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1,066 results for “bayesian”
Bayesian stable isotope mixing models effectively characterize the diet of an Arctic raptor
<p>1. Bayesian stable isotope mixing models (BSIMMs) for δ13C and δ15N can be a useful tool to reconstruct diets, characterize trophic relationships, and assess spatiotemporal variation in food webs. However, use of this approach typically requires a priori knowledge on the level of enrichment occurring between the diet and tissue of the consumer being sampled (i.e., a trophic discrimination factor or TDF).</p> <p>2. TDFs derived from captive feeding studies are highly variable, and it is challenging to select the appropriate TDF for diet estimation in wild populations. We introduce a novel method for estimating TDFs in a wild population: a proportionally balanced equation that uses high-precision diet estimates from nest cameras installed on a subset of nests in lieu of a controlled feeding study (TDFCAM).</p> <p>3. We tested the ability of BSIMMs to characterize diet in a free-living population of gyrfalcon (Falco rusticolus) nestlings by comparing model output to high-precision nest camera diet estimates. We analyzed the performance of models formulated with a TDFCAM against other relevant TDFs and assessed model sensitivity to an informative prior. We applied the most parsimonious model inputs to a larger sample to analyze broad-scale temporal dietary trends.</p> <p>4. BSIMMs fitted with a TDFCAM and uninformative prior had the best agreement with nest camera data, outperforming TDFs derived from captive feeding studies. BSIMMs produced with a TDFCAM produced reliable diet estimates at the nest level and accurately identified significant temporal shifts in gyrfalcon diet within and between years.</p> <p>5. Our method of TDF estimation produced more accurate estimates of TDFs in a wild population than traditional approaches, consequently improving BSIMM diet estimates. We demonstrate how BSIMMs can complement a high-precision diet study by expanding its spatiotemporal scope of inference and recommend this integrative methodology as a powerful tool for future trophic studies. </p>
Evaluating Bayesian stable isotope mixing models of wild animal diet and the effects of trophic discrimination factors and informative priors
<blockquote> <p>1. Ecologists quantify animal diets using direct and indirect methods, including analysis of faeces, pellets, prey items and gut contents. For stable isotope analyses of diet, Bayesian stable isotope mixing models (BSIMMs) are increasingly used to infer the relative importance of food sources to consumers. Although a powerful approach, it has been hard to test BSIMM performance for wild animals because precise, direct dietary data are difficult to collect.<br> 2. We evaluated the performance of BSIMMs in quantifying animal diets when using δ13C and δ15N stable isotope ratios from the feathers and red blood cells of common buzzard Buteo buteo chicks. We analysed mixing model outcomes with various trophic discrimination factors (TDFs), with and without informative priors, and compared these to direct observations of prey provisioned to chicks by adults at nests, using remote cameras. <br> 3. Although BSIMMs with different TDFs varied markedly in their performance, the statistical package SIDER generated TDFs for both feathers and blood that resulted in model outputs that accorded well with direct observations of prey provisioning. Using feather TDFs derived from captive peregrines Falco peregrinus resulted in estimates of diet composition that were also similar to provisioned prey, though blood TDFs from the same study performed poorly. The inclusion of informative priors, based on conventional analysis of pellet and prey remains, markedly reduced model performance.<br> 4. BSIMMs can provide accurate assessments of diet in wild animals. TDF estimates from the SIDER package performed well. The inclusion of informative priors from conventional methods in Bayesian mixing models can transfer biases into model outcomes, leading to erroneous results.</p> </blockquote>
Data for "Bayesian inference of mantle viscosity from whole-mantle density models"
<p><strong>Supplementary Data</strong><br> Rudolph, M.L., Moulik, P., and Lekic, V. (2020). Bayesian inference of mantle viscosity from whole-mantle density models. Geochemistry, Geophysics, Geosystems</p> <p>This data archive contains files needed to reproduce the figures from our 2020 G-Cubed paper, including the full ensemble solutions for mantle viscosity structure.</p>
FIGURE 25. Bayesian 50 in Notes on genera of Sarimini with description of two new species in the genera Microsarimodes and Tetrichina (Hemiptera: Fulgoromorpha: Issidae)
FIGURE 25. Bayesian 50% consensus tree of Sarimini based on combined genes of 18S rDNA, 28S rDNA, COI and Cytb using Issini (Issus coleoptratus), Parahiraciini (Fortunia sp.) and Hemisphaeriini (Hemisphaerius coccinelloides) as outgroups. The names 'Gen. nov.', 'Eusarima sp. 1', and 'sp. 4' refer to the same taxa as in Wang et al. (2016). Posterior probability support value is provided at each node.
