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1,634 results for “Data integration”
Data from: Hybrid Integration of Silicon Photonic Devices on Lithium Niobate for Optomechanical Wavelength Conversion
<p>Source data for Figures.</p>
Data from: Ocean acidification impacts spine integrity but not regenerative capacity of spines and tube feet in adult sea urchins
Increasing atmospheric carbon dioxide (CO2) has resulted in a change in seawater chemistry and lowering of pH, referred to as ocean acidification. Understanding how different organisms and processes respond to ocean acidification is vital to predict how marine ecosystems will be altered under future scenarios of continued environmental change. Regenerative processes involving biomineralization in marine calcifiers such as sea urchins are predicted to be especially vulnerable. In this study, the effect of ocean acidification on regeneration of external appendages (spines and tube feet) was investigated in the sea urchin Lytechinus variegatus exposed to ambient (546 µatm), intermediate (1027 µatm) and high (1841 µatm) partial pressure of CO2 (pCO2) for eight weeks. The rate of regeneration was maintained in spines and tube feet throughout two periods of amputation and regrowth under conditions of elevated pCO2. Increased expression of several biomineralization-related genes indicated molecular compensatory mechanisms; however, the structural integrity of both regenerating and homeostatic spines was compromised in high pCO2 conditions. Indicators of physiological fitness (righting response, growth rate, coelomocyte concentration and composition) were not affected by increasing pCO2, but compromised spine integrity is likely to have negative consequences for defence capabilities and therefore survival of these ecologically and economically important organisms.
Data from: Evaluating population viability and efficacy of conservation management using integrated population models
Predicting population responses to environmental conditions or management scenarios is a fundamental challenge for conservation. Proper consideration of demographic, environmental and parameter uncertainties is essential for projecting population trends and optimal conservation strategies. We developed a coupled integrated population model-Bayesian population viability analysis to assess the (1) impact of demographic rates (survival, fecundity, immigration) on past population dynamics; (2) population viability 10 years into the future; and (3) efficacy of possible management strategies for the federally endangered Great Lakes piping plover Charadrius melodus population. Our model synthesizes long-term population survey, nest monitoring and mark–resight data, while accounting for multiple sources of uncertainty. We incorporated latent abundance of eastern North American merlins Falco columbarius, a primary predator of adult plovers, as a covariate on adult survival via a parallel state-space model, accounting for the influence of an imperfectly observed process (i.e. predation pressure) on population viability. Mean plover abundance increased from 18 pairs in 1993 to 75 pairs in 2016, but annual population growth (math formula) was projected to be 0.95 (95% CI 0.72–1.12), suggesting a potential decline to 67 pairs within 10 years. Without accounting for an expanding merlin population, we would have concluded that the plover population was projected to increase (math formula = 1.02; 95% CI 0.94–1.09) to 91 pairs by 2026. We compared four conservation scenarios: (1) no proposed management; (2) increased control of chick predators (e.g. Corvidae, Laridae, mammals); (3) increased merlin control; and (4) simultaneous chick predator and merlin control. Compared to the null scenario, chick predator control reduced quasi-extinction probability from 11.9% to 8.7%, merlin control more than halved (3.5%) the probability and simultaneous control reduced quasi-extinction probability to 2.6%. Synthesis and applications. Piping plover recovery actions should consider systematic predator control, rather than current ad hoc protocols, especially given the predicted increase in regional merlin abundance. This approach of combining integrated population models with Bayesian population viability analysis to identify limiting components of the population cycle and evaluate alternative management strategies for conservation decision-making shows great utility for aiding recovery of threatened populations.
