Morphology of the submerged Ferdinandea Island, the ‘Neverland’ of the Sicily Channel (central Mediterranean Sea)

We present the bathy-morphological map at a scale of 1: 50,000 of the area around the submerged Ferdinandea Island, the ‘Neverland’ of the Sicily Channel (central Mediterranean Sea). We investigate an area of 100 km2, between 10 and 350 m, which is part of a triangular morphological high, 360 km2 wide, representing the SE-wards prolongation of the Adventure Bank. The study is based on the morphometric analysis based on high resolution multibeam, and sub-bottom CHIRP profiles collected in 2015. The area around the remains of Ferdinandea Island is morphologically shaped by the interplay between volcanic, tectonic, fluid seepage, and oceanographic processes. Since the study area is considered a hot spot of biodiversity affected by maritime traffic (especially in Ferdinandea Channel) and hosting communication pipelines, this map provides insights both for habitat mapping purposes and preliminary marine geohazard assessment due to the occurrence of historically active submarine volcanoes, pockmarks, and mass transport deposits

Noise Induced Phenomena in the Dynamics of Two Competing Species

Noise through its interaction with the nonlinearity of the living systems can give rise to counter-intuitive phenomena. In this paper we shortly review noise induced effects in different ecosystems, in which two populations compete for the same resources. We also present new results on spatial patterns of two populations, while modeling real distributions of anchovies and sardines. The transient dynamics of these ecosystems are analyzed through generalized Lotka-Volterra equations in the presence of multiplicative noise, which models the interaction between the species and the environment. We find noise induced phenomena such as quasi-deterministic oscillations, stochastic resonance, noise delayed extinction, and noise induced pattern formation. In addition, our theoretical results are validated with experimental findings. Specifically the results, obtained by a coupled map lattice model, well reproduce the spatial distributions of anchovies and sardines, observed in a marine ecosystem. Moreover, the experimental dynamical behavior of two competing bacterial populations in a meat product and the probability distribution at long times of one of them are well reproduced by a stochastic microbial predictive model.Comment: 23 pages, 8 figures; to be published in Math. Model. Nat. Phenom. (2016

Spatio-temporal dynamics of a planktonic system and chlorophyll distribution in a 2D spatial domain: matching model and data

Field data on chlorophyll distribution are investigated in a two-dimensional spatial domain of the Mediterranean Sea by using for phytoplankton abundances an advection-diffusion-reaction model, which includes real values for physical and biological variables. The study exploits indeed hydrological and nutrients data acquired in situ, and includes intraspecific competition for limiting factors, i.e. light intensity and phosphate concentration. As a result, the model allows to analyze how both the velocity field of marine currents and the two components of turbulent diffusivity affect the spatial distributions of phytoplankton abundances in the Modified Atlantic Water, the upper layer of the water column of the Mediterranean Sea. Specifically, the spatio-temporal dynamics of four phytoplankton populations, responsible for about 80% of the total chlorophyll a, are reproduced. Results for phytoplankton abundances obtained by the model are converted in chlorophyll a concentrations and compared with field data collected in twelve marine sites along the Cape Passero (Sicily)- Misurata (Libya) transect. Statistical checks indicate a good agreement between theoretical and experimental distributions of chlorophyll concentration. The study can be extended to predict the spatio-temporal behaviour of the primary production, and to prevent the consequent decline of some fish species in the Mediterranean Sea

Stochastic models for phytoplankton dynamics in Mediterranean Sea

In this paper, we review some results obtained from three one-dimensional stochastic models, which were used to analyze picophytoplankton dynamics in two sites of the Mediterranean Sea. Firstly, we present a stochastic advection\u2013reaction\u2013diffusion model to describe the vertical spatial distribution of picoeukaryotes in a site of the Sicily Channel. The second model, which is an extended version of the first one, is used to obtain the vertical stationary profiles of two groups of picophytoplankton, i.e. Pelagophytes and Prochlorococcus, in the same marine site as in the previous case. Here, we include intraspecific competition of picophytoplanktonic groups for limiting factors, i.e. light intensity and nutrient concentration. Finally, we analyze the spatio-temporal behaviour of five picophytoplankton populations in a site of the Tyrrhenian Sea by using a reaction\u2013diffusion\u2013taxis model. The study is performed, taking into account the seasonal changes of environmental variables, obtained starting from experimental findings. The multiplicative noise source, present in all three models, mimics the random fluctuations of temperature and velocity field. The vertical profiles of chlorophyll concentration obtained from the stochastic models show a good agreement with experimental data sampled in the two marine sites considered. The results could be useful to devise a new class of models based on a stochastic approach and able to predict future changes in biomass primary production

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

The spatio-temporal behaviour of total chlorophyll concentration is investigated in the middle of the Tyrrhenian Sea by using a stochastic approach. The study is based on a reaction-diffusion-taxis model, which is used to analyse the dynamics of five phytoplankton groups, responsible for about 80% of the total chlorophyll a inside the euphotic zone of the water column. The analysis is performed by considering: (i) the intraspecific competition of the phytoplanktonic groups for limiting factors, i.e. light intensity and nutrient concentration, (ii) the seasonal changes of environmental variables, and (iii) the random fluctuations of the components of the velocity field and temperature. Specifically, we investigate the effects of external perturbations, both deterministic and random, on the dynamics of phytoplankton populations, by inserting a term of multiplicative noise into the differential equation of the nutrient dynamics. The theoretical results of the phytoplankton abundances obtained by the stochastic model are converted in chlorophyll a concentrations, and compared with the experimental findings. The statistical checks, based on the chi-square test, show that the vertical distributions of total chlorophyll concentration are in a good agreement with the experimental data. Finally, we observe that the high intensity of environmental noise strongly modifies the steady spatial distributions of two phytoplankton groups usually localized in deeper layers, causing algal blooms in surface water

Modeling of Sensory Characteristics Based on the Growth of Food Spoilage Bacteria

During last years theoretical works shed new light and proposed new hypothesis on the mechanisms which regulate the time behaviour of biological populations in different natural systems. Despite of this, a relevant physical and biological issue such as the role of environmental variables in ecological systems is still an open question. Filling this gap of knowledge is a crucial task for a deeper comprehension of the dynamics of biological populations in real ecosystems. The aim of this work is to study how dynamics of food spoilage bacteria influences the sensory characteristics of fresh fish specimens. This topic is worth of investigation in view of a better understanding of the role played by the bacterial growth on the organoleptic properties, and becomes crucial in the context of quality evaluation and risk assessment of food products. We therefore analyze and reproduce the time behaviour, in fresh fish specimens, of sensory characteristics starting from the growth curves of two spoilage bacterial communities. The theoretical study, initially based on a deterministic model, is performed by using the temperature profiles obtained during the experimental analysis. As a first step, a model of predictive microbiology is used to reproduce the experimental behaviour of the two bacterial populations. Afterwards, the theoretical bacterial growths are converted, through suitable differential equations, into "sensory" scores, based on the Quality Index Method (QIM), a scoring system for freshness and quality sensory estimation of fishery products. As a third step, the theoretical curves of QIM scores are compared with the experimental data obtained by sensory analysis. Finally, the differential equations for QIM scores are modified by adding terms of multiplicative white noise, which mimics the effects of uncertainty and variability in sensory analysis. A better agreement between experimental and theoretical QIM scores is observed, in some cases, in the presence of suitable values of noise intensity respect to the deterministic analysis