FIGURE 20. Majority-rule consensus tree from Bayesian analysis using 16S in Revision of the French Polycirridae (Annelida, Terebelliformia), with descriptions of eight new species
FIGURE 20. Majority-rule consensus tree from Bayesian analysis using 16S. Asterisks indicate posterior probability> 90 %. Text in red refers to specimens sequenced during this study.
Data from: Association between metabolic syndrome components and the risk of developing nephrolithiasis: Bayesian meta-analysis and meta-regression with dose-response analysis
<p>Nephrolithiasis has shifted to be a systemic disease. As opposed to an isolated urinary metabolic problem, it became determined that nephrolithiasis turned into considerably related to link with systemic diseases such as hypertension, obesity, dyslipidemia, and insulin resistance. The interplay between these four factors defines MetS (metabolic syndrome). In this review we aim to clarify the associations of metabolic syndrome and its components to kidney stone incident. Online databases of EMBASE, MEDLINE, and Google Scholar were searched up to October 2020 to identify observational studies examining the association between metabolic syndrome components and kidney stone incident. Bayesian Random-Effects Meta-Analysis and Meta-Regression were performed to observe the association. Linear dose-response analyses were conducted to shape the direction of the association. Data analysis was performed using STATA, and R statistics. This dataset contains supplementary material and figures as additional analysis of the study.</p>
Measurement of the B-band Galaxy Luminosity Function with Approximate Bayesian Computation
<p>In our recent paper Tortorelli et al. 2020 (arXiv: 2001.07727), we presented the first measurement in literature of galaxy population properties using the Approximate Bayesian Computation (ABC), specifically the B-band Galaxy Luminosity function. The novel methodology we developed that combines forward-modeling and ABC offers excellent prospects to robustly measure galaxy population properties as a function of redshift in large wide-field galaxy surveys, such as LSST and NGRST. The methodology has the advantage of overcoming part of the limitations that arise in wide-field galaxy studies, such as incorrect redshift estimation or separation of galaxies into red and blue. We forward model wide-field broad-band galaxy surveys using the fast image simulator UFig. We use ABC to constrain the galaxy population model parameters of the simulations and match data from the CFHTLS. We define a number of distance metrics between the simulated and the survey data. By exploring the parameter space of the galaxy population model through ABC to find the set of parameters that minimize these distance metrics, we obtain constraints on the LFs of blue and red galaxies as a function of redshift. We compare our results to other measurements, finding good agreement at all redshifts, for both blue and red galaxies. We also compare the redshift distribution we obtain applying the same cuts as the VIPERS survey on our image simulations, finding good agreement with survey data.</p>
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals
Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs' distributions and to analyze whether their distributions have shifted along with environmental changes. Location: Arctic shelf area. The Kara Sea. Methods: Our literature search focused on survey data regarding polar bears (Ursus maritimus), Atlantic walruses (Odobenus rosmarus rosmarus) and ringed seals (Phoca hispida). We mapped the data on a grid and built a hierarchical Poisson point process model to analyze species' densities. The heterogeneous data lacked information on survey intensity and we could model only the relative density of each species. We explained relative densities with environmental covariates and random effects reflecting excess spatiotemporal variation and the unknown, varying sampling effort. The relative density of polar bears was explained also by the relative density of seals. Results: The most important covariates explaining AMMs' relative densities were ice concentration and distance to the coast, and regarding polar bears, also the relative density of seals. The results suggest that due to the decrease in the average ice concentration, the relative densities of polar bears and walruses slightly decreased or stayed constant during the 17-yearlong study period, whereas seals shifted their distribution from the Eastern to the Western Kara Sea. Main conclusions: Point process modelling is a robust methodology to estimate distributions from heterogeneous observations, providing spatially explicit information about ecosystems and thus serves advances for conservation efforts in the Arctic. In a simple trophic system, a distribution model of a top predator benefits from utilizing prey species' distributions compared to a solely environmental model. The decreasing ice cover seems to have led to changes in AMMs' distributions in the marginal Arctic region.
