0000000000362594
AUTHOR
Cosimo Solidoro
Stochastic 0-dimensional Biogeochemical Flux Model: Effect of temperature fluctuations on the dynamics of the biogeochemical properties in a marine ecosystem
Abstract We present a new stochastic model, based on a 0-dimensional version of the well known biogeochemical flux model (BFM), which allows to take into account the temperature random fluctuations present in natural systems and therefore to describe more realistically the dynamics of real marine ecosystems. The study presents a detailed analysis of the effects of randomly varying temperature on the lower trophic levels of the food web and ocean biogeochemical processes. More in detail, the temperature is described as a stochastic process driven by an additive self-correlated Gaussian noise. Varying both correlation time and intensity of the noise source, the predominance of different plank…
Effects of solar irradiance noise on a complex marine trophic web
AbstractThe analysis of experimental data of the solar irradiance, collected on the marine surface, clearly highlights the intrinsic stochasticity of such an environmental parameter. Given this result, effects of randomly fluctuating irradiance on the population dynamics of a marine ecosystem are studied on the basis of the stochastic 0-dimensional biogeochemical flux model. The noisy fluctuations of the irradiance are formally described as a multiplicative Ornstein-Uhlenbeck process, that is a self-correlated Gaussian noise. Nonmonotonic behaviours of the variance of the marine populations’ biomass are found with respect to the intensity and the autocorrelation time of the noise source, ma…
Changes of energy fluxes in marine animal forests of the anthropocene: Factors shaping the future seascape
12 pages, 3 figures
The Synergistic Impacts of Anthropogenic Stressors and COVID-19 on Aquaculture: A Current Global Perspective
13 pages, 6 figures, 2 tables.-- This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License
Random Forest model and TRIX used in combination to assess and diagnose the trophic status of Bizerte Lagoon, southern Mediterranean
International audience; A combined multimetric trophic index (TRIX) and the Random Forest (RF) model were used to characterize the trophic status of Bizerte Lagoon. The RF model was used to build a predictive model of chlorophyll a using physicochemical variables (nitrite, nitrate, ammonium, phosphate, oxygen, temperature and salinity) as predictors. The approach is based on physicochemical and biological parameters measured in samples collected twice weekly from January to December 2012 at one representative sampling station located at the lagoon center.The observed TRIX values vary from 5.18 to 6.12, reflecting waters ranging from moderate to poor quality with a high trophic level. The re…
Machine learning predictions of trophic status indicators and plankton dynamic in coastal lagoons
Abstract Multivariate trophic indices provide an efficient way to assess and classify the eutrophication level and ecological status of a given water body, but their computation requires the availability of experimental information on many parameters, including biological data, that might not always be available. Here we show that machine learning techniques – once trained against a full data set – can be used to infer plankton biomass information from chemical and physical parameter only, so that trophic index can then be computed without using additional biological data. More specifically, we reconstruct plankton information from chemical and physical data, and this information together w…