Fluctuating optimum and temporally variable selection on breeding date in birds and mammals.

Temporal variation in natural selection is predicted to strongly impact the evolution and demography of natural populations, with consequences for the rate of adaptation, evolution of plasticity, and extinction risk. Most of the theory underlying these predictions assumes a moving optimum phenotype, with predictions expressed in terms of the temporal variance and autocorrelation of this optimum. However, empirical studies seldom estimate patterns of fluctuations of an optimum phenotype, precluding further progress in connecting theory with observations. To bridge this gap, we assess the evidence for temporal variation in selection on breeding date by modeling a fitness function with a fluctuating optimum, across 39 populations of 21 wild animals, one of the largest compilations of long-term datasets with individual measurements of trait and fitness components. We find compelling evidence for fluctuations in the fitness function, causing temporal variation in the magnitude, but not the direction of selection. However, fluctuations of the optimum phenotype need not directly translate into variation in selection gradients, because their impact can be buffered by partial tracking of the optimum by the mean phenotype. Analyzing individuals that reproduce in consecutive years, we find that plastic changes track movements of the optimum phenotype across years, especially in bird species, reducing temporal variation in directional selection. This suggests that phenological plasticity has evolved to cope with fluctuations in the optimum, despite their currently modest contribution to variation in selection.

A synthesis of senescence predictions for indeterminate growth, and support from multiple tests in wild lake trout.

Senescence-the deterioration of functionality with age-varies widely across taxa in pattern and rate. Insights into why and how this variation occurs are hindered by the predominance of laboratory-focused research on short-lived model species with determinate growth. We synthesize evolutionary theories of senescence, highlight key information gaps and clarify predictions for species with low mortality and variable degrees of indeterminate growth. Lake trout are an ideal species to evaluate predictions in the wild. We monitored individual males from two populations (1976-2017) longitudinally for changes in adult mortality (actuarial senescence) and body condition (proxy for energy balance). A cross-sectional approach (2017) compared young (ages 4-10 years) and old (18-37 years) adults for (i) phenotypic performance in body condition, and semen quality-which is related to fertility under sperm competition (reproductive senescence)-and (ii) relative telomere length (potential proxy for cellular senescence). Adult growth in these particular populations is constrained by a simplified foodweb, and our data support predictions of negligible senescence when maximum size is only slightly larger than maturation size. Negative senescence (aka reverse senescence) may occur in other lake trout populations where diet shifts allow maximum sizes to greatly exceed maturation size.

The role of selection and evolution in changing parturition date in a red deer population.

Changing environmental conditions cause changes in the distributions of phenotypic traits in natural populations. However, determining the mechanisms responsible for these changes-and, in particular, the relative contributions of phenotypic plasticity versus evolutionary responses-is difficult. To our knowledge, no study has yet reported evidence that evolutionary change underlies the most widely reported phenotypic response to climate change: the advancement of breeding times. In a wild population of red deer, average parturition date has advanced by nearly 2 weeks in 4 decades. Here, we quantify the contribution of plastic, demographic, and genetic components to this change. In particular, we quantify the role of direct phenotypic plasticity in response to increasing temperatures and the role of changes in the population structure. Importantly, we show that adaptive evolution likely played a role in the shift towards earlier parturition dates. The observed rate of evolution was consistent with a response to selection and was less likely to be due to genetic drift. Our study provides a rare example of observed rates of genetic change being consistent with theoretical predictions, although the consistency would not have been detected with a solely phenotypic analysis. It also provides, to our knowledge, the first evidence of both evolution and phenotypic plasticity contributing to advances in phenology in a changing climate.

Discovery of species-wide tool use in the Hawaiian crow.

