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Abstract (Eng.):
Thunnus thynnus is a pelagic species found in the Mediterranean, particularly along the
Algerian coast. It is much sought-after by fishermen because of its high commercial value and
nutritional value. Because of the ecological and economic importance of these fish at national,
regional and international level, the aim of this work is to provide knowledge for understanding
the behaviour of this species in relation to its biotope. The use of remote sensing to collect
oceanographic data, combined with geo-referenced fishing data, has enabled us to gain a better
understanding of how these environmental factors influence the presence and distribution of
this species on the Algerian coast. We used these datasets to solve our problem: how does the
environment contribute to the spatio-temporal distribution of bluefin tuna? And what are the
environmental factors that influence this distribution along the Algerian coast? This tunaenvironment research has 4 objectives: i) to collect and structure a consistent database; ii) to
understand the behaviour and distribution of tuna populations in the face of variability in
environmental factors; iii) to update the growth parameters of Thunnus thynnus on the Algerian
coast; iv) to help scientists manage stocks. In this thesis, we developed two spatio-temporal
linear models using multiple linear regression analysis, in order to improve our knowledge of
ecosystems and to answer the questions raised by the management and conservation of this
species. This analysis enabled us to define two better equations for the spatio-temporal linear
correction model. The predictive quality of these two models is expressed as a coefficient of
determination with 99% for the spatial model and 70.3% for the temporal model. The
determining factors for the spatio-temporal distribution of bluefin tuna along the Algerian coast
are: temperature, salinity, chlorophyll a, current speed, wave height, dissolved oxygen and
nitrate.
Abstract (Eng.):
Thunnus thynnus is a pelagic species found in the Mediterranean, particularly along the
Algerian coast. It is much sought-after by fishermen because of its high commercial value and
nutritional value. Because of the ecological and economic importance of these fish at national,
regional and international level, the aim of this work is to provide knowledge for understanding
the behaviour of this species in relation to its biotope. The use of remote sensing to collect
oceanographic data, combined with geo-referenced fishing data, has enabled us to gain a better
understanding of how these environmental factors influence the presence and distribution of
this species on the Algerian coast. We used these datasets to solve our problem: how does the
environment contribute to the spatio-temporal distribution of bluefin tuna? And what are the
environmental factors that influence this distribution along the Algerian coast? This tunaenvironment research has 4 objectives: i) to collect and structure a consistent database; ii) to
understand the behaviour and distribution of tuna populations in the face of variability in
environmental factors; iii) to update the growth parameters of Thunnus thynnus on the Algerian
coast; iv) to help scientists manage stocks. In this thesis, we developed two spatio-temporal
linear models using multiple linear regression analysis, in order to improve our knowledge of
ecosystems and to answer the questions raised by the management and conservation of this
species. This analysis enabled us to define two better equations for the spatio-temporal linear
correction model. The predictive quality of these two models is expressed as a coefficient of
determination with 99% for the spatial model and 70.3% for the temporal model. The
determining factors for the spatio-temporal distribution of bluefin tuna along the Algerian coast
are: temperature, salinity, chlorophyll a, current speed, wave height, dissolved oxygen and
nitrate.