Search results for "PHYTOPLANKTON DYNAMICS"

showing 3 items of 13 documents

Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics

2013

In this paper, by using a stochastic reaction-diffusion-taxis model, we analyze the picophytoplankton dynamics in the basin of the Mediterranean Sea, characterized by poorly mixed waters. The model includes intraspecific competition of picophytoplankton for light and nutrients. The multiplicative noise sources present in the model account for random fluctuations of environmental variables. Phytoplankton distributions obtained from the model show a good agreement with experimental data sampled in two different sites of the Sicily Channel. The results could be extended to analyze data collected in different sites of the Mediterranean Sea and to devise predictive models for phytoplankton dynam…

Stochastic modellingFOS: Physical sciencesStructural basinBiologyRandom processe01 natural sciencesIntraspecific competitionMediterranean sea0103 physical sciencesPhytoplanktonMarine ecosystemSpatial ecologyMarine ecosystem14. Life underwaterQuantitative Biology - Populations and Evolution010306 general physicsPhytoplankton dynamic010301 acousticsEcology Evolution Behavior and SystematicsDeep chlorophyll maximumEcologyEcological ModelingPopulations and Evolution (q-bio.PE)Spatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Oceanography13. Climate actionPhysics - Data Analysis Statistics and ProbabilityFOS: Biological sciencesSpatial ecologyStochastic differential equationsDeep chlorophyll maximumData Analysis Statistics and Probability (physics.data-an)
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A stochastic reaction-diffusion-taxis model for picophytoplankton dynamics

2011

The dynamics of picophytoplankton communities in marine environment is studied by astochastic reaction-dìffusìon-taxis model, analyzing the time evolution of the biomass concentration along a water column. The model is based on two stochastic differentìal equations, where the random fluctuations of the environmental variables are considered by inserting two multiplicative noise terms. Specifically, the model describes the dynamics of diffusion of picophytoplankton biomass and nutrient concentrations. In the proposed model the marine environment is characterized by poorly mixed waters and picophytoplankton is subject to intraspecific competition for light and nutrients. By numerically solvin…

marine ecosystemSpatial ecologyrandom processeSpatial ecology; marine ecosystems; phytoplankton dynamics; deep chlorophyll maximum; random processes; stochastic differential equationsdeep chlorophyll maximumphytoplankton dynamicstochastic differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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A stochastic reaction-diffusion-taxis model for two picophytoplankton populations

2012

In this work, the stationary distributions of two populations of picophytoplankton, i.e. picoeukaryotes and Prochlorococcus, are studied. This two groups account on average for 60% of the total chlorophyll a (chl a) and divinil chlorophyll a (divinil chl a) concentration in Mediterranean Sea. The interaction of these populations with the environment occurs through two factors that limit the growth of the aquatic microorganisms: light intensity and nutrient, i.e. phosphorus. The dynamics of the two picophytoplanktonic groups, distributed at different depth along a water column (one-dimensional spatial domain), is analyzed starting from a deterministic reaction-diffusion-taxis model. This con…

marine ecosystemspatial ecologyspatial ecology; marine ecosystems; phytoplankton dynamics; deep chlorophyll maximum; random processes; stochastic differential equationsrandom processedeep chlorophyll maximumphytoplankton dynamicstochastic differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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