Rank-invariant estimation of inbreeding coefficients

The two alleles an individual carries at a locus are identical by descent (ibd) if they have descended from a single ancestral allele in a reference population, and the probability of such identity is the inbreeding coefficient of the individual. Inbreeding coefficients can be predicted from pedigrees with founders constituting the reference population, but estimation from genetic data is not possible without data from the reference population. Most inbreeding estimators that make explicit use of sample allele frequencies as estimates of allele probabilities in the reference population are confounded by average kinships with other individuals. This means that the ranking of those estimates depends on the scope of the study sample and we show the variation in rankings for common estimators applied to different subdivisions of 1000 Genomes data. Allele-sharing estimators of within-population inbreeding relative to average kinship in a study sample, however, do have invariant rankings across all studies including those individuals. They are unbiased with a large number of SNPs. We discuss how allele sharing estimates are the relevant quantities for a range of empirical applications.Subject terms: Population genetics, Evolutionary biology, Molecular ecology     

Behavioural Lateralization in Budgerigars Varies with the Task and the Individual

Handedness/footedness and side biases are a well-known phenomenon in many animals, including humans. However, these so-called biases have mostly been studied at the population level - individual biases have received less attention, especially with regard to consistency over different tasks. Here we investigate behavioral lateralization in 12 male Budgerigars, Melopsittacus undulatus, a social parrot inhabiting the Australian bushlands. We performed 5 types of experiments to investigate lateralization, in tasks that involved climbing onto a perch, or landing on perches arranged in various configurations. The birds displayed highly significant, individually varying biases. The bias displayed by any particular individual varied with the task, in strength as well as polarity. Analysis of the data revealed that the preferred foot used for climbing did not coincide with the foot that was used while landing. Thus, landing choices are probably not determined by foot bias. Furthermore, these individual preferences were overridden completely when a bird had to perform a task simultaneously with another bird.     

Estimating equations with nonignorably missing response data

Troxel, Lipsitz, and Brennan (1997, Biometrics 53, 857-869) considered parameter estimation from survey data with nonignorable nonresponse and proposed weighted estimating equations to remove the biases in the complete-case analysis that ignores missing observations. This paper suggests two alternative modifications for unbiased estimation of regression parameters when a binary outcome is potentially observed at successive time points. The weighting approach of Robins, Rotnitzky, and Zhao (1995, Journal of the American Statistical Association 90, 106-121) is also modified to obtain unbiased estimating functions. The suggested estimating functions are unbiased only when the missingness probability is correctly specified, and misspecification of the missingness model will result in biases in the estimates. Simulation studies are carried out to assess the performance of different methods when the covariate is binary or normal. For the simulation models used, the relative efficiency of the two new methods to the weighting methods is about 3.0 for the slope parameter and about 2.0 for the intercept parameter when the covariate is continuous and the missingness probability is correctly specified. All methods produce substantial biases in the estimates when the missingness model is misspecified or underspecified. Analysis of data from a medical survey illustrates the use and possible differences of these estimating functions.     

Group composition influences on behavioral sequence patterns of the Guiana dolphin Sotalia guianensis

Analysis of behavioral sequences displayed by different individuals can be used to infer individual decisions under diverse conditions. This study investigates whether behavioral transitions and routines differ according to the group composition of Guiana dolphins (Sotalia guianensis). We used the Z-score binomial test to detect significant behavioral transitions from a first-order transition matrix. The directed tree method was used to identify behavioral routines. Solitary individuals presented fewer transitions than heterogeneous groups. More routines were observed for heterogeneous than for homogeneous groups, and fewer routines for solitary individuals. Homogeneous groups maximized routines ending in traveling and milling, while heterogeneous groups presented higher probabilities of socializing. The analyses indicate that subgroups formed during Guiana dolphin fission–fusion events differed in probability of behavioral sequences, reflecting different feeding, resting, and socializing needs at different moments.     

