Marine ecosystems are facing increasing pressure due to anthropogenic activities (fisheries, pollution and climate change) that need to be managed in a holistic (ecosystem-based) and reactive way. The management of marine resources is still based in most cases on annual statistical stock assessment analyses ignoring the environmental and climate variability. There is a need for new complementary approaches for the management and real-time monitoring of marine resources, relying on the development of ecosystem models (e.g., Lehodey et al. 2008; Senina et al. 2008; Sibert et al. 2012) that can be used in routine by the fishing authorities.	Acoustic Profile and micronecton sampling (Credit: Dr Jock Young, CSIRO)
Surface micronecton biomass prediction	The predictions of the physical-biogeochemical oceanic environment are the basic inputs needed to develop ecosystem models of higher biological levels including exploited species. P rogresses of the last two decades make possible such realistic simulations of ocean physic and the modeling of lower trophic levels, i.e., the phytoplankton and zooplankton, is also rapidly progressing (Brasseur et al. 2010). However, a key explanatory variable is usually missing to understand individual behaviour and population dynamics of large oceanic predators. This is the modelling and prediction of the spatial distribution of micronekton.
Micronecton organisms are indeed both the prey of large ocean predators, but are themselves also predators of eggs and larvae of many species from which most fishes. Providing real-time distributions of micronecton would pave the way for a new approach of monitoring large ocean predators that are either targeted by fisheries (tuna , swordfish, marlin, etc.) or strictly controlled in by-catch (bluefin tuna, sharks), or fully protected (marine turtles, seabirds, marine mammals) as illustrated here. Succeeding in simulating preys (micronecton) is the key for predicting large predators behavior	Movements of 3 elephant seals (black) and micronecton biomass around the Kerguelen Islands (Credit: Dr Cedric Cotté, MNHN)
An original modeling approach of micronekton has been proposed recently (Lehodey et al., 2010a). The key input parameters needed as input to this model are the 3-D ocean currents and temperature together with net primary production and euphotic layer depth. All of them can be obtained directly or indirectly from space oceanography: infrared/microwave radiometry for the surface temperature and salinity, altimetry and space gravity measurements for the surface currents, ocean colour for the net primary production and euphotic layer depth. Regarding the ocean temperature, salinity and currents, more sophisticated approaches are needed that enable to project the surface information measured from space into depth. These methods require the a-priori knowledge of the ocean state covariances. A common approach is to use historical in-situ datasets of the ocean state at depth coincident with surface space information to compute statistical functions.	Fin whales movements and micronecton biomass in the Mediterranean Sea
In this project, we will demonstrate how the synergetic use of space observations from many different Earth Observation satellites (CRYOSAT, GOCE, SMOS, ENVISAT, together with other non-ESA satellites) and in-situ data can provide the key input variables for an accurate estimation of the micronecton distribution.