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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0">
  <front>
    <journal-meta><journal-id journal-id-type="publisher">BG</journal-id><journal-title-group>
    <journal-title>Biogeosciences</journal-title>
    <abbrev-journal-title abbrev-type="publisher">BG</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Biogeosciences</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1726-4189</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/bg-15-4431-2018</article-id><title-group><article-title>Impact of decadal reversals of the north Ionian circulation<?xmltex \hack{\break}?> on phytoplankton
phenology</article-title><alt-title>Impact of decadal reversals of the north Ionian circulation</alt-title>
      </title-group><?xmltex \runningtitle{Impact of decadal reversals of the north Ionian circulation}?><?xmltex \runningauthor{H. Lavigne et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Lavigne</surname><given-names>Héloise</given-names></name>
          <email>hlavigne@naturalsciences.be</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Civitarese</surname><given-names>Giuseppe</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Gačić</surname><given-names>Miroslav</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>D'Ortenzio</surname><given-names>Fabrizio</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Royal Belgian Institute of Natural Sciences, Operational Directorate
Natural Environment,<?xmltex \hack{\break}?> Gulledelle 100, 1200 Brussels, Belgium</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Istituto Nazionale di Oceanografia e di Geofisica Sperimentale – OGS,
Dip. di Oceanografia,<?xmltex \hack{\break}?> Borgo Grotta Gigante 42/c, 34010 Sgonico (Trieste),
Italy</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Laboratoire d'Oceanographie de Villefranche, Université Pierre et
Marie Curie et CNRS, UMR 7093,<?xmltex \hack{\break}?> Villefranche-sur-Mer, France</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Héloise Lavigne (hlavigne@naturalsciences.be)</corresp></author-notes><pub-date><day>19</day><month>July</month><year>2018</year></pub-date>
      
      <volume>15</volume>
      <issue>14</issue>
      <fpage>4431</fpage><lpage>4445</lpage>
      <history>
        <date date-type="received"><day>19</day><month>November</month><year>2017</year></date>
           <date date-type="rev-request"><day>18</day><month>December</month><year>2017</year></date>
           <date date-type="rev-recd"><day>20</day><month>June</month><year>2018</year></date>
           <date date-type="accepted"><day>22</day><month>June</month><year>2018</year></date>
      </history>
      <permissions>
        
        
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://bg.copernicus.org/articles/.html">This article is available from https://bg.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://bg.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://bg.copernicus.org/articles/.pdf</self-uri>
      <abstract>
    <p id="d1e129">In the north Ionian, water circulation is characterized by a decadal
alternation of cyclonic and anticyclonic regime driven by the mechanism
called BiOS (bimodal oscillating system). The circulation regimes affect both
vertical dynamics and the nutrient distribution. The north Ionian is then a
good study area to investigate how changes in circulation can affect
phytoplankton dynamics in oligotrophic regions. From in situ observations,
for each circulation regime the averaged distribution of isopycnals is
provided, and a depth difference of about 80 m is estimated for the
nitracline between the cyclonic and anticyclonic regime. Based on phytoplankton
phenology metrics extracted from annual time series of satellite ocean color
data for the period 1998–2012, the cyclonic and anticyclonic regimes are
compared. Results show that the average chlorophyll in March, the date of
bloom onset and the date of maximum chlorophyll were affected by circulation
patterns in the north Ionian. In the center of the north Ionian gyre, the
bloom started in December and chlorophyll was low in March when circulation
was anticyclonic, whereas during the cyclonic circulation regime, a late
chlorophyll peak, likely resulting from different phytoplankton dynamics, was
commonly observed in March. An additional analysis shows that the winter
buoyancy losses, which govern the mixed layer depth (MLD), also contribute to
explaining the interannual variability in bloom onset and intensity. Two trophic
regimes were then identified in the north Ionian gyre (NIG) and they could be
explained with the relative position of the MLD and nitracline. The first one
is characterized by an early winter bloom onset and the absence of
a chlorophyll peak in March. It was observed when circulation was anticyclonic
or when winter MLD was relatively shallow. Dominant regenerated production
all year and an absence of significant nutrient supplies to surface
waters are proposed to explain this trophic regime. Conversely, the second
trophic regime is marked by a bloom onset in late winter (i.e., February) and
a chlorophyll peak in March. The chlorophyll increase was interpreted as a
direct response to the nutrient enrichment of surface waters. This winter–spring
bloom was observed when circulation was cyclonic and when winter mixing was
relatively strong.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p id="d1e139">Phytoplankton phenology aims to analyze periodic events in phytoplankton
seasonal cycles, such as blooms (Ji et al., 2010). Phytoplankton blooms are
crucial events in the ocean as they contribute significantly to primary
production and carbon export, (Buesseler, 1998) but also sustain the trophic
food web. Thus, any changes in phytoplankton phenology may have large
consequences on higher trophic levels (Edwards and Richardson, 2004; Koeller
et al., 2009). Although the characterization of phytoplankton phenology in
the open ocean has long been hindered by data scarcity, in the past few
years, satellite ocean color observations have offered a general view of the
phenology of the surface<?pagebreak page4432?> phytoplankton biomass at global scale (Platt et al.,
2010). Satellite-based studies have mainly attempted to describe
phytoplankton blooms (Yoder and Kennelly, 1993;
Racault et al., 2012; Winder and
Cloern, 2010) but have also tried to explain their spatiotemporal
variability. The mixed layer depth (MLD) is recognized to be one of the main
factors influencing phytoplankton phenology as it controls both light and
nutrient availability for phytoplankton growth (Mann and Lazier, 2006).
Numerous studies have attempted to explain variability in phytoplankton
phenology with MLD (Lavigne et al., 2013; Henson et al., 2006; Zhai et al.,
2011) or with factors influencing it (Follows and Dutkiewicz, 2001; Ji et
al., 2008). These studies have shown that, generally, a deeper winter mixing
results in a delayed and stronger bloom in subtropical regions but in a
weaker bloom in subpolar regions. Nevertheless, in most cases, MLD has failed
to explain the overall phytoplankton variability, suggesting that all the
factors that impact phytoplankton phenology are still not known.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p id="d1e144">Study area <bold>(a)</bold> and schematic representation of the north
Ionian gyre upper-layer circulation during anticyclonic <bold>(b)</bold> and
cyclonic <bold>(c)</bold> regimes. AW, LSW and LIW refer to Atlantic Water,
Levantine Surface Water and Levantine Intermediate Water, respectively. See
text for a definition of regions S1, S2 (Sect. 2.1) and S3 (Sect. 3.2).
The underlying maps represent the 1995 <bold>(b)</bold> and 1999 <bold>(c)</bold> average absolute
dynamic topography.</p></caption>
        <?xmltex \igopts{width=298.753937pt}?><graphic xlink:href="https://bg.copernicus.org/articles/15/4431/2018/bg-15-4431-2018-f01.jpg"/>