Data from: Phenotypic integration in an extended phenotype: among‐individual variation in nest‐building traits of the alfalfa leafcutting bee (Megachile rotundata)
Structures such as nests and burrows are an essential component of many organisms' life-cycle and requires a complex sequence of behaviors. Because behaviors can vary consistently among individuals and be correlated with one another, we hypothesized that these structures would 1) show evidence of among-individual variation, 2) be organized into distinct functional modules, and 3) show evidence of trade-offs among functional modules due to limits on energy budgets. We tested these hypotheses using the alfalfa leafcutting bee, Megachile rotundata, a solitary bee and important crop pollinator. M. rotundata constructs complex nests by gathering leaf materials to form a linear series of cells in pre-existing cavities. In this study, we examined variation in the following nest construction traits: reproduction (number of cells per nest and nest length), nest protection (cap length and number of leaves per cap), cell construction (cell size and number of leaves per cell), and cell provisioning (cell mass) from 60 nests. We found a general decline in investment in cell construction and provisioning with each new cell built. In addition, we found evidence for both repeatability and plasticity in cell provisioning with little evidence for trade-offs among traits. Instead, most traits were positively, albeit weakly, correlated (r ~ 0.15), and traits were loosely organized into covarying modules. Our results show that individual differences in nest construction are detectable at a level similar to that of other behavioral traits and that these traits are only weakly integrated. This suggests that nest components are capable of independent evolutionary trajectories.
Data from: Why does offspring size affect performance? Integrating metabolic scaling with life-history theory
Within species, larger offspring typically outperform smaller offspring. While the relationship between offspring size and performance is ubiquitous, the cause of this relationship remains elusive. By linking metabolic and life-history theory, we provide a general explanation for why larger offspring perform better than smaller offspring. Using high-throughput respirometry arrays, we link metabolic rate to offspring size in two species of marine bryozoan. We found that metabolism scales allometrically with offspring size in both species: while larger offspring utilise absolutely more energy than smaller offspring, larger offspring use proportionally less of their maternally-derived energy throughout the dependent, non-feeding phase. The increased metabolic efficiency of larger offspring while dependent on maternal investment may explain offspring size effects –larger offspring reach nutritional independence (feed for themselves) with a higher proportion of energy relative to structure than smaller offspring. These findings offer a potentially universal explanation for why larger offspring tend to perform better than smaller offspring but studies on other taxa are needed.
Data from: Integrating abundance and diet data to improve inferences of food web dynamics
1. Both population abundances and chemical tracers are useful tools for studying consumer-resource interactions. Food web models parameterized with abundances are often used to understand how interactions structure communities and to inform management decisions of complex ecological systems. Unfortunately, collecting abundance data to parameterize these models is often expensive and time-consuming. Another approach is to use chemical tracers to estimate the proportional diets of consumers by relating the tracers in their tissues to those found in their food sources. Although tracer data are often inexpensive to collect relative to abundances, diet proportions provide little information on the per-capita consumption rates of consumers. Here, we show how integrating these data sources can be used to better estimate of consumption rates. 2. Our modeling approach informs traditional multispecies population abundance models using proportional diet data. We used simulations to determine whether integrated food web datasets were more informative than traditional abundance datasets and demonstrated the use of our integrated approach by estimating consumption rates of humpback whales (\textit{Megaptera novaeangliae}) in the western Gulf of Alaska using abundances coupled with stable isotopes as a tracer. 3. Our simulations demonstrated that integrated models improved the ability to resolve alternative hypotheses about the functional response and yielded more precise parameter estimates relative to standard food web models. The integrated data approach was especially informative under low sample sizes or high process variance. Our application of the integrated modeling approach to humpback whale indicated that fish averaged about 25\% of whale diets, though this proportion declined over the course of the study. We also found that traditional abundance model estimates of humpback whale consumption were non-estimable and that the integrated food web model led to estimable consumption rates. 4. Our results show that integrating stable isotopes and abundance datasets provides an exciting way forward for parameterizing multispecies models in data-limited systems. We expect that future developments of these integrated approaches will extend current food web theory by allowing ecologists to study predation dynamics over seasonal time scales and at the individual level.
Data from: The demographic effects of functional traits: an integral projection model approach reveals population-level consequences of reproduction-defense tradeoffs
Quantitatively linking individual variation in functional traits to demography is a necessary step to advance our understanding of trait-based ecological processes. We constructed a population model for Asclepias syriaca to identify how functional traits affect vital rates and population growth and whether tradeoffs in chemical defense and demography alter population growth. Plants with higher foliar cardenolides had lower fiber, cellulose, and lignin levels, as well as decreased sexual and clonal reproduction. Average cardenolide concentrations had the strongest effect on population growth. In both the sexual and clonal pathway, the tradeoff between reproduction and defense affected population growth. We found that both increasing the mean of the distribution of individual plant values for cardenolides and herbivory decreased population growth. However, increasing the variance in both defense and herbivory increased population growth. Functional traits can impact population growth and quantifying individual-level variation in traits should be included in assessments of population-level processes.
