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1,663 results for “BIAS”
Data from: Biased generalization of salient traits drives the evolution of warning signals
The importance of receiver biases in shaping the evolution of many signalling systems is widely acknowledged. Here we show that receiver bias can explain which traits evolve to become warning signals. For warning colouration, a generalization bias for a signalling trait can result from predators learning to discriminate unprofitable from profitable prey. However, since the colour patterns of prey are complex traits with multiple components, it is crucial to understand which of the many aspects of prey appearance evolve into signals. We provide experimental evidence that the more salient differences in prey traits give rise to greater generalization bias, corresponding to stronger selection towards trait exaggeration. Our results are based on experiments with domestic chickens as predators in a Skinner-box-like setting, and imply that the difference in appearance between profitable and unprofitable prey that is most rapidly learnt produces the greatest generalization bias. As a consequence, certain salient traits of unprofitable prey are selected towards exaggeration to even higher salience, driving the evolution of warning colouration. This general idea may also help to explain the evolution of many other striking signalling traits found in nature.
Data from: Population structure leads to male-biased population sex ratios under environmental sex determination
Spatial structure has been shown to favor female-biased sex allocation, but current theory fails to explain male biases seen in many taxa, particularly those with environmental sex determination (ESD). We present a theory and accompanying individual-based simulation model that demonstrates how population structure leads to male-biased population sex ratios under ESD. Our simulations agree with earlier work showing that the high productivity of female-producing habitats creates a net influx of sex-determining alleles into male-producing habitats, causing larger sex ratio biases and lower productivity in male-producing environments (Harts et al. 2014). In contrast to previous findings, we show that male-biasing habitats disproportionately impact the global sex ratio, resulting in stable male-biased population sex ratios under ESD. The failure to detect a male bias in earlier work can be attributed to small subpopulation sizes leading to local mate competition, a condition unlikely to be met in most ESD systems. Simulations revealed that consistent male biases are expected over a wide range of population structures, environmental conditions, and genetic architectures of sex determination, with male excesses as large as 30 percent under some conditions. Given the ubiquity of genetic structure in natural populations, we predict that modest, enduring male biased allocation should be common in ESD species, a pattern consistent with reviews of ESD sex ratios.
Data from: Correction for bias in meta-analysis of little-replicated studies
1. Meta-analyses conventionally weight study estimates on the inverse of their error variance, in order to maximize precision. Unbiased variability in the estimates of these study-level error variances increases with the inverse of study-level replication. Here we demonstrate how this variability accumulates asymmetrically across studies in precision-weighted meta-analysis, to cause undervaluation of the meta-level effect size or its error variance (the meta-effect and meta-variance). 2. Small samples, typical of the ecological literature, induce big sampling errors in variance estimation, which substantially bias precision-weighted meta-analysis. Simulations revealed that biases differed little between random- and fixed-effects tests. Meta-estimation of a one-sample mean from 20 studies, with sample sizes of 3 to 20 observations, undervalued the meta-variance by ~20%. Meta-analysis of two-sample designs from 20 studies, with sample sizes of 3 to 10 observations, undervalued the meta-variance by 15-20% for the log response ratio (lnR); it undervalued the meta-effect by ~10% for the standardised mean difference (SMD). 3. For all estimators, biases were eliminated or reduced by a simple adjustment to the weighting on study precision. The study-specific component of error variance prone to sampling error and not parametrically attributable to study-specific replication was replaced by its cross-study mean, on the assumption of random sampling from the same population variance for all studies, and sufficient studies for averaging. Weighting each study by the inverse of this mean-adjusted error variance universally improved accuracy in estimation of both the meta-effect and its significance, regardless of number of studies. For comparison, weighting only on sample size gave the same improvement in accuracy, but could not sensibly estimate significance. 4. For the one-sample mean and two-sample lnR, adjusted weighting also improved estimation of between-study variance by DerSimonian-Laird and REML methods. For random-effects meta-analysis of SMD from little-replicated studies, the most accurate meta-estimates obtained from adjusted weights following conventionally-weighted estimation of between-study variance. 5. We recommend adoption of weighting by inverse adjusted-variance for meta-analyses of well- and little-replicated studies, because it improves accuracy and significance of meta-estimates, and it can extend the scope of the meta-analysis to include some studies without variance estimates.
