Review of algorithms estimating export production from satellite derived properties

Whereas the vertical transport of biomass from productive surface waters to the deep ocean (the biological pump) is a critical component of the global carbon cycle, its magnitude and variability is poorly understood. Global-scale estimates of ocean carbon export vary widely, ranging from ∼5 to ∼20 Gt C y – 1 due to uncertainties in methods and unclear definitions. Satellite-derived properties such as phytoplankton biomass, sea surface temperature, and light attenuation at depth provide information about the oceanic ecosystem with unprecedented coverage and resolution in time and space. These products have been the basis of an intense effort over several decades to constrain different biogeochemical production rates and fluxes in the ocean. One critical challenge in this effort has been to estimate the magnitude of the biological pump from satellite-derived properties by establishing how much of the primary production is exported out of the euphotic zone, a flux that is called export production. Here we present a review of existing algorithms for estimating export production from satellite-derived properties, available in-situ datasets that can be used for testing the algorithms, and earlier evaluations of the proposed algorithms. The satellite-derived products used in the algorithm evaluation are all based largely on the Ocean Colour Climate Change Initiative (OC-CCI) products, and carbon products derived from them. The different resources are combined in a meta-analysis

How Can Present and Future Satellite Missions Support Scientific Studies that Address Ocean Acidification?

Space-based observations offer unique capabilities for studying spatial and temporal dynamics of the upper ocean inorganic carbon cycle and, in turn, supporting research tied to ocean acidification (OA). Satellite sensors measuring sea surface temperature, color, salinity, wind, waves, currents, and sea level enable a fuller understanding of a range of physical, chemical, and biological phenomena that drive regional OA dynamics as well as the potentially varied impacts of carbon cycle change on a broad range of ecosystems. Here, we update and expand on previous work that addresses the benefits of space-based assets for OA and carbonate system studies. Carbonate chemistry and the key processes controlling surface ocean OA variability are reviewed. Synthesis of present satellite data streams and their utility in this arena are discussed, as are opportunities on the horizon for using new satellite sensors with increased spectral, temporal, and/or spatial resolution. We outline applications that include the ability to track the biochemically dynamic nature of water masses, to map coral reefs at higher resolution, to discern functional phytoplankton groups and their relationships to acid perturbations, and to track processes that contribute to acid variation near the land-ocean interface.This is the publisher’s final pdf. The published article is copyrighted by Oceanography Society and can be found at: https://doi.org/10.5670/oceanog.2015.3

Primary-productivity in Upwelling Systems (PRIMUS)

Conferencia sobre los Sistemas de Afloramiento de Borde Oriental (EBUS): Pasado, Presente y Futuro & Segunda Conferencia Internacional sobre el Sistema de Corrientes de Humboldt, 19-23 de Septiembre de 2022, Lima, PerúThe ESA-supported Primary-productivity in Upwelling Systems (PRIMUS) project aims to provide the best possible characterisation of net primary productivity (NPP) and its relationship to upwelling in Atlantic Eastern Boundary Upwelling Systems (EBUS), including the Iberian/Canary and Benguela systems. It will create a 25-year time series of 1-km satellite-derived NPP over the Atlantic, and, experimentally, at higher-resolution (300m) using the unique capabilities of the MERIS and OLCI satellite sensors. PRIMUS will use these data to advance analyses of Atlantic EBUS including temporal and spatial variability in NPP and its statistical relationship to upwelling and climate indices (such as the North Atlantic Oscillation). PRIMUS will also conduct eight further science cases in specific science áreas / regional settings: aquaculture in Galicia; fisheries and eutrophication in the Portuguese upwelling region; potential EBUS impacts on ocean carbón pools; Lagrangian estimates of NPP; and air-sea interaction and acidification impacts. Science cases will make use of EO and in situ data, as well as numerical model outputs (freely available through the EU’s Copernicus and elsewhere) to investigate the 4D character of EBUS, for example linking Lagrangian NPP with sediment traps samples at depth. PRIMUS will also conduct demonstrations that transfer science into solutions for society, working together with scientific, agency, policy and commercial “early-adopters”, building on three science case studies (EBUS and aquaculture; fisheries; and eutrophication monitoring). Furthermore, evaluating transition of data production to operational initiatives such as Copernicus and GMES and Africa and the potential for data exploitation by the European and international ecosystem modelling community. This communication will present initial results from the 25-year NPP time series and high resolution NPP computations as well as selected science casesN

Global beta diversity patterns of microbial communities in the surface and deep ocean

