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234 results for “Global Ocean”
Supporting Data for Ocean acidification drives global reshuffling of ecological communities
<p>The paradigm that climate change will alter global marine biodiversity is one of the most widely accepted. Yet, its predictions remain difficult to test because laboratory systems are inadequate at incorporating ecological complexity, and common biodiversity metrics have varying sensitivity to detect change. Here, we test for the prevalence of global responses in biodiversity and community-level change to future climate (acidification and warming) from studies at volcanic CO<sub>2</sub> vents across four major global coastal ecosystems and studies in laboratory mesocosms. We detected globally replicable patterns of species replacements and community reshuffling under ocean acidification in major natural ecosystems, yet species diversity and other common biodiversity metrics were often insensitive to detect such community change, even under significant habitat loss. Where there was a lack of consistent patterns of biodiversity change, these were a function of similar numbers of studies observing negative vs positive species responses to climate stress. Laboratory studies showed weaker sensitivity to detect species replacements and community reshuffling in general. We conclude that common biodiversity metrics can be insensitive in revealing the anticipated effects of climate stress on biodiversity – even under significant biogenic habitat loss – and can mask widespread reshuffling of ecological communities in a future ocean. Whilst the influence of ocean acidification on community restructuring can be less evident than species loss, such changes can drive the dynamics of ecosystem stability or their functional change. Importantly, species identity matters, representing a substantial influence of future oceans.</p>
Asymmetries in the Southern Ocean contribution to global heat and carbon uptake
<p><span>Supporting data files in </span><span>Heat_Carbon_diag_CMIP6.tar.gz, NetCDF format </span><span>:</span></p> <p><span>(1) Carbon diagnostics</span></p> <p><span>Ocean carbon storage (Cstorage) and uptake (Cuptake) for each model</span></p> <p><span>time series of the global, north of 30N, south of 30S; four scenarios:</span></p> <p><span>historical, historical with GHG, historical with aerosols, SSP2-4.5</span></p> <p><span>Ocean_Cstorage_CMIP6_historical.nc</span></p> <p><span>Ocean_Cstorage_CMIP6_historical_greenhouse_gases.nc</span></p> <p><span>Ocean_Cstorage_CMIP6_historical_only_aerosols.nc</span></p> <p><span>Ocean_Cstorage_CMIP6_ssp245.nc</span></p> <p><span>Ocean_Cuptake_CMIP6_historical.nc</span></p> <p><span>Ocean_Cuptake_CMIP6_historical_greenhouse_gases.nc</span></p> <p><span>Ocean_Cuptake_CMIP6_historical_only_aerosols.nc</span></p> <p><span>Ocean_Cuptake_CMIP6_ssp245.nc</span></p> <p><span>Contributions of Southern Ocean (frac_SO) and northern ocean (frac_NO) </span></p> <p><span>carbon uptake to global carbon uptake, model mean and STD</span></p> <p><span>frac_Carb_hist-GHG.nc</span></p> <p><span>frac_Carb_historical.nc</span></p> <p><span>frac_Carb_ssp245.nc</span></p> <p><span>Carbon flux into the ocean, model mean and STD 2D fields for all 4 scenarios</span></p> <p><span>Carbon_flux_Figure3_UPD.nc </span></p> <p><span>(2) Heat diagnostics at the Top of the Atmosphere (TOA)</span></p> <p><span>TOA heat uptake (N) and radiative response (dR), 2D model mean and STD</span></p> <p><span>for all 4 scenarios; radiative forcing (F) from balance:<span> </span>N = F - dR</span></p> <p><span>N_dR_hist-GHG.nc</span></p> <p><span>N_dR_hist-aer.nc</span></p> <p><span>N_dR_historical.nc</span></p> <p><span>N_dR_ssp245.nc</span></p> <p><span>N_F_hist-GHG_std.nc</span></p> <p><span>N_F_hist-aer_std.nc</span></p> <p><span>N_F_historical_std.nc</span></p> <p><span>N_F_ssp245_std.nc</span></p> <p><span>(3) Ocean heat uptake diagnostics</span></p> <p><span>Ocean surface heat uptake (heat_flux), 2D fields for each model; all 4 scenarios</span></p> <p><span>Spatial_heat_content_and_flux_change_historical.nc</span></p> <p><span>Spatial_heat_mean_flux_change_hist_aer_and_hist_GHG.nc</span></p> <p><span>Spatial_heat_mean_flux_change_historical_and_ssp245_new_dates.nc</span></p> <p><span>Time series of ocean heat content anomaly (content_anom) and cumulative </span></p> <p><span>ocean surface heat flux (cumulative_flux) for each model;</span></p> <p><span>global, Southern Ocean (SO) and northern ocean (north); all 4 scenarios</span></p> <p><span>SO_north_and_global_allmodel_uptake_storage_and_transport_hist-GHG.nc</span></p> <p><span>SO_north_and_global_allmodel_uptake_storage_and_transport_hist-aer.nc</span></p> <p><span>SO_north_and_global_allmodel_uptake_storage_and_transport_historical.nc</span></p> <p><span>SO_north_and_global_allmodel_uptake_storage_and_transport_ssp245.nc</span></p> <p><span>Contributions of Southern Ocean (frac_SO) and northern ocean (frac_NO)</span></p> <p><span>heat uptake to global heat uptake, model mean and STD</span></p> <p><span>frac_OHU_hist-GHG.nc</span></p> <p><span>frac_OHU_historical.nc</span></p> <p><span>frac_OHU_ssp245.nc</span></p> <p><span>The diagnostics is based on the model outputs from the CMIP6 simulations, </span></p> <p><span>available from the Earth System Grid Federation at the CMIP6 archive </span></p> <p><span>https://esgf-node.llnl.gov/search/cmip6</span></p>
Code and Data for "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Journal of Geophysical Research: Oceans.