      </fig>

      <p id="d1e168">In oligotrophic environments where nutrients are the primary factor
controlling phytoplankton growth, changes in the subsurface distribution of
nutrients should also affect phytoplankton phenology. Nutrient distribution
is controlled by the interplay between biogeochemical and physical processes
and external sources (Williams and Follows, 2003). Among the physical
processes, oceanic circulation, which at global scale contributes to the
transport of nutrients, can also regionally uplift or depress the nutricline
and modify nutrient concentrations through cyclonic and anticyclonic
circulation patterns (Williams and Follows, 2003). At basin scale, the
trophic status of subtropical (subpolar) gyres is determined by anticyclonic
(cyclonic) circulation, which controls the depth of the nutricline. At
smaller scales, observations and modeling experiments have demonstrated that
the formation of cyclonic eddies causes the upwelling of the nutricline just
above the base of the productive layer, resulting in an increase in
primary production in subsurface waters (McGillicuddy et al., 1998; Falkowski
et al., 1991; Salihoglu et al., 1990). These observations were confirmed by a
statistical analysis carried out in the Costa Rica Dome area (Kahru et al.,
2007). In fact, the authors revealed a strong coupling between the sea level
anomaly (SLA) and the chlorophyll anomaly with positive chlorophyll anomalies
associated with negative SLA. Regarding phytoplankton phenology, little is
known about the impact of the cyclonic–anticyclonic circulation on it. To our
knowledge, only two recent analyses have dealt with this point. A modeling
analysis demonstrated that in long-lived cyclonic eddies of the Kuroshio
current (lifetime greater than 1 year), the spring phytoplankton bloom is
reinforced thanks to a larger nutrient supply associated with vertical mixing
(Sasai et al., 2010). In the northwestern Mediterranean Sea, D'Ortenzio et
al. (2014), using Bio-Argo data, suggested that large-scale cyclonic
circulation could be the first forcing factor of the phytoplankton bloom and
demonstrated that deep winter convection is not essential for bloom
development. To further investigate the influence of the upwelling (downwelling)
of the nutricline on the phytoplankton seasonal cycle, we present an analysis
of the phytoplankton phenology during the cyclonic and anticyclonic phases of
the north Ionian gyre (NIG; see Fig. 1). Thus, our aim is to determine
whether and how changes in cyclonic–anticyclonic circulation can affect
interannual variability in phytoplankton phenology.</p>
      <p id="d1e171">The north Ionian Sea has been selected as the study area because this region of
the eastern Mediterranean Sea has the specificity to experience reversals of
its surface circulation at a decadal timescale (Gačić et al., 2010). More
specifically, due to the feedback with the Adriatic Sea (see below), the
north Ionian circulation oscillates between cyclonic and the anticyclonic
modes (Fig. 1b and c). Variations in horizontal circulation patterns have
been detected mainly from altimetric measurements, while the vertical
structure of the Ionian circulation has been inferred only recently using
float and oceanographic campaign data (Gačić et al., 2014). It has been shown
that the Ionian behaves as a two-layer fluid and that the decadal inversions
of the NIG are generated by the spreading of the dense water formed in the
Adriatic (AdDW). During the Eastern Mediterranean Transient in the early
1990s, a large amount of dense water of Aegean origin (about 3 Sv)
contributed both to reinforcing the anticyclonic circulation and generating
the reversal (Borzelli et al., 2009). Dense water of interannually varying
density changes the horizontal pressure gradient in the lower layer,
affecting the horizontal circulation over the entire water column. The
mechanism at the base of the decadal reversal of the circulation regime was
called Adriatic–Ionian bimodal oscillating system (BiOS; Gačić et al.,
2010). From a limited number of nitrate vertical profiles, Civitarese et
al. (2010) showed that NIG circulation reversals influence north Ionian
biogeochemistry, especially the depth of the nitracline. However, the
impact on phytoplankton remained unclear. Comparing surface chlorophyll <inline-formula><mml:math id="M1" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>
measured by the CZCS (Coastal Zone Color Scanner; 1979–1985) and SeaWiFS
(Sea-viewing Wide Field-of-view Sensor; 1997–2000),
D'Ortenzio et al. (2003) observed just a slight difference in the timing of
main bloom events and, during the SeaWiFS period, a recurrent and large patch
of [Chl <inline-formula><mml:math id="M2" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]. More recently, Mayot et al. (2016) studied interannual
variability in phytoplankton phenology in the Mediterranean Sea. The authors
showed that phytoplankton phenology is extremely dynamic in the north Ionian
Sea with significant changes in the annual cycle of surface chlorophyll <inline-formula><mml:math id="M3" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>
concentration from year to year. However, they did not investigate the
potential causes of this interannual variability. The present analysis
attempts to reconsider the impact of NIG circulation on phytoplankton
phenology focusing on the satellite chlorophyll <inline-formula><mml:math id="M4" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> concentration (hereafter
[Chl <inline-formula><mml:math id="M5" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]) phenology and analyzing the 1998–2012 period.</p>
      <p id="d1e210">In Sect. 2, all the datasets used and the related methods are presented.
Subsequently, the temporal variability of the NIG circulation is analyzed and
then the uplift (depression) of isopycnals and the nitracline during the<?pagebreak page4433?> cyclonic
(anticyclonic) regime is discussed. From the analysis of phenological
metrics, differences are sought between cyclonic and anticyclonic regimes in
[Chl <inline-formula><mml:math id="M6" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] phenology. Phenological metrics are used here because they provide
a synthetic method to highlight specific features of the [Chl <inline-formula><mml:math id="M7" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] annual
time series. These metrics are also demonstrated to be extremely informative over
various environments and regions (Follows and Dutkiewicz, 2001;
Henson et al., 2009; Lavigne et al., 2013) despite the fact that they can be
affected by data gaps (Cole et al., 2012) and noise (Ji et al., 2010).
Focusing then on the start dates of [Chl <inline-formula><mml:math id="M8" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] increase, the impacts of
interannual variability in the north Ionian circulation and winter buoyancy
fluxes are compared and discussed. Finally, hypotheses about causes and
consequences of the observed patterns in [Chl <inline-formula><mml:math id="M9" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] phenology are proposed.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p id="d1e243"><bold>(a)</bold> Dotted line is the ADT difference between regions S1 and
S2 (S1 <inline-formula><mml:math id="M10" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> S2; see Fig. 1b). Annual periods used for the phenology
analysis, which range from July of year <inline-formula><mml:math id="M11" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula> to June of year <inline-formula><mml:math id="M12" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>, are featured
as white and grey bands. For each of them, black diamonds and grey circles
represent the averaged ADT difference during the periods October to March (also
named ICI) and July to June, respectively. The zero level differentiates
cyclonic (negative values) and anticyclonic (positive values) regimes.
Panels <bold>(b)</bold> to <bold>(f)</bold> represent the average ADT pattern for different periods.
Squares represent the regions S1 (south) and S2 (north).</p></caption>
        <?xmltex \igopts{width=312.980315pt}?><graphic xlink:href="https://bg.copernicus.org/articles/15/4431/2018/bg-15-4431-2018-f02.pdf"/>

