Meta-analysis of magnitudes, differences and variation in evolutionary parameters

Quantifying the phenome-wide response to sex-specific selection in Drosophila melanogaster

In species with separate sexes, the selection on males causes evolutionary change in female traits values (and vice versa) via genetic correlations, which has far-reaching consequences for adaptation. Here, we utilize a sex-specific form of Robertson's Secondary Theorem of Natural Selection to estimate the expected response to selection for 474 organismal-level traits and ~28,000 gene expression traits measured in the Drosophila Genetic Reference Panel (DGRP). Across organismal-level traits, selection acting on males produced a larger predicted evolutionary response than did selection acting on females, even for female traits; while for transcriptome traits selection on each sex produced a roughly equal average evolutionary response. For most traits, the selection on males and females was predicted to move average trait values in the same direction, though for some traits, the selection on one sex increased trait values while the selection on the other sex decreased them, implying intralocus sexual conflict. Our results provide support for the hypothesis that males experience stronger selection than females, potentially accelerating adaptation in females. Furthermore, sex-opposite responses to selection appear to exist for only a small proportion of traits, consistent with observations that the intersex genetic correlation for fitness is positive but less than one in most populations so far studied.

The paradox of predictability provides a bridge between micro- and macroevolution

The relationship between the evolutionary dynamics observed in contemporary populations (microevolution) and evolution on timescales of millions of years (macroevolution) has been a topic of considerable debate. Historically, this debate centers on inconsistencies between microevolutionary processes and macroevolutionary patterns. Here, we characterize a striking exception: emerging evidence indicates that standing variation in contemporary populations and macroevolutionary rates of phenotypic divergence is often positively correlated. This apparent consistency between micro- and macroevolution is paradoxical because it contradicts our previous understanding of phenotypic evolution and is so far unexplained. Here, we explore the prospects for bridging evolutionary timescales through an examination of this "paradox of predictability." We begin by explaining why the divergence-variance correlation is a paradox, followed by data analysis to show that the correlation is a general phenomenon across a broad range of temporal scales, from a few generations to tens of millions of years. Then we review complementary approaches from quantitative genetics, comparative morphology, evo-devo, and paleontology to argue that they can help to address the paradox from the shared vantage point of recent work on evolvability. In conclusion, we recommend a methodological orientation that combines different kinds of short-term and long-term data using multiple analytical frameworks in an interdisciplinary research program. Such a program will increase our general understanding of how evolution works within and across timescales.

Three modes of evolution? Remarks on rates of evolution and time scaling

Rates of evolution get smaller when they are measured over longer time intervals. As first shown by Gingerich, rates of morphological change measured from fossil time series show a robust minus-one scaling with time span, implying that evolutionary changes are just as large when measured over a hundred years as when measured over a hundred-thousand years. On even longer time scales, however, the scaling shifts toward a minus-half exponent consistent with evolution behaving as Brownian motion, as commonly observed in phylogenetic comparative studies. Here, I discuss how such scaling patterns arise, and I derive the patterns expected from standard stochastic models of evolution. I argue that observed shifts cannot be easily explained by simple univariate models, but require shifts in mode of evolution as time scale is changing. To illustrate this idea, I present a hypothesis about three distinct, but connected, modes of evolution. I analyze the scaling patterns predicted from this, and use the results to discuss how rates of evolution should be measured and interpreted. I argue that distinct modes of evolution at different time scales act to decouple micro- and macroevolution, and criticize various attempts at extrapolating from one to the other.

Linking divergence in phenotypic selection on floral traits to divergence in local pollinator assemblages in a pollination-generalized plant

Divergent patterns of phenotypic selection on floral traits can arise in response to interactions with functionally distinct pollinators. However, there are a limited number of studies that relate patterns of phenotypic selection on floral traits to variation in local pollinator assemblages in pollination-generalized plant species. We studied phenotypic selection on floral traits of Viscaria vulgaris, a plant that interacts with a broad range of diurnal and nocturnal pollinators, and related divergence in phenotypic selection on floral traits to the expected level of divergence in local pollinator assemblages. We detected phenotypic selection on floral traits involved in the attraction of pollinators and the mechanics of pollen removal and deposition, and demonstrated that floral traits are subject to spatiotemporal variation in the strength and direction of phenotypic selection. We revealed that diurnal and nocturnal pollinators, when considered in isolation, mediated divergent patterns of phenotypic selection on floral traits. Consistent with the Grant-Stebbins model, we observed that divergence in phenotypic selection on floral traits increased with the expected level of divergence in local pollinator assemblages. Thus, generalized plant-pollinator interactions can mediate phenotypic selection on floral traits, and distinct local pollinator assemblages can generate a geographic mosaic of divergent patterns of phenotypic selection. We underscore that these outcomes are not exclusive to specialized plant-pollinator interactions and can emerge at a local geographic scale.

The battle of the sexes in humans is highly polygenic

Sex-differential selection (SDS), which occurs when the fitness effects of alleles differ between males and females, can have profound impacts on the maintenance of genetic variation, disease risk, and other key aspects of natural populations. Because the sexes mix their autosomal genomes each generation, quantifying SDS is not possible using conventional population genetic approaches. Here, we introduce a method that exploits subtle sex differences in haplotype frequencies resulting from SDS acting in the current generation. Using data from 300K individuals in the UK Biobank, we estimate the strength of SDS throughout the genome. While only a handful of loci under SDS are individually significant, we uncover highly polygenic signals of genome-wide SDS for both viability and fecundity. Selection coefficients of [Formula: see text] may be typical. Despite its ubiquity, SDS may impose a mortality load of less than 1%. An interesting life-history tradeoff emerges: Alleles that increase viability more strongly in females than males tend to increase fecundity more strongly in males than in females. Finally, we find marginal evidence of SDS on fecundity acting on alleles affecting arm fat-free mass. Taken together, our findings connect the long-standing evidence of SDS acting on human phenotypes with its impact on the genome.

Meta-analytical evidence for frequency-dependent selection across the tree of life

Explaining the maintenance of genetic variation in fitness-related traits within populations is a fundamental challenge in ecology and evolutionary biology. Frequency-dependent selection (FDS) is one mechanism that can maintain such variation, especially when selection favours rare variants (negative FDS). However, our general knowledge about the occurrence of FDS, its strength and direction remain fragmented, limiting general inferences about this important evolutionary process. We systematically reviewed the published literature on FDS and assembled a database of 747 effect sizes from 101 studies to analyse the occurrence, strength, and direction of FDS, and the factors that could explain heterogeneity in FDS. Using a meta-analysis, we found that overall, FDS is more commonly negative, although not significantly when accounting for phylogeny. An analysis of absolute values of effect sizes, however, revealed the widespread occurrence of modest FDS. However, negative FDS was only significant in laboratory experiments and non-significant in mesocosms and field-based studies. Moreover, negative FDS was stronger in studies measuring fecundity and involving resource competition over studies using other fitness components or focused on other ecological interactions. Our study unveils key general patterns of FDS and points in future promising research directions that can help us understand a long-standing fundamental problem in evolutionary biology and its consequences for demography and ecological dynamics.

