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	Provedor de dados AgEcon (1) ArchiMer (1) Autor Cho, Seong-Hoon (1) Clark, Christopher D. (1) Lindstrom, Ulf (1) Loots, Christophe (1) Park, William M. (1) Petitgas, Pierre (1) Planque, Benjamin (1) Vaz, Sandrine (1) Mais... Palavra-chave Spatial dependency (2) C31 (1) Community (1) Community/Rural/Urban Development (1) Demographic structure (1) Density-dependent habitat selection (1) Environmental control (1) Fish spatial distribution models (1) Housing density (1) Multi-model inference (1) Population memory (1) R21 (1) Spatial heterogeneity (1) Mais... Tipo do documento Journal Article (1) Text (1) Ano 2011 (1) 2006 (1) País France (1) United States (1) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Understanding what controls the spatial distribution of fish populations using a multi-model approach ArchiMer Planque, Benjamin; Loots, Christophe; Petitgas, Pierre; Lindstrom, Ulf; Vaz, Sandrine. Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology. The spatial distribution of fish populations observed in the wild results from the complex interactions of multiple controls both external or internal to the fish populations. Whilst species distribution models (SDMs) have been mostly concerned with static description of species distribution as a function of environmental constraints, models of animal movements (MAMs) have focussed on the dynamic nature of spatial distribution of groups of individuals under a number of constraints external and internal to the population. Besides SDMs and MAMs, modelling the spatial distribution of fish populations can be achieved by models that are... Tipo: Text Palavras-chave: Demographic structure; Density-dependent habitat selection; Environmental control; Fish spatial distribution models; Multi-model inference; Population memory; Spatial dependency. Ano: 2011 URL: http://archimer.ifremer.fr/doc/00022/13309/10360.pdf Two Dimensions of the Spatial Distribution of Housing: Dependency and Heterogeneity across Tennessee’s Six Metropolitan Statistical Areas AgEcon Cho, Seong-Hoon; Clark, Christopher D.; Park, William M.. A two-stage multinomial logit selection model is used to model the relationship between demographic characteristics and housing density across Tennessee’s six metropolitan statistical areas. The study finds that there is both spatial correlation and heterogeneity in the most densely populated area, has the least amount of spatial correlation among housing density at the neighborhood level, while Johnson City, which has the lowest overall housing density, has the highest degree of spatial correlation. Tipo: Journal Article Palavras-chave: Community; Housing density; Spatial dependency; Spatial heterogeneity; Community/Rural/Urban Development; C31; R21. Ano: 2006 URL: http://purl.umn.edu/43763 Registros recuperados: 2 Primeira ... 1 ... Última

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