      </fig>

</sec>
<sec id="Ch1.S2">
  <title>Data and methods</title>
<sec id="Ch1.S2.SS1">
  <title>Satellite and modeling data</title>
      <?pagebreak page4434?><p id="d1e297">Daily [Chl <inline-formula><mml:math id="M13" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] products with a 4 km resolution delivered by the Ocean
Colour Climate Change Initiative (OC_CCI) project version 1.0
(<uri>http://www.esa-oceancolour-cci.org/</uri>, last access:
January 2016) were used. The OC_CCI dataset,
which covers the period September 1997 to July 2012, was created by
band-shifting and bias-correcting MERIS and MODIS data to match SeaWiFS data
and by merging the datasets with a simple average (Storm et al., 2013). Daily
data were merged to obtain 8-day resolution maps. During the period from 1997
to March 2002 (only the SeaWiFS sensor available), the 8-day average map time
series contains only 80 % good data, but from April 2002 more than
96 % good data were available. To fill the gaps, a linear interpolation
was applied to each time series. Then, the time series were smoothed with a
three-point median filter. OC_CCI [Chl <inline-formula><mml:math id="M14" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] products are processed with the
algorithm OC4v6, which has been fitted on a global dataset (O'Reilly et al.,
2000). It has been demonstrated that this algorithm overestimates by a factor
close to 2 [Chl <inline-formula><mml:math id="M15" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] in oligotrophic conditions
([Chl <inline-formula><mml:math id="M16" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] <inline-formula><mml:math id="M17" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.4 mg m<inline-formula><mml:math id="M18" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and alternative algorithms have been
developed for the Mediterranean Sea (Bricaud et al., 2002; Volpe et al.,
2007). However, as for OC4, Mediterranean algorithms are based on the
blue–green reflectance band ratio model: [Chl <inline-formula><mml:math id="M19" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] increases with a decrease
in the blue–green band ratio. Hence, similar patterns in [Chl <inline-formula><mml:math id="M20" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] variations
are obtained with each class of algorithms. As the present study focuses
only on the intercomparison of [Chl <inline-formula><mml:math id="M21" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] patterns in the Ionian Sea, the
utilization of the global algorithm is valid. In addition, it allows for
comparison with reference papers on Mediterranean phytoplankton phenology
(D'Ortenzio and Ribera d'Alcalà, 2009; Mayot et al., 2016), which are also based on global
[Chl <inline-formula><mml:math id="M22" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] products.</p>
      <p id="d1e379">The SSALTO–Duacs delayed-time maps of the absolute dynamic topography (ADT)
(Rio et al., 2007) for the Mediterranean Sea (<inline-formula><mml:math id="M23" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">8</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M24" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) computed and
distributed by AVISO (<uri>http://www.aviso.altimetry.fr/</uri>,
last access: January 2016) were downloaded
for the period 1993–2014. As proposed by Gačić et al. (2014), the sea level
gradient between the north and the center of the NIG was used to determine
the cyclonic–anticyclonic nature of the NIG circulation. In practice, the ADT
difference between rectangles S2 (18.75–19.25<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E and
39.5–40<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N; see Fig. 1b) and S1 (18.5–19<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E and
37.5–38<inline-formula><mml:math id="M28" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W; see Fig. 1b) was computed. Then, the daily time series
was smoothed with a 30-day moving average filter (dotted line Fig. 2a). As
the anticyclonic (cyclonic) circulation regime is characterized by a doming
(depression) of sea level, it is characterized by a positive (negative) ADT
difference value.</p>
      <p id="d1e442">Net air–sea heat fluxes of longwave radiation and shortwave radiation,
sensible heat flux, latent heat flux and precipitation were obtained from
the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim
reanalysis (Dee et al., 2011). Data were available at 6 h intervals and
downloaded at 0.5<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> resolution. Then, daily averages were computed and
the net heat flux was calculated as the sum of the four air–sea flux
components. The surface buoyancy flux per unit area was computed according to
Anderson et al. (1996), with coefficients proposed by Gačić et al. (2002) for
the Mediterranean Sea. Total winter buoyancy losses were then calculated as
the time integral for the period from 21 December to 20 March.</p>
      <p id="d1e454">Daily temperature and salinity profiles for the product
MEDSEA_REANALYSIS_PHY_006_004 produced by the Mediterranean
Forecasting System and delivered<?pagebreak page4435?> by the CMEMS
(<uri>http://marine.copernicus.eu</uri>, last access: June 2016) were used to derive the depth of the 28.9 kg m<inline-formula><mml:math id="M30" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
isopycnal and MLD for the time range 1993–2012.
The MEDSEA_REANALYSIS_PHY_006_004 product results from a hydrodynamic
model supplied by the Nucleus for European Modelling of the Ocean (NEMO),
with a variational data assimilation scheme for temperature and salinity
vertical profiles and satellite sea level anomaly along-track data. The model
horizontal grid resolution is <inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">16</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M32" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> and there are 72 unevenly spaced
vertical levels. An evaluation of the product performance showed that
temperature and salinity present an RMS of 0.34<inline-formula><mml:math id="M33" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> and 0.1 psu,
respectively, on average in the water column (Fratianni et al., 2016).</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>In situ data</title>
      <p id="d1e507">A total of 71 243 temperature and salinity profiles (52 % from Argo floats) were
collected from the Coriolis web portal (<uri>http://www.coriolis.eu.org/</uri>,
last access: October 2015) during the period
1990 from 2012 in the region between 36–40<inline-formula><mml:math id="M34" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and
16–21<inline-formula><mml:math id="M35" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E. Only the best quality (Coriolis sensu) data were
retained. Then, potential density profiles were calculated and the depth of
the 28.9 kg m<inline-formula><mml:math id="M36" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> isopycnal was determined.</p>
      <p id="d1e543">Nitrate concentration, temperature and salinity profiles from oceanographic
cruises in the area of interest (36–40<inline-formula><mml:math id="M37" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 17–22<inline-formula><mml:math id="M38" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) were
obtained: POEM-BC-O91 (October 1991, 55 profiles), POEM-BC-A62
(April–May 1992, 40 profiles) and EMTEC (April–May 1999, 20 profiles). From
nitrate concentration profiles, the nitracline depth was estimated as the
depth of the 1 <inline-formula><mml:math id="M39" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>M isoline (Cermeño et al., 2008; Lavigne et al.,
2013; Pasqueron de Fommervault et al., 2015) and compared to the depth of
the 28.9 kg m<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> isopycnals (Fig. 3c). The 28.9 kg m<inline-formula><mml:math id="M41" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> isopycnal was
chosen here because it is located within the transition layer between the
Atlantic Waters (AWs; density ranging between 27.4 and 28.6 kg m<inline-formula><mml:math id="M42" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>),
which are generally nutrient depleted, and the Levantine Intermediate Waters
(LIWs; density ranging between 29.0 and 29.1 kg m<inline-formula><mml:math id="M43" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) in which nutrients
accumulate (Malanotte-Rizzoli et al., 1997; Ribera d'Alcalà et al.,
2003). Although it was demonstrated that phytoplankton growth is co-limited
by nitrate and phosphate in the eastern Mediterranean Sea (Psarra et al.,
2005; Thingstad et al., 2005), only nitrate dynamics are considered here as
both elements covary and control phytoplankton growth (Ribera
d'Alcalà et al., 2003) and since the quality of phosphate data in the database
was not good enough for such analyses.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3"><caption><p id="d1e622">Climatological maps of the estimation of the depth of the isopycnal
28.9 kg m<inline-formula><mml:math id="M44" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for cyclonic <bold>(a)</bold> and anticyclonic <bold>(b)</bold> regimes.
Data were spatially interpolated with kriging, and black dots indicate in situ
data used for kriging. Relationship between the depth of the nitracline and
the depth of the isopycnal 28.9 kg m<inline-formula><mml:math id="M45" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in the north Ionian Sea <bold>(c)</bold>
