Biology subjects

Neves, K.

Publications and source records attributed to Neves, K..

7 recordsLinked to original sources

bioRxiv2025

Weak and inverse latitudinal diversity gradients in the 10 most abundant and diverse flying insect clades

Latitudinal diversity gradients are a key concept in biodiversity science, but the available data are skewed towards large-bodied, charismatic taxa. To address this bias, we analyzed DNA barcode data for 1.35 million specimens of flying insects collected using 101 Malaise traps in 27 countries across six continents. We identify those ten families that consistently contribute more than half of all specimens and species across climates, habitats, and continents. Contrary to canonical expectations, five families have inverse or non-significant latitudinal gradients while the remaining five exhibit only weak to average gradients compared to 470 other terrestrial datasets. Furthermore, precipitation seasonality, rather than temperature, emerged as the strongest climatic correlate. Overall, we thus not only reveal a surprising convergence in the globally dominant insect clades but also illustrate that key textbook concepts in macroecology need testing for poorly studied invertebrate taxa that contribute most of Earths animal biodiversity and may behave unexpectedly.

ecology↗

bioRxiv2025

Estimating the replicability of Brazilian biomedical science

Concerns over the replicability and reproducibility of published research have grown in many research fields, but empirical data to inform policies are still scarce. Biomedical research in Brazil expanded rapidly over the last three decades, with no systematic assessment of the replicability of its findings. With this in mind, we set up the Brazilian Reproducibility Initiative, a multicenter replication of published experiments from Brazilian science using three common experimental methods: the MTT assay, the reverse transcription polymerase chain reaction (RT-PCR) and the elevated plus maze (EPM). A total of 56 laboratories performed 143 replications of 56 experiments; of these, 90 replications of 45 experiments were considered valid by an independent committee. Replication rates for these experiments varied between 20 and 44% according to five predefined criteria. In median terms, ratios between group means were 58% lower in replications than in original experiments, while coefficients of variation were 82% higher. Effect size decrease was smaller for MTT experiments, original results with less variability and those considered more challenging to replicate, while t values for replications were positively correlated with researcher predictions about replicability, and negatively correlated with the rate of publications by the original articles last author. Deviations from preregistered protocols were very common in replications, most frequently due to reasons inherent to the experimental model or related to infrastructure and logistics. Our results highlight factors that limit the replicability of results published by researchers in Brazil and suggest ways by which this scenario can be improved.

scientific communication and education↗

bioRxiv2024

Evaluating UCE data adequacy and integrating uncertainty in a comprehensive phylogeny of ants

While some relationships in phylogenomic studies have remained stable since the era of Sanger sequencing, many challenging nodes elude resolution, even with genome-scale data. As early studies grappled with random error and insufficient information, incongruence or lack of resolution in phylogenomics is generally associated with inadequate modeling of biological phenomena combined with analytical issues leading to systematic biases. Few phylogenomic studies, however, explore the potential for random error or establish an expectation of what level of resolution should be expected from a given empirical dataset. In presenting incongruent results, phylogeneticists face a choice of providing a diverse array of results from different approaches or a single preferred tree, with few attempting to integrate uncertainties across methods. Recent phylogenetic work has uncovered many well-supported and often novel relationships, as well as more contentious findings, across the phylogeny of ants. Ants are the most species-rich lineage of social insects and among the most ecologically important terrestrial animals. As a result, they have attracted much research, including regarding systematics. To date, however, there has been no comprehensive genus-level phylogeny of the ants inferred using genomic data combined with an effort to evaluate signal and incongruence throughout. Here we provide deeper insight into and quantify uncertainty across the ant tree of life. We accomplish this with the most taxonomically comprehensive Ultraconserved Elements dataset to date, including 277 (81%) of recognized ant genera from all 16 extant subfamilies, representing over 98% of described species-level diversity. We use simulations to establish expectations for resolution, identify branches with less-than-expected concordance, and dissect the effects of data and model selection on recalcitrant nodes. We also construct a consensus tree integrating uncertainty from multiple analyses. Simulations show that hundreds of loci are needed to resolve recalcitrant nodes on our genus-level ant phylogeny, even under a best-case scenario of known model parameters and without systematic bias. This demonstrates that random error continues to play a role in phylogenomics. Our analyses provide a comprehensive picture of support and incongruence across the ant phylogeny, and our consensus topology is congruent with a recent phylogenomic study on the subfamily-level, while rendering a more realistic picture of uncertainty and significantly expanding generic sampling. We use this topology for divergence dating and find that assumptions about root age have significant impact on the dates inferred. Our results suggest that improved understanding of ant phylogeny will require both more data and better phylogenetic models. We also provide a workflow to identify under-supported nodes in concatenation analyses, outline a pragmatic way to reconcile conflicting results in phylogenomics, and introduce a user-friendly locus selection tool for divergence dating.