Only a handful of bird species are known to use foraging tools in the wild. Amongst them, the New Caledonian crow (Corvus moneduloides) stands out with its sophisticated tool-making skills. Despite considerable speculation, the evolutionary origins of this species' remarkable tool behaviour remain largely unknown, not least because no naturally tool-using congeners have yet been identified that would enable informative comparisons. Here we show that another tropical corvid, the 'Alala (C. hawaiiensis; Hawaiian crow), is a highly dexterous tool user. Although the 'Alala became extinct in the wild in the early 2000s, and currently survives only in captivity, at least two lines of evidence suggest that tool use is part of the species' natural behavioural repertoire: juveniles develop functional tool use without training, or social input from adults; and proficient tool use is a species-wide capacity. 'Alala and New Caledonian crows evolved in similar environments on remote tropical islands, yet are only distantly related, suggesting that their technical abilities arose convergently. This supports the idea that avian foraging tool use is facilitated by ecological conditions typical of islands, such as reduced competition for embedded prey and low predation risk. Our discovery creates exciting opportunities for comparative research on multiple tool-using and non-tool-using corvid species. Such work will in turn pave the way for replicated cross-taxonomic comparisons with the primate lineage, enabling valuable insights into the evolutionary origins of tool-using behaviour.

No evidence that warmer temperatures are associated with selection for smaller body sizes.

Reductions in animal body size over recent decades are often interpreted as an adaptive evolutionary response to climate warming. However, for reductions in size to reflect adaptive evolution, directional selection on body size within populations must have become negative, or where already negative, to have become more so, as temperatures increased. To test this hypothesis, we performed traditional and phylogenetic meta-analyses of the association between annual estimates of directional selection on body size from wild populations and annual mean temperatures from 39 longitudinal studies. We found no evidence that warmer environments were associated with selection for smaller size. Instead, selection consistently favoured larger individuals, and was invariant to temperature. These patterns were similar in ectotherms and endotherms. An analysis using year rather than temperature revealed similar patterns, suggesting no evidence that selection has changed over time, and also indicating that the lack of association with annual temperature was not an artefact of choosing an erroneous time window for aggregating the temperature data. Although phenotypic trends in size will be driven by a combination of genetic and environmental factors, our results suggest little evidence for a necessary ingredient-negative directional selection-for declines in body size to be considered an adaptive evolutionary response to changing selection pressures.

Analogues of the fundamental and secondary theorems of selection, assuming a log-normal distribution of expected fitness.

It is increasingly common for studies of evolution in natural populations to infer the quantitative genetic basis of fitness (e.g., the additive genetic variance for relative fitness), and of relationships between traits and fitness (e.g., the additive genetic covariance of traits with relative fitness). There is a certain amount of tension between the theory that justifies estimating these quantities, and methodological considerations relevant to their empirical estimation. In particular, the additive genetic variances and covariances involving relative fitness are justified by the fundamental and secondary theorems of selection, which pertain to relative fitness on the scale that it is expressed. However, naturally-occurring fitness distributions lend themselves to analysis with generalized linear mixed models (GLMMs), which conduct analysis on a different scale, typically on the scale of the logarithm of expected values, from which fitness is expressed. This note presents relations between evolutionary change in traits, and the rate of adaptation in fitness, and log quantitative genetic parameters of fitness, potentially reducing the discord between theoretical and methodological considerations to the operationalization of the secondary and fundamental theorems of selection.

Estimation of Genetic Variance in Fitness, and Inference of Adaptation, When Fitness Follows a Log-Normal Distribution.

Additive genetic variance in relative fitness (σA2(w)) is arguably the most important evolutionary parameter in a population because, by Fisher's fundamental theorem of natural selection (FTNS; Fisher RA. 1930. The genetical theory of natural selection. 1st ed. Oxford: Clarendon Press), it represents the rate of adaptive evolution. However, to date, there are few estimates of σA2(w) in natural populations. Moreover, most of the available estimates rely on Gaussian assumptions inappropriate for fitness data, with unclear consequences. "Generalized linear animal models" (GLAMs) tend to be more appropriate for fitness data, but they estimate parameters on a transformed ("latent") scale that is not directly interpretable for inferences on the data scale. Here we exploit the latest theoretical developments to clarify how best to estimate quantitative genetic parameters for fitness. Specifically, we use computer simulations to confirm a recently developed analog of the FTNS in the case when expected fitness follows a log-normal distribution. In this situation, the additive genetic variance in absolute fitness on the latent log-scale (σA2(l)) equals (σA2(w)) on the data scale, which is the rate of adaptation within a generation. However, due to inheritance distortion, the change in mean relative fitness between generations exceeds σA2(l) and equals (exp⁡(σA2(l))-1). We illustrate why the heritability of fitness is generally low and is not a good measure of the rate of adaptation. Finally, we explore how well the relevant parameters can be estimated by animal models, comparing Gaussian models with Poisson GLAMs. Our results illustrate 1) the correspondence between quantitative genetics and population dynamics encapsulated in the FTNS and its log-normal-analog and 2) the appropriate interpretation of GLAM parameter estimates.

