Why Worry about How Many Species and Their Loss?

We are astonishingly ignorant about how many species are alive on earth today, and even more ignorant about how many we can lose yet still maintain ecosystem services that humanity ultimately depends upon. Mora et al.'s paper is important in offering an imaginative new approach to assessing total species numbers, both on land and in the sea.     

How much can parentage analyses tell us about precapture dispersal?

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

How much do we know about the current extinction rate?

Since about J600, 486 animal species have been recorded extinct. This represents about 0.04% of all animal species so far described. In the same period, 600 plant species are known to have disappeared, about 0.25% of the total. These figures are much smaller than those of the Permian/ Triassic and Cretaceous/Tertiary mass extinctions. One might therefore conclude that at present life on earth is at comparatively little risk of extinction. However, there is a growing body of data to show that the converse is true.     

How much can cladistics tell us about early hominid relationships?

Although cladistic analysis has been used to compare hypotheses of relationships among early hominids, the outcomes of different studies have depended entirely on the assumptions made by different investigators. Problems include the close genetic relationship of early hominid taxa, small fossil sample sizes, possible correlations among characters, and a lack of understanding about the evolutionary factors affecting characters. This study investigates the interaction of some of these problems affecting early hominid phylogenetics. Monte Carlo simulations of character state evolution in closely related taxa demonstrate that the sample sizes and close genetic relationships of early hominids do not permit cladistic analyses to obtain unequivocal results. Even with unrealistically good assumptions about the evolutionary dynamics affecting characters, the probability of the most parsimonious hypothesis being true is unacceptably small. In the face of these problems, even phylogenetic statements that are supported by a strong consensus of cladistic studies may nevertheless be in error, and such errors are likely to confound the placement of new specimens and taxa. Advancement in our knowledge of hominid phylogeny can depend only on a fuller understanding of the natural history and evolutionary dynamics of traits.     

How much can we know about the causes of evolutionary trends?

One of the first questions that paleontologists ask when they identify a large-scale trend in the fossil record (e.g., size increase, complexity increase) is whether it is passive or driven. In this article, I explore two questions about driven trends: (1) what is the underlying cause or source of the directional bias? and (2) has the strength of the directional bias changed over time? I identify two underdetermination problems that prevent scientists from giving complete answers to these two questions.     

Machine Learning: How Much Does It Tell about Protein Folding Rates?

The prediction of protein folding rates is a necessary step towards understanding the principles of protein folding. Due to the increasing amount of experimental data, numerous protein folding models and predictors of protein folding rates have been developed in the last decade. The problem has also attracted the attention of scientists from computational fields, which led to the publication of several machine learning-based models to predict the rate of protein folding. Some of them claim to predict the logarithm of protein folding rate with an accuracy greater than 90%. However, there are reasons to believe that such claims are exaggerated due to large fluctuations and overfitting of the estimates. When we confronted three selected published models with new data, we found a much lower predictive power than reported in the original publications. Overly optimistic predictive powers appear from violations of the basic principles of machine-learning. We highlight common misconceptions in the studies claiming excessive predictive power and propose to use learning curves as a safeguard against those mistakes. As an example, we show that the current amount of experimental data is insufficient to build a linear predictor of logarithms of folding rates based on protein amino acid composition.     

How about Lunch? Consequences of the Meal Context on Cognition and Emotion

Although research addresses the effects of a meal’s context on food preference, the psychological consequences of meal situations are largely unexplored. We compared the cognitive and emotional effects of a restaurant meal eaten in the company of others to a solitary meal consumed in a plain office using pre- and post-tests analysis and controlling for the kind and amount of food consumed. Three tasks were conducted, measuring: (1) semantic memory (2) cognitive control and error monitoring, and (3) processing of emotional facial expressions. Covert processes in these tasks were assessed with event-related brain potentials. A mood rating questionnaire indicated a relaxation effect of the restaurant as compared to the plain meal situation. The restaurant meal increased sensitivity to threatening facial expressions and diminished cognitive control and error monitoring. No effects were observed for semantic memory. These findings provide the first experimental evidence that a restaurant meal with a social component may be more relaxing than a meal eaten alone in a plain setting and may reduce cognitive control.     

