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21,983 results for “UNITE”
Data from: Collection methods and distribution modeling for Strepsiptera in the United States
<p>The twisted-wing parasite order (Strepsiptera Kirby, 1813) is difficult to study due to the complexity of strepsipteran life histories, small body sizes, and a lack of accessible distribution data for most species. Here, we present a review of the strepsipteran species known from New York State. We also demonstrate successful collection methods and a survey of species carried out in an old-growth deciduous forest dominated by native New York species (Black Rock Forest, Cornwall, NY) and a private site in the Catskill Mountains (Shandaken, NY). Additionally, we model suitable habitat for Strepsiptera in the United States with species distribution modeling. We base our models on host distributions and climatic variables to inform predictions of where these twisted-wing parasites are likely to be found. With this work, we hope to provide a useful reference for the future collection of Strepsiptera.</p>
Data from: Rates and drivers of carbon emissions from hydropower reservoirs in the southeastern United States
<p>Reservoirs are a significant source of carbon (C) to the atmosphere, but their emission rates vary in space and time. We compared C emissions via diffusive and ebullitive pathways at several stations in six large hydropower reservoirs in the southeastern US that were previously sampled in summer 2012. We found that carbon dioxide (<span>CO<sub>2</sub></span>) diffusion was the dominant flux pathway during 2012 and 2022, with only three exceptions where methane (<span>CH<sub>4</sub></span>) diffusion or <span>CH<sub>4</sub></span> ebullition dominated. <span>CH<sub>4</sub></span> diffusion rates were positively associated with water temperature. However, we found no clear predictors of <span>CH<sub>4</sub></span> ebullition, which had extremely high variability, with rates ranging from 0 to 739 mg C m<sup>-2</sup> day<sup>-1</sup>. For <span>CO<sub>2</sub></span> diffusion, the direction of the flux shifted between 2012 and 2022, where all but three stations across all reservoirs emitted <span>CO<sub>2</sub></span> in summer 2012, but every station sequestered <span>CO<sub>2</sub></span> in summer 2022. Here, indicators of greater algal production were associated with <span>CO<sub>2</sub></span> sequestration, including surface chlorophyll-<em>a</em> concentration, surface dissolved oxygen saturation, and pH. Additional sampling campaigns outside the summer season highlighted the importance of seasonal phenology in primary production on the direction of <span>CO<sub>2</sub></span> diffusive fluxes, which shifted to positive <span>CO<sub>2</sub></span> fluxes by the end of August as productivity decreased. Our results demonstrate the importance of capturing <span>CO<sub>2</sub></span> sequestration in field and modelling measurements and understanding the seasonal drivers of these estimates. Measuring C emissions from multiple pathways in reservoirs and understanding their spatiotemporal responses and variability is vital to reducing uncertainties in global upscaling efforts.</p>
Bumble bee responses to climate and landscapes: Investigating habitat associations and species assemblages across geographic regions in the United States of America
<p><span>Bumble bees are integral pollinators of native and cultivated plant communities, but species are undergoing significant changes in range and abundance on a global scale. Climate change and land cover alteration are key drivers in pollinator declines; however, limited research has evaluated the cumulative effects of these factors on bumble bee<em> </em>assemblages. This study tests bumble bee assemblage (calculated as richness and abundance) responses to climate and land use by <span>modeling </span>species-specific habitat requirements, and assemblage-level responses across geographic regions. <span>We integrated species richness, abundance, and distribution data for 18 bumble bee species with site-specific bioclimatic, landscape composition, and landscape configuration data to evaluate</span> the effects of multiple environmental stressors <span>on bumble bee assemblages throughout</span> 433 agricultural fields in<span> Florida, Indiana, Kansas, Kentucky, Maryland, South Carolina, Utah, Virginia, and West Virginia from 2018 to 2020. Distinct east vs. west groupings emerged when evaluating species-specific habitat associations, prompting a detailed evaluation of bumble bee assemblages by geographic region. Maximum temperature of warmest month and precipitation of driest month had a positive impact on bumble bee assemblages in the Corn Belt/Appalachian/northeast, southeast, and northern plains regions, but a negative impact in the mountain region. Further, </span>forest land cover surrounding agricultural fields was highlighted as supporting more rich and abundant bumble bee assemblages<span>. Overall, climate and land use combine to drive bumble bee assemblages, but how those processes operate is idiosyncratic and spatially contingent across regions. From these findings, we suggested regionally specific management practices to best support rich and abundant bumble bee assemblages in agroecosystems. </span>Results from this study contribute to a better understanding of climate and landscape factors affecting bumble bees and their habitats throughout the USA. </span></p>
