Consulta: subjectFacets:"Modèle en boîtes"
Registros recuperados: 2
Data/hora: 01/06/2024 02:30:01

Capacité trophique du bassin de Marennes-Oléron : couplage d'un modèle de transport particulaire et d'un modèle de croissance de l'huître Crassostrea gigas
Provedor de dados: 5
Autores: Bacher, Cedric.
The trophic relationship between a population of cultivated oysters and potential food was modeled in Marennes-Oleron Bay. Coupling the transport process of particulate matter with assimilation by a population of oysters was achieved through a box mode!. Transport between boxes was based on a mass conservation equation. Parameters were derived from volumes of the boxes, tidal movements and residual 110ws between boxes, and were computed from a numerical hydrodynamical model. Consumption, assimilation and respiration terms were put into an energetic budget equation which enabled simulation of growth. A result of the model was the variability of growth along an axis from North to South, which was related to the oysters' accumulated consumption of food....
Tipo: Text
Palavras-chave: Marennes Oleron Bay; Growth; Energetic budget; Crassostrea gigas; Trophic capacity; Box model; Marennes Oléron; Croissance; Bilan énergétique; Crassostrea gigas; Capacité trophique; Modèle en boîtes.
Ano: 1989
URL: http://archimer.ifremer.fr/doc/1989/publication-2882.pdf

Construction et étude d'un modèle de réseau trophique de la vasière de Brouage (bassin de marennes Oléron, France). Prise en compte de la saisonnalité et des échanges physiques pour la synthèse constructive des connaissances sur une zone intertidale d'une région tempérée.
Provedor de dados: 5
Autores: Leguerrier, Dephine.
In order to better understand the functioning of the Brouage intertidal mudflat (Marennes- Oléron Basin, France), its carbon-based trophic web has been modelled and analyzed. The foodweb building is based on the 4 step method of Inverse Analysis: 1) conceive an a priori model as the graph of compartments (nodes) between which exist fluxes of material (vertices). These vertices are the unknowns for the problem; 2) gather all the existing knowledge about the ecosystem and translate it into linear equations and inequalities involving the fluxes; 3) complete this set of data by common knowledge on the behaviour of the compartments and translate it into inequalities, 4) solve the obtained linear system under the parsimony principle to find a unique solution...
Tipo: Text
Palavras-chave: Brouage Mudflat; Box Model; Seasonality; Dynamic Model; Static Model; Monte Carlo; Markov Chains; Network Analysis; Intertidal Mudflat; Food Web; Inverse Analysis; Vasière de Brouage; Modèle en boîtes; Saisonnalité; Modèle Dynamique; Modèle Statique; Monte Carlo; Chaînes de Markov; Analyse des Réseaux; Vasière Intertidale; Réseau Trophique; Analyse Inverse.
Ano: 2005
URL: http://archimer.ifremer.fr/doc/2005/these-2260.pdf