evolutionary biology↗

bioRxiv2022

Mapping the content of comments on bioRxiv and medRxiv preprints

IntroductionPreprints have been increasingly used in biomedical sciences, providing the opportunity for research to be publicly assessed before journal publication. With the increase in attention over preprints during the COVID-19 pandemic, we decided to assess the content of comments left on preprint platforms. MethodsPreprints posted on bioRxiv and medRxiv in 2020 were accessed through each platforms API, and a random sample of preprints that had received between 1 and 20 comments was analyzed. Comments were evaluated in triplicate by independent evaluators using an instrument that assessed their features and general content. Results7.3% of preprints received at least 1 comment during a mean follow-up of 7.5 months. Analyzed comments had a median size of 43 words. Criticisms, corrections or suggestions were the most prevalent type of content, followed by compliments or positive appraisals and questions. Most critical comments regarded interpretation, data collection and methodological design, while compliments were usually about relevance and implications. ConclusionsOnly a small percentage of preprints posted in 2020 in bioRxiv and medRxiv received comments in these platforms. When present, however, these comments address content that is similar to that analyzed by traditional peer review. A more precise taxonomy of peer review functions would be desirable to describe whether post-publication peer review fulfills these roles.

scientific communication and education↗

bioRxiv2019

The reliability of the isotropic fractionator method for counting total cells and neurons

BackgroundThe Isotropic Fractionator (IF) is a method used to determine the cellular composition of nervous tissue. It has been mostly applied to assess variation across species, where differences are expected to be large enough not to be masked by methodological error. However, understanding the sources of variation in the method is important if the goal is to detect smaller differences, for example, in same-species comparisons. Comparisons between different mice strains suggest that the IF is consistent enough to detected these differences. Nevertheless, the internal validity of the method has not yet been examined directly.\n\nMethodIn this study, we evaluate the reliability of the IF method for the determination of cellular and neuronal numbers. We performed repeated cell counts of the same material by different experimenters to quantify different sources of variation.\n\nResultsIn total cell counts, we observed that for the cerebral cortex most of the variance was at the counter level. For the cerebellum, most of the variance is attributed to the sample itself. As for neurons, random error along with the immunological staining correspond to most of the variation, both in the cerebral cortex and in the cerebellum. Test-retest reliability coefficients were relatively high, especially for cell counts.\n\nConclusionsAlthough biases between counters and random variation in staining could be problematic when aggregating data from different sources, we offer practical suggestions to improve the reliability of the method. While small, this study is a most needed step towards more precise measurement of the brains cellular composition.\n\nHighlightsO_LIMost variance in cell counts was between counters ({eta} = 0.58) for cerebral cortices.\nC_LIO_LIFor cerebella, most of the variance was attributed to the samples ({eta} = 0.49).\nC_LIO_LIVariance in immunocytochemical counts was mostly residual/random ({eta} > 0.8).\nC_LIO_LITest-retest reliability was high (same counter, same sample).\nC_LIO_LIPractical suggestions are offered to improve the reliability of the method.\nC_LI

neuroscience↗

bioRxiv2018

Lack of correlation between number of neurons and behavioral performance in Swiss mice

Neuronal number varies by several orders of magnitude across species, and has been proposed to predict cognitive capability across species. Remarkably, numbers of neurons vary across individual mice by a factor of 2 or more. We directly addressed the question of whether there is a relationship between performance in behavioral tests and the number of neurons in functionally relevant structures in the mouse brain. Naive Swiss mice went through a battery of behavioral tasks designed to measure cognitive, motor and olfactory skills. We estimated the number of neurons in different brain regions (cerebral cortex, hippocampus, olfactory bulb, cerebellum and remaining areas) and crossed the two datasets to test the a priori hypothesis of correlation between cognitive abilities and numbers of neurons. As previous evidence indicates that environmental enrichment may increase neurogenesis and improve neuronal survival, we added a control group that did not undergo cognitive testing to rule out the possibility that our test battery could alter the neuronal number. We found that behavioral testing did not change numbers of neurons in the cerebral cortex and in the hippocampus. Surprisingly, performance in the behavioral tasks did not correlate strongly with number of neurons in any of the brain regions studied. Our results show that whereas neuronal number is a good predictor of cognitive skills across species, it is not a predictor of cognitive, sensory or motor ability across individuals within a species, which suggests that other factors are more relevant for explaining cognitive differences between individuals of the same species.

neuroscience↗

bioRxiv2017

How Many Females Are There? Cheating and Female Dispersion Can Explain Mating Behavior Evolution

Only around 3% of all mammalian species are socially monogamous and the conditions that favor the evolution of this mating system in mammals are not well understood. With several approaches, studies have proposed different hypotheses relating female dispersion and infanticide as drivers for the evolution of social monogamy. Here, we used an agent-based model, that allowed us to examine how different mating behaviors affect populations in a controlled computational environment. We found that the evolution of social monogamy does not rely on a single factor. Rather, our experimental results support an interplay of different factors in the evolution of social monogamy - female dispersion and availability and breeding season duration - and suggests that polygamy will only evolve in populations with a female-biased operational sex ratio or one where cheating is common. These results can explain why social monogamy is so uncommon in mammals and points to new lines for ethological investigation of mammalian behavior.

ecology↗