This is contribution 1112 from AZTI Marine Research Division.-- 14 pages, 4 figures, 3 tables, supporting information https://doi.org/10.1111/geb.13572.-- Data Availability Statement: DNA sequences for surface prokaryotes are publicly available at the European Nucleotide Archive [http://www.ebi.ac.uk/ena; accession number PRJEB25224 (16S rRNA genes)], for deep prokaryotes at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (http://www.ncbi.nlm.nih.gov/Traces/sra) under accession ID SRP031469, and for surface and deep picoeukaryotes at the European Nucleotide Archive with accession number PRJEB23771 (http://www.ebi.ac.uk/ena). Environmental data used in this study are available from https://github.com/ramalok/malaspina.surface.metabacoding, Giner et al. (2020) and Salazar et al. (2015). The code to analyze the data and produce the figures of this research is available from the corresponding author upon request.-- This is the pre-peer reviewed version of the following article: Ernesto Villarino, James R. Watson, Guillem Chust ,A. John Woodill, Benjamin Klempay, Bror Jonsson, Josep M. Gasol, Ramiro Logares, Ramon Massana, Caterina R. Giner, Guillem Salazar, X. Anton Alvarez-Salgado, Teresa S. Catala, Carlos M. Duarte, Susana Agusti, Francisco Mauro, Xabier Irigoien, Andrew D. Barton; Global beta diversity patterns of microbial communities in the surface and deep ocean; Global Ecology and Biogeography 31(11): 2323-2336 (2022), which has been published in final form at https://doi.org/10.1111/geb.13572. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsAim: Dispersal and environmental gradients shape marine microbial communities, yet the relative importance of these factors across taxa with distinct sizes and dispersal capacity in different ocean layers is unknown. Here, we report a comparative analysis of surface and deep ocean microbial beta diversity and examine how these patterns are tied to oceanic distance and environmental gradients. Location: Tropical and subtropical oceans (30°N–40°S). Time period: 2010-2011. Major taxa studied: Prokaryotes and picoeukaryotes (eukaryotes between 0.2 and 3 μm). Methods: Beta diversity was calculated from metabarcoding data on prokaryotic and picoeukaryotic microbes collected during the Malaspina expedition across the tropical and subtropical oceans. Mantel correlations were used to determine the relative contribution of environment and oceanic distance driving community beta diversity. Results: Mean community similarity across all sites for prokaryotes was 38.9% in the surface and 51.4% in the deep ocean, compared to mean similarity of 25.8 and 12.1% in the surface and deep ocean, respectively, for picoeukaryotes. Higher dispersal rates and smaller body sizes of prokaryotes relative to picoeukaryotes likely contributed to the significantly higher community similarity for prokaryotes compared with picoeukaryotes. The ecological mechanisms determining the biogeography of microbes varied across depth. In the surface ocean, the environmental differences in space were a more important factor driving microbial distribution compared with the oceanic distance, defined as the shortest path between two sites avoiding land. In the deep ocean, picoeukaryote communities were slightly more structured by the oceanic distance, while prokaryotes were shaped by the combined action of oceanic distance and environmental filtering. Main conclusions: Horizontal gradients in microbial community assembly differed across ocean depths, as did mechanisms shaping them. In the deep ocean, the oceanic distance and environment played significant roles driving microbial spatial distribution, while in the surface the influence of the environment was stronger than oceanic distanceData collection was funded by the Malaspina 2010 Circumnavigation Expedition project (Consolider-Ingenio 2010, CSD2008-00077) and cofunded by the Basque Government (Department Deputy of Agriculture, Fishing and Food Policy). We acknowledge funding from the Spanish Government through the “Severo Ochoa Center of Excelence” accreditation CEX2019-000928-S. [...] We also acknowledge H2020 Mission Atlantic project (Ref. Grant Agreement Number 862428). EV was supported by an international exchange post-doc scholarship to Scripps Institution of Oceanography and Oregon State University granted by the Education Department of the Basque GovernmentPeer reviewe

Experimental study of differentially rotating supersonic plasma flows produced by aluminium wire array Z-pinches

