Transcript Morvan Barnes - Observatoire Océanologique de Villefranche sur Mer

Biogeochemical Inferences from the Diel Variability of Optical
Properties in the NW Mediterranean (BOUSSOLE site)
Morvan
Barnes1
David
Morvan Barnes
Antoine1
Post-Doc
1 Laboratoire d’Océanographie de Villefranche, CNRS and Université Pierre et Marie Curie, 06238 Villefranche sur Mer, FRANCE
I. High-resolution observations of IOPs
II. Diel & Seasonal Variability of IOPs
c) Climatology cp
AIM: Examine variability of cp and bbp across
different seasons and trophic states.
Introduction
The interpretation and understanding of oceanographic
field observations are intimately linked to their inherent
spatial and temporal scales of variation. Whilst satellite
observations are adapted for describing large-scale
oceanographic phenomena – moored buoys are suited
to study transient phenomena or to produce real-time
estimates of biogeochemical properties. In particular,
the link between the temporal variability of IOPs and
phytoplankton production at the diurnal scale has been
relatively understudied.
Aims
a) Season delineation
Map showing Boussole station (black square) in
case 1 Mediterranean waters.
In the framework of the BIOCAREX (BIOoptics and CARbon Experiment) and BOUSSOLE (BOUée
pour l’acquiSition d’une Série Optique à Long termE) projects, our aims are: To better understand biooptics in Mediterranean waters and the links with biological carbon production by exploiting continuous
high-frequency observations on a fixed site; To understand the daily and seasonal changes in optical
properties.
Time series of the mixed layer depth (full circles with
standard deviation in grey) and surface chlorophyll
measurements (dotted line) from the monthly sampling at
Boussole. Data were separated into 4 seasons: Mixed (MLD
> 100 m), Bloom & Collapse (Chl > 0.8 mg m-3 ), and
Oligotrophy (Chl < 0.4 mg m-3).
Climatology of surface cp at Boussole showing 10-day mean
(blue line) and associated standard deviation (blue area).
d) Seasonality of cp & bbp
b) Diel cycles of cp & bbp
Methods
Time series (2006-2011) of high
frequency (15 min) and hyper-spectral
optical observations in surface waters
at the BOUSSOLE site. Vertical
profiles of cp (660 nm) at a lower
frequency (monthly) from CTD profiles.
Net community production (NCP) is
calculated from the diel increase in cp
following Claustre et al (2008, Example of a diel cycle of cp at Boussole
from Gernez et al (2011, L&O 56). The
Biogeosci 5) whereby:
top axis represents fractions of the
normalized day where 0 is sunrise and
0.5 is sunset. Also shown are the rate
of variation (r) and the daily rate (µ).
III. Vertical structure of cp
a) Seasonal profiles
Climatology of surface cp at Boussole showing 10-day mean
(blue line) and associated standard deviation (blue area).
KEY POINTS
High-frequency transmissiometer data
can offer more than sole beam attenuation.
Mean diel cycles of cp and
bbp during bloom periods.
Rate of diel cp variation can be used to investigate
carbon accumulation of particle assemblage.
Characteristic seasonal vertical profiles of cp may be
used to extend the IOP-based production model
through the water column, although assuming vertical
homogeneity of ΣΔPOC yields comparable results.
Seasonal estimates of net community production
AIM: Characterise the
reveal production maxima in March, whilst diel
relationship between surface
variations confirm a late-morning maxima.
cp and its integrated content
over the water column. Apply
towards vertical extension of cpbased production model.
NCP values are comparable to
chl-based PP estimates.
c) ΔPOC-to-cp ratio
• Differences between diel cycles of cp and bbp
including a notable lag in the daily maxima of cp
during blooming periods in particular.
• Strong seasonal differences in diel variation of cp and bbp and in the
mean daily values.
• Both cp and bbp on average twice as high during
during periods of oligotrophy or strong mixing.
April than
IV. NCP from IOPs
AIM: Determine whether IOPs such as cp can be used to derive
high resolution community or primary production data; Examine
the diel and seasonal variations in community production.
c) Diel NCP0m variations
a) Seasonal NCP
Characteristic vertical profiles of cp by season
showing mean fit to in situ profile data (r2).
b) Cp vertical extension
Relationship between mean surface cp and ΔPOC,
the diel increase in POC.
d) ΔPOC vertical extension
Comparison of in situ cp with both vertical
modulation (using profiles) and vertical integration
from surface values.
Climatology of cp-derived NCP showing 10-day mean (blue
line) and associated standard deviation (blue area). Ten-fold
variations in the 10-day mean were observed.
b) NCP vs PP estimates
Time series of cp-derived NCP (open circles) and primary
production estimates from calculated from a chlorophyll-based
model (Morel 1991, P in O 26).
Mean (black line) and 95% confidence intervals (white
lines) of NCP calculated at 30 min intervals based on
variations in cp. Percentage of total data for pooled NCP
values are indicated as the colour scale.
Differences between ΣΔPOC (total water column)
calculated using both methods of vertical extension.
• Vertical distribution of cp can be accurately depicted by 4 characteristic seasonal profiles.
•These profiles improve on previously assumed vertical homogeneity which often underestimated cp
from 10-50 m and overestimated at depths below 50 m.
• Community carbon production is greatest in March at the beginning of the increase in surface cp.
• Optically-derived NCP measurements are comparable to traditional chlorophyll-based primary
production measurements both in terms of magnitude and temporal variability.
• However, this technique enables the calculation of diel variations in NCP. This reveals, for example,
maximal carbon fixation before midday with very little variability during periods of oligotrophy.
• A strong relationship between surface ΔPOC (daily increase in POC calculated from cp)
and mean daily cp allows for application of profiles to surface ΔPOC.
• However, the use of vertical cp profiles had no significant effect on ΣΔPOC.
Further Questions
Could combining buoy data with data from profiling floats increase
our understanding of optical variability?
Could bbp be similarly used to estimate biogeochemical properties?
What optical/biogeochemical properties can be used to characterise
the anomalous optical properties of the Mediterranean?
For more information - on diel cycles of Boussole optics (Poster Session
3: 111.Kheireddine), data quality control (Poster Session 2: 227.Vellucci)
and other Boussole achievements (Poster Session 1: 61.Diamond).
Acknowledgements
Funding Partners
This study is a contribution to the BIOCAREX and
BOUSSOLE projects with funding and technical and logistic
support provided by the organisations listed. The authors are
grateful to the members of the BOUSSOLE staff for lab
analyses and data quality control, and to the crews of the
research vessels for ship measurements and sampling.
Contact us: Laboratoire Océanographique de Villefranche, Quai de La Darse, 06238 Villefranche, France
T +33(0)493763736 E [email protected] W www.obs-vlfr.fr/LOV/OMT/