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Mesoscale physical processes influence marine ecosystems.
As seen above, several spatio-temporal scales occur in the ocean. Here we focus on the mesoscale and submesoscale processes that have a tremendous importance in the current knowledge of the oceans. Mesoscale physical processes are consist-ing in eddies, filamental structures and frontal oceanic structure. Their forcing mechanisms are mainly instabilities from the large-scale circulation, interactions between currents and bathymetry, the direct effect of the atmosphere, in particu-lar of the wind, and their interactions. In the ocean, the strength (in velocity and thermohaline signatures) of these mesoscale processes generally exceeds that of the mean flow by an order of magnitude or more. Most of the eddy kinetic energy is generated by instabilities of the mean flow, but fluctuating winds can also pro-vide a direct forcing mechanism, which is particularly evident in low-eddy energy regions. Eddies can feed energy and momentum back into the mean flow and help drive the deep ocean circulation (Holland [1978]; Wunsch and Ferrari. [2004]). Ed-dies also transport heat, salt, carbon, nutrients and oceanic non motile biota (as phytoplankton) as they propagate in the ocean (Danabasoglu et al. [1994]). Finally they are often associated with a strong hydrodynamic signature, especially vertical velocities, which are of importance for planktonic life in the ocean. Thus mesoscale processes play a significant role in the global budgets of these tracers, and have a strong impact on the ecosystem. For most operational oceanography applications (e.g. pollution monitoring, toxic algal bloom, coastal management, fisheries man-agement, etc…) mesoscale structures need also to be documented and understood. The impact of the vertical and horizontal exchanges of tracers due to mesoscale eddies has stimulated a large number of biogeochemical studies in the past decade. The quantification of these vertical exchanges (totally ignored in the past stud-ies) indicates that they represent the second most important contribution to the annual nutrient requirement for phytoplankton on a global scale (Garçon et al. [2001]). There are a lot of observational as well as modelling evidences showing that mesoscale processes strongly modulate the functioning and the structure of marine planktonic ecosystem.
Horizontal transport, stirring and phytoplankton patchiness:
The observed patchy distribution of phytoplankton is subject to debate in the com-munity: it is not clear whether it is the biological or physical processes which are responsible for this specific spatial structure. Biological processes by themselves, such as growth, grazing and behaviour, and the non-linear dynamics of ecosys-tems, all contribute to the spatial structure we see in plankton distributions. How-ever, lateral advection and stirring by oceanic eddies and fronts at mesoscale are highly responsible for the observed patchiness distribution of phytoplankton in the surface ocean (see Fig. 1.3). Several processes such as shear effects, filamenta-tion, patches formation, turbulent stirring, and diffusion are involved (Abraham [1998]; Martin [2003]). Academic modelling studies also reported the effect of hor-izontal stirring on tracer distribution. López et al. [2001] stressed the existence of a smooth-filamental transition in the plankton concentration patterns depending on the relative strength of the stirring by the chaotic flow and the relaxation prop-erties of planktonic dynamical systems. More recently, McKiver and Neufeld [2009] showed the importance of the ratio between phytoplankton growth rate and the flow advection time scale. Birch et al. [2008] explained the small scale formation of plankton thin layers by shear and death by diffusion. Indeed all authors found different mechanisms to explain that lateral stirring and mixing can influence spatial structure in plankton distributions. Martin [2003] discussed the need to maintain the recent developments in sampling, instrumentation, image analysis and tur-bulence theory to obtain more data to determine which, if any, of these proposed mechanisms are the most important. Martin [2003] added that even though the em-phasis is on lateral stirring and mixing, horizontal currents were also often strongly related to the vertical circulation (see Subsection below).
Eddies and filaments are also responsible for horizontal transport. They con-tain water masses with specific characteristics inside their core, relatively isolated from the surrounding ones, while moving in the surface ocean. The most notable transport is achieved when eddies or filaments develop in rich coastal areas and then move to oligotrophic offshore zones. Moore et al. [2007] studied eddies on the Western coast of Australia and found that anticyclonic eddies, formed adjacent to the shelf, entrain shelf waters with relatively high chlorophyll concentrations as they propagate westward, exporting coastal phytoplankton communities offshore. They suggest that sub-mesoscale injection of nutrients is associated with the eddy activity and displacement, developing at its boundary. Alvarez-Salgado et al. [2007] studied the impact of the horizontal transport within filaments. They found that transport by filaments accounts for 2.5 to 4.5 times the offshore carbon export driven by Ekman transport in an upwelling system. Since filaments are ubiquitous features in all coastal transition zone systems, they must represent a significant flux of carbon to the open ocean, which should be considered in global biogeo-chemical models.
