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43 results for “rate heterogeneity”
Machine learning predicts earthquakes in the continuum model of a rate-and-state fault with frictional heterogeneities
<p>Numerical data used to make Figures in the manuscript entitled "Machine learning predicts earthquakes in the continuum model of a rate-and-state fault with frictional heterogeneities". We provide the data to create Figures 1 to 4 from the main text and Figures S1 to S9 from the supplementary information. We also provide Python scripts to plot them.</p>
The ClaDS rate-heterogeneous birth-death prior for full phylogenetic inference in BEAST2
<p>Bayesian phylogenetic inference requires a tree prior, which models the underlying diversification process which gives rise to the phylogeny. Existing birth-death diversification models include a wide range of features, for instance lineage-specific variations in speciation and extinction rates. While across-lineage variation in speciation and extinction rates is widespread in empirical datasets, few heterogeneous rate models have been implemented as tree priors for Bayesian phylogenetic inference. As a consequence, rate heterogeneity is typically ignored when reconstructing phylogenies, and rate heterogeneity is usually investigated on fixed trees. In this paper, we present a new BEAST2 package implementing the cladogenetic diversification rate shift (ClaDS) model as a tree prior. ClaDS is a birth-death diversification model designed to capture small progressive variations in birth and death rates along a phylogeny. Unlike previous implementations of ClaDS, which were designed to be used with fixed, user-chosen phylogenies, our package is implemented in the BEAST2 framework and thus allows full phylogenetic inference, where the phylogeny and model are co-estimated from a molecular alignment. Our package provides all necessary components of the inference, including a new tree object and operators to propose moves to the MCMC. It also includes a graphical interface through BEAUti. We validate our implementation of the package by comparing the produced distributions to simulated data, and show an empirical example of the full inference, using a cetaceans dataset.</p>
The ClaDS rate-heterogeneous birth-death prior for full phylogenetic inference in BEAST2
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Heterogeneity in the rate of molecular sequence evolution substantially impacts the accuracy of detecting shifts in diversification rates
<p>As species richness varies along the tree of life, there is a great interest in identifying factors that affect the rates by which lineages speciate or go extinct. To this end, theoretical biologists have developed a suit of phylogenetic comparative methods that aim to identify where shifts in diversification rates had occurred along a phylogeny and whether they are associated with some traits. Using these methods, numerous studies have predicted that speciation and extinction rates vary across the tree of life. In this study we show that asymmetric rates of sequence evolution rates lead to systematic biases in the inferred phylogeny, which in turn lead to erroneous inferences regarding lineage diversification patterns. The results demonstrate that as the asymmetry in sequence evolution rates increases, so does the tendency to select more complicated models that include the possibility of diversification rate shifts. These results thus suggest that any inference regarding shifts in diversification pattern should be treated with great caution, at least until any biases regarding the molecular substitution rate have been ruled out.</p>
Antibiotics Change the Growth Rate Heterogeneity and Morphology of Bacteria
<p>Each experiment was conducted on the Multipad Agarose Plate (MAP) and is labeled with BE followed by a number. This repository contains four main elements:</p> <ol> <li>The file <code>Experiment condition map.json</code> describes how the MAP platforms were set up for each experiment. Some datasets also include data that was discarded. </li> <li>The folder <code>Benchmarking</code> contains data for how we validated the performance of our <code>PadAnalyser</code> package. <code>Originals</code> have a set of images of bacteria affected by antibiotics that produce different morphologies. <code>Annotated_raw</code> is the human-labelled version of these, and <code>Annotated</code> are these converted to a format that can be used by code for comparison. <code>Segmentation Benchmarking.ipynb</code><em> </em>is a Jupyter Notebook that segments the cells and compares the output to the annotated data. </li> <li>The folder <code>Dataframes</code><em> </em>contains Pandas data frames from all experiments, classified by bacteria species. </li> <li>The folder <code>Videos</code> contains debug videos visualising how the segmentation algorithm performed on the different datasets. Contact us for access to the raw data. Videos in the format <code>*_ssi.mp4</code> contain single-cell masks, and <code>*_css.mp4</code> contains colony masks. </li> </ol>
Growth orientations, rather than heterogeneous growth rates, dominate jaw joint morphogenesis in the larval zebrafish
<p>Supplementary material for paper entitled "Growth orientations, rather than heterogeneous growth rates, dominate jaw joint morphogenesis in the larval zebrafish".</p> <p>Raw data, scripts, models and results are made available along with supplementary figures.</p>
