The first step was to rebuild the history of Atlantic Albacore tuna under the combined effects of fishing and environmental variability based on historical catch data collected by ICCAT and ocean variables available from satellite observation and ocean models. Then the results were transferred into an operational chain of production regularly updated with CMEMS products and showing variability due to fishing and the environment. We followed an approach similar to the one we developed for the project INDESO for tropical tuna species.

GOOS Essential Ocean Variables (EOVs) are used to drive the albacore tuna model for the historical reconstruction and the weekly bulletin. They include primary production derived from satellite ocean color and surface solar radiation, and ocean temperature and currents from operational models assimilating satellite (sea surface temperature, sea surface height) and in situ data (temperature, salinity and currents) provided by moorings and profilers. Other essential ocean variables are the dissolved oxygen concentration currently provided from climatology (i.e. monthly average) and the zooplankton (prey of tuna larvae) and micronekton biomass (prey of juvenile and adult tuna) that are simulated from the same ocean variables. Finally, the fishing impact data used was provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT).

SEAPODYM simulates the change in abundance over time and space of Atlantic albacore by age class from larvae to oldest adults under the influence of environmental variables that drive the movement between feeding and spawning grounds, the success of spawning and the mortality of fish. Multiple international fisheries are characterized (fishing gear, strategy, size selectivity, etc.) and their catches are included to measure fishing impact. As in the standard fish stock assessment modelling approach, a statistical method is used to calibrate the model parameters and thus provide estimates of fish abundance by age class based on observations (catch, fishing effort and size frequencies of catch).

The simulations of albacore history enable us to analyse the impact of current fishing levels, and the near real-time outputs should help management and monitoring decisions and the detection of illegal fishing. They should also assist the fishing industry to plan their operations in order to maximise cost efficiency, decreasing fuel consumption and allowing profit at lower level of catch, thus providing favorable conditions to release fishing pressure on the exploited stock.

• The model parameters are estimated with a maximum likelihood estimation approach that minimises the differences between the observed and predicted fishery values from multiple fisheries. Due to intense computational needs for parameter optimisation, this phase uses a coarse resolution (2° x month).
• Data used are georeferenced catch, fishing effort, catch per unit of effort (CPUE) and the size frequencies of catch. Catch by age are predicted based on the observed fishing effort and a catchability coefficient and a selectivity function characterising the fishing fleet. Catch is also used to account for fishing mortality.
• Density of larvae recruited in the first cohort results from density od adult mature fish and the favorability of the spawning habitat index combining temperature preference and coincidence of spawning with presence or absence of predators (micronekton) and food (zooplankton) for larvae.
• After the spawning, different life stages are considered: larvae, juveniles, immature and mature adults. At larvae and juvenile phases, fish drift with currents; later on they become autonomous, whereby in addition to the currents velocities their movement has additional component linked to their size and the habitat value. The feeding habitat is based on the accessibility of tuna to the groups of micronektonic forage.
• From the pre-defined age at first maturity fish start spawning and their displacements are controlled by a seasonal switch between feeding and spawning habitats, effective outside of the equatorial region where changes in the day length are marked enough and above a threshold value.

Monthly maps showing the predicted average biomass of adult mature albacore and their feeding migrations in Atlantic ocean distributions over 2001-2010. The circles show the catches by fisheries targeting mature albacore.

• The operational chain of production has been implemented to provide near real time of mid-trophic functional groups and then tuna density distributions.
• Before running the tuna model, a downscaling approach is needed to adapt the parameterization achieved at coarse resolution to the new environmental forcing at higher resolution.
• Downscaling ensures that spatial distribution and biomass will not differ too greatly from the ones estimated with Maximum Likelihood estimation.
• This task is ongoing.
• The operational configuration at higher resolution provides better and more accurate outputs in key zones, such as in North Atlantic areas where the fishing effort by the European fleet is high and concentrated in a region not well represented at coarse resolution.

North Atlantic                             South Atlantic

• Two simulations are run in parallel with and without fishing impact. The difference gives the fishing impact on the stock while environmental variability is illustrated from unfished stock simulation.
• Albacore model outputs are aggregated by life stage and presented with density maps, and time series of key indicators, including total biomass of adult (spawning biomass), young recruits, and biomass reduction due to fishing.
• Given that fishing data are not yet collected in near real-time, an average (last 5 years) of fishing effort and catch was used to avoid a drift of the model estimates in the absence of fishing.
• In the future, such a model could be directly plugged into to the catch and fishing efforts collected in near real-time using Vessel Monitoring Systems (VMS) and Electronic Reporting Systems (ERS).

Impact of fishing on Atlantic albacore. Map showing the reduction of biomass in adult (spawning) albacore for the year 2010. The color scale highlights the reduction of biomass (kg km-2) in the map and the iso-contours display the percentage decline.