Variations in Remotely-Sensed Phytoplankton Size Structure of a Cyclonic Eddy in the Southwest Indian Ocean

Phytoplankton size classes were derived from weekly-averaged MODIS Aqua chlorophyll a data over the southwest Indian Ocean in order to assess changes in surface phytoplankton community structure within a cyclonic eddy as it propagated across the Mozambique Basin in 2013. Satellite altimetry was used to identify and track the southwesterly movement of the eddy from its origin off Madagascar in mid-June until mid-October, when it eventually merged with the Agulhas Current along the east coast of South Africa. Nano- and picophytoplankton comprised most of the community in the early phase of the eddy development in June, but nanophytoplankton then dominated in austral winter (July and August). Microphytoplankton was entrained into the eddy by horizontal advection from the southern Madagascar shelf, increasing the proportion of microphytoplankton to 23% when the chlorophyll a levels reached a peak of 0.36 mg·m−3 in the third week of July. Chlorophyll a levels declined to 50% of the population. As far as is known, this is the first study to investigate temporal changes in chlorophyll a and community structure in a cyclonic eddy propagating across an ocean basin in the southwest Indian Ocean

Seasonal variation in remotely-sensed phytoplankton size structure around Southern Africa

The three-component model of Brewin et al. (2010) computes fractional contributions of three phytoplankton size classes (micro- (> 20μm), nano- (2–20μm), picophytoplankton ( 1 mgm−3 was limited to shelf regions along the coasts of Southern Africa and Madagascar, while values 50% of the total Chla in these regions with little change throughout the year. The AR shelf differed, with picophytoplankton dominating in summer, and micro- and nanophytoplankton the rest of the year. In the open ocean domains of the NB, SB, and AB regions, nanophytoplankton dominated for most of the year, with picophytoplankton being more prevalent during summer and autumn. In contrast, in the AR open ocean, nanophytoplankton were dominant only during winter and early spring, whereas picophytoplankton dominated throughout the year in the MC open ocean. The refined model characterised previously unknown spatial and temporal changes in size structure in various ecosystems around Southern Africa

Ocean-colour products for climate-change studies: What are their ideal characteristics?

Ocean-colour radiometry is recognised as an Essential Climate Variable (ECV) according to the Global Climate Observing System (GCOS), because of its capability to observe significant properties of the marine ecosystem at synoptic to global scales. Yet the value of ocean colour for climate-change studies depends to a large extent not only on the decidedly important quality of the data per se, but also on the qualities of the algorithms used to convert the multi-spectral radiance values detected by the ocean-colour satellite into relevant ecological, bio-optical and biogeochemical variables or properties of the ocean. The algorithms selected from the pool of available algorithms have to be fit for purpose: detection of marine ecosystem responses to climate change. Marine ecosystems might respond in a variety of ways to changing climate, including perturbations to regional distributions in the quantity and in the type of phytoplankton present, their locations and in their seasonal dynamics. The ideal algorithms would be capable of distinguishing between abundance and type, and would not mistake one for the other. They would be robust to changes in climate, and would not rely on assumptions that might be valid only under current climatic conditions. Based on such considerations, we identify a series of ideal qualitative traits that algorithms for climate-change studies would possess. Necessarily, such traits would have to complement the quantitative requirements for precision, accuracy and stability in the data over long time scales. We examine the extent to which available algorithms meet the criteria, according to the work carried out in the Ocean Colour Climate Change Initiative, and where improvements are still needed

Twenty‐year variations in satellite‐derived chlorophyll‐a and phytoplankton size in the Bohai Sea and Yellow Sea

