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5,805 results for “Data model”
Estimating the burden of underdiagnosis within England: a modelling study of linked primary care data
<p>These datasets are the modelling outputs supporting our paper titled: <strong><span>Estimating the burden of underdiagnosis within England: a modelling study of linked primary care data. </span></strong><span>The details of how these data were produced were described in the paper. </span></p> <p> </p> <p> </p>
Data for the systematic review of OR modelling for alcohol consumption and its consequences
<p>This file contains the data of the 182 papers that were relevant for the literature review, which was used to produce the plots and analysis for this paper. </p>
Model and data files of TomoATT for regional tomography in central California near Parkfield
<p>The model and data files of TomoATT for regional tomography in central California near Parkfield.</p>
Model and data files of TomoATT for teleseismic tomography in Thailand and adjacent areas
<p>Model and data files of TomoATT for teleseismic tomography in Thailand and adjacent areas.</p>
Data from: Boechera, a model system for ecological genomics
The selection and development of a study system for evolutionary and ecological functional genomics (EEFG) depends on a variety of factors. Here we present the genus Boechera as an exemplary system with which to address ecological and evolutionary questions. Our focus on Boechera is based on several characteristics: 1) native populations in undisturbed habitats where current environments reflect historical conditions over several thousand years; 2) functional genomics benefitting from its close relationship to Arabidopsis thaliana; 3) inbreeding tolerance enabling development of recombinant inbred lines, near-isogenic lines, and positional cloning; 4) interspecific crosses permitting mapping for genetic analysis of speciation; 5) apomixis (asexual reproduction by seeds) in a genetically tractable diploid; and 6) broad geographic distribution in North America, permitting ecological genetics for a large research community. These characteristics, along with the current sequencing of three Boechera species by the Joint Genome Institute, position Boechera as a rapidly advancing system for EEFG studies.
Data from: Central place foragers and moving stimuli: a hidden-state model to discriminate the processes affecting movement
1. Human activities can influence the movement of organisms, either repelling or attracting individuals depending on whether they interfere with natural behavioural patterns or enhance access to food. To discern the processes affecting such interactions, an appropriate analytical approach must reflect the motivations driving behavioural decisions at multiple scales. 2. In this study, we developed a modelling framework for the analysis of foraging trips by central place foragers. By recognising the distinction between movement phases at a larger scale and movement steps at a finer scale, our model can identify periods when animals are actively following moving attractors in their landscape. 3. We applied the framework to GPS tracking data of northern fulmars Fulmarus glacialis, paired with contemporaneous fishing boat locations, to quantify the putative scavenging activity of these seabirds on discarded fish and offal. We estimated the rate and scale of interaction between individual birds and fishing boats and the interplay with other aspects of a foraging trip. 4. The model classified periods when birds were heading out to sea, returning towards the colony or following the closest boat. The probability of switching towards a boat declined with distance and varied depending on the phase of the trip. The maximum distance at which a bird switched towards the closest boat was estimated around 35 km, suggesting the use of olfactory information to locate food. Individuals spent a quarter of a foraging trip, on average, following fishing boats, with marked heterogeneity among trips and individuals. 5. Our approach can be used to characterise interactions between central place foragers and different anthropogenic or natural stimuli. The model identifies the processes influencing central place foraging at multiple scales, which can improve our understanding of the mechanisms underlying movement behaviour and characterise individual variation in interactions with a range of human activities that may attract or repel these species. Therefore, it can be adapted to explore the movement of other species that are subject to multiple dynamic drivers.
Data from: Spatiotemporal diversification of the true frogs (Genus Rana): a historical framework for a widely studied group of model organisms
True frogs of the genus Rana are widely used as model organisms in studies of development, genetics, physiology, ecology, behavior, and evolution. Comparative studies among the more than 100 species of Rana rely on an understanding of the evolutionary history and patterns of diversification of the group. We estimate a well-resolved, time-calibrated phylogeny from sequences of six nuclear and three mitochondrial loci sampled from most species of Rana, and use that phylogeny to clarify the group's diversification and global biogeography. Our analyses consistently support an "Out of Asia" pattern with two independent dispersals of Rana from East Asia to North America via Beringian land bridges. The more species-rich lineage of New World Rana appears to have experienced a rapid radiation following its colonization of the New World, especially with its expansion into montane and tropical areas of Mexico, Central America, and South America. In contrast, Old World Rana exhibit different trajectories of diversification; diversification in the Old World began very slowly and later underwent a distinct increase in speciation rate around 29–18 Ma. Net diversification is associated with environmental changes and especially intensive tectonic movements along the Asian margin from the Oligocene to early Miocene. Our phylogeny further suggests that previous classifications were misled by morphological homoplasy and plesiomorphic color patterns, as well as a reliance primarily on mitochondrial genes. We provide a phylogenetic taxonomy based on analyses of multiple nuclear and mitochondrial gene loci.