How much can the orientation of G's eigenvectors tell us about genetic constraints?

A key goal in evolutionary quantitative genetics is to understand how evolutionary trajectories are constrained by pleiotropic coupling among multiple traits. Because studying pleiotropic constraints directly at the molecular genetic level remains very difficult, several analytical approaches attempt to draw conclusions about constraints by relating the orientation of the eigenvectors of the traits' (co)variance matrix to vectors of multivariate selection. On the basis of explicit models of genetic architecture, I here argue that the value of such approaches is greatly overestimated. The reason is that eigenvector orientation can be highly unstable and lack a biologically meaningful relationship with the underlying traits' genetic architecture. Genetic constraints are more profitably explored through experimental approaches avoiding the mathematical abstraction inherent in eigenanalysis.     

How do SNP ascertainment schemes and population demographics affect inferences about population history?

Background

The selection of variable sites for inclusion in genomic analyses can influence results, especially when exemplar populations are used to determine polymorphic sites. We tested the impact of ascertainment bias on the inference of population genetic parameters using empirical and simulated data representing the three major continental groups of cattle: European, African, and Indian. We simulated data under three demographic models. Each simulated data set was subjected to three ascertainment schemes: (I) random selection; (II) geographically biased selection; and (III) selection biased toward loci polymorphic in multiple groups. Empirical data comprised samples of 25 individuals representing each continental group. These cattle were genotyped for 47,506 loci from the bovine 50 K SNP panel. We compared the inference of population histories for the empirical and simulated data sets across different ascertainment conditions using F_ST and principal components analysis (PCA).

Results

Bias toward shared polymorphism across continental groups is apparent in the empirical SNP data. Bias toward uneven levels of within-group polymorphism decreases estimates of F_ST between groups. Subpopulation-biased selection of SNPs changes the weighting of principal component axes and can affect inferences about proportions of admixture and population histories using PCA. PCA-based inferences of population relationships are largely congruent across types of ascertainment bias, even when ascertainment bias is strong.

Conclusions

Analyses of ascertainment bias in genomic data have largely been conducted on human data. As genomic analyses are being applied to non-model organisms, and across taxa with deeper divergences, care must be taken to consider the potential for bias in ascertainment of variation to affect inferences. Estimates of F_ST, time of separation, and population divergence as estimated by principal components analysis can be misleading if this bias is not taken into account.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1469-5) contains supplementary material, which is available to authorized users.     

How does salinity influence habitat selection and growth in juvenile American eels Anguilla rostrata?

The influence of salinity on habitat selection and growth in juvenile American eels Anguilla rostrata captured in four rivers across eastern Canada was assessed in controlled experiments in 2011 and 2012. Glass eels were first categorized according to their salinity preferences towards fresh (FW), salt (SW) or brackish water (BW) and the growth rate of each group of elvers was subsequently monitored in controlled FW and BW environments for 7 months. Most glass eels (78–89%) did not make a choice, i.e. they remained in BW. Salinity preferences were not influenced by body condition, although a possible role of pigmentation could not be ruled out. Glass eels that did make a choice displayed a similar preference for FW (60–75%) regardless of their geographic origin but glass eels from the St Lawrence Estuary displayed a significantly higher locomotor activity than those from other regions. Neither the salinity preferences showed by glass eels in the first experiment nor the rearing salinities appeared to have much influence on growth during the experiments. Elvers from Nova Scotia, however, reached a significantly higher mass than those from the St Lawrence Estuary thus supporting the hypothesis of genetically (or epigenetically) based differences for growth between A. rostrata from different origins. These results provide important ecological knowledge for the sustained exploitation and conservation of this threatened species.