Properties and unbiased estimation of F- and D-statistics in samples containing related and inbred individuals

The Patterson F- and D-statistics are commonly used measures for quantifying population relationships and for testing hypotheses about demographic history. These statistics make use of allele frequency information across populations to infer different aspects of population history, such as population structure and introgression events. Inclusion of related or inbred individuals can bias such statistics, which may often lead to the filtering of such individuals. Here, we derive statistical properties of the F- and D-statistics, including their biases due to the inclusion of related or inbred individuals, their variances, and their corresponding mean squared errors. Moreover, for those statistics that are biased, we develop unbiased estimators and evaluate the variances of these new quantities. Comparisons of the new unbiased statistics to the originals demonstrates that our newly derived statistics often have lower error across a wide population parameter space. Furthermore, we apply these unbiased estimators using several global human populations with the inclusion of related individuals to highlight their application on an empirical dataset. Finally, we implement these unbiased estimators in open-source software package funbiased for easy application by the scientific community.     

Biases in Visual,Auditory, and Audiovisual Perception of Space

Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1) if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors), and (2) whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli). Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers) was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s) driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only improves the precision of perceptual estimates, but also the accuracy.     

Attentional Bias towards Positive Emotion Predicts Stress Resilience

There is extensive evidence for an association between an attentional bias towards emotionally negative stimuli and vulnerability to stress-related psychopathology. Less is known about whether selective attention towards emotionally positive stimuli relates to mental health and stress resilience. The current study used a modified Dot Probe task to investigate if individual differences in attentional biases towards either happy or angry emotional stimuli, or an interaction between these biases, are related to self-reported trait stress resilience. In a nonclinical sample (N = 43), we indexed attentional biases as individual differences in reaction time for stimuli preceded by either happy or angry (compared to neutral) face stimuli. Participants with greater attentional bias towards happy faces (but not angry faces) reported higher trait resilience. However, an attentional bias towards angry stimuli moderated this effect: The attentional bias towards happy faces was only predictive for resilience in those individuals who also endorsed an attentional bias towards angry stimuli. An attentional bias towards positive emotional stimuli may thus be a protective factor contributing to stress resilience, specifically in those individuals who also endorse an attentional bias towards negative emotional stimuli. Our findings therefore suggest a novel target for prevention and treatment interventions addressing stress-related psychopathology.     

Potential for parasite-induced biases in aquatic invertebrate population studies

Recent studies highlight the need to include estimates of detection/capture probability in population studies. This need is particularly important in studies where detection and/or capture probability is influenced by parasite-induced behavioral alterations. We assessed potential biases associated with sampling a population of the amphipod Gammarus lacustris in the presence of Polymorphus spp. acanthocephalan parasites shown to increase positive phototaxis in their amphipod hosts. We trapped G. lacustris at two water depths (benthic and surface) and compared number of captures and number of parasitized individuals at each depth. While we captured the greatest number of G. lacustris individuals in benthic traps, parasitized individuals were captured most often in surface traps. These results reflect the phototaxic movement of infected individuals from benthic locations to sunlit surface waters. We then explored the influence of varying infection rates on a simulated population held at a constant level of abundance. Simulations resulted in increasingly biased abundance estimates as infection rates increased. Our results highlight the need to consider parasite-induced biases when quantifying detection and/or capture probability in studies of aquatic invertebrate populations.     

