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10,016 results for “Observation”
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données arachnologiques de contributeurs étrangers.
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données arachnologiques de contributeurs étrangers". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/352611b5-758a-422f-bcd4-dae9246fbf57">https://bionomia.net/dataset/352611b5-758a-422f-bcd4-dae9246fbf57</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/352611b5-758a-422f-bcd4-dae9246fbf57">https://gbif.org/dataset/352611b5-758a-422f-bcd4-dae9246fbf57</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données de LACOSTE Frédéric (SAPROX).
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données de LACOSTE Frédéric (SAPROX)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a83f9054-983d-473b-8faf-a8076296f429">https://bionomia.net/dataset/a83f9054-983d-473b-8faf-a8076296f429</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a83f9054-983d-473b-8faf-a8076296f429">https://gbif.org/dataset/a83f9054-983d-473b-8faf-a8076296f429</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Friches urbaines de Marseille.
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Friches urbaines de Marseille". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/322aa8be-9ead-4b5e-849c-6c8cbce9a101">https://bionomia.net/dataset/322aa8be-9ead-4b5e-849c-6c8cbce9a101</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/322aa8be-9ead-4b5e-849c-6c8cbce9a101">https://gbif.org/dataset/322aa8be-9ead-4b5e-849c-6c8cbce9a101</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données liées à des déterminations effectuées par DUSOULIER François.
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données liées à des déterminations effectuées par DUSOULIER François". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/ce91ad1f-989f-47ad-a55e-81d866a1fa72">https://bionomia.net/dataset/ce91ad1f-989f-47ad-a55e-81d866a1fa72</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/ce91ad1f-989f-47ad-a55e-81d866a1fa72">https://gbif.org/dataset/ce91ad1f-989f-47ad-a55e-81d866a1fa72</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données naturalistes de Lilian LEONARD.
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données naturalistes de Lilian LEONARD". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/abf9b70d-8d79-4444-ba75-7aa8039f55bc">https://bionomia.net/dataset/abf9b70d-8d79-4444-ba75-7aa8039f55bc</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/abf9b70d-8d79-4444-ba75-7aa8039f55bc">https://gbif.org/dataset/abf9b70d-8d79-4444-ba75-7aa8039f55bc</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données bibliographiques saisies et analysées par DUSOULIER François.
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données bibliographiques saisies et analysées par DUSOULIER François". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a32bf1ee-335d-42c4-bb00-76cd28b68a83">https://bionomia.net/dataset/a32bf1ee-335d-42c4-bb00-76cd28b68a83</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a32bf1ee-335d-42c4-bb00-76cd28b68a83">https://gbif.org/dataset/a32bf1ee-335d-42c4-bb00-76cd28b68a83</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données arachnologiques de LEDOUX Jean-Claude.
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données arachnologiques de LEDOUX Jean-Claude". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/aea6d6c7-9d6a-43b0-9d55-0d03cbe991ce">https://bionomia.net/dataset/aea6d6c7-9d6a-43b0-9d55-0d03cbe991ce</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/aea6d6c7-9d6a-43b0-9d55-0d03cbe991ce">https://gbif.org/dataset/aea6d6c7-9d6a-43b0-9d55-0d03cbe991ce</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Études entomologiques pilotées par la Société entomologique Antilles-Guyane - Observations naturalistes et collection entomologique en Guyane (SEAG, Julien Touroult).
Natural history specimen data linked to collectors and determiners held within, "Études entomologiques pilotées par la Société entomologique Antilles-Guyane - Observations naturalistes et collection entomologique en Guyane (SEAG, Julien Touroult)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a73d9e11-def6-4644-88fd-8cc40d9b8ffe">https://bionomia.net/dataset/a73d9e11-def6-4644-88fd-8cc40d9b8ffe</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a73d9e11-def6-4644-88fd-8cc40d9b8ffe">https://gbif.org/dataset/a73d9e11-def6-4644-88fd-8cc40d9b8ffe</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données naturalistes de Pascal Dupont.