Pedigree-Based Estimation of Reproductive Value.

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

Individual variation in reproductive behaviour is linked to temporal heterogeneity in predation risk.

Variation in predation risk is a major driver of ecological and evolutionary change, and, in turn, of geographical variation in behaviour. While predation risk is rarely constant in natural populations, the extent to which variation in predation risk shapes individual behaviour in wild populations remains unclear. Here, we investigated individual differences in reproductive behaviour in 16 Trinidadian guppy populations and related it to the observed variation in predator biomass each population experienced. Our results show that high heterogeneity in predator biomass is linked to individual behavioural diversification. Increased within-population heterogeneity in predator biomass is also associated with behavioural polymorphism. Some individuals adjust the frequency of consensual mating behaviour in response to differences in sex ratio context, while others display constantly at elevated frequencies. This pattern is analogous to a 'live fast, die young' pace-of-life syndrome. Notably, both high and low mean differences in predator biomass led to a homogenization of individual frequency of consensual mating displays. Overall, our results demonstrate that individual behavioural variation is associated with heterogeneity in predator biomass, but not necessarily with changes in mean values of predator biomass. We suggest that heterogeneity in predator biomass is an informative predictor of adaptive responses to changes in biotic conditions.

Into the wild-WAMBAM goes to Canada.

The sixth Wild Animal Models Bi-Annual Meeting was held in July 2017 in Québec, with 42 participants. This report documents the evolution of questions asked and approaches used in evolutionary quantitative genetic studies of wild populations in recent decades, and how these questions and approaches were represented at the recent meeting. We explore how ideas from previous meetings in this series have developed to their present states, and consider how the format of the meetings may be particularly useful at fostering the rapid development and proliferation of ideas and approaches.

Natural selection for body shape in resource polymorphic Icelandic Arctic charr.

Resource polymorphisms exhibit remarkable intraspecific diversity and in many cases are expected to be maintained by diversifying selection. Phenotypic trade-offs can constrain morphologically intermediate individuals from effectively exploiting both alternate resources, resulting in ecological barriers to gene flow. Determining if and how phenotypic trade-offs cause fitness variation in the wild is challenging because of phenotypic and environmental correlations associated with alternative resource strategies. We investigated multiple pathways through which morphology could affect organismal performance, as measured by growth rate, and whether these effects generate diversifying selection in polymorphic Icelandic Arctic charr (Salvelinus alpinus) populations. We considered direct effects of morphology on growth and indirect effects via trophic resource use, estimated by stable isotopic signatures, and via parasitism associated with trophic resources. We sampled over 3 years in (lakes) Thingvallavatn and Vatnshlíðarvatn using the extended selection gradient path analytical approach and estimating size-dependent mortality. We found evidence for diversifying selection only in Thingvallavatn: more streamlined and terminally mouthed planktivore charr experienced greater growth, with the opposite pattern in small benthic charr. However, this effect was mediated by parasitism and nontrophic pathways, rather than trophic performance as often expected. Detection of between-morph differences in the presence (Vatnshlíðarvatn) and direction (Thingvallavatn) of size-dependent mortality, together with nontrophic effects of shape, suggests that a morphological trophic performance explanation for polymorphism is insufficient. This rare insight into selection during early diversification suggests that a complex of interacting local factors must be considered to understand how phenotype influences fitness, despite morphological variation reflecting intuitive trade-off explanations.

Reversible, orally available ADP receptor (P2Y12) antagonists Part I: Hit to lead process.

A hit to lead process to identify reversible, orally available ADP receptor (P2Y12) antagonists lead compounds is described. High throughput screening afforded 1. Optimization of 1, using parallel synthesis methods, a methyl scan to identify promising regions for optimization, and exploratory SAR on these regions, provided 22 and 23. Compound 23 is an orally available, competitive reversible antagonist (KB = 94 nM for inhibition of ADP-induced platelet aggregation). It exhibits high metabolic stability in human, rat and dog liver microsomes and is orally absorbed. Although plasma level after oral dosing of 22 and 23 to rats is low, reasonable levels were achieved to merit extensive lead optimization of this structural class.

