Nutrient ratios influence variability in Pseudo-nitzschia species diversity and particulate domoic acid production in the Bay of Seine (France)

Harmful Algae 68 (2017) 192–205

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Nutrient ratios influence variability in Pseudo-nitzschia species diversity and particulate domoic acid production in the Bay of Seine (France) Maxine Thorela,b,1, Pascal Claquina,b , Mathilde Schapirad,2 , Romain Le Gendred,3 , Philippe Rioud, Didier Gouxc, Bertrand Le Roya,b , Virginie Raimbaulta,b,4 , Anne-Flore Deton-Cabanillasa,b,5 , Pauline Bazina,b , Valérie Kientz-Boucharte, Juliette Fauchota,b,* a

Normandie Univ, UNICAEN, CNRS, BOREA, 14000 Caen, France UMR BOREA, CNRS-7208, IRD-207, MNHN, UPMC, UCBN, 14032 Caen, France CMAbio-SF 4206 ICORE UNICAEN, 14032 Caen, France d Ifremer, LER/N, 14520 Port en Bessin, France e LABEO Frank Duncombe, Saint-Contest, 14053 Caen Cedex, France b c

A R T I C L E I N F O

Article history: Received 10 January 2017 Received in revised form 10 July 2017 Accepted 17 July 2017 Available online xxx Keywords: Pseudo-nitzschia Species diversity Domoic acid English channel Bloom dynamics Nutrient ratios

A B S T R A C T

The population dynamics of different Pseudo-nitzschia species, along with particulate domoic acid (pDA) concentrations, were studied from May 2012 to December 2013 in the Bay of Seine (English Channel, Normandy). While Pseudo-nitzschia spp. blooms occurred during the two years of study, Pseudo-nitzschia species diversity and particulate domoic acid concentrations varied greatly. In 2012, three different species were identified during the spring bloom (P. australis, P. pungens and P. fraudulenta) with high pDA concentrations (
1400 ng l1) resulting in shellfish harvesting closures. In contrast, the 2013 spring was characterised by a P. delicatissima bloom without any toxic event. Above all, the results show that high pDA concentrations coincided with the presence of P. australis and with potential silicate limitation (Si: N < 1), while nitrate concentrations were still replete. The contrasting environmental conditions between 2012 and 2013 highlight different environmental controls that might favour the development of either P. delicatissima or P. australis. This study points to the key role of Pseudo-nitzschia diversity and cellular toxicity in the control of particulate domoic acid variations and highlights the fact that diversity and toxicity are influenced by nutrients, especially nutrient ratios. © 2017 Elsevier B.V. All rights reserved.

1. Introduction

* Corresponding author at: UMR BOREA, Universite De Caen Normandie, Esplanade de la Paix, CS 14032, 14032 Caen Cedex 5, France. E-mail address: [email protected] (J. Fauchot). 1 Present address: Aix Marseille Univ, Univ Avignon, CNRS, IRD, IMBE, Marseille, France. 2 Present address: Ifremer, LER/MPL/NT, 44301 Nantes CEDEX 03, France. 3 Present address: Ifremer, Unité de Recherche Lagons, Ecosystèmes et Aquaculture Durable, Nouméa, 98848, New-Caledonia, France. 4 Present address: Laboratoire Phycotoxines  IFREMER Nantes, 44311 Nantes, France. 5 Present address: Institut de Biologie de l’Ecole Normale Supérieure, CNRS UMR8197, Paris, France. http://dx.doi.org/10.1016/j.hal.2017.07.005 1568-9883/© 2017 Elsevier B.V. All rights reserved.

Some species of the pennate diatom Pseudo-nitzschia produce a neurotoxin known as domoic acid (DA). DA can bioaccumulate in marine food webs and is responsible for amnesic shellfish poisoning (ASP) events that result in intoxication and mortality of higher trophic level organisms such as birds, marine mammals and humans (Wright et al., 1989; Work et al., 1993; Scholin et al., 2000). Most Pseudo-nitzschia species are cosmopolitan (Hasle, 2002; Lundholm and Moestrup, 2002). Pseudo-nitzschia spp. generally bloom during the spring/summer and autumn periods (Bates et al., 1998; Trainer et al., 2002; Fehling et al., 2006; QuijanoScheggia et al., 2008a; Klein et al., 2010; Mari c et al., 2011; DownesTettmar et al., 2013; Husson et al., 2016). In many coastal ecosystems, they bloom as part of the diatom successions (e.g.

M. Thorel et al. / Harmful Algae 68 (2017) 192–205

Pannard et al., 2008; Quijano-scheggia et al., 2008a; Klein et al., 2010; Macintyre et al., 2011; Napoléon et al., 2013). In situ studies have shown that the water temperature (Fehling et al., 2006; Klein et al., 2010; McCabe et al., 2016; McKibben et al., 2017) plays a key role on their growth dynamics, as well as salinity (Fehling et al., 2006; Macintyre et al., 2011; Liefer et al., 2013; Downes-Tettmar et al., 2013), irradiance (Fehling et al., 2006; Macintyre et al., 2011; Mari c et al., 2011), photoperiod (Fehling et al., 2006; Almandoz et al., 2008; Mari c et al., 2011; Downes-Tettmar et al., 2013), rainfall (Downes-Tettmar et al., 2013) and rapid variation of nutrient inputs (Klein et al., 2010; Schnetzer et al., 2013). All these studies also underline the impact of macronutrient concentrations on Pseudo-nitzschia growth dynamics. In coastal ecosystems, Pseudonitzschia spp. blooms are especially common in nutrient-rich waters. Several Pseudo-nitzschia blooms and ASP events have been reported in coastal upwelling systems (Trainer et al., 2000; Kudela et al., 2010). High abundance levels of Pseudo-nitzschia are also associated with high nutrient inputs (Smith et al., 1990; Parsons et al., 2002; Spatharis et al., 2007; Lundholm et al., 2010). More specifically, Pseudo-nitzschia abundance can be stimulated by high nitrate concentrations (Carter et al., 2005; Paul et al., 2008; Parsons et al., 2013), and a high abundance of Pseudo-nitzschia spp. often coincides with low Si:N and Si:P ratios (Anderson et al., 2010; Liefer et al., 2013; Parsons et al., 2013). The factors that trigger Pseudonitzschia spp. blooms and even more DA production remain however unclear and site-specific (e.g. Husson et al., 2016). The various Pseudo-nitzschia species often present distinct dynamics and specific responses to environmental factors (Kaczmarska et al., 2007; Schnetzer et al., 2007; Almandoz et al., 2008; DownesTettmar et al., 2013). For example, Fehling et al. (2006) showed that species of the P. delicatissima complex (<3 mm width) bloom in spring and coincide with lower salinity and irradiance and colder water temperatures, whereas species of the P. seriata complex (>3 mm width) bloom in summer and are favoured by warm water temperatures, high ammonium levels and a longer photoperiod. On a historical timescale, the study of the sediments in Mariager Fjord (Denmark) highlighted that P. multiseries, the dominant species until the mid-20th century, had been replaced by P. pungens. This pronounced regional shift in species composition

