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59 results for “marine organisms”
Data for paper publication "Modelling emission and transport of key components of primary marine organic aerosol using the global aerosol-climate model ECHAM6.3–HAM2.3"
<p>The dataset presented here is related to the article by Leon-Marcos et al. 2025: "Modelling emission and transport of key components of primary marine organic aerosol using the global aerosol-climate model ECHAM6.3–HAM2.3" accepted for publication in GMD. It comprises global fields of the FESOM2.1-REcoM3 biogeochemistry model tracers employed to calculate the ocean biomolecule concentration that serve as input data for the aerosol model. Additionally, the ECHAM6.3–HAM2.3 code of the marine aerosol implementation and the required scripts to run the model experiments are provided here. The aerosol-climate model simulation results of the marine aerosol emission, as well as the evaluation of the model results compared to observations, are also included. For further information, please refer to the attached data description. </p> <p> </p> <h2> </h2>
Marine plastics alter the organic matter composition of the air-sea boundary layer, with influences on CO2 exchange: a large-scale analysis method to explore future ocean scenarios
<p>Microplastics are substrates for microbial activity and can influence biomass production. This has potentially important implications in the sea-surface microlayer, the marine boundary layer that controls gas exchange with the atmosphere and where biologically produced organic compounds can accumulate. In the present study, we used six large scale mesocosms to simulate future ocean scenarios of high plastic concentration. Each mesocosm was filled with 3 m3 of seawater from the oligotrophic Sea of Crete, in the Eastern Mediterranean Sea. A known amount of standard polystyrene microbeads of 30 μm diameter was added to three replicate mesocosms, while maintaining the remaining three as plastic-free controls. Over the course of a 12-day experiment, we explored microbial organic matter dynamics in the sea-surface microlayer in the presence and absence of microplastic contamination of the underlying water. Our study shows that microplastics increased both biomass production and enrichment of carbohydrate-like and proteinaceous marine gel compounds in the sea-surface microlayer. Importantly, this resulted in a 3 % reduction in the concentration of dissolved CO2 in the underlying water. This reduction was associated to both direct and indirect impacts of microplastic pollution on the uptake of CO2 within the marine carbon cycle, by modifying the biogenic composition of the sea's boundary layer with the atmosphere.</p>
SBC LTER: OCEAN: Particulate Organic Matter Content and Composition of Stream, Estuarine, and Marine Sediments
An unprecedented five-year drought in California, coupled with conditions of anomalously low ocean productivity and the prospect of one of the strongest El Niño periods on record with above average rainfall were the impetus for this RAPID award, which seeks to test specific hypotheses pertaining to the origin, distribution, processing, and bioavailability of terrestrial organic matter in coastal marine sediments and their potential for serving as a reservoir of nitrogen storage to fuel nearshore primary production during periods when nitrate concentrations are low. The goals of the research were to: (1) measure bulk properties and biomarker tracers of particulate organic matter (POM) in stream water and in coastal marine sediments at SBC LTER and other reef sites differing in exposure to terrestrial runoff prior to and following large storm events, (2) determine the bioavailability of dissolved organic matter (DOM) released from POM in marine sediments following large runoff events, and (3) measure changes in concentrations of dissolved inorganic and organic nitrogen in pore water of marine sediments near to and distant from stream mouths in the Santa Barbara Channel. Samples were analyzed for organic matter content using a loss-on-ignition combustion method, and samples were also analyzed for organic carbon and nitrogen content and isotopes using a stable isotope mass spectrometer interfaced with an elemental analyzer. Subsamples were shipped to the laboratory of Marc Lucotte at the University of Québec, Montréal for analysis of lignin content using the cupric oxidation method.
Modeling Early Life Histories of Marine Organisms
<p>This is a recorded presentation to introduce students to ecosystem modeling. The presentation was developed for students of an early life histories class so discusses lagrangian individual-based modeling but the supporting material for understanding eulerian physical and lower trophic level models is also introduced.</p> <p>If you use part or all of this educational material as part of your lesson content it would be appreciated if you could inform the author (gagibson@alaska.edu) for tracking purposes.</p>
SBC LTER: Beach: Distribution of terrestrial organic material in intertidal and nearshore marine sediment due to debris flow response efforts
These data describe the distribution and processing of terrestrial organic material observed in the Santa Barbara Channel (Goleta Bay) during the spring of 2018. Specifically, beach, slough, and marine sediments were sampled during and after the debris disposal event that took place between January and February 2018 following the Thomas Fire and the subsequent Montecito Debris Flow. Data are contained in one table, including organic carbon, carbon isotope, lignin phenol, and pyrogenic carbon measurements analyzed from sediment cores collected at different depths and locations in the nearshore region.