New horizons for comparative studies and meta-analyses

Comparative analyses and meta-analyses are key tools to elucidate broad biological principles, yet the two approaches often appear different in purpose. We propose an integrated approach that can generate deeper insights into ecoevolutionary processes. Marrying comparative and meta-analytic approaches will allow for (i) a more accurate investigation of drivers of biological variation, (ii) a greater ability to account for sources of non-independence in experimental data, (iii) more effective control of publication bias, and (iv) improved transparency and reproducibility. Stronger integration of meta-analytic and comparative studies can also broaden the scope from species-centric investigations to community-level responses and function-valued traits (e.g., reaction norms). We illuminate commonalities, differences, and the transformative potential of combining these methodologies for advancing ecology and evolutionary biology.

How seasonality influences the thermal biology of lizards with different thermoregulatory strategies: a meta-analysis

Ectotherms that maintain thermal balance in the face of varying climates should be able to colonise a wide range of habitats. In lizards, thermoregulation usually appears as a variety of behaviours that buffer external influences over physiology. Basking species rely on solar radiation to raise body temperatures and usually show high thermoregulatory precision. By contrast, species that do not bask are often constrained by climatic conditions in their habitats, thus having lower thermoregulatory precision. While much focus has been given to the effects of mean habitat temperatures, relatively less is known about how seasonality affects the thermal biology of lizards on a macroecological scale. Considering the current climate crisis, assessing how lizards cope with temporal variations in environmental temperature is essential to understand better how these organisms will fare under climate change. Activity body temperatures (Tb ) represent the internal temperature of an animal measured in nature during its active period (i.e. realised thermal niche), and preferred body temperatures (Tpref ) are those selected by an animal in a laboratory thermal gradient that lacks thermoregulatory costs (i.e. fundamental thermal niche). Both traits form the bulk of thermal ecology research and are often studied in the context of seasonality. In this study, we used a meta-analysis to test how environmental temperature seasonality influences the seasonal variation in the Tb and Tpref of lizards that differ in thermoregulatory strategy (basking versus non-basking). Based on 333 effect sizes from 137 species, we found that Tb varied over a greater magnitude than Tpref across seasons. Variations in Tb were not influenced by environmental temperature seasonality; however, body size and thermoregulatory strategy mediated Tb responses. Specifically, larger species were subjected to greater seasonal variations in Tb , and basking species endured greater seasonal variations in Tb compared to non-basking species. On the other hand, the seasonal variation in Tpref increased with environmental temperature seasonality regardless of body size. Thermoregulatory strategy also influenced Tpref , suggesting that behaviour has an important role in mediating Tpref responses to seasonal variations in the thermal landscape. After controlling for phylogenetic effects, we showed that Tb and Tpref varied significantly across lizard families. Taken together, our results support the notion that the relationship between thermal biology responses and climatic parameters can be taxon and trait dependent. Our results also showcase the importance of considering ecological and behavioural aspects in macroecological studies. We further highlight current systematic, geographical, and knowledge gaps in thermal ecology research. Our work should benefit those who aim to understand more fully how seasonality shapes thermal biology in lizards, ultimately contributing to the goal of elucidating the evolution of temperature-sensitive traits in ectotherms.

The missing fraction problem as an episodes of selection problem

In evolutionary quantitative genetics, the missing fraction problem refers to a specific kind of bias in parameters estimated later in life that occurs when nonrandom subsets of phenotypes are missing from the population due to prior viability selection on correlated traits. The missing fraction problem thus arises when the following hold: (a) viability selection and (b) correlation between later-life traits and traits important for early-life survival. Although it is plausible that these conditions are widespread in wild populations, this problem has received little empirical attention. This may be natural: the problem could appear intractable, given that it is impossible to measure phenotypes of individuals that have previously died. However, it is not impossible to correctly measure lifetime selection, or correctly predict evolutionary trajectories, of later-life traits in the presence of the missing fraction. Two basic strategies are available. First, given phenotypic data on selected early life traits, well established but underused episodes of selection theory can yield correct values of evolutionary parameters throughout life. Second, when traits subjected to early-life viability selection are not known and/or measured, it is possible to use the genetic association of later-life traits with early-life viability to correctly infer important information about the consequences of prior viability selection for later-life traits. By carefully reviewing the basic nature of the missing fraction problem, and describing the tractable solutions to the problem, we hope that future studies will be able to be better designed to cope with the (likely pervasive) consequences of early-life viability selection.

Sexually concordant selection on floral traits despite greater opportunity for selection through male fitness

Pollinators are important drivers of floral trait evolution, yet plant populations are not always perfectly adapted to their pollinators. Such apparent maladaptation may result from conflicting selection through male and female sexual functions in hermaphrodites. We studied sex-specific mating patterns and phenotypic selection on floral traits in Aconitum gymnandrum. After genotyping 1786 offspring, we partitioned individual fitness into sex-specific selfed and outcrossed components and estimated phenotypic selection acting through each. Relative fitness increased with increasing mate number, and more so for male function. This led to greater opportunity for selection through outcrossed male fitness, though patterns of phenotypic selection on floral traits tended to be similar, and with better support for selection through female rather than male fitness components. We detected directional selection through one or more fitness component for larger flower number, larger flowers, and more negative nectar gradients within inflorescences. Our results are consistent with Bateman's principles for sex-specific mating patterns and illustrate that, despite the expected difference in opportunity for selection, patterns of variation in selection across traits can be rather similar for the male and female sexual functions. These results shed new light on the effect of sexual selection on the evolution of floral traits.

Drift on holey landscapes as a dominant evolutionary process

An organism's phenotype has been shaped by evolution but the specific processes have to be indirectly inferred for most species. For example, correlations among traits imply the historical action of correlated selection and, more generally, the expression and distribution of traits is expected to be reflective of the adaptive landscapes that have shaped a population. However, our expectations about how quantitative traits-like most behaviors, physiological processes, and life-history traits-should be distributed under different evolutionary processes are not clear. Here, we show that genetic variation in quantitative traits is not distributed as would be expected under dominant evolutionary models. Instead, we found that genetic variation in quantitative traits across six phyla and 60 species (including both Plantae and Animalia) is consistent with evolution across high-dimensional "holey landscapes." This suggests that the leading conceptualizations and modeling of the evolution of trait integration fail to capture how phenotypes are shaped and that traits are integrated in a manner contrary to predictions of dominant evolutionary theory. Our results demonstrate that our understanding of how evolution has shaped phenotypes remains incomplete and these results provide a starting point for reassessing the relevance of existing evolutionary models.

Both Diet and Sociality Affect Primate Brain-Size Evolution

Increased brain size in humans and other primates is hypothesized to confer cognitive benefits but brings costs associated with growing and maintaining energetically expensive neural tissue. Previous studies have argued that changes in either diet or levels of sociality led to shifts in brain size, but results were equivocal. Here we test these hypotheses using phylogenetic comparative methods designed to jointly account for and estimate the effects of adaptation and phylogeny. Using the largest current sample of primate brain and body sizes with observation error, complemented by newly compiled diet and sociality data, we show that both diet and sociality have influenced the evolution of brain size. Shifting from simple to more complex levels of sociality resulted in relatively larger brains, while shifting to a more folivorous diet led to relatively smaller brains. While our results support the role of sociality, they modify a range of ecological hypotheses centered on the importance of frugivory, and instead indicate that digestive costs associated with increased folivory may have resulted in relatively smaller brains. [adaptation; allometry; bayou; evolutionary trend; energetic constraints; phylogenetic comparative methods; primate brain size; Slouch; social-brain hypothesis.].

