Background Background

The water column is the most widespread habitat of the planet and is entirely heterogeneous. The presence of gyres, eddies, fronts, temporary currents etc. defines specific conditions that are conducive to different expressions of ecosystem functioning (European Marine Board, 2013). The objective of this project is to identify the daily habitat of key marine species, mainly fish of market value, using satellite-derived data of the sea surface in support of the management and control of fisheries and the implementation of spatial  protection measures.

The target species are currently the blue shark, the Atlantic bluefin tuna, the European hake (recruits) and fin whale in the Mediterranean Sea as well as skipjack tuna species in the tropical Atlantic and Indian Ocean. We also focused on the favourable feeding habitat of mesozooplankton species highlighting the tight link between chlorophyll-a frontal features and mesozooplankton biomass. 

This leads to a more generic index of Ocean Productivity available to Fish (OPFish) which is beoing compared to highly spatial and temporal fisheries data. The OPFish, as bieng independent of fisheries, monitors the influences of climate and nutrient run-off on the productivity of marine food webs and thus reflect the potential fishing yield once integrated over the fish lifetime (typically one year). The OPFish index shall also be used to classify the pelagic habitats in terms of productivity available to high trophic levels to be used as an indicator for the Marine Strategy Framework Directive (MSFD).

The aims of the research project may vary with the target species but generally are:

  • to improve fisheries management (prediction of catch and abundance to adapt the local fishing effort [OPFish], identification of spatio-temporal harvest rules based on environmental variation and regime shifts) and species protection (identification of Essential Fish Habitat such as nurseries [hake] or species to be preserved limiting bycatch [blue shark]),
  • to increase knowledge on behaviour and migration patterns (for instance bluefin tuna migration in the Mediterranean Sea for spawning),
  • to improve the assessment of fish stocks (standardization of Catch Per Unit Effort) as the perception of stocks is partial for higly migratory species (such as bluefin tuna),
  • to increase knowledge on the marine ecosystem dynamics exploiting the best of Earth observation,
  • to highlight the need of the highly spatial and temporal ('smart') fisheries management.

Methodology Methodology

Two main behaviours are recognized in most fish: feeding and spawning. The JRC habitat model uses satellite data of surface chlorophyll content (CHL) from NASA sensors, i..e. SeaWiFS (1998-2010) and MODIS-Aqua (since July 2002) to compute daily habitats.

The chosen modelling approach of species distribution relies on the niche theory, which utilizes existing knowledge of environmental processes and species ecology to select a limited set of predictors and improve model interpretability. The relevant information for the habitat of specific marine species which is contained in the daily variability of the surface ocean is presently fully exploited.

The feeding habitat is derived for all species while the spawning habitat is computed only for tuna species.

The potential feeding habitat is mainly derived from the occurrence of frontal features of productivity derived from satellite surface chlorophyll-a content (chlorophyll-a horizontal gradient). The potential spawning habitat was mostly inferred from the heating of surface waters (daily temperature difference in a floating window of 30 days) and surface currents. While the favourable feeding habitat is centered on chlorophyll-a frontal features (proxy for food availability), physical environmental variables extracted from operational models (Marine Copernicus Services - CMEMSare used to exclude unfavourable conditionsSee species specific publications for further details.

The daily maps of potential habitats are calibrated and validated with geo-located observations from scientific surveys or fisheries operations. An independent calibration is performed for each satellite sensor providing surface chlorophyll-a content. Monthly, seasonal and annual maps of potential feeding and spawning habitat were then computed from daily maps for the last two decades.