Data from: Swapping birth and death: symmetries and transformations in phylodynamic models
Stochastic birth--death models provide the foundation for studying and simulating evolutionary trees in phylodynamics. A curious feature of such models is that they exhibit fundamental symmetries when the birth and death rates are interchanged. In this paper, we first provide intuitive reasons for these known transformational symmetries. We then show that these transformational symmetries (encoded in algebraic identities) are preserved even when individuals at the present are sampled with some probability. However, these extended symmetries require the death rate parameter to sometimes take a negative value. In the last part of this paper, we describe the relevance of these transformations and their application to computational phylodynamics, particularly to maximum likelihood and Bayesian inference methods, as well as to model selection.
Data from: Demographic expansion and genetic load of the halophyte model plant Eutrema salsugineum
Eutrema salsugineum is a widely distributed species, which provide a good model to study long-distance dispersal and accumulation of deleterious mutations. Based on population genomic data, we clarified demographic history of E. salsugineum and showed how deleterious alleles accumulated.
Data from: Spatial modeling improves understanding patterns of invasive species defoliation by a biocontrol herbivore
Spatial modeling has proven to be useful in understanding the drivers of plant populations in the field of ecology, but has yet to be applied to understanding variation in biocontrol impact. In this study, we employ multi-scale analysis (Moran's Eigenvector Maps) to better understand the variation in tree canopy exposed to defoliation by a biocontrol beetle (Diorhabda spp.). The control of the exotic tree Tamarix in riparian areas has long been a priority for land managers and ecologists in the American southwest. Diorhabda spp. was introduced as a bio-control agent beginning in 2001 and has since become an inseparable part of Tamarix-dominated river systems in the southwest. Between 2013 and 2016 tamarisk dieback was assessed at 79 sites across Grand County, Utah, arguably the epicenter of Diorhabda impact in the U.S. Canopy cover of Tamarix was between 73%-81% at these sites, with the percent that was live cover fluctuating by year with a minimum of 42%. Using a traditional general linear model, we found that readily and commonly measured environmental factors could explain only up to 26% of the variation in Tamarix live canopy each year, including that number of defoliations was correlated with an increase rather than a decrease in percent live canopy, suggesting compensatory growth. Spatial structure alone explained 22-40% of variation. We found fine scale spatial structure at less than 10 km and broad scale spatial structure from 10-30 km. Combining both traditional and novel spatial statistical methods we increased that percentage to 43-63%, depending on year. These results suggest that scientists and land managers must look beyond commonly measured environmental variables to explain non-random biocontrol impact in this system. In particular, this study points to the potential for biotic interactions and variation in flood cycles for further exploration of the identified spatial structure.
Data from: Do ecological niche models accurately identify climatic determinants of species ranges?
Defining species' niches is central to understanding their distributions and is thus fundamental to basic ecology and climate change projections. Ecological niche models (ENMs) are a key component of making accurate projections and include descriptions of the niche in terms of both response curves and rankings of variable importance. In this study, we evaluate Maxent's ranking of environmental variables based on their importance in delimiting species' range boundaries by asking whether these same variables also govern annual recruitment based on long-term demographic studies. We found that Maxent-based assessments of variable importance in setting range boundaries in the California tiger salamander (Ambystoma californiense; CTS) correlate very well with how important those variables are in governing ongoing recruitment of CTS at the population level. This strong correlation suggests that Maxent's ranking of variable importance captures biologically realistic assessments of factors governing population persistence. However, this result holds only when Maxent models are built using best-practice procedures and variables are ranked based on permutation importance. Our study highlights the need for building high-quality niche models and provides encouraging evidence that when such models are built, they can reflect important aspects of a species' ecology.