Data from: A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error
Stakeholder support is vital for achieving conservation success, yet there are few reliable mechanisms to monitor stakeholder attitudes towards conservation. Importantly, few approaches account for bias arising from reporting errors; that is, reporting a positive attitude towards conservation when the respondent actually does not have one (a false positive error), or not reporting a positive attitude when the respondent is positive towards conservation (a false negative error). We borrow from developments in applied conservation science to use a Bayesian hierarchical model to quantify stakeholder attitudes as the probability of having a positive attitude towards wildlife, notionally (or in abstract terms) and at localized scales. The model allows us to assess stakeholder attitudes, and factors influencing these attitudes, while accounting for false negative and false positive reporting errors. We show through simulations that this method has lower bias than naïve estimates of the proportion of respondents who are positive towards wildlife, or Likert‐scores. We demonstrate the utility of the model by applying it to questionnaire surveys on Asian elephants Elephas maximus in the Kaziranga–Karbi Anglong landscape, Northeast India. After accounting for reporting errors, we estimated the probability of being positive towards elephants notionally as 0.85; at a localized scale, however, the proportion of respondents that were positive towards elephants was 50%. In comparison, without accounting for reporting errors, the proportion of respondents professing positive attitudes towards elephants in at least one of the certain questions, was 0.69 and 0.23, notionally and at local scales, respectively. False (positive and negative) reporting probabilities were consistently non‐zero (0.22–0.68). We submit that regular and reliable assessment of stakeholder attitudes––combined with an understanding of factors contributing to variation in attitudes––can feed into participatory conservation monitoring programs, help assess the success of initiatives aimed at facilitating human behavioral change, and inform conservation decision‐making.
Data from: Multilocus phylogeny and Bayesian estimates of species boundaries reveal hidden evolutionary relationships and cryptic diversity in Southeast Asian monitor lizards
Recent conceptual, technological, and methodological advances in phylogenetics have enabled increasingly robust statistical species delimitation in studies of biodiversity. As the variety of evidence purporting species diversity has increased, so too have the kinds of tools and inferential power of methods for delimiting species. Here we showcase an organismal system for a data-rich, comparative molecular approach to evaluating strategies of species delimitation among monitor lizards of the genus Varanus. The water monitors (Varanus salvator Complex), a widespread group distributed throughout Southeast Asia and southern India, have been the subject of numerous taxonomic treatments, which have drawn recent attention due to the possibility of undocumented species diversity. To date, studies of this group have relied on purportedly diagnostic morphological characters, with no attention given to the genetic underpinnings of species diversity. Using a 5-gene dataset, we estimated phylogeny and used multilocus genetic networks, analysis of population structure, and a Bayesian coalescent approach to infer species boundaries. Our results contradict previous systematic hypotheses, reveal surprising relationships between island and mainland lineages, and uncover novel, cryptic evolutionary lineages (i.e. new putative species). Our study contributes to a growing body of literature suggesting that, used in concert with other sources of data (e.g., morphology, ecology, biogeography), multilocus genetic data can be highly informative to systematists and biodiversity specialists when attempting to estimate species diversity and identify conservation priorities. We recommend holding in abeyance taxonomic decisions until multiple, converging lines of evidence are available to best inform taxonomists, evolutionary biologists, and conservationists.
Data from: Bayesian clustering analyses for genetic assignment and study of hybridization in oaks: effects of asymmetric phylogenies and asymmetric sampling schemes
Bayesian clustering methods have been widely used for studying species delimitation and genetic introgression. In order to test the effect of phylogenetic relationships and sampling scheme on the inferred clustering solution and on the performance of Bayesian clustering analysis, I simulated genotypes of the interfertile oak species Quercus robur, Quercus petraea, and Quercus pubescens and I run analyses using two popular software programs, STRUCTURE and BAPS. First, based on purebred simulations, I compared clustering solutions resulting from different sample size configurations. While clustering solution generally reflected the taxonomic relationships when equal samples of each species were included, spurious partition was inferred by STRUCTURE when some species were represented by larger and others by smaller samples. In very unbalanced configurations, STRUCTURE failed to identify the three species, even if three subpopulations were assumed. By contrast, BAPS could properly identify the three species under any sampling scheme. Second, based on simulations of purebreds and hybrids, I tested the performance of individual assignments with variable number of loci. This analysis showed that STRUCTURE can detect introgressed individuals more efficiently than BAPS. However, BAPS could assign purebreds more efficiently with a lower number of loci. Method performance also depended on phylogenetic relationships. In the case of Q. petraea, Q. pubescens, and their hybrids, method performance was lower due to their phylogenetic affinity. Inclusion of three instead of two species into the analysis led to reduction of performance, and to misclassification of hybrids, which often reflected the phylogenetic affinity between Q. petraea and Q. pubescens.