Estimated reflectance hyperspectral libraries for Vigo sediment sample, seafloor sand samples and marine organism
<h2>Abstract</h2> <p>Estimated reflectance hyperspectral libraries created for sand samples from seafloor at Vigo sea zone 1, 2 and 3, sediment samples from Vigo fieldwork Sept. 2023 and some Vigo marine organisms such as sea cucumber, sea pens, sea stars, coral, seaweed.</p> <p>This depository contains data generated within the European S34 project.</p> <h2>Metadata Information</h2> <table> <tbody> <tr> <td> <p><strong>Identification</strong></p> </td> </tr> <tr> <td> <p>Full Title</p> </td> <td> <p>Estimated reflectance hyperspectral libraries for Vigo sediment sample, seafloor sand samples and marine organism</p> </td> </tr> <tr> <td> <p>Abstract</p> </td> <td> <p>Estimated reflectance hyperspectral libraries created for sand samples from seafloor at Vigo sea zone 1, 2 and 3, sediment samples from Vigo fieldwork Sept. 2023 and some Vigo marine organisms such as sea cucumber, sea pens, sea stars, coral, seaweed.</p> </td> </tr> <tr> <td> <p>Keywords</p> </td> <td> <p>Reflectance hyperspectral signature, library, sediment, sand, sea cucumber, sea star, coral, seaweed</p> </td> </tr> <tr> <td> <p>Pilot area</p> </td> <td> <p>Ria de Vigo</p> </td> </tr> <tr> <td> <p>Associated resources</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Language</p> </td> <td> <p>English</p> </td> </tr> <tr> <td> <p>URL</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Categories</p> </td> <td> <p>Other</p> </td> </tr> <tr> <td> <p><strong>Temporal reference</strong></p> </td> </tr> <tr> <td> <p>Creation date (dd.mm.yyyy)</p> </td> <td> <p>25.05.2024</p> </td> </tr> <tr> <td> <p>Revision date (dd.mm.yyyy)</p> </td> <td> <p>25.05.2024</p> </td> </tr> <tr> <td> <p><strong>Quality and validity</strong></p> </td> </tr> <tr> <td> <p>Representation type</p> </td> <td> <p>Other</p> </td> </tr> <tr> <td> <p>Format</p> </td> <td> <p>CSV</p> </td> </tr> <tr> <td> <p>Lineage</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Spatial resolution</p> </td> <td> <p>0.25m</p> </td> </tr> <tr> <td> <p>Positional accuracy</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Maintenance information</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Coordinate system</p> </td> <td> <p>EPSG 3035</p> </td> </tr> <tr> <td> <p><strong>Constranits related to access and use</strong></p> </td> </tr> <tr> <td> <p>Use limitation</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Access constraint</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Public/Private</p> </td> <td> <p>Public</p> </td> </tr> <tr> <td> <p><strong>Responsible organisation</strong></p> </td> </tr> <tr> <td> <p>Responsible Contact</p> </td> <td> <p>Ecotone AS, info@ecotone.com</p> </td> </tr> <tr> <td> <p>Responsible Party</p> </td> <td> <p>Ecotone AS</p> </td> </tr> <tr> <td> <p><strong>Metadata on metadata</strong></p> </td> </tr> <tr> <td> <p>Contact</p> </td> <td> <p>Ecotone AS, info@ecotone.com</p> </td> </tr> <tr> <td> <p>Metadata language</p> </td> <td> <p>English</p> </td> </tr> </tbody> </table>
Figure 5 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 5. Vigtorniella spp. Haplotype network of cytochrome c oxidase subunit I (COI). Each large circle represents a sequence from an individual of Vigtorniella ardabilia that has been collected in Sweden (white) or Norway (grey). Black circles represent V. flokati, collected in the Pacific Ocean, three specimens sampled sharing the same haplotype. Letters in circles, A-G, represent haplotypes of V. ardabilia sampled in this study (Table 1). Each line represents a mutation and small empty circles are inferred haplotypes not present in the current study.
Figure 4 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 4. Vigtorniella ardabilia sp. nov., specimen from whale-fall in Sweden, light micrographs: (A) parapodia from mid-body region, (B) detail of neuropodial falcigers, (C) detail of notopodial spine. Scale bar in (A) is 100 Mm, in (B) and (C) 10 Mm.