Data from: Learning to speciate: the biased learning of mate preferences promotes adaptive radiation
Bursts of rapid repeated speciation called adaptive radiations have generated much of Earth's biodiversity and fascinated biologists since Darwin, but we still do not know why some lineages radiate and others do not. Understanding what causes assortative mating to evolve rapidly and repeatedly in the same lineage is key to understanding adaptive radiation. Many species that have undergone adaptive radiations exhibit mate preference learning, where individuals acquire mate preferences by observing the phenotypes of other members of their populations. Mate preference learning can be biased if individuals also learn phenotypes to avoid in mates, and shift their preferences away from these avoided phenotypes. We used individual-based computational simulations to study whether biased and unbiased mate preference learning promote ecological speciation and adaptive radiation. We found that ecological speciation can be rapid and repeated when mate preferences are biased, but is inhibited when mate preferences are learned without bias. Our results suggest that biased mate preference learning may play an important role in generating animal biodiversity through adaptive radiation.
Data from: Elevated substitution rate estimates from ancient DNA: model violation and bias of Bayesian methods
The increasing ability to extract and sequence DNA from non-contemporaneous tissue offers biologists the opportunity to analyze ancient DNA (aDNA) together with modern DNA (mDNA) to address the taxonomy of extinct species, evolutionary origins, historical phylogeography and biogeography. Perhaps more exciting are recent developments in coalescence-based Bayesian inference that offer the potential to use temporal information from aDNA and mDNA for the estimation of substitution rates and divergence dates as an alternative to fossil and geological calibration. This comes at a time of growing interest in the possibility of time dependency for molecular rate estimates. Here we provide a critical assessment of Bayesian MCMC analysis for the estimation of substitution rate using simulated samples of aDNA and mDNA. We conclude that the current models and priors employed in Bayesian MCMC analysis of heterochronous mtDNA are susceptible to an upward bias in the estimation of substitution rates due to model misspecification when the data comes from populations with less than simple demographic histories, including sudden short-lived population bottlenecks or pronounced population structure. However when model misspecification is only mild, then the 95% HPD intervals provide adequate frequentist coverage of the true rates.
Data from: Tree imbalance causes a bias in phylogenetic estimation of evolutionary timescales using heterochronous sequences
Phylogenetic estimation of evolutionary timescales has become routine in biology, forming the basis of a wide range of evolutionary and ecological studies. However, there are various sources of bias that can affect these estimates. We investigated whether tree imbalance, a property that is commonly observed in phylogenetic trees, can lead to reduced accuracy or precision of phylogenetic timescale estimates. We analysed simulated data sets with calibrations at internal nodes and at the tips, taking into consideration different calibration schemes and levels of tree imbalance. We also investigated the effect of tree imbalance on two empirical data sets: mitogenomes from primates and serial samples of the African swine fever virus. In analyses calibrated using dated, heterochronous tips, we found that tree imbalance had a detrimental impact on precision and produced a bias in which the overall timescale was underestimated. A pronounced effect was observed in analyses with shallow calibrations. The greatest decreases in accuracy usually occurred in the age estimates for medium and deep nodes of the tree. In contrast, analyses calibrated at internal nodes did not display a reduction in estimation accuracy or precision due to tree imbalance. Our results suggest that molecular-clock analyses can be improved by increasing taxon sampling, with the specific aims of including deeper calibrations, breaking up long branches and reducing tree imbalance.
Data from: Prolific observer bias in the life sciences: why we need blind data recording
Observer bias and other "experimenter effects" occur when researchers' expectations influence study outcome. These biases are strongest when researchers expect a particular result, are measuring subjective variables, and have an incentive to produce data that confirm predictions. To minimize bias, it is good practice to work "blind," meaning that experimenters are unaware of the identity or treatment group of their subjects while conducting research. Here, using text mining and a literature review, we find evidence that blind protocols are uncommon in the life sciences and that nonblind studies tend to report higher effect sizes and more significant p-values. We discuss methods to minimize bias and urge researchers, editors, and peer reviewers to keep blind protocols in mind.