This is the final version. Available from American Geophysical Union (AGU) via the DOI in this record. Phytoplankton cell size is a useful ecological indicator for evaluating the response of phytoplankton community structure to environmental changes. Ocean‐color remote observations and algorithms have allowed us to estimate phytoplankton size classes (PSCs) at decadal scale, helping us to understand their trends under ocean warming. Here a large data set of pigments, derived through high performance liquid chromatography, was collected in the Bohai Sea (BS) and Yellow Sea (YS) between 2014 and 2016. The data set was used to reparametrize the sea surface temperature (SST)‐dependent three‐component model of Brewin et al. (2017) to the region. The model was validated using independent in situ data set and subsequently applied to satellite chlorophyll‐a data from Ocean Colour Climate Change Initiative, spanning from 1997 to 2016, to derive percentages of three PSCs to total chlorophyll‐a. Monthly‐averaged PSCs exhibited spatial‐temporal variations in the study area, linked to topography, temperature, solar radiation, currents, and monsoonal winds. In the surface central south Yellow Sea (SYS), influenced by bottom Yellow Sea Cold Water Mass, tight relationships between PSCs and environmental factors were observed, where high SST, high sea level anomaly, low mixed‐layer depth, and low wind speed resulted in higher proportions of nanoplankton and picoplankton from June to October. Significant interannual anomlies in PSCs were found associated with El Niño events in the central SYS, related to anomalies in SST. The refined model characterized 20‐year variations in chlorophyll‐a concentration and PSCs in complicated optical, hydrodynamic, and biogeochemical environments in the BS and YS.China Scholarship Council (CSC)National Natural Science Foundation of China (NSFC)WLKX

Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData availability statement: The in-situ datasets and code used for data processing can be found in the following GitHub repository https://github.com/rjbrewin/POC-PON-TChl-analysis. This includes an Jupyter Notebook Python Script, that can be run through binder (https://mybinder.org) without having to install Python software. Datasets from satellite observations of ocean colour are publicly accessible from https://www.oceancolour.org.Despite the critical role phytoplankton play in marine biogeochemical cycles, direct methods for determining the content of two key elements in natural phytoplankton samples, nitrogen (N) and carbon (C), remain difficult, and such observations are sparse. Here, we extend an existing approach to derive phytoplankton N and C indirectly from a large dataset of in-situ particulate N and C, and Turner fluorometric chlorophyll-a (Chl-a), gathered in the off-shore waters of the Northwest Atlantic and the Arabian Sea. This method uses quantile regression (QR) to partition particulate C and N into autotrophic and non-autotrophic fractions. Both the phytoplankton C and N estimates were combined to compute the C:N ratio. The algal contributions to total N and C increased with increasing Chl-a, whilst the C:N ratio decreased with increasing Chl-a. However, the C:N ratio remained close to the Redfield ratio over the entire Chl-a range. Five different phytoplankton taxa within the samples were identified using data from high-performance liquid chromatography pigment analysis. All algal groups had a C:N ratio higher than Redfield, but for diatoms, the ratio was closer to the Redfield ratio, whereas for Prochlorococcus, other cyanobacteria and green algae, the ratio was significantly higher. The model was applied to remotely-sensed estimates of Chl-a to map the geographical distribution of phytoplankton C, N, and C:N in the two regions from where the data were acquired. Estimates of phytoplankton C and N were found to be consistent with literature values, indirectly validating the approach. The work illustrates how a simple model can be used to derive information on the phytoplankton elemental composition, and be applied to remote sensing data, to map pools of elements like nitrogen, not currently provided by satellite services.European Space AgencySimons FoundationUK National Centre for Earth Observation (NCEOUKR

Micro-phytoplankton photosynthesis, primary production and potential export production in the Atlantic Ocean