Remotely sensed crown nutrient concentrations modulate forest reproduction across the contiguous United States
<p>Global forests are increasingly lost to climate change, disturbance, and human management. Evaluating forests' capacities to regenerate and colonize new habitats has to start with the seed production of individual trees and how it depends on nutrient access. Studies on the linkage between reproduction and foliar nutrients are limited to a few locations and few species, due to the large investment needed for field measurements on both variables. We synthesized tree fecundity estimates from the Masting Inference and Forecasting (MASTIF) network with crown nutrient concentrations from hyperspectral remote sensing at the National Ecological Observatory Network (NEON) across the United States. We evaluated the relationships between seed production and foliar nutrients for 56,544 tree-years from 26 species at individual and community scales. We found a prevalent association between high foliar phosphorous (P) concentration and low individual seed production (ISP) at the continental scale. With-species coefficients to nitrogen (N), potassium (K), calcium (Ca), and magnesium (Mg) are related to species differences in nutrient demand, with distinct biogeographic patterns. Community seed production (CSP) decreased four orders of magnitude from the lowest to the highest foliar P. This first study on hyperspectral imagery indicates promise for future monitoring of reproductive potential. The fact that both ISP and CSP decline at high foliar P levels has immediate applications in improving forest demographic and regeneration models by providing more realistic nutrient effects at multiple scales.</p>
Identifying Episodes of Hypovigilance in Intensive Care Units Using Routine Physiological Parameters and Artificial Intelligence: a Derivation Study. Open Code and Dataset
<p>The purpose of this project is to detect hypogilance using the EVEILS database.</p> <p>Database is ICU data from Hôtel-Dieu De Lévis , Québec, Canada. Please cite us if you use either the data or code. </p> <p>This code was written during Raphaëlle Giguère Msc in Computer Science. The goal of her project is to detect hypovigilance using machine learning in the ICU. In this repository, you have the data set before preprocessing:</p> <ul> <li>df_hypovigilance : Contains the hours, date and value of the vigilance level, using either the RASS or Ramsay and already converted using the thresholds shown in the paper.</li> <li>raw_df : Contains the raw values from the gateway for each participant. All of the identifying values have been removed.</li> </ul> <p>At the end of the preprocessing_anonymous script, you should generate a new dataset called "df_final". This dataset is used for the training_model script.</p> <p>The cross validation employs groups of random size meaning the results might differ from time to time but should stay consistent.</p> <p> </p>
Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States: Data
<p>The data in this repository are associated with the manuscript from Huber et al. (2024) titled "Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States" in the Journal of Geophysical Research: Atmospheres. Additional information regarding these data can be found in the attached readme file.</p>
Figure 4 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 4. Mennerotodus mackayi sp. nov. lower-dentition hypodigm, Paleocene (Danian) Pine Barren Member of the Clayton Formation, site ALn-13, Lowndes County, Alabama, USA. (a–d) MSC 42407, first lower left anterior tooth (paratype). (a) Distal view. (b) Lingual view. (c) Labial view. (d) Basal view. (e) Close-up of distal cusplet. (f–i) MSC 42405, second lower right anterior tooth (paratype). (f) Distal view. (g) Lingual view. (h) Labial view. (i) Basal view. (j) Close-up of mesial cusplet. (k–n) MSC 42410, third lower right anterior tooth (paratype). (k) Mesial view. (l) Lingual view. (m) Labial view. (n) Basal view. (o) Close-up of mesial denticle and cusplet. (p–s) MSC 42406, fourth lower left anterior tooth (paratype; reversed). (p) Mesial view. (q) Lingual view. (r) Labial view. (s) Basal view. (t) Close-up of mesial denticle and cusplet. (u–x) MSC 42409, lower right lateral tooth (paratype). (u) Mesial view. (v) Lingual view. (w) Labial view. (x) Basal view. (y) Close-up of mesial denticle. (z–ad) MSC 42632, lower right posterior tooth. (z) Close-up of distal cusplet. (aa) Lingual view. (ab) Labial view. (ac) Mesial view. (ad) Basal view. Labial at bottom in (d), (i), (n), (s), (x), and (ad). Scale bars = 5 mm.