What Are the Environmental Determinants of Phenotypic Selection? A Meta-analysis of Experimental Studies.

Although many selection estimates have been published, the environmental factors that cause selection to vary in space and time have rarely been identified. One way to identify these factors is by experimentally manipulating the environment and measuring selection in each treatment. We compiled and analyzed selection estimates from experimental studies. First, we tested whether the effect of manipulating the environment on selection gradients depends on taxon, trait type, or fitness component. We found that the effect of manipulating the environment was larger when selection was measured on life-history traits or via survival. Second, we tested two predictions about the environmental factors that cause variation in selection. We found support for the prediction that variation in selection is more likely to be caused by environmental factors that have a large effect on mean fitness but not for the prediction that variation is more likely to be caused by biotic factors. Third, we compared selection gradients from experimental and observational studies. We found that selection varied more among treatments in experimental studies than among spatial and temporal replicates in observational studies, suggesting that experimental studies can detect relationships between environmental factors and selection that would not be apparent in observational studies.

A 17-Year-Old Girl With Acute Onset of Hemiparesis.

The presentation of acute-onset hemiparesis in a teenager can be challenging and offers a wide differential diagnosis. We discuss the approach to the patient (which should begin with thorough history taking and physical examination) and advanced imaging as directed by the patient's signs and symptoms. We report the case of an otherwise well 17-year-old girl who presented to the pediatric emergency department with a 2-day history of left-sided weakness and difficulty ambulating. Her eventual diagnosis of Balo concentric sclerosis, a rare form of multiple sclerosis, is discussed.

Robust estimates of environmental effects on population vital rates: an integrated capture-recapture model of seasonal brook trout growth, survival and movement in a stream network.

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses. We developed an integrated capture-recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival. We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature. Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall. These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful.

Consumer detection and acceptability of reduced-sodium bread.

OBJECTIVE: Bread is the largest contributor of Na to the American diet and excess Na consumption contributes to premature death and disability. We sought to determine the Na level at which consumers could detect a difference between reduced-Na bread and bread with typical Na content, and to determine if consumer sensory acceptability and purchase intent differed between reduced-Na bread and bread with typical Na content. DESIGN: Difference testing measured ability to detect differences in control bread and reduced-Na bread using two-alternative forced choice testing. Acceptability was measured using a nine-point hedonic scale and purchase intent was measured using a five-point purchase intent scale. SETTING: Difference and acceptability testing were conducted in Portland, OR, USA in January 2013. SUBJECTS: Eighty-two consumers participated in difference testing and 109 consumers participated in acceptability testing. RESULTS: Consumers did not detect a difference in saltiness between the control bread and the 10 % reduced-Na bread, but did detect a difference between the control bread and bread reduced in Na content by 20 % and 30 %. Na reductions had no effect on consumer acceptability of sensory characteristics, including overall liking, appearance, aroma, flavour, sweetness, salt level and texture, or purchase intent. CONCLUSIONS: Reducing Na levels by up to 30 % in the sandwich bread tested did not affect consumer liking or purchase intent of the product. These results support national recommendations for small, incremental Na reductions in the food supply over time and assure bread manufacturers that sensory characteristics and consumer purchase intent of their products will be preserved after Na reductions occur.

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.

Fine scale diversity in the lava: genetic and phenotypic diversity in small populations of Arctic charr Salvelinus alpinus.

