Hydrographic observations and seawater sampling were carried out during three research cruises performed in the Red Sea between February and April 2015 aboard the R/V Thuwal: in the Southern Red Sea (SRS) (8–21 February 2015); in the Central Red Sea (CRS) (29 March-3 April 2015) and in the Northern Red Sea (NRS) (17–28 April 2015). A total of 17 stations were sampled: four in the SRS, six in the CRS and seven in the NRS (Figure 1). Temperature and salinity profiles were obtained using a SBE 9 (Sea-Bird Electronics) Conductivity-Temperature-Depth (CTD) probe. Discrete seawater samples for determining phytoplankton pigments were collected using a rosette system equipped with 10 L Niskin bottles at 8–12 depths within the upper 200 m of the water column. The euphotic layer depth, Z_eu, defined as the depth where Photosynthetically Active Radiation (PAR) is reduced to 1% of its surface value was computed using in situ Chlorophyll a concentration profiles according to the model developed by Morel and Maritorena (2001). To provide a general overview of the spatial distribution of phytoplankton community and size structure along the central axis of the Red Sea, measurements collected during the three different research campaigns were combined.

We followed the HPLC analytical procedure proposed by Ras et al. (2008). Briefly, photosynthetic phytoplankton pigments were obtained at different depths in the upper 200 m of the water column. Seawater samples of 2.8 L were collected from Niskin bottles and filtered through 25 mm diameter Whatman GF/F filters (0.7 μm porosity). Filters were stored in liquid nitrogen during the cruise, then at −80°C in the laboratory until analysis. Samples were extracted in 3 mL 100% methanol, disrupted with glass pearls on a cooled vibratory homogenizer, centrifuged, and filtered (Teflon syringe filter of 0.2 μm) 2 h later. Within 24 h, the extracts were analyzed by HPLC using a complete 1,260 Agilent Technologies system. This method has proven to be satisfactory in terms of resolution, sensitivity, accuracy, and precision (Hooker et al., 2005). The limit of detection (three times signal:noise ratio) for Chlorophyll a is of 0.0005 mg m⁻³ and with an injection precision of 0.6%. The HPLC method enables the identification and quantification of pigments that were used in this study (see Table 1 for details and pigment abbreviations).

Uncertainties of the determination of pigment concentrations were calculated using the principles of uncertainty propagation and were ~5.3% for the primary pigments and 5.9% on average for the secondary pigments.

It is now well established that accessory pigments are typical of phytoplankton groups and may be used as biomarkers to estimate the composition of phytoplankton communities. This approach, however, has rarely been compared with others techniques such as flow cytometry, microscopy, and molecular analysis (Claustre, 1994; Vidussi et al., 2001; Uitz et al., 2006). We utilized seven major diagnostic pigments to estimate the biomass associated with three pigment-derived size classes, i.e., microphytoplankton, nanophytoplankton, and picophytoplankton. These seven pigments are fucoxanthin, peridinin, 19′ hexanoyloxyfucoxanthin, 19′-butanoyloxyfucoxanthin, alloxanthin, Total Chlorophyll b (TChlb), and zeaxanthin (abbreviations in Table 1).

The basic assumptions are as follows: (1) fucoxanthin and peridinin are diagnostic pigments for diatoms and dinoflagellates, which dominate the microphytoplankton (>20 μm); (2) nanophytoplankton (2–20 μm) is characterized by alloxanthin, 19′ hexanoyloxyfucoxanthin and 19′-butanoyloxyfucoxanthin, that are abundant in cryptophytes, chromophytes, and nanoflagellates and (3) picophytoplankton (<2 μm) is assessed from zeaxanthin and TChlb, which are abundant in green flagellates, prochlorophytes, and cyanobacteria.