Data from: Assessing cetacean populations using integrated population models: an example with Cook Inlet beluga whales
<p>Effective conservation and management of animal populations requires knowledge of abundance and trends. For many species, these quantities are estimated using systematic visual surveys. Additional individual-level data are available for some species. Integrated population modelling (IPM) offers a mechanism for leveraging these datasets into a single estimation framework. IPMs that incorporate both population- and individual-level data have previously been developed for birds, but have rarely been applied to cetaceans. Here, we explore how IPMs can be used to improve the assessment of cetacean populations. We combined three types of data that are typically available for cetaceans of conservation concern: population-level visual survey data, individual-level capture-recapture data, and data on anthropogenic mortality. We used this IPM to estimate the population dynamics of the Cook Inlet population of beluga whales (CIBW; <i>Delphinapterus leucas</i>) as a case study. Our state-space IPM included a population process model and three observational submodels: 1) a group detection model to describe group size estimates from aerial survey data; 2) a capture-recapture model to describe individual photographic capture-recapture data; and 3) a Poisson regression model to describe historical hunting data. The IPM produces biologically plausible estimates of population trajectories consistent with all three datasets. The estimated population growth rate since 2000 is less than expected for a recovering population. The estimated juvenile/adult survival rate is also low compared to other cetacean populations, indicating that low survival may be impeding recovery. This work demonstrates the value of integrating various data sources to assess cetacean populations and serves as an example of how multiple, imperfect datasets can be combined to improve our understanding of a population of interest. The model framework is applicable to other cetacean populations and to other taxa for which similar data types are available.</p>
Data from: Sexual dimorphism, phenotypic integration, and the evolution of head structure in casque-headed lizards
Sexes can differ in features associated with differential reproduction, which can be used during courtship or aggressive encounters. Some traits tend to evolve independently between sexes and emerge as sexually dimorphic within the organismal phenotype. We characterize such a relationship by estimating the phenotypic integration of the head morphology and modularity of the crest in the casque-headed lizards (Corytophanidae). In this clade, some species show extreme sexual dimorphism (e.g., head crests in the genus Basiliscus) while in others, both sexes are monomorphic. To characterize these patterns, we define phenotypic integration at the interspecific level as a pattern or network of traits evidenced by phylogenetically adjusted correlations that persist among species. At this level, modularity is an increased connectedness (e.g., higher correlation) among sections of these networks that persist in a lineage during the evolution of complex phenotypes. To test both concepts, we used phylogenetic geomorphometrics to characterize the head structure of corytophanid lizards, based on a time-calibrated phylogeny that includes candidate fossil ancestors. We found evidence of an older diversification of corytophanids than previously reported (~67 vs. ~23.5 MYA) and show that this clade includes two morphological head architectures: (1) Sexually dimorphic crests present in males that are evolving independently from the rest of the head structure, and (2) full integration of the head morphology in monomorphic species. We propose that both architectures are optimal evolutionary trajectories of the parietal crest bones in the head of these lizards. In sexually dimorphic species, these bones are elongated and thinner, and gave rise to the extended crest used in male courtship displays. In monomorphic species, the parietal crest grew thicker in both sexes to allow for a better insertion of muscles associated with a stronger bite.