Quantitative evidence synthesis: a practical guide on meta-analysis, meta-regression, and publication bias tests for environmental sciences

Meta-analysis is a quantitative way of synthesizing results from multiple studies to obtain reliable evidence of an intervention or phenomenon. Indeed, an increasing number of meta-analyses are conducted in environmental sciences, and resulting meta-analytic evidence is often used in environmental policies and decision-making. We conducted a survey of recent meta-analyses in environmental sciences and found poor standards of current meta-analytic practice and reporting. For example, only ~ 40% of the 73 reviewed meta-analyses reported heterogeneity (variation among effect sizes beyond sampling error), and publication bias was assessed in fewer than half. Furthermore, although almost all the meta-analyses had multiple effect sizes originating from the same studies, non-independence among effect sizes was considered in only half of the meta-analyses. To improve the implementation of meta-analysis in environmental sciences, we here outline practical guidance for conducting a meta-analysis in environmental sciences. We describe the key concepts of effect size and meta-analysis and detail procedures for fitting multilevel meta-analysis and meta-regression models and performing associated publication bias tests. We demonstrate a clear need for environmental scientists to embrace multilevel meta-analytic models, which explicitly model dependence among effect sizes, rather than the commonly used random-effects models. Further, we discuss how reporting and visual presentations of meta-analytic results can be much improved by following reporting guidelines such as PRISMA-EcoEvo (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Ecology and Evolutionary Biology). This paper, along with the accompanying online tutorial, serves as a practical guide on conducting a complete set of meta-analytic procedures (i.e., meta-analysis, heterogeneity quantification, meta-regression, publication bias tests and sensitivity analysis) and also as a gateway to more advanced, yet appropriate, methods.

Publication bias impacts on effect size, statistical power, and magnitude (Type M) and sign (Type S) errors in ecology and evolutionary biology

Collaborative efforts to directly replicate empirical studies in the medical and social sciences have revealed alarmingly low rates of replicability, a phenomenon dubbed the 'replication crisis'. Poor replicability has spurred cultural changes targeted at improving reliability in these disciplines. Given the absence of equivalent replication projects in ecology and evolutionary biology, two inter-related indicators offer the opportunity to retrospectively assess replicability: publication bias and statistical power. This registered report assesses the prevalence and severity of small-study (i.e., smaller studies reporting larger effect sizes) and decline effects (i.e., effect sizes decreasing over time) across ecology and evolutionary biology using 87 meta-analyses comprising 4,250 primary studies and 17,638 effect sizes. Further, we estimate how publication bias might distort the estimation of effect sizes, statistical power, and errors in magnitude (Type M or exaggeration ratio) and sign (Type S). We show strong evidence for the pervasiveness of both small-study and decline effects in ecology and evolution. There was widespread prevalence of publication bias that resulted in meta-analytic means being over-estimated by (at least) 0.12 standard deviations. The prevalence of publication bias distorted confidence in meta-analytic results, with 66% of initially statistically significant meta-analytic means becoming non-significant after correcting for publication bias. Ecological and evolutionary studies consistently had low statistical power (15%) with a 4-fold exaggeration of effects on average (Type M error rates = 4.4). Notably, publication bias reduced power from 23% to 15% and increased type M error rates from 2.7 to 4.4 because it creates a non-random sample of effect size evidence. The sign errors of effect sizes (Type S error) increased from 5% to 8% because of publication bias. Our research provides clear evidence that many published ecological and evolutionary findings are inflated. Our results highlight the importance of designing high-power empirical studies (e.g., via collaborative team science), promoting and encouraging replication studies, testing and correcting for publication bias in meta-analyses, and adopting open and transparent research practices, such as (pre)registration, data- and code-sharing, and transparent reporting.

Clinician- versus caregiver-rated scales as outcome measures of repetitive-restricted behaviors in clinical trials of autism: A systematic review and meta-analysis

The agreement between treatment effects measured by clinician- and caregiver-ratings of repetitive-restricted behaviors (RRBs) is important for clinical practice and research but is still unclear. Therefore, we conducted a post-hoc meta-analysis of placebo-controlled randomized-controlled trials (RCTs) investigating pharmacological and dietary-supplement treatments for autism that reported both clinician- and caregiver-ratings of RRBs. Treatment effects between medications and placebo were quantified with standardized mean differences (SMDs). The agreement between clinician- and caregiver-rated SMDs was investigated with an intraclass correlation coefficient (ICC) and random-effects meta-analysis of their difference (Δg). A meta-regression investigated the association between clinician (dependent) and caregiver-rated SMDs (independent variable). Certainty in the evidence was evaluated using the GRADE approach. We identified 15 eligible placebo-controlled RCTs with 1567 participants, from which 13 included children/adolescents and 9 reported data for the pair of the clinician-rated Yale-Brown Obsessive Compulsive Scale (YBOCS) and the caregiver-rated Aberrant Behavior Checklist-Stereotypic Behavior (ABC-S). There was on average a good agreement between clinician- and caregiver-rated SMDs (ICC=0.84, 95% confidence intervals [0.55, 0.95]), no clear difference between them (Δg=0.08, 95%CI[-0.06, 0.21], 95% prediction intervals [-0.16, 0.31]), and the beta of the meta-regression was 0.62, 95%CI[0.27, 0.97]. The certainty of the evidence was low due to concerns in imprecision and inconsistency. Our analysis showed on average a good agreement between clinician- and caregiver-rated treatment effects in RRBs, yet discordance could be expected in future RCTs, given the wide prediction intervals. It is also not certain that these results could be generalizable to other rating scales and intervention modalities. Ethics committee approval: Not applicable as a meta-analysis of previously published studies..

From whom do animals learn? A meta-analysis on model-based social learning

Social learning via the observation of or interaction with other individuals can allow animals to obtain information about the local environment. Once social information is obtained, animals may or may not act on and use this information. Animals may learn from others selectively based on particular characteristics (e.g., familiarity, age, dominance) of the information provider, which is thought to maximize the benefits of social learning. Biases to copy certain individuals over others plays an important role in how information is transmitted and used among individuals, and can influence the emergence of group-level behaviors (i.e., traditions). Two underlying factors can affect from whom animals learn: the population social dynamics - with whom you associate (e.g., familiar), and status of the demonstrator (e.g., dominant). We systematically surveyed the literature and conducted a meta-analysis to test whether demonstrator characteristics consistently influence social learning, and if social dynamics strategies differ from status strategies in their influence on social learning. We extracted effect sizes from papers that used an observer-demonstrator paradigm to test if the characteristics of the individual providing social information (i.e., the demonstrator) influence social information use by observers. We obtained 139 effect sizes on 33 species from 54 experiments. First, we found an effect of experimental design on the influence of demonstrator characteristics on social learning: between-subject designs had stronger effects compared to within-subject designs. Second, we found that demonstrator characteristics do indeed influence social learning. Characteristics based on social dynamics and characteristics based on status had a significant effect on social learning, especially when copying familiar and kin demonstrators. These results highlight the role that demonstrator characteristics play on social learning, which can have implications for the formation and establishment of behavioural traditions in animals.