Data from: A modelling framework to assess the effect of pressures on river abiotic habitat conditions and biota
River biota are affected by global reach-scale pressures, but most approaches for predicting biota of rivers focus on river reach or segment scale processes and habitats. Moreover, these approaches do not consider long-term morphological changes that affect habitat conditions. In this study, a modelling framework was further developed and tested to assess the effect of pressures at different spatial scales on reach-scale habitat conditions and biota. Ecohydrological and 1D hydrodynamic models were used to predict discharge and water quality at the catchment scale and the resulting water level at the downstream end of a study reach. Long-term reach morphology was modelled using empirical regime equations, meander migration and 2D morphodynamic models. The respective flow and substrate conditions in the study reach were predicted using a 2D hydrodynamic model, and the suitability of these habitats was assessed with novel habitat models. In addition, dispersal models for fish and macroinvertebrates were developed to assess the re-colonization potential and to finally compare habitat suitability and the availability / ability of species to colonize these habitats. Applicability was tested and model performance was assessed by comparing observed and predicted conditions in the lowland Treene River in northern Germany. Technically, it was possible to link the different models, but future applications would benefit from the development of open source software for all modelling steps to enable fully automated model runs. Future research needs concern the physical modelling of long-term morphodynamics, feedback of biota (e.g., macrophytes) on abiotic habitat conditions, species interactions, and empirical data on the hydraulic habitat suitability and dispersal abilities of macroinvertebrates. The modelling framework is flexible and allows for including additional models and investigating different research and management questions, e.g., in climate impact research as well as river restoration and management.
Data from: Dinoflagellates with relic endosymbiont nuclei as models for elucidating organellogenesis
<p><span>Nucleomorphs are relic endosymbiont nuclei so far found only in two algal groups, cryptophytes and chlorarachniophytes, which have been studied to model the evolutionary process of integrating an endosymbiont alga into a host-governed plastid (organellogenesis). However, past studies suggested that DNA transfer from the endosymbiont to host nuclei had already ceased in both cryptophytes and chlorarachniophytes, implying that the organellogenesis at the genetic level has been completed in the two systems. Moreover, we have yet to pinpoint the closest free-living relative of the endosymbiotic alga engulfed by the ancestral chlorarachniophyte or cryptophyte, making it difficult to infer how organellogenesis altered the endosymbiont genome. To counter the above issues, we need novel nucleomorph-bearing algae, in which endosymbiont-to-host DNA transfer is on-going and for which endosymbiont/plastid origins can be inferred at a fine taxonomic scale. Here, we report two previously undescribed dinoflagellates, strains MGD and TGD, with green algal endosymbionts enclosing plastids as well as relic nuclei (nucleomorphs). We provide evidence for the presence of DNA in the two nucleomorphs and the transfer of endosymbiont genes to the host (dinoflagellate) genomes. Furthermore, DNA transfer between the host and endosymbiont nuclei was found to be in progress in both the MGD and TGD systems. Phylogenetic analyses successfully resolved the origins of the endosymbionts at the genus level. With the combined evidence, we conclude that the host-endosymbiont integration in MGD/TGD is less advanced than that in cryptophytes/chrorarachniophytes, and propose the two dinoflagellates as models for elucidating organellogenesis.</span></p>
Data from: Modeling of the larval response of green sea urchins to thermal stratification using a random walk approach
Larval transport in the ocean can be affected by their vertical position in the water column. In biophysical models that are often used to predict larval horizontal dispersal, generally larval vertical positions are either ignored or incorporated as static parameters. Here, we evaluate the ability of one dimensional random walk based model to predict larval vertical distribution of Strongylocentrotus droebachiensis in response to thermal stratification. Vertical swimming velocities were recorded at various temperatures and used to parameterize the model. Data from a previous laboratory study on the effects of thermal stratification on larval vertical distribution of S. droebachiensis were compared to the model results to evaluate the predictive ability of the model. The model predicts general trends in vertical distribution fairly well, but has a systematic bias which can be explained by un-quantified larval behaviors at the boundaries of the experimental water column. Overall, our behavioral model successfully reproduces the mechanism which regulates larval vertical distribution in response to thermal structure. Collectively, the findings suggest that simple behavioral models parameterized using simple lab experiments can prove useful in estimating the vertical distributions of invertebrate larvae in the laboratory and likely in the ocean. Such models can then be linked to bio-physical models to more accurately predict larval dispersal.
Data from: Population genomic tests of models of adaptive radiation in Lake Victoria region cichlid fish.
Adaptive radiation is usually thought to be associated with speciation, but the evolution of intraspecific polymorphisms without speciation is also possible. The radiation of cichlid fish in Lake Victoria is perhaps the most impressive example of a recent rapid adaptive radiation, with 600+ very young species. Key questions about its origin remain poorly characterized, such as the importance of speciation versus polymorphism, whether species persist on evolutionary time scales, and if speciation happens more commonly in small isolated or in large connected populations. We used 320 individuals from 105 putative species from Lakes Victoria, Edward, Kivu, Albert, Nabugabo and Saka, in a radiation-wide AFLP genome scan to address some of these questions. We demonstrate pervasive signatures of speciation supporting the classical model of adaptive radiation associated with speciation. A positive relationship between the age of lakes and the average genomic differentiation of their species, and a significant fraction of molecular variance explained by above-species level taxonomy suggest the persistence of species on evolutionary time scales, with radiation through sequential speciation rather than a single starburst. Finally the large gene diversity retained from colonization to individual species in every radiation suggests large effective population sizes and makes speciation in small geographical isolates unlikely.
