Coral reef fish larvae show no evidence for map-based navigation after physical displacement.

Millions of minute, newly hatched coral reef fish larvae get carried into the open ocean by highly complex and variable currents. To survive, they must return to a suitable reef habitat within a species-specific time. Strikingly, previous studies have demonstrated that return to home reefs is much more frequent than would be expected by chance. It has been shown that magnetic and sun compass orientation can help cardinalfish maintain their innate swimming direction but do they also have a navigational map to cope with unexpected displacements? If displaced settling-stage cardinalfish Ostorhinchus doederleini use positional information during their pelagic dispersal, we would expect them to re-orient toward their home reef. However, after physical displacement by 180 km, the fish showed a swimming direction indistinguishable from original directions near the capture site. This suggests that the tested fish rely on innate or learned compass directions and show no evidence for map-based navigation.

Demerelate: calculating interindividual relatedness for kinship analysis based on codominant diploid genetic markers using R.

The Demerelate package offers algorithms to calculate different interindividual relatedness measurements. Three different allele sharing indices, five pairwise weighted estimates of relatedness and four pairwise weighted estimates with sample size correction are implemented to analyse kinship structures within populations. Statistics are based on randomization tests; modelling relatedness coefficients by logistic regression, modelling relatedness with geographic distance by mantel correlation and comparing mean relatedness between populations using pairwise t-tests. Demerelate provides an advance on previous software packages by including some estimators not available in R to date, along with FIS , as well as combining analysis of relatedness and spatial structuring. An UPGMA tree visualizes genetic relatedness among individuals. Additionally, Demerelate summarizes information on data sets (allele vs. genotype frequencies; heterozygosity; FIS values). Demerelate is - to our knowledge - the first R package implementing basic allele sharing indices such as Blouin's Mxy relatedness, the estimator of Wang corrected for sample size (wangxy ), estimators based on Morans I adapted to genetic relatedness as well as combining all estimators with geographic information. The R environment enables users to better understand relatedness within populations due to the flexibility of Demerelate of accepting different data sets as empirical data, reference data, geographical data and by providing intermediate results. Each statistic and tool can be used separately, which helps to understand the suitability of the data for relatedness analysis, and can be easily implemented in custom pipelines.

Positive Preferences: The Emotional Valence of What an Avatar Says Matters.

This study examined preferences and ascriptions of human control for avatars associated with positive and negative language. An avatar is a graphical representation of an individual user in a virtual world. Users form judgments of other virtual world users based on the appearance and behavior of their avatars in the absence of physical cues. In particular, users have previously displayed sensitivity toward anthropomorphism and verbal behavior of avatars they encounter within virtual environments. Thus far, investigations of language in online and virtual spaces have been limited to specific contexts. University student participants and Amazon Mechanical Turk workers were shown two avatars. Each pair consisted of two out of three possible appearances: a tiger, a male, or a female. Each avatar was aligned with a different text introduction: one containing words of positive emotional valence and the other of negative emotional valence. Participants from both samples preferred avatars associated with positive language, regardless of appearance, but participants did not ascribe human control of an avatar based on either emotional valance or appearance. Significant differences for reported preferences and likeability demonstrate the salience of emotive language as a social cue even in short text introductions for avatars. These findings suggest that those we like and want to be around in virtual environments might not necessarily align with whom we view as human.

Calculations of population differentiation based on GST and D: forget GST but not all of statistics!

G(ST)-values and its relatives (F(ST)) belong to the most used parameters to define genetic differences between populations. Originally, they were developed for allozymes with very low number of alleles. Using highly polymorphic microsatellite markers it was often puzzling that G(ST)-values were very low but statistically significant. In their papers, Jost (2008) and Hedrick (2005) explained that G(ST)-values do not show genetic differentiation, and Jost suggested calculating D-values instead. Theoretical mathematical considerations are often difficult to follow; therefore, we chose an applied approach comparing two artificial populations with different number of alleles at equal frequencies and known genetic divergence. Our results show that even for more than one allele per population G(ST)-values do not calculate population differentiation correctly; in contrast, D-values do reflect the genetic differentiation indicating that data based on G(ST)-values need to be re-evaluated. In our approach, statistical evaluations remained similar. We provide information about the impact of different sample sizes on D-values in relation to number of alleles and genetic divergence.