Progress in Oceanography

Standing stocks of biomass and biovolume as directly and indirectly estimated from photographs using a length-weight relationship (LWR) approach and a generalised volumetric method (GVM). The datasets correspond to: - the fresh trawl-caught specimens from the Porcupine Abyssal Plain Sustained Observatory (PAP-SO; 4850m water depth, northeast Atlantic); - the case study of benthic ecology based on a large photographic dataset derived from AUV surveys on the Celtic Shelf (100 m water depth, northeast Atlantic); - the inter-operator variation assessment of biomass and biovolume estimation using the LWR method and the GVM.

This file contains data from a study done in the Barcelona coastal ecosystem (NW Mediterranean) consisting in eight cruises done in summer and winter-spring seasons. Phytoplankton primary production and chromophoric dissolved organic matter were measured. For a more detailed description of the study see: Guallar, C., Flos, J., 2017. Enhanced primary production in summer and winter-spring seasons in a populated NW Mediterranean coastal ecosystem. J. Sea Res. 120, 1–12. doi:10.1016/j.seares.2016.10.009

It is the data used in our research, including catch data for the Yellow Sea and East China Sea Large Marine Ecosystems, local-scale environmental variables, large-scale climate indices and fishing effort.

Appendix Collection year, month, positions, genus, species, body mass, δ13C, δ15N, organisms and vertical habitat in the North western Pacific for estimating the isoscapes.

Corrected (subtracting the effect of surface tides) PIES-observed acoustic travel time data at diurnal and semidiurnal frequency band.

Surface and underwater photosyntheically active radiation (PAR) for the Boulder Patch, Stefansson Sound, Alaska. Year range:1984-2015.

This github code is a simple, 1-dimensional NPZD model in Matlab, based on Kuhn et al. (2015, doi.org/10.1016/j.pocean.2015.07.004), with a Graphical User Interface (GUI). The model is representative of a location at 50 degree N in the North Atlantic Ocean and the mixed layer evolution from this location is imposed. The model is run for 2 years, but only the 2nd year is shown in the auto-generated plots. The satellite-observed surface phytoplankton evolution at this location is shown for comparison in the surface property plot. The GUI is called from the Matlab command line as follows: >> GUI_NPZD A window will pop up that allows the user to modify 4 parameters: the latitude of solar forcing, the initial nutrient concentration, the maximum phytoplankton growth rate, and the maximum zooplankton grazing rate. These parameters can be adjusted by using the sliders or typing new values directly into the corresponding editbox. If the value entered is outside the allowable range indicated by the slider, it will be reset to the corresponding allowable maximum or minimum. The buttons below the four sliders allow the user to run the model or quit the GUI. The evolution of state variables at the surface layer will be written into a Matlab file along with essential meta-information. The code is also used in the article "Ocean Biogeochemical Modelling" in Nature Review Methods Primers by Fennel et al. (2022).

This dataset contains the results of the fluorescent dissolved organic matter characterisation (FDOM) and water mass optimum multiparameter analysis from the MAFIA cruise (Migrants and Active Flux In the Atlantic ocean). Samples were collected in the tropical and subtropical Atlantic during the MAFIA cruise (April 2015) on board the BIO Hespérides. Seawater samples for biogeochemical analyses were collected at 13 stations (from the Brazilian coast to the Canary Islands), from the surface down to 3500 m, using a General Oceanics oceanographic rosette equipped with 24 l PVC Niskin bottles. Oxygen solubility was computed using the equation of Benson and Krause (1984). AOU (µmol/kg) was calculated by subtracting measured oxygen concentration from the oxygen solubility values at saturation, with respect to the atmosphere. Fluorescence measurements were performed with a Perkin-Elmer LS55 spectrofluorometer and FDOM was characterised by means of a Parallel Factor analysis. The flag denotes if FDOM values were from direct measurement or are interpolated values (some interpolated values were added to match the 16S amplicon data). Integrated values were estimated by multiplying the discrete measurements by the distance, in meters, between samples.The aim of this dataset was to jointly characterise the FDOM and water mass distributions to infer the processes that shape the dissolved organic matter pool in the deep ocean (water mass mixing and history vs. local processes).

This dataset contains the results of the fluorescent dissolved organic matter characterisation (FDOM) and water mass optimum multiparameter analysis from the MAFIA cruise (Migrants and Active Flux In the Atlantic ocean). Samples were collected in the tropical and subtropical Atlantic during the MAFIA cruise (April 2015) on board the BIO Hespérides. Seawater samples for biogeochemical analyses were collected at 13 stations (from the Brazilian coast to the Canary Islands), from the surface down to 3500 m, using a General Oceanics oceanographic rosette equipped with 24 l PVC Niskin bottles. Oxygen solubility was computed using the equation of Benson and Krause (1984). AOU (µmol/kg) was calculated by subtracting measured oxygen concentration from the oxygen solubility values at saturation, with respect to the atmosphere. Fluorescence measurements were performed with a Perkin-Elmer LS55 spectrofluorometer and FDOM was characterised by means of a Parallel Factor analysis. Integrated values were estimated by multiplying the discrete measurements by the distance, in meters, between samples. The contribution of each water mass to each sample was objectively quantified applying an optimum multiparameter analysis (excluding mixed layer samples, here < 100 m). The aim of this dataset was to jointly characterise the FDOM and water mass distributions to infer the processes that shape the dissolved organic matter pool in the deep ocean (water mass mixing and history vs. local processes).

Model output was created using the high-performance computing support from Cheyenne (https://doi.org/10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation (NSF).