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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. ArchiMer
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
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Residential Consumption of Gas and Electricity in the U.S.: The Role of Prices and Income AgEcon
Alberini, Anna; Gans, Will; Velez-Lopez, Daniel.
We study residential demand for electricity and gas, working with nationwide household-level data that cover recent years, namely 1997-2007. Our dataset is a mixed panel/multi-year cross-sections of dwellings/households in the 50 largest metropolitan areas in the United States as of 2008. To our knowledge, this is the most comprehensive set of data for examining household residential energy usage at the national level, containing the broadest geographical coverage, and with the longest longitudinal component (up to 6 observations per dwelling). We estimate static and dynamic models of electricity and gas demand. We find strong household response to energy prices, both in the short and long term. From the static models, we get estimates of the own price...
Tipo: Working or Discussion Paper Palavras-chave: Residential Electricity and Gas Demand; Price Elasticity Of Energy Demand; Static Model; Dynamic Panel Data Model; Partial Adjustment Model; Resource /Energy Economics and Policy; Q4; Q41; Q48; Q54; Q58.
Ano: 2011 URL: http://purl.umn.edu/99637
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