Eurasian otter (<Emphasis Type="Italic">Lutra lutra</Emphasis>) density estimate based on radio tracking and other data sources

Estimating animal population size is a critical task in both wildlife management and conservation biology. Precise and unbiased estimates are nonetheless mostly difficult to obtain, as estimates based on abundance over unit area are frequently inflated due to the “edge effect” bias. This may lead to the implementation of inappropriate management and conservation decisions. In an attempt to obtain an as accurate and conservative as possible picture of Eurasian otter (Lutra lutra) numbers, we combined radio tracking data from a subset of tracked individuals from an extensive project on otter ecology performed in Southern Portugal with information stemming from other data sources, including trapping, carcasses, direct observation of tagged and untagged individuals, relatedness estimates among genotyped individuals, and a minor contribution from non-invasive genetic sampling. In 158 km of water network, which covers a sampling area of 161 km² and corresponds to the minimum convex polygon constructed around the locations of five radio-tracked females, 21 animals were estimated to exist. They included the five radio-tracked, reproducing females and six adult males. Density estimates varied from one otter per 3.71–7.80 km of river length (one adult otter per 7.09–14.36 km) to one otter per 7.67–7.93 km² of range, depending on the method and scale of analysis. Possible biases and implications of methods used for estimating density of otters and other organisms living in linear habitats are highlighted, providing recommendations on the issue.     

Are shy individuals less behaviorally variable? Insights from a captive population of mouse lemurs

Increasingly, individual variation in personality has become a focus of behavioral research in animal systems. Boldness and shyness, often quantified as the tendency to explore novel situations, are seen as personality traits important to the fitness landscape of individuals. Here we tested for individual differences within and across contexts in behavioral responses of captive mouse lemurs (Microcebus murinus) to novel objects, novel foods, and handling. We report consistent differences in behavioral responses for objects and handling. We also found that the responses to handling and novel objects were correlated and repeatable. Lastly, we show that shyer individuals may show less variability in their behavioral responses. This study provides new information on the potential for behavioral syndromes in this species and highlights differences in the degree to which behavioral types (e.g., shy/bold) vary in their behavioral responses.     

Percent lipid is associated with body size but not task in the bumble bee <Emphasis Type="Italic">Bombus impatiens</Emphasis>

In some group-living organisms, labor is divided among individuals. This allocation to particular tasks is frequently stable and predicted by individual physiology. Social insects are excellent model organisms in which to investigate the interplay between physiology and individual behavior, as division of labor is an important feature within colonies, and individual physiology varies among the highly related individuals of the colony. Previous studies have investigated what factors are important in determining how likely an individual is, compared to nestmates, to perform certain tasks. One such task is foraging. Corpulence (i.e., percent lipid) has been shown to determine foraging propensity in honey bees and ants, with leaner individuals being more likely to be foragers. Is this a general trend across all social insects? Here we report data analyzing the individual physiology, specifically the percent lipid, of worker bumble bees (Bombus impatiens) from whom we also analyze behavioral task data. Bumble bees are also unusual among the social bees in that workers may vary widely in size. Surprisingly we find that, unlike other social insects, percent lipid is not associated with task propensity. Rather, body size closely predicts individual relative lipid stores, with smaller worker bees being allometrically fatter than larger worker bees.     

Analyzing time‐ordered event data with missed observations

A common problem with observational datasets is that not all events of interest may be detected. For example, observing animals in the wild can difficult when animals move, hide, or cannot be closely approached. We consider time series of events recorded in conditions where events are occasionally missed by observers or observational devices. These time series are not restricted to behavioral protocols, but can be any cyclic or recurring process where discrete outcomes are observed. Undetected events cause biased inferences on the process of interest, and statistical analyses are needed that can identify and correct the compromised detection processes. Missed observations in time series lead to observed time intervals between events at multiples of the true inter‐event time, which conveys information on their detection probability. We derive the theoretical probability density function for observed intervals between events that includes a probability of missed detection. Methodology and software tools are provided for analysis of event data with potential observation bias and its removal. The methodology was applied to simulation data and a case study of defecation rate estimation in geese, which is commonly used to estimate their digestive throughput and energetic uptake, or to calculate goose usage of a feeding site from dropping density. Simulations indicate that at a moderate chance to miss arrival events (p = 0.3), uncorrected arrival intervals were biased upward by up to a factor 3, while parameter values corrected for missed observations were within 1% of their true simulated value. A field case study shows that not accounting for missed observations leads to substantial underestimates of the true defecation rate in geese, and spurious rate differences between sites, which are introduced by differences in observational conditions. These results show that the derived methodology can be used to effectively remove observational biases in time‐ordered event data.     