Data from: Ultra-fine scale spatially-integrated mapping of habitat and occupancy using structure-from-motion
Organisms respond to and often simultaneously modify their environment. While these interactions are apparent at the landscape extent, the driving mechanisms often occur at very fine spatial scales. Structure-from-Motion (SfM), a computer vision technique, allows the simultaneous mapping of organisms and fine scale habitat, and will greatly improve our understanding of habitat suitability, ecophysiology, and the bi-directional relationship between geomorphology and habitat use. SfM can be used to create high-resolution (centimeter-scale) three-dimensional (3D) habitat models at low cost. These models can capture the abiotic conditions formed by terrain and simultaneously record the position of individual organisms within that terrain. While coloniality is common in seabird species, we have a poor understanding of the extent to which dense breeding aggregations are driven by fine-scale active aggregation or limited suitable habitat. We demonstrate the use of SfM for fine-scale habitat suitability by reconstructing the locations of nests in a gentoo penguin colony and fitting models that explicitly account for conspecific attraction. The resulting digital elevation models (DEMs) are used as covariates in an inhomogeneous hybrid point process model. We find that gentoo penguin nest site selection is a function of the topography of the landscape, but that nests are far more aggregated than would be expected based on terrain alone, suggesting a strong role of behavioral aggregation in driving coloniality in this species. This integrated mapping of organisms and fine scale habitat will greatly improve our understanding of fine-scale habitat suitability, ecophysiology, and the complex bi-directional relationship between geomorphology and habitat use.
Data from: Integrating life history traits into predictive phylogeography
Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine-learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive frameworks due to difficulties inherent to the scoring of trait data across a taxonomically broad set of taxa. We refine predictive frameworks from two North American systems, the inland temperate rainforests of the Pacific Northwest (PNW) and the Southwestern Aridlands (SWAL), by incorporating a number of organismal trait variables. Our results indicate that incorporating life history traits as predictor variables improves the performance of the supervised machine-learning approach to predictive phylogeography, especially for the SWAL system, in which predictions made from only taxonomic and climate variables meets only moderate success. In particular, traits related to reproduction (e.g., reproductive mode; clutch size) and trophic level appear to be particularly informative to the predictive framework. Predictive frameworks offer an important mechanism for integration of organismal trait, environmental data, and genetic data in phylogeographic studies.
Data for: Including Performance Benchmarks into Continuous Integration to Enable DevOps
<p>The DevOps movement intends to improve communication, collaboration, and integration between software developers (Dev) and IT operations professionals (Ops). Automation of software quality assurance is key to DevOps success. We present how automated performance benchmarks may be included into continuous integration. As an example, we report on regression benchmarks for application monitoring frameworks and illustrate the inclusion of automated benchmarks into continuous integration setups.</p> <p>This dataset supplements the paper and contains the raw experimental data for each experiment.</p>
FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure
<p>This upload contains the FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure.</p> <p>If you use the datasets, we would be grateful if you cited the following paper:</p> <p>Zou, C., Zhang, Y., Ouyang, Z. (2016) HSA: integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure. Genome Biology, 17: 40.</p>
Figure 3. from: A first integrative study of the identity and origins of the British Dwarf Pill Millipede populations, Trachysphaera cf. lobata (Diplopoda, Glomerida, Glomeridae) - Biodiversity Data Journal 3: e5176 (09 June 2015) https://doi.org/10.3897/BDJ.3.e5176
Figure 3. - TW18: T.lobata, female, Isle of Wight
Supplementary material 17: Generating Interactive Dashboard Charts Based on Plazi Treatment Data from: Integrating and visualizing primary data from prospective and legacy taxonomic literature - Biodiversity Data Journal 3: e5063 (12 May 2015) https://doi.org/10.3897/BDJ.3.e5063
A brief explanation of how to create and customize interactive charts using data on Plazi.
