laying sequence serve to mitigate the effects of age-related hierarchies. We also show that between-clutch variation in prenatal developmental rate exists and that it is mainly environmental in origin rather than genetic., (© 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.)

Using 20 years of demographic and genetic data from four populations of banner-tailed kangaroo rats (Dipodomys spectabilis), we asked whether dispersing individuals gain benefits during adulthood that might compensate for the substantial survival costs they experience as juveniles. Compared to philopatric animals, within- and between-population dispersers gained no measureable advantages in adult survival, fecundity, or probability of recruiting offspring to adulthood. Restricting analyses to members of two central populations living more than 15 times the median dispersal distance from the study site edge, and using peripheral populations only to detect dispersal or offspring recruitment "offsite," did not change this result. Population density during year of birth had small negative effects on adult survival and fecundity, but there were no interactions with dispersal phenotype. We found no evidence that dispersers gained access to superior habitat or that their offspring suffered less inbreeding depression. Our results are consistent with fitness advantages being indirect; by leaving, dispersers release their kin from competition. Our results are also consistent with the possibility that dispersal is the "best of a bad lot." If dispersal is a conditional strategy, then the benefits may be obscured in observational data that compare dispersing individuals to philopatric individuals rather than to individuals whose dispersal phenotype is experimentally manipulated.

Genetic correlations between parasite resistance and other traits can act as an evolutionary constraint and prevent a population from evolving increased resistance. For example, previous studies have found negative genetic correlations between host resistance and life-history traits. In invertebrates, the level of resistance often depends on the combination of the host and parasite genotypes, and in this study, we have investigated whether such specific resistance also acts as an evolutionary constraint. We measured the resistance of different genotypes of the fruit fly Drosophila melanogaster to different genotypes of a naturally occurring pathogen, the sigma virus. Using a multitrait analysis, we examine whether genetic covariances alter the potential to select for general resistance against all of the different viral genotypes. We found large amounts of heritable variation in resistance, and evidence for specific interactions between host and parasite, but these interactions resulted in little constraint on Drosophila evolving greater resistance., (© 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.)

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., (© 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.)

Pathogens switching to new hosts can result in the emergence of new infectious diseases, and determining which species are likely to be sources of such host shifts is essential to understanding disease threats to both humans and wildlife. However, the factors that determine whether a pathogen can infect a novel host are poorly understood. We have examined the ability of three host-specific RNA-viruses (Drosophila sigma viruses from the family Rhabdoviridae) to persist and replicate in 51 different species of Drosophilidae. Using a novel analytical approach we found that the host phylogeny could explain most of the variation in viral replication and persistence between different host species. This effect is partly driven by viruses reaching a higher titre in those novel hosts most closely related to the original host. However, there is also a strong effect of host phylogeny that is independent of the distance from the original host, with viral titres being similar in groups of related hosts. Most of this effect could be explained by variation in general susceptibility to all three sigma viruses, as there is a strong phylogenetic correlation in the titres of the three viruses. These results suggest that the source of new emerging diseases may often be predictable from the host phylogeny, but that the effect may be more complex than simply causing most host shifts to occur between closely related hosts.

Cryptic evolution has been defined as adaptive evolutionary change being masked by concurrent environmental change. Empirical studies of cryptic evolution have usually invoked a changing climate and/or increasing population density as the form of detrimental environmental change experienced by a population undergoing cryptic evolution. However, Fisher (1958) emphasized that evolutionary change in itself is likely to be an important component of "environmental deterioration," a point restated by Cooke et al. (1990) in the context of intraspecific competition. In this form, environmental deterioration arises because a winning lineage has to compete against more winners in successive generations as the population evolves. This "evolutionary environmental deterioration" has different implications for the selection and evolution of traits influenced by resource competition than general environmental change. We reformulate Cooke's model as a quantitative genetic model to show that it is identical in form to more recent developments proposed by quantitative geneticists. This provides a statistical framework for discriminating between the alternative hypotheses of environmental change and environmental deterioration caused by evolutionary change. We also demonstrate that in systems where no phenotypic change has occurred, there are many reasonable biological processes that will generate patterns in predicted breeding values that are consistent with what has been interpreted as cryptic evolution, and care needs to be taken when interpreting these patterns. These processes include mutation, sib competition, and invisible fractions.

