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301 results for “bloom”
Figure 1 in Limited response of a spring bloom community inoculated with filamentous cyanobacteria to elevated temperature and pCO
Figure 1: Environmental conditions during the experiment. (A) Temperature (°C) at ambient (blue: 1°C) and elevated (red: 4°C) conditions. (B) Radiation conditions (PAR, 400–700 nm) during the experiment. Gray areas (A) and error bars (B) indicate standard deviation, n = 2.
Figure 3 in Limited response of a spring bloom community inoculated with filamentous cyanobacteria to elevated temperature and pCO
Figure 3: Photosynthetic activity of phytoplankton in different temperature and pCO 2 treatments. (A) Maximum quantum yield: Fv/Fm. (B) Initial slope of the rapid light curve (photosynthetic efficiency): αPSII. (C) Minimum saturation irradiance: E (µmol photons m−2 s−1). (D) Maximum relative electron transport rate: rETR. Error bars indicate standard deviation, n = 3. k max
Figure 2 in Limited response of a spring bloom community inoculated with filamentous cyanobacteria to elevated temperature and pCO
Figure 2: Inorganic nutrient concentrations in different temperature and pCO2 treatments. (A) Dissolved inorganic nitrogen (DIN; NO − + NO −). (B) Dissolved inorganic silica (DISi). (C) Dissolved inorganic phosphate (DIP). Error bars 3 2 indicate standard deviation, n = 3.
Figure 5 in Limited response of a spring bloom community inoculated with filamentous cyanobacteria to elevated temperature and pCO
Figure 5: Heterotrophic bacterial abundance and bacterial production in different temperature and pCO2 treatments. (A) Bacterial abundance (109 cells l−1). (B) Cell-specific production (CSP, 10−9 µg C cell−1 d−1). Error bars indicate standard deviation, n = 3.
An evaluation of new particle formation events in Helsinki during a Baltic Sea cyanobacterial summer bloom
<p>The data set is linked to the manuscript: Thakur, R. C., Dada, L., Beck, L. J., Quéléver, L. L. J., Chan, T., Marbouti, M., He, X.-C., Xavier, C., Sulo, J., Lampilahti, J., Lampimäki, M., Tham, Y. J., Sarnela, N., Lehtipalo, K., Norkko, A., Kulmala, M., Sipilä, M., and Jokinen, T.: An evaluation of new particle formation events in Helsinki during a Baltic Sea cyanobacterial summer bloom, Atmos. Chem. Phys. Discuss. 2022.</p>
Dataset for "Number-size distribution and CCN activity of atmospheric aerosols in the western North Pacific during spring pre-bloom period: Influences of terrestrial and marine sources, J. Geophys. Res. Atmos."
<p>A cruise observation was conducted over the western North Pacific Ocean in March 2015. The dataset in the excel sheet contains aerosol number-size distributions and CCN number concentrations along with ship positions and date/time. This dataset is for Kawana et al. in Journal of Geophysical Research: Atmospheres.</p> <p>Kaori Kawana, Yuzo Miyazaki, Yuko Omori, Hiroshi Tanimoto, Sara Kagami, Koji Suzuki, Youhei Yamashita, Jun Nishioka, Yange Deng, Hikari Yai, and Michihiro Mochida: Number-size distribution and CCN activity of atmospheric aerosols in the western North Pacific during spring pre-bloom period: Influences of terrestrial and marine sources, J. Geophys. Res. Atmos.</p>
Supplementary material 7 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
This document contains an annotated set of data quality checks that participants report they use when evaluating and cleaning datasets. These items outline how participants are judging if the data suits their purpose.
Supplementary material 3 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
The informed consent request and workshop survey questions given to participants after the workshop each day for 4 consecutive days.
Supplementary material 2 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
This document shows just the questions we asked the applicants who applied to participate in this Georeferencing for Research Use workshop. We used a Google Form to deliver these questions and collect responses. It is both an application and serves as our pre-workshop survey.
Supplementary material 8 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Summary of desired future workshop topics that were listed by participants on the last day of the workshop.