The interactions between the mean flow and islands is also a preferential source for creation of mesoscale eddies, that are then influencing greatly the ecosystem embedded inside. Aristegui et al. [1997] detailed two mechanisms: the first one is about nutrient pumping and vertical uplifting of the deep chlorophyll maximum by cyclonic eddies in the oligotrophic waters of the Canary region. The second deals with the incorporation into cyclonic eddies of water with high chlorophyll content, resulting from island stirring or local upwelling at the flanks of the islands, being subsequently transported downstream. More recently, Sangra et al. [2009] studied the ’Canary Eddy Corridor’. They suggested that constant formation of long-lived mesoscale eddies may stimulate the total PP through eddy pulsation along their route, being comparable to the PP of the northwest African upwelling system. These effects have been also studied in idealized settings by Sandulescu et al. [2008].
Horizontal turbulence plays a role on the spatial distribution of a single tracer, but it also strongly affects the competition between specific tracers, as it influences the community composition. Karolyi et al. [2000] argue that a peculiar small-scale, spatial heterogeneity generated by chaotic advection can lead to coexistence of sev-eral specific tracers. In open flows, this imperfect mixing lets the populations accu-mulate along fractal filaments, where competition occurs. They in fact provided an hydrodynamical explanation for the spatial and temporal heterogeneity of resources and populations in the presence of imperfect chaotic mixing. A recent coupled mod-elling study by Perruche et al. [2010] showed that a spatially extended and coupled system exhibits a wide range of ecosystem structures, allowing for instance coex-istence between several phytoplankton species. They examinated the physical and biological time scales and concluded on the likely coupling between ecosystem and ocean dynamics in three dimensions.
IN-SITU data from oceanographic surveys.
Oceanographic surveys are the most direct way to collect data of the ocean. The general sampling strategy (stations location and duration) of sea surveys is gener-ally designed before the campaign itself. As a consequence, it is highly depending on the general a priori knowledge we have of the area. Another approach can be a lagrangian study, where the whole campaign is designed while following a wa-ter mass, tracked by drifters released at the beginning of the survey. In our case, the strategy was decided prior to the campaign itself (number and type of transects performed) but precise locations of stations and sections, as well as the sequence of events, were adjusted onboard twice a day, by using real-time acquisition of satel-lite data of Sea Surface Temperature (SST) and chlorophyll a. This strategy was a good compromise to obtain a nice data set on selected processes:
• North-South variability.
• Cross-shore gradient.
• Development of a filament.
• Diurnal cycle at selected location.
Data from CTD sensors.
Physical observations from MOUTON 2007 were made using a Conductivity-Temperature-Depth (CTD) instrument, a Lowered Acoustic Doppler Current Profiler (LADCP) functioning at 300 kHz, and also two Vessel Mounted Acoustic Doppler Cur-rent Profiler (VMADCP), functioning respectively at 38 kHz and 150 kHz. A Seasoar was also onboard (see fig. 2.1), which allows high resolution coverage of hydrogra-phy, but data are not presented in this manuscript.
Simultaneously, a set of biogeochemical sensors were also deployed on the CTD-rosette (see fig. 2.2). We lowered two fluorometers (a Chelsea Aqua 3 for chlorophyll a and a Chelsea Aquatrack a for UV measurements, which can be converted to Colored Dissolved Organic Matter), a dissolved oxygen sensor SBE43 and a Tur-bidimeter CSS-631. There were also few optical sensors: a transmissiometer Wetlab for light transmission and attenuation, a Photosynthetically Active Radiation sen-sor (PAR) and a Surface PAR sensor. The sampling was adjusted to 24 scans per second and the lowering speed of the CTD was about 0.5 m/s. The CTD casts were limited to the upper 200 m (or above when the bathymetry was shallower) due to the maximum working depth of some biogeochemical sensors.
Data from water sample measurements and zooplankton net.
Seawater samples were collected at 1387 stations using a CTD-rosette system equipped with 12 ten litres Niskin bottles (see fig. 2.2). At each station, up to five depths in the water column were sampled: the surface (1 m), the upper thermocline, the deep chlorophyll maximum, the lower thermocline and an additional depth of interest. The conducting cable allowed us to monitor all measured variables during the descent and to determine at the same time our depths of interest. Then water samples were collected on the way up at the depths selected during the CTD de-scent. Although there was a small time-lag between the descent and the ascent, and although internal waves are known to be conspicuous in this area, the main structure were quite successfully sampled.
In-situ data from oceanographic surveys.
To collect seawater for nutrient analysis, the container was first precautiously rinsed with the corresponding water and then samples were collected and iden-tified. The 612 samples where then stored at −20◦C for later analysis.