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within the Pseudo-nitzschia genus was most likely caused by an increase in nitrogen concentrations and water temperature that promoted P. pungens abundance (Lundholm et al., 2010). Nutrient concentrations and nutrient ratios play important roles not only in Pseudo-nitzschia population dynamics, but also in DA production. Several laboratory studies highlighted that DA production is stimulated under silicate and phosphate limitation in several Pseudo-nitzschia species, including P. australis (Cusack et al., 2002), P. multistriata (Amato et al., 2005), P. seriata (Fehling et al., 2004b) and P. multiseries (Bates et al., 1991; Pan et al., 1996a,b). By contrast, nitrate limitation suppresses DA production (Bates et al., 1991). In the Bay of Seine (English Channel, Normandy), DA concentrations in shellfish exceeded regulatory limits (DA events) in 2004, 2011, and 2012, resulting in closures of king scallop Pecten maximus harvesting sites (Husson et al., 2016). A high diversity in Pseudonitzschia species is observed in the English Channel (Klein et al., 2010; Downes-Tettmar et al., 2013). Pseudo-nitzschia spp. abundance on the French coast of the eastern English Channel increased between 1992 and 2011 (Hernández-Fariñas et al., 2013). Studies on Pseudo-nitzschia spp. blooms in the English Channel and on the link between Pseudo-nitzschia species diversity and DA events are however scarce. The species specific phenology of these blooms still needs to be investigated. The aim of this work was therefore to study the population dynamics of Pseudo-nitzschia species and particulate DA concentrations in the Bay of Seine as a function of physicochemical and biological factors during two contrasting years, 2012 and 2013, respectively with and without DA events. Determining of the environmental factors that promote DA events is necessary to provide scenarios for ecosystem management. 2. Materials and methods 2.1. Study area and sampling strategy The study site is located in the Bay of Seine, on the French side of the central part of the English Channel (Fig. 1). The Bay of Seine stretches over an area of 4000 km2; it is a macrotidal ecosystem with a maximum tidal range of 7 m. Its freshwater inputs derive

Fig. 1. Map of the Bay of Seine (eastern English Channel). The black dot and the black cross indicate Luc-sur-Mer station and the sampling station, respectively.

pDA Pdel.cplx Pser.cplx

0.51* 0.19 0.01 0.03 0.08 0.01 0.71* 0.65* 0.22 0.62* 0.12 0.05 0.31 0.56* 0.86* 1 Pdel.cplx

PN spp

0.55* 0.1 0.08 0.19 0.12 0.09 0.80* 0.74* 0.12 0.65* 0.14 0.19 0.59* 0.69* 1 Pser.cplx

0.33* 0.15 0.11 0.43* 0.27 0.16 0.42* 0.39* 0.16 0.29 0.03 0.39* 0.67* 0.47* 0.56* 0.17 1 pDA

0.34* 0.05 0.05 0.17 0.07 0.01 0.26 0.23 0.01 0.21 0.24 0.08 0.34* 0.16 0.27 0.36* 0.12 1

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mainly from the discharge of the Seine river, with an annual mean of 510 m3 s1. The site is also under the influence of the Orne river (annual mean discharge of 33 m3 s1). The Seine watershed covers 75,000 km2 with high human population densities and a high proportion of cultivated land that entail strong anthropogenic pressures and nutrient enrichment of the Seine waters, especially in nitrogen and phosphorus (Billen et al., 2007). Samples were collected at one location (49 2101400 W–0 190 4100 E) off the coast of Luc-sur-Mer (Normandy, Fig. 1) weekly from May 2012 to October 2012 and fortnightly from November 2012 to December 2013. Seawater samples were collected at high tide  2 h at 2 m depth (average depth at the sampling station = 12 m) using a 5 l Niskin bottle.

0.50* 0.01 0.22 0.18 0.23 0.01 0.69* 0.62* 0.01 0.55* 0.41* 0.24 0.72* 1 PN spp 0.45* 0.12 0.37* 0.55* 0.49* 0.04 0.55* 0.48* 0.31 0.49* 0.37* 0.53* 1 Chl a

N:P

0.06 0.02 0.40* 0.21 0.29 0.28 0.16 0.04 0.3 0.06 1 Si:N 0.47* 0.01 0.22 0.32 0.3 0.12 0.66* 0.63* 0.09 1 Si:P

Si:N Si:P NH4

0.23 0.22 0.83* 0.68* 0.82* 0.62* 0.43* 0.53* 1 NH4 0.61* 0.22 0.18 0 0.1 0.32* 1 P

0.63* 0.2 0.32* 0.03 0.19 0.45* 0.97* 1 Nox

Si

0.07 0.11 0.76* 0.62* 1 Orne 0.23 0.22 0.36* 1 Seine

0.38* 0.05 0.81* 0.08 0.56* 1 Si

Seine Salinity

0.14 1 Temp

0.23 0.03 1 Salinity

SolarRad

1 Rainfall

Rainfall

Temp

Orne

P

NOx

0.1 0.12 0.58* 0.50* 0.56* 0.34* 0.03 0.04 0.55* 0.09 0.19 1 N:P

Chl a

2.2. Physical and chemical parameters

SolarRad

Table 1 Pearson correlation for physicochemical and biological variables in surface water over the study period (May 2012–December 2013). Values in bold with an asterisk are significant at a = 0.05. Seine: Seine runoff; Orne: Orne runoff; SolarRad: solar radiation; Si: Si(OH)4; P: PO4; NOx: NO3 + NO2; pDA: particulate domoic acid; Chl a: chlorophyll a; P.s cplx: Pseudo-nitzschia seriata complex abundance; P.d cplx: Pseudo-nitzschia delicatissima complex abundance; PN spp: Pseudo-nitzschia spp. abundance.