Sex differences in allometry for phenotypic traits in mice indicate that females are not scaled males

Sex differences in the lifetime risk and expression of disease are well-known. Preclinical research targeted at improving treatment, increasing health span, and reducing the financial burden of health care, has mostly been conducted on male animals and cells. The extent to which sex differences in phenotypic traits are explained by sex differences in body weight remains unclear. We quantify sex differences in the allometric relationship between trait value and body weight for 363 phenotypic traits in male and female mice, recorded in >2 million measurements from the International Mouse Phenotyping Consortium. We find sex differences in allometric parameters (slope, intercept, residual SD) are common (73% traits). Body weight differences do not explain all sex differences in trait values but scaling by weight may be useful for some traits. Our results show sex differences in phenotypic traits are trait-specific, promoting case-specific approaches to drug dosage scaled by body weight in mice.

Predator-induced transgenerational plasticity in animals: a meta-analysis

There is growing evidence that the environment experienced by one generation can influence phenotypes in the next generation via transgenerational plasticity (TGP). One of the best-studied examples of TGP in animals is predator-induced transgenerational plasticity, whereby exposing parents to predation risk triggers changes in offspring phenotypes. Yet, there is a lack of general consensus synthesizing the predator-prey literature with existing theory pertaining to ecology and evolution of TGP. Here, we apply a meta-analysis to the sizable literature on predator-induced TGP (441 effect sizes from 29 species and 49 studies) to explore five hypotheses about the magnitude, form and direction of predator-induced TGP. Hypothesis #1: the strength of predator-induced TGP should vary with the number of predator cues. Hypothesis #2: the strength of predator-induced TGP should vary with reproductive mode. Hypothesis #3: the strength and direction of predator-induced TGP should vary among offspring phenotypic traits because some traits are more plastic than others. Hypothesis #4: the strength of predator-induced TGP should wane over ontogeny. Hypothesis #5: predator-induced TGP should generate adaptive phenotypes that should be more evident when offspring are themselves exposed to risk. We found strong evidence for predator-induced TGP overall, but no evidence that parental predator exposure causes offspring traits to change in a particular direction. Additionally, we found little evidence in support of any of the specific hypotheses. We infer that the failure to find consistent evidence reflects the heterogeneous nature of the phenomena, and the highly diverse experimental designs used to study it. Together, these findings set an agenda for future work in this area.

A comprehensive database of amphibian heat tolerance

Rising temperatures represent a significant threat to the survival of ectothermic animals. As such, upper thermal limits represent an important trait to assess the vulnerability of ectotherms to changing temperatures. For instance, one may use upper thermal limits to estimate current and future thermal safety margins (i.e., the proximity of upper thermal limits to experienced temperatures), use this trait together with other physiological traits in species distribution models, or investigate the plasticity and evolvability of these limits for buffering the impacts of changing temperatures. While datasets on thermal tolerance limits have been previously compiled, they sometimes report single estimates for a given species, do not present measures of data dispersion, and are biased towards certain parts of the globe. To overcome these limitations, we systematically searched the literature in seven languages to produce the most comprehensive dataset to date on amphibian upper thermal limits, spanning 3,095 estimates across 616 species. This resource will represent a useful tool to evaluate the vulnerability of amphibians, and ectotherms more generally, to changing temperatures.

Polygenic signals of sex differences in selection in humans from the UK Biobank

Sex differences in the fitness effects of genetic variants can influence the rate of adaptation and the maintenance of genetic variation. For example, "sexually antagonistic" (SA) variants, which are beneficial for one sex and harmful for the other, can both constrain adaptation and increase genetic variability for fitness components such as survival, fertility, and disease susceptibility. However, detecting variants with sex-differential fitness effects is difficult, requiring genome sequences and fitness measurements from large numbers of individuals. Here, we develop new theory for studying sex-differential selection across a complete life cycle and test our models with genotypic and reproductive success data from approximately 250,000 UK Biobank individuals. We uncover polygenic signals of sex-differential selection affecting survival, reproductive success, and overall fitness, with signals of sex-differential reproductive selection reflecting a combination of SA polymorphisms and sexually concordant polymorphisms in which the strength of selection differs between the sexes. Moreover, these signals hold up to rigorous controls that minimise the contributions of potential confounders, including sequence mapping errors, population structure, and ascertainment bias. Functional analyses reveal that sex-differentiated sites are enriched in phenotype-altering genomic regions, including coding regions and loci affecting a range of quantitative traits. Population genetic analyses show that sex-differentiated sites exhibit evolutionary histories dominated by genetic drift and/or transient balancing selection, but not long-term balancing selection, which is consistent with theoretical predictions of effectively weak SA balancing selection in historically small populations. Overall, our results are consistent with polygenic sex-differential-including SA-selection in humans. Evidence for sex-differential selection is particularly strong for variants affecting reproductive success, in which the potential contributions of nonrandom sampling to signals of sex differentiation can be excluded.

A meta-analysis on the evolution of the Lombard effect reveals that amplitude adjustments are a widespread vertebrate mechanism

Animal communication is central to many animal societies, and effective signal transmission is crucial for individuals to survive and reproduce successfully. One environmental factor that exerts selection pressure on acoustic signals is ambient noise. To maintain signal efficiency, species can adjust signals through phenotypic plasticity or microevolutionary response to natural selection. One of these signal adjustments is the increase in signal amplitude, called the Lombard effect, which has been frequently found in birds and mammals. However, the evolutionary origin of the Lombard effect is largely unresolved. Using a phylogenetically controlled meta-analysis, we show that the Lombard effect is also present in fish and amphibians, and contradictory results in the literature can be explained by differences in signal-to-noise ratios among studies. Our analysis also demonstrates that subcortical processes are sufficient to elicit the Lombard effect and that amplitude adjustments do not require vocal learning. We conclude that the Lombard effect is a widespread mechanism based on phenotypic plasticity in vertebrates for coping with changes in ambient noise levels.

Sensory recruitment in visual short-term memory: A systematic review and meta-analysis of sensory visual cortex interference using transcranial magnetic stimulation

Sensory visual areas are involved in encoding information in visual short-term memory (VSTM). Yet it remains unclear whether sensory visual cortex is a necessary component of the brain network for maintenance of information in VSTM. Here, we aimed to systematically review studies that have investigated the role of the sensory visual cortex in VSTM using transcranial magnetic stimulation (TMS) and to quantitatively explore these effects using meta-analyses. Fourteen studies were identified and reviewed. Eight studies provided sufficient data for meta-analysis. Two meta-analyses, one regarding the VSTM encoding phase (17 effect sizes) and one regarding the VSTM maintenance phase (15 effect sizes), two meta-regressions (32 effect sizes in each), and one exploratory meta-analysis were conducted. Our results indicate that the sensory visual cortex is similarly involved in both the encoding and maintenance VSTM phase. We suggest that some cases where evidence did not show significant TMS effects was due to low memory or perceptual task demands. Overall, these findings support the idea that sensory visual areas are part of the brain network responsible for successfully maintaining information in VSTM.