In the laboratory, the common nutrients concentrations – namely nitrate, sili-cate and phosphate – were determined by colorimetric methods, following Aminot and Kerouel. [2007]’s method. All solutions were prepared in Milli-Q water (Milli-pore Milli-Q water system) with reagent analytical grade salts. Artificial seawater for standards calibration, as well as for nitrate, silicate and phosphate samples, was prepared at a salinity of 34.7 g/l with sodium chloride (NaCl). All calibra-tions of working standards were prepared as described in the WOCE operation and method manual Gordon et al. [1995]. The automated procedure for the detec-tion of nitrate and nitrite uses the procedure where nitrate is reduced to nitrite by a copper-cadmium reduction column. The nitrite then reacts with sulfanilamide under acidic conditions to form a diazo compound. This compound couples with N-1-naphthylethylene diamine dihydrochloride to form a purple azo dye, which is measured at 540 nm. The detection of soluble silicates (silicic acid) is based on the reduction of silicomolybdate in acidic solution to molybdenum blue by ascorbic acid. Oxalic acid is introduced in the sample stream before the addition of ascorbic acid to minimize interference from phosphates. The absorbance is then measured at 820 nm. To measure ortho-phosphate, a blue color entity is formed by the re-action of ortho-phosphate, molybdate ion and antimony ion followed by reduction with ascorbic acid at a pH < 1. The reduced blue phospho-molybdenum complex is measured at 820 nm.
Eulerian / Lagrangian description.
The description of fluid motion can be addressed following two different ways: one can evaluate the velocity, pressure and density fields at fixed spatial locations in the fluid, or either follow the trajectory of each fluid particle. The first approach is called Eulerian and the second one Lagrangian. In principle both are equivalent, and if we denote by v(x, t) the Eulerian velocity field, providing us the value of the fluid velocity at any space-time point (x, t), then the motion of a fluid particle with initial localization x(0) is given by: dx = v(x, t). (2.5).
This expression establishes the physical connection between the Eulerian and Lagrangian description. It clearly says that when a particular fluid particle is known to be at a specific space-time point, its Lagrangian velocity must be equal to the Eulerian field value at that space-time point.
The non asymptotic Finite-Size Lyapunov Exponents.
The existence of chaotic behavior systems was first introduced by the French mathematician Henri Poincaré in the 1890s in a paper on the stability of the Solar System. Some time later, other scientists found additional chaotic systems and they developed new mathematics and theories (Kovalevska, Hopf, Kolmogorov, Lorentz among others). Chaos is a motion irregular in time, unpredictable in the long term, hyper-sensitive to initial conditions and complex, but ordered, in the phase space: it is associated with a fractal structure. In present day literature, a system is said to be chaotic if small (i.e. infinitesimal) perturbations grow exponentially with time, which is connected to a positive Lyapunov exponent.
The classical Lyapunov exponent is defined as the exponential rate of separa-tion, averaged over infinite time, of particle trajectories initially separated infinites-imally. Consider x(t0) and x(t) = x(t0) + δx(t) the position of two particle separated Materials and Methods: a set of complementary tools to study the influence of physical processes on ecosystem dynamics at mesoscale. initially by a distance δx(t0). The global Lyapunov exponent is defined by λ = lim lim 1 ln |δx(t)| , (2.8) |δx(t0)| t→∞ δx(t0 )→0 t.
The Lyapunov exponent is quite useful in the study of time-independent dynam-ical systems. The seminal work of Lyapunov [1992] was very important in laying the theory of Lyapunov exponent for time-independent systems. Then the manuscript by Barreira and Pesin [2002] contains a good modern and comprehensive treat-ment of the subject. However, many dynamical systems of practical importance, especially in the realm of fluids, are time-dependent and only known over a finite interval of time and space. Because of its asymptotic nature, the classical Lya-punov exponent is not suited for analyzing these dynamical systems. The infinite-time limit in Eq.(2.8) makes the Lyapunov exponent of limited practical use when dealing with experimental data. A generalization of the Lyapunov exponent, called the Local Lyapunov exponent (LLE), has been proposed to study the growth of non-infinitesimal perturbations (distance between trajectories) in dynamical systems. Recently the concept of a LLE has been applied to study dispersion in turbulent flow fields. The LLE is a scalar value which characterizes the amount of stretching about the trajectory of point x over a time interval. The LLE varies as a function of space and time. The LLE is not an instantaneous separation rate, but rather measures the average, or integrated, separation between trajectories. This distinction is im-portant because in time-dependent flows, the instantaneous velocity field is often not revealing much about actual trajectories, that is, instantaneous streamlines can quickly diverge from actual particle trajectories. However the LLE accounts for the integrated effect of the flow because it is derived from particle trajectories, and is thus more indicative of the actual transport behavior. Depending on which asymptotic character is eliminated, there are two non-asymptotic Lyapunov expo-nents: finite-time (FTLE) and finite-size (FSLE) Lyapunov exponents, that are very similar.
