Data include all physicochemical and phytoplankton data collected during the STRATIPHYT I and II cruises in the Northeast Atlantic Ocean. Cruises took place during the summer of 2009 and spring of 2011 aboard the R/V Pelagia. Water samples were collected in the top 250 m from at least 10 separate depths using 24 plastic samplers (General Oceanics type Go-Flow, 10 liter) during STRATIPHYT I and Teflon samplers (NIOZ design Pristine Bottles, 27 L) during STRATIPHYT II. Samplers were mounted on an ultra-clean (trace-metal free) system consisting of a fully titanium sampler frame equipped with CTD (Seabird 91; standard conductivity, temperature, and pressure sensors) and auxiliary sensors for chlorophyll autofluorescence (Chelsea Aquatracka Mk III), light transmission (Wet-Labs C-star) and photosynthetic active radiation (PAR; Satlantic). Data from the chlorophyll autofluorescence sensor were calibrated against HPLC data to determine total chlorophyll a (Chl a). Samples were taken inside a 6 m Clean Container from each depth for inorganic nutrients, flow cytometry, and phytoplankton pigments. Temperature eddy diffusivity (KT) data, referred to here as the vertical mixing coefficient, were derived from temperature and conductivity microstructure profiles measured using the commercial microstructure profiler Self Contained Autonomous Microprofiler (SCAMP). Phytoplankton consisting of photoautotrophic prokaryotic cyanobacteria and eukaryotic algae

Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Related Publications
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

Sampling location: Northeast Atlantic in the area located between 29 degN and 63degN (~15 degW), which spans from the Canary Islands to Iceland. Water samples were collected in the top 250 m from at least 10 separate depths. During each cruise, 32 stations (separated by approximately 100 km) were sampled.

Water samples were collected in the top 250 m from at least 10 separate depths using 24 plastic samplers (General Oceanics type Go-Flow, 10 liter) during STRATIPHYT I and Teflon samplers (NIOZ design Pristine Bottles, 27 L) during STRATIPHYT II. Samplers were mounted on an ultra-clean (trace-metal free) system consisting of a fully titanium sampler frame equipped with CTD (Seabird 91; standard conductivity, temperature, and pressure sensors) and auxiliary sensors for chlorophyll autofluorescence (Chelsea Aquatracka Mk III), light transmission (Wet-Labs C-star) and photosynthetic active radiation (PAR; Satlantic). Data from the chlorophyll autofluorescence sensor were calibrated against HPLC data according to van de Poll et al. (2013) to determine total chlorophyll a (Chl a) for this study. Samples were taken inside a 6 m Clean Container from each depth for inorganic nutrients (5 mL), flow cytometry (10 mL), and phytoplankton pigments (10 L).

Temperature eddy diffusivity (KT) data, referred to here as the vertical mixing coefficient, were derived from temperature and conductivity microstructure profiles measured using the commercial microstructure profiler Self Contained Autonomous Microprofiler (SCAMP) . A detailed description of SCAMP methodology and data for both STRATIPHYT cruises have been described by Jurado et al. (2012a,b). The SCAMP was deployed at fewer stations (i.e., 17 and 14 in spring and summer, respectively) and to lower depths (up to 100 m) than the remainder of the data (23 stations and up to 250 m depth) in this study. To correct for this deficiency, data were interpolated using the spatial kriging function “krig” executed in R using the “fields” package (Furrer et al. 2012). Interpolated KT values were bounded below by the minimum value measured for each of the two cruise datasets; the upper values were left unbounded. This resulted in estimated KT values which preserved the qualitative pattern and range of values previously reported (Jurado et al. 2012a,b), i.e., continuous stratification during the summer STRATIPHYT I cruise and two distinct zones of mixing during the spring STRATIPHYT II cruise; stratification in the south and deep strong mixing in the north. SCAMP data were also used to quantify the strength of background  stratification according to the square of the Brunt–Vaisala frequency. N^2 values were depth averaged over the top 100 m of the water column and classified based on the following criteria: N^2<2 x10^-5 rad^2 s^-2 for nonstratified, 2 x 10^-5<N^2<5 x 10-5 rad^2 s^-2 for weakly stratified and N^2>5 x 10^-5 rad^2 s^-2 for strongly stratified. In addition, the depth of the mixed layer (Zm), was determined as the depth at which the temperature difference with respect to the surface was 0.5degC.