from in situ data collected during three oceanographic cruises (see colors).</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://bg.copernicus.org/articles/15/4431/2018/bg-15-4431-2018-f03.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S2.SS3">
  <title>Phenological metrics</title>
      <p id="d1e670">A set of phenological metrics has been computed from each annual [Chl <inline-formula><mml:math id="M46" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]
remotely sensed time series. Annual time series were defined from July of
year <inline-formula><mml:math id="M47" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula> to June of year <inline-formula><mml:math id="M48" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> in order to better display the
winter-to-spring transition. For each pixel, 14 annual time series could be
defined ranging from July 1998 to June 2012. Hereafter, the annual time
series are referred to as year <inline-formula><mml:math id="M49" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> (e.g., 2000 for the annual time series
1999–2000).</p>
      <p id="d1e711">Phenological metrics were defined to describe the main characteristics of the
phytoplankton annual cycle. They were selected to focus on the [Chl <inline-formula><mml:math id="M50" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]
content and on the date of the main growing period. The metrics CHL_Year,
CHL_March and CHL_Max refer to the yearly average [Chl <inline-formula><mml:math id="M51" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>], the March
average [Chl <inline-formula><mml:math id="M52" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] and the [Chl <inline-formula><mml:math id="M53" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] annual maximum, respectively.
CHL_March has been defined here because previous studies demonstrated that
the Mediterranean Sea trophic situation is highly variable in March,
spatially and interannually ranging from oligotrophy to bloom conditions
(D'Ortenzio et al., 2009, 2003; Mayot et al., 2016). The
bloom onset was defined as the date of the maximum growth rate. The date of
the maximum growth rate represents an objective and efficient way to
determine the bloom onset date, although the methodology can be affected by data
noise and then requires an efficient smoothing of the time series (Brody et
al., 2013). The 8-day annual time series were twice filtered with running
means using a three-point window, which decreases small-scale noise without
strongly degrading the main pattern of the [Chl <inline-formula><mml:math id="M54" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] annual time series.
Then, the middle date of the 8-day interval corresponding to the maximum
[Chl <inline-formula><mml:math id="M55" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] increase<?pagebreak page4436?> was defined as Date_GR_Max. Finally, the metric
indicating the date of maximum [Chl <inline-formula><mml:math id="M56" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] is referred to in the following as
Date_Max.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><caption><p id="d1e766">Hovmöller diagram of the 8-day satellite [Chl <inline-formula><mml:math id="M57" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] along the
18.5<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E meridian (see vertical line in Fig. 1a). [Chl <inline-formula><mml:math id="M59" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] is
expressed in mg m<inline-formula><mml:math id="M60" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Solid lines indicate 1-year periods (January to
December) and dotted lines 3-month periods.</p></caption>
          <?xmltex \igopts{width=312.980315pt}?><graphic xlink:href="https://bg.copernicus.org/articles/15/4431/2018/bg-15-4431-2018-f04.pdf"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results and discussion</title>
<sec id="Ch1.S3.SS1">
  <title>Physical and chemical characterization of the NIG</title>
      <p id="d1e822">The time series of ADT difference between regions S1 and S2 (Fig. 1b) shows
decadal and seasonal variability (Fig. 2). Globally, a first anticyclonic
phase is evidenced from altimetry data (positive ADT difference) in
1992–1997 (Fig. 2a). The anticyclonic phase is then followed by a cyclonic
period (negative ADT difference) from 1998 through 2005. Then, a shorter
anticyclonic period took place between 2006 and 2010. In 2012, the
circulation was again cyclonic. To determine the average circulation state
during each bloom, the ADT difference values were averaged for a period
ranging from October to March, which largely covers the annual [Chl <inline-formula><mml:math id="M61" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]
increase (see Fig. 4). The resulting values (grey circles on Fig. 2a) are
referred to as the ICI (Ionian circulation index) in the following. Although the ICI
shows an interannual variability similar to the annual averages (July to
June, black diamonds in Fig. 2a), the differences with respect to yearly
means suggest that it is affected by a seasonal signal that has to be
considered for the determination of the circulation regime during
transitional phases (i.e., when ADT differences are close to zero). During
these phases, the October–March ADT maps (Fig. 2, panels b to f) were also
investigated since the impact of small-scale structures on the ADT
difference criteria could be substantial. From 2005 to 2006, the circulation
turned from cyclonic to anticyclonic. In Fig. 2b, the north of the Ionian
domain is dominated by negative ADT values, and in the 34–36<inline-formula><mml:math id="M62" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N
band, a clear front representing the mid-Ionian jet is observed. These
patterns indicate a cyclonic circulation. In 2006 (Fig. 2c), high ADT values
extend northward and the lowest ADT values are pushed along the Italian and Greek
coasts. This pattern represents the transition towards an anticyclonic
regime, which is characterized by a higher ADT value in the center of the
north Ionian basin than at its periphery. From Fig. 2d to f, the transition
from an anticyclonic (Fig. 2d) to a cyclonic (Fig. 2f) circulation regime is
represented. Indeed, similarly to Fig. 2c, in Fig. 2d a tongue with higher
ADT values extends northward from the mid-Ionian jet to the center of the
NIG. Finally, the analysis of the ICI time series and the examination
of selected ADT brought us to the conclusion that from July 1998 to June 2005
and from July 2011 to June 2012, NIG circulation can be considered as
cyclonic and that the periods 1993–1997 and July 2007–June 2010 are clearly
dominated by the anticyclonic regime. No definite circulation regime can be
attributed to the years 2006 and 2011 as they correspond to transitional
phases.</p>
      <p id="d1e841"><?xmltex \hack{\newpage}?>In the Coriolis database, 26 318 potential density profiles were available
to describe the anticyclonic situation (data collected between 1990 and 1996
and between 2006 and 2009) and 34 753 to describe the cyclonic situation
(data collected between 1998 and 2005 and between 2011 and 2012). Optimal
interpolation applied to each dataset provides an estimation of the depth of
the isopycnal 28.9 kg m<inline-formula><mml:math id="M63" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for cyclonic and anticyclonic regimes
(Fig. 3a and b, respectively). The resulting maps exhibit very different
features. In the cyclonic pattern (Fig. 3a), the depth of the isopycnal
28.9 kg m<inline-formula><mml:math id="M64" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> ranges between 40 and 120 m north of 37<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N.
South of 37<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, a steep gradient, implying isopycnal southward
deepening, is observed consistently with the position of the mid-Ionian jet, which
is reinforced during the cyclonic regime of the NIG (Bessieres et al., 2013;
Gačić et al., 2014). The shallowest isopycnals are located around
39<inline-formula><mml:math id="M67" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and 18<inline-formula><mml:math id="M68" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, offshore of the Italian coast,
representing the center of the cyclone. During the anticyclonic phase, the
isopycnal 28.9 kg m<inline-formula><mml:math id="M69" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> is very deep (240 m) in the center of the Ionian
Sea and is shallower at the border of the basin. This isopycnal depth pattern
is consistent with an anticyclonic circulation.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p id="d1e920">(Column <bold>a</bold>) Interannual average values (1998–2012) of phenological
metrics. CHL_Year, CHL_March and CHL_Max are expressed in mg m<inline-formula><mml:math id="M70" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Columns <bold>(b)</bold> and <bold>(c)</bold> show the anomaly of metrics compared to the
interannual average for the cyclonic (column <bold>b</bold>) and anticyclonic
(column <bold>c</bold>) periods. They are expressed in percent difference for CHL_Year,
CHL_March and CHL_Max and in days for Date_Max and
Date_GR_Max. Solid black lines refer to areas with significant
differences between cyclonic and anticyclonic patterns (<inline-formula><mml:math id="M71" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value <inline-formula><mml:math id="M72" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.05).</p></caption>
          <?xmltex \igopts{width=384.112205pt}?><graphic xlink:href="https://bg.copernicus.org/articles/15/4431/2018/bg-15-4431-2018-f05.jpg"/>