Figure 3 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 3. Vigtorniella ardabilia sp. nov., specimen from whale-fall in Sweden. SEM micrographs of (A) head region dorsal view, (B) head region ventral view, (C) fine neuropodial falcigers from segment 2, (D) neuropodial falcigers from mid-body region, and (E) notopodial spine. Scale bars in (A) and (B) are 150 Mm, in (C) 7.5 Mm, in (D) 15 Mm and in (E) 6 Mm.
Figure 2 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 2. Vigtorniella ardabilia sp. nov., live photo of specimen from whale-fall in Sweden. The worm is 6 mm long.
Figure 3 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 3. Relationship between the number of chaetigers and total bodylength in 15 specimens of Vigtorniella ardabilia and 33 specimens of V. flokati.
Figure 6. Diagram showing Kimura 2 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 6. Diagram showing Kimura 2 Parameter (K2P)-distances between congeneric species in four chrysopetalid genera, for two nuclear genes (18S, 28S) and two mitochondrial genes (16S, cytochrome c oxidase subunit I (COI)).
Dataset from: Ultraviolet refractive index values of organic aerosol extracted from deciduous forestry, urban and marine environments
<p>The refractive index values of atmospheric aerosols are required to address the large uncertainties in the magnitude of atmospheric radiative forcing and measurements of the refractive index dispersion with wavelength of particulate matter sampled from the atmosphere are rare over ultraviolet wavelengths. An ultraviolet-optimized spectroscopic system illuminates optically-trapped single particles from a range of tropospheric environments to determine the particle’s optical properties. Aerosol from remote marine, polluted urban, and forestry environments is collected on quartz filters, and the organic fraction is extracted and nebulized to form micron-sized spherical particles. The radius and the real component of refractive index dispersion with wavelength of the optically trapped particles are determined to a precision of 0.001 µm and 0.002 respectively over a near-ultraviolet-visible wavelength range of 0.320–0.480 µm. Remote marine aerosol is observed to have the lowest refractive index (n=1.442 (λ=0.350 µm)), with above-canopy rural forestry aerosol (n=1.462–1.481 (λ=0.350 µm)) and polluted urban aerosol (n=1.444–1.485 (λ=0.350 µm)) showing similar refractive index dispersions with wavelength. In-canopy rural forestry aerosol is observed to have the highest refractive index value (n=1.508 (λ=0.350 µm)). The study presents the first single particle measurements of the dispersion of refractive index with wavelength of atmospheric aerosol samples below wavelengths of 0.350 µm. The Cauchy dispersion equation, commonly used to describe the visible refractive index variation of aerosol particles, is demonstrated to extend to ultraviolet wavelengths below 0.350 µm for the urban, forestry, and atmospheric aerosol water-insoluble extracts from these environments. A 1D radiative-transfer calculation of the difference in top-of-the-atmosphere albedo between atmospheric core-shell mineral aerosol with and without films of this material demonstrates the importance of organic films forming on mineral aerosol.</p> <p>The raw experimental spectra collected and analysed in this study are provided, as well as files for the calibrated wavelengths.</p>
Data from: Marine latitudinal diversity gradients, niche conservatism, and out of the tropics and Arctic: climatic sensitivity of small organisms
<ul> <li>Aim</li> </ul> <p>The latitudinal diversity gradient (LDG) is a consequence of evolutionary and ecological mechanisms acting over long history, and thus is best investigated with organisms that have rich fossil records. However, combined neontological-paleontological investigations are mostly limited to large, shelled invertebrates, which keeps our mechanistic understanding of LDGs in its infancy. This paper aims to describe the modern meiobenthic ostracod LDG and to explore the possible controlling factors and the evolutionary mechanisms of this large-scale biodiversity pattern.