A meta-analysis of impacts of immune response and infection on oxidative status in vertebrates

Inferring from patterns observed in biomedical research, ecoimmunological theory predicts that oxidative stress is a ubiquitous physiological cost that contributes to generating variation in immune function between individuals or species. This prediction is, however, often challenged by empirical studies testing the relationship between immune response or infection and oxidative status markers. This points out the importance of combining ecological immunology and oxidative stress ecology to further our understanding of the proximate causes and fitness consequences of individual variation in health, and adaptability to natural and anthropogenic environmental changes. I reviewed evidence and performed phylogenetic meta-analyses of changes in oxidative status markers owing to either injection of an antigen or infection in captive and free-living vertebrates (141 studies, 1262 effect sizes, 97 species). The dataset was dominated by studies on fish, birds and mammals, which provided 95.8% of effect sizes. Both antigen injection and parasite exposure were associated with changes of oxidative status. There were significant effects of taxonomic class and experimental environment (captivity vs. wild). In contrast with my predictions, age category (young vs. adult), study design (correlational vs. experimental) and proxies of pace of life (clutch size, litter size, and body mass; for birds and mammals only) were negligible in this dataset. Several methodological aspects (type of immunostimulant, laboratory assay, tissue analysed) showed significant effects on both strength and direction of effect. My results suggest that alterations of oxidative status are a widespread consequence of immune function across vertebrates. However, this work also identified heterogeneity in strength and direction of effect sizes, which suggests that immune function does not necessarily result in oxidative stress. Finally, this work identifies methodological caveats that might be relevant for the interpretation and comparability of results and for the application in conservation programs.

Sexual dimorphism in phenotypic plasticity and persistence under environmental change: An extension of theory and meta-analysis of current data

Populations must adapt to environmental changes to remain viable. Both evolution and phenotypic plasticity contribute to adaptation, with plasticity possibly being more important for coping with rapid change. Adaptation is complex in species with separate sexes, as the sexes can differ in the strength or direction of natural selection, the genetic basis of trait variation, and phenotypic plasticity. Many species show sex differences in plasticity, yet how these differences influence extinction susceptibility remains unclear. We first extend theoretical models of population persistence in changing environments and show that persistence is affected by sexual dimorphism for phenotypic plasticity, trait genetic architecture, and sex-specific selection. Our models predict that female-biased adaptive plasticity-particularly in traits with modest-to-low cross-sex genetic correlations-typically promotes persistence, though we also identify conditions where sexually monomorphic or male-biased plasticity promotes persistence. We then perform a meta-analysis of sex-specific plasticity under manipulated thermal conditions. Although examples of sexually dimorphic plasticity are widely observed, systematic sex differences are rare. An exception-cold resistance-is systematically female-biased and represents a trait wherein sexually dimorphic plasticity might elevate population viability in changing environments. We discuss our results in light of debates about the roles of evolution and plasticity in extinction susceptibility.

Meta-analytic approaches and effect sizes to account for 'nuisance heterogeneity' in comparative physiology

Meta-analysis is a powerful tool used to generate quantitatively informed answers to pressing global challenges. By distilling data from broad sets of research designs and study systems into standardised effect sizes, meta-analyses provide physiologists with opportunities to estimate overall effect sizes and understand the drivers of effect variability. Despite this ambition, research designs in the field of comparative physiology can appear, at the outset, as being vastly different to each other because of 'nuisance heterogeneity' (e.g. different temperatures or treatment dosages used across studies). Methodological differences across studies have led many to believe that meta-analysis is an exercise in comparing 'apples with oranges'. Here, we dispel this myth by showing how standardised effect sizes can be used in conjunction with multilevel meta-regression models to both account for the factors driving differences across studies and make them more comparable. We assess the prevalence of nuisance heterogeneity in the comparative physiology literature - showing it is common and often not accounted for in analyses. We then formalise effect size measures (e.g. the temperature coefficient, Q10) that provide comparative physiologists with a means to remove nuisance heterogeneity without the need to resort to more complex statistical models that may be harder to interpret. We also describe more general approaches that can be applied to a variety of different contexts to derive new effect sizes and sampling variances, opening up new possibilities for quantitative synthesis. By using effect sizes that account for components of effect heterogeneity, in combination with existing meta-analytic models, comparative physiologists can explore exciting new questions while making results from large-scale data sets more accessible, comparable and widely interpretable.

Meta-analysis reveals an extreme "decline effect" in the impacts of ocean acidification on fish behavior

Ocean acidification-decreasing oceanic pH resulting from the uptake of excess atmospheric CO2-has the potential to affect marine life in the future. Among the possible consequences, a series of studies on coral reef fish suggested that the direct effects of acidification on fish behavior may be extreme and have broad ecological ramifications. Recent studies documenting a lack of effect of experimental ocean acidification on fish behavior, however, call this prediction into question. Indeed, the phenomenon of decreasing effect sizes over time is not uncommon and is typically referred to as the "decline effect." Here, we explore the consistency and robustness of scientific evidence over the past decade regarding direct effects of ocean acidification on fish behavior. Using a systematic review and meta-analysis of 91 studies empirically testing effects of ocean acidification on fish behavior, we provide quantitative evidence that the research to date on this topic is characterized by a decline effect, where large effects in initial studies have all but disappeared in subsequent studies over a decade. The decline effect in this field cannot be explained by 3 likely biological explanations, including increasing proportions of studies examining (1) cold-water species; (2) nonolfactory-associated behaviors; and (3) nonlarval life stages. Furthermore, the vast majority of studies with large effect sizes in this field tend to be characterized by low sample sizes, yet are published in high-impact journals and have a disproportionate influence on the field in terms of citations. We contend that ocean acidification has a negligible direct impact on fish behavior, and we advocate for improved approaches to minimize the potential for a decline effect in future avenues of research.

Low statistical power and overestimated anthropogenic impacts, exacerbated by publication bias, dominate field studies in global change biology

Field studies are essential to reliably quantify ecological responses to global change because they are exposed to realistic climate manipulations. Yet such studies are limited in replicates, resulting in less power and, therefore, potentially unreliable effect estimates. Furthermore, while manipulative field experiments are assumed to be more powerful than non-manipulative observations, it has rarely been scrutinized using extensive data. Here, using 3847 field experiments that were designed to estimate the effect of environmental stressors on ecosystems, we systematically quantified their statistical power and magnitude (Type M) and sign (Type S) errors. Our investigations focused upon the reliability of field experiments to assess the effect of stressors on both ecosystem's response magnitude and variability. When controlling for publication bias, single experiments were underpowered to detect response magnitude (median power: 18%-38% depending on effect sizes). Single experiments also had much lower power to detect response variability (6%-12% depending on effect sizes) than response magnitude. Such underpowered studies could exaggerate estimates of response magnitude by 2-3 times (Type M errors) and variability by 4-10 times. Type S errors were comparatively rare. These observations indicate that low power, coupled with publication bias, inflates the estimates of anthropogenic impacts. Importantly, we found that meta-analyses largely mitigated the issues of low power and exaggerated effect size estimates. Rather surprisingly, manipulative experiments and non-manipulative observations had very similar results in terms of their power, Type M and S errors. Therefore, the previous assumption about the superiority of manipulative experiments in terms of power is overstated. These results call for highly powered field studies to reliably inform theory building and policymaking, via more collaboration and team science, and large-scale ecosystem facilities. Future studies also require transparent reporting and open science practices to approach reproducible and reliable empirical work and evidence synthesis.