Natural history specimen data linked to collectors and determiners held within, "CardObs : Observations naturalistes issues de l'outil de saisie et gestion CardObs mis en place par le Service du Patrimoine Naturel (MNHN) / UMS PatriNat (OFB - CNRS - MNHN) - Données naturalistes de Pascal Dupont". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/eae096ac-c585-4234-99cb-b32e7c517604">https://bionomia.net/dataset/eae096ac-c585-4234-99cb-b32e7c517604</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/eae096ac-c585-4234-99cb-b32e7c517604">https://gbif.org/dataset/eae096ac-c585-4234-99cb-b32e7c517604</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Lajitietokeskus/FinBIF - Notebook, general observations.
Natural history specimen data linked to collectors and determiners held within, "Lajitietokeskus/FinBIF - Notebook, general observations". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/df12ca07-f133-4550-ab3b-fde13f0e76ba">https://bionomia.net/dataset/df12ca07-f133-4550-ab3b-fde13f0e76ba</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/df12ca07-f133-4550-ab3b-fde13f0e76ba">https://gbif.org/dataset/df12ca07-f133-4550-ab3b-fde13f0e76ba</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Artportalen (Swedish Species Observation System).
Natural history specimen data linked to collectors and determiners held within, "Artportalen (Swedish Species Observation System)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/38b4c89f-584c-41bb-bd8f-cd1def33e92f">https://bionomia.net/dataset/38b4c89f-584c-41bb-bd8f-cd1def33e92f</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/38b4c89f-584c-41bb-bd8f-cd1def33e92f">https://gbif.org/dataset/38b4c89f-584c-41bb-bd8f-cd1def33e92f</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: New Morphological Observations And Phylogenetic Placement Of Capnia Shasta (Plecoptera: Capniidae).
Natural history specimen data linked to collectors and determiners held within, "New Morphological Observations And Phylogenetic Placement Of Capnia Shasta (Plecoptera: Capniidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/e65a83c9-69bc-4c11-bc50-16e60a41d706">https://bionomia.net/dataset/e65a83c9-69bc-4c11-bc50-16e60a41d706</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/e65a83c9-69bc-4c11-bc50-16e60a41d706">https://gbif.org/dataset/e65a83c9-69bc-4c11-bc50-16e60a41d706</a>. Formatted as a Frictionless Data package.
Output from Linear Inverse Models (LIMs) emulating the observed spatiotemporal statistics of Australian precipitation and global sea surface temperatures
<p><strong>Data repository for <em>How unusual was Australia's 2017–2019 Tinderbox Drought?</em></strong></p> <p>This repository contains LIM data underpinning the paper <em>How unusual was Australia's 2017–2019 Tinderbox Drought?</em> [doi: 10.1016/j.wace.2024.100734 <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.wace.2024.100734" target="_blank" rel="noopener">available online in <em>Weather and Climate Extremes</em> 17 October 2024</a>]. All other datasets used in the paper are freely available online (see Data Availability statement in the paper for details). </p> <p>The repository contains 12 netcdf files, which together comprise the Linear Inverse Model (LIM) outputs described in the paper. <strong>In all cases, please see the paper for important details on the data and how they were produced.</strong> </p> <p><em>Global LIMs</em></p> <ul> <li>`LIM5000_COBE-globalSST_prec-anoms-aus_monthly.nc` <ul> <li>contains 5000 years of emulated Australian precipitation variability, modelled using Australian rainfall data from the Australian Gridded Climate Dataset v2 (AGCD) and global SST data from 'Centennial in situ Observation-Based Estimates of the Variability of SST and Marine Meteorological Variables version 2' (COBE)</li> </ul> </li> <li>`LIM5000_ERSST-globalSST_prec-anoms-aus_monthly.nc` <ul> <li>contains 5000 years of emulated Australian precipitation variability, modelled using Australian rainfall data from the AGCD and global SST data from US National Oceanic and Atmospheric Administration 'Extended Reconstruction SST version 5’ (ERSST)</li> </ul> </li> <li>`LIM5000_COBE-globalSST_SST-anoms-global_monthly.nc` <ul> <li>contains 5000 years of emulated global SST