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301 results for “bloom”
Climate-driven change to phytoplankton blooms across the global ocean - CMIP6 Phenology Outputs
<p>Bloom phenology metrics calculated from CMIP6 chlos outputs archived. Models include 'CNRM-ESM2-1-LR', 'MPI-ESM1-2-LR', 'NorESM2-LM' and 'NorESM2-MM'. Metrics calculated using daily outputs resampled to 5 day means with the methods outlined in Thomalla et al. (2023) Nature Climate Change (doi: 10.1038/s41558-023-01768-4).</p><p>Data are organised along the dimensions of model, year, latitude and longitude.</p><p>Data include the Historical (1850-2014) and high emissions SSP5-8.5 (2015-2100) simulations.</p><p>Metrics include bloom initiation, bloom termination, bloom duration, bloom integrated chlorophyll-a, bloom mean chlorophyll-a, bloom maximum chlorophyll-a, bloom maximum date, number of bloom peaks and seasonal cycle reproducibility.</p>
Supplementary material 9 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Table S4
Supplementary material 3 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Figure S3
Supplementary material 8 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Table S3
Supplementary material 5 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Figure S5
Supplementary material 6 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Table S1
Supplementary material 1 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Figure S1
Supplementary material 7 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Table S2
Supplementary material 2 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Figure S2
Supplementary material 4 from: Pearman JK, Casas L, Michell C, Aldanondo N, Mojib N, Holtermann K, Georgakakis I, Curdia J, Carvalho S, Gusti A, Irigoien X (2022) Comparative metagenomics of phytoplankton blooms after nutrient enrichment of oligotrophic marine waters. Metabarcoding and Metagenomics 6: e79208. https://doi.org/10.3897/mbmg.6.79208
Figure S4
Fig. 1. A – 18S in A Hotspot of Amoebae Diversity: 8 New Naked Amoebae Associated with the Planktonic Bloom-forming Cyanobacterium Microcystis
Fig. 1. A – 18S rDNA maximum likelihood phylogeny of Vannella, including Microcystis–associated strains (in bold). ML bootstrap values respectively posterior probabilities are shown at the nodes. GenBank accession numbers are given together with the species names. B – LM pictures of V. planctonica (strains A2FBB: 2, 4, 5, 9–13 and A4P4ZHB: 1, 3, 6–8) showing locomotive trophozoites (1–8), a grazing amoeba with a Microcystis cell inside a food vacuole (9), floating forms (10–11) and a cyst stage (12–13). C – LM pictures of V. simplex (strain A17WVB) showing the floating form (14), locomotive amoebae (15–18) with the presence of food vacuoles containing partly digested Microcystis cells (17), posteriorly adhered fecal pellets (15–16), a long flagellum-like pseudopodium encircling a Microcystis cell (17–18) and grazing amoebae on a colony of Microcystis aeruginosa with expanded (arrow) or contracted (arrowhead) flagellum-like pseudopodia visible in some of the trophozoites (19). The presence of a contracticle vacuole, a nucleus or a cyst opening is indicated by a black arrow, a black arrowhead or a white arrow respectively. Scale bars: 20 µm.
Planktonic drivers of carbon transformation during different stages of the spring bloom at the Patagonian Shelf-break front
<p>This dataset originates from a detailed study on the carbon cycle in the Argentine Patagonian Shelf, a crucial area for global carbon sequestration. The data were collected during the austral spring to investigate the structure of microbial communities, including viruses, and their impact on the transformation of dissolved carbon during different phases of the spring phytoplankton bloom.</p>
Figure 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
Figure 4 Initial expertise (color of the bar) vs final confidence (y-axis) after the GRU workshop for participants responding to final survey. Example for how to interpret this graphic: the blue color bar at the top indicates that before the workshop roughly 50% of respondents said their knowledge of GEOLocate was "neither high nor low" but after the workshop these same respondents selected "much higher" for their knowledge of GEOLocate.
Figure 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
Figure 3 An illustrative example of the two methods of uncertainty capture when georeferencing specimens. Method A, or polygon, creates a shape around the river (in blue). Method B, or point-radius, creates a circle of uncertainty around the origin. The illustration is based on output from GeoLocate software (Rios 2018) for both polygon and point-radius.
Figure 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
Figure 2 This specimen record is an example from the University of California Collection Network Symbiota Portal. The large image is an edit of the record to include a medium size version of the image for easier viewing in this article. The portal software is open source and it is freely available for reuse through the Symbiota GitHub repository. The image is an example of a specimen record that includes an image of the specimen with label data. The image is contributed by the UCSB Invertebrate Zoology Collection at the Cheadle Center for Biodiversity and Ecological Restoration. The usage rights for the image is Creative Commons 0 (public domain).
Figure 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
Figure 1 Map created using SimpleMappr (Shorthouse 2010) that illustrates geolocated specimens for Genus=Cicindela in California as found on iDigBio.
Figure 4 in Occurrence and temporal variation in the size-frequency distribution of 2 bloom-forming jellyfishes, Catostylus perezi (L. Agassiz, 1862) and Rhizostoma pulmo (Cuvier, 1800), in the Indus Delta along the coast of Sindh, Pakistan
Figure 4. Temporal variation in size frequency distribution of R. pulmo at Keti Bunder during the study period.
Fig. 3. Cytostrombidium wailesi and C. longisomum. a, b in Insights on Short-term Blooms of Planktonic Ciliates, Provided by an Easily Recognised Genus: Cyrtostrombidium
Fig. 3. Cytostrombidium wailesi and C. longisomum. a, b – Lugol's preserved, protargol impregnated examples of C. wailesi; c – Lugol's preserved, protargol impregnated, conjugating C. wailesi; d – Lugol's preserved, conjugating C. wailesi; e – Lugol's preserved, protargol impregnated examples of C. longisomum; f – protargol impregnated example of C. longisomum; g – Lugol's preserved C. longisomum; h – protargol impregnated example of C. longisomum with two parasites (p). Scale bars: 5 µm.
Fig. 2 in Insights on Short-term Blooms of Planktonic Ciliates, Provided by an Easily Recognised Genus: Cyrtostrombidium
Fig. 2. Temporal variability in the abundance of the total heterotophic ciliate assemblage and the two Cyrtostrombidium species (ml–1), with an indication of the occurrence of conjugating pairs (arrows), at site C (Fig. 1).
Figure 2 in Unusual winter zooplankton bloom in the open southern Adriatic Sea
Figure 2. Maps of Chl concentrations (mg m–3) retrieved from MODIS Aqua17: February 2015; 18 February 2015; 19 February 2015; 20 February 2015; 03 March 2015; 06 March 2015.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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