Meta-analysis reveals an extreme "decline effect" in the impacts of ocean acidification on fish behavior

Ocean acidification-decreasing oceanic pH resulting from the uptake of excess atmospheric CO2-has the potential to affect marine life in the future. Among the possible consequences, a series of studies on coral reef fish suggested that the direct effects of acidification on fish behavior may be extreme and have broad ecological ramifications. Recent studies documenting a lack of effect of experimental ocean acidification on fish behavior, however, call this prediction into question. Indeed, the phenomenon of decreasing effect sizes over time is not uncommon and is typically referred to as the "decline effect." Here, we explore the consistency and robustness of scientific evidence over the past decade regarding direct effects of ocean acidification on fish behavior. Using a systematic review and meta-analysis of 91 studies empirically testing effects of ocean acidification on fish behavior, we provide quantitative evidence that the research to date on this topic is characterized by a decline effect, where large effects in initial studies have all but disappeared in subsequent studies over a decade. The decline effect in this field cannot be explained by 3 likely biological explanations, including increasing proportions of studies examining (1) cold-water species; (2) nonolfactory-associated behaviors; and (3) nonlarval life stages. Furthermore, the vast majority of studies with large effect sizes in this field tend to be characterized by low sample sizes, yet are published in high-impact journals and have a disproportionate influence on the field in terms of citations. We contend that ocean acidification has a negligible direct impact on fish behavior, and we advocate for improved approaches to minimize the potential for a decline effect in future avenues of research.

Detecting patterns of correlational selection with sampling error: A simulation study

The adoption of a multivariate perspective of selection implies the existence of multivariate adaptive peaks and pervasive correlational selection that promotes co-adaptation between traits. However, to test for the ubiquity of correlational selection in nature, we must first have a sense of how well can we estimate multivariate nonlinear selection (i.e., the γ-matrix) in the face of sampling error. To explore the sampling properties of estimated γ-matrices, we simulated inidividual traits and fitness under a wide range of sample sizes, using different strengths of correlational selection and of stabilizing selection, combined with different number of traits under selection, different amounts of residual variance in fitness, and distinct patterns of selection. We then ran nonlinear regressions with these simulated datasets to simulate γ-matrices after adding random error to individual fitness. To test how well could we detect the imposed pattern of correlational selection at different sample sizes, we measured the similarity between simulated and imposed γ-matrices. We show that detection of the pattern of correlational selection is highly dependent on the total strength of selection on traits and on the amount of residual variance in fitness. Minimum sample size needs to be at least 500 to precisely estimate the pattern of correlational selection. Furthermore, a pattern of selection in which different sets of traits contribute to different functions is the easiest to diagnose, even when using a large number of traits (10 traits), but with sample sizes in the order of 1000 individuals. Consequently, we recommend working with sets of traits from distinct functional complexes and fitness proxies less prone to effects of environmental and demographic stochasticity to test for correlational selection with lower sample sizes.

Viviparous mothers impose stronger glucocorticoid-mediated maternal stress effects on their offspring than oviparous mothers

Maternal stress during gestation has the potential to affect offspring development via changes in maternal physiology, such as increases in circulating levels of glucocorticoid hormones that are typical after exposure to a stressor. While the effects of elevated maternal glucocorticoids on offspring phenotype (i.e., "glucocorticoid-mediated maternal effects") have been relatively well established in laboratory studies, it remains poorly understood how strong and consistent such effects are in natural populations. Using a meta-analysis of studies of wild mammals, birds, and reptiles, we investigate the evidence for effects of elevated maternal glucocorticoids on offspring phenotype and investigate key moderators that might influence the strength and direction of these effects. In particular, we investigate the potential importance of reproductive mode (viviparity vs. oviparity). We show that glucocorticoid-mediated maternal effects are stronger, and likely more deleterious, in mammals and viviparous squamate reptiles compared with birds, turtles, and oviparous squamates. No other moderators (timing and type of manipulation, age at offspring measurement, or type of trait measured) were significant predictors of the strength or direction of the phenotypic effects on offspring. These results provide evidence that the evolution of a prolonged physiological association between embryo and mother sets the stage for maladaptive, or adaptive, prenatal stress effects in vertebrates driven by glucocorticoid elevation.

Herbivore-Mediated Selection on Floral Display Covaries Nonlinearly With Plant-Antagonistic Interaction Intensity Among Primrose Populations

Quantifying the relations between plant-antagonistic interactions and natural selection among populations is important for predicting how spatial variation in ecological interactions drive adaptive differentiation. Here, we investigate the relations between the opportunity for selection, herbivore-mediated selection, and the intensity of plant-herbivore interaction among 11 populations of the insect-pollinated plant Primula florindae over 2 years. We experimentally quantified herbivore-mediated directional selection on three floral traits (two display and one phenological) within populations and found evidence for herbivore-mediated selection for a later flowering start date and a greater number of flowers per plant. The opportunity for selection and strength of herbivore-mediated selection on number of flowers varied nonlinearly with the intensity of herbivory among populations. These parameters increased and then decreased with increasing intensity of plant-herbivore interactions, defined as an increase in the ratio of herbivore-damaged flowers per individual. Our results provide novel insights into how plant-antagonistic interactions can shape spatial variation in selection on floral traits and contribute toward understanding the mechanistic basis of geographic variation in angiosperm flowers.

Evolvability: A Quantitative-Genetics Perspective

The concept of evolvability emerged in the early 1990s and soon became fashionable as a label for different streams of research in evolutionary biology. In evolutionary quantitative genetics, evolvability is defined as the ability of a population to respond to directional selection. This differs from other fields by treating evolvability as a property of populations rather than organisms or lineages and in being focused on quantification and short-term prediction rather than on macroevolution. While the term evolvability is new to quantitative genetics, many of the associated ideas and research questions have been with the field from its inception as biometry. Recent research on evolvability is more than a relabeling of old questions, however. New operational measures of evolvability have opened possibilities for understanding adaptation to rapid environmental change, assessing genetic constraints, and linking micro- and macroevolution.

Preferred reporting items for systematic reviews and meta-analyses in ecology and evolutionary biology: a PRISMA extension

Since the early 1990s, ecologists and evolutionary biologists have aggregated primary research using meta-analytic methods to understand ecological and evolutionary phenomena. Meta-analyses can resolve long-standing disputes, dispel spurious claims, and generate new research questions. At their worst, however, meta-analysis publications are wolves in sheep's clothing: subjective with biased conclusions, hidden under coats of objective authority. Conclusions can be rendered unreliable by inappropriate statistical methods, problems with the methods used to select primary research, or problems within the primary research itself. Because of these risks, meta-analyses are increasingly conducted as part of systematic reviews, which use structured, transparent, and reproducible methods to collate and summarise evidence. For readers to determine whether the conclusions from a systematic review or meta-analysis should be trusted - and to be able to build upon the review - authors need to report what they did, why they did it, and what they found. Complete, transparent, and reproducible reporting is measured by 'reporting quality'. To assess perceptions and standards of reporting quality of systematic reviews and meta-analyses published in ecology and evolutionary biology, we surveyed 208 researchers with relevant experience (as authors, reviewers, or editors), and conducted detailed evaluations of 102 systematic review and meta-analysis papers published between 2010 and 2019. Reporting quality was far below optimal and approximately normally distributed. Measured reporting quality was lower than what the community perceived, particularly for the systematic review methods required to measure trustworthiness. The minority of assessed papers that referenced a guideline (~16%) showed substantially higher reporting quality than average, and surveyed researchers showed interest in using a reporting guideline to improve reporting quality. The leading guideline for improving reporting quality of systematic reviews is the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Here we unveil an extension of PRISMA to serve the meta-analysis community in ecology and evolutionary biology: PRISMA-EcoEvo (version 1.0). PRISMA-EcoEvo is a checklist of 27 main items that, when applicable, should be reported in systematic review and meta-analysis publications summarising primary research in ecology and evolutionary biology. In this explanation and elaboration document, we provide guidance for authors, reviewers, and editors, with explanations for each item on the checklist, including supplementary examples from published papers. Authors can consult this PRISMA-EcoEvo guideline both in the planning and writing stages of a systematic review and meta-analysis, to increase reporting quality of submitted manuscripts. Reviewers and editors can use the checklist to assess reporting quality in the manuscripts they review. Overall, PRISMA-EcoEvo is a resource for the ecology and evolutionary biology community to facilitate transparent and comprehensively reported systematic reviews and meta-analyses.