Data from: Tales of the unexpected: Phylogeography of the arctic-alpine model plant Saxifraga oppositifolia (Saxifragaceae) revisited
Arctic-alpine biota occupy enormous areas in the Arctic and the northern hemisphere mountain ranges, and have undergone major range shifts during their comparatively short history. The origins of individual arctic-alpine species remain largely unknown. In the case of the Purple saxifrage, Saxifraga oppositifolia, an important model for arctic-alpine plants, phylogeographic studies have remained inconclusive about early stages of the species' spatiotemporal diversification, but have provided evidence for long-range colonization out of a presumed Beringian origin to cover today's circumpolar range. . We re-evaluated the species' large-scale range dynamics based on a geographically extended sampling including crucial areas such as Central Asia and the (south-)eastern European mountain ranges and employing up-to-date phylogeographic analyses of a plastid sequence and a more restricted AFLP data set. In accordance with previous studies, we detected two major plastid DNA lineages also reflected in AFLP divergence, suggesting a long and independent vicariant history. Although we were unable to determine the species' area of origin, our results point to the Alps and probably Central Asia, respectively, as the likely ancestral areas of the two main clades. AFLP data suggested that contact areas between the two clades in Eastern Europe, Northern Siberia and Greenland were secondary. In marked contrast to high levels of diversity revealed in previous studies, populations from the major arctic refugium Beringia did not exhibit any plastid sequence polymorphism. Our study shows that adequate sampling of the southern, refugial populations is crucial for understanding the range dynamics of arctic-alpine species.
Data from: Modelling the area of occupancy of habitat types with remote sensing
1. A current challenge of biodiversity and conservation is the estimation of the spatial extent of habitat types across broad territories. In the absence of fine-resolution maps, predictive modelling helps in assessing the spatial distribution of vegetation cover. However, such approaches are still uncommon in regional planning and management. Here, we present a framework for mapping the area of occupancy (AOO) of habitat types that allows highly suitable estimates at different scales. 2. We model the potential AOO with abiotic variables related to topography and climate, resulting in broad AOO estimates that are subsequently downscaled to the local AOO with remote sensing. The combination of individual local AOO estimates allows the defining of the realized AOO, comprising locations with a high likelihood of occurrence and low uncertainty for each habitat. We applied this framework to mapping 24 protected habitat types of Natura 2000 sites in northern Spain. 3. Local and realized AOO were highly accurate, with a 70% overall accuracy for the realized AOO. Remote sensing data, and especially LiDAR, were the most important predictors in habitat types related to forests and shrubs, followed by rock outcrops and pastures. Environmental variables were also relevant for specific habitats subject to abiotic constraints. 4. The combination of ecological modelling with remote sensing offers multiple advantages over traditional field surveys and image interpretation, allowing the harmonization of habitat maps across large regions and through time. This is particularly useful for implementing conservation actions under Natura 2000 principles or assessing IUCN criteria for ecosystems.
Data from: Detecting hybridization by likelihood calculation of gene tree extra lineages given explicit models
Explanations for gene tree discordance with respect to a species tree are commonly attributed to deep coalescence (also known as incomplete lineage sorting [ILS]), as well as different evolutionary processes such as hybridization, horizontal gene transfer and gene duplication. Among these, deep coalescence is usually quantified as the number of extra lineages and has been studied as the principal source of discordance among gene trees, while the other processes that could contribute to gene tree discordance have not been fully explored. This is an important issue for hybridization because interspecific gene flow is well documented and widespread across many plant and animal groups. Here, we propose a new way to detect gene flow when ILS is present that evaluates the likelihood of different models with various levels of gene flow, by comparing the expected gene tree discordance, using the number of extra lineages. This approach consists of proposing a model, simulating a set of gene trees to infer a distribution of expected extra lineages given the model, and calculating a likelihood function by comparing the fit of the real gene trees to the simulated distribution. To count extra lineages, the gene tree is first reconciled within the species tree, and for a given species tree branch the number of gene lineages minus one is counted. We develop a set of R functions to parallelize software to allow simulations, and to compare hypotheses via a likelihood ratio test to evaluate the presence of gene flow when ILS is present, in a fast and simple way. Our results show high accuracy under very challenging scenarios of high impact of ILS and low gene flow levels, even using a modest dataset of five to ten loci and five to ten individuals per species. We present a powerful and fast method to detect hybridization in presence of ILS. We discuss its advantage with large dataset (such as genomic scale), and also identifies possible issues that should be explored with more complex models in future studies.