Data from: Exact Bayesian inference for animal movement in continuous time
It is natural to regard most animal movement as a continuous-time process, generally observed at discrete times. Most existing statistical methods for movement data ignore this; the remainder mostly use discrete-time approximations, the statistical properties of which have not been widely studied, or are limited to special cases. We aim to facilitate wider use of continuous-time modelling for realistic problems. We develop novel methodology which allows exact Bayesian statistical analysis for a rich class of movement models with behavioural switching in continuous time, without any need for time discretization error. We represent the times of changes in behaviour as forming a thinned Poisson process, allowing exact simulation and Markov chain Monte Carlo inference. The methodology applies to data that are regular or irregular in time, with or without missing values. We apply these methods to GPS data from two animals, a fisher (Pekania [Martes] pennanti) and a wild boar (Sus scrofa), using models with both spatial and temporal heterogeneity. We are able to identify and describe differences in movement behaviour across habitats and over time. Our methods allow exact fitting of realistically complex movement models, incorporating environmental information. They also provide an essential point of reference for evaluating other existing and future approximate methods for continuous-time inference.
Data from: Movement of a Heliconius hybrid zone over 30 years: a Bayesian approach
Hybrid zones have long been of interest to biologists as natural laboratories where we can gain insight into the processes of adaptation and speciation. Repeated sampling of individual hybrid zones has been particularly useful in elucidating the dynamic balance between selection and dispersal that maintains most hybrid zones. Here, we revisit a hybrid zone between Heliconius erato butterflies in Panamá for a third time over more than 30 years. We combine a novel Bayesian extension of stepped‐cline hybrid zone models with environmental data to understand the genetic and environmental causes of cline dynamics in this species. The cline has continued to move west, likely due to dominance drive, but has slowed and broadened. Environmental analyses suggest that widespread deforestation in Panamá could be leading to decreased avian predation and relaxed selection, causing the observed changes in cline dynamics.
Data from: ClonEstiMate, a Bayesian method for quantifying rates of clonality of populations genotyped at two-time steps
Partial clonality is commonly used in Eukaryotes and has large consequences for their evolution and ecology. Assessing accurately the relative importance of clonal versus sexual reproduction matters for studying and managing such species. Here, we proposed a Bayesian approach, ClonEstiMate, to infer rates of clonality c from populations sampled twice over a short time interval, ideally one generation time. The method relies on the likelihood of the transitions between genotype frequencies of ancestral and descendent populations, using an extended Wright-Fisher model explicitly integrating reproductive modes. Our model provides posterior probability distribution of inferred c, given the assumed rates of mutation, as well as inbreeding and selfing when occurring. Tested under various conditions, this model provided accurate inferences of c, especially when the amount of information was modest, i.e. low sample sizes, few loci, low polymorphism and strong linkage disequilibrium. Inferences remained robust when mutation models and rates were misinformed. However, the method was sensitive to moderate frequencies of null alleles and when the time interval between required samplings exceeding two generations. Misinformed rates on mating modes (inbreeding and selfing) also resulted in biased inferences. Our method was tested on eleven datasets covering five partially clonal species, for which the extent of clonality was formerly deciphered. It delivered highly consistent results with previous information on the biology of those species. ClonEstiMate represents a powerful tool for detecting and inferring clonality in finite populations, genotyped with SNPs or microsatellites. It is freely available at http://https://w">https://w w w 6.rennes.inra.fr / igepp_eng/ Productions/ Software.
