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FIGURE 11 in A new species of Cymodoce Leach, 1814 (Crustacea: Isopoda: Sphaeromatidae) based on morphological and molecular data, with a key to the Northern Indian Ocean species

FIGURE 11. Cymodoce waegelei sp. nov., SEM, paratype (ZMH-K-42595); A, dorsal view; B, pleotelson anterodorsal part; C, pleotelson dorsal view; D, details of pleotelson dorsal boss; E, frons and anterior of head.

FIGURE 7 in A new species of Cymodoce Leach, 1814 (Crustacea: Isopoda: Sphaeromatidae) based on morphological and molecular data, with a key to the Northern Indian Ocean species

FIGURE 7. Cymodoce waegelei sp. nov., holotype (ZMH-K-42594); A, dorsal view; B, lateral view; C, antennula; D, antenna; E, epistome; F, female.

FIGURE 14. Unrooted Neighbour-joining phylogram the 28S in A new species of Cymodoce Leach, 1814 (Crustacea: Isopoda: Sphaeromatidae) based on morphological and molecular data, with a key to the Northern Indian Ocean species

FIGURE 14. Unrooted Neighbour-joining phylogram the 28S rDNA: D8 expansion fragment of Cymodoce delavrii, C. tribullis and C. waegelei based on p-distances.

FIGURE 5. Cymodoce tribullis Harrison & Holdich 1984 in A new species of Cymodoce Leach, 1814 (Crustacea: Isopoda: Sphaeromatidae) based on morphological and molecular data, with a key to the Northern Indian Ocean species

FIGURE 5. Cymodoce tribullis Harrison & Holdich 1984, (QM W31864); A, SEM, dorsal view; B, pleotelson anterodorsal part; C, pleotelson dorsal boss with lateral tubercles; D, pleotelson dorsal view; E, paratype (QM W9643); E, pleotelson dorsal view; F, pleotelson anterodorsal part.

FIGURE 4. Cymodoce tribullis Harrison & Holdich 1984 in A new species of Cymodoce Leach, 1814 (Crustacea: Isopoda: Sphaeromatidae) based on morphological and molecular data, with a key to the Northern Indian Ocean species

FIGURE 4. Cymodoce tribullis Harrison & Holdich 1984, paratype (QM W9643); A–E, pleopods 1–5; F, penes.

opencc-by-4.0Nov 2024View details →

Supporting data for: "Heritage of Tethyan oceanic transform faults within Alpine orogens: Paleomagnetic evidence from the Shkoder-Peja transverse zone (Northern Albania)"

Paleomagnetic data from the Shkoder-Peja transverse zone, collected in the Krasta-Cukali and Albanian Alps tectonic units (Northern Albania). To open and navigate with Remasoft software (https://www.agico.com/text/software/remasoft/remasoft.php).

Moisture Flux for the Arctic Ocean AIRS-AMSU Version 6 data

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Data from: Do genetic ecotypes drive physiological responses to a changing world? Indications that coastal Atlantic cod are better adapted to ocean stressors

Genotypic information for 48 Atlantic cod (Gadus morhua) used in study by Perry et al.: Do genetic ecotypes drive physiological responses to a changing world? Indications that coastal Atlantic cod are better adapted to ocean stressors.Genotypes provided in the GenePop format, with the 3776 SNP loci used detailed in Henriksson et al. (in prep). For further information, please contact Simon Henriksson (simon.henriksson@gu.se).