variability, modelled using global SST data from COBE</li> </ul> </li> <li>`LIM5000_ERSST-globalSST_SST-anoms-global_monthly.nc` <ul> <li>contains 5000 years of emulated global SST variability, modelled using global SST data from ERSST</li> </ul> </li> </ul> <p><em>Tropical Pacific Ocean LIMs</em></p> <ul> <li>`LIM5000_COBE-TropicalPacificSST_prec-anoms-aus_monthly.nc` <ul> <li>contains 5000 years of emulated Australian precipitation variability, modelled using Australian rainfall data from the AGCD and tropical Pacific Ocean SST data from COBE</li> </ul> </li> <li>`LIM5000_ERSST-TropicalPacificSST_prec-anoms-aus_monthly.nc` <ul> <li>contains 5000 years of emulated Australian precipitation variability, modelled using Australian rainfall data from the AGCD and tropical Pacific Ocean SST data from ERSST</li> </ul> </li> <li>`LIM5000_COBE-TropicalPacificSST_SST-anoms-TropicalPacific_monthly.nc` <ul> <li>contains 5000 years of emulated global SST variability, modelled using tropical Pacific Ocean SST data from COBE</li> </ul> </li> <li>`LIM5000_ERSST-TropicalPacificSST_SST-anoms-TropicalPacific_monthly.nc` <ul> <li>contains 5000 years of emulated global SST variability, modelled using tropical Pacific Ocean SST data from ERSST</li> </ul> </li> </ul> <p><em>Indian Ocean LIMs</em></p> <ul> <li>`LIM5000_COBE-IndianOceanSST_prec-anoms-aus_monthly.nc` <ul> <li>contains 5000 years of emulated Australian precipitation variability, modelled using Australian rainfall data from the AGCD and Indian Ocean SST data from COBE</li> </ul> </li> <li>`LIM5000_ERSST-IndianOceanSST_prec-anoms-aus_monthly.nc` <ul> <li>contains 5000 years of emulated Australian precipitation variability, modelled using Australian rainfall data from the AGCD and Indian Ocean SST data from ERSST</li> </ul> </li> <li>`LIM5000_COBE-IndianOceanSST_SST-anoms-TropicalPacific_monthly.nc` <ul> <li>contains 5000 years of emulated global SST variability, modelled using Indian Ocean SST data from COBE</li> </ul> </li> <li>`LIM5000_ERSST-IndianOceanSST_SST-anoms-TropicalPacific_monthly.nc` <ul> <li>contains 5000 years of emulated global SST variability, modelled using Indian Ocean SST data from ERSST</li> </ul> </li> </ul> <p><strong>How to cite this</strong> <strong>repository</strong></p> <p>If using this data, please cite the original publication, available from <a href="https://www.sciencedirect.com/science/article/pii/S2212094724000951" target="_blank" rel="noopener">https://www.sciencedirect.com/science/article/pii/S2212094724000951.</a> </p>
Retrievals of aerosol optical, componential, and radiative properties from joint observations of sun photometer and Lidar using GRASP algorithm
<p>The site location is <span>114°21′E, 30°32′N (Central China). The time period is from 2021.07 to 2022.08.</span></p> <p><span>Data includes AOD (all sequences), SSA, ASY, ASD, CRI (only retrieved from sky irradiance), components (black carbon, brown carbon, dust, iron oxide, water-soluble inorganic salt and water), and vertical profiles of shapes of total extinction, fine-mode extinction, and coarse-mode extinction.</span></p>
TreeGOER Holdridge Life Zone Distributions: Observations for 48,129 tree species across 45 historical (1901-1920) and contemporary (1979-2013) terrestrial life zones
<p><strong>TreeGOER (Tree Globally Observed Environmental Ranges)</strong> is a database that documents the environmental ranges (minimum, maximum, median, mean and 5%, 25%, 75% and 95% quantiles) for 48,129 tree species and for 51 environmental variables, including 38 bioclimatic variables, 8 soil variables and 3 topographic variables. TreeGOER is available from the following Zenodo archives: <a href="https://doi.org/10.5281/zenodo.7922927">https://doi.org/10.5281/zenodo.7922927.