Mixed layer depth variability and phytoplankton phenology in the

Mediterranean Sea

H. Lavigne1, F. D’Ortenzio1, M. Ribera d’Alcalà2, H. Claustre1

1. Laboratoire d’Océanographie de Villefranche, France2. Stazione Zoologica A. Dohrn, Naples, Italy

45th Liège Colloquium – May 17th 2013

•It is now well recognized that the phytoplankton phenology is impacted by mixed layer depth (MLD) variability (blooms events are good examples).•However, it is still challenging to observe

and characterize the impact of MLD on phytoplankton (MLD and phytoplankton biomass change rapidly, low availability of the phytoplankton biomass data). •Merging in situ MLD data and ocean color

chlorophyll-a concentration ([Chl]SAT) data represents a way to explore interactions between MLD annual cycle and phytoplankton phenology.

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

Present analysis was performed on the Mediterranean Sea because

Data availability (weak cloud coverage for [Chl]SAT, and important CTD sampling).

contrasting biogeochemical regimes co-exist over the basin.

Present analysis was based on :The generation of concomitant MLD and [Chl]SAT

annual cycles.Spatial averages computed in established

bioregions.Description of MLD and [Chl]SAT cycles based on a

new set of metrics.

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

Data

•SeaWiFS (1998 – July 2007) et MODIS-Aqua (July 2007 - 2010) •Level 3, 8-day , 9km •Standard NASA algorithm (O’Reilly et al.,

2007)

Satellite surface chlorophyll-a concentration ([Chl]SAT)

•Historical database (D’Ortenzio et al. 2005 updated with Coriolis).•72186 profiles of temperature and

salinity•Computation of MLD (criteria in density

difference 0.03 kg m-3)

Mixed Layer Depth (MLD) calculated from in situ CTD measurements.

The data density is not sufficient to

work with a regular mesh grid.

A bioregionalization was used instead.

The geographical framework - Starting point the bioregionalization of the Mediterranea Sea proposed by D’Ortenzio and Ribera d’Alcalà (2009).

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

bloom no bloomintermittent

3 mains kinds of dynamics appeared

Result from a k-means cluster analysis based on the seasonal

cycle of SeaWiFS

chlorophyll- a concentrationSource: D’Ortenzio et Ribera D’alcalà (2009)

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

Med NW - Bloom bioregion

Ionian - No bloom bioregion

Climatological scaleAll MLD and [Chl]SAT observations are

mixed to produce a climatological cycle.

Interannual scaleData are averaged for

each year separately.

spatial

tem

pora

l

Data processing

MLD and [Chl]SAT observations

Generation of concomitant MLD and [Chl]SAT annual cycles at 8-day resolution

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

CHL-MAX: annual maximum of [Chl]SATMLD-MAX: annual maximum of MLDΔINIT: Time lag between the initiation of mixing and the initiation of [Chl]SAT increase (determination of the initiation date: annual median + 5%; Siegel et al., 2002).ΔMAX: Time lag between the date of MLD maxima and the date of [Chl]SAT maxima.

Metrics to describe annual MLD and [Chl]SAT cycles

July year n Juneyear n+1

MLD [Chl]SAT

MLD-MAXCHL-MAX

ΔINIT ΔMAX

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

The climatological scaleMed NW - Bloom

Ionian - No Bloom

MLD-MAX CHL-MAX ΔINIT ΔMAX

185 m 0.99 mg m-3 48 days 48 days

MLD-MAX CHL-MAX ΔINIT ΔMAX

90 m 0.22mg m-3 16 days 8 days

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

The interannual scale : the analysis of annual cycles

•The shape of MLD and [Chl]SAT cycles vary from year to year.•For 4 cycles out of 5, the succession MLD deepening followed by [Chl]SAT increase

and decay is repeated.•Cycle 2006/2007 is anomalous.

•The shape of MLD and [Chl]SAT cycles are fairly similar to the climatology.•The absolute values, especially for MLD and [Chl]SAT peaks, are variable.