<p>This repository contains the code and data for the study of "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Journal of Geophysical Research: Oceans.</p> <p>Specifically, this repository contains the following items: </p> <p>(1) The codes needed for assessing the representation and prediction skills of Random Forest (RF) and Convolutional Neural Network (CNN) models. </p> <p>(2) Original and normalized data to run these codes.</p> <p>(3) Code here is built on early work from our laboratory (Guan et al., 2022; Zhang et al., 2023), though great modifications have been made tailored to our scientific question.</p> <div>[1] Guan, W., Chen, R., Zhang, H., Yang, Y., & Wei, H. (2022). Seasonal surface eddy mixing in the Kuroshio Extension: Estimation and machine learning prediction. Journal of Geophysical Research: Oceans, 127 (3), e2021JC017967.</div> <div>[2] Zhang, G., Chen, R., Li, X., Li, L., Wei, H., & Guan, W. (2023). Temporal variability of global surface eddy diffusivities: Estimates and machine learning prediction. Journal of Physical Oceanography, 53 (7), 1711–1730.</div>
Source data for "Submesoscales are a significant turbulence source in global ocean surface boundary layer"
<p>The files here provide the data and codes for reproducing figures from the paper titled "Submesoscales are a significant turbulence source in global ocean surface boundary layer" by Dong et al.</p> <p>It should be clarified that Fig.1 is originally generated by Python and then produced in Illustrator, and Fig.5 is completely produced by Illustrator. All other figures are produced by MATLAB.</p>
Data from: Going with the flow: the role of ocean circulation in global marine ecosystems under a changing climate
Ocean warming, acidification, deoxygenation and reduced productivity are widely considered to be the major stressors to ocean ecosystems induced by emissions of CO2. However, an overlooked stressor is the change in ocean circulation in response to climate change. Strong changes in the intensity and position of the western boundary currents have already been observed, and the consequences of such changes for ecosystems are beginning to emerge. In this study, we address climatically induced changes in ocean circulation on a global scale but relevant to propagule dispersal for species inhabiting global shelf ecosystems, using a high resolution global ocean model run under the IPCC RCP 8.5 scenario. The ¼ degree model resolution allows improved regional realism of the ocean circulation beyond that of available CMIP5-class models. We use a Lagrangian approach forced by modelled ocean circulation to simulate the circulation pathways that disperse planktonic life stages. Based on trajectory backtracking, we identify present-day coastal retention, dominant flow and dispersal range for coastal regions at the global scale. Projecting into the future, we identify areas of the strongest projected circulation change and present regional examples with the most significant modifications in their dominant pathways. Climatically-induced changes in ocean circulation should be considered as an additional stressor of marine ecosystems in a similar way to ocean warming or acidification.
Data from: A daily global mesoscale ocean eddy dataset from satellite altimetry
Mesoscale ocean eddies are ubiquitous coherent rotating structures of water with radial scales on the order of 100 kilometers. Eddies play a key role in the transport and mixing of momentum and tracers across the World Ocean. We present a global daily mesoscale ocean eddy dataset that contains ~45 million mesoscale features and 3.3 million eddy trajectories that persist at least two days as identified in the AVISO dataset over a period of 1993–2014. This dataset, along with the open-source eddy identification software, extract eddies with any parameters (minimum size, lifetime, etc.), to study global eddy properties and dynamics, and to empirically estimate the impact eddies have on mass or heat transport. Furthermore, our open-source software may be used to identify mesoscale features in model simulations and compare them to observed features. Finally, this dataset can be used to study the interaction between mesoscale ocean eddies and other components of the Earth System.
