Continuous monitoring of surface optical properties across a geostrophic front: Biogeochemical inferences

Abstract

A system was designed for the continuous surface monitoring of hydrological, bio-optical, and biogeochemical properties in the vicinity of the Almeria-Oran jet-front system (Northwestern Mediterranean Sea). This system included a thermosalinograph, a fluorometer, an optical particle counter, and an absorbance-attenuance meter (AC9), allowing the estimation of the absorption [a(), (m Ϫ1 )] and scattering [b(), (m Ϫ1 )] coefficients at nine wavelengths. More than 500 multivariate records were acquired over a transect crossing the jet-front system three times and encompassing the diversity of water types encountered in this area. A method is proposed to retrieve relevant biogeochemical or bio-optical quantities, among which are the chlorophyll a concentration [from a(676)], the particulate carbon concentration [from b(555)], the colored dissolved organic matter [CDOM, from a (412)], and the chlorophyll-specific scattering coefficient at 555 nm, b*(555) (m 2 mg Chl a Ϫ1 ). The analyses of these various quantities with respect to the surface hydrodynamic fields reveal two main features. First, the particle pool displays highly dynamic quantitative variations across the frontal structure. Qualitatively, flagellate-dominated populations are associated with moderate density waters and maximal jet velocity, while diatoms are recorded at the narrow limit between the jet-front and the Mediterranean waters, where jet velocity is minimal. Second, the CDOM pool presents remarkable covariations with the surface-density field. In particular, the lowest a CDOM (412) values are reproducibly associated with the highest density values, which track upwelled flow associated with the frontal circulation; accumulation of CDOM is always observed inside the frontal waters, at a density value of 27.2 kg m Ϫ3 . These CDOM variations suggest that the frontal system is the place of enhanced biological activity.Hydrodynamics drive the distribution of phytoplankton in the light and nutrient fields. This forcing determines the productivity of a system, its trophic status, and finally the cycle of biogenic elements. To describe these properties, a proper sampling strategy requires simultaneous description of the physical and biogeochemical fields. For observation conducted at small scale, such a statement is far from being trivial: observations of biogeochemical fields are generally based on measurements performed on discrete samples, and thus cannot be conducted at the same resolution as obser-1 Corresponding author (claustre@obs-vlfr.fr). AcknowledgmentsWe acknowledge the financial support of the EEC Coastlooc program (contract ENV4-CT96-0310), of Frontal-ALMOFRONT, PROSOPE, and DYFAMED operations of the PROOF-program and of the CNRS ''Direction des Relations Internationales.'' Kadija Oubelkheir received a CNRS and Région PACA fellowship. We thank Anabelle Cuttelod for the calibrations of the Seatech transmissiometer and fluorometer in POC and chlorophyll a concentrations, respectively. Patrick Chang is thanked for fine tuning the Engl...

Partitioning total spectral absorption in phytoplankton and colored detrital material contributions

“…CDM absorption coefficients computed using the present method are compared with the values estimated at 412 nm over the same area and on the same dataset using a different method published by Claustre et al (2000) and briefly recalled here. In the method presented by Claustre et al (2000), a t (676) -a w (676) is assumed to equal a ϕ (676), and a statistical relationship is used to estimate a ϕ (412) from a ϕ (676). Then, a CDM (412) is derived by subtracting a ϕ (412) from a t (412) ).…”

“…The horizontal distribution of the total spectral absorption and attenuation coefficients was determined in the near-surface waters at high spatial resolution using an underway WETLabs ac-9 along a transect crossing the frontal area several times. A detailed description of the data acquisition and analysis is presented in Claustre et al (2000), together with a complete biooptical characterization of the near-surface waters in the Almeria-Oran frontal system.…”

“…In the near-surface waters over the frontal area, CDM computed using the method of Claustre et al (2000) contributed for 55 to 75% of total minus water absorption coefficient at 412 nm (their fig. 6).…”

“…Phytoplankton absorption coefficients vary as a result of changes in pigment packaging effect due to changes in algal cell size and internal pigment concentration and, to a lesser extent, in pigment composition (Bricaud et al 2004 and references therein). The contribution of the optically significant constituents to the total minus water absorption coefficient of seawater measured in situ can be separated by experimental and numerical methods ranging from seawater filtration for the determination of dissolved absorption coefficient (Prieur and Sathyendranath 1981;Twardowski and Donaghay 2001), to chemical bleaching of the material retained on the filters (Kishino et al 1985;Ferrari and Tassan 1999) or the use of numerical methods (Morrow et al 1989;Bricaud and Stramski 1990) to partition phytoplankton and non-algal particle absorption coefficient, to the use of empirical relationships to discriminate between phytoplankton and colored detrital matter absorption coefficients (Roesler et al 1989;Claustre et al 2000).…”

“…Chang and Dickey (1999) applied the method implemented by Roesler et al (1989) to time series of total minus water spectral absorption coefficient measured with a high temporal resolution (ac-9 meters on moorings), and ultimately discriminated CDOM from non-algal particle contributions based on discrete CDOM samples taken on a regular basis. Claustre et al (2000) used statistical relationships derived from discrete measurements performed in the same area to partition surface horizontal profiles of total spectral absorption coefficient into CDOM, algal, and non-algal contributions. Recently, Gallegos and Neale (2002) introduced a method relying on normalized absorption cross-sectional areas of the absorbing components and a matrix inversion method, and Schofield et al (2004) implemented an optical inversion-optimization method to extract optical weights of various constituents in the bulk signal.…”