        </fig>

      <p id="d1e971">As previously demonstrated for the global ocean (While and Haine, 2010; Omand
and Mahadevan, 2013), the depth of an isopycnal can be representative of the
nitracline depth in the case of a stratified water column. This is confirmed in the
north Ionian from the obtained linear relationship between the depth of the
nitracline and the 28.9 kg m<inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> isopycnal (Fig. 3c, <inline-formula><mml:math id="M74" display="inline"><mml:mrow><mml:msup><mml:mi>r</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.93</mml:mn></mml:mrow></mml:math></inline-formula>). The
data used here were collected in different seasons (i.e., in October 1991 and
April–May 1992 and 1999) but always during the long period during which the
water column is stratified. As soon as vertical mixing reaches the nitracline
depth, this relationship is no longer valid. Nevertheless, such events are
rare and short in the north Ionian Sea. By applying this relationship, it
appears that in the center of the north Ionian, the nitracline depth ranges
between 60 and 80 m during the cyclonic regime, whereas it reaches 150 m
when the NIG is anticyclonic. Considering that this nitracline depth range
(i.e., 60 to 150 m) overlaps climatological values of winter MLDs in the
Ionian Sea (i.e., 80–130 m; D'Ortenzio et al., 2005; Houpert et al., 2015),
changes in NIG circulation should have a significant impact on the entrainment
of nutrients to the surface layer by mixing and consequently on
phytoplankton growth and primary production.</p>
</sec>
<sec id="Ch1.S3.SS2">
  <title>General patterns of phytoplankton phenology in the Ionian Sea</title>
      <?pagebreak page4437?><p id="d1e1007">Phytoplankton phenology in the Ionian Sea is typical of very oligotrophic
regions with low [Chl <inline-formula><mml:math id="M75" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] (values range between 0.05 and 0.5 mg m<inline-formula><mml:math id="M76" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
in open waters) and a seasonal cycle characterized by very low [Chl <inline-formula><mml:math id="M77" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]
values during summer and higher values during winter (Fig. 4; D'Ortenzio and
Ribera d'Alcalà, 2009). The highest [Chl <inline-formula><mml:math id="M78" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] values are observed along
the coast, especially along the southern Italian coast where local upwelling
can take place (D'Ortenzio et al., 2003). Offshore, a north–south gradient is
observed (Figs. 4 and 5a) with higher values in the northern part of the
basin (above 38<inline-formula><mml:math id="M79" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N). In the whole basin, the lowest [Chl <inline-formula><mml:math id="M80" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] values are
observed in midsummer, then [Chl <inline-formula><mml:math id="M81" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] increases starting in October
(Fig. 4). Date_GR_Max occurs later, in December for the central Ionian
Sea and in mid-January for the north Ionian and for the Italian coastal
region (Fig. 5). Spatial variability in the Date_GR_Max indicates that
differences in [Chl <inline-formula><mml:math id="M82" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] phenology should exist between the northern and
southern parts of the basin. This is confirmed by the analysis of the
seasonal [Chl <inline-formula><mml:math id="M83" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] pattern in the Hovmöller diagram (Fig. 4). Indeed,
during some winters, for example 1999, 2000, 2003 and 2005, there is a
distinct local maximum in [Chl <inline-formula><mml:math id="M84" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] generally centered in March. These March
peaks are situated in the 38–39<inline-formula><mml:math id="M85" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N band and are never observed
below 37<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N. However, they are not observed in all situations and,
for instance, no [Chl <inline-formula><mml:math id="M87" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] peak appears in March 2001, 2007 or 2008. This
special feature of the [Chl <inline-formula><mml:math id="M88" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] seasonal cycle is related to the location of
the isopycnal doming area during a cyclonic regime (Fig. 3a), suggesting that
interannual variability in [Chl <inline-formula><mml:math id="M89" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] patterns in this region may be related
to the NIG circulation pattern.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p id="d1e1131">Average Ionian circulation index (ICI; ADT difference values between
regions S1 and S2 averaged over October–March), winter buoyancy fluxes (WBFs)
and phenological metrics in the region S3. ICI is expressed in centimeters and WBFs are
expressed in percent relative difference compared to the 1999–2012
interannual average. CHL_Year (yearly average [Chl <inline-formula><mml:math id="M90" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]), CHL_March
(March average [Chl <inline-formula><mml:math id="M91" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]) and CHL_Max (annual maximum [Chl <inline-formula><mml:math id="M92" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]) are
expressed in mg m<inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Numbers in brackets are standard deviations. For
Date_Max (date of annual maximum [Chl <inline-formula><mml:math id="M94" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]) and Date_GR_Max (date of
maximum growth rate in [Chl <inline-formula><mml:math id="M95" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]), standard deviations are expressed in days.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="9">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="left"/>
     <oasis:colspec colnum="9" colname="col9" align="left"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Year</oasis:entry>
         <oasis:entry colname="col2">Regime</oasis:entry>
         <oasis:entry colname="col3">ICI</oasis:entry>
         <oasis:entry colname="col4">WBF</oasis:entry>
         <oasis:entry colname="col5">CHL_Year</oasis:entry>
         <oasis:entry colname="col6">CHL_March</oasis:entry>
         <oasis:entry colname="col7">CHL_Max</oasis:entry>
         <oasis:entry colname="col8">Date_Max</oasis:entry>
         <oasis:entry colname="col9">Date_GR_Max</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">1999</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M96" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>3.522</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M97" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>7.7 (2.9)</oasis:entry>
         <oasis:entry colname="col5">0.19 (0.011)</oasis:entry>
         <oasis:entry colname="col6">0.36 (0.07)</oasis:entry>
         <oasis:entry colname="col7">0.45 (0.12)</oasis:entry>
         <oasis:entry colname="col8">16 Mar (37)</oasis:entry>
         <oasis:entry colname="col9">4 Mar (39)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2000</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M98" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>4.186</oasis:entry>
         <oasis:entry colname="col4">26.2 (3.2)</oasis:entry>
         <oasis:entry colname="col5">0.18 (0.008)</oasis:entry>
         <oasis:entry colname="col6">0.30 (0.04)</oasis:entry>
         <oasis:entry colname="col7">0.46 (0.16)</oasis:entry>
         <oasis:entry colname="col8">2 Apr (29)</oasis:entry>
         <oasis:entry colname="col9">12 Mar (38)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2001</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M99" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>1.826</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M100" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>23.8 (0.8)</oasis:entry>
         <oasis:entry colname="col5">0.15 (0.008)</oasis:entry>
         <oasis:entry colname="col6">0.17 (0.01)</oasis:entry>
         <oasis:entry colname="col7">0.29 (0.03)</oasis:entry>
         <oasis:entry colname="col8">19 Jan (34)</oasis:entry>
         <oasis:entry colname="col9">30 Dec (28)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2002</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M101" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>2.905</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M102" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.9 (0.6)</oasis:entry>
         <oasis:entry colname="col5">0.17 (0.011)</oasis:entry>
         <oasis:entry colname="col6">0.26 (0.03)</oasis:entry>
         <oasis:entry colname="col7">0.33 (0.05)</oasis:entry>
         <oasis:entry colname="col8">28 Feb (14)</oasis:entry>
         <oasis:entry colname="col9">31 Jan (41)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2003</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M103" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>3.966</oasis:entry>
         <oasis:entry colname="col4">5.3 (0.6)</oasis:entry>
         <oasis:entry colname="col5">0.17 (0.008)</oasis:entry>
         <oasis:entry colname="col6">0.26 (0.03)</oasis:entry>
         <oasis:entry colname="col7">0.39 (0.06)</oasis:entry>
         <oasis:entry colname="col8">2 Apr (2)</oasis:entry>
         <oasis:entry colname="col9">20 Mar (15)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2004</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M104" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>2.395</oasis:entry>
         <oasis:entry colname="col4">15.2 (2.2)</oasis:entry>
         <oasis:entry colname="col5">0.17 (0.008)</oasis:entry>
         <oasis:entry colname="col6">0.34 (0.04)</oasis:entry>
         <oasis:entry colname="col7">0.46 (0.10)</oasis:entry>
         <oasis:entry colname="col8">24 Mar (6)</oasis:entry>
         <oasis:entry colname="col9">20 Mar (6)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2005</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M105" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>1.281</oasis:entry>
         <oasis:entry colname="col4">42.2 (3.1)</oasis:entry>
         <oasis:entry colname="col5">0.18 (0.013)</oasis:entry>