Monthly Turbulent Flux Dataset for the Arctic Ocean using AIRS-AMSU version 6 data

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Data for Responses of Marine Trophic Levels to the Combined Effects of Ocean Acidification and Warming

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opencc-by-4.0Dec 2023View details →

Free-air gravity anomaly data at the continental margin and oceanic basin north of the Daimao Seamount of the South China Sea

This archive includes the free-air gravity anomaly data (in mGal) from the continental margin to the oceanic basin north of the Daimao Seamount in the South China Sea. The data was collected with the help of the Guangzhou Marine Geological Survey.

opencc-by-4.0Dec 2023View details →

Dataset for "Enhanced Regional Ocean Ensemble Data Assimilation Through Atmospheric Coupling in the SKRIPS Model"

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embargoedcc-by-4.0Feb 2024View details →

FESOM-REcoM model data: Predicting future distribution of Antarctic toothfish (Dissostichus mawsoni), with implications for Marine Protected Areas in the Southern Ocean

This data set belongs to "Predicting future distribution of Antarctic toothfish (Dissostichus mawsoni), with implications for Marine Protected Areas in the Southern Ocean" by <a>Rebecca Konijnenberg, Cara Nissen, Casper Kraan, Jilda Cavacco, Peter Yates, Philippe Ziegler, and Katharina Teschke (in preparation). </a> Contact for data set: cara.nissen@colorado.edu The data provided here are post-processed from the raw FESOM1.4-REcoM2 model output which can be obtained  at the World Data Center for Climate (WDCC): <a href="https://www.wdc-climate.de/ui/project?acronym=HighRes_highLat_SO">https://www.wdc-climate.de/ui/project?acronym=HighRes_highLat_SO</a> simA (historical simulation): <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_hist_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_hist_vA_vC</a> simA-ssp126: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s126_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s126_vA_vC</a> simA-ssp245: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s245_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s245_vA_vC</a> simA-ssp370: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s370_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s370_vA_vC</a> simA-ssp585: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s585_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s585_vA_vC</a> simB (control simulation): <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_B_1921_cA_cC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_B_1921_cA_cC</a> Here, we provide decadal monthly climatologies of the following variables: sea-ice fraction, surface small-phytoplankton chlorophyll, surface diatom chlorophyll, as well as potential temperature, practical salinity and oxygen concentrations (all at the surface, at the bottom, at 100m, at 250m, at 500m, at 1000m, and at 1500m). For example, "tos" is temperature in ocean at surface", while "tob" is "temperature in ocean at bottom" (with bottom here being the deepest available model grid cell at each location). We also provide the script used to re-grid the original model output to the regular 0.25° x 0.0625° mesh used in this study.

opencc-by-4.0Dec 2023View details →

Code and data for the paper "Dominating inflation of the Arctic Ocean's Beaufort Gyre in a warming climate"

Code and data used to generate the figures for the paper "Dominating inflation of the Arctic Ocean's Beaufort Gyre in a warming climate".

opencc-zeroNov 2021View details →

Data from: Northwest range shifts and shorter wintering period of an Arctic seabird in response to four decades of changing ocean climate

Climate change is altering the marine environment at a global scale, with some of the most dramatic changes occurring in Arctic regions. These changes may affect the distribution and migration patterns of marine species throughout the annual cycle. Species distribution models have provided detailed understanding of the responses of terrestrial species to climate changes, often based on observational data; biologging offers the opportunity to extend those models to migratory marine species that occur in marine environments where direct observation is difficult. We used species distribution modelling and tracking data to model past changes in the non-breeding distribution of thick-billed murres Uria lomvia from a colony in Hudson Bay, Canada, between 1982 and 2019. The predicted distribution of murres shifted during fall and winter. The largest shifts have occurred for fall migration, with range shits of 211 km west and 50 km north per decade, compared with a 29 km shift west per decade in winter. Regions of range expansions had larger declines in sea ice cover, smaller increases in sea surface temperature, and larger increases in air temperature than regions where the range was stable or declining. Murres migrate in and out of Hudson Bay as ice forms each fall and melts each spring. Habitat in Hudson Bay has become available later into the fall and earlier in the spring, such that habitat in Hudson Bay was available for 21 d longer in 2019 than in 1982. Clearly, marine climate is altering the distribution and annual cycle of migratory marine species that occur in areas with seasonal ice cover.

opencc-by-4.0Jan 2022View details →

Code and data for "Seasonal Surface Eddy Mixing in the Kuroshio Extension: Estimation and Machine Learning Prediction" By Guan et al. Submitted to JGR Oceans.

