Explore the vast range of titles available.

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called \"stasis paradox\" highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is superior to purely phenotypic estimates of selection and evolutionary change.

Evolutionary adaptation through genetic change requires genetic variation and is a key mechanism enabling species to persist in changing environments. Although a substantial body of work has focused on understanding how and why additive genetic variance (VA) differs among traits within species, we still know little about how they vary among species. Here we make a first attempt at testing for interspecific variation in two complementary measures of VA and the role of phylogeny in shaping this variation. To this end, we performed a phylogenetic comparative analysis using 1822 narrow‐sense heritability (h2) for 68 species of birds and mammals and 378 coefficients of additive genetic variance (CVA) estimates for 23 species. Controlling for within‐species variation attributable to estimation method and trait type, we found some interspecific variation in h2 (~15%) but not CVA. Although suggestive of interspecific variation in the importance of non‐(additive) genetic sources of variance, sample sizes were insufficient to test this hypothesis directly. Additionally, although power was low, no phylogenetic signal was detected for either measure. Hence, while this suggests interspecific variation in VA is probably small, our understanding of interspecific variation in the adaptive potential of wild vertebrate populations is currently hampered by data limitations, a scarcity of CVA estimates and a measure of their uncertainty in particular. Evolutionary adaptation through genetic change requires genetic variation, but little is known about how much this varies across species. To this end, we performed a phylogenetic comparative analysis using 1822 narrow‐sense heritability for 68 species of birds and mammals and 378 coefficients of additive genetic variance estimates for 23 species. Although data limitations meant statistical power was low, we found that species varied little in their additive genetic variance and none of this was explained by phylogeny.

Amongst the numerous problems associated with the use of impact factors as a measure of quality are the systematic differences in impact factors that exist among scientific fields. While in theory this can be circumvented by limiting comparisons to journals within the same field, for a diverse and multidisciplinary field like evolutionary biology, in which the majority of papers are published in journals that publish both evolutionary and non-evolutionary papers, this is impossible. However, a journal's overall impact factor may well be a poor predictor for the impact of its evolutionary papers. The extremely high impact factors of some multidisciplinary journals, for example, are by many believed to be driven mostly by publications from other fields. Despite plenty of speculation, however, we know as yet very little about the true impact of evolutionary papers in journals not specifically classified as evolutionary. Here I present, for a wide range of journals, an analysis of the number of evolutionary papers they publish and their average impact. I show that there are large differences in impact among evolutionary and non-evolutionary papers within journals; while the impact of evolutionary papers published in multidisciplinary journals is substantially overestimated by their overall impact factor, the impact of evolutionary papers in many of the more specialized, non-evolutionary journals is significantly underestimated. This suggests that, for evolutionary biologists, publishing in high-impact multidisciplinary journals should not receive as much weight as it does now, while evolutionary papers in more narrowly defined journals are currently undervalued. Importantly, however, their ranking remains largely unaffected. While journal impact factors may thus indeed provide a meaningful qualitative measure of impact, a fair quantitative comparison requires a more sophisticated journal classification system, together with multiple field-specific impact statistics per journal.

Biosensors have become integrated into our lives. Current technology requires biosensors not only to have high sensitivity but also to have high specificity for one target, while repelling all other molecules and materials in the biological medium. These goals are met by surfaces that combine a biorecognition element and a high‐quality antifouling layer. In this review, we largely focus on polymer brushes that are grafted from the surface, as these are known to exhibit excellent antifouling properties. We also discuss how to functionalize these with biorecognition elements. Based on the current research on antifouling brushes, we recommend using poly(2‐hydroxypropylmethacrylamide) (HPMAA) and/or poly(carboxybetainemethacrylamide) (CBMAA) brushes, with a thickness between 20–30 nm. Furthermore, we note the importance of high polymer chain densities in such brushes and highlight that a proper comparison requires, among others, similar pre‐treatments. These antifouling brushes are biospecific after receptors are integrated with efficient coupling strategies. Here the opportunities and limitations of frequently used approaches of antifouling polymer brushes within biosensors are highlighted. Also, with the resulting combination of high specificity and low (bio‐)chemical noise levels, we envision an increase in the incorporation of novel polymer brushes for the development of stable biospecific sensors. Modern biosensors offer high sensitivity but often struggle with long‐term stability and selectivity for specific targets. Antifouling polymer brushes help enhance both stability and selectivity. In this review, we compare recent antifouling coatings, their design parameters, and how they are integrated with biorecognition elements for improved biosensor performance. We also explore their current applications in the sensing field.

