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Figure 1 in Evaluation of Plastic Shipping Bags for Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae) Containment
Figure 1. Diagram of Hypothenemus hampei (Ferrari) shipping bag observation arenas used in this experiment. Arenas were constructed of lidded 3.78 L (1-gal) glass jars with drying treated coffee in one of nine bag treatments suspended from the top by a hot-glued string tether to allow escaping (left) or not escaping (right) H. hampei observation in the bottom of the jar.
Dataset: Grindrod Shipping Holdings Ltd. (GRIN) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Flag Ship Acquisition Corporation (FSHPU) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Seanergy Maritime Holdings Corp. (SHIP) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Performance Shipping Inc. (PSHG) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Figure 4 in Investigating the risk of non-indigenous species introduction through ship hulls in Chile
Figure 4. Taxa distribution on ships' hulls of the three studied vessels (Esmeralda, USA and ARG tankers) (a) nMDS showing the taxa assemblages in protected vs. exposed areas of the ships' hulls. (b) Taxa richness in exposed and protected areas of the hulls of the three studied vessels. (c) Relationship between the number of taxa found on the hulls and the number of ports visited by each ship.
Figure 6 in Investigating the risk of non-indigenous species introduction through ship hulls in Chile
Figure 6. Distribution of the COI haplotypes of Ciona robusta per sample, with their number indicated in the barplot. For each sample, the number of specimens is indicated in parentheses. The correspondence between the haplotypes found in this study, and those referenced in GenBank is given in Table S3.
Figure 2 in Investigating the risk of non-indigenous species introduction through ship hulls in Chile
Figure 2. Location of the different areas of the vessel from which the samples were obtained. Protected areas: sea box, rope guard, water discharge holes, top of the rudder and the Kort nozzle. Exposed areas: bilge keel, the helm in general and the rudder. Modified from Sylvester and MacIsaac (2010).
Figure 5 in Investigating the risk of non-indigenous species introduction through ship hulls in Chile
Figure 5. Taxa richness recorded in the Talcahuano port on settlement plates made of different types of materials and maintained at different depths for two months total, considering the two periods of time. Values include averages and ± one standard error.
Figure 1 in Investigating the risk of non-indigenous species introduction through ship hulls in Chile
Figure 1. The black circle corresponds to the locality where the sampling was carried out in each type of sampling (ships, settlement plates in the port of Talcahuano and natural substrates in the El Manzano pier).
Figure 3. Graphical representation using a in Investigating the risk of non-indigenous species introduction through ship hulls in Chile
Figure 3. Graphical representation using a nMDS based on Bray-Curtis distances, of the taxa assemblages in each sampling type (ships, settlement plates in the Talcahuano port, and natural substrates at El Manzano pier). Stress value is 0.17.
Figure 8 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 8. Results for the long-term approach to future status. Equilibrium abundance relative to carrying capacity is shown for Sobs ¼ 10 and a range of multipliers of current levels of 2013 vessels. The model was projected forward 100 yr for each posterior sample under a constant multiplier (x-axis value). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. The probability that the population is depleted (i.e., below 60% of K) is shown as a curved line. The solid vertical line denotes the median ratio of vessels in 2050 to 2013, i.e., the multiplier in 2050 estimated by our vessel model.
Figure 7 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 7. Results of the short-term approach to future status. Future ship strikes, abundances, and abundances relative to carrying capacity for Sobs ¼ 10 are shown for three mitiga2013 tion cases (columns). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. "Status quo" means no additional mitigation, "mitigation" refers to halving the ship strikes after 2013, and "none" is a complete elimination of future ship strikes. The horizontal lines at 0.6 denote the level below which the population is considered depleted.
Figure 4 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 4. Posterior densities for the abundance relative to carrying capacity in 2013 for Sobs ¼ 10 (top) and Sobs ¼ 35 (bottom) and the two priors for r. The vertical line at 0.6 2013 2013 denotes the level below which the population is considered depleted.
Figure 6 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 6. Absolute abundance, the abundance estimates and anthropogenic mortalities for Sobs ¼ 10 and the two priors for r. The rectangles at the bottom denote total estimated mor2013 talities (median catches + median strikes) for each year. The five abundance estimates (points) are shown with their 95% confidence intervals (bars). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles.
Figure 2 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 2. Results of the vessel model. The points are data from worldwide statistics for vessels over 100 gross tons from Lloyd's of London, as used in Laist et al. (2001). Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles.
Figure 1 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 1. Prior and marginal posterior probability distributions for the parameters of the theta-logistic population dynamics model for Sobs ¼ 10 and both priors for r (columns).