         <oasis:entry colname="col6">0.44 (0.06)</oasis:entry>
         <oasis:entry colname="col7">0.90 (0.19)</oasis:entry>
         <oasis:entry colname="col8">24 Mar (2)</oasis:entry>
         <oasis:entry colname="col9">20 Mar (3)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2006</oasis:entry>
         <oasis:entry colname="col2">Transition</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M106" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>2.49</oasis:entry>
         <oasis:entry colname="col4">6.2 (1.8)</oasis:entry>
         <oasis:entry colname="col5">0.17 (0.014)</oasis:entry>
         <oasis:entry colname="col6">0.28 (0.03)</oasis:entry>
         <oasis:entry colname="col7">0.34 (0.06)</oasis:entry>
         <oasis:entry colname="col8">8 Mar (22)</oasis:entry>
         <oasis:entry colname="col9">31 Jan (31)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2007</oasis:entry>
         <oasis:entry colname="col2">Anticyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M107" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>7.5</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M108" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>17.3 (2.0)</oasis:entry>
         <oasis:entry colname="col5">0.14 (0.019)</oasis:entry>
         <oasis:entry colname="col6">0.20 (0.03)</oasis:entry>
         <oasis:entry colname="col7">0.24 (0.04)</oasis:entry>
         <oasis:entry colname="col8">20 Feb (26)</oasis:entry>
         <oasis:entry colname="col9">20 Nov (39)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2008</oasis:entry>
         <oasis:entry colname="col2">Anticyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M109" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>5.53</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M110" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>23.9 (2.5)</oasis:entry>
         <oasis:entry colname="col5">0.16 (0.024)</oasis:entry>
         <oasis:entry colname="col6">0.20 (0.08)</oasis:entry>
         <oasis:entry colname="col7">0.32 (0.09)</oasis:entry>
         <oasis:entry colname="col8">19 Jan (28)</oasis:entry>
         <oasis:entry colname="col9">30 Dec (47)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2009</oasis:entry>
         <oasis:entry colname="col2">Anticyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M111" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>2.73</oasis:entry>
         <oasis:entry colname="col4">12.4 (2.9)</oasis:entry>
         <oasis:entry colname="col5">0.16 (0.019)</oasis:entry>
         <oasis:entry colname="col6">0.20 (0.02)</oasis:entry>
         <oasis:entry colname="col7">0.36 (0.08)</oasis:entry>
         <oasis:entry colname="col8">4 Feb (11)</oasis:entry>
         <oasis:entry colname="col9">6 Dec (18)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2010</oasis:entry>
         <oasis:entry colname="col2">Anticyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M112" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>0.75</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M113" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>18.1 (3.2)</oasis:entry>
         <oasis:entry colname="col5">0.19 (0.025)</oasis:entry>
         <oasis:entry colname="col6">0.25 (0.03)</oasis:entry>
         <oasis:entry colname="col7">0.36 (0.08)</oasis:entry>
         <oasis:entry colname="col8">11 Jan (11)</oasis:entry>
         <oasis:entry colname="col9">14 Dec (26)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2011</oasis:entry>
         <oasis:entry colname="col2">Transition</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M114" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>0.28</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M115" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>26.3 (2.9)</oasis:entry>
         <oasis:entry colname="col5">0.18 (0.015)</oasis:entry>
         <oasis:entry colname="col6">0.22 (0.02)</oasis:entry>
         <oasis:entry colname="col7">0.33 (0.07)</oasis:entry>
         <oasis:entry colname="col8">18 Dec (17)</oasis:entry>
         <oasis:entry colname="col9">12 Nov (22)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2012</oasis:entry>
         <oasis:entry colname="col2">Cyclonic</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M116" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>3.795</oasis:entry>
         <oasis:entry colname="col4">44.6 (3.8)</oasis:entry>
         <oasis:entry colname="col5">0.16 (0.010)</oasis:entry>
         <oasis:entry colname="col6">0.35 (0.07)</oasis:entry>
         <oasis:entry colname="col7">0.46 (0.13)</oasis:entry>
         <oasis:entry colname="col8">24 Mar (6)</oasis:entry>
         <oasis:entry colname="col9">3 Dec (2)</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S3.SS3">
  <?xmltex \opttitle{Impact of the NIG circulation on the {[}Chl $a${]} phenology}?><title>Impact of the NIG circulation on the [Chl <inline-formula><mml:math id="M117" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] phenology</title>
      <p id="d1e1820">Figure 5 displays the July 1998–June 2012 average of phenological metrics
(left panels) and the anomalies for the cyclonic (1999–2005 and
2012) and the anticyclonic (2007–2010) regimes compared to the interannual
average. Regarding [Chl <inline-formula><mml:math id="M118" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] content, no significant difference is observed
for the annually averaged [Chl <inline-formula><mml:math id="M119" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] content (i.e., CHL_Year), with a
relative difference ranging between <inline-formula><mml:math id="M120" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>10 and <inline-formula><mml:math id="M121" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>10 %. During the
anticyclonic regime, a small positive anomaly is generally observed along the
coast, while central Ionian displays negative anomalies (Fig. 5c). When March
only is considered, the CHL_March displays much stronger differences
between cyclonic and anticyclonic regimes (panels e and f). Significant
differences are observed in the center of the north Ionian Sea with a
<inline-formula><mml:math id="M122" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>15 % anomaly during the cyclonic regime and a <inline-formula><mml:math id="M123" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>20 % anomaly
during the anticyclonic regime. In the south Ionian, no major differences are
observed in March, which is in agreement with the low interannual variability
observed below 37<inline-formula><mml:math id="M124" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 4). Similarly to CHL_March, CHL_Max
shows significant differences in the central north Ionian with a positive or
a negative anomaly during cyclonic and anticyclonic regimes, respectively. In
the south Ionian, the same feature is observed due to the variability of the AW
advection modulated by the BiOS. Regarding metrics<?pagebreak page4438?> measuring the timing of
the bloom, significant differences are again observed in the center of the
north Ionian. Indeed, Date_Max and Date_GR_Max are delayed by about
20 and 30 days, respectively, when the NIG circulation is cyclonic. On the other
hand, both are early by more than 40 days when the circulation is
anticyclonic.</p>
      <?pagebreak page4439?><p id="d1e1875">The present analysis suggests that in the north Ionian, two types of
[Chl <inline-formula><mml:math id="M125" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] phenology coexist, one characterizing the cyclonic regime and the
other one characterizing the anticyclonic regime. This is also confirmed by
the analysis of annual [Chl <inline-formula><mml:math id="M126" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] cycles in the region S3
(17.5–18.5<inline-formula><mml:math id="M127" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 38–39<inline-formula><mml:math id="M128" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N; Fig. 6). We have chosen the
position in area S3 to calculate spatially averaged phenological
metrics so that they coincide with the region where the extremes of [Chl <inline-formula><mml:math id="M129" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]
anomalies occur (Fig. 5). During the anticyclonic regime (2007–2010), all
cycles show a regular increase in [Chl <inline-formula><mml:math id="M130" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] from October to the end of
January (Fig. 6, right panel). The maximum growth rate appears between late
November and late December and maximum [Chl <inline-formula><mml:math id="M131" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] between mid-January and
mid-February (Table 1). During the cyclonic regime (Fig. 6, left panel), as
for the anticyclonic one, a first increase in [Chl <inline-formula><mml:math id="M132" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] occurs in
mid-September and extends to January. In March, most of the time series
display a narrow and strong peak in [Chl <inline-formula><mml:math id="M133" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]. The annual maximum growth rate
is clearly associated with this March peak generally occurring a few days
(10 days on average) before the date of the [Chl <inline-formula><mml:math id="M134" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] maximum (Table 1).
Although the cyclonic mode is characterized by the March [Chl <inline-formula><mml:math id="M135" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] peak and
a higher amplitude of the annual [Chl <inline-formula><mml:math id="M136" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>], this does not significantly
impact the yearly average [Chl <inline-formula><mml:math id="M137" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>].</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p id="d1e1977">[Chl <inline-formula><mml:math id="M138" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] (mg m<inline-formula><mml:math id="M139" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) annual cycles for the cyclonic and
anticyclonic regimes averaged in the region S3 (see Fig. 1).</p></caption>
          <?xmltex \igopts{width=327.206693pt}?><graphic xlink:href="https://bg.copernicus.org/articles/15/4431/2018/bg-15-4431-2018-f06.pdf"/>