</a></p> <p>The TreeGOER ranges were calculated after cleaning occurrence records and standardizing species names with the <a href="https://bsapubs.onlinelibrary.wiley.com/doi/10.1002/aps3.11388">WorldFlora</a> R package to <a href="https://onlinelibrary.wiley.com/doi/10.1002/tax.12373">World Flora Online</a> or the <a href="https://www.nature.com/articles/s41597-021-00997-6">World Checklist of Vascular Plants</a> for a global GBIF occurrence download of 44,267,164 occurrences (GBIF.org 2021 <strong>GBIF Occurrence Download</strong> <a href="https://doi.org/10.15468/dl.77gcvq">https://doi.org/10.15468/dl.77gcvq</a>). The process of compilation of TreeGOER with 30 arc-seconds global grid layers, two examples of BIOCLIM applications that investigated the effects of climate change on global tree diversity patterns and R scripts to repeat these analyses have been described by Kindt, R. (2023). <strong>TreeGOER: A database with globally observed environmental ranges for 48,129 tree species</strong>. Global Change Biology 29: 6303–6318. <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914</a>.</p> <p>This Zenodo archive documents the occurrence of the same previously compiled and cleaned observations for the TreeGOER across global raster layers that document the contemporary (1979-1920) and historical (1901-1920) distribution of 45 <strong>Terrestrial Life Zones</strong>. These global raster layers were created for the following article:</p> <ul> <li>Elsen, P. R., Saxon, E. C., Simmons, B. A., Ward, M., Williams, B. A., Grantham, H. S., Kark, S., Levin, N., Perez-Hammerle, K.-V., Reside, A. E., & Watson, J. E. M. (2022). Accelerated shifts in terrestrial life zones under rapid climate change. <em>Global Change Biology</em>, 28, 918–935. <a href="https://doi.org/10.1111/gcb.15962">https://doi.org/10.1111/gcb.15962</a></li> </ul> <p>and are <a href="https://datadryad.org/stash/dataset/doi:10.5061/dryad.41ns1rnff">available for download from DRYAD</a>:</p> <ul> <li>Elsen, Paul R.; Saxon, Earl C.; Simmons, B. Alexander; Ward, Michelle; Williams, Brooke A.; Grantham, Hedley S.; Kark, Salit; Levin, Noam; Perez-Hammerle, Katharina-Victoria; Reside, April E.; Watson, James E. M.; Perez‐Hammerle, Katharina‐Victoria. 2021. Data from: Accelerated shifts in terrestrial life zones under rapid climate change.<strong> </strong>Nov 05 2021 version files. <a href="https://doi.org/10.5061/dryad.41ns1rnff">https://doi.org/10.5061/dryad.41ns1rnff</a></li> </ul> <p>The raster layers were processed using <em>R</em> and <em>Google Earth Engine</em> following the methodology described in Elsen et al (<a href="https://doi.org/10.1111/gcb.15962">2022</a>). Documentation of the different zones are partially available from this README file: <a href="https://datadryad.org/stash/downloads/file_stream/1145694">https://datadryad.org/stash/downloads/file_stream/1145694</a></p> <p>For each of the 48,129 tree species, the distribution is given for:</p> <ul> <li>Contemporary climate: number of observations in life zones mapped by <a href="https://datadryad.org/stash/downloads/file_stream/1145680">https://datadryad.org/stash/downloads/file_stream/1145680</a></li> <li>Historical climate: number of observations in life zones mapped by <a href="https://datadryad.org/stash/downloads/file_stream/1145681">https://datadryad.org/stash/downloads/file_stream/1145681</a></li> <li>Mixed climate: number of observations for contemporary life zones if GBIF observations were from 1979 or later, and number of observations for historical life zones if GBIF observations were from before 1979</li> <li>Static climate: number of observations in the same zone in the contemporary and historical climate. The number of observations in areas where the life zone changed are listed in the variable of 'H-0'.</li> </ul> <p>Observations outside the life zone maps are listed in the variable of 'H-1'.</p> <p> </p> <p>The development of this data set archive supported by the <strong>Darwin Initiative</strong> to project DAREX001 of <em>Developing a Global Biodiversity Standard certification for tree-planting and restoration</em>, by <strong>Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia</strong> to the <em>Provision of Adequate Tree Seed Portfolio</em> project in Ethiopia, by the <strong>Green Climate Fund</strong> through the IUCN-led <em>Transforming the Eastern Province of Rwanda through Adaptation</em> and through the <em>Readiness proposal on Climate Appropriate Portfolios of Tree Diversity for Burkina Faso</em> projects, by the <strong>Bezos Earth Fund</strong> to the <em>Quality Tree Seed for Africa in Kenya and Rwanda</em> project and by the <strong>German International Climate Initiative (IKI)</strong> to the regional tree seed programme on <em>The Right Tree for the Right Place for the Right Purpose in Africa</em>.</p>