Discrete water samples for dissolved inorganic phosphate (PO4), ammonium (NH4), nitrate (NO3), and nitrite (NO2) were gently filtered through 0.2 lm pore size polysulfone Acrodisk filters (32 mm, Pall), after which samples were stored at -20degC until analysis. Dissolved inorganic nutrients were analyzed onboard using a Bran+Luebbe Quaatro Auto- Analyzer for dissolved orthophosphate (Murphy and Riley 1962), inorganic nitrogen (nitrate+nitrite: NOx) (Grasshoff 1983) and ammonium (Koroleff 1969; Helder and De Vries 1979). Detection limits ranged between the two cruises from 0.06-0.10 microM for NOx, 0.010-0.028 microM for PO4 and 0.05-0.09 microM for NH4.

Phytoplankton consisting of photoautotrophic prokaryotic cyanobacteria and eukaryotic algae<20 microns were enumerated on fresh samples using a Becton-Dickinson FACSCalibur flow cytometer (FCM) equipped with an air-cooled Argon laser with an excitation wavelength of 488 nm (15 mW). Samples were measured for 10 min using a high flow rate with the discriminator set on red chlorophyll autofluorescence. Phytoplankton populations were distinguished using bivariate scatter plots of autofluorescent properties (orange autofluorescence from phycoerythrin for the cyanobacteria Synechococcus spp. and red autofluorescence from Chl a for photoautotrophs) against side scatter. The obtained list-mode files were analyzed using the freeware CYTOWIN (Vaulot 1989). Regularly throughout the cruise transect, size-fractionation was performed to provide average cell size for the different phytoplankton subpopulations. Specifically, a whole water sample (10 mL) was size-fractionated by sequential gravity filtration through 8, 5 , 3, 2, 1, 0.8, and 0.4 micron pore-size polycarbonate filters. Each fraction was then analyzed using FCM as described above. The equivalent spherical diameter for each population was determined as the size displayed by the median (50%) number of cells retained for that cluster. In total nine different phytoplankton populations were distinguished, consisting of six eukaryotic and three cyanobacterial populations, i.e., Synechococcus spp. (average size range between the two cruises of 0.9-1.0 micron), Prochlorococcus high light population (HL; 0.6 micron) and Prochlorococcus low light population (LL; 0.7-0.8 micron). The photosynthetic eukaryotic populations consisted of two pico-sized groups, i.e., Pico I (1.0-1.4 micron) and Pico II (1.5-2.0 micron), and four nano-sized groups, i.e., Nano I (3-4 micron), Nano II (6-8 micron), Nano III (8-9 micron), and Nano IV (9 micron). To estimate the contribution of the different phytoplankton groups to carbon biomass, carbon-conversion factors were applied to FCM cell counts. Specifically, cell counts were transformed assuming spherical diameters equivalent to the average cell size determined from size fractionation and applying conversion factors of 237 fg C per cubic micrometer (Worden et al. 2004) and 196.5 fg C per cubic micrometer  for pico- and nano-sized plankton (Garrison et al. 2000), respectively.