        </fig>

      <p id="d1e2006">Referring to the climatological analysis of the shapes of [Chl <inline-formula><mml:math id="M140" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] annual
cycles proposed by D'Ortenzio and Ribera d'Alcalà (2009), the
anticyclonic cycles (Fig. 6) are close to the so-called “no bloom” shape,
whereas most of the cyclonic cycles could be assimilated to the
“intermittent” [Chl <inline-formula><mml:math id="M141" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] annual cycle. Lavigne et al. (2013) interpreted
the “intermittent” dynamics as an intermediate state between the “no
bloom” dynamics and the typical dynamics of spring bloom as observed in the
northwestern Mediterranean Sea (Marty et al., 2002). The “no bloom” shape
was identified in areas where winter mixing rarely reaches the nitracline
depth and where light is always sufficient to support phytoplankton growth
(Lavigne et al., 2013).</p>
</sec>
<sec id="Ch1.S3.SS4">
  <title>Role of the NIG circulation patterns compared to the interannual
variability in MLD (focus on the region S3)</title>
      <p id="d1e2029">In the north Ionian where the bimodal behavior of the circulation (i.e.,
cyclonic versus anticyclonic) has a direct influence on phytoplankton
phenology (see Sect. 3.3), interannual variability also exists independently
of the BiOS switch (see Table 1 and Fig. 6). Still, focusing on the S3 area,
the interannual variability of phenological metrics is compared to
the variability of the ICI (see definition Sect. 3.1) and total winter buoyancy
losses. The total winter buoyancy losses are considered here because they
largely contribute to the formation of the mixed layer (Gill, 1982) and are
thus expected to affect bloom development (Follows and Dutkiewicz, 2001).
Regarding the cyclonic regime, the main feature in [Chl <inline-formula><mml:math id="M142" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] phenology is the
absence of a late [Chl <inline-formula><mml:math id="M143" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] peak in March 2001 and 2002 (Fig. 6, Table 1).
The years 2001 and 2002 exhibit the lowest values for CHL_March and CHL_Max
and, more importantly, the earliest dates for Date_Max and
Date_GR_Max, which occurred as early as January–February and
December–January, respectively (Table 1). This special pattern may be
explained by the buoyancy losses, which were weak: <inline-formula><mml:math id="M144" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>24 % (2001) and
<inline-formula><mml:math id="M145" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35 % (2002) compared to the reference 1999–2012 average (Table 1). In
2001 and 2002, a shallow winter MLD probably prevented significant nutrient
inputs from reaching the surface layer and consequently hindered the spring
phytoplankton bloom (see discussion below). On the other hand, in 2005 and
2012 winter buoyancy losses were particularly high (<inline-formula><mml:math id="M146" display="inline"><mml:mo lspace="0mm">+</mml:mo></mml:math></inline-formula>42, <inline-formula><mml:math id="M147" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>43 %,
respectively) and CHL_Max and CHL_March show the highest values
observed. More generally, we observed<?pagebreak page4440?> a positive Spearman correlation between
the buoyancy flux anomaly and CHL_March (correlation 0.79) or
CHL_Max (correlation 0.89), suggesting that in addition to the
circulation regime, winter buoyancy losses affect the presence and the
strength of the [Chl <inline-formula><mml:math id="M148" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>]. Regarding the anticyclonic regime and the
transitional years 2006 and 2011, a very low interannual variability is
observed: only the year 2006 (transitional regime) displays a [Chl <inline-formula><mml:math id="M149" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] peak
in early March (Table 1) that coincides with an ICI value close to 0
(transitional regime) and a weak positive anomaly in buoyancy losses
(<inline-formula><mml:math id="M150" display="inline"><mml:mo lspace="0mm">+</mml:mo></mml:math></inline-formula>6 %; Table 1). During the anticyclonic regime, no significant
correlation was found between buoyancy losses and phenological metrics. To
sum up, in the center of the north Ionian, both the circulation patterns and
air–sea exchanges would affect [Chl <inline-formula><mml:math id="M151" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] cycles. Nevertheless, it seems that
the impact of air–sea exchanges may be stronger when circulation is cyclonic
and apparently affects the amplitude of the March peak.</p>
      <p id="d1e2103">Given the general oligotrophy of the eastern Mediterranean (Ribera
d'Alcalà et al., 2003), horizontal nutrient advection in the Ionian Sea
should not have any significant impact on the late winter–early spring
[Chl <inline-formula><mml:math id="M152" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] peak observed during the cyclonic regime. However, an analysis of
Table 1 and the spatial correspondence between phenological anomalies
and isopycnal uplift–depression suggest that, in the north Ionian Sea, the
March bloom would be favored by cyclonic circulation, which tends to
uplift isopycnals and the nitracline depth towards the surface, and by strong
negative winter buoyancy fluxes, which contribute to deepening the MLD. In other
words, north Ionian phytoplankton phenology is driven by the interactions
between the nutrient field and MLD, which is consistent with subtropical
regions where phytoplankton growth is almost permanently limited by nutrient
availability (Longhurst, 2006). From these results, we propose two scenarios
to explain interannual changes in phytoplankton phenology in the north Ionian
Sea. These scenarios are based on the relative position of the nitracline and the
winter MLD. In the first scenario (scenario A), the deepest winter MLD
remains above the nitracline depth and there is no spring phytoplankton
bloom,
whereas in the second scenario (scenario B), winter MLD lies deeper than the
fall nitracline depth, which drives remarkable nutrient supplies to the
surface and supports the development of a March bloom. The first scenario
results in a deep nitracline depth and/or a shallow MLD. Conversely,
scenario B occurs if the nitracline depth is shallow and/or if the MLD is
deep.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p id="d1e2115">Time series for the region S3 of the mean nitracline depth (solid
black line), depth of the isopycnal 28.9 kg m<inline-formula><mml:math id="M153" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (solid grey line) and
MLD computed with a density criteria of 0.005 kg m<inline-formula><mml:math id="M154" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (solid red line)
and 0.03 kg m<inline-formula><mml:math id="M155" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (dotted red line) from a surface reference of 10 m.
Nitracline depth was derived from the depth of the isopycnal 28.9 kg m<inline-formula><mml:math id="M156" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
with the linear relationship established in Fig. 3c. Circles represent
the mean Date_GR_Max dates for the region S3.</p></caption>
          <?xmltex \igopts{width=327.206693pt}?><graphic xlink:href="https://bg.copernicus.org/articles/15/4431/2018/bg-15-4431-2018-f07.pdf"/>