1. Efforts to understand the links between evolutionary and ecological dynamics hinge on our ability to measure and understand how genes influence phenotypes, fitness and population dynamics. Quantitative genetics provides a range of theoretical and empirical tools with which to achieve this when the relatedness between individuals within a population is known. 2. A number of recent studies have used a type of mixed-effects model, known as the animal model, to estimate the genetic component of phenotypic variation using data collected in the field. Here, we provide a practical guide for ecologists interested in exploring the potential to apply this quantitative genetic method in their research. 3. We begin by outlining, in simple terms, key concepts in quantitative genetics and how an animal model estimates relevant quantitative genetic parameters, such as heritabilities or genetic correlations. 4. We then provide three detailed example tutorials, for implementation in a variety of software packages, for some basic applications of the animal model. We discuss several important statistical issues relating to best practice when fitting different kinds of mixed models. 5. We conclude by briefly summarizing more complex applications of the animal model, and by highlighting key pitfalls and dangers for the researcher wanting to begin using quantitative genetic tools to address ecological and evolutionary questions.

Studies on the evolution of cooperative behaviour are typically confined to understanding its adaptive value. It is equally essential, however, to understand its potential to evolve, requiring knowledge about the phenotypic consistency and genetic basis of cooperative behaviour. While previous observational studies reported considerably high heritabilities of helping behaviour in cooperatively breeding vertebrates, experimental studies disentangling the relevant genetic and non-genetic components of cooperative behaviour are lacking. In a half-sibling breeding experiment, we investigated the repeatability and heritability of three major helping behaviours performed by subordinates of the cooperatively breeding fish Neolamprologus pulcher. To experimentally manipulate the amount of help needed in a territory, we raised the fish in two environments differing in egg predation risk. All three helping behaviours were significantly repeatable, but had very low heritabilities. The high within-individual consistencies were predominantly due to maternal and permanent environment effects. The perceived egg predation risk had no effect on helping, but social interactions significantly influenced helping propensities. Our results reveal that developmentally plastic adjustments of provided help to social context shape cooperative phenotypes, whereas heritable genetic variation plays a minor role.

Theoretical and laboratory research suggests that phenotypic plasticity can evolve under selection. However, evidence for its evolutionary potential from the wild is lacking. We present evidence from a Dutch population of great tits (Parus major) for variation in individual plasticity in the timing of reproduction, and we show that this variation is heritable. Selection favoring highly plastic individuals has intensified over a 32-year period. This temporal trend is concurrent with climate change causing a mismatch between the breeding times of the birds and their caterpillar prey. Continued selection on plasticity can act to alleviate this mismatch.

Gene flow in evolution Evolutionary theory has a lot to say on the way that natural populations adapt to their environment, and it is an important factor when considering the impact of human actions on evolutionary dynamics of populations. But experimental data to support the theory are scarce, and two groups this week report findings at odds with accepted thinking. It is commonly assumed that population divergence is a balance between the diversifying effect of selection and the homogenizing effect of gene flow caused by immigration and dispersal. But both of these experiments, on populations of the great tit Parus major , show that differential dispersal can maintain and even emphasize genetic differences. Understanding the capacity of natural populations to adapt to their local environment is a central topic in evolutionary biology. Phenotypic differences between populations may have a genetic basis, but showing that they reflect different adaptive optima requires the quantification of both gene flow and selection 1 , 2 , 3 . Good empirical data are rare 4 . Using data on a spatially structured island population of great tits ( Parus major ), we show here that a persistent difference in mean clutch size between two subpopulations only a few kilometres apart has a major genetic component. We also show that immigrants from outside the island carry genes for large clutches. But gene flow into one subpopulation is low, as a result of a low immigration rate together with strong selection against immigrant genes. This has allowed for adaptation to the island environment and the maintenance of small clutches. In the other area, however, higher gene flow prevents local adaptation and maintains larger clutches. We show that the observed small-scale genetic difference in clutch size is not due to divergent selection on the island, but to different levels of gene flow from outside the island. Our findings illustrate the large effect of immigration on the evolution of local adaptations and on genetic population structure.

Evolutionary ecologists dating back to Darwin (1871) have sought to understand why males are larger than females in some species, and why females are the larger sex in others. Although the former is widespread in mammals, rodents and other small mammals usually exhibit low levels of sexual size dimorphism (SSD). Here, we investigate patterns of sexual dimorphism in 34 vole species belonging to the subfamily Arvicolinae in a phylogenetic comparative framework. We address the potential role of sexual selection and fecundity selection in creating sex differences in body size. No support was found for hyperallometric scaling of male body size to female body size. We observed a marginally significant relationship between SSD and the ratio of male to female home range size, with the latter being positively related to the level of intrasexual competition for mates. This suggests that sexual selection favours larger males. Interestingly, we also found that habitat type, but not mating system, constitutes a strong predictor of SSD. Species inhabiting open habitats – where males have extensive home ranges in order to gain access to as many females as possible – exhibit a higher mean dimorphism than species inhabiting closed habitats, where females show strong territoriality and an uniform distribution preventing males to adopt a territorial strategy for gaining copulations. Nonetheless, variation in the strength of sexual selection is not the only selective force shaping SSD in voles; we also found a positive association between female size and litter size across lineages. Assuming this relationship also exists within lineages (i.e. fecundity selection on female size), this suggests an additional role for variation in the strength of fecundity selection shaping interspecific differences in female size, and indirectly in SSD. Therefore our results suggest that different selective processes act on the sizes of males and females, but because larger size is favoured in both sexes, SSD is on average relatively small.