Data from: A tale of two studies: detection and attribution of the impacts of invasive plants in observational surveys
1.Short-term experiments cannot characterize how long-lived, invasive shrubs influence ecological properties that can be slow to change, including native diversity and soil fertility. Observational studies are thus necessary, but often suffer from methodological issues. 2.To highlight ways of improving the design and interpretation of observational studies that assess the impacts of invasive plants, we compare two studies of nutrient cycling and earthworms along two separate gradients of invasive shrub abundance. By considering the divergent sampling strategies and statistical analyses of these two studies, and interpreting their contradictory results in the context of other studies, we also aim to better describe the impacts of the focal invader, Rhamnus cathartica. 3.In a new study of a single site in Minnesota, we observed positive correlations between buckthorn abundance and soil pH, soil nutrient pools, nutrient fluxes through leaf litterfall, earthworm abundance, and root biomass. Multiple regression models showed these relationships persisted after accounting for variability in soil texture and tree species composition. For a separate, more expansive study in Illinois, other authors reported little to no correlation between buckthorn abundance and 10 soil properties, including earthworm abundance, pH, and nutrient concentrations. However, like many other studies, their regression models only assessed predictors related to invader abundance. R2 values for models of ecosystem properties ranged from 0-0.79 (adjusted-R2) for our study in Minnesota and from <0.05-0.16 (unadjusted) for the prior study in Illinois. 4.Differences in sampling error and use of predictor variables between the two studies likely explain the contrasting results. 5.Synthesis and applications. To reduce the uncertainty of conclusions from observational studies of invasive plants, future studies must ensure that heterogeneity of soils and vegetation is adequately accounted for in the sampling strategy and statistical analyses (e.g., analysis of covariance, multiple regression). Particular attention should be given to ecosystem properties with variability that likely predates the invader (e.g., geophysical features and tree community composition). In our study, effects of buckthorn on ecosystem properties were not only robust to the inclusion of potentially confounding predictors, but also consistent with expectations based on ecological stoichiometry and mass balance of element flow.
Dataset of "Direct Observation of Shallow Trap States in Thermal Equilibrium with Band-Edge Excitons in Strongly Confined CsPbBr3 Perovskite Nanoplatelets""
<p>Dataset underpinning the published article:</p> <p>Direct Observation of Shallow Trap States in Thermal Equilibrium with Band-Edge Excitons in Strongly Confined CsPbBr<sub>3</sub> Perovskite Nanoplatelets</p> <p><em>Adv. Optical Mater.</em> <strong>2021</strong>, <em>9</em>, 2001308. DOI: <a href="http://doi.org/10.1002/adom.202001308">10.1002/adom.202001308</a></p>
Data set: Huai et al. (2021). JAMC. Quantifying rainfall in Greenland: a combined observational and modelling approach
<p>Abstract Paper. This paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in-situ precipitation gauge measurements to seven different precipitation phase schemes to separate rain- and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a Dynamic Correction Model (DCM) for Automatic Weather Stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R=0.3-0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02-1.40) are smaller than those for snowfall (1.27-2.80), and hence the observations more robust. With a horizontal resolution of 5.5 km and simulation period from 1958-present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients.</p> <p>The dataset contains:<br> Automatic weather station data:<br> AWS-daily.zip: per station daily values of snowfall and rain fall derived from raw precipitation data and for 7 methods to divide between rain and snowfall<br> AWS-factork.zip: per station the factor with which the data is corrected for undercatch<br> AWS-script.zip: the scripts used for the analyses</p> <p>Staffed weather stations:<br> Meteo-daily.zip: per station daily values of snowfall and rain fall derived from the precipitation data and for 7 methods to divide between rain and snowfall<br> Meteo-factork.zip: per station the factor with which the data is corrected for undercatch<br> Meteo-script.zip: the scripts used for the analyses</p> <p> </p>