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Seawater temperature and salinity at 2 m depth were recorded with an SBE 19-plus V2 multi-parameter probe (Seabird). The global solar radiation (J cm2) data were monitored daily on shore at the CREC marine station (49 190 600 N–0 210400 W, Luc sur Mer, Fig. 1) using a Vantage Pro 2–ISS 6150C sensor and were transformed into mmol photons m2 s1 using the method described by Sudhakar et al. (2013). The Seine river runoff data are monitored at the Poses dam station (49 50 4200 N–1290 2100 E) and are freely available on the GIP Seine-Aval website (http://seineaval.crihan.fr/web/). The Orne river runoff data are measured at the Grimbosq dam station (49 30 5600 N–0 260 5600 W) and were provided by the DREAL  Normandy. For dissolved inorganic nutrient analysis (NOx (NO3 + NO2), and Si(OH)4), 100-ml, the samples were pre-filtered NH4+, PO3 4 (48 mm) on board directly from the Niskin bottle. For Si(OH)4, the water samples were subsequently filtered through an 0.45 mm acetate cellulose membrane. The samples were stored at 20  C for  NOx, NH4+ and PO3 4 and at 4 C for Si(OH)4 until analysis. Dissolved nutrients were quantified within one month after field collection with an auto-analyser (Technicon III) following standard protocols (Aminot and Kérouel, 2007). The quantification limits were 0.2 mM for silicate, 0.1 mM for nitrate, 0.02 mM for nitrite, 0.04 mM for phosphate and 0.1 mM for ammonia. In the following text and figures, “NOx” and “N” represent NO3 + NO2 and NOx + NH4+, respectively.

2.3. Chlorophyll a concentration To estimate phytoplankton biomass, chlorophyll a (chl a) concentrations were measured using the Welschmeyer method (1994). The samples (1 l) were gently filtered through GF/F filters (47 mm diameter, 0.7 mm pore size) and stored in black tubes (15 ml, FALCON, USA) at 80  C until analysis. Chl a was extracted on filters in 10 ml of 90% (v/v) acetone overnight in the dark at 4  C. After centrifugation, the chl a concentrations were measured by fluorometry (TD-700, Turner Designs, Sunnyvale, California, USA). 2.4. Microphytoplankton enumeration and identification Immediately after sampling, 1 l of seawater was preserved using acid Lugol solution (2 ml l1). The Utermöhl (1958) method was used to identify and enumerate microphytoplankton. After homogenisation, a 10 ml water sample was poured into a sedimentation chamber and left to settle for at least 8 h. The phytoplankton cells on the chamber bottom were identified and counted using an inverted microscope (Leica DMI 3000B). The organisms were identified to the lowest taxonomic level possible. While the total abundance of Pseudo-nitzschia spp. (cells l1) was determined by light microscopy using the Utermöhl method,

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Pseudo-nitzschia spp. cells were also separated in two distinct groups on the basis of cell width: the Pseudo-nitzschia seriata complex (>3 mm width) and the Pseudo-nitzschia delicatissima complex (<3 mm width) (Hasle and Syvertsen, 1996). P. americana does not belong to these two complexes and, in light microscopy, is easy to discriminate from them, but not from some other small pennate diatoms (Lundholm et al., 2002b), so it was not included in the “Pseudo-nitzschia spp.” counts. When Pseudo-nitzschia spp. concentrations were higher than 15,000 cells l1, Pseudo-nitzschia species were identified using transmission electron microscopy (TEM, JEOL/JEM-1011). For TEM observations of Pseudo-nitzschia frustules, samples were cleaned to remove organic material according to the method of Lundholm et al., 2002a, except that 2 ml of hydrochloric acid were used in addition to sulfuric acid. 2.5. Particulate domoic acid concentration Particulate DA concentrations were analysed as described in Thorel et al. (2014). For each sample, 1 l of seawater was filtered on a GF/F filter (47-mm diameter) at low vacuum pressure, to preserve the phytoplankton cells, and filters were stored frozen at 20  C until analysis. The concentration of particulate DA on the filters was determined according to Wang et al. (2007) by HPLC/MS–MS (1290 Infinity, Agilent Technologies). The quantification limit (QL) of the method was 2.5 ng DA/filter, but the detection limit (DL) was 0.8 ng DA on the filter. Cellular DA (cDA) concentrations in the samples were calculated from the particulate DA concentration (pDA) and Pseudo-nitzschia spp. concentrations (PNspp): ½cDA ¼

½pDA ½PNspp

ð1Þ

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photons m2 s1 and 6  C in winter in late December-early January and March. Surface salinity (Fig. 2C) ranged from 31.3 (Dec 2013) to 34.2 (Oct 2012). The lowest salinity levels were measured in 2013. Maximum salinity values were measured in October 2012 (34.2) and October 2013 (33.2). The lowest salinity values were related to an increase in river runoff (Fig. 2D) in winter. There was a significant negative correlation between salinity and the Seine runoff (r = 0.6, p < 0.05, Table 1). The Seine (Fig. 2D) presented the lowest runoffs in summer (161 m3 s1 in September 2012, 240 m3 s1 in August 2013) and peak discharges in spring and autumn (1150 and 1210 m3 s1 in May and November 2013, respectively). The Orne runoff had the same dynamics as the Seine runoff (Fig. 2D, Table 1) and varied between 1.12 m3 s1 (August 2013) and 61.7 m3 s1 (December 2012). The nutrient concentrations measured at the sampling station showed clear seasonal patterns (Fig. 2E): they increased over the winter months (up to 25.7 mmol l1 for Si(OH)4, 1.1 mmol l1 for PO43 and 42.9 mmol l1 for NOx) and decreased in spring and summer. Nutrients reached extremely low levels during the two years, down to 0.54 mmol l1 in May for Si(OH)4, 0.06 mmol l1 in June and July for PO43, and 0.1 mmol l1 in July for NOx. The maximum concentrations of Si(OH)4 and NOx were measured in autumn 2013 and autumn 2012 for PO43. It is worth noting that Si (OH)4 and NOx concentrations were generally higher in spring 2013 than spring 2012. The temporal evolution of nutrient ratios is presented in Fig. 3. The lowest Si:P (Fig. 3A) and Si:N (Fig. 3B) ratios were observed between April and June, but were lower in 2012 for Si:P (minimum 7.1 in 2012 and 13.0 in 2013). Si:N ratios were lower during the summer of 2013 (down to 0.09 in July) as compared to 2012 (minimum value 0.9 in July). N:P ratios also presented a clear seasonal pattern (Fig. 3C), with higher ratios in May and June. N:P ratios also remained high in July and August 2013. 3.2. Microphytoplankton dynamics