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordMicro-phytoplankton is the >20 μm component of the phytoplankton community and plays a major role in the global ocean carbon pump, through the sequestering of anthropogenic CO2 and export of organic carbon to the deep ocean. To evaluate the global impact of the marine carbon cycle, quantification of micro-phytoplankton primary production is paramount. In this paper we use both in situ data and a satellite model to estimate the contribution of micro-phytoplankton to total primary production (PP) in the Atlantic Ocean. From 1995 to 2013, 940 measurements of primary production were made at 258 sites on 23 Atlantic Meridional Transect Cruises from the United Kingdom to the South African or Patagonian Shelf. Micro-phytoplankton primary production was highest in the South Subtropical Convergence (SSTC ∼ 409 ± 720 mg C m−2 d−1), where it contributed between 38 % of the total PP, and was lowest in the North Atlantic Gyre province (NATL ∼ 37 ± 27 mg C m−2 d−1), where it represented 18 % of the total PP. Size-fractionated photosynthesis-irradiance (PE) parameters measured on AMT22 and 23 showed that micro-phytoplankton had the highest maximum photosynthetic rate (PmB) (∼5 mg C (mg Chl a)−1 h−1) followed by nano- (∼4 mg C (mg Chl a)−1 h−1) and pico- (∼2 mg C (mg Chl a)−1 h−1). The highest PmB was recorded in the NATL and lowest in the North Atlantic Drift Region (NADR) and South Atlantic Gyre (SATL). The PE parameters were used to parameterise a remote sensing model of size-fractionated PP, which explained 84 % of the micro-phytoplankton in situ PP variability with a regression slope close to 1. The model was applied to the SeaWiFS time series from 1998–2010, which illustrated that micro-phytoplankton PP remained constant in the NADR, NATL, Canary Current Coastal upwelling (CNRY), Eastern Tropical Atlantic (ETRA), Western Tropical Atlantic (WTRA) and SATL, but showed a gradual increase in the Benguela Upwelling zone (BENG) and South Subtropical Convergence (SSTC). The mean annual carbon fixation of micro-phytoplankton was highest in the CNRY (∼140 g C m−2 yr−1), and lowest in the SATL (27 g C m−2 yr−1). A Thorium-234 based export production (ThExP) algorithm was applied to estimates of total PP in each province. There was a strong coupling between micro-phytoplankton PP and ThExP in the NADR and SSTC where between 23 and 39 % of micro-phytoplankton PP contributed to ThExP. The lowest contribution by micro-phytoplankton to ThExP was in the ETRA and WTRA which were 15 and 21 % respectively. The results suggest that micro-phytoplankton PP in the SSTC is the most efficient export system and the ETRA is the least efficient in the Atlantic Ocean.UK Natural Environment Research Council National CapabilityPOGOEU FP7 project GreenSeasNCE

Drivers of spectral optical scattering by particles in the upper 500 m of the Atlantic Ocean

Optical models have been proposed to relate spectral variations in the beam attenuation (cp) and optical backscattering (bbp) coefficients to marine particle size distributions (PSDs). However, due to limited PSD data, particularly in the open ocean, optically derived PSDs suffer from large uncertainties and we have a poor empirical understanding of the drivers of spectral cp and bbp coefficients. Here we evaluated PSD optical proxies and investigated their drivers by analyzing an unprecedented dataset of co-located PSDs, phytoplankton abundances and optical measurements collected across the upper 500 m of the Atlantic Ocean. The spectral slope of cp was correlated (r>0.59) with the slope of the PSD only for particles with diameters >1 µm and also with eukaryotic phytoplankton concentrations. No significant relationships between PSDs and the spectral slope of bbp were observed. In the upper 200 m, the bbp spectral slope was correlated to the light absorption by particles (ap; r<-0.54) and to the ratio of cyanobacteria to eukaryotic phytoplankton. This latter correlation was likely the consequence of the strong relationship we observed between ap and the concentration of eukaryotic phytoplankton (r=0.83)

Ocean-colour products for climate-change studies: What are their ideal characteristics?