Data from: State-dependent judgement bias in Drosophila: evidence for evolutionarily primitive affective processes
Affective states influence decision-making under ambiguity in humans and other animals. Individuals in a negative state tend to interpret ambiguous cues more negatively than individuals in a positive state. We demonstrate that the fruit fly, Drosophila melanogaster, also exhibits state-dependent changes in cue interpretation. Drosophila were trained on a Go/Go task to approach a positive (P) odour associated with a sugar reward and actively avoid a negative (N) odour associated with shock. Trained flies were then either shaken to induce a purported negative state or left undisturbed (control), and given a choice between: air or P; air or N; air or ambiguous odour (1:1 blend of P:N). Shaken flies were significantly less likely to approach the ambiguous odour than control flies. This 'judgement bias' may be mediated by changes in neural activity that reflect evolutionarily primitive affective states. We cannot say whether such states are consciously experienced, but utilisation of this model organism's versatile experimental tool kit may facilitate elucidation of their neural and genetic basis.
Data from: Sex-biased gene expression in dioecious garden asparagus (Asparagus officinalis)
Sex chromosomes have evolved independently in phylogenetically diverse flowering plant lineages. The genes governing sex determination in dioecious species remain unknown, but theory predicts that the linkage of genes influencing male and female function will spur the origin and early evolution of sex chromosomes. For example, in an XY system, the origin of an active Y may be spurred by the linkage of female suppressing and male promoting genes. Garden asparagus (Asparagus officinalis) serves as a model for plant sex chromosome evolution, given that it has recently evolved an XX/XY sex chromosome system. In order to elucidate the molecular basis of gender differences and sex determination, we used RNA-sequencing (RNA-Seq) to identify differentially expressed genes between female (XX), male (XY) and supermale (YY) individuals. We identified 570 differentially expressed genes, and showed that significantly more genes exhibited male-biased than female-biased expression in garden asparagus. In the context of anther development, we identified genes involved in pollen microspore and tapetum development that were specifically expressed in males and supermales. Comparative analysis of genes in the Arabidopsis thaliana, Zea mays and Oryza sativa anther development pathways shows that anther sterility in females probably occurs through interruption of tapetum development before microspore meiosis.
Data from: Mate finding, Allee effects, and selection for sex-biased dispersal
Although dispersal requires context-dependent decision-making in three distinct stages (emigration, transit, immigration), these decisions are commonly ignored in simple models of dispersal. For sexually reproducing organisms, mate availability is an important factor in dispersal decisions. Difficulty finding mates can lead to an Allee effect where population growth decreases at low densities. Surprisingly, theoretical studies on mate finding and on sex-biased dispersal produce opposing predictions: in the former one sex is predicted to move less if the other sex evolves to search more, whereas in the latter mate-finding difficulties can select for less sex bias in dispersal when mate finding occurs after dispersal. Here we develop a pair of models to examine the joint evolution of dispersal and settlement behaviour. Our first model resolves the apparent contradiction from the mate-search and dispersal literatures. Our second model demonstrates that the relationship between mating system and sex-biased dispersal is more complex than a simple contrast between resource-defence monogamy and female-defence polygyny. Our results highlight that a key factor is the timing of mating relative to dispersal (before, during, or after). We also show that although movement has the potential to alleviate a mate-finding Allee effect, in some cases it can actually exacerbate the effect.