        </fig>

      <p id="d1e2172">Scenario B was observed in some subtropical regions, like the BATS station in
the subtropical North Atlantic (Steinberg et al., 2001). There, vertical
mixing represents one of the major processes to supply nutrients to the
illuminated surface layer (Steinberg et al., 2001; Hansell and Carlson,
2001). At lower latitudes and generally in the trade wind biome regions according
to Longhurst (2006), trophic regimes close to scenario A are observed. For
instance, at the station HOT in the North Pacific subtropical gyre (Karl and
Lukas, 1996), winter mixed layers rarely reach the deep nutrient-repleted
waters and a deep chlorophyll maximum is almost permanent (Letelier et al.,
2004). The rate of primary production is then explained by stochastic
nutrient injections into the euphotic zone caused, for instance, by internal
waves, cyclonic mesoscale eddies or wind-driven Ekman pumping (Hayward, 1991;
Karl, 1999). In the Mediterranean Sea, Lavigne et al. (2013) showed that in
the south Ionian Sea and in the Levantine Sea, the probability that the MLD
reaches the nitracline depth is very low. These results were corroborated by
a recent analysis based on Bio-Argo floats (Pasqueron de Fommervault et al., 2015).
However, in regions where mesoscale circulation is cyclonic (e.g., south
Adriatic gyre, Rhodes gyre), there is evidence of surface nutrient
enrichment caused by vertical mixing (Gačić et al., 2002; Lascaratos et al.,
1993; Salihoglu et al., 1990). Thus, the eastern Mediterranean Sea likely
holds both trophic regimes: one involving subsequent surface nutrient
supplies by winter vertical mixing and the other not receiving such a supply.</p>
      <p id="d1e2176">Figure 7 supports our previous hypothesis to explain interannual variability
in phytoplankton phenology. Indeed, during the anticyclonic phases of the
circulation regime (i.e.,<?pagebreak page4441?> 1993–1997 and 2007–2010), the estimated nitracline
depth was relatively deep and ranged between 100 and 150 m. The nitracline
is never reached by the MLD estimated with the difference density criterion
of 0.005 kg m<inline-formula><mml:math id="M157" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (Brainerd and Gregg, 1995) and was rarely reached by
the deepest MLD estimated with the difference density criterion of
0.03 kg m<inline-formula><mml:math id="M158" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (de Boyer Montégut et al., 2004). In addition, during
the anticyclonic period, the isopycnal 28.9 kg m<inline-formula><mml:math id="M159" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> never intersected
the surface, indicating that winter mixing is not able to penetrate this
layer. During the cyclonic phases (1999–2005 and 2012), the nitracline was
shallower (generally less than 100 m). Except for 2001, the shallowest MLD
estimations exceeded the fall nitracline depth and almost reached the
surface,
indicating a penetration of mixing down to the isopycnal 28.9 kg m<inline-formula><mml:math id="M160" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
layer and a possible nutrient enrichment.</p>
      <p id="d1e2227">A common explanation for the fall and spring bloom is the succession of an
entrainment bloom (i.e., bloom driven by MLD deepening in nutrient-limited
conditions) in fall followed by a spring bloom (light-limited, Cullen et al.,
2002; Lévy et al., 2005). The onset of the spring bloom, which is initially
prevented by a deficiency of light in the surface mixed layer, is generally
explained by a stratification or a stabilization of the water column.
Stratification can be caused by the shoaling of the mixed layer (Sverdrup,
1953) or, as recently suggested, by submesoscale eddies (Mahadevan et al.,
2012). Other studies have shown that a phytoplankton bloom can be induced by
a decrease in the water column turbulence (Huisman et al., 1999) in response,
for instance, to the inversion of the surface heat fluxes (Taylor and
Ferrari, 2011). However, previous hypotheses about fall and spring
phytoplankton blooms were developed for temperate and subpolar regions and
do not fit with the light and nutrient conditions of the Ionian Sea. Indeed,
on the one hand, in the Ionian Sea, winter solar irradiation is sufficient to
support phytoplankton growth according to the Sverdrup (1953) approach
(Lavigne et al., 2013). On the other hand, Fig. 7 shows that when the first
Chl <inline-formula><mml:math id="M161" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> increase is observed in fall (October to December), the MLD is
shallower than the nitracline depth, making the entrainment bloom hypothesis
an unconvincing explanation for the fall [Chl <inline-formula><mml:math id="M162" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] rise. A possible
explanation for the early increase in [Chl <inline-formula><mml:math id="M163" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] could be sought in the
seasonal increase in Chl <inline-formula><mml:math id="M164" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> content per cell in response to a diminution of
the light intensity (Winn et al., 1995; Behrenfeld et al., 2005). Indeed,
from a modeling approach, Taylor et al. (1997) showed that the phytoplankton
carbon to chlorophyll ratio varies by a factor of 2 in subtropical regions
(<inline-formula><mml:math id="M165" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 35<inline-formula><mml:math id="M166" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) from early fall to December.</p>
      <p id="d1e2275">Spring peaks in [Chl <inline-formula><mml:math id="M167" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>], mainly observed during the cyclonic circulation
regime, can be considered as typical spring blooms (i.e., detrainment blooms,
Cullen et al., 2002), which are light driven. Indeed, Date_GR_Max was
sometimes observed during the MLD shallowing. However, the tight coupling
between MLD deepening (deeper than nitracline) and [Chl <inline-formula><mml:math id="M168" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] increase as well
as the lack of light limitation in the eastern Mediterranean (Lavigne et al.,
2013) lead us to conclude that [Chl <inline-formula><mml:math id="M169" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] increase is the result of a late
winter entrainment bloom (nutrient driven). In addition, as the date of the
bloom is determined from surface [Chl <inline-formula><mml:math id="M170" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>], the dilution effect during the
mixed layer deepening masks the phytoplankton accumulation, causing an
artificial delay in the computed date of the bloom (Behrenfeld, 2010).</p>
</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <title>Conclusion</title>
      <p id="d1e2313">In this study we show that in the Ionian Sea two trophic regimes coexist. In
one case, the absence of a spring bloom peak in March indicates a lack of
nutrient supply to the surface layer. In that case, the rate of regenerated
production is high year-round and new primary production would only be
sustained by sporadic nutrient injections through the nutricline. In the
second case, the presence of a [Chl <inline-formula><mml:math id="M171" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] peak in<?pagebreak page4442?> March could be explained by
a significant nutrient supply by vertical mixing, which sustains the
phytoplankton bloom and the seasonal boost in new primary production. We
showed that these differences in the phytoplankton dynamics were associated
with the variability of the circulation regime of the NIG. Namely, the March
[Chl <inline-formula><mml:math id="M172" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] peak was commonly observed during the cyclonic phases, whereas no
peak was observed in the anticyclonic case. In addition to the strength and sense
of the circulation, the [Chl <inline-formula><mml:math id="M173" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>] annual cycle is also affected by the winter
buoyancy losses, which determine the MLD. Thus, it appears that phytoplankton
phenology is the result of the interplay between surface circulation and
atmospheric conditions, affecting the nitracline depth and the MLD.
Hypotheses based on the relative position of the nitracline depth and the
winter deepest MLD were then proposed to explain observed phenological
patterns.</p>
      <p id="d1e2337">The dependence of phytoplankton phenology on the circulation regime in the
Ionian (driven by BiOS) establishes a link between phytoplankton dynamics
and the semi-closed thermohaline cell of the eastern Mediterranean. As shown
previously (Gačić et al., 2014), the Adriatic Sea, where the thermohaline
cell of the eastern Mediterranean originates, is highly sensitive to the
winter air–sea heat fluxes. For example, the exceptionally severe winter of
2012 resulted in the occasional production of a large amount of very dense
water in the Adriatic, whose spreading in the deep Ionian caused a partial
reversal of the circulation.</p>
      <p id="d1e2340">In conclusion, future studies on phytoplankton dynamics in the Ionian Sea
should not take into account just the local circulation regime, but also winter
climatic conditions over the Adriatic Sea.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability">

      <p id="d1e2348">All the data used for this article are publicly available via web applications. Please
refer to Sect. 2.1 and 2.2 for details.</p>
  </notes><notes notes-type="authorcontribution">

      <p id="d1e2354">HL conducted the data analysis and produced the figures.
The paper was written by HL with the contribution of MG, GC and FD'O. MG
and GC provided their expertise on Ionian circulation and biogeochemistry. FD'O
provided expertise on phytoplankton phenology and Mediterranean
biogeography.</p>
  </notes><notes notes-type="competinginterests">

      <p id="d1e2360">The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e2366">The authors thank the ESA Ocean Colour CCI team for providing OC-CCI
chlorophyll data, NASA for providing SeaWiFS, MODIS and MERIS chlorophyll
data, the ECMWF for providing meteorological data and AVISO for support from
CNES for distributing altimeter products produced by SSALTO–Duacs. The
Coriolis Centre for in situ Oceanographic Data and the National Oceanographic
Data Center of the OGS (NODC-OGS) are acknowledged for the collection of the
CTD and nitrate profiles that were made available for this study. This study
was conducted using EU Copernicus Marine Service Information. We are
also grateful to Dhyan Aranha for proofreading an earlier version of this paper. We
acknowledge the European Commission (co-funded by the European Union under
“FP7 – People – Co-funding of Regional, National and International
Programmes”, GA no. 600407) and the RITMARE Flagship Project for
support to Héloise Lavigne during her stay at OGS. This work is also a
contribution to the French “Equipement d'Avenir” NAOS project (ANR
J11R107-F) and to the PERSEUS EU project. Miroslav Gačić was partially
supported by the Croatian Science Foundation under the project SCOOL
(IP-2014-09-5747). Two anonymous reviewers are thanked for their constructive
comments on a first draft of the paper.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: Marilaure Grégoire<?xmltex \hack{\newline}?> Reviewed by: two anonymous
referees</p></ack><ref-list>
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    <!--<article-title-html>Impact of decadal reversals of the north Ionian circulation on phytoplankton phenology</article-title-html>
<abstract-html><p>In the north Ionian, water circulation is characterized by a decadal
alternation of cyclonic and anticyclonic regime driven by the mechanism
called BiOS (bimodal oscillating system). The circulation regimes affect both
vertical dynamics and the nutrient distribution. The north Ionian is then a
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patterns in the north Ionian. In the center of the north Ionian gyre, the
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chlorophyll peak, likely resulting from different phytoplankton dynamics, was
commonly observed in March. An additional analysis shows that the winter
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explaining the interannual variability in bloom onset and intensity. Two trophic
regimes were then identified in the north Ionian gyre (NIG) and they could be
explained with the relative position of the MLD and nitracline. The first one
is characterized by an early winter bloom onset and the absence of
a chlorophyll peak in March. It was observed when circulation was anticyclonic
or when winter MLD was relatively shallow. Dominant regenerated production
all year and an absence of significant nutrient supplies to surface
waters are proposed to explain this trophic regime. Conversely, the second
trophic regime is marked by a bloom onset in late winter (i.e., February) and
a chlorophyll peak in March. The chlorophyll increase was interpreted as a
direct response to the nutrient enrichment of surface waters. This winter–spring
bloom was observed when circulation was cyclonic and when winter mixing was
relatively strong.</p></abstract-html>
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