2.6. Statistical analyses Multivariate analyses were performed using R 2.15.3 software program. Pearson correlations for physicochemical and biological variables in surface water throughout the study (May 2012– December 2013) were tested (Table 1). Principal component analyses (PCA) were performed to characterise the relationships between physicochemical parameters (temperature, solar radiation, salinity, nutrients, Seine and Orne runoffs, rainfall) and biological parameters (chl a, DA). The influence of physicochemical parameters on Pseudo-nitzschia spp. dynamics was studied over the whole May 2012–December 2013 period. In addition, in order to compare the two years 2012 and 2013 and study more precisely the environmental control of the blooms of each Pseudo-nitzschia complex, the influence of these parameters on the abundance levels of the P. seriata and P. delicatissima complexes was studied, from May to December of each year (the January to April period was not studied in 2012). Biological parameters were log-transformed, standardised, and added to the PCA as illustrative variables. 3. Results 3.1. Seasonal variations of environmental parameters The temporal evolution of solar radiation and water temperature was characterised by clear seasonal patterns typical of northwestern Europe (Fig. 2A and B). Both variables generally increased in early spring to reach their maximum in summer (around 500 mmol photons m2 s1 and 19  C in late June-early July and August) and decreased in autumn to reach around 9 mmol

The highest chl a concentrations were recorded during the spring/summer periods (Fig. 2F): following the increase in irradiance, maximum concentrations were observed in June 2012 (5.8 mg l1) and in April 2013 (8 mg l1), during the diatom blooms (Fig. 4A). Chl a concentrations decreased in autumn and winter (from September to March) down to 0.54 mg l1 in January 2013 and 0.55 mg l1 in December 2013. In the spring/summer period, chl a concentrations were higher in 2013 than in 2012 (Fig. 2F). Diatoms represented the dominant microphytoplankton taxon (95%), except in autumn 2012 and 2013 when Dinoflagellates were more abundant (up to 33% and 80%, respectively) and in October 2012 and December 2013 when Dinoflagellates increased in abundance or even became dominant (up to 79%, data not shown). In 2012, diatoms showed two distinct blooms in spring and summer, with the highest cell concentrations in May with 2.6 106 cells l1 and in July with 4.2 106 cells l1. In contrast, diatoms were abundant in 2013 (maximum abundance 1.7 106 cells l1 in July). During both 2012 blooms, the diatom assemblage was largely dominated by Chaetoceros spp. followed by Guinardia delicatula (Cleve) Hasle in spring (data not shown). In 2013, an uninterrupted succession of different dominant species was rather observed: (i) Skeletonema marinoï Sarno and Zingone dominated between January and March, (ii) Pseudo-nitzschia spp. in June, (iii) Leptocylindrus sp. and Chaetoceros spp. in July, and (iv) only Chaetoceros spp. in August. Pseudo-nitzschia spp. was thus present in the spring/summer diatom assemblage the two years, but became dominant only in spring 2013 (8.4 105 cells l1, in June 2013). In spring or summer of the two years, Pseudo-nitzschia spp. was observed simultaneously with high abundances of Chaetoceros spp., Guinardia delicatula and Leptocylindrus sp. (data not shown).

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Fig. 2. Time series plots of A) global solar radiations, B) water temperature, C) salinity, D) Seine and Orne runoffs, E) nutrients concentrations (NOx, PO4 and Si(OH)4), and F) Chl a concentrations throughout the sampling period (from May 2012 to December 2013). Grey areas indicate the periods of Pseudo-nitzschia spp. blooms.

3.3. Temporal evolution of Pseudo-nitzschia species diversity and particulate DA concentrations During the sampling period, Pseudo-nitzschia spp. was detected in 72% of the samples, with densities up to 8.4 105 cells l1. As previously mentioned, two groups of Pseudo-nitzschia were identified and enumerated by light microscopy: the P. seriata

complex (>3 mm width) and the P. delicatissima complex (< 3 mm width). These two complexes presented different population dynamics between 2012 and 2013 (Fig. 4A). The P. seriata and P. delicatissima complexes represented 99.8% and 0.2%, respectively, of the Pseudo-nitzschia assemblage from May to December 2012. In contrast, during the same period in 2013, the P. seriata complex made up 1.2% of Pseudo-nitzschia cells and the P. delicatissima

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Fig. 3. Nutrient ratios from May 2012 to December 2013: A) Si:P, B) Si:N, and C) N:P. Grey areas indicate the periods of Pseudo-nitzschia spp. blooms.

complex 98.8%. Moreover, higher cell concentrations were observed in late spring 2013 than in 2012 with a peak at 8.4 105 cells l1 in June for the P. delicatissima complex whereas the P. seriata complex only reached 1.5 105 cells l1 in late May 2012 (Fig. 4A). Infection of Pseudo-nitzschia by fungal parasites (Supplementary material Fig. S1A) and the presence of cells with discharge tubes (Supplementary material Fig. S1 B) were observed during the 2012 Pseudo-nitzschia bloom dominated by the P. seriata complex. These two stages of infected Pseudo-nitzschia cells were present in the samples on three occasions: at the end of May, early June and July 2012, just before the decrease in Pseudo-nitzschia spp. abundance (Fig. 4A). Cell infection rates however did not exceed 1% of total Pseudo-nitzschia spp. and no infection was detected in 2013. Samples in which the Pseudo-nitzschia concentration was above 15,000 cells l1 were examined by TEM to identify Pseudo-nitzschia

species. Five species were identified: P. fraudulenta (Cleve) Hasle, P. pungens (Grunow ex Cleve) Hasle, P. australis Frenguelli (belonging to the P. seriata complex), P. delicatissima (Cleve) Heiden (P. delicatissima complex) and P. americana (Hasle) Fryxell (data not shown). Pseudo-nitzschia australis, P. pungens and P. fraudulenta were observed during the 2012 Pseudo-nitzschia bloom: P. australis was dominant in May whereas P. pungens was dominant in June. In contrast, P. delicatissima largely dominated the Pseudo-nitzschia bloom in 2013 with P. pungens also observed in June. P. australis and P. fraudulenta were not observed in 2013 (Fig. 4B). Particulate domoic acid (pDA) concentrations varied greatly and ranged from
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Fig. 4. Dynamics of A) total diatom and Pseudo-nitzschia complex abundance, B) proportions of the different Pseudo-nitzschia species, and C) particulate DA measured in surface water at the sampling site from May 2012 to December 2013. Black stars in A indicate the presence of parasitized Pseudo-nitzschia cells and black crosses in C represent values of pDA below the quantification limit.