Figure 3 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 3. Results of the ship strike model. Predicted ship strikes for the uninformative prior for r and observed ship strikes in 2013 as 10 or 35. Annual trajectories (panels A and B) are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. Panels C and D show the posterior distributions of strikes in 2013 (histogram) as well as the Poisson likelihood (line).
Figure 5 in Do ship strikes threaten the recovery of endangered eastern North Pacific blue whales?
Figure 5. Trajectories for Abundance relative to carrying capacity for Sobs ¼ 10 and both 2013 priors for r. Model trajectories are shown as filled gray areas representing the 0.95, 0.75, 0.5, 0.25, and 0.05 posterior percentiles. The horizontal lines at 0.6 denote the level below which the population is considered depleted.
Surface Marine Carbonate System Data (2019-2024) from Volunteer Observing Ship monitoring across the Western Mediterranean Sea
<p><strong><span><span>1.<span> </span></span></span></strong><strong><span>Introduction</span></strong></p> <p><span>We present here a high-resolution dataset which spans five years (February 2019 - February 2024) and is based on weekly physicochemical observations of the surface waters along the western boundary of the Mediterranean Sea. Data were automatically collected by a Surface Ocean Observation Platform (SOOP) operating in underway mode aboard the Volunteer Observing Ship (VOS) MV JONA SOPHIE (formerly RENATE P until November 2021), a container ship managed by Nisa Maritima on the route between the Canary Islands and Barcelona. A total of 92 routes were completed in the Mediterranean Sea during the observation period.</span></p> <p><span>The SOOP CanOA-VOS line, designed and maintained by the QUIMA research group at IOCAG-ULPGC, is part of Spain’s contribution to the Integrated Carbon Observation System (ICOS-ERIC) since 2021 and is recognized as an ICOS Class 1 Ocean Station, ensuring that the measurement equipment and data collection techniques meet ICOS-ERIC's high-quality standards and methodological recommendations. The data collected is also available at the ICOS Data Portal (<a href="https://www.icos-cp.eu/data-products/ocean-release">https://www.icos-cp.eu/data-products/ocean-release</a>).</span></p> <p><strong><span><span>2.<span> </span></span></span></strong><strong><span>Data collection</span></strong></p> <p><span>The dataset includes continuous monitoring of CO<sub>2</sub> levels in both surface ocean and low atmosphere, following protocols to ensure data comparability and quality given by Pierrot et al., (2009). A detailed description is provided by Curbelo-Hernández et al., 2021a, 2021b). An automated CO2 molar fraction (xCO2) measurement system, developed by Craig Nail and commercialized by General Oceanics™, was installed on the ship. This system integrates air and seawater equilibrators with a non-dispersive infrared analyzer by LICOR® for xCO2 detection. The analyzer is regularly calibrated using standard gases provided by the NOAA, traceable to the World Meteorological Organization (WMO). They were in the order of 0 ppm, 250 ppm, 400 ppm and 550 ppm until January 2021, when the gas bottles for standard 2 to 4 were changed for a new set with concentrations in the order of 300 ppm, 500 ppm and 800 ppm. </span></p> <p><span>In addition to xCO2, sea surface temperature (SST) and sea surface salinity (SSS) were monitored using high-precision instruments. The SST was monitored by using a SBE38 thermometer placed at the main seawater intake in the engine room, with a reported error of ±0.01ºC. A SBE45 thermosalinograph and a Hart Scientific HT1523 Handheld Thermometer, with reported errors of ±0.01ºC, were used to monitor the temperature at the entrance of the wet box and inside the equilibrator, respectively. The SBE45 thermosalinograph measured the sea surface salinity (SSS) with an estimated error of ±0.005.</span></p> <p><span>Discrete seawater samples were also collected during three round trips in February 2020, March 2021, and October 2023, for further analysis of total alkalinity and dissolved inorganic carbon. </span><span>A total of 102 discrete samples has been collected in the Mediterranean Sea. Total alkalinity (AT) and total inorganic carbon (CT) were determined using a VINDTA 3C according to Mintrop et al., 2000. AT was analyzed via potentiometric titration with HCl, following the carbonic acid endpoint method (Millero et al., 1993; Dickson and Goyet, 1994), while CT was determined through coulometric titration (Johnson et al., 1993). The VINDTA 3C was calibrated using Certified Reference Material (CRMs) by A. Dickson, ensuring an accuracy of ±1.5 </span><span>μ</span><span>mol kg-1 for AT and ±1.0 </span><span>μ</span><span>mol kg-1 for CT.