Figure 1 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 1. Generalized location and surface stratigraphy of site ALn-13, Lowndes County, AL, USA. (a) Geographic maps showing the location of site ALn-13 in country, state, and county contexts. (b) Danian surface stratigraphy in Alabama, USA. Shaded areas on the stratigraphic chart represent unconformities.
Figure 7 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 7. Lingual view of right dentitions of Carcharias taurus, Mennerotodus mackayi sp. nov., and Mennerotodus parmleyi sp. nov. (a–b) C. taurus, unnumbered specimen from Gordon Hubbell Collection, natural tooth set. (a) Upper dentition. (b) Lower dentition. (c–d) M. mackayi sp. nov., artificial tooth set. (c) M. mackayi sp. nov. upper dentition, from left to right: MSC 42411, paratype; MSC 42408, paratype; MSC 42413, paratype (reversed); MSC 42495; MSC 42718; MSC 42412, holotype; MSC 42421; MSC 42494; MSC 42497; MSC 42416 (reversed). (d) M. mackayi sp. nov. lower dentition, from left to right: MSC 42407, paratype; MSC 42405, paratype (reversed); MSC 42410, paratype; MSC 42406, paratype (reversed); MSC 42719 (reversed); MSC 42409, paratype; MSC 42500; MSC 42498; MSC 42501; MSC 42632. (e–f) M. parmleyi sp. nov., artificial tooth set. (e) M. parmleyi sp. nov. upper dentition, from left to right: SC2013.44.117, paratype; SC2013.44.119, paratype (reversed); SC2013.44.122, paratype (reversed); SC2013.44.120, paratype (reversed); SC2004.34.175, holotype (reversed); SC2004.34.178; SC2004.34.179; SC2004.34.177 (reversed); SC2013.44.1123 (reversed); SC2013.44.153; SC2004.34.38. (f) M. parmleyi sp. nov. lower dentition, from left to right: SC2013.44.128, paratype; SC2013.44.130, paratype; SC2013.44.132, paratype; SC2004.34.182, paratype; SC2013.44.157, paratype; SC2004.34.176 (reversed); SC2013.44.154; SC2013.44.155; SC2013.44.156; SC2004.34.181, paratype. Scale bars = 5 mm.
Figure 6 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 6. Mennerotodus parmleyi sp. nov. lower-dentition hypodigm, Eocene (Bartonian) Clinchfield Formation, Hardie Mine, Wilkinson County, Georgia, USA. (a–e) SC2013.44.128, first lower right anterior tooth (paratype). (a) Close-up of distal cusplet. (b) Basal view. (c) Labial view. (d) Lingual view. (e) Distal view. (f–j) SC2013.44.130, second lower left anterior tooth (paratype). (f) Close-up of mesial cusplet. (g) Basal view. (h) Labial view. i) Lingual view. (j) Mesial view. (k–o) SC2013.44.132, lower right anterior tooth (paratype). (k) Closeup of distal cusplet. (l) Basal view. (m) Labial view. (n) Lingual view. (o) Mesial view. (p–t) SC2004.34.182, fourth lower left anterior tooth (paratype). (p) Close-up of mesial cusplet. (q) Basal view. (r) Labial view. (s) Lingual view. (t) Mesial view. (u–y) SC2013.44.157, lower left lateral tooth (paratype). (u) Close-up of mesial cusplet. (v) Basal view. (w) Labial view. (x) Lingual view. (y) Distal view. (z– ad) SC2004.34.181, lower right posterior tooth (paratype). (z) Close-up of distal cusplet. (aa) Basal view. (ab) Lingual view. (ac) Labial view. (ad) Mesial view. Labial at bottom in (b), (g), (l), (q), (v), and (aa). Scale bars = 5 mm.
Figure 5 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 5. Mennerotodus parmleyi sp. nov. upper-dentition hypodigm, Eocene (Bartonian) Clinchfield Formation, Hardie Mine, Wilkinson County, Georgia, USA. (a–e) SC2013.44.117, first upper left anterior tooth (paratype). (a) Basal view. (b) Labial view. (c) Lingual view. (d) Mesial view. (e) Close-up of distal cusplet. (f–j) SC2013.44.119, second upper left anterior tooth (paratype). (f) Basal view. (g) Labial view. (h) Lingual view. (i) Mesial view. (j) Close-up of mesial cusplet. (k–o) SC2013.44.122, third upper left anterior tooth (paratype). (k) Basal view. (l) Labial view. (m) Lingual view. (n) Mesial view. (o) Close-up of mesial cusplet. (p–t) SC2013.44.120, upper left intermediate tooth (paratype). (p) Close-up of mesial cusplet. (q) Labial view. (r) Lingual view. (s) Mesial view. (t) Basal view. (u–y) SC2004.34.175, upper left lateral tooth (holotype). (u) Close-up of mesial denticle and cusplets. (v) Labial view. (w) Lingual view. (x) Mesial view. (y) Basal view. Labial at top in (a), (f), (k), (t), and (y). Scale bars = 5 mm.