Why do chimpanzees have diverse behavioral repertoires yet lack more complex cultures? Invention and social information use in a cumulative task

Humans are distinctive in their dependence upon products of culture for survival, products that have evolved cumulatively over generations such that many cannot now be created by a single individual. Why the cultural capacity of humans appears unrivalled in the animal kingdom is a topic of ongoing debate. Here we explore whether innovation and/or social learning propensities may constrain the ability of one of our closest living relatives, chimpanzees (Pan troglodytes), to master an extractive foraging and tool-use task designed to afford opportunities for cumulative culture to develop. We further explore the potential demographic characteristics associated with novel task solutions. Chimpanzees (N = 53) were inventive, flexibly exploring the novel task, albeit complex inventions were rare and shaped by prior individual experience with similar tool-use tasks. However, they displayed no evidence of cumulative cultural learning. Communities displayed richer behavioral repertoires and had greater task success than chimpanzees tested in an asocial control condition, but their solution complexity did not surpass what individuals invented. The lack of social transmission of complex and beneficial solutions in contexts like those we studied provides one explanation for the limited cumulative culture observed in this species.     

Reducing Bias in Auditory Duration Reproduction by Integrating the Reproduced Signal

Duration estimation is known to be far from veridical and to differ for sensory estimates and motor reproduction. To investigate how these differential estimates are integrated for estimating or reproducing a duration and to examine sensorimotor biases in duration comparison and reproduction tasks, we compared estimation biases and variances among three different duration estimation tasks: perceptual comparison, motor reproduction, and auditory reproduction (i.e. a combined perceptual-motor task). We found consistent overestimation in both motor and perceptual-motor auditory reproduction tasks, and the least overestimation in the comparison task. More interestingly, compared to pure motor reproduction, the overestimation bias was reduced in the auditory reproduction task, due to the additional reproduced auditory signal. We further manipulated the signal-to-noise ratio (SNR) in the feedback/comparison tones to examine the changes in estimation biases and variances. Considering perceptual and motor biases as two independent components, we applied the reliability-based model, which successfully predicted the biases in auditory reproduction. Our findings thus provide behavioral evidence of how the brain combines motor and perceptual information together to reduce duration estimation biases and improve estimation reliability.     

Modelling developmental instability in relation to individual fitness: a fully Bayesian latent variable model approach

Since the influential paper by Palmer and Strobeck in 1986, the statistical analysis of fluctuating asymmetry and developmental stability has received much attention. Most studies deal with one of the following four difficulties: (i) correcting for bias in asymmetry estimates due to measurement error; (ii) quantifying sampling error in the estimation of individual developmental stability using individual asymmetry; (iii) the detection of directional asymmetry and antisymmetry; and (iv) combining data from several traits. Yet, few studies have focused on statistical properties of estimating a relationship between individual developmental stability and other factors (e.g. fitness). In this paper I introduce a fully Bayesian model in which the unobservable individual developmental stability is treated as a latent variable. The latter is then related to individual fitness. I show by means of the analysis of simulated data that this approach has several advantages over traditional techniques. First, the method provides unbiased (but slightly less accurate) estimates of slopes between developmental stability and fitness taking all sources of error into account. Secondly, it allows proper investigation of non‐linear associations. Finally, the model allows unbiased estimation of unobserved fitness of individuals that have been measured on left and right side.     