BACKGROUND: A major goal in evolutionary biology is to understand the processes underlying phenotypic variation in nature. Commonly, studies have focused on large interconnected populations or populations found along strong environmental gradients. However, studies on small fragmented populations can give strong insight into evolutionary processes in relation to discrete ecological factors. Evolution in small populations is believed to be dominated by stochastic processes, but recent work shows that small populations can also display adaptive phenotypic variation, through for example plasticity and rapid adaptive evolution. Such evolution takes place even though there are strong signs of historical bottlenecks and genetic drift. Here we studied 24 small populations of the freshwater fish Arctic charr (Salvelinus alpinus) found in groundwater filled lava caves. Those populations were found within a few km2-area with no apparent water connections between them. We studied the relative contribution of neutral versus non-neutral evolutionary processes in shaping phenotypic divergence, by contrasting patterns of phenotypic and neutral genetic divergence across populations in relation to environmental measurements. This allowed us to model the proportion of phenotypic variance explained by the environment, taking in to account the observed neutral genetic structure. RESULTS: These populations originated from the nearby Lake Mývatn, and showed small population sizes with low genetic diversity. Phenotypic variation was mostly correlated with neutral genetic diversity with only a small environmental effect. CONCLUSIONS: Phenotypic diversity in these cave populations appears to be largely the product of neutral processes, fitting the classical evolutionary expectations. However, the fact that neutral processes did not explain fully the phenotypic patterns suggests that further studies can increase our understanding on how neutral evolutionary processes can interact with other forces of selection at early stages of divergence. The accessibility of these populations has provided the opportunity for long-term monitoring of individual fish, allowing tracking how the environment can influence phenotypic and genetic divergence for shaping and maintaining diversity in small populations. Such studies are important, especially in freshwater, as habitat alteration is commonly breaking populations into smaller units, which may or may not be viable.

Density Spectral Array EEG for Sleep Staging in Pediatric Patients.

PURPOSE: Sleep is an essential physiologic process, which is frequently disrupted in children with illness and/or injury. Accurate identification and quantification of sleep may provide insights to improve long-term clinical outcomes. Traditionally, however, the identification of sleep stages has relied on the resource-intensive and time-consuming gold standard polysomnogram. We sought to use limited EEG data, converted into density spectrum array EEG, to accurately identify sleep stages in a clinical pediatric population. METHODS: We reviewed 87 clinically indicated pediatric polysomnographic studies with concurrent full montage EEG, between March 2017 and June 2020, of which 11 had normal polysomnogram and EEG interpretations. We then converted the EEG data of those normal studies into density spectral array EEG trends and had five blinded raters classify sleep stage (wakefulness, nonrapid eye movement [NREM] 1, NREM 2, NREM 3, and rapid eye movement) in 5-minute epochs. We compared the classified sleep stages from density spectral array EEG to the gold standard polysomnogram. RESULTS: Inter-rater reliability was highest (κ = 0.745, P < 0.0001) when classifying state into wakefulness, NREM sleep, and rapid eye movement sleep. Agreement between group classification and polysomnogram was highest (κ = 0.873, [0.819, 0.926], P < 0.0001) when state was classified into wakefulness and sleep and was lowest (κ = 0.674 [0.645, 0.703], P < 0.0001) when classified into wakefulness, NREM 1, NREM 2, NREM 3, and rapid eye movement. The most common error that raters made was overscoring of NREM 1. CONCLUSIONS: Density spectral array EEG can be used to identify sleep stages in clinical pediatric patients without relying on traditional polysomnography.

A Comparison of Automatically Extracted Quantitative EEG Features for Seizure Risk Stratification in Neonatal Encephalopathy.

PURPOSE: Seizures occur in up to 40% of neonates with neonatal encephalopathy. Earlier identification of seizures leads to more successful seizure treatment, but is often delayed because of limited availability of continuous EEG monitoring. Clinical variables poorly stratify seizure risk, and EEG use to stratify seizure risk has previously been limited by need for manual review and artifact exclusion. The goal of this study is to compare the utility of automatically extracted quantitative EEG (qEEG) features for seizure risk stratification. METHODS: We conducted a retrospective analysis of neonates with moderate-to-severe neonatal encephalopathy who underwent therapeutic hypothermia at a single center. The first 24 hours of EEG underwent automated artifact removal and qEEG analysis, comparing qEEG features for seizure risk stratification. RESULTS: The study included 150 neonates and compared the 36 (23%) with seizures with those without. Absolute spectral power best stratified seizure risk with area under the curve ranging from 63% to 71%, followed by range EEG lower and upper margin, median and SD of the range EEG lower margin. No features were significantly more predictive in the hour before seizure onset. Clinical examination was not associated with seizure risk. CONCLUSIONS: Automatically extracted qEEG features were more predictive than clinical examination in stratifying neonatal seizure risk during therapeutic hypothermia. qEEG represents a potential practical bedside tool to individualize intensity and duration of EEG monitoring and decrease time to seizure recognition. Future work is needed to refine and combine qEEG features to improve risk stratification.