The impact of environmental and social factors on learning abilities: a meta-analysis

Since the 1950s, researchers have examined how differences in the social and asocial environment affect learning in rats, mice, and, more recently, a variety of other species. Despite this large body of research, little has been done to synthesize these findings and to examine if social and asocial environmental factors have consistent effects on cognitive abilities, and if so, what aspects of these factors have greater or lesser impact. Here, we conducted a systematic review and meta-analysis examining how different external environmental features, including the social environment, impact learning (both speed of acquisition and performance). Using 531 mean-differences from 176 published articles across 27 species (with studies on rats and mice being most prominent) we conducted phylogenetically corrected mixed-effects models that reveal: (i) an average absolute effect size |d| = 0.55 and directional effect size d = 0.34; (ii) interventions manipulating the asocial environment result in larger effects than social interventions alone; and (iii) the length of the intervention is a significant predictor of effect size, with longer interventions resulting in larger effects. Additionally, much of the variation in effect size remained unexplained, possibly suggesting that species differ widely in how they are affected by environmental interventions due to varying ecological and evolutionary histories. Overall our results suggest that social and asocial environmental factors do significantly affect learning, but these effects are highly variable and perhaps not always as predicted. Most notably, the type (social or asocial) and length of interventions are important in determining the strength of the effect.

Predicting the Evolution of Sexual Dimorphism in Gene Expression

Sexual dimorphism in gene expression is likely to be the underlying source of dimorphism in a variety of traits. Many analyses implicitly make the assumption that dimorphism only evolves when selection favors different phenotypes in the two sexes, although theory makes clear that it can also evolve as an indirect response to other kinds of selection. Furthermore, previous analyses consider the evolution of a single transcript or trait at a time, ignoring the genetic covariance with other transcripts and traits. We first show which aspects of the genetic-variance-covariance matrix, G, affect dimorphism when these assumptions about selection are relaxed. We then reanalyze gene expression data from Drosophila melanogaster with these predictions in mind. Dimorphism of gene expression for individual transcripts shows the signature of both direct selection for dimorphism and indirect responses to selection. To account for the effect of measurement error on evolutionary predictions, we estimated a G matrix for eight linear combinations of expression traits. Sex-specific genetic variances in female- and male-biased transcription, as well as one relatively unbiased combination, were quite unequal, ensuring that most forms of selection on these traits will have large effects on dimorphism. Predictions of response to selection based on the whole G matrix showed that sexually concordant and antagonistic selection are equally capable of changing sexual dimorphism. In addition, the indirect responses of dimorphism due to cross-trait covariances were quite substantial. The assumption that sexual dimorphism in transcription is an adaptation could be incorrect in many specific cases.

Random Effects in Magnetobiology and a Way to Summarize Them

In magnetobiology, it is difficult to reproduce the nonspecific (not associated with specialized receptors) biological effects of weak magnetic fields. This means that some important characteristic of the data may be missed in standard statistical processing, where the set of measurements to be averaged belongs to the same population so that the contribution of fluctuations decreases according to the Central Limit Theorem. It has been shown that a series of measurements of a nonspecific magnetic effect contains not only the usual scatter of data around the mean but also a significant random component in the mean itself. This random component indicates that measurements belong to different statistical populations, which requires special processing. This component, otherwise called heterogeneity, is an additional characteristic that is typically overlooked, and which reduces reproducibility. The current method for studying and summarizing highly heterogeneous data is the random-effect meta-analysis of absolute values, i.e., of magnitudes, rather than the values themselves. However, this estimator-the average of absolute values-has a significant positive bias when it comes to the small effects that are characteristic of magnetobiology. To solve this problem, an improved estimator based on the folded normal distribution that gives several times less bias is proposed. We used this improved estimator to analyze the nonspecific effect of the hypomagnetic field in the Stroop test in 40 subjects and found a statistically significant meta-effect with a standardized average of magnitudes of about 0.1. It has been shown that the proposed approach can also be applied to a single study. © 2021 Bioelectromagnetics Society.

The genetic architecture of sexual dimorphism in the moss Ceratodon purpureus

A central problem in evolutionary biology is to identify the forces that maintain genetic variation for fitness in natural populations. Sexual antagonism, in which selection favours different variants in males and females, can slow the transit of a polymorphism through a population or can actively maintain fitness variation. The amount of sexually antagonistic variation to be expected depends in part on the genetic architecture of sexual dimorphism, about which we know relatively little. Here, we used a multivariate quantitative genetic approach to examine the genetic architecture of sexual dimorphism in a scent-based fertilization syndrome of the moss Ceratodon purpureus. We found sexual dimorphism in numerous traits, consistent with a history of sexually antagonistic selection. The cross-sex genetic correlations (rmf) were generally heterogeneous with many values indistinguishable from zero, which typically suggests that genetic constraints do not limit the response to sexually antagonistic selection. However, we detected no differentiation between the female- and male-specific trait (co)variance matrices (Gf and Gm, respectively), meaning the evolution of sexual dimorphism may be constrained. The cross-sex cross-trait covariance matrix B contained both symmetric and asymmetric elements, indicating that the response to sexually antagonistic or sexually concordant selection, and the constraint to sexual dimorphism, are highly dependent on the traits experiencing selection. The patterns of genetic variances and covariances among these fitness components is consistent with partly sex-specific genetic architectures having evolved in order to partially resolve multivariate genetic constraints (i.e. sexual conflict), enabling the sexes to evolve towards their sex-specific multivariate trait optima.

Species sensitivities to a global pollutant: A meta-analysis on acoustic signals in response to anthropogenic noise

Anthropogenically driven environmental changes affect our planet at an unprecedented rate. Among these changes are those in the acoustic environment caused by anthropogenic noise, which can affect both animals and humans. In many species, acoustic communication plays a crucial role to maintain social relationships by exchanging information via acoustic signals. However, how species relying on acoustic communication differ in their adjustments to anthropogenic noise is little understood. Yet, this is crucial because protecting species effectively depends on our capability to predict how species differ in their response to human-induced environmental changes. Using a phylogenetically controlled meta-analysis, we quantified differences in adjustments of acoustic signals to anthropogenic noise among species. The effect sizes included in the analysis were obtained from noise exposure experiments, as only carefully controlled experiments allow to establish cause-and-effect relationships. We found that animals changed acoustic signals when exposed to noise, but the magnitude and the direction of adjustments differed among species. Given the importance of communication in the animal kingdom, these adjustments can affect social relationships in many species. The diversity of responses among species highlights the necessity to assess the effect of environmental stressors not only for a few species, because an effect may be positive in one species but negative in another depending on the species' biology. Thus, an effective conservation approach to protect different species is to preserve natural soundscapes of ecosystems to which species have adapted to by reducing or mitigating the emission of anthropogenic noise into the environment.