Supplementary material 6 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Summary of topics to be covered in an ideal workshop as identified by workshop applicants in the workshop call for participation. We incorporated as many as possible that also fit our scope.
Supplementary material 5 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Questions we asked in the Georeferencing for Research Follow Up Survey done 3 months after the workshop.
Supplementary material 4 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Three months after the workshop, participants were surveyed to assess what workshop-related knowledge and materials were being used and disseminated to others. This document summarized data collected in this particular survey.
Supplementary material 1 from: Seltmann K, Lafia S, Paul D, James S, Bloom D, Rios N, Ellis S, Farrell U, Utrup J, Yost M, Davis E, Emery R, Motz G, Kimmig J, Shirey V, Sandall E, Park D, Tyrrell C, Thackurdeen R, Collins M, O'Leary V, Prestridge H, Evelyn C, Nyberg B (2018) Georeferencing for Research Use (GRU): An integrated geospatial training paradigm for biocollections researchers and data providers. Research Ideas and Outcomes 4: e32449. https://doi.org/10.3897/rio.4.e32449
Darwin Core Archive file downloaded from the iDigBio portal for use in the Georeferencing for Research Use workshop. Total 25,429 records, accessed on 2016-08-29. Collections contributing to the record set are listed in the archive records.citation.txt file. Dataset GUID: a69d1541-4726-465d-84ad-50c7ed556eee
Code and data for: The evolution of light and vertical mixing across a phytoplankton ice-edge bloom
<p>This is a first release of the code (and the data and figures it produced) used by Randelhoff et al. for "The evolution of light and vertical mixing across a phytoplankton ice-edge bloom", Elementa: Science of the Anthropocene (2019).</p>
Climate-induced interannual variability and projected change of two harmful algal bloom taxa in Chesapeake Bay, USA
<p>This dataset include the input files for the hindcast simulation of ROMS-RCA in Chesapeake Bay during 2002-2011.</p> <p>ROMS (Regional Ocean Modeling System) model used in this study is version 3.4.</p> <p>RCA (Row-Column AESOP) water quality model used in this study is improved by UMCES, coupling with ROMS output.</p>
FIGURE 2. A–B. Coreopsis bakeri. A. Habitat, with blooming plants. B in Coreopsis bakeri (Asteraceae; Coreopsideae), a new species from Florida, USA
FIGURE 2. A–B. Coreopsis bakeri. A. Habitat, with blooming plants. B. Plants in bloom, showing substrate with exposed bare rock. Photographs taken by A. Johnson.
FIGURES 20–25. Cosmarium distentum. 20. Blooming population. 21 in Taxonomic notes on Dutch desmids VII (new species, new names, new record)
FIGURES 20–25. Cosmarium distentum. 20. Blooming population. 21. Cell in frontal view. 22. Cell in lateral view. 23. Cell in apical view. 24–25. Zygospores. Scale bar = 10 μm.
FIGURE 2. Thalictrum austrotibeticum J. Y. Li, L. Xie & L. Q. Li. a. A blooming individual. b & e in A new species of Thalictrum (Ranunculaceae) from southern Tibet (Xizang), China
FIGURE 2. Thalictrum austrotibeticum J. Y. Li, L. Xie & L. Q. Li. a. A blooming individual. b & e. Upper and lower leaves showing color and morphology variation. c. Inflorescence. d. Mature flower and fruits showing purple filaments and compressed fruits. (Photos from Gyirong and Nyalam populations by J. Y. Li, L. Xie, and X. T. Ma)
Quantitative real-time PCR assays Q2 for species-specific detection and quantification of Baltic Sea spring bloom dinoflagellates
<p>These are the data behind figures 2 to 7 in the paper: Brink AM, Kremp A and Gorokhova E (2024) Quantitative real-time PCR assays for species-specific detection and quantification of Baltic Sea spring bloom dinoflagellates. Front. Microbiol. 15:1421101. doi: 10.3389/fmicb.2024.1421101</p>
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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.