The relative proportions of picophytoplankton (size <2 μm), nanophytoplankton (2–20 μm), and microphytoplankton (20–200 μm) are derived from the concentrations of phytoplankton diagnostic pigments using the equations described in Uitz et al. (2006):

where DP is the sum of the seven diagnostic pigment concentrations:

It is also possible to derive the Total Chlorophyll a concentration associated with each of the three phytoplankton classes ([TChla]-micro, [TChla]-nano and [TChla]-pico) according to the following equations:

There are certainly many exceptions to these pigment/size relationships. Previous studies (Claustre, 1994; Vidussi et al., 2001; Uitz et al., 2006, 2008) mentioned that these assumptions may sometimes lead to errors. For example, some diagnostic pigments are shared by several phytoplankton groups and some groups may cover a broad size range, such as zeaxanthin containing Trichodesmium (microphytoplankton), or 19′BF and 19′HF, pigments specific of prymnesiophytes, present in some picoplankton prymnesiophytes. Additionally, some phytoplankton groups may spread over a wide size range (Moon-van der Staay et al., 2000; Cuvelier et al., 2010; Jardillier et al., 2010; Treusch et al., 2012). Nevertheless, this approach has proven valuable to provide the dominant trends of the phytoplankton community and size structure at the regional and seasonal scales (Uitz et al., 2006, 2015; Ras et al., 2008).

The class-specific primary production model rates were computed according to the bio-optical primary production model proposed by Morel and Andre (1991) in combination with the phytoplankton class-specific photophysiological properties proposed by Uitz et al. (2008). The model requires the following inputs: (1) surface PAR estimated from ocean color remote sensing (https://oceancolor.gsfc.nasa.gov/); (2) vertical profiles of [TChla]-micro, [TChla]-nano and [TChla]-pico and (3) the class-specific photophysiological properties proposed by Uitz et al. (2008).

A model describing the dependence of phytoplankton photophysiological properties (i.e., the chlorophyll-specific absorption coefficient, and the dependent quantum yield of carbon fixation, the photosaturation parameter and the slope of the photosynthesis-irradiance curve) on the phytoplankton community and size structure and water column depth was provided by Uitz et al. (2008) allowing estimation of vertical profiles of photophysiological properties for each pigment-based phytoplankton size class. The model was established by analyzing a large database including measurements of HPLC-determined pigments, phytoplankton absorption spectra, and photosynthesis-irradiance curve parameters collected in various temperate, subtropical, and tropical open ocean regions.

In this study, the photophysiological parameters required for running the primary production model of Morel and Andre, 1991) were computed from our in situ pigment-based phytoplankton size class profiles using the model established by Uitz et al. (2008). Computations applied to the vertical profiles of phytoplankton class-specific enable estimation of the primary production rates associated with micro-, nano-, and picophytoplankton over the productive layer. The depth of this layer is defined as 1.5 times the depth of Z_eu. The total primary production, attributed to the whole algal biomass, is defined as the sum of the contributions of each class.

Essential information about the computation of the class-specific primary production rates are provided in Morel and Andre (1991) and Uitz et al. (2006, 2008).

In this section, datasets of hydrographic measurements (temperature, salinity, and density) and phytoplankton pigments acquired in the SRS from 8 to 21 February 2015, in the CRS from 29 March to 03 April 2015 and in the NRS from 17 to 28 April 2015 have been combined to provide a basin scale perspective of the Red Sea and facilitate interpretation of the data in Figures 2–7. While the data set is not synoptic, it provides a general perspective of the phytoplankton community distributions along the physico-chemical latitudinal gradients observed in the Red Sea.

Latitudinal variations in temperature, salinity and density are shown in Figure 2. As observed in previous studies, the Red Sea is characterized by a strong latitudinal gradient in salinity, temperature and density (Sofianos and Johns, 2007; Yao et al., 2014a,b). Low salinity water (<37) enters the Red Sea from the Gulf of Aden, and surface salinity then generally increases from south to north through evaporation (Figure 2b). Temperature generally decreases from south to north (Figure 2a). The northern Red Sea, is characterized by the highest upper layer salinities, with surface salinities in excess of 40.3 observed near 27.25°N (Figure 2b). These salty waters results from evaporation with almost no precipitation input. The doming of temperature and salinity isolines at 27.3° N is indicative of an upwelling of deeper waters, which is typical of a cyclonic eddy (cold core eddy; Figures 2a,b) and confirmed by density fields (Figure 2c). The surface water in the eddy center was ~1.5°C cooler, 0.3 saltier, and 0.4 kg m⁻³ denser than adjacent surface waters outside the eddy. Modeling results indicate that the northern Red Sea is often characterized by a cyclonic circulation (Yao et al., 2014a,b). In the CRS, the isotherm and isohaline surfaces generally tilted upward from south to north resulting in cooler, saltier and denser water present nearer the surface toward the north (Figures 2a–c). In the SRS, the upper layer was characterized by relatively cold (<26°C), less saline (<38.25), and less dense (<27 kg m⁻³) water advecting from the south (16.75°–17.4° N) (Figures 2a–c).