Cranial morphology of captive mammals: a meta-analysis

BACKGROUND

Captive facilities such as zoos are uniquely instrumental in conservation efforts. To fulfill their potential as bastions for conservation, zoos must preserve captive populations as appropriate proxies for their wild conspecifics; doing so will help to promote successful reintroduction efforts. Morphological changes within captive populations may be detrimental to the fitness of individual animals because these changes can influence functionality; thus, it is imperative to understand the breadth and depth of morphological changes occurring in captive populations. Here, we conduct a meta-analysis of scientific literature reporting comparisons of cranial measures between captive and wild populations of mammals. We investigate the pervasiveness of cranial differences and whether cranial morphological changes are associated with ecological covariates specific to individual species, such as trophic level, dietary breadth, and home range size.

RESULTS

Cranial measures of skull length, skull width, and the ratio of skull length-to-width differed significantly between many captive and wild populations of mammals reported in the literature. Roughly half of captive populations differed from wild populations in at least one cranial measure, although the degree of changes varied. Carnivorous species with a limited dietary breadth displayed the most consistent changes associated with skull widening. Species with a more generalized diet displayed less morphological changes in captivity.

CONCLUSIONS

Wild and captive populations of mammals differed in cranial morphology, but the nature and magnitude of their cranial differences varied considerably across taxa. Although changes in cranial morphology occur in captivity, specific changes cannot be generalized for all captive mammal populations. The nature of cranial changes in captivity may be specific to particular taxonomic groups; thus, it may be possible to establish expectations across smaller taxonomic units, or even disparate groups that utilize their cranial morphology in a similar way. Given that morphological changes occurring in captive environments like zoos have the potential to limit reintroduction success, our results call for a critical evaluation of current captive husbandry practices to prevent unnecessary morphological changes.

Using ecological context to interpret spatiotemporal variation in natural selection

Spatiotemporal variation in natural selection is expected, but difficult to estimate. Pollinator-mediated selection on floral traits provides a good system for understanding and linking variation in selection to differences in ecological context. We studied pollinator-mediated selection in five populations of Dalechampia scandens (Euphorbiaceae) in Costa Rica and Mexico. Using a nonlinear path-analytical approach, we assessed several functional components of selection, and linked variation in pollinator-mediated selection across time and space to variation in pollinator assemblages. After correcting for estimation error, we detected moderate variation in net selection on two out of four blossom traits. Both the opportunity for selection and the mean strength of selection decreased with increasing reliability of cross-pollination. Selection for pollinator attraction was consistently positive and stronger on advertisement than reward traits. Selection on traits affecting pollen transfer from the pollinator to the stigmas was strong only when cross-pollination was unreliable and there was a mismatch between pollinator and blossom size. These results illustrate how consideration of trait function and ecological context can facilitate both the detection and the causal understanding of spatiotemporal variation in natural selection.

Consequences of multiple imputation of missing standard deviations and sample sizes in meta-analysis

Meta-analyses often encounter studies with incompletely reported variance measures (e.g., standard deviation values) or sample sizes, both needed to conduct weighted meta-analyses. Here, we first present a systematic literature survey on the frequency and treatment of missing data in published ecological meta-analyses showing that the majority of meta-analyses encountered incompletely reported studies. We then simulated meta-analysis data sets to investigate the performance of 14 options to treat or impute missing SDs and/or SSs. Performance was thereby assessed using results from fully informed weighted analyses on (hypothetically) complete data sets. We show that the omission of incompletely reported studies is not a viable solution. Unweighted and sample size-based variance approximation can yield unbiased grand means if effect sizes are independent of their corresponding SDs and SSs. The performance of different imputation methods depends on the structure of the meta-analysis data set, especially in the case of correlated effect sizes and standard deviations or sample sizes. In a best-case scenario, which assumes that SDs and/or SSs are both missing at random and are unrelated to effect sizes, our simulations show that the imputation of up to 90% of missing data still yields grand means and confidence intervals that are similar to those obtained with fully informed weighted analyses. We conclude that multiple imputation of missing variance measures and sample sizes could help overcome the problem of incompletely reported primary studies, not only in the field of ecological meta-analyses. Still, caution must be exercised in consideration of potential correlations and pattern of missingness.

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics

Sexually antagonistic (SA) genetic variation-in which alleles favored in one sex are disfavored in the other-is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research-including F ST and F IS statistics, genome-wide association studies, pedigree analyses, reciprocal transplant studies, and evolve-and-resequence experiments-to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.

Predicting Multivariate Responses of Sexual Dimorphism to Direct and Indirect Selection

AbstractSexual dimorphism is often assumed to result from balancing the strength of antagonistic selection in favor of dimorphism against the degree of constraint imposed by the shared genome of the sexes, reflected in the B matrix of genetic intersexual covariances. To investigate the totality of forces shaping dimorphism, we reparameterized the Lande equation to predict changes in trait averages and trait differences between the sexes. As genetic constraints on the evolution of dimorphism in response to antagonistic selection become larger, dimorphism will tend to respond more rapidly to concordant selection (which favors the same direction of change in male and female traits) than to antagonistic selection. When we apply this theory to four empirical estimates of B in Drosophila melanogaster, the indirect responses of dimorphism to concordant selection are of comparable or larger magnitude than the direct responses of dimorphism to antagonistic selection in two suites of traits with typical levels of intersex correlation. Antagonistic selection is more important in two suites of traits where the intersex correlations are unusually low. This suggests that the evolution of sexual dimorphism may sometimes be dominated by concordant selection rather than antagonistic selection.

An effect size statistical framework for investigating sexual dimorphism in non-avian dinosaurs and other extinct taxa

Despite reports of sexual dimorphism in extinct taxa, such claims in non-avian dinosaurs have been rare over the last decade and have often been criticized. Since dimorphism is widespread in sexually reproducing organisms today, under-reporting in the literature might suggest either methodological shortcomings or that this diverse group exhibited highly unusual reproductive biology. Univariate significance testing, especially for bimodality, is ineffective and prone to false negatives. Species recognition and mutual sexual selection hypotheses, therefore, may not be required to explain supposed absence of sexual dimorphism across the grade (a type II error). Instead, multiple lines of evidence support sexual selection and variation of structures consistent with secondary sexual characteristics, strongly suggesting sexual dimorphism in non-avian dinosaurs. We propose a framework for studying sexual dimorphism in fossils, focusing on likely secondary sexual traits and testing against all alternate hypotheses for variation in them using multiple lines of evidence. We use effect size statistics appropriate for low sample sizes, rather than significance testing, to analyse potential divergence of growth curves in traits and constrain estimates for dimorphism magnitude. In many cases, estimates of sexual variation can be reasonably accurate, and further developments in methods to improve sex assignments and account for intrasexual variation (e.g. mixture modelling) will improve accuracy. It is better to compare estimates for the magnitude of and support for dimorphism between datasets than to dichotomously reject or fail to reject monomorphism in a single species, enabling the study of sexual selection across phylogenies and time. We defend our approach with simulated and empirical data, including dinosaur data, showing that even simple approaches can yield fairly accurate estimates of sexual variation in many cases, allowing for comparison of species with high and low support for sexual variation.