Phytoplankton taxonomic composition was determined by pigment analysis of 10 L GF/F filtered samples (47 mm, Whatman; flash frozen and stored at 2808C until analysis) using HPLC as described by Hooker et al. (2009). In short, filters were freeze-dried (48 h) and pigments extracted using 5 mL 90% acetone (v/v, 48 h, 48C, darkness) and separated using a HPLC (Waters 2695 separation module, 996 photodiode array detector) equipped with a Zorbax Eclipse  XDB-C8 3.5 micrometer column (Agilent Technologies). Peak identification was based on retention time and diode array spectroscopy. Pigments standards (DHI LAB products) were used for quantification of chlorophyll a1, chlorophyll a2, chlorophyll b, chlorophyll c2, chlorophyll c3, peridinin, 19-butanoyloxyfucoxanthin, 19-hexanoyloxyfucoxanthin, fucoxanthin, neoxanthin, prasinoxanthin, alloxanthin, and zeaxanthin. The sum of Chl a and divinyl Chl a was used as indicator for algal biomass as these pigments are universal in algae and Prochlorococcus. Specific marker pigments were used to reveal the presence of taxonomically distinct pigment signatures using CHEMTAX (version 195; Mackey et al. 1996) software, thereby estimating the concentration of each taxonomic group relative to Chl a. CHEMTAX was run separately for oligotrophic and non-oligotrophic stations and for spring and summer samples. Oligotrophic areas defined by nutrient (i.e., NO30.13 lM and PO40.03 lM; van de Poll et al. 2013) or by Chl a concentrations (< 0.07 mg Chl m-3), delineating regions south of 40degN and 45degN as oligotrophic for the spring and summer, respectively. CHEMTAX was run with 500 iterations, with all elements varied (100% for Chl a and divinyl Chl a and 500% for the other pigments). Initial pigment ratios in the iterations were based on van de Poll et al. (2013), where high-light initial pigment ratios were implemented for surface samples (0-50 m) of oligotrophic stations and low-light initial pigment ratios for subsurface samples (> 50 m) of oligotrophic and all nonoligotrophic samples. To compare to taxonomic composition data provided by CHEMTAX, the percent contribution of different FCM distinguished groups to total carbon biomass (< 20 micron) was also determined. Likewise, Chl a and CHEMTAX taxonomic composition were used to determine the group-specific Chl a concentrations.

A detailed description of SCAMP methodology and data for both STRATIPHYT cruises have been described by Jurado et al. (2012a,b). The SCAMP was deployed at fewer stations (i.e., 17 and 14 in spring and summer, respectively) and to lower depths (up to 100 m) than the remainder of the data (23 stations and up to 250 m depth) in this study. To correct for this deficiency, data were interpolated using the spatial kriging function “krig” executed in R using the “fields” package (Furrer et al. 2012). Interpolated KT values were bounded below by the minimum value measured for each of the two cruise datasets; the upper values were left unbounded. This resulted in estimated KT values which preserved the qualitative pattern and range of values previously reported (Jurado et al. 2012a,b), i.e., continuous stratification during the summer STRATIPHYT I cruise and two distinct zones of mixing during the spring STRATIPHYT II cruise; stratification in the south and deep strong mixing in the north. 

Flow cytometry list-mode files were analyzed using the freeware CYTOWIN (Vaulot 1989).

Taxonomically distinct pigment signatures identified using CHEMTAX (version 195; Mackey et al. 1996) software

Website: https://www.nwo.nl/en/projects/83908420

NWO Award Abstract:

Global warming will change physical, chemical and biological processes in the oceans. Ocean-climate models predict that warming of the surface layer may strengthen vertical stratification, starting earlier in spring and lasting longer in autumn. This results in suppressed upward mixing of nutrients from the deep ocean. Changes in stratification will have major effects on the growth and species composition of the phytoplankton. This will subsequently impact grazing, viral lysis and sedimentation rates, with cascading effects on ecosystem functioning and biogeochemical fluxes. Little is known, however, on the exact implications of global warming for these fundamental processes. We propose to investigate how changes in vertical stratification affect phytoplankton communities (growth, losses and composition) along a North-South gradient in the Atlantic Ocean. Our study will be based on oceanographic cruises from Iceland to the Canary Islands and detailed laboratory experiments with representative phytoplankton species, both integrated in advanced models of hydrodynamics and plankton dynamics and productivity. We have chosen for the Northeast Atlantic Ocean, because it is a key area in global ocean circulation and a large sink for atmospheric CO2, and a major determinant of the climate in Western Europe. Furthermore, the Atlantic Ocean offers a gradient from weak seasonal stratification in the North to strong permanent stratification in the (sub)tropics. This gradient offers ideal opportunities for the comparative study of different stratification regimes. Our integrated approach of physical, chemical, and biological processes, by a new multidisciplinary research team, will enable a better understanding of the implications of global warming for plankton growth in the Northeast Atlantic Ocean.