Success-biased social learning: Cultural and evolutionary dynamics

Success bias is a social learning strategy whereby learners tend to acquire the cultural variants of successful individuals. I develop a general model of success-biased social learning for discrete cultural traits with stochastic payoffs, and investigate its dynamics when only two variants are present. I find that success bias inherently favors rare variants, and consequently performs worse than unbiased imitation (i.e. random copying) when success payoffs are at least mildly stochastic and the optimal variant is common. Because of this weakness, success bias fails to replace unbiased imitation in an evolutionary model when selection is fairly weak or when the environment is relatively stable, and sometimes fails to invade at all. I briefly discuss the optimal strength of success bias, the complicated nature of defining success in social learning contexts, and the value of variant frequency as an important source of information to social learners. I conclude with predictions regarding the prevalence of success bias in different behavioral domains.     

No Evidence for the Association between a Polymorphism in the PCLO Depression Candidate Gene with Memory Bias in Remitted Depressed Patients and Healthy Individuals

The PCLO rs2522833 candidate polymorphism for depression has been associated to monoaminergic neurotransmission. In healthy and currently depressed individuals, the polymorphism has been found to affect activation of brain areas during memory processing, but no direct association of PCLO with memory bias was found. We hypothesized that the absence of this association might have been obscured by current depressive symptoms or genetically driven individual differences in reactivity to stressful events. Experiencing stressful childhood events fosters dysfunctional assumptions that are related to cognitive biases, and may modulate the predisposition for depression via epigenetic effects. The association between PCLO and memory bias, as well as interaction between PCLO and childhood events was studied in patients remitted from depression (N = 299), as well as a sample of healthy individuals (N = 157). The participants performed an emotional verbal memory task after a sad mood induction. Childhood trauma and adversity were measured with a questionnaire. The Genotype main effect, and Genotype by Childhood Events interaction were analyzed for memory bias in both samples. PCLO risk allele carrying remitted depressed patients did not show more negatively biased memory than non-risk allele carriers, not even patients with stressful childhood events. A similar pattern of results was found in healthy individuals. Memory bias may not be strongly associated with the PCLO rs2522833 polymorphism. We did not find any support for the PCLO-childhood events interaction, but the power of our study was insufficient to exclude this possibility.     

Self-amplification as a source of interindividual variability: Shelter selection in cockroaches

Although group effect and collective decisions have been described in many insect species, the behavioral mechanisms involved in the process remain poorly documented at the individual level. We examined how individual behavior depends on the environmental context and we precisely characterized the behavioral rules leading to settlement of individual cockroaches in resting site. We focused on the spatial and temporal distribution of individuals in absence of conspecifics. Using isolated adult males of the cockroach Periplaneta americana, we showed that the quality of resting sites and the duration of the settlement exerted an influence on the individual decision-making: the probability of leaving a resting site decreased with the time spent under a shelter. A numerical model derived from experimental data suggested that this simple rule of self-amplification can also account for the interindividual variability.     

Estimating the number of channels in patch recordings

The estimation of the number of channels in a patch was assumed to be equivalent to the estimation of the binomial parameter n. Seven estimators were evaluated, using data sets simulated for a range of parameters appropriate for single channel recording experiments. No single estimator was best for all parameters; a combination of estimators is a possible option to avoid the biases of individual estimators. All estimators were highly accurate in estimating n in the case that n = 1. For n ≤ 4 the simplest estimator, the maximum number of simultaneously open channels, was the best, For larger values of n the best estimators were Bayesian.     

非等试验设计胚乳品质性状的遗传分析方法

根据朱军(1996)提出的包括基因型×环境互作的胚乳品质性状三倍体遗传模型,运用蒙特卡罗模拟证明,以混合线性模型统计分析的MINQUE法,对非等试验设计获得的实验数据进行数量遗传分析是可行的.蒙特卡罗模拟结果表明在样本群体大小基本一致的条件下,采用相等试验设计或非等试验设计所估算的遗传参数的偏差(Blas)和功效值(Power)没有明显差异,表明以非等试验设计获得的非平衡数据也可用来进行遗传分析,估算上述遗传模型中的各项遗传方差分量和协方差分量,并且可以采用朱军(1993)提出的AUP法来预测遗传模型中的各项遗传效应值.