FIGURE 12. Bunburia javanica n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 12. Bunburia javanica n. sp. Holotype female: cheliped, right, (A) outer and (A`) inner views; pereopod-1, (B) right and (B`) left; (C–G) pereopods 2–6, right. Asterisk indicates missing part. Scale bar: 100 µm.
FIGURE 10. Bunburia javanica n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 10. Bunburia javanica n. sp. Southwest Java, Indonesia. Non-ovigerous female holotype (ZRC 2020.0316): habitus, (A) dorsal and (B) lateral views; (C) cephalothorax, ventral view; (D) pleotelson and uropods, ventral view. Asterisk indicates missing part. Scale bars: 1 mm (A–C); 100 µm (D).
FIGURE 14. Paranarthrura sundanensis n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 14. Paranarthrura sundanensis n. sp. Southwest Java, Indonesia. (A) Juvenile male allotype (ZRC 2020.0318) and (B–D) non-ovigerous female holotype (ZRC 2020.0317): habitus, (A) lateral (after right pereopods removed) and (B) dorsal views; (C) cephalothorax, ventral view; (D) pleotelson and uropods, ventral view. Asterisk indicates missing part. Scale bars: 0.5 mm (A–B); 100 µm (C–D).
FIGURE 11. Bunburia javanica n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 11. Bunburia javanica n. sp. Holotype female: (A) antennule, left; (B) antenna, left; (C) labrum; mandibles, (D) right and (D`) left; (E) labium; (F) maxillule; (G) maxillipeds. Asterisk indicates missing part. Scale bars: 100 µm.
FIGURE 17. Paranarthrura sundanensis n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 17. Paranarthrura sundanensis n. sp. Holotype female: setae at the base of (A) left and (B) right antennule; (C) heavily chitinised 'three-lobed' ventral process (in darker colouration) on chela; (D) dorsodistal spiniform setae on pereopod-5 propodus. Scale bars: 50 µm.
FIGURE 8. Agathotanais cilacapicus n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 8. Agathotanais cilacapicus n. sp. Paratype female: (A) cheliped, left; (B–G) pereopods 1–6, left. Asterisk indicates missing part. Scale bar: 100 µm.
FIGURE 7. Agathotanais cilacapicus n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 7. Agathotanais cilacapicus n. sp. Southwest Java, Indonesia. Non-ovigerous female paratype (ZRC 2020.0313): (A) antennule, left; (B) antenna, left; (C) labrum; mandibles, (D) left and (D`) right; (E) labium; (F) maxillule; (G) maxillipeds. Asterisk indicates missing part. Scale bars: 100 µm.
FIGURE 9. Agathotanais cilacapicus n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 9. Agathotanais cilacapicus n. sp. Paratype female: (A) terminal setae on antenna; medial (B) and lateral (C) projections on labium; (D) dorsodistal spiniform setae on pereopod-2 propodus. Scale bar: 50 µm.
FIGURE 6. Agathotanais cilacapicus n in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 6. Agathotanais cilacapicus n. sp. Southwest Java, Indonesia. Non-ovigerous female holotype (ZRC 2020.0311): habitus, (A) dorsal and (B) lateral views; (C) cephalothorax, ventral view; (D) pleotelson and uropods, ventral view. Scale bars: 0.5 mm (A, B); 200 µm (C); 100 µm (D).
FIGURE 4 in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 4. Global distribution of Paranarthrura. Specific and approximate locations represented by red circle and blue triangle, respectively. Approximate locations were based on coordinates provided for geographic name in www.marineregions.org when latitude and longitude are not available in the respective literature.
FIGURE 5 in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 5. Agathotanaids of Southwest Java, Indonesia: (A) Agathotanais cilacapicus n. sp.; (B) Bunburia javanica n. sp.; (C) Paranarthrura sundanensis n. sp..
FIGURE 2 in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 2. Global distribution of Allodaposia (red triangle), Bunburia (orange inverted triangle), Metagathotanais (green square) and Ozagathus (blue circle).
FIGURE 23 in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 23. Percentage frequency of sampling instruments used to collect Agathotanaidae. Value above each bar indicates the number of stations.
FIGURE 3 in Three new species of agathotanaids (Tanaidacea: Paratanaoidea: Tanaidomorpha) from the lower bathyal zone off southwestern Java, Indonesia, Indian Ocean with notes on the global distribution and diversity of Agathotanaidae
FIGURE 3. Global distribution of Paragathotanais. Specific and approximate locations represented by red circle and blue triangle, respectively. Approximate locations were based on coordinates provided for geographic name in www.marineregions. org when latitude and longitude are not available in the respective literature.
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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.