A novel approach to cylindrical wire array z-pinches has been developed in order to create a rotating plasma flow analogous to astrophysical accretion discs. The method involves subjecting the wire array to a cusp magnetic field (B_r) to create converging off axis ablation streams to form a rotating flow. The rotation is sustained by the ram pressure of the ablation streams in a quasi-equilibrium state for approximately 150 ns. This corresponds to one full rotation of the plasma about the axis. The rotating plasma is supersonic with Mach number ~2 and a radially constant rotation velocity between 60 and 75 km/s; the angular velocity therefore has an r^-1 dependence and the flow is differential. A Thomson scattering diagnostic is used to measure the electron and ion temperatures as Te ~30 eV and Ti >55 eV and the ionisation of the plasma (Z) between 6 and 8. These parameters are used to calculate the Reynolds number (10^5 to 10^6) and magnetic Reynolds numbers (20 to 100) which are large enough for viscous and resistive effects to be negligible on the large scale of the flow. These are of sufficient magnitude for the experiment to be scalable to astrophysical accretion discs. Further more the Reynolds number for the experiment is large enough for shear instabilities to manifest in the plasma. Some evidence for this can be seen in XUV images and Thomson spectra which indicate the development of perturbations and vorticity within the flow. Predictions for the growth rate of the Kelvin Helmholtz instability, 12 to 40 ns, agree reasonably well with the observed perturbation growth of ~30 ns. It is also possible that shear instabilities are driving hydrodynamic turbulence. Turbulent heating of the plasma could explain the approximately 500 eV increase in the ion temperature observed from some Thomson spectra. Further work is required however to prove the existence of shear flows and turbulence within the experiments.Open Acces

Some Concepts of Estuarine Modeling

If an estuarine system is to be investigated using an oceanographic modeling approach, a decision must be made whether to use a simple and robust framework based on e.g. mass-balance considerations, or if a more advanced process-resolving three-dimensional (3-D) numerical model are necessary. Although the former are straightforward to apply, certain fundamental constraints must be fulfilled. 3-D modeling, even though requiring significant efforts to implement, generates an abundance of highly resolved data in time and space, which may lead to problems when attempting to specify the "representative state" of the system, a common goal in estuarine studies. In this thesis, different types of models suitable for investigating estuarine systems have been utilized in various settings. A mass-balance model was applied to investigate potential changes of water fluxes and salinities due to the restoration of a mangrove estuary in northern Colombia. Seiches, i.e. standing waves, in the Baltic Sea were simulated using a 2-D shallow-water model which showed that the dominating harmonic oscillation originates from a fjord seiche in the Gulf of Finland rather than being global. Another study pertaining to the Gulf of Finland used velocity-fields from a 3-D numerical model together with Lagrangian-trajectory analyses to investigate the mixing dynamics. The results showed that water from the Baltic proper is mixed with that from the river Neva over a limited zone in the inner parts of the Gulf. Lagrangian-trajectory analysis was finally also used as a tool to compare mass-balance and 3-D model results from the Gulf of Riga and the Bay of Gdansk, highlighting when and where each method is applicable. From the present thesis it can be concluded that the above described estuarine-modeling approaches not only require different levels of effort for their implementation, but also yield results of varying quality. If oceanographic aspects are to be taken into account within Integrated Coastal Zone Managment, which most likely should be the case, it is therefore important to decide as early as possible in the planning process which model to use, since this choice ultimately determines how much information about the physical processes characterizing the system the model can be expected to provide

TRACMASS: Lagrangian trajectory code

<p>This is the first public release of a functional time-analytical scheme for TRACMASS. The code is used for all the anaylsis in "More accurate and computationally efficient trajectory schemes with the TRACMASS Lagrangian trajectory code"</p

Variation of summer phytoplankton community composition and its relationship to nitrate and regenerated nitrogen assimilation across the North Atlantic Ocean