2013 when P. delicatissima was dominant, pDA was only detected in very low concentrations (from
runoffs and nutrient concentrations in winter and high solar radiation and temperature in spring/summer (Fig. 5B). The chl a concentration was positively correlated with irradiance, highlighting that the spring microphytoplankton bloom was controlled by light. Pseudo-nitzschia spp. abundance was highly related to chl a concentrations, demonstrating that this genus belonged to the diatom spring bloom. Si(OH)4 and PO43 were negatively correlated to this high biomass value, while NOx did not have a clear relationship with other nutrients or phytoplankton biomass. NOx concentrations seemed to be driven by both the Seine and Orne river runoffs. The PCA confirmed that particulate DA was positively related to the presence of Pseudo-nitzschia spp. over the whole sampling period. The second (Fig. 6) and third (Fig. 7) PCAs compared the relationships between physicochemical parameters and Pseudonitzschia dynamics between the two years. The first two axes of the two PCAs explained 68 and 73% of the total variance, respectively. Over the two years (Figs. 6 and 7), high chl a concentrations and Pseudo-nitzschia complex abundance levels coincided with high N:

M. Thorel et al. / Harmful Algae 68 (2017) 192–205

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Fig. 5. Principal component analysis (PCA) from May 2012 to December 2013 in the plane defined by the two first axes showing the link between physicochemical and biological parameters and Pseudo-nitzschia spp. abundance. A) Relation between physicochemical and biological parameters and Pseudo-nitzschia spp. abundance (see correlation matrix among these factors in Table 1), dashed arrows represent Supplementary variables. B) Projection of sampling dates as a function of physicochemical parameters. WatT: water temperature; NOx: NO3 + NO2; Sal: salinity; SolarRad: solar radiation; Chl: chlorophyll a; pDA: particulate domoic acid; PN: Pseudo-nitzschia sp. abundance.

P ratios. The P. delicatissima complex was misrepresented on the PCA performed on the 2012 data set due to the low abundance of the complex that year. By contrast, it was clearly discriminated in 2013 when it was very abundant. In 2012, pDA was positively related to the P. seriata complex, which included P. australis (Fig. 6).

In 2013, pDA seemed to be related to both Pseudo-nitzschia complexes (Fig. 7), but very low concentrations of pDA were detected that year (Fig. 4C). The high P. seriata complex abundance levels associated with high levels of pDA in 2012 were correlated to low Si:P ratios. Furthermore, the high P. delicatissima complex

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Fig. 6. Principal component analysis (PCA) from May 2012 to December 2012 in the plane defined by the two first axes showing the link between physicochemical parameters, chl a, pDA and the abundance of the two Pseudo-nitzschia complexes. The correlation matrix among these factors is reported in Table 1. Dashed arrows represent Supplementary variables. P.ser: Pseudo-nitzschia seriata complex abundance; P.del: Pseudo-nitzschia delicatissima complex abundance; Chl: chlorophyll a; pDA: particulate domoic acid; WatT: water temperature; Sal: salinity.

abundance levels in 2013 were linked to low Si:N ratios. Therefore, the balance between Si(OH)4 and other nutrients like PO43 and NOx seemed to control Pseudo-nitzschia species diversity. 4. Discussion This study presents two contrasting years in terms of Pseudonitzschia abundance, diversity and toxin concentrations. The relationships between dynamics of Pseudo-nitzschia diversity, toxin production and environmental factors were characterised. 4.1. Pseudo-nitzschia spp. and microphytoplankton blooms Physicochemical and biological parameters showed a typical seasonal pattern of temperate areas with inter-annual variations (Pannard et al., 2008; Napoléon et al., 2013). Furthermore, the general pattern of the structure of the microphytoplankton assemblage was characteristic of the central English Channel and triggered by seasonality (Videau et al., 1998; Jouenne et al., 2007; Pannard et al., 2008; Napoléon et al., 2014). Low biomass characterised the winter periods, followed by an extensive spring bloom dominated by diatoms. Diatom abundance then decreased due to nutrient depletion, and dinoflagellates increased in abundance in late summer and autumn. Diatoms are known to dominate phytoplankton assemblages in high-nutrient and highturbulence systems, whereas dinoflagellates are likely to dominate under low nutrient and turbulence conditions (Margalef, 1978; Cullen et al., 2007). In 2012, during the spring and summer periods, two distinct blooms of diatoms dominated by Chaetoceros spp. were observed. By contrast, in 2013 diatom blooms appeared less separated (probably due to the reduced sampling frequency) and

dominance was shared among several diatom species (Skeletonema marinoï, Pseudo-nitzschia spp., Leptocylindrus sp. and Chaetoceros spp). Pseudo-nitzschia spp. abundance levels were positively linked to chl a concentrations, highlighting that this genus forms part of the microphytoplankton spring bloom. Maximum Pseudo-nitzschia abundance (8.4 105 cells l1) was observed in spring 2013; it was in the range of Pseudo-nitzschia spp. concentrations previously reported for the Bay of Seine (Klein et al., 2010; Husson et al., 2016). The association of Pseudo-nitzschia spp. with Leptocylindrus sp. and Chaetoceros sp. appears to be recurrent; it was observed in the same area (Pannard et al., 2008) and in other temperate ecosystems (Trigueros and Orive, 2001) suggesting ecological similarities among these species. 4.2. Environmental factors controlling Pseudo-nitzschia spp. bloom dynamics Multivariate analyses indicated that the occurrence of the Pseudo-nitzschia genus was significantly correlated with different sets of environmental parameters. Among these factors, variations in irradiance influenced Pseudo-nitzschia blooms in the Bay of Seine. The highest Pseudo-nitzschia concentrations were observed from spring to early summer, when light intensity and the photoperiod increased, in agreement with previous results from different French coastal areas (Husson et al., 2016). As mentioned by Napoléon et al. (2013), light intensity appears to be the major limiting factor of diatom production in the region. High abundance levels of Pseudo-nitzschia occurred when irradiance ranged between 90 and 350 mmol photons m2 s1. These values are in accordance with the optimal growth irradiance measured for monoclonal cultures of Pseudo-nitzschia several species, such as P.