Total Chlorophyll a (TChl a) concentrations in the Red Sea ranged between 0.04 and 0.60 mg m⁻³ in the upper 0–20 m, while at the deep chlorophyll maximum (DCM) the concentrations varied between 0.28 and 0.78 mg m⁻³ (Figure 3). Within our sampling, surface TChla concentrations were lowest in the northern Red Sea (0.04 mg m⁻³), while the highest surface values were found at both extremities of the Red Sea, up to 0.60 mg m⁻³ in the south and 0.43 mg m⁻³ in the north. The highest TChl a concentrations of the northern region were observed within a feature with steeply shallowing isopycnals, characteristic of a cyclonic eddy, centered at 27.3° N. Within the feature, the mixed layer depth (MLD) increased to about ~80 m, computed using a density gradient criterion of 0.125 kg m⁻³ (Figure 3). The Red Sea was characterized by increasing oligotrophic conditions with a deepening of the DCM position and a decrease in TChla concentrations from south to north (16.75°–27°N). These results are in agreement with the expected Chlorophyll a gradients along the Red Sea (Racault et al., 201), where Chlorophyll a concentrations tend to be higher in the south than in the north. The Chlorophyll a maximum reaches its deepest position (around 80 m) in the northern Red Sea and its shallowest position (around 20 m) in the Southern Red Sea. Fluctuations in the DCM depth occurred between 27° and 28°N where the DCM was shallower (~50 m at 27.5°N) at stations associated with the eddy and when the MLD reached its deepest position (at 27.75°N) around 115 m (Figure 3). The position of the DCM is mostly close to Z_eu, suggesting that the DCM is light-driven.

The distribution of some accessory pigments did not always exhibit the same pattern as TChla distribution. The respective spatial distribution of some of the pigments appeared to relate with water mass variability. Fuco, specifically, appeared to be associated with the northern cyclonic eddy.

The distributions of TChlb and 19′HF were generally similar to that of TChla. The deep maxima of both TChlb and 19′HF deepened from the SRS to the CRS, and shallowed in the vicinity of the eddy in the NRS (Figures 4A,D). The 19′HF concentrations below the DCM (110–160 m depth) in the CRS and NRS were two to three times higher than surface concentrations (Figure 4D). In previous studies, high concentrations of 19′HF below the DCM have been reported in the Atlantic Ocean (Claustre and Marty, 1995) and the Pacific Ocean (Ras et al., 2008). DVChla was mainly observed in the CRS and in the NRS except in the eddy area (Figure 4B). The DVChla trend is characterized by a progressive increase in concentrations from the surface to the depth of the DCM (Figure 4B). Zea was detected in the surface layer along the entire transect and generally decreased depth below the mixed layer (Figure 4C). High concentrations of Fuco were observed within the cyclonic eddy in the NRS (0.160 ± 0.028 mg m⁻³) and in lower concentrations (>0.051 mg m⁻³) within the DCM in the SRS (Figure 4E). Elsewhere, Fuco concentrations were very low (0.0178 ± 0.004 mg m⁻³).

Low amounts of minor accessory pigments (0.0005–0.059 mg m⁻³) have also been identified and are of interest as biomarkers for particular phytoplankton groups. Briefly, Pras, Viola, Allo, Peri, and Neo, were detected at DCM throughout the study area: highest concentrations were found in the SRS and in the eddy (Figure 5). In the 0–35 m layer, Pras, Allo, and Neo were hardly detected in the SRS and were below detection in this surface layer in the other regions of the basin (Figures 5A–C). Only Viola and Peri persisted throughout the basin from surface to 100 m depth (Figures 5D,E). The highest concentrations of Viola and Peri occurred the most southern stations within the DCM in the low salinity Gulf of Aden inflow (Figures 5D,E). The vertical distribution of most of the pigments were affected by the cyclonic eddy.