Linked selection, differential introgression and recombination rate variation promote heterogeneous divergence in a pair of yellow croakers
<p><span>Understanding the mechanisms underlying heterogeneous genomic divergence is of particular interest in evolutionary biology. Highly differentiated genomic regions, known as genomic islands, often evolve between diverging lineages. These genomic islands may be related to selection promoting adaptation or reproductive isolation. Based on whole genome assembly and genome-wide RAD sequencing in a pair of yellow croakers (genus: <em>Larimichthys</em>), we investigated the evolutionary processes shaping genomic landscapes of divergence. Demographic modelling indicated that the two species diverged following a secondary contact scenario, where differential introgression and linked selection were suggested to be involved in heterogeneous genomic divergence. We identified reduced recombination rate in genomic islands and a relatively good conservation of both genetic diversity and recombination landscapes between species, which highlight the roles of linked selection and recombination rate variation in promoting heterogeneous divergence in the common ancestral lineage of the two species. In addition, we found a positive correlation between differentiation (F<sub>ST</sub>) and absolute sequence divergence (<em>D</em><sub>xy</sub>), and elevated </span><span><span><em>D</em><sub>xy</sub></span> in genomic islands, which were different from the patterns under linked selection. Restricted gene flow in highly differentiated regions has likely remodeled the landscape of heterogeneous genomic divergence. Moreover, genomic islands showed little evidence of overlapping within and between species, implying that high gene flow and divergent selection when colonizing new habitats have reshaped the patterns of intraspecific divergence. This study highlights that highly differentiated genomic regions can also be from linked selection and variation of recombination rate, and thus are not necessarily related to speciation islands or local adaptation. </span></p>
Cycling Rate-Induced Spatially-Resolved Heterogeneities in Commercial Cylindrical Li-Ion Batteries: Datasets
<p>Sinogram XRD-CT data used in the manuscript entitled "Cycling Rate-Induced Spatially-Resolved Heterogeneities in Commercial Cylindrical Li-Ion Batteries".</p>
Heterogeneity in the rate of molecular sequence evolution substantially impacts the accuracy of detecting shifts in diversification rates
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Extinction and ecosystem function debt across dispersal rate and behavior in a heterogeneous metacommunity model
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Linked selection, differential introgression and recombination rate variation promote heterogeneous divergence in a pair of yellow croakers
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Semi-analytical modeling of rate-dependent relative permeability in heterogeneous formations
<p>Numerical codes and results for MS: Semi-analytical modeling of rate-dependent relative permeability in heterogeneous formations</p>
Data from: Depletion of heterogeneous source species pools predicts future invasion rates
Predicting how increasing rates of global trade will result in new establishments of potentially damaging invasive species is a question of critical importance to the development of national and international policies aimed at minimizing future invasions. Centuries of historical movement and establishment of invading species may have depleted the supply of species available for future invasions, and it has been suggested that the problem of invasions will diminish as a result of this. However, the extent to which source pool depletion affects future invasions remains unclear. Here we describe a mechanistic model that captures the simultaneous effects of depletion of source species pools along with increases in pathway rates (e.g. imports) to predict future numbers of new invasions. We assume that the distribution of species abundance within invasion pathways is positively skewed, which is modelled using a log-normal distribution. Given their high propagule pressure, the most abundant species are likely to invade first, while the many rare species are likely to invade only under high pathway volumes. We apply this model to the case study of bark beetle, Scolytinae, invasions in the USA. Source species pools in Europe and Asia (225 and 655 species of Scolytinae, respectively) are much larger than numbers that have historically established (16 and 32). Parameterization of the model indicates a highly skewed species abundance distribution in the pathway and this is confirmed by species frequencies in port inspection records, thus explaining why only a small fraction of species has historically invaded. Forecasts from the model indicate that with increasing rates of imports, more species from these regions are likely to invade in the future despite the depletion of the most abundant species from source species pools. Previous statistical models tend to underestimate future establishments in the presence of increasing import rates due to their failure to account for key underlying mechanisms. Policy implications. The mechanistic model developed here is widely applicable for predicting future invasions of all taxa and provides insights into how increases in rates of imports counteract the species pool depletion effect, resulting in the continued establishment of new species.