</p> <ul> <li>Location</li> </ul> <p>Present-day Western North Atlantic</p> <ul> <li>Taxon</li> </ul> <p>Ostracoda</p> <ul> <li>Methods</li> </ul> <p>We compiled census data from ostracods living in shallow marine environments of the western North Atlantic Ocean. Using these data, we documented the marine LDG with multiple metrics of alpha, beta (nestedness and turnover), and gamma diversity, and we tested whether macroecological patterns could be governed by different environmental factors, including temperature, salinity, dissolved oxygen, pH and primary productivity. We also explored the geologic age distribution of ostracod genera to investigate the evolutionary mechanisms underpinning the LDG.</p> <ul> <li>Results</li> </ul> <p>Our results show that temperature and climatic niche conservatism are important in setting LDGs of these small, poorly-dispersing organisms. We also found evidence for some dispersal-driven spatial dynamics in the ostracod LDG. Compared to patterns observed in marine bivalves, however, dispersal dynamics were weaker and they were bi-directional, rather than following the "out-of-the-tropics" model.</p> <ul> <li>Main Conclusions</li> </ul> <p>Our detailed analyses revealed that meiobenthic organisms, which comprise two-thirds of marine diversity, do not always follow the same rules as larger, better-studied organisms. Our findings suggest that the under-studied majority of biodiversity may be more sensitive to climate than are well-studied, large organisms. This implies that the impacts of ongoing Anthropocene climatic change on marine ecosystems may be much more serious than presently thought.</p>
Marine vesicles: one more layer of complexity in the dissolved organic fraction
<p>These data include the genome of the <em>Vibrio kanaloae</em> strain, which was isolated in pure culture from a seawater sample collected on May 31, 2022, from Cape Huertas (Alicante, Spain). The genome was sequenced using PacBio HiFi long reads. Additionally, reads sequences from the extracellular vesicles (EVs) in the 20% OptiPrep fraction were isolated from the <em>Vibrio kanaloae</em> culture incubated in dialysis tubing cellulose membranes (Sigma-Aldrich, ref: D9652-100FT, width: 33 mm, 14 kDa). These membranes were immersed in an aquarium filled with natural seawater collected on December 9, 2022, from Cape Huertas (Mediterranean Sea, Alicante) and incubated at room temperature (approximately 18–20°C) for 1 week.</p> <p>EVs_20_rep1_AQ_1C_culture_1 represents reads of the EVs 20% fraction isolated from the <em>Vibrio kanaloae strain 1C</em> aquarium culture, with rep1 and rep2 denoting the first and second replicates, respectively.</p> <p>The EV reads were analyzed to facilitate a comprehensive evaluation of the representation and distribution of the mapped reads across the <em>Vibrio</em> genome.</p> <p>This mapping approach enables the discernment of whether the mapped reads exhibit a uniform distribution, characteristic of a random DNA release process, or a non-uniform distribution, indicating a proclivity for alignment with specific genetic loci within the <em>Vibrio</em> genome. This distinction is crucial for unraveling the underlying intricacies governing DNA release and transfer in <em>Vibrio kanaloae</em>, thereby advancing our understanding of these complex processes.</p>
Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction
<p>The data consists of Illumina raw reads obtained from prokaryotes from coastal Mediterranean seawaters in Alicante, Spain, over the course of one year. Illumina DNA prep kit (IDT, Ref. 20026930) was used following the manufacturer's protocol to generate and sequence the libraries for the obtained DNA samples from prokaryotic metagenomes. Subsequently, these libraries were sequenced using HiSeq X technology (150 PE, 1 lane) by two different facilities: Macrogen in Seoul, Republic of Korea, and the Genomics Unit of the Center for Genomic Regulation (CRG) in Barcelona, Spain. The dataset was used in order to ascertain the main microbial producers involved in the release of DNA packaged in EVs in our annual sampling.</p> <p>The samples are named according to the convention 'prokmeta[Month], where 'prokmeta' signifies prokaryotic metagenome, '[Month]' indicates the month of sampling, and "1" represents the forward , while (2) represent the reverse read. For instance, 'prokmetaDEC.1' denotes the prokaryotic metagenome for sample of December, with '1' indicating the forward read, while 'prokmetaDEC.2' represents the corresponding reverse read. This naming scheme is consistent across all samples in the dataset from sample of November 2021 to sample of June 2022.</p> <p> </p>
Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction.
