Lagrangian studies of sedimentation and transport. Impact on marine ecosystems

In the last decades there has been an increasing availability of ocean velocity data from satellite measurements, drifters and computer models that has produced important advances in the Lagrangian description of ocean transport. A variety of tools for this purpose have emerged, most of them have been borrowed from dynamical systems theory and adapted to the finite time and resolution. These techniques can be divided into two main categories. One group is focused on geometric objects and they are based on the non-asymptotic version of Lyapunov exponents. On the other hand, there is a probabilistic approach focussing on the moving fluid regions themselves, the so-called set-oriented methods. They are based on the discretization of the Perron-Frobrenius operator.
Ocean biology is an area where Lagrangian processes are undoubtedly important. Although we can consider marine organisms as active particles, in the case of larvae, due to their small size, they can be considered as passive tracers. This and the fact that some species are rather territorial in their adult stage, allows to study the population connec- tivity computing their Lagrangian trajectories. The Lagrangian Flow Network (LFN) technique has demonstrated great effectiveness in studying the structure of marine pop- ulations which are commonly organized as discrete subpopulations. It is a modeling framework in which geographical sub-areas of the ocean are represented as nodes in a network interconnected by links representing the transport of propagules (eggs and larvae) by currents. While this approach has been already applied in different contexts, the global robustness and sensitivity of metrics derived from LFNs have not been quantitatively assessed yet. Here we assess in chapter 3 the sensitivity and robustness of four connectivity metrics derived from LFN that measure retention and exchange processes, thus providing a systematic characterization of propagule dispersal. The most relevant parameters are tested over large ranges: the density of released particles, the node size (spatial-scales of discretization), the Pelagic Larval Duration (PLD) and the modality of spawning. Our results have important implications to design properly connectivity experiments with particle-tracking models and to evaluate the reliability of their results.
Another important biological process in the ocean that can be studied by a Lagrangian approach is the downward flux of carbon-rich biogenic particles from the marine surface into the deep ocean. It is a key process of the biological carbon pump, responsi- ble (together with the solubility and the physical carbon pumps) of much of the oceans’ role in the Earth carbon cycle. The problem of sinking particles is studied (chapter 4) in a realistic oceanic flow, with major energetic structures in the mesoscale, focussing on the range of particle sizes and densities appropriate for marine biogenic particles. Our results show that the finite-size corrections are negligible compared to the most important terms, which are passive motion with the velocity of the flow, and a constant added vertical velocity due to gravity. Nevertheless, we show that two-dimensional cuts or projections of evolving three-dimensional particle clouds display horizontal clustering.
The spatial distribution of sinking particles in the seafloor it also studied (chapter 5). This was made considering a horizontal sheet of falling particles immersed in an oceanic flow, and determining how they spatially distribute when the particles sediment on the seabed (or are collected at a layer at a given depth). This is performed from a Lagrangian viewpoint attending to the oceanic flow properties and the physical characteristics (size and density) of typical biogenic sinking particles. Two main processes determine the distribution, the stretching of the sheet caused by the flow and its projection on the surface where particles accumulate. These mechanisms are checked, besides an analysis of their relative importance to produce inhomogeneities, with numerical experiments in the Benguela region. We show that faster (heavier or larger) sinking particles distribute more homogeneously than slower ones.