Estimating rates of movement among populations is never simple, and where young animals cannot all be captured at their birth sites, traditional field methods potentially underestimate dispersal rates. Genetic assignment tests appear to hold promise for detecting 'precapture' dispersal, and recent evidence suggests that even on the scale of dispersal between populations, genetic parentage analyses can also be informative. Herein, we examine the performance of both types of analysis with data from a 17-year study of dispersal in banner-tailed kangaroo rats Dipodomys spectabilis. We compare estimates of precapture dispersal from (i) the commonly used parentage analysis program cervus (ii) a pedigree-reconstruction program, MasterBayes, that combines genetic with spatial and other nongenetic information and (iii) genetic assignment procedures implemented by the program geneclass2, with (iv) rates of dispersal observed through recapture of a subset of animals initially marked shortly after weaning. geneclass2 estimates a larger proportion of precapture dispersers than MasterBayes, but both approaches as well as those based on field data alone, suggest that approximately 10% of adults in local populations are immigrants and that interpopulation dispersal is slightly female-biassed. All genetic procedures detect precapture dispersal between populations, but dispersers identified by MasterBayes are particularly compatible with what is independently known about body mass at dispersal, dispersal distance and distance between parents. Parentage analyses have considerable potential to infer the value of this otherwise elusive demographic parameter when most candidate parents can be genotyped and when nongenetic information, especially the distance separating candidate mothers and fathers, can be incorporated into the procedure., (© 2011 Blackwell Publishing Ltd.)

Mating behaviour is a fundamental aspect of the evolutionary ecology of sexually reproducing species, but one that has been under-researched in parasitic nematodes. We analysed mating behaviour in the parasitic nematode Trichostrongylus tenuis by performing a paternity analysis in a population from a single red grouse host. Paternity of the 150 larval offspring of 25 mothers (sampled from one of the two host caeca) was assigned among 294 candidate fathers (sampled from both caeca). Each candidate father's probability of paternity of each offspring was estimated from 10-locus microsatellite genotypes. Seventy-six (51%) offspring were assigned a father with a probability of >0.8, and the estimated number of unsampled males was 136 (95% credible interval (CI) 77-219). The probability of a male from one caecum fathering an offspring in the other caecum was estimated as 0.024 (95% CI 0.003-0.077), indicating that the junction of the caeca is a strong barrier to dispersal. Levels of promiscuity (defined as the probability of two of an adult's offspring sharing only one parent) were high for both sexes. Variance in male reproductive success was moderately high, possibly because of a combination of random mating and high variance in post-copulatory reproductive success. These results provide the first data on individual mating behaviour among parasitic nematodes.

Phenotypic differences between populations often correlate with climate variables, resulting from a combination of environment-induced plasticity and local adaptation. Species comprising populations that are genetically adapted to local climatic conditions should be more vulnerable to climate change than those comprising phenotypically plastic populations. Assessment of local adaptation generally requires logistically challenging experiments. Here, using a unique approach and a large dataset (>50,000 observations from across Britain), we compare the covariation in temperature and first spawning dates of the common frog (Rana temporaria) across space with that across time. We show that although all populations exhibit a plastic response to temperature, spawning earlier in warmer years, between-population differences in first spawning dates are dominated by local adaptation. Given climate change projections for Britain in 2050-2070, we project that for populations to remain as locally adapted as contemporary populations will require first spawning date to advance by approximately 21-39 days but that plasticity alone will only enable an advance of approximately 5-9 days. Populations may thus face a microevolutionary and gene flow challenge to advance first spawning date by a further approximately 16-30 days over the next 50 years.

Knowledge of the parentage of individuals is required to address a variety of questions concerning the evolutionary dynamics of wild populations. A major advance in parentage inference in natural populations has been the use of molecular markers and the development of statistical methods to analyse these data. Cervus, one of the most widely used parentage inference programs, uses molecular data to determine parent-offspring relationships. However, Cervus does not make use of all available information: additional phenotypic information may exist predicting parent-offspring relationships, and additional genetic information may be exploited by simultaneously considering multiple types of relationships rather than just pairwise or just parent-offspring relationships. Here we reanalyse data from a wild red deer population using two programs capable of using this additional information, MasterBayes and COLONY2, and quantify the impact of these alternative approaches by comparison with a 'known pedigree' estimated using a larger suite of microsatellite makers for a subset of the population. The use of phenotypic information and multiple relationships increased the number of correct assignments. We highlight the differences between programs, particularly the use of population- rather than individual-level statistical confidence in Cervus. We conclude that the use of additional information allows MasterBayes and COLONY2 to assign more correct paternities, whereas their use of individual- rather than population-level confidence generates fewer erroneous assignments. We suggest that maximal information may be gained by combining outputs from different programs. Higher accuracy and completeness of pedigree information will improve parameters estimated from pedigree information in studies of natural populations.