Data from: Bias and sensitivity in the placement of fossil taxa resulting from interpretations of missing data
The utility of fossils in evolutionary contexts is dependent on their accurate placement in phylogenetic frameworks, yet intrinsic and widespread missing data make this problematic. The complex taphonomic processes occurring during fossilization can make it difficult to distinguish absence from non-preservation, especially in the case of exceptionally preserved soft-tissue fossils: is a particular morphological character (e.g. appendage, tentacle or nerve) missing from a fossil because it was never there (phylogenetic absence), or just happened to not be preserved (taphonomic loss)? Missing data has not been tested in the context of interpretation of non-present anatomy nor in the context of directional shifts and biases in affinity. Here, complete taxa, both simulated and empirical, are subjected to data loss through the replacement of present entries (1s) with either missing (?s) or absent (0s) entries. Both cause taxa to drift down trees, from their original position, toward the root. Absolute thresholds at which downshift is significant are extremely low for introduced absences (2 entries replaced, 6 % of present characters). The opposite threshold in empirical fossil taxa is also found to be low; two absent entries replaced with presences causes fossil taxa to drift up trees. As such, only a few instances of non-preserved characters interpreted as absences will cause fossil organisms to be erroneously interpreted as more primitive than they were in life. This observed sensitivity to coding non-present morphology presents a problem for all evolutionary studies that attempt to use fossils to reconstruct rates of evolution or unlock sequences of morphological change. Stem-ward slippage, whereby fossilization processes cause organisms to appear artificially primitive, appears to be a ubiquitous and problematic phenomenon inherent to missing data, even when no decay biases exist. Absent characters therefore require explicit justification and taphonomic frameworks to support their interpretation.
Data from: Developmental shifts in social cognition: socio-emotional biases across the lifespan in rhesus monkeys
Humans exhibit a suite of developmental changes in social cognition across the lifespan. To what extent are these developmental patterns unique? We first review several social domains in which humans undergo critical ontogenetic changes in socio-cognitive processing, including social attention and theory of mind. We then examine whether one human developmental transition—a shift in socioemotional preferences—also occurs in nonhuman primates. Specifically, we experimentally measured socioemotional processing in a large population of rhesus macaques (Macaca mulatta) ranging from infancy to old age. We tested whether macaques, like humans, also exhibited developmental shifts from a negativity bias at younger ages, indicating preferential attention to negative socioemotional stimuli, to a positivity bias at older ages. We first assessed monkeys' (n = 337) responses to negative socioemotional stimuli by comparing their duration of looking towards photos of negative conspecific signals (threat displays) versus matched neutral expressions. In contrast to the pattern observed in humans, we found that older monkeys were more attentive to negative emotional stimuli than were younger monkeys. In a second study, we used the same method to examine monkeys' (n = 132) attention to positive (affiliative displays) versus matched neutral expressions. Monkeys did not exhibit an overall preference for positive stimuli, nor major age-related changes in their attention. These results indicate that while monkeys show robust ontogenetic shifts in social preferences, they differ from humans by exhibiting an increasing negativity bias with age. Studies of comparative cognitive development can therefore provide insight into the evolutionary origins of human socio-cognitive development.
Data from: The biased evolution of generation time
Many life-history traits are important determinants of the generation time. For instance, semelparous species whose adults reproduce only once have shorter generation times than iteroparous species that reproduce on several occasions – assuming equal development duration. A shorter generation time ensures a higher growth rate in stable environments where resources are in excess, and is therefore a positively selected feature in this situation. In a stable and limiting environment, all combinations of traits that produce the same number of viable offspring are selectively equivalent. Here we study the neutral evolution of life-history strategies with different generation times, and show that the slowest strategy represents the most likely evolutionary out- come when mutation is considered. Indeed, strategies with longer generation times generate fewer mutants per time unit, which makes them less likely to be replaced within a given time period. This 'turnover bias' favors the evolution of strategies with long generation times. Its real impact, however, depends on both the population size and the nature of selection on life-history strategies. The latter is primarily impacted by the relationships between life- history traits whose estimation will be crucial to understand the evolution of life-history strategies.