Data from: Using parsimony-guided tree proposals to accelerate convergence in Bayesian phylogenetic inference
<p>Sampling across tree space is one of the major challenges in Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) algorithms. Standard MCMC tree moves consider small random perturbations of the topology, and select from candidate trees at random or based on the distance between the old and new topologies. MCMC algorithms using such moves tend to get trapped in tree space, making them slow in finding the globally most probable trees (known as `convergence') and in estimating the correct proportions of the different types of them (known as `mixing'). Here, we introduce a new class of moves, which propose trees based on their parsimony scores. The proposal distribution derived from the parsimony scores is a quickly computable albeit rough approximation of the conditional posterior distribution over candidate trees. We demonstrate with simulations that parsimony-guided moves correctly sample the uniform distribution of topologies from the prior. We then evaluate their performance against standard moves using six challenging empirical datasets, for which we were able to obtain accurate reference estimates of the posterior using long MCMC runs, a mix of topology proposals, and Metropolis coupling. On these datasets, ranging in size from 357 to 934 taxa and from 1,740 to 5,681 sites, we find that single chains using parsimony-guided moves usually converge an order of magnitude faster than chains using standard moves. They also exhibit better mixing, that is, they cover the most probable trees more quickly. Our results show that tree moves based on quick and dirty estimates of the posterior probability can significantly outperform standard moves. Future research will have to show to what extent the performance of such moves can be improved further by finding better ways of approximating the posterior probability, taking the trade-off between accuracy and speed into account.</p>
Data from: Reconstructing the demographic history of orang-utans using approximate Bayesian computation
Investigating how different evolutionary forces have shaped patterns of DNA variation within and among species requires detailed knowledge of their demographic history. Orang-utans, whose distribution is currently restricted to the Southeast Asian islands of Borneo (Pongo pygmaeus) and Sumatra (Pongo abelii), have likely experienced a complex demographic history, influenced by recurrent changes in climate and sea levels, volcanic activities and anthropogenic pressures. Using the most extensive sample set of wild orang-utans to date, we employed an approximate Bayesian computation (ABC) approach to test the fit of 12 different demographic scenarios to the observed patterns of variation in autosomal, X-chromosomal, mitochondrial and Y-chromosomal markers. In the best-fitting model, Sumatran orang-utans exhibit a deep split of populations north and south of Lake Toba, probably caused by multiple eruptions of the Toba volcano. In addition, we found signals for a strong decline in all Sumatran populations ~24 ka, probably associated with hunting by human colonizers. In contrast, Bornean orang-utans experienced a severe bottleneck ~135 ka, followed by a population expansion and substructuring starting ~82 ka, which we link to an expansion from a glacial refugium. Therefore, we showed that orang-utans went through drastic changes in population size and connectedness, caused by the recurrent contraction and expansion of rainforest habitat during Pleistocene glaciations, and probably also by the impact of hunting by early humans. Our findings also emphasize the fact that important aspects of the evolutionary past of species with complex demographic histories might remain obscured when applying overly simplified models.
Data from: Phylogeny, macroevolutionary trends and historical biogeography of sloths: insights from a Bayesian morphological clock analysis
Sloths, like other xenarthrans, are an extremely interesting group of mammals that, after a long history of evolution and diversification in South America, became established on islands in the Caribbean and later reached North America during the Great American Biotic Interchange. In all three regions they were part of the impressive Pleistocene megafauna. Most taxa became extinct and only two small, distantly related tree-dwelling genera survived. Here we incorporate several recently described genera of sloths into an assembled morphological data supermatrix and apply Bayesian inference, using phylogenetic and morphological clock methods, to 64 sloth genera. Thus, we investigate the evolution of the group in terms of the timing of divergence of different lineages and their diversity, morphological disparity and biogeographical history. The phylogeny obtained supports the existence of the commonly recognized clades for the group. Our results provide divergence time estimates for the major clades within Folivora that could not be dated with molecular methods. Lineage diversity shows an early increase, reaching a peak in the Early Miocene followed by a major drop at the end of the Santacrucian (Early Miocene). A second peak in the Late Miocene was also followed by a major drop at the end of the Huayquerian (Late Miocene). Both events show differential impact at the family level. After that, a slight Plio-Pleistocene decline was observed before the marked drop with the extinction at the end of the Pleistocene. Phenotypic evolutionary rates were high during the early history of the clade, mainly associated with Mylodontidae, but rapidly decreased to lower values around 25 Ma, whereas Megalonychidae have lower values at the beginning followed by a steady increase, peaking during the Late Miocene and the Pliocene. Morphological disparity showed a similar trend, with an early increase, followed by a slowly increasing phase through the Late Oligocene and Early Miocene, and ending with another increase beginning at the middle of the Miocene. Biogeographic analysis showed southern South America as the most probable area of origin of the clade and the main region in which the early diversification events took place. Both Megatheriinae and Nothrotheriinae basal nodes were strongly correlated with Andean uplift events, whereas the early history of Mylodontidae is closely associated with southern South America and also shows an early occupation of the northern regions. Within Megalonychidae, our results show Choloepus as a descendant of an island dispersing ancestor and a probable re-ingression to South America by a clade that originated in Central or North America.