Although many of the statistical techniques used in comparative biology were originally developed in quantitative genetics, subsequent development of comparative techniques has progressed in relative isolation. Consequently, many of the new and planned developments in comparative analysis already have well-tested solutions in quantitative genetics. In this paper, we take three recent publications that develop phylogenetic meta-analysis, either implicitly or explicitly, and show how they can be considered as quantitative genetic models. We highlight some of the difficulties with the proposed solutions, and demonstrate that standard quantitative genetic theory and software offer solutions. We also show how results from Bayesian quantitative genetics can be used to create efficient Markov chain Monte Carlo algorithms for phylogenetic mixed models, thereby extending their generality to non-Gaussian data. Of particular utility is the development of multinomial models for analysing the evolution of discrete traits, and the development of multi-trait models in which traits can follow different distributions. Meta-analyses often include a nonrandom collection of species for which the full phylogenetic tree has only been partly resolved. Using missing data theory, we show how the presented models can be used to correct for nonrandom sampling and show how taxonomies and phylogenies can be combined to give a flexible framework with which to model dependence.

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.

It is common practice to use microsatellites to detect parents and their offspring in wild and captive populations, in order to reconstruct a pedigree. However, correct inference is often constrained by a number of factors, including the absence of demographic data and ignorance regarding the completeness of parental sampling. Here we present a new Bayesian estimator that simultaneously estimates the pedigree and the size of the unsampled population. The method is robust to genotyping error, and can estimate pedigrees in the absence of demographic data. Using a large-scale microsatellite assay in four wild cichlid fish populations of Lake Tanganyika (1000 individuals in total), we assess the performance of the Bayesian estimator against the most popular assignment program, Cervus. We found small but significant pedigrees in each of the tested populations using the Bayesian procedure, but Cervus had very high type I error rates when the size of the unsampled population was assumed to be lower than what it was. The need of pedigree relationships to infer adaptive processes in natural populations places strong constraints on sampling design and identification of multigenerational pedigrees in natural populations.

Recent studies have suggested that females of the field cricket Gryllus bimaculatus exercise post-copulatory choice over the paternity of their offspring. There is evidence that these choices are made in relation to the genetic compatibility of mates rather than their absolute quality, but the magnitude of heritable differences in males has not been thoroughly examined. Using a half-sib breeding design we measured additive genetic variance and dam effects in a suite of reproductive and non-reproductive traits. Both components explained relatively little of the phenotypic variance across traits. The dam component in our design contains variance caused by both maternal effects and dominance. If maternal effects are negligible as suggested by previous studies, our data suggest that dominance variance is an important source of variation in these traits. The lack of additive genetic variation, but possible existence of large amounts of non-additive genetic variation is consistent with the idea that female mate choice and multiple mating may be driven by differences in genetic compatibility between potential mates rather than by differences in genetic quality.

Some individuals die before a trait is measured or expressed (the invisible fraction), and some relevant traits are not measured in any individual (missing traits). This paper discusses how these concepts can be cast in terms of missing data problems from statistics. Using missing data theory, I show formally the conditions under which a valid evolutionary inference is possible when the invisible fraction and/or missing traits are ignored. These conditions are restrictive and unlikely to be met in even the most comprehensive long-term studies. When these conditions are not met, many selection and quantitative genetic parameters cannot be estimated accurately unless the missing data process is explicitly modelled. Surprisingly, this does not seem to have been attempted in evolutionary biology. In the case of the invisible fraction, viability selection and the missing data process are often intimately linked. In such cases, models used in survival analysis can be extended to provide a flexible and justified model of the missing data mechanism. Although missing traits pose a more difficult problem, important biological parameters can still be estimated without bias when appropriate techniques are used. This is in contrast to current methods which have large biases and poor precision. Generally, the quantitative genetic approach is shown to be superior to phenotypic studies of selection when invisible fractions or missing traits exist because part of the missing information can be recovered from relatives.