The North Atlantic Ocean is considered a nitrogen (N) limited system once vernal stabilisation of the water column alleviates light limitation and allows phytoplankton growth to deplete surface nutrients to virtually undetectable levels. Ammonium and other regenerated N forms are then the main surface N source for phytoplankton production. The effort to determine which phytoplankton groups contribute to long-term biological export production would be greatly aided by information on which phytoplankton groups are responsible for the assimilation of nitrate, as opposed to those assimilating predominantly regenerated N. In this study, we used the natural abundance N isotopes to examine basin-scale patterns of nitrate and regenerated N assimilation and evaluated the relationships between these trends and phytoplankton community composition. Samples were collected during a summertime cruise transect (August–September 2013) from the subtropical (36°N 73°W) to the subarctic (54°N 20°W) North Atlantic and analysed for the N isotopic composition (δ15N vs. N2 in air) of particulate nitrogen (PN) and nitrate, size-fractionated chlorophyll a, and phytoplankton group biomass using flow cytometry. The depth of the 300 nmol l−1 nitrate isopleth shoaled from the subtropics (79 m), where phytoplankton stripped surface waters of nitrate, to the subarctic, where it intersected with the surface and the upward nutrient supply drove a summer phytoplankton bloom. The δ15N of PN above the nitracline increased from the subtropics (−0.3‰) to the subarctic (4.2‰), reflecting both a change in the δ15N of the subsurface nitrate source (from 2.4‰ to 5.1‰) and increased reliance by phytoplankton on nitrate relative to regenerated N. Throughout the transect, the phytoplankton community was mainly composed of pico- and nano-sized cells (>88% of chlorophyll a in the <20 µm size fraction). In the part of the transect southwest of the Grand Banks, Prochlorococcus and Synechococcus together dominated the picophytoplankton biomass (58% and 18% on average) and comprised 35% and 9%, respectively, of combined pico- and nanophytoplankton biomass. Pico- and nanoeukaryotes showed the opposite pattern, becoming more important closer to the subarctic (up to 31% and 86% of combined pico- and nanophytoplankton biomass, respectively). The North Atlantic summertime patterns in N assimilation implied by the N isotopes were consistent with a higher degree of nitrate assimilation by larger eukaryotic cells and greater reliance on regenerated N by cyanobacterial picophytoplankton, congruent with the observed biomass distributions

Large-scale microbial connectivity across ocean depth

Ocean Sciences Meeting (OSM), 16-21 February 2020, San Diego, CA, USAMarine microbes play central roles in marine food webs, carbon cycling, and climate regulation. Yet our understanding of how dispersal and environmental gradients shape microbial community composition in different layers of the ocean is limited. Here, using samples collected during the Malaspina expedition, we analyze spatial variations in the community structure of marine prokaryotes and pico-eukaryotes, and contrast patterns observed in the surface and deep ocean (4000 m). We found that in both groups, community similarity is significantly higher in the surface ocean relative to deep sea. We also found that for both groups, at the surface and at depth, community similarity decreases with horizontal distance. The decay in community similarity with horizontal distance is greater than expected from the strength of horizontal environmental gradients alone. In contrast, strong environmental gradients in the vertical direction correlate with large changes in prokaryotic community structure. We speculate that horizontal variations in marine microbiome assembly are strongly influenced by dispersal, while variations in the vertical direction are driven largely by niche segregationPeer reviewe

Particle Size Distribution and Size-partitioned Phytoplankton Carbon Using a Two-Component Coated-Spheres Bio-optical Model: Monthly Global 4 km Imagery Based on the OC-CCI v5.0 Merged Ocean Color Satellite Data Set

Monthly global 4km satellite products spanning September 1997 to December 2020. The data contains Particle Size Distribution (PSD) parameters of an assumed power-law PSD, absolute and fractional size-partitioned phytoplankton carbon and associated variables such as particulate organic carbon (POC) and Chlorophyll-a as derived from the PSD algorithm. The retrieval is based on a backscattering bio-optical model using two particle populations and coated spheres for phytoplankton inherent optical properties (IOP) modeling, and a retrieval using spectral angle mapping (SAM - where satellite spectra are classified using a comparison to a collection of modeled end-member spectra, by treating spectra as vectors and using their dot product). Partial uncertainties are given as standard deviation and are estimated using a combination of Monte Carlo simulations and analytical error propagation. An empirical tuning factor is given for attaining more realistic estimated model concentrations of POC and Chlorophyll-a. The tuning factor is multiplicative, to be applied in linear space. This tuning factor has not been applied to the monthly data, users can choose whether or not to apply it to absolute carbon and Chlorophyll-a concentrations. The factor does not affect retrievals of fractional contributions of phytoplankton size classes to total phytoplankton carbon. Monthly climatologies files and an overall climatology file are also provided, and in those files, both untuned (tuning factor not applied) and tuned (tuning factor applied) variables are provided, for user convenience. Input remote-sensing reflectance data are v5.0 of the Ocean Colour -Climate Change Initiative (OC-CCI) of the European Space Agency. The OC-CCI general reference is Sathyendranath et al. (2019; doi:10.3390/s19194285), and for v5.0 of the dataset, the reference is Sathyendranath et al. (2021; doi:10.5285/1dbe7a109c0244aaad713e078fd3059a). More detailed metadata, including geospatial metadata, are given in the netCDF files. Variable names should be self-explanatory. Quick browse images are provided as well. Coastlines in these quick browse images are from v2.3.7 of the GSHHS data set - see Wessel and Smith (1996) (doi:10.1029/96JB00104). Modeling and data processing was done in MATLAB ®