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordOcean-colour radiometry is recognised as an Essential Climate Variable (ECV) according to the Global Climate Observing System (GCOS), because of its capability to observe significant properties of the marine ecosystem at synoptic to global scales. Yet the value of ocean colour for climate-change studies depends to a large extent not only on the decidedly important quality of the data per se, but also on the qualities of the algorithms used to convert the multi-spectral radiance values detected by the ocean-colour satellite into relevant ecological, bio-optical and biogeochemical variables or properties of the ocean. The algorithms selected from the pool of available algorithms have to be fit for purpose: detection of marine ecosystem responses to climate change. Marine ecosystems might respond in a variety of ways to changing climate, including perturbations to regional distributions in the quantity and in the type of phytoplankton present, their locations and in their seasonal dynamics. The ideal algorithms would be capable of distinguishing between abundance and type, and would not mistake one for the other. They would be robust to changes in climate, and would not rely on assumptions that might be valid only under current climatic conditions. Based on such considerations, we identify a series of ideal qualitative traits that algorithms for climate-change studies would possess. Necessarily, such traits would have to complement the quantitative requirements for precision, accuracy and stability in the data over long time scales. We examine the extent to which available algorithms meet the criteria, according to the work carried out in the Ocean Colour Climate Change Initiative, and where improvements are still needed.National Centre for Earth Observation of the Natural Environment Research Council of the U

Climate variability shifts the vertical structure of phytoplankton in the Sargasso Sea

This is the final version. Available from Nature Research via the DOI in this record. Data availability. BATS data used in this study were acquired freely from the BATS data server (http://bats.bios.edu/bats-data/) and the BATS project page at the Biological-Chemical Oceanography Data Management Office (https://www.bco-dmo.org/project/2124). Atlantic Meridional Oscillation index data used in this study were downloaded from NCAR’s climate data guide (https://climatedataguide.ucar.edu/climate-data/atlantic-multi-decadal-oscillation-amo). Satellite MODIS 8-day composite PAR data were downloaded from the NASA ocean colour page (https://oceancolor.gsfc.nasa.gov/resources/atbd/par/). Two-community model data output of modelled Chl-a and POC vertical profiles are available via Zenodo at https://doi.org/10.5281/zenodo.13150754 (ref. 53).Marine phytoplankton are essential to ocean biogeochemical cycles. However, our understanding of changes in phytoplankton rely largely on satellite data, which can only assess changes in surface phytoplankton. How climate variability is impacting their vertical structure remains unclear. Here we use 33 years’ worth of data from the Sargasso Sea to show distinct seasonal and long-term phytoplankton climate responses in the surface mixed layer compared with the subsurface. Seasonally, the surface community alters their carbon-to-chlorophyll ratio without changing their carbon biomass, whereas the chlorophyll and carbon of the subsurface community covaries with no change in their carbon-to-chlorophyll ratio. Over the last decade, the subsurface phytoplankton biomass has increased in response to warming, whereas the surface phytoplankton have altered their carbon-to-chlorophyll ratio with minimal change in their carbon biomass. Given that satellites can only view the surface ocean, sustained subsurface monitoring is required to provide a full understanding of how phytoplankton are responding to climate change.UK Research and Innovatio

Substantial energy input to the mesopelagic ecosystem from the seasonal mixed-layer pump

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record.The ocean region known as the mesopelagic zone, which is at depths of about 100-1,000 m, harbours one of the largest ecosystems and fish stocks on the planet. Life in this region is believed to rely on particulate organic carbon supplied by the biological carbon pump. Yet this supply appears insufficient to meet mesopelagic metabolic demands. An additional organic carbon source to the mesopelagic zone could be provided by the seasonal entrainment of surface waters in deeper layers, a process known as the mixed-layer pump. Little is known about the magnitude and spatial distribution of this process globally or its potential to transport carbon to the mesopelagic zone. Here we combine mixed-layer depth data from Argo floats with satellite estimates of particulate organic carbon concentrations to show that the mixed-layer pump supplies an important seasonal flux of organic carbon to the mesopelagic zone. We estimate that this process is responsible for a global flux of 0.1-0.5 Pg C yr-1. In high-latitude regions where the mixed layer is usually deep, this flux amounts on average to 23% of the carbon supplied by fast sinking particles, but it can be greater than 100%. We conclude that the seasonal mixed-layer pump is an important source of organic carbon for the mesopelagic zone.UK National Centre for Earth Observation, UK NERCMarie Curie(UK) NERC National Capability in Sustained Observations and Marine ModellingEuropean Research CouncilH2020 ATLANTOS EU projec