Data from: Characterization of the genome and transcriptome of the blue tit Cyanistes caeruleus: polymorphisms, sex-biased expression and selection signals
Decoding genomic sequences and determining their variation within populations has potential to reveal adaptive processes and unravel the genetic basis of ecologically relevant trait variation within a species. The blue tit Cyanistes caeruleus – a long-time ecological model species – has been used to investigate fitness consequences of variation in mating and reproductive behaviour. However, very little is known about the underlying genetic changes due to natural and sexual selection in the genome of this songbird. As a step to bridge this gap, we assembled the first draft genome of a single blue tit, mapped the transcriptome of five females and five males to this reference, identified genomewide variants and performed sex-differential expression analysis in the gonads, brain and other tissues. In the gonads, we found a high number of sex-biased genes, and of those, a similar proportion were sex-limited (genes only expressed in one sex) in males and females. However, in the brain, the proportion of female-limited genes within the female-biased gene category (82%) was substantially higher than the proportion of male-limited genes within the male-biased category (6%). This suggests a predominant on-off switching mechanism for the female-limited genes. In addition, most male-biased genes were located on the Z-chromosome, indicating incomplete dosage compensation for the male-biased genes. We called more than 500 000 SNPs from the RNA-seq data. Heterozygote detection in the single reference individual was highly congruent between DNA-seq and RNA-seq calling. Using information from these polymorphisms, we identified potential selection signals in the genome. We list candidate genes which can be used for further sequencing and detailed selection studies, including genes potentially related to meiotic drive evolution. A public genome browser of the blue tit with the described information is available at http://public-genomes-ngs.molgen.mpg.de.
Data from: Two sources of bias explain errors in facial age estimation
Accurate age estimates underpin our everyday social interactions, the provision of age-restricted services and police investigations. Previous work suggests that these judgments are error-prone, but the processes giving rise to these errors are not understood. Here we present the first systematic test of bias in age estimation using a large database of standardized passport images of heterogeneous ages (n = 3948). In three experiments we tested a range of perceiver age groups (n = 84), and found average age estimation error to be approximately 8 years. We show that this error can be attributed to two separable sources of bias. First, and accounting for the vast majority of variance, our results show an assimilative serial dependency whereby estimates are systematically biased towards the age of the preceding face. Second, younger faces are generally perceived to be older than they are, and older faces to be younger. In combination, these biases account for around 95% of variance in age estimates. We conclude that that perception of age is modulated by representations that encode both a viewer's recent and normative exposure to faces. The finding that age perception is subject to strong top-down influences based on our immediate experience has implications for our understanding of perceptual processes involved in face perception, and for improving accuracy of age estimation in important real world tasks.
Is GPT-4 Less Politically Biased than GPT-3.5? A Renewed Investigation of ChatGPT's Political Biases
Open the record for dataset details and reuse information.
Effects of Parametric Uncertainty on ITCZ Precipitation: Understanding the Role of Interactions between Parameters in Reducing the Double ITCZ Bias
<p>Data used to draw figures in the manuscript.</p>
Supplementary material 3 from: Hsieh Y-C, Huang JC-C, Yeh W-C, Tsai C-Y, Lin C-J, Lu S-S (2023) Male-biased night foraging by bumblebees (Hymenoptera, Apidae, Bombus spp.) in Taiwan. Journal of Hymenoptera Research 96: 949-954. https://doi.org/10.3897/jhr.96.113486
A bumblebee worker licking unopened flowers of Ligustrum pricei
Supplementary material 1 from: Hsieh Y-C, Huang JC-C, Yeh W-C, Tsai C-Y, Lin C-J, Lu S-S (2023) Male-biased night foraging by bumblebees (Hymenoptera, Apidae, Bombus spp.) in Taiwan. Journal of Hymenoptera Research 96: 949-954. https://doi.org/10.3897/jhr.96.113486
Identification keys to bumblebee species of the Fushan area
Supplementary material 2 from: Hsieh Y-C, Huang JC-C, Yeh W-C, Tsai C-Y, Lin C-J, Lu S-S (2023) Male-biased night foraging by bumblebees (Hymenoptera, Apidae, Bombus spp.) in Taiwan. Journal of Hymenoptera Research 96: 949-954. https://doi.org/10.3897/jhr.96.113486
Behavior of a male bumblebee on the inflorescences of Ligustrum pricei at night
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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