<p>The dataset consists of third part of data for the same paper " Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction." Data were uploaded separately due to the limited space available for uploading which is f 50.00 GB and since i have more I could not upload them together.</p> <p>The data are Illumina raw reads obtained from vesicle fractions of 20%, isolated from Coastal Mediterranean seawaters in Alicante, Spain, over the course of one year. Illumina DNA prep kit (IDT, Ref. 20026930) was used following the manufacturer's protocol to generate and sequence the libraries for the obtained DNA samples from EVs 20% fraction metagenomes. Subsequently, these libraries were sequenced using HiSeq X technology (150 PE, 1 lane) by two different facilities: Macrogen in Seoul, Republic of Korea, and the Genomics Unit of the Center for Genomic Regulation (CRG) in Barcelona, Spain. The dataset was used in order to ascertain the main microbial organisms involved in the production of EVs and packaging of DNA into those EVs in our annual sampling and the types of genes that were packaged in vessicles isolated from the Coastal Mediterranean seawaters (Functional annotation of genes packaged in vesicles).</p> <p> The data are labeled as "EVs_20_DEC_1.fastq" which denotes the vesicle 20% Optiprep fraction for sample collected in December, with "1" indicating the forward read, while "EVs_20_DEC_2.fastq" represents the corresponding reverse read. This naming scheme is consistent across all vesicle fraction samples in the dataset.</p>
Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction
<p>The data consists second part of data for the same paper " Annual dynamics and metagenomics of marine vesicles: a layer of complexity in the dissolved organic fraction." Data were uploaded separately due to the limited space available for uploading.</p> <p>The data are Illumina raw reads obtained from vesicle fractions of 25%, isolated from coastal Mediterranean seawaters in Alicante, Spain, over the course of one year. Illumina DNA prep kit (IDT, Ref. 20026930) was used following the manufacturer's protocol to generate and sequence the libraries for the obtained DNA samples from EVs fractions metagenomes. Subsequently, these libraries were sequenced using HiSeq X technology (150 PE, 1 lane) by two different facilities: Macrogen in Seoul, Republic of Korea, and the Genomics Unit of the Center for Genomic Regulation (CRG) in Barcelona, Spain. The dataset was used in order to ascertain the main microbial organisms involved in the production of EVs and packaging of DNA into those EVs in our annual sampling and the types of genes that were packaged in vessicles isolated from the Coastal Mediterranean seawaters (Functional annotation of genes packaged in vesicles).</p> <p> The data are labeled as "EVs_25_DEC_1.fastq" which denotes the vesicle 25% Optiprep fraction for sample collected in December, with "1" indicating the forward read, while "EVs_25_DEC_2.fastq" represents the corresponding reverse read. This naming scheme is consistent across all vesicle fraction samples in the dataset. </p>
Dataset for the Global Prediction Of Total Organic Carbon In Marine Sediments Using Deep Neural Networks (nn-toc)
<p>The data folder contains the raw features and labels used for training machine learning models to predict total organic carbon in marine sediments. </p> <p>The data folder has three subfolders:</p> <ol> <li>raw : contains the labels, features and other data used to train the machine learnign models</li> <li>interim : transformed data, which has to be reproduced</li> <li>output : output from the models, used for analysis and visualisation</li> </ol> <p>The data folder has to be integrated in the Git repository nn-toc, to execute the code.</p> <p> </p> <p> </p>
Data from: Skeletal mineralogy of marine organisms shaped by seawater temperature and evolutionary history - a case study of cheilostome bryozoans
<p>The record of CaCO<sub>3</sub> biominerals serves as a valuable repository documenting Earth's evolutionary history and environmental changes. An in-depth understanding of the mineralogical diversity within calcifying organisms is essential for interpreting the evolutionary record of CaCO<sub>3</sub> and evaluating the adaptability of biomineralizers to past and future environmental change. To offer insights into the relative importance of environment vs. phylogenetic history in determining mineralogy, this study explores the modern-day global distribution of mineralogies in cheilostome bryozoans.</p> <p>Cheilostome bryozoans vary considerably in their mineral composition: in our dataset 65% of the species possess purely calcite skeletons, 15% exclusively employ aragonite, and 20% exhibit mixed (i.e., calcite and aragonite) mineralogies. Temperature is the predominant measured environmental factor influencing bryozoan skeletal mineralogy, accounting for 20% of its variability across species, when phylogenetic relatedness is unaccounted for. Bryozoans in lower latitudes, characterized by higher seawater temperatures, have higher aragonite concentrations. By accounting for phylogenetic structure using a subset of 87 species for which we have topological information, 40% of the observed mineralogical variability could be attributed to present-day temperature. In contrast, depth and salinity played minor roles, explaining less than 1% of the mineralogical variation each.</p> <p>This study emphasizes the influence of evolutionary history on the mineralogical variability of calcifying organisms, even when it can be shown that a single environmental factor (temperature) explains a substantial amount of this variability. When confronted with changing temperature, calcifiers such as bryozoans are likely to respond in diverse ways, depending on the species, given their phylogenetic relatedness and the external conditions they meet.</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.