Global warming has had numerous effects on populations of animals and plants, with many species in temperate regions experiencing environmental change at unprecedented rates. Populations with low potential for adaptive evolutionary change and plasticity will have little chance of persistence in the face of environmental change. Assessment of the potential for adaptive evolution requires the estimation of quantitative genetic parameters, but it is as yet unclear what impact, if any, global warming will have on the expression of genetic variances and covariances. Here we assess the impact of a changing climate on the genetic architecture underlying three reproductive traits in a wild bird population. We use a large, long-term, data set collected on great tits (Parus major) in Wytham Woods, Oxford, and an 'animal model' approach to quantify the heritability of, and genetic correlations among, laying date, clutch size and egg mass during two periods with contrasting temperature conditions over a 40-year period (1965-1988 [cooler] vs. 1989-2004 [warmer]). We found significant additive genetic variance and heritability for all traits under both temperature regimes. We also found significant negative genetic covariances and correlations between clutch size and egg weight during both periods, and among laying date and clutch size in the colder years only. The overall G matrix comparison among periods, however, showed only a minor difference among periods, thus suggesting that genotype by environment interactions are negligible in this context. Our results therefore suggest that despite substantial changes in temperature and in mean laying date phenotype over the last decades, and despite the large sample sizes available, we are unable to detect any significant change in the genetic architecture of the reproductive traits studied.

Bijma et al. (2007a,b) presented a quantitative genetic theory of multilevel selection and showed how to estimate the relevant parameters using standard restricted maximum-likelihood (REML) methodology. Extending their results we develop a wider class of models that provide a more realistic framework for capturing the effects of interacting individuals. These models also make use of standard REML techniques and include the original model as a special case.

Related individuals often have similar phenotypes, but this similarity may be due to the effects of shared environments as much as to the effects of shared genes. We consider here alternative approaches to separating the relative contributions of these two sources to phenotypic covariances, comparing experimental approaches such as cross-fostering, traditional statistical techniques and more complex statistical models, specifically the 'animal model'. Using both simulation studies and empirical data from wild populations, we demonstrate the ability of the animal model to reduce bias due to shared environment effects such as maternal or brood effects, especially where pedigrees contain multiple generations and immigration rates are low. However, where common environment effects are strong, a combination of both cross-fostering and an animal model provides the best way to avoid bias. We illustrate ways of partitioning phenotypic variance into components of additive genetic, maternal genetic, maternal environment, common environment, permanent environment and temporal effects, but also show how substantial confounding between these different effects may occur. Whilst the flexibility of the mixed model approach is extremely useful for incorporating the spatial, temporal and social heterogeneity typical of natural populations, the advantages will inevitably be restricted by the quality of pedigree information and care needs to be taken in specifying models that are appropriate to the data.

Theory predicts that biogeographic factors should play a central role in promoting population divergence and speciation. Previous empirical studies into biogeography and diversification have been relatively restricted in terms of the geographical area, phylogenetic scope, and the range of biogeographic factors considered. Here we present a global analysis of allopatric phenotypic divergence (measured as subspecies richness) across more than 9600 bird species. The main aim of this study was to examine the extent to which biogeographical factors can explain patterns of phenotypic divergence. Analysis of the taxonomic distribution of subspecies among species suggests that subspecies formation and extinction have occurred at a considerably faster rate than has species formation. However, the observed distribution departs from the expectation under a random birth-death model of diversification. Across 19 phylogenetic trees, we find no significant linear relationship between species age and subspecies richness, implying that species age is a poor predictor of subspecies richness. Both subspecies richness and subspecies diversification rate are found to exhibit low phylogenetic signal, meaning that closely related species do not tend to possess similar numbers of subspecies. As predicted by theory, high subspecies richness was associated with large breeding range size, island dwelling, inhabitation of montane regions, habitat heterogeneity, and low latitude. Of these factors, breeding range size was the variable that explained the most variation. Unravelling whether species that have invaded previously glacial areas have more or fewer subspecies than expected proves to be complicated due to a covariation between the postglacial colonization, latitude, geographic range size, and subspecies richness. However, the effect of postglacial colonization on subspecies richness appears to be small. Mapping the distribution of species' subspecies richness globally reveals geographical patterns that correspond to many of the predictions of the statistical models, but may also reflect geographical variation in taxonomic practice. Overall, we demonstrate that biogeographic models can explain about 30% of the global variation in subspecies richness in birds.