Phaeopigments (Phaeophorbide a + Phaeophytin a) revealed a spatial distribution similar to the distribution of Fuco (Figures 4E, 5F, respectively). Phaeopigment concentrations were very low within the CRS and more abundant in the SRS (~30–40 m depth) and in the eddy in the NRS (20–120 m depth).

For a quantitative comparison of phytoplankton biomass distribution in the Red Sea, concentrations of TChla, [TChla]-pico, [TChla]-nano, and [TChla]-micro were integrated over the productive layer (1.5 Z_eu) (Figure 8A). The average integrated TChla biomass for each subregion was 26.25 ± 2.75, 27.36 ± 5.46, and 29.74 ± 6.93 mg m⁻² for the SRS, CRS, and NRS, respectively. Picophytoplankton communities were most abundant in the CRS (15.55 ± 3.59 mg m⁻²). The lowest integrated [TChla]-pico (5.69 ± 2.55 mg m⁻²) occurred within the eddy. The distribution of the integrated [TChla]-nano supports the substantial contribution prymnesiophytes (nanophytoplankton group) in the Red Sea and suggests that prymnesiophytes are likely a ubiquitous group. The highest integrated [TChla]-nano was observed at the northern edge of the transect with a value of 22.72 mg m⁻². Along the basin, integrated [TChla]-micro values were low in the CRS and NRS except within the cyclonic eddy (3.5 ± 1.8 mg m⁻²) and tended to increase in the SRS where concentrations ranging between 5.6 and 6.91 mg m⁻² were observed. The highest integrated [TChla]-micro concentration (14.6 ± 2.94 mg m⁻²) was observed in the eddy.

The distribution of calculated primary production was marked by high values at the southern and northern edges of the transect (500 and 650 mgC m⁻² d⁻¹, respectively) and also within the cyclonic eddy (480 ± 100 mgC m⁻² d⁻¹) where environmental conditions enhance biological responses (Figure 8B). In the SRS, primary production ranged between 360 and 500 mgC m⁻² d⁻¹, in the CRS between 300 and 420 mgC m⁻² d⁻¹ and in the NRS, between 300 and 650 mgC m⁻² d⁻¹ (Figure 8B). The rates of primary production in the Red sea are in the range of rates reported for other oligotrophic regions of the global ocean (220–600 mgC m⁻² d⁻¹) (Koblentz-Mishke et al., 1970; Knauer et al., 1990; Lohrenz et al., 1992a,b; Karl et al., 1996; Uitz et al., 2010). As expected, the contribution of picophytoplankton was highest in the CRS (49.2%). The minimum contribution of picophytoplankton occurred within the northern eddy. Nanophytoplankton accounted for 30–60% of primary production. Microphytoplankton showed the greatest variability (11–54%) in their relative contribution to the integrated productivity. Contributions of diatoms to primary production were similar or slightly higher than their contribution to phytoplankton biomass in all regions, ranging from 25–35, 12–20, 14–20, and 35–55% in the SRS, CRS, NRS, and within the eddy area, respectively. These results agree with those reported in numerous studies (Nelson and Brzezinski, 1997; Brzezinski et al., 2011; Krause et al., 2011). Each of these studies demonstrates similar disproportionate importance of diatoms in primary production relative to their biomass, suggesting that diatoms play quantitatively significant roles in biogeochemical cycles. Numerous studies have also shown that mesoscale features can be disproportionately important for primary production, nutrient cycling, and trophic ecology (Nelson and Smith, 1986; Yoder et al., 1994; Powell and Ohman, 2015). Within these features, diatoms biomass may be stimulated and increase primary production in response to their high growth and grazing rates (in contrast to areas beyond the eddy; Benitez-Nelson et al., 2007; McGillicuddy et al., 2007; Krause et al., 2009a,b, 2010; Taylor et al., 2012). Microphytoplankton are known to develop in a dynamic environment where nutrients and light are available (Malone, 1981; Goldman, 1993; as is the case in the SRS), in upwelling systems (e.g., cyclonic eddy) and where vertical mixing episodically delivers new nutrients into the euphotic zone. Because of their response to available nutrients microphytoplankton generally increase the total primary production of an area.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.