Data from: Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification
The binary-state speciation and extinction (BiSSE) model has been used in many instances to identify state-dependent diversification and reconstruct ancestral states. However, recent studies have shown that the standard procedure of comparing the fit of the BiSSE model to constant-rate birth–death models often inappropriately favours the BiSSE model when diversification rates vary in a state-independent fashion. The newly developed HiSSE model enables researchers to identify state-dependent diversification rates while accounting for state-independent diversification at the same time. The HiSSE model also allows researchers to test state-dependent models against appropriate state-independent null models that have the same number of parameters as the state-dependent models being tested. We reanalyse two data sets that originally used BiSSE to reconstruct ancestral states within squamate reptiles and reached surprising conclusions regarding the evolution of toepads within Gekkota and viviparity across Squamata. We used this new method to demonstrate that there are many shifts in diversification rates across squamates. We then fit various HiSSE submodels and null models to the state and phylogenetic data and reconstructed states under these models. We found that there is no single, consistent signal for state-dependent diversification associated with toepads in gekkotans or viviparity across all squamates. Our reconstructions show limited support for the recently proposed hypotheses that toepads evolved multiple times independently in Gekkota and that transitions from viviparity to oviparity are common in Squamata. Our results highlight the importance of considering an adequate pool of models and null models when estimating diversification rate parameters and reconstructing ancestral states.
Data from: Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification
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Data from: Depletion of heterogeneous source species pools predicts future invasion rates
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Data from: The impact of rate heterogeneity on inference of phylogenetic models of trait evolution
Rates of trait evolution are known to vary across phylogenies; however, standard evolutionary models assume a homogeneous process of trait change. These simple methods are widely applied in small-scale phylogenetic studies, whereas models of rate heterogeneity are not, so the prevalence and patterns of potential rate variation in groups up to hundreds of species remain unclear. The extent to which trait evolution is modelled accurately on a given phylogeny is also largely unknown because studies typically lack absolute model fit tests. We investigated these issues by applying both rate-static and variable-rates methods on (i) body mass data for 88 avian clades of 10–318 species, and (ii) data simulated under a range of rate-heterogeneity scenarios. Our results show that rate heterogeneity is present across small-scaled avian clades, and consequently applying only standard single-process models prompts inaccurate inferences about the generating evolutionary process. Specifically, these approaches underestimate rate variation, and systematically mislabel temporal trends in trait evolution. Conversely, variable-rates approaches have superior relative fit (they are the best model) and absolute fit (they describe the data well). We show that rate changes such as single internal branch variations, rate decreases and early bursts are hard to detect, even by variable-rates models. We also use recently developed absolute adequacy tests to highlight misleading conclusions based on relative fit alone (e.g. a consistent preference for constrained evolution when isolated terminal branch rate increases are present). This work highlights the potential for robust inferences about trait evolution when fitting flexible models in conjunction with tests for absolute model fit.