This repository contains the code and data for the machine learning analysis of "Seasonal Surface Eddy Mixing in the Kuroshio Extension: Estimation and Machine Learning Prediction”By Guan et al. Submitted to JGR Oceans. Specifically, this repository contains the following items: (1) Codes for assessing the representation skill of the machine learning and linear regression (LR) methods. Three machine learning methods are considered: random forest (RF), back-propagation neural network (BP), and convolutional neural network (CNN). (2) Codes for assessing the prediction skill of the machine learning and LR methods.   (3) Seasonal-mean and annual-mean input data to run these codes.   (4) The package needed to run the random forest code, i.e. the RF_MexStandalone-v0.02 program package from https://code.google.com/archive/p/randomforest-matlab/downloads .

opencc-zeroJan 2022View details →

Phenotypic data for M. edulis responses to warming and ocean acidification

1. In mosaic marine habitats, such as intertidal zones, ocean acidification (OA) is exacerbated by high variability of pH, temperature, and biological CO2 production. The non-linear interactions among these drivers can be context-specific and their effect on organisms in these habitats remains largely unknown, warranting further investigation. 2. We were particularly interested in Mytilus edulis (the blue mussel) from intertidal zones of the Gulf of Maine (GOM), USA for this study. GOM is a hot spot of global climate change (average Sea Surface Temperature (SST) increasing by > 0.2 °C y−1 ) with > 60% decline in mussel population over the past 40 years. 3. Here, we utilize bioenergetic underpinnings to identify limits of stress tolerance in M. edulis from GOM exposed to warming and OA. We have measured whole-organism oxygen consumption rates and metabolic biomarkers in mussels exposed to control and elevated temperatures (10 vs. 15 °C, respectively) and current and moderately elevated PCO2 levels (~ 400 vs. 800 µatm, respectively). 4. Our study demonstrates that adult M. edulis from GOM are metabolically resilient to the moderate OA scenario but responsive to warming as seen in changes in metabolic rate, energy reserves (total lipids), metabolite profiles (glucose and osmolyte dimethyl amine) and enzyme activities (carbonic anhydrase and calcium-ATPase). 5. Our results are in agreement with recent literature that OA scenarios for the next 100-300 years do not affect this species, possibly as a consequence of maintaining its in vivo acid−base balance.

opencc-zeroFeb 2022View details →

Data from: Ocean acidification alters sperm responses to egg-derived chemicals in a broadcast spawning mussel

The continued and unprecedented emissions of anthropogenic carbon dioxide (CO2) are causing progressive ocean acidification (OA). While deleterious effects of OA on biological systems are well documented in the growth of calcifying organisms, lesser studied impacts of OA include potential effects on gamete interactions that determine fertilisation, which are likely to influence the many marine species that spawn gametes externally. Here, we explore the effects of OA on the signalling mechanisms that enable sperm to track egg-derived chemicals (sperm chemotaxis). We focus on the mussel Mytilus galloprovincialis, where sperm chemotaxis enables eggs to selectively bias fertilisation in favour of genetically compatible males. Using a factorial experimental design, we test whether the experimental manipulation of seawater pH (comparing ambient conditions to predicted end-of-century scenarios) alters these patterns of differential sperm chemotaxis. While we find no evidence that patterns of male-female gametic compatibility are impacted by OA, we do find that individual males exhibit consistent variation in how their sperm perform in lowered pH levels. This finding of individual variability in the capacity of ejaculates to respond to chemoattractants under acidified conditions suggests that climate change will exert considerable pressure on male genotypes that can withstand an increasingly hostile fertilisation environment.

opencc-by-4.0Mar 2022View details →

Data of publication "Impact of biomass burning and stratospheric intrusions in the remote South Pacific Ocean troposphere" by N. Daskalakis et al.

Modeled data and measured data as used for the publication " Impact of biomass burning and stratospheric intrusions in the remote South Pacific Ocean troposphere" by N. Daskalakis et al. All measured data were obtained from the official sources, and model results are described in the publication. Please refer to the manuscript for further information for the data and the model.