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Fig. 7. Principal component analysis (PCA) from May 2013 to December 2013 in the plane defined by the two first axes showing the link between physicochemical and biological parameters and the abundance of the Pseudo-nitzschia seriata and Pseudo-nitzschia delicatissima complexes. The correlation matrix among these factors is reported in Table 1. Dashed arrows represent Supplementary variables. P.ser: Pseudo-nitzschia seriata complex abundance; P.del: Pseudo-nitzschia delicatissima complex abundance; Chl: chlorophyll a; pDA: particulate domoic acid; WatT: water temperature; Sal: salinity.

australis (Cochlan et al., 2008; Bill et al., 2012; Thorel et al., 2014), P. multiseries (Bates, 1998; Bates et al., 1998) and P. pungens (unpublished data), even if the light intensity at the sampling depth was probably lower. Moreover, these results confirm that Pseudo-nitzschia species can grow under a wide irradiance range in situ and possess high photoacclimation capacities (Thorel et al., 2014). High inter-annual variability in seasonal river runoffs was observed, with higher runoffs in 2013 than in 2012 for both the Seine and Orne rivers, entailing differences in salinity and nutrient inputs. NOx concentrations were strongly correlated to river runoffs and were much higher between May and December of 2013 than 2012. Such higher nitrate concentrations may partly explain the significantly higher Pseudo-nitzschia abundance recorded in 2013: different in situ and mesocosm studies previously showed that Pseudo-nitzschia blooms could be stimulated by nitrate inputs (Parsons et al., 2002; Carter et al., 2005; Liefer et al., 2009; Macintyre et al., 2011; Claquin et al., 2010; Downes-Tettmar et al., 2013). In addition, the results point to a strong negative correlation between silicate, phosphate and the occurrence of Pseudo-nitzschia blooms. This negative correlation is due to nutrient uptake for growth and does not necessarily indicate that Pseudo-nitzschia spp. can grow under low nutrient concentrations. This result however suggests that silicate and phosphate were limiting factors during the diatom bloom. Pseudo-nitzschia spp. blooms therefore occurred from May to August when irradiance levels were high, nitrate was still available and when silicate and phosphate concentrations were very low. Previous laboratory studies showed that Pseudo-

nitzschia species could grow under low silicate concentrations (Cusack et al., 2002) and could be more competitive than other diatom species during silicate depletion periods (Marchetti et al., 2004). During the 2012 Pseudo-nitzschia blooms, a few Pseudonitzschia cells infected by fungal parasites were detected, probably zoosporic members of Oomycetes and/or Chytridiomycetes (Hanic et al., 2009). The abundance levels of Pseudo-nitzschia spp. decreased just after the infection events, suggesting that the parasitic fungi impacted the blooms. To our knowledge only one study has attempted a careful study of the parasitic infections of Pseudo-nitzschia (Hanic et al., 2009), while others have shown or suspected that parasitic fungi may play an important role in phytoplankton dynamics and in the termination of Pseudonitzschia blooms (Bates et al., 1998; Hasle et al., 1996; Trainer et al., 2012). Such events especially affected P. pungens and P. multiseries in North Atlantic waters, mainly off the Canadian and U. S. coasts. The low prevalence of infected cells recorded in this study (1%) does not allow us to conclude on the role of parasitism in the Pseudo-nitzschia dynamics; however, this does not necessarily mean that parasitism had no significant consequences on the host population. The life cycle of fungal parasites is likely to be completed within a short time (e.g. 2–3 days in Bruning and Ringelberg, 1987; Gerphagnon et al., 2013), and may then induce a rapid regulation of blooming phytoplankton species in a few days. By comparison, the weekly/fortnightly sampling resolution used here was probably too low because observations of infected Pseudo-nitzschia are difficult and rare in natural samples. The phase

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of rapid increase in parasite prevalence that precede the bloom decline may have been missed during this study. These preliminary observations question the role of such a biotic control in Pseudonitzschia bloom dynamics.

suggest that the variations in nutrient ratios, and especially of Si:P and Si:N, could influence on the selection of the different Pseudonitzschia species during the bloom season. Such a result could be explained by differences in nutrient uptake abilities, cell quotas and stoichiometry between Pseudo-nitzschia species.

4.3. Pseudo-nitzschia: a significant species diversity 4.4. Implication of Pseudo-nitzschia diversity in toxicity Significant differences were measured in Pseudo-nitzschia abundance levels between the spring blooms of 2012 and 2013. In 2012, the Pseudo-nitzschia assemblage was dominated by species belonging to the Pseudo-nitzschia seriata complex. More particularly, at the species level, in 2012 the spring bloom was dominated by P. australis and the summer bloom by P. pungens. In 2013, the Pseudo-nitzschia assemblage was largely dominated by a single species, P. delicatissima. All the Pseudo-nitzschia species identified during this study, except P. americana, have been described as potentially toxic (Fryxell and Hasle, 2003). All these species have already been observed on the French coast of the English Channel (Nezanet al., 2006; Klein et al., 2010). In contrast to Nezan et al. (2006) and Klein et al. (2010), we did not observe P. multiseries or P. multistriata in 2012 and 2013, suggesting that the inter-annual variability of Pseudo-nitzschia species diversity might be even greater than revealed in the present study. The results show that the occurrence of the two Pseudonitzschia complexes was triggered by different nutrient conditions. The two complexes were positively correlated to high N:P ratios, confirming that nitrate-rich environments can favour Pseudonitzschia spp. growth. In 2012, the P. seriata complex was correlated with low Si:P ratios, whereas in 2013 the P. delicatissima complex was correlated with low Si:N ratios. Low Si:P ratios in 2012 were reached after the microphytoplankton spring bloom when both Si and P were limiting. In contrast, the low Si:N ratios during the 2013 spring reflected the imbalance between nutrients linked to higher nitrate concentrations in 2013 than in 2012. This study thus suggests differences in nutrient stoichiometry preferendum of Pseudo-nitzschia species. These results are in agreement with previous studies pointing out that Pseudo-nitzschia delicatissima appeared to be promoted by high nitrate and low silicate concentrations (Kaczmarska et al., 2007; Klein et al., 2010; Quijano-Scheggia et al., 2008a), even if a negative correlation was found between nitrate and the P. delicatissima complex on the western English Channel (Downes-Tettmar et al., 2013). During this study, P. delicatissima was highly abundant at low temperatures (8.4 105 cells l1 at
13  C) which is in accordance with studies by Quijano-scheggia et al. (2008b) and Klein et al. (2010). The affinity of P. fraudulenta for lower temperatures (Quijanoscheggia et al., 2008b; Klein et al., 2010; Downes-Tettmar et al., 2013) also explains the occurrence of this species in early spring 2012. P. pungens was observed during the two years of study, underlining its high acclimation capacities. The results are also in agreement with the low environmental constraint previously described for this species in comparison with other Pseudonitzschia species (Klein et al., 2010) and its worldwide distribution (Hasle, 2002). Low concentrations of phosphate and silicate and low Si:P ratios appeared to promote the development of P. australis. This result matches those of Klein et al. (2010) in the Bay of Seine, but do not match with Almandoz et al. (2007) who found that P. australis reached high densities when nitrate and phosphate concentrations were low in the continental shelf waters of Argentina. An increase in nitrogen and phosphorus has been observed in many coastal ecosystems. In some cases, nutrient increases also changed nutrient ratios, as in the Mississippi River where the Si:N ratio decreased over the last century (Turner and Rabelais, 1991). As a result, imbalances in nutrient ratios stimulated Pseudonitzschia blooms (Parsons et al., 2002). The results of this study

