Dynamics of Two Picophytoplankton Groups in Mediterranean Sea: Analysis of the Deep Chlorophyll Maximum by a Stochastic Advection-Reaction-Diffusion Model

Abstract

A stochastic advection-reaction-diffusion model with terms of multiplicative white Gaussian noise, valid for weakly mixed waters, is studied to obtain the vertical stationary spatial distributions of two groups of picophytoplankton, i.e., picoeukaryotes and Prochlorococcus, which account about for 60% of total chlorophyll on average in Mediterranean Sea. By numerically solving the equations of the model, we analyze the one-dimensional spatio-temporal dynamics of the total picophytoplankton biomass and nutrient concentration along the water column at different depths. In particular, we integrate the equations over a time interval long enough, obtaining the steady spatial distributions for the cell concentrations of the two picophytoplankton groups. The results are converted into chlorophyll a and divinil chlorophyll a concentrations and compared with experimental data collected in two different sites of the Sicily Channel (southern Mediterranean Sea). The comparison shows 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.

Stochastic models for phytoplankton dynamics in Mediterranean Sea

“…This could help to devise strategies to prevent the decline of the primary production (phytoplankton biomass), with the consequent decrease of fish species due to the global warming (Kiorboe, 2008;Denaro et al, 2013b;Denaro, 2014;Valenti et al, 2015).…”

“…For this purpose, in the present work we discuss some findings obtained within the context of the spatiotemporal dynamics of phytoplankton populations in Mediterranean Sea, presenting in the last section new results obtained by a stochastic five-population model. Here oligotrophic conditions are guaranteed during the whole year and phosphorus is the nutrient component playing the role of limiting factor for the growth of the phytoplankton communities (Thingstad and Rassoulzadegan, 1995;Ribera d'Alcalà et al, 2003;Denaro et al, 2013b;Valenti et al, 2015). The theoretical approach is based on stochastic advection-reaction-diffusion models, which allows to analyze and reproduce the vertical profiles of chlorophyll a concentration obtained from data collected in two sites of the Mediterranean Sea, during different oceanographic surveys in the period from 22 August 2006 to 9 June 2007.…”

The role of noise on the steady state distributions of phytoplankton populations

“…Accordingly, in this paper we study the spatio-temporal behaviour of phytoplankton populations by using a stochastic model. This allows the reproduction of the experimental profiles of the chlorophyll a concentration collected during dierent oceanographic surveys [3,4,15,[17][18][19].…”

“…The biological parameters have been fixed within specific ranges of values, according to the theoretical and experimental results reported in previous works [37,49,50,54,[69][70][71][72][73][74][75][76][77][78][79]. In the present study, we intend to choose the values of the parameters within these ranges in such a way as to guarantee the coexistence of all picophytoplankton populations [15,19,35,55,59] along the water column with the environmental conditions observed during the whole period investigated. For this purpose, we perform a preliminary analysis (results here not reported), which indicates that the dierent values of half-saturation constants, K R i and K I i , and nutrient contents, 1/Y i , cause significant modifications in the stationary distributions of the phytoplankton cell concentrations.…”

Impact of two types of time delays and cross-correlated multiplicative and additive noises on stability and stochastic resonance for a metapopulation system

“…In the meantime, it appears that the combination of time delay and noise is ubiquitous in nature and often changes fundamentally the dynamics of the system [27][28][29][30][31] . More works on stochastic resonance and the transition time between the stable states for the biological systems induced by noise sources can be found in Refs [48][49][50][54][55][56][57][58][59][60][61][62] .…”