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Autor: =Bingtuan, Li.
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Publicación seriada
Referencias AnalíticasReferencias Analíticas
Autor: Bingtuan, Li. ; Wolkowicz, Gail S. K ; Kuang, Yang
Título: Global Asymptotic Behavior of a Chemostat Model with Two Perfectly Complementary Resources and Distributed Delay
Páginas/Colación: pp. 2058-2086
Url: Ir a http://siamdl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=SMJMAP000060000006002058000001&idtype=cvips&gifs=Yeshttp://siamdl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=SMJMAP000060000006002058000001&idtype=cvips&gifs=Yes
SIAM Journal on Applied Mathematics Vol. 60, no. 6 May/June 2000
Información de existenciaInformación de existencia

Palabras Claves: Palabras: CHEMOSTAT CHEMOSTAT, Palabras: COEXISTENCE COEXISTENCE, Palabras: COMPETITION COMPETITION, Palabras: COMPETITIVE EXCLUSION COMPETITIVE EXCLUSION, Palabras: DISTRIBUTED DELAYS DISTRIBUTED DELAYS, Palabras: GLOBAL ASYMPTOTIC BEHAVIOR GLOBAL ASYMPTOTIC BEHAVIOR, Palabras: INTEGRAL DIFFERENTIAL EQUATIONS INTEGRAL DIFFERENTIAL EQUATIONS, Palabras: PERFECTLY COMPLEMENTARY RESOURCES PERFECTLY COMPLEMENTARY RESOURCES

Resumen
RESUMEN

RESUMEN

 

A model of the chemostat involving two species of microorganisms competing for two perfectly complementary, growth-limiting nutrients is considered. The model incorporates distributed time delay in the form of integral differential equations in order to describe the time involved in converting nutrient to biomass. The delays are included in the nutrient and species concentrations simultaneously. A general class of monotone increasing functions is used to describe nutrient uptake. Sufficient conditions based on biologically meaningful parameters in the model are given that predict competitive exclusion for certain parameter ranges and coexistence for others. We prove that the global asymptotic attractivity of steady states of the model is similar to that of the corresponding model without time delays. However, our results indicate that when the inherent delays are in fact large, ignoring them may result in incorrect predictions.

 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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