In the Bay of Seine, major DA events were observed in 2004, 2011, and 2012 with DA levels in king scallops (Pecten maximus) above the EU-regulatory limit of 20 mg DA g1 tissue for several months (Husson et al., 2016). In 2012, pDA concentrations in surface water were among the highest reported to date in the region (
1400 ng DA l1). These concentrations are relatively low when compared with values found in other areas and especially on the west coast of North America (Trainer et al., 2002; Schnetzer et al., 2007; Anderson et al., 2009). For example, pDA concentrations up to 52 mg DA l1 were measured in the surface waters of San Pedro Channel (Stauffer et al., 2012), known to be a “hotspot” for toxic Pseudo-nitzschia species. In the Bay of Seine, high pDA concentrations were significantly associated with the occurrence of the P. seriata complex (r = 0.62, p < 0.05, Table 1). More precisely, the highest toxicity level was observed concomitantly with the highest abundance of P. australis. This species is considered as one of the most toxic species of its genus (Trainer et al., 2009); this confirms that it is the main source of DA in the Bay of Seine, as already suspected by Nezan et al. (2006) and Klein et al. (2010). Maximum pDA concentrations were recorded in 2012 when silicate and phosphate were both limiting. Domoic acid production is often stimulated by either phosphate or silicate limitation (Fehling et al., 2004a). Therefore, considering environmental conditions, silicate and phosphate limitations may be driving factors of in situ DA production. In the study area, pDA was correlated with the abundance of the P. seriata complex, solar radiation and the N:P ratio. It is hard to tell whether this reflects an influence of irradiance and nutrient ratios directly on pDA production or on the development of the toxic species, or both. We can safely assume that in the Bay of Seine, pDA concentrations in the phytoplankton depend not only on the abundance of Pseudonitzschia spp. but also on Pseudo-nitzschia species diversity, especially on the occurrence and abundance of P. australis, and maybe also on the influence of the nutrient environment on DA production by this species. No correlation was found between cellular DA content (cDA) and Pseudo-nitzschia spp. concentrations (data not shown). The highest cDA values (
10 pg DA cell1 in May 2012 and
16 pg DA cell-1 in July 2012) were observed when P. australis and P. pungens dominated the Pseudo-nitzschia assemblage and Si:N ratios were low. The influence of the Si:N ratio and Pseudo-nitzschia species composition on cDA concentrations is highlighted in Fig. 8. This diagram summarises three possible situations: i) high cDA concentrations when P. australis and/or P. pungens are present and associated with low Si:N ratios; ii) low cDA concentrations when P. australis and/or P. pungens are present and associated with high Si:N ratios; iii) low cDA concentrations when P. fraudulenta or P. delicatissima are present, even when P. australis is in higher proportions. The fact that a sample characterised by low proportions of P. pungens and P. fraudulenta associated with high proportions of P. australis presented low cDA concentrations suggests important variability in cDA among Pseudo-nitzschia species in the area, and possible underestimation of cell toxicity when using total Pseudo-nitzschia spp. concentrations to calculate cDA. These results confirm that P. australis is the main toxic species triggering DA events in the Bay of Seine. Furthermore, they imply

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Fig. 8. Diagram of cellular domoic acid (cDA) as a function of the Si:N ratios and the proportions of Pseudo-nitzschia species.

that Si:N ratios may influence DA production by Pseudo-nitzschia species, especially P. australis and P. pungens. 4.5. Consequences for future monitoring and predictive studies of Pseudo-nitzschia toxic blooms in the Bay of Seine

This is of particular importance since the results presented here stress the fact that the Pseudo-nitzschia issue needs to be addressed by monitoring and understanding bloom dynamics at the species level, and not only at the genius or complex levels. 5. Conclusion

The results of the present study are very informative for understanding the environmental factors that promote toxic Pseudo-nitzschia blooms in the Bay of Seine. The next step could consist in providing scenarios for ecosystem management and developing early warning tools for potential DA events. Predictive models could be developed as previously done for Pseudo-nitzschia blooms in other ecosystems (Blum et al., 2006; Anderson et al., 2009, 2010; Lane et al., 2009). In these studies, laboratory and/or field data were used to develop statistic models to predict the probability for a toxic bloom to occur, based on environmental predictor variables. The development of such models for the Bay of Seine requires long-term time series of Pseudo-nitzschia spp. abundance, species diversity, pDA concentrations and physicochemical data. The environmental factors correlated with the P. seriata complex and high pDA (nutrient concentrations, nutrient ratios and irradiance) could then be tested as predictor variables to develop a statistic model of toxic bloom occurrence based on Pseudo-nitzschia and DA data from the Bay of Seine. The available laboratory data for Pseudo-nitzschia strains from the same ecosystem (e.g. Claquin et al., 2008; Thorel et al., 2014) may also be used to improve this model (Blum et al., 2006). This tool should be developed for the prediction of Pseudo-nitzschia complex abundance, but also species diversity and pDA concentrations, as recommended by Lane et al. (2009) and Anderson et al. (2009).