</span></p> <p><span>The dataset contains some gaps, including a year-long gap from September 2021 to 2022 due to vessel maintenance and shorter gaps due to technical issues, which were addressed during routine maintenance. Some technical issues in 2020 were delayed due to COVID-19 constraints.</span></p> <p><strong><span>3. Dataset content</span></strong></p> <p><span>The dataset includes the following variables: </span></p> <p><span><span>·<span> </span></span></span><span>“Date” (dd/mm/yyyy)</span></p> <p><span><span>·<span> </span></span></span><span>“Time” (hh:mm:ss)</span></p> <p><span><span>·<span> </span></span></span><span>“Latitude”</span></p> <p><span><span>·<span> </span></span></span><span>“Longitude”</span></p> <p><span><span>·<span> </span></span></span><span>“equTemp”: seawater temperature measured inside the equilibrator using a Hart Scientific HT1523 Handheld Thermometer.</span></p> <p><span><span>·<span> </span></span></span><span>“stdVal”: value of the standard gases used for automatically calibrations.</span></p> <p><span><span>·<span> </span></span></span><span>“xCO2”: measured CO2 molar fraction without performing any correlation (raw data).</span></p> <p><span><span>·<span> </span></span></span><span>“atmPress”: Atmospheric pressure (units: atm).</span></p> <p><span><span>·<span> </span></span></span><span>“equPress”: Diffeence in pressure between the atmosphere and the equilibrator (units: atm).</span></p> <p><span><span>·<span> </span></span></span><span>“SST_SBE38”: Sea surface temperature measured with a SBE38 thermometer at the main seawater intake of the vessel.</span></p> <p><span><span>·<span> </span></span></span><span>“Temp_SBE45”: Seawater temperature measured with a SBE45 thermosalinograph just before the water supply to the equilibrator.</span></p> <p><span><span>·<span> </span></span></span><span>“SSS_SBE45”: Sea surface salinity measured with a SBE45 thermosalinograph just before the water supply to the equilibrator.</span></p> <p><span><span>·<span> </span></span></span><span>“xCO2corr_sw”: CO2 molar fraction measured in the sea surface after correction by using standard gases.</span></p> <p><span><span>·<span> </span></span></span><span>“xCO2corr_atm”: CO2 molar fraction measured in low atmosphere after correction by using standard gases.</span></p> <p><span><span>·<span> </span></span></span><span>“pCO2sw”: Partial pressure of CO2 in the sea surface (units: µatm).</span></p> <p><span><span>·<span> </span></span></span><span>“pCO2atm”: Partial pressure of CO2 in low atmosphere (units: µatm).</span></p> <p><span><span>·<span> </span></span></span><span>“fCO2sw”: fugacity of CO2 in the sea surface (units: µatm).</span></p> <p><span><span>·<span> </span></span></span><span>“fCO2atm”: fugacity of CO2 in low atmosphere (units: µatm).</span></p> <p><span><span>·<span> </span></span></span><span>“AT”: Total Alkalinity (µmol kg-1)</span></p> <p><span><span>·<span> </span></span></span><span>“CT”: Total Inorganic Carbon (µmol kg-1)</span></p> <p><span><span>·<span> </span></span></span><span>“pH”: pH in surface seawater at in situ temperature computed in CO2sys using as input variables AT and fCO2sw.</span></p> <p><span><span>·<span> </span></span></span><span>“pH25”: pH in surface seawater at constant temperature of 25ºC computed in CO<sub>2sys</sub> using as input variables AT and fCO2sw.</span></p> <p><span> </span></p> <p><strong><span>Acknowledgement</span></strong></p> <p><span>This research was supported by the Canary Islands Government and the Loro Parque Foundation through the CanBIO project, CanOA subproject (2019–2024), and the CARBOCAN agreement (Consejería de Transición Ecológica y Energía, Gobierno de Canarias). We would like to thank the JONA SOPHIE ship owner, the NISA-Marítima company and the captains and crew members for the support during this collaboration. Special thanks to the technician Adrian Castro-Alamo for biweekly equipment maintenance and discrete sampling of total alkalinity aboard the ship. The SOOP CanOA-VOS line is part of the Spanish contribution to the Integrated Carbon Observation System (ICOS-ERIC; https://www.icos-cp.eu/) since 2021 and has been recognized as an ICOS Class 1 Ocean Station. <span>The participation of D. C-H was funded by the PhD grant PIFULPGC-2020-2 ARTHUM-2</span></span></p>
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DANDI Archive for NWB datasets
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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.