In this thesis, the stochastic advection-reaction-diffusion models are analyzed to obtain the vertical stationary spatial distributions of the main groups of picophytoplankton, which account about for 80% of total chlorophyll on average in Mediterranean Sea. In Chapter 1 we give a short presentation of the experimental and phytoplanktonic data collected during different oceanographic surveys in Mediterranean Sea. In Chapter 2 we introduce the deterministic and stochastic approaches (one-population model) adopted to describe the picoeukaryotes dynamics in Sicily Channel. Moreover, numerical results for the biomass concentration are compared with experimental data by using chi-squared goodness-of-fit test. In Chapter 3 we modify the previous one-population model to study the population dynamics of two picophytoplankton groups, i.e. picoeukaryotes and picoprokaryotes (Prochlorococcus). The agreement between theoretical results and experimental findings is checked by using two comparative methods: chi-squared goodness-of-fit test and Kolmogorov-Smirnov (K-S) test. In Chapter 4 we introduce a deterministic model used to perform the spatio-temporal analysis of five picophytoplankton species sampled in a site of the Tyrrhenian Sea: numerical results are compared with experimental data acquired during different oceanographic surveys in the period from 24 November 2006 to 9 June 2007. The models investigated in the chapters 2, 3 and 4, show that real distributions are well reproduced by theoretical profiles. Specifically, position, shape and magnitude of the theoretical deep chlorophyll maximum exhibit a good agreement with the experimental values. Finally, conclusions and future prospects of this thesis are discussed.
Denaro, G. (2014). Stochastic models for phytoplankton dynamics in marine ecosystems.
|Titolo:||Stochastic models for phytoplankton dynamics in marine ecosystems|
|Altri titoli:||Modelli stocastici di dinamica di fitoplancton negli ecosistemi marini|
|Data di pubblicazione:||24-feb-2014|
|Citazione:||Denaro, G. (2014). Stochastic models for phytoplankton dynamics in marine ecosystems.|
|Appare nelle tipologie:||4.2 Tesi di dottorato|