Data from: A mistletoe tale: postglacial invasion of Psittacanthus schiedeanus (Loranthaceae) to Mesoamerican cloud forests revealed by molecular data and species distribution modeling
Background: Ecological adaptation to host taxa is thought to result in mistletoe speciation via race formation. However, historical and ecological factors could also contribute to explain genetic structuring particularly when mistletoe host races are distributed allopatrically. Using sequence data from nuclear (ITS) and chloroplast (trnL-F) DNA, we investigate the genetic differentiation of 31 Psittacanthus schiedeanus (Loranthaceae) populations across the Mesoamerican species range. We conducted phylogenetic, population and spatial genetic analyses on 274 individuals of P. schiedeanus to gain insight of the evolutionary history of these populations. Species distribution modeling, isolation with migration and Bayesian inference methods were used to infer the evolutionary transition of mistletoe invasion, in which evolutionary scenarios were compared through posterior probabilities. Results: Our analyses revealed shallow levels of population structure with three genetic groups present across the sample area. Nine haplotypes were identified after sequencing the trnL-F intergenic spacer. These haplotypes showed phylogeographic structure, with three groups with restricted gene flow corresponding to the distribution of individuals/populations separated by habitat (cloud forest localities from San Luis Potosí to northwestern Oaxaca and Chiapas, localities with xeric vegetation in central Oaxaca, and localities with tropical deciduous forests in Chiapas), with post-glacial population expansions and potentially corresponding to post-glacial invasion types. Similarly, 44 ITS ribotypes suggest phylogeographic structure, despite the fact that most frequent ribotypes are widespread indicating effective nuclear gene flow via pollen. Gene flow estimates, a significant genetic signal of demographic expansion, and range shifts under past climatic conditions predicted by species distribution modeling suggest post-glacial invasion of P. schiedeanus mistletoes to cloud forests. However, Approximate Bayesian Computation (ABC) analyses strongly supported a scenario of simultaneous divergence among the three groups isolated recently. Conclusions: Our results provide support for the predominant role of isolation and environmental factors in driving genetic differentiation of Mesoamerican parrot-flower mistletoes. The ABC results are consistent with a scenario of post-glacial mistletoe invasion, independent of host identity, and that habitat types recently isolated P. schiedeanus populations, accumulating slight phenotypic differences among genetic groups due to recent migration across habitats. Under this scenario, climatic fluctuations throughout the Pleistocene would have altered the distribution of suitable habitat for mistletoes throughout Mesoamerica leading to variation in population continuity and isolation. Our findings add to an understanding of the role of recent isolation and colonization in shaping cloud forest communities in the region.
Data from: Mapping beta diversity from space: Sparse Generalized Dissimilarity Modelling (SGDM) for analysing high-dimensional data
1. Spatial patterns of community composition turnover (beta diversity) may be mapped through Generalised Dissimilarity Modelling (GDM). While remote sensing data are adequate to describe these patterns, the often high-dimensional nature of these data poses some analytical challenges, potentially resulting in loss of generality. This may hinder the use of such data for mapping and monitoring beta-diversity patterns. 2. This study presents Sparse Generalised Dissimilarity Modelling (SGDM), a methodological framework designed to improve the use of high-dimensional data to predict community turnover with GDM. SGDM consists of a two-stage approach, by first transforming the environmental data with a sparse canonical correlation analysis (SCCA), aimed at dealing with high-dimensional datasets, and secondly fitting the transformed data with GDM. The SCCA penalisation parameters are chosen according to a grid search procedure in order to optimise the predictive performance of a GDM fit on the resulting components. The proposed method was illustrated on a case study with a clear environmental gradient of shrub encroachment following cropland abandonment, and subsequent turnover in the bird communities. Bird community data, collected on 115 plots located along the described gradient, were used to fit composition dissimilarity as a function of several remote sensing datasets, including a time series of Landsat data as well as simulated EnMAP hyperspectral data. 3. The proposed approach always outperformed GDM models when fit on high-dimensional datasets. Its usage on low-dimensional data was not consistently advantageous. Models using high-dimensional data, on the other hand, always outperformed those using low-dimensional data, such as single date multispectral imagery. 4. This approach improved the direct use of high-dimensional remote sensing data, such as time series or hyperspectral imagery, for community dissimilarity modelling, resulting in better performing models. The good performance of models using high-dimensional datasets further highlights the relevance of dense time series and data coming from new and forthcoming satellite sensors for ecological applications such as mapping species beta diversity.
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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.