ASSESSMENT OF ADHERENCE TO NEW ORAL ANTICOAGULANTS IN ATRIAL FIBRILLATION PATIENTS WITHIN THE OUTPATIENT REGISTRY PROFILE. PROSPECTIVE OBSERVATIONAL STUDY (ANTEY study)
<p><strong>Rationale</strong></p> <p>Prevention of stroke and thromboembolic complications in non-valvular atrial fibrillation is one of the most common indications for the use of all NOACs and warfarin in cardiology. The issue of regular intake of all OACs, i.e. the issue of adherence to anticoagulation therapy, is paramount for better treatment. The problem of assessment of different aspects of adherence to OACs in patients with atrial fibrillation within an outpatient registry is of current interest.</p> <p><strong>Primary</strong> <strong>Study</strong> <strong>Objectives</strong></p> <p>The aim of the present study is to assess adherence to therapy and factors associated with adherence in patients with CV disease complicated by non-valvular atrial fibrillation requiring OAC treatment within the outpatient registry PROFILE (prospective, observational study).</p> <ol> <li>Data collection in patients with non-valvular atrial fibrillation requiring OAC treatment included in the registry</li> <li>Evaluation of actual patient adherence to OACs</li> </ol> <p><strong>Secondary Study Objective(s)</strong></p> <ol> <li>Evaluation of potential patient adherence to OACs</li> <li>Determination of most significant factors associated with adherence to OACs in patients with non-valvular AF</li> <li>Validation of new original questionnaire</li> <li>Evaluation of doctor’s adherence to OAC prescription according to Guidelines (ESC). Management of atrial fibrillation,2016)</li> </ol> <p><strong>Material and methods</strong></p> <p>.The study included 201 patients with nonvalvular AF from the outpatient "PROFILE" registry, 118 (58,7%) males. The mean age was 71,1 ±8,7 years. The study protocol consisted of the inclusion visit (V0), 6-month follow-up visit (V1), and phone contact 1 year after V0 (follow-up, FU). In V0, all patients were prescribed one of the NOACs. At V1 doctors could recommend warfarin or another NOAC to patients, who have refused to take prescribed NOAC. Medical adherence was determined using the original questionnaire</p> <p><strong>Inclusion Criteria (detailed)</strong></p> <ul> <li>Men and women above 18 years of age who were included in the "PROFILE" registry by the start of the observational study</li> <li>Presence of written informed consent to participate in the study, fill in the study questionnaires, and have personal data analyzed</li> <li>Presence of any form of non-valvular atrial fibrillation with CHA<sub>2</sub>DS<sub>2</sub>-VASc score of ≥1 or patients with CHA<sub>2</sub>DS<sub>2</sub>-VASc score = 0, who are already taking OAK</li> </ul> <p><strong>Exclusion Criteria</strong></p> <p>Patients with high bleeding risk, including patients with:</p> <ul> <li>Congenital or acquired bleeding disorders</li> <li>Uncontrolled resistant hypertension</li> <li>Exacerbation of gastric and duodenal ulcer</li> <li>Vascular retinopathy</li> <li>Recent history of intracranial or intracerebral hemorrhage</li> <li>Pathology of the brain and spinal cord vessels</li> <li>Recent history of the brain, spinal cord, or eye surgery</li> <li>History of bronchiectasis or pulmonary hemorrhage</li> <li>A CHA<sub>2</sub>DS<sub>2</sub>-VASc score of 0 (OACs are not indicated)</li> <li>Pregnancy, lactation</li> <li>Planned surgery</li> <li>Known hypersensitivity to ingredients of medications used in the study</li> </ul> <p><strong>Visit schedule</strong></p> <p>Visit schedule</p> <p>Two visits at 6-month intervals are scheduled for each patient as part of routine clinical practice:</p> <p>Visit 0– visit at study entry:</p> <ul> <li>receiving written informed consent to participate in research from patients</li> <li>inclusion in the program</li> <li>assessment of inclusion and exclusion criteria</li> <li>verification of non-valvular atrial fibrillation diagnosis (according to medical documentation, confirming the history of atrial fibrillation: ECG, Holter monitoring, etc..)