Here we will detail only the Finite-Size Lyapunov Exponent (FSLE) which is a measure for the growth rate of a perturbation.
Table of contents :
1 General Introduction
1.1 Global Climate change and Biogeochemistry.
1.2 Spatial and temporal scales in the Ocean.
1.3 Mesoscale physical processes influence marine ecosystems.
1.4 The Eastern Boundary Upwelling systems.
1.5 Thesis objectives and plan.
1.6 Résumé Introduction (français).
2 Materials and Methods: a set of complementary tools to study the influence of physical processes on ecosystem dynamics at mesoscale.
2.1 In-situ data from oceanographic surveys.
2.1.1 Data from CTD sensors.
2.1.2 Data from water sample measurements and zooplankton net
2.1.3 Other data in marine sciences.
2.2 Satellite data
2.2.1 Ocean Color.
2.2.2 Ocean altimetry.
a – Generalities and basic principles:
b – Sea Surface Height, Quikscat wind stress and derived geostrophic currents:
2.3 The Finite-Size Lyapunov Exponents: a lagrangian powerful tool.
2.3.1 Eulerian / Lagrangian description.
2.3.2 Dynamical systems and manifolds.
2.3.3 The non asymptotic Finite-Size Lyapunov Exponents.
2.3.4 Lagrangian Coherent Structures (LCS) as ridges in the FSLE field
2.4 Academic and realistic numerical modelling.
2.4.1 Interests and principles.
2.4.2 Hydrodynamical and biological models.
3 A mesoscale survey of the northern and central Iberian Peninsula Upwelling System: spatial variability and bio-physical interactions.
3.1 Article 1: A mesoscale survey of the northern and central Iberian Peninsula Upwelling System: spatial variability and bio-physical interactions, Rossi et al., Progr. Oceanogr.
3.2 Résumé de l’article 1 (français).
3.3 Perspectives and other study derived from the survey.
3.3.1 Distribution of Volatile Halogenated Organic Compounds in the Iberian Peninsula Upwelling System.
3.3.2 Zooplankton communities and size spectra in the Iberian Peninsula Upwelling System.
4 Punctual small scale physical processes observed during MOUTON 2007 and their academic studies.
4.1 Article 2: Effect of the wind on the shelf dynamics: formation of a secondary upwelling along the continental margin, Rossi et al., Ocean Modelling, 2010.
4.2 Résumé de l’article 2 (français).
4.3 Article 3: Influence of a bottom topography on an upwelling current: generation of long trapped filaments, Meunier, Rossi et al., in revision, Ocean Modelling.
4.4 Résumé de l’article 3 (français).
5 Biological activity and mesoscale horizontal stirring in the surface ocean of the 4 Eastern Boundary Upwelling Systems: a comparative study.
5.1 Article 4: Comparative study of mixing and biological activity of the Benguela and Canary upwelling systems, Rossi et al., 2008 Geophysical Research Letters
5.2 Résumé de l’article 4 (français).
5.3 Article 5: Horizontal stirring and biological activity in the surface ocean of the four Eastern Boundary Upwelling Systems, Rossi et al., 2009 Nonlinear Processes in Geophysics
5.4 Résumé de l’article 5 (français).
6 Conclusions and perspectives.
6.1 Conclusions
6.2 Perspectives
6.2.1 Mesoscale variability of the Iberian Peninsula Upwelling System.
6.2.2 Inhibiting effect of mesoscale turbulence from FSLE on the surface chlorophyll in the EBUS: toward an identification of effective processes.
a – An academic modelling of the Benguela Upwelling System.
b – Toward a 3D realistic coupled modelling of the IPUS using HYCOM.
c – Extension of the Finite Size Lyapunov exponents theory.
6.2.3 General perspectives.
6.3 Conclusions et perspectives (français)
6.3.1 Conclusions (français).
6.3.2 Perspectives (français).
References
Annexe A : Distribution of Volatile Halogenated Organic Compounds in the Iberian Peninsula Upwelling System.
.1 Article 6: Distribution of Volatile Halogenated Organic Compounds in the Iberian Peninsula Upwelling System, Raimund, Vernet, Rossi et al., 2010 to be submitted to Journal of Geophysical Research
Annexe B : Top marine predators track Lagrangian coherent structures.
.2 Article 7: Top marine predators track Lagrangian coherent structures, Tewkai, Rossi et al., 2009 Proceedings of the National Academy of Sciences of USA