Data for: Density dependence and spatial heterogeneity limit the population growth rate of invasive pines at the landscape scale
<p class="MsoBodyText"><span><span><span><span><span><span><span><span><span><span><span>Determining population growth across large scales is difficult because it is often impractical to collect data at large scales and over long timespans. Instead, the growth of a population is often only measured at a small, plot-level scale and then extrapolated to derive a mean field estimate. However, this approach is prone to error since it simplifies spatial processes such as the neighbourhood effects of density and dispersal. We present a novel approach that estimates how spatial processes derived from the effects of density and dispersal affect population growth between plot scales and landscape scales. The method is based on a scale transition theory and calculates a transition term to measure the spatial scaling of population growth, which we extend to unstable, expanding populations in order to assess whether landscape-scale population dynamics are different from those estimated at smaller spatial scales. We illustrate this approach using aerial imagery of eight locations in New Zealand experiencing non-native pine invasions. Analyses examined the dynamics at a plot scale (1 hectare) and compared this to estimates across entire landscapes (between 24 and 1600 hectares), in several cases for more than one time period. We used a Bayesian spatial random effects model to examine population growth and to account for neighbourhood effects and dispersal between plots in a rapidly changing system. </span></span></span></span></span></span></span></span></span></span></span></p> <p class="MsoBodyText"><span><span><span><span><span><span><span><span><span><span><span>We found that the estimates of the scale transition term were typically 10-25% of the mean field estimates, which led to mean field estimates of population growth extrapolated from plots being considerably higher than landscape estimates. The approach we have developed will not only have applications for predicting the populations' growth of invasive species, but also for studies examining the scaling of landscape-scale phenomena.</span></span></span></span></span></span></span></span></span></span></span></p>
Fast likelihood calculations for automatic identification of macroevolutionary rate heterogeneity in continuous and discrete traits
<p>Understanding phenotypic disparity across the tree of life requires identifying where and when evolutionary rates change on phylogeny. A primary methodological challenge in macroevolution is therefore to develop methods for accurate inference of among-lineage variation in rates of phenotypic evolution. Here, we describe a method for inferring among-lineage evolutionary rate heterogeneity in both continuous and discrete traits. The method assumes that the present-day distribution of a trait is shaped by a variable-rate process arising from a mixture of constant-rate processes and uses a single-pass tree traversal algorithm to estimate branch-specific evolutionary rates. By employing dynamic programming optimization techniques and approximate maximum likelihood estimators where appropriate, our method permits rapid exploration of the tempo and mode of phenotypic evolution. Simulations indicate that the method reconstructs rates of trait evolution with high accuracy. Application of the method to datasets on squamate reptile reproduction and turtle body size recovers patterns of rate heterogeneity identified by previous studies but with computational costs reduced by many orders of magnitude. Our results expand the set of tools available for detecting macroevolutionary rate heterogeneity and point to the utility of fast, approximate methods for studying large scale biodiversity dynamics.</p>
Data from: Cis- and trans-acting genetic factors contribute to heterogeneity in the rate of crossing over between the Drosophila simulans clade species
In the genus Drosophila, variation in recombination rates has been found within and between species. Genetic variation for both cis- and trans-acting factors has been shown to affect recombination rates within species, but little is known about the genetic factors that affect differences between species. Here we estimate rates of crossing over for seven segments that tile across the euchromatic length of the X chromosome in the genetic backgrounds of three closely related Drosophila species. We first generated a set of Drosophila mauritiana lines each having two semi-dominant visible markers on the X chromosome and then introgressed these doubly marked segments into the genetic backgrounds of its sibling species, D. simulans and D. sechellia. Using these 21 lines (7 segments, 3 genetic backgrounds) we tested whether recombination rates within the doubly marked intervals differed depending on genetic background. We find significant heterogeneity among intervals and among species backgrounds. Our results suggest that a combination of both cis- and trans-acting factors have evolved among the three D. simulans clade species and interact to affect recombination rate.
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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
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.