Digestive activity and stomach temperature in farmed bluefin tuna Thunnus thynnus measured by acoustic tag.

Eight farmed Atlantic bluefin tuna Thunnus thynnus were tagged with temperature and depth transmitters inserted in chub mackerels Scomber colias to characterize their digestive activity, feeding physiology and behaviour in captivity. Results obtained in the experiment can be used to optimize daily T. thynnus feeding strategy in farms, reducing the early regurgitation of food and thus the environmental effects of inappropriate feeding practices.

Feeding ecology of silky sharks Carcharhinus falciformis associated with floating objects in the western Indian Ocean.

The silky shark Carcharhinus falciformis is commonly associated with floating objects, including fish aggregating devices (FADs), in the Indian Ocean. While the motives for this associative behaviour are unclear, it does make them vulnerable to capture in the tuna purse seine fishery that makes extensive use of FADs. Here, the diet of 323 C. falciformis, caught at FADs in the Indian Ocean, was investigated to test the hypothesis that trophic benefits explain the associative behaviour. A high proportion of stomachs with fresh contents (57%) suggested that extensive feeding activity occurred while associated with FADs. Multiple dietary indices showed that typical non-associative prey types dominated, but were supplemented with fishes typically found at FADs. While the trophic benefits of FAD association may be substantial, our results suggest that associative behaviour is not driven solely by feeding.

Population assessment of tropical tuna based on their associative behavior around floating objects.

Estimating the abundance of pelagic fish species is a challenging task, due to their vast and remote habitat. Despite the development of satellite, archival and acoustic tagging techniques that allow the tracking of marine animals in their natural environments, these technologies have so far been underutilized in developing abundance estimations. We developed a new method for estimating the abundance of tropical tuna that employs these technologies and exploits the aggregative behavior of tuna around floating objects (FADs). We provided estimates of abundance indices based on a simulated set of tagged fish and studied the sensitivity of our method to different association dynamics, FAD numbers, population sizes and heterogeneities of the FAD-array. Taking the case study of yellowfin tuna (Thunnus albacares) acoustically-tagged in Hawaii, we implemented our approach on field data and derived for the first time the ratio between the associated and the total population. With more extensive and long-term monitoring of FAD-associated tunas and good estimates of the numbers of fish at FADs, our method could provide fisheries-independent estimates of populations of tropical tuna. The same approach can be applied to obtain population assessments for any marine and terrestrial species that display associative behavior and from which behavioral data have been acquired using acoustic, archival or satellite tags.

Scaling in animal group-size distributions.

An elementary model of animal aggregation is presented. The group-size distributions resulting from this model are truncated power laws. The predictions of the model are found to be consistent with data that describe the group-size distributions of tuna fish, sardinellas, and African buffaloes.

Simulation of large-scale tropical tuna movements in relation with daily remote sensing data: the artificial life approach.

Tunas are known to be able to travel long distances. The aim of this paper is to propose new ethological models which reproduce some tuna movements using the dynamics of their environment. We use sea surface temperature animations (from remote sensing data) to model the South West Indian Ocean, and French purse seiners data are used to estimate movements of fish. The objective of the models will be to find a northern movement from the Mozambique Channel to the Seychelles Islands at the appropriate time (May-July). The initial model uses our ecological knowledge of tunas, i.e. the search behavior for high concentrations of food commonly associated with thermal fronts. In some cases, this simple model creates some northern movements from the Mozambique Channel, but it cannot be used to reproduce large-scale movements between the Mozambique Channel and the Seychelles Islands. The next generation model is created where tuna behaviors are modeled by an artificial neural network, using a genetic algorithm to adjust the connection weights. The tuna school-network receives daily information from its local environment and chooses the best actions in order to be able to pass from the Mozambique Channel to the Seychelles Islands at the appropriate time. One neural network emerges and represents an adaptive behavior able to interpret daily sea surface temperatures to mimic large-scale tuna movements. This artificial behavior can be generalized to each possible departure position from the Mozambique Channel. This modelling represents a new tool to study large-scale movements of pelagic fish, and is a first step towards real-time management of fisheries.