Cross-disease integration of single-cell RNA sequencing data from lung myeloid cells reveals TAM signature in in vitro model
<p>Single cells from a 3D human cell-based model comprising tumor cell line-derived spheroids, cancer-associated fibroblasts and primary monocytes were dissociated and analyzed using scRNAseq. 4 monocyte donors were used in the 3D model, and 3 monocyte donors were used for 2D differentiation of macrophages.</p>
Data for One Earth publication "Breaching planetary boundaries: Over half of global land area suffers critical losses in functional biosphere integrity"
<p>This repository contains data and processing scripts for the study: Stenzel et al. 2025, One Earth, "Breaching planetary boundaries: Over half of global land area suffers critical losses in functional biosphere integrity".</p>
VCF files and regression analyses for: Assessing fine-scale pondscape connectivity with amphibian eyes: an integrative approach using genomic and capture-mark-recapture data
<p><span>In the face of habitat loss, preserving functional connectivity is essential to maintain genetic diversity and the demographic dynamics required for the viability of biotic communities. This requires knowledge of the dispersal behavior of target species, which can be modeled as kernels, or probability density functions of dispersal distances at increasing geographic distances. We present an integrative approach to investigate the relationships between genetic connectivity and demographic parameters in organisms with low vagility focusing on five syntopic pond-breeding amphibians. We genotyped 1,056 individuals of two anuran and three urodele species (1,732–3,913 SNPs per species) from populations located in a landscape comprising 64 ponds to characterize fine-scale genetic structure in a comparative framework and combined this genetic data with information obtained in a previous two-year capture-mark-recapture (CMR) study. Specifically, we contrasted graphs reconstructed from genomic data with connectivity graphs based on dispersal kernels and demographic information obtained from CMR data from previous studies and assessed the effects of population size, population density, geographical distances, inverse movement probabilities and the presence of habitat patches potentially functioning as stepping stones on genetic differentiation. Our results suggest a significant influence of local population sizes on patterns of genetic connectivity at small spatial scales. In addition, m</span><span>ovement records and cluster-derived kernels provide robust inferences on most likely dispersal paths that are consistent with </span><span>genomic inferences on genetic connectivity. The integration of genetic and CMR data holds great potential for understanding genetic connectivity at spatial scales relevant to individual organisms, with applications for the implementation of management actions at the landscape level. </span></p>
Data from: Pan-evolutionary and regulatory genome architecture delineated by integrated macro- and microsynteny approach
<p>Based on the published algorithms or tools developed by our and other groups, we introduce a detailed protocol for the most comprehensive and up-to-date genome synteny pipeline (called PanSyn) and provides step-by-step instructions as well as application examples for demonstrating how to use it. PanSyn pipeline includes three major modules (microsynteny analysis, macrosynteny analysis, and integrated micro & macro analysis). PanSyn not only fills a gap of lacking a user-friendly, highly-customized tool for genome macrosynteny analysis but also allows for integrated pan-evolutionary and regulatory analysis of genome microsyntenty and macrosynteny which are not yet available in any public synteny software or tools. PanSyn has been tested under Linux system. PanSyn has multiple subroutines. Users only need to simply modify the configuration file and corresponding command parameters to execute them. Outputs include vector diagrams that are suitable for custom modification. <br> </p>
The Arabidopsis Leaf Quantitative Atlas: a cellular and subcellular mapping through unified data integration
<p>Additional data accompanying Tolleter et. al. The Arabidopsis Leaf Quantitative Atlas: a cellular and subcellular mapping through unified data integration <em>Quantitative Plant Biology</em>. 2024.</p> <p>Quantitative analyses and models are required to connect a plant's cellular organization with its metabolism. However, quantitative data are often scattered over multiple studies, and finding such data and converting them into useful information is time consuming. Consequently, there is a need to centralize the available data and to highlight the remaining knowledge gaps. Here, we present a step-by-step approach to manually extract quantitative data from various information sources, and to unify the data format. First, data from Arabidopsis leaf were collated, checked for consistency and correctness, and curated by cross-checking sources. Second, quantitative data were combined by applying calculation rules. They were then integrated into a unique comprehensive, referenced, modifiable and reusable data compendium representing an Arabidopsis reference leaf. This atlas contains the metrics of the 15 cell types found in leaves at the cellular and subcellular levels.</p> <p>Table_S1_2023_12_12.xlsx: All supplementary data relating to the Arabidopsis Leaf Quantitative Atlas</p> <p>ChloroKB data export.ipynb: A jupyter notebook containing code to convert Quantitative_data_2023_12_13.xlsx (from http://umr5558-chlorokb.univ-lyon1.fr:8080/ChloroKB_Grails/static/images/csv/Quantitative_data.csv) into Table_S5_2023_12_13.xlsx.</p> <p>Variable_conversion_table.xlsx ,Localisation_conversion_table.xlsx, Localisation_conversion_table_isolated_organelles.xlsx: Conversion factors required by ChloroKB data export.ipynb for unit conversion. </p>
ScienceDex guides
Understand access before you commit
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.