Data from: Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates
We propose a two-step procedure for estimating multiple migration rates in an approximate Bayesian computation (ABC) framework, accounting for global nuisance parameters. The approach is not limited to migration, but generally of interest for inference problems with multiple parameters and a modular structure (e.g. independent sets of demes or loci). We condition on a known, but complex demographic model of a spatially subdivided population, motivated by the reintroduction of Alpine ibex (Capra ibex) into Switzerland. In the first step, the global parameters ancestral mutation rate and male mating skew have been estimated for the whole population in Aeschbacher et al. (Genetics 2012; 192: 1027). In the second step, we estimate in this study the migration rates independently for clusters of demes putatively connected by migration. For large clusters (many migration rates), ABC faces the problem of too many summary statistics. We therefore assess by simulation if estimation per pair of demes is a valid alternative. We find that the trade-off between reduced dimensionality for the pairwise estimation on the one hand and lower accuracy due to the assumption of pairwise independence on the other depends on the number of migration rates to be inferred: the accuracy of the pairwise approach increases with the number of parameters, relative to the joint estimation approach. To distinguish between low and zero migration, we perform ABC-type model comparison between a model with migration and one without. Applying the approach to microsatellite data from Alpine ibex, we find no evidence for substantial gene flow via migration, except for one pair of demes in one direction.
Data from: Phylogeographic inference using Bayesian model comparison across a fragmented chorus frog species complex
Fragmented species complexes provide an interesting system for investigating biogeographic history and the present distribution of genetic variation. Recent advances in sequencing technology and statistical phylogeography enable the collection and rigorous analysis of large multilocus data sets, but designing studies that produce meaningful phylogeographic inferences remains challenging. We implemented a Bayesian model comparison approach to investigate previous biogeographic hypotheses while simultaneously inferring the presence of genetic structure in a chorus frog species complex. The Illinois chorus frog (Pseudacris illinoensis), originally described as a subspecies of the broadly distributed Strecker's chorus frog (Pseudacris streckeri), occurs in small, disjunct regions associated with scarce sand prairie habitats that have been impacted by human development. We used high-throughput sequencing to develop and collect a multitiered genetic data set comprised of three different marker types (23 anonymous nuclear sequence loci, four mitochondrial genes and 14 microsatellite loci) designed to address questions across different evolutionary timescales. Phylogenetic analyses uncovered a deep divergence between populations in the Edwards Plateau of central Texas and all other P. streckeri/P. illinoensis populations, but suggest the disjunct distribution of P. illinoensis occurred more recently. Our best-supported migration model is consistent with the hypothesis that central Texas represented a refugium from which populations expanded via multiple routes. This model also indicates that disjunct northern and southern regions of P. illinoensis should be considered genetically distinct management units. Our study provides an evolutionary context for future studies and conservation efforts in P. illinoensis and demonstrates the utility of model-based approaches for phylogeographic inference.
Data from: Empirical and Bayesian approaches to fossil-only divergence times: a study across three reptile clades
Estimating divergence times on phylogenies is critical in paleontological and neontological studies. Chronostratigraphically-constrained fossils are the only direct evidence of absolute timing of species divergence. Strict temporal calibration of fossil-only phylogenies provides minimum divergence estimates, and various methods have been proposed to estimate divergences beyond these minimum values. We explore the utility of simultaneous estimation of tree topology and divergence times using BEAST tip-dating on datasets consisting only of fossils by using relaxed morphological clocks and birth-death tree priors that include serial sampling (BDSS) at a constant rate through time. We compare BEAST results to those from the traditional maximum parsimony (MP) and undated Bayesian inference (BI) methods. Three overlapping datasets were used that span 250 million years of archosauromorph evolution leading to crocodylians. The first dataset focuses on early Sauria (31 taxa, 240 chars.), the second on early Archosauria (76 taxa, 400 chars.) and the third on Crocodyliformes (101 taxa, 340 chars.). For each dataset three time-calibrated trees (timetrees) were calculated: a minimum-age timetree with node ages based on earliest occurrences in the fossil record; a 'smoothed' timetree using a range of time added to the root that is then averaged over zero-length internodes; and a tip-dated timetree. Comparisons within datasets show that the smoothed and tip-dated timetrees provide similar estimates. Only near the root node do BEAST estimates fall outside the smoothed timetree range. The BEAST model is not able to overcome limited sampling to correctly estimate divergences considerably older than sampled fossil occurrence dates. Conversely, the smoothed timetrees consistently provide node-ages far older than the strict dates or BEAST estimates for morphologically conservative sister-taxa when they sit on long ghost lineages. In this latter case, the relaxed-clock model appears to be correctly moderating the node-age estimate based on the limited morphological divergence. Topologies are generally similar across analyses, but BEAST trees for crocodyliforms differ when clades are deeply nested but contain very old taxa. It appears that the constant-rate sampling assumption of the BDSS tree prior influences topology inference by disfavoring long, unsampled branches.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.