Med NW - Bloom

Ionian – No Bloom

bioregion MLD-MAX CHL-MAX ΔINIT ΔMAX

Med NW - Bloom 368m[119 – 524]

1.44 mg m-3

[0.84 – 1.72]14 days[0 – 40]

31 days[(-16) – (+72)]

Ionian - No Bloom 108m[76 – 158]

0.25 mg m-3

[0.19 – 0.30]17 days

[(-8) – (+32)]11 days

[(-56) – (+88)]

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

The interannual scale: the analysis of metrics

•The metric MLD-MAX is highly variable, by comparison to CHL-MAX.• MLD-MAX and CHL-MAX are both higher in the

“Bloom” bioregion than in the “No Bloom” bioregion. •ΔINIT is relatively stable and similar for the “Bloom”

and “No Bloom” bioregions.•ΔMAX is more variable, especially for the “No Bloom”

bioregion. •ΔMAX is higher for the “Bloom” than for the “No

Bloom” bioregion.

DATA & METHODS RESULTS DISCUSSION CONCLUSIONINTRODUCTION

Summary

Metrics are a powerful tool to identify patterns in the MLD and [Chl]SAT cycles.

These patterns are relatively consistent between interannual and climatological analyses.

Metrics analysis confirmed that in the Mediterranean Sea stronger biomass accumulation matches with areas where winter MLDs are the deepest.

Metrics analysis revealed temporal differences between main MLD and [Chl]SAT events (measured with ΔINIT and ΔMAX). c ΔINIT ΔMAX

BLOOM ~30 days ~30 days

NO BLOOM ~30 days ~0 days

How we can explain the ΔMAX difference and the ΔINIT of 30 days?

DATA & METHODS DISCUSSION CONCLUSIONINTRODUCTION RESULTS

Do light and nutrient availability can explain the ΔINIT and ΔMAX values in the « Bloom » and « No Bloom » bioregions? PrNUT PrLIGHT

Probability that the MLD is deeper than the nitracline depth.

Empirical estimation (MLD and nitracline datasets are confronted)

Nitracline data set: Nitracline = isoline 1µM

Calculated from a dataset of 5318 nitrates profiles (MEDAR, SESAME

projects).

Probability that the MLD is above the critical depth (Dcr, Sverdrup

1953).Empirical estimation (MLD

dataset is compared to a climatological estimation of the

critical depth, calculation method Siegel et al. 2002)

SeaWiFS climatology

1.3 mol photon m-2 d-1

DATA & METHODS DISCUSSION CONCLUSIONINTRODUCTION RESULTS

Med NW - Bloom Ionian – No Bloom

Do light and nutrient availability can explain the ΔINIT and ΔMAX values in the « Bloom » and « No Bloom » bioregions?

Med NW - Bloom Ionian – No Bloom

P rNU

TP rL

IGHT

DATA & METHODS CONCLUSIONINTRODUCTION RESULTS DISCUSSION

ΔINIT ♦ BLOOM : ~ 30 days♦ NO BLOOM : ~ 30 days

ΔMAX ♦ BLOOM: ~ 30 days

♦ NO BLOOM : ~ 0 days

Hypothesis:[Chl]SAT increase only when the MLD is below the nitracline (November)

Hypothesis:Episodically, a deficit of light could limit the growth during winter.

Hypothesis:Light is always available and irregular nutrients supplies by mixing sustain phytoplankton growth during winter.

• Metrics are a powerful tool to identify phenological patterns and characterize the influence of the mixed layer.

• The relevance of metrics ΔINIT and ΔMAX was emphasized.

• In the Mediterranean Sea, we proposed some hypotheses to explain their behaviors. (Lavigne et al. JGR, in revision)

• The proposed phenological metrics could be particularly adapted for profiling floats observations.

DATA & METHODS CONCLUSIONINTRODUCTION RESULTS DISCUSSION

Conclusions and Perspectives

Thanks to Fabrizio D’Ortenzio (my supervisor), Loïc Houpert (CEFREM, Perpignan FRANCE) and Rosario Lavezza (SZN, Napoli, Italy) for their help on CTD and nitrate data.

Thank you to for your attention

Contact: lavigne@obs-vlfr.fr

Method Lavigne et al., 2012