The present work reveals that the occurrence of two Pseudonitzschia complexes in the Bay of Seine showed a differential response to nutrient ratios. The P. seriata complex was mainly favoured by low Si:P ratios, while the P. delicatissima complex was associated with low Si:N ratios and high nitrate concentrations. These findings indicate that the nutrient balance probably plays a role in Pseudo-nitzschia species selection. Such a regulation needs to be investigated through a complementary laboratory approach on the nutrient uptake capacities of the different species and longterm monitoring in the environment. High particulate DA concentrations responsible for shellfish harvesting closures in the Bay of Seine were related to the development of P. australis. These results underline the importance of identifying Pseudonitzschia at the species level to understand their dynamics and toxin production. The predictive models to be used as early warning tools for DA events in the Bay of Seine will therefore have to take into account nutrients and species dynamics. DA concentrations in phytoplankton and the potentially resulting DA events actually depend on Pseudo-nitzschia species diversity that varies each year, but also on the cellular toxicity of these species. Both are differentially influenced by nutrient ratios, since P. australis occurrence was favoured by low Si:P ratios while high cDA was favoured by low Si:N ratios. This work demonstrates that

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besides N fluxes, the dynamics of nutrient ratios should be carefully considered in ecosystem management programs. Acknowledgements In memory of Franck Bruchon. The authors thank the Ifremer LER/N staff (E. Rabiller, S. Françoise, B. Simon, F. Maheux and O. Pierre-Duplessix) for material, technical and analytical assistance during the study. We also thank the BOREA laboratory and CREC marine station staffs for their help during the field work and Estelle Ozouf (LABEO Franck Duncombe) for DA analyses. We are grateful to Catherine Dreanno, Charlotte Noyer and Raffaele Siano for constructive discussions. We also thank the 2 anonymous reviewers for their comments and suggestions that helped improve the manuscript. This work was funded by the TAPAS (Agence de l’eau Seine Normandie  Fonds Européens pour la Pêche) and FLAM (Agence de l’eau Seine Normandie  programme LITEAU, Ministère de l’Environnement, de l’Énergie et de la Mer) programmes. M. Thorel received a PhD fellowship from the Ministère de la Recherche et de l’Enseignement Supérieur and this paper is part of her Ph.D. thesis.[CG] Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.hal.2017.07.005. References Almandoz, G.O., Ferrario, M.E., Ferreyra, G. a., Schloss, I.R., Esteves, J.L., Paparazzo, F. E., 2007. The genus Pseudo-nitzschia (Bacillariophyceae) in continental shelf waters of Argentina (Southwestern Atlantic Ocean, 38–55(S). Harmful Algae 6, 93–103. doi:http://dx.doi.org/10.1016/j.hal.2006.07.003. Almandoz, G.O., Ferreyra, G. a., Schloss, I.R., Dogliotti, A.I., Rupolo, V., Paparazzo, F.E., Esteves, J.L., Ferrario, M.E., 2008. Distribution and ecology of Pseudo-nitzschia species (Bacillariophyceae) in surface waters of the Weddell Sea (Antarctica). Polar Biol. 31, 429–442. doi:http://dx.doi.org/10.1007/s00300-007-0369-9. Amato, A., Orsini, L., D’Alelio, D., Montresor, M., 2005. Life cycle, size reduction patterns, and ultrastructure of the pennate planktonic diatom Pseudo-nitzschia delicatissima (Bacillariophyceae): life cycle of Pseudo-nitzschia delicatissima. J. Phycol. 41, 542–556. doi:http://dx.doi.org/10.1111/j.1529-8817.2005.00080.x. Aminot, A., Kérouel, R., 2007. Dosage automatique des nutriments dans les eaux marines. Quae, Quae, Versailles. Anderson, C.R., Siegel, D.A., Kudela, R.M., Brzezinski, M.A., 2009. Empirical models of toxigenic Pseudo-nitzschia blooms: potential use as a remote detection tool in the Santa Barbara Channel. Harmful Algae 8, 478–492. doi:http://dx.doi.org/ 10.1016/j.hal.2008.10.005. Anderson, C.R., Sapiano, M.R.P., Krishna, M.B., Long, W., Tango, P.J., Brown, C.W., Murtugudde, R., 2010. Predicting potentially toxigenic Pseudo-nitzschia blooms in the Chesapeake Bay. J. Mar. Syst. 83, 127–140. doi:http://dx.doi.org/10.1016/j. jmarsys.2010.04.003. Bates, S.S., De Freitas, A.S.W., Milley, J.E., Pocklington, R., Quilliam, M.A., Smith, J.C., Worms, J., 1991. Controls on domoic acid production by the diatom Nitzschia pungens f. multiseries in culture: nutrients and irradiance. Can. J. Fish. Aquat. Sci. 48, 1136–1144. Bates, S.S., Garrison, D.L., Horner, R.A., 1998. Bloom dynamics and physiology producing Pseudo-nitzschia species of domoic acid kainic acid glutamic acid, 267–292. Bates, S.S., 1998. Ecophysiology and metabolism of ASP toxin production. In: Anderson, D.M., Cembella, A.D., Hallegraeff, G.M. (Eds.), Phycological Ecology of Harmful Algal Blooms. Springer-Verlag, Heidelberg, pp. 405–426. Bill, B.D., Cochlan, W.P., Trainer, V.L., 2012. The effect of light on growth rate and primary productivity in Pseudo-nitzschia australis and Pseudo-nitzschia turgidula. In: Pagou, P., Hallegraeff, G. (Eds.), Proceedings of the 14th International Conference on Harmful Algae, International Society for the Study of Harmful Algae and Intergovernmental Oceanographic Commission of UNESCO, pp. 78–80. Billen, G., Garnier, J., Némery, J., Sebilo, M., Sferratore, A., 2007. A long-term view of nutrient transfers through the Seine river continuum. Sci. Total Environ. 375, 80–97. doi:http://dx.doi.org/10.1016/j.scitotenv.2006.12.005. Blum, I., Subba Rao, D.V., Pan, Y., Swaminathan, S., Adams, N.G., 2006. Development of statistical models for prediction of the neurotoxin domoic acid levels in the pennate diatom Pseudonitzschia multiseries utilizing data from cultures and natural blooms. In: Subba Rao, D.V. (Ed.), Algal Cultures, Analogues of Blooms and Applications. Science Publishers, Enfield, NH, pp. 891–916.

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