</li> <li>collecting information on received medication therapy, including OACs</li> <li>physical examination of patients (measurements of blood pressure, heart rate, height, weight, waist circumference)</li> <li>questioning of patients to determine potential and actual adherence to OACs</li> <li>computation of points on the scale CHA<sub>2</sub>DS<sub>2</sub>-VASc and HAS-BLED to determine the indications for the appointment of the OACs and the identification of an increased risk of bleeding</li> <li>to determine the INR in patients who agreed to replace the use of warfarin with one of the NOACs</li> <li>prescription of OACs according to routine clinical practice and official labels for these medications</li> <li>instructing patients (according to the specifically designed scheme) to regularly take prescribed medications, be aware of precautionary measures when taking OACs, telling them about the pros and cons of treatment with OACs</li> </ul> <p>Visit 1 – visit at 6 months after the Visit 0:</p> <ul> <li>collecting information on patients’ compliance with doctor’s recommendations</li> <li>collecting information on patients’ actual medication therapy</li> <li>collecting information on the safety of treatment with OACs (in case the patient has been taking them), recording all adverse events that occurred during the study period</li> <li>measurements of blood pressure, heart rate as a part of routine clinical practice</li> <li>questioning of patients to determine potential and actual adherence to OACs</li> </ul> <p>FU - follow-up calls to patients (one year)</p> <p>Phone contact to determine patient’s life status, possible (fatal and non-fatal complications of non-valvular atrial fibrillation) and fill (after receiving patient’s consent) the original questionnaire.</p> <p><strong>Primary Outcome</strong></p> <p>The proportion of complete, partial adherent and non-adherent patients according to the original questionnaire</p> <p><strong>Secondary Outcomes </strong></p> <ul> <li>The proportion of potentially adherent patients (according to the original questionnaire)</li> <li>Identification of baseline characteristics associated with adherence</li> <li>The proportion of doctors prescribed OAC according to guidelines.</li> </ul> <p><strong>Safety Outcomes </strong></p> <p>Adverse events and outcomes were recorded from the start of treatment with the OAC until the end of the observational study period. The doctor evaluated the severity of adverse events and outcomes if necessary took measures for their medical treatment according to current clinical practice.</p> <p> </p> <p> </p>
Earth-observation based products from the CoastObs project
<p>The Earth-observation based products are in the CoastObs portal: https://coastobs.lizard.net. Login details to the portal will be provided after finalising the CoastObs training materials: https://coastobs.eu/e-training</p> <p>Products in the portal include demonstration products of the following parameters:</p> <p>Basic products:</p> <ul> <li>Chl-a</li> <li>Suspended matter</li> <li>Turbidity</li> <li>Sea surface temperature</li> </ul> <p>Innovative and higher level products:</p> <ul> <li>Sea grass percentage coverage</li> <li>Phytoplankton size classes</li> <li>Harmful algae bloom (HAB) indicators for Pseudonitzschia and Alexandrium</li> <li>(Mean) food quality for shell fish</li> <li>Mussel growth potential</li> <li>Relative growth rate (of mussels)</li> </ul> <p>There are products for the following areas:</p> <ul> <li>Loire Estuary (France)</li> <li>Bourgneuf Bay (France)</li> <li>Eastern Scheldt + Voordelta (Netherlands)</li> <li>Wadden Sea (Netherlands)</li> <li>Venice Lagoon (Italy)</li> <li>Galician coast (Spain)</li> <li>Rias Baixas (Spain)</li> </ul> <p>In the portfolio are more products, such as:</p> <ul> <li>Primary production</li> <li>WFD indicators</li> <li>HAB forecasts</li> <li>Plume morphology</li> <li>Phytoplankton bloom morphology</li> </ul>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.