Figure 2 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 2. Generalized location and surface stratigraphy of the Hardie Mine site, Wilkinson County, GA, USA. (a) Geographic maps showing the location of the Hardie Mine site in country, state, and county contexts. (b) Middle to late Eocene lithostratigraphic units formerly exposed in the mine. Shaded areas on the stratigraphic chart represent unconformities.
Figure 3 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 3. Mennerotodus mackayi sp. nov. upper-dentition hypodigm, Paleocene (Danian) Pine Barren Member of the Clayton Formation, site ALn-13, Lowndes County, Alabama, USA. (a–e) MSC 42411, first upper right anterior tooth (paratype). (a) Basal view. (b) Labial view. (c) Lingual view. (d) Mesial view. (e) Close-up of distal cusplet. (f–j) MSC 42408, second upper right anterior tooth (paratype). (f) Basal view. (g) Labial view. (h) Lingual view. (i) Mesial view. (j) Close-up of distal cusplet and denticle. (k–o) MSC 42413, third upper left anterior tooth (paratype). (k) Basal view. (l) Labial view. (m) Lingual view. (n) Mesial view. (o) Close-up of distal cusplet. (p–t) MSC 42412, upper lateral tooth (holotype). (p) Basal view. (q) Labial view. (r) Lingual view. (s) Mesial view. (t) Close-up of distal cusplet and denticle. Labial at top in (a), (f), (k), and (p). Scale bars = 5 mm.
Figure 9 in Two new species of Mennerotodus Zhelezko, 1994 (Chondrichthyes: Lamniformes: Odontaspididae), from the Paleogene of the southeastern United States
Figure 9. Variation in denticle and cusplet morphology on Mennerotodus teeth. (a–f) Mennerotodus parmleyi sp. nov. (a) SC 2013.44.125, upper right lateral tooth in labial view. (b) SC 2004.34.19, upper left lateral tooth in labial view (reversed). (c) SC 2013.44.78, fourth lower left anterior tooth in labial view. (d) SC 2004.34.185, upper right lateral tooth in labial view. (e) SC 2013.44.158, upper left lateral tooth in labial view. (f) SC2013.44.151, second lower right anterior tooth in mesial view. (g–l) Mennerotodus mackayi sp. nov., teeth in labial view. (g) MSC 42408, second upper right anterior tooth (paratype; reversed). (h) MSC 42412, upper left lateral tooth (holotype; reversed). (i) MSC 42410, third lower right anterior tooth (paratype; reversed). (j) MSC 42405, second lower right anterior tooth (paratype; reversed). (k) MSC 42406, fourth lower left anterior tooth (paratype). (l) MSC 42409, lower right lateral tooth (paratype; reversed).
The Provincelands of Cape Cod National Seashore, Barnstable County, Massachusetts, USA. The reddish vegetation in the center of the photo is a cranberry (Vaccinium macrocarpon) bog, a wetland used for breeding by the Fowler's toad. The surrounding landscape is ideal for the Fowler's toad and supports one of the largest populations of this species in the United States. The landscape contains a patchwork of sand, pitch pine (Pinus rigida), scrub oak (Quercus ilicifolia), and dune grass (Ammophila breviligulata). Photo by Rebecca Flaherty. in Fowler's Toad (Anaxyrus fowleri) occupancy in the southern mid-Atlantic, USA
The Provincelands of Cape Cod National Seashore, Barnstable County, Massachusetts, USA. The reddish vegetation in the center of the photo is a cranberry (Vaccinium macrocarpon) bog, a wetland used for breeding by the Fowler's toad. The surrounding landscape is ideal for the Fowler's toad and supports one of the largest populations of this species in the United States. The landscape contains a patchwork of sand, pitch pine (Pinus rigida), scrub oak (Quercus ilicifolia), and dune grass (Ammophila breviligulata). Photo by Rebecca Flaherty.
Synchronously recorded gait kinematic data with Inertial Measurement Units and a photogrammetry system for a validation assessment
<h3>Description</h3> <p>A gait database of 32 healthy adult subjects was built , volunteers were between 20 and 63 y.o. (33.64 ± 12.44) and 71.88% were females. Every individual underwent a barefoot walking test recorded simultaneously with Inertial Measurement Units (IMUs) and the photogrammetry system Vicon. The dataset contains the kinematic gait information of the hip, knee, and ankle joints in the three planes of motion: sagittal, frontal, and transversal. </p> <p>The signals recorded by the IMUs are referred to as I(t) and were captured with a sampling frequency of 50 Hz, and those recorded by the photogrammetry system are called V(t) and were captured with a sampling frequency of 100 Hz. To perform a comparative study of both systems, the V(t) signals must be resampled to 50 Hz. Then, the delay between the two signals must be corrected to align them. Finally, gait cycles can be extracted for each pair of trials following the data information provided, obtaining a pair of waveforms for each gait cycle [I(t), V(t)]. A total of 268 synchronous gait cycles [I(t), V(t)] can be recovered and analyzed in the three planes of motion per limb.</p> <h3>Data information</h3> <ul> <li><em>raw_data</em>: folder containing the 32 subjects raw kinematic signals recorded with IMUs (sampling frequency 50 Hz) and photogrammetry system (sampling frequency 100 Hz) synchronously.<br> <ul> <li>For IMUs records: <ul> <li>Z: sagittal plane.</li> <li>X: frontal plane.</li> <li>Y: transversal plane.</li> </ul> </li> <li>For photogrammetry system records: <ul> <li>X: sagittal plane.</li> <li>Y: frontal plane.</li> <li>Z: transversal plane.</li> </ul> </li> </ul> </li> </ul> <ul> <li><em>captures_information.xlsx</em>: table containing the delay correction and the samples corresponding to the events of the gait cycles. The delay correction is the number of samples for which each photogrammetry signal V(t), after being resampled to 50 Hz, must be moved to be completely aligned with its synchronous IMUs signal couple I(t). <ul> <li>If the delay is positive (+) the V(t) signal must be delayed by adding zeros at the beginning.</li> <li>If the delay is negative (-) the V(t) signal must be moved forward by removing zeros at the beginning.</li> </ul> </li> </ul>
Figure 2 in Seed-shattering phenology at soybean harvest of economically important weeds in multiple regions of the United States. Part 1: Broadleaf species
Figure 2. Cumulative percent shatter over four time periods (soybean physiological maturity, maturity þ 2 wk,maturity þ 3 wk, maturity þ 4 wk) for each species.The darker the bar, the greater percent of sampled site-years that corresponded to the percent shatter value. This normalizes across species with different sampling efforts. Species sampled in just a single site-year are indicated by a single black square, which represents 100% of the sampling effort. Species are denoted by their EPPO codes.
Figure 3 in Seed-shattering phenology at soybean harvest of economically important weeds in multiple regions of the United States. Part 1: Broadleaf species
Figure 3. Cumulative percent seed shatter for all species from planting date to soybean physiological maturity (black vertical line) for each state in 2016 and 2017. Species are denoted by their EPPO codes.
Figure 1. Heat map indicating the cumulative percent seed shatter across the participating states for a in Seed-shattering phenology at soybean harvest of economically important weeds in multiple regions of the United States. Part 1: Broadleaf species
Figure 1. Heat map indicating the cumulative percent seed shatter across the participating states for a window starting from soybean physiological maturity to 4 wk past maturity in 2016 and 2017. States were included in these maps only if they conducted sampling during the week indicated (e.g., In 2017, Arkansas sampled on October 2, October 18, and November 3, none of which are within ±3 d of the October 10 maturity date or maturity þ2 wk on October 24 in the state that year. Hence only data from maturity þ3 wk are for Arkansas for 2017.)
Fig. 3 A in Comparative analysis of metacyclogenesis and infection curves in different discrete typing units of Trypanosoma cruzi
Fig. 3 A The production of amastigotes per cell in T. cruzi infections provides insight into the intracellular dynamics of T. cruzi within host cells. B Percentage of uninfected cells observed along the infection curves, susceptibility dynamics, and infection progression, highlighting variations in the percentage of uninfected cells throughout the experimental period. C Release of cell-derived trypomastigotes during infection of Vero cells, Neubauer chamber count
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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.