A novel application of and an adaptable modeling approach to the management of toxic microalgal bloom events in coastal areas.

Harmful algal blooms have been increasing in frequency in recent years, and attention has shifted from describing to modeling and trying to predict these phenomena, since in many cases they pose a risk to human health and coastal activities. Predicting ecological phenomena is often time and resource consuming, since a large number of field collected data are required. We propose a novel approach that involves the use of modeled meteorological data as input features to predict the concentration of the toxic benthic dinoflagellate Ostreopsis cf. ovata in seawater. Ten meteorological features were used to train a Quantile Random Forests model, which was then validated using field collected concentration data over the course of a summer sampling season. The proposed model was able to accurately describe Ostreopsis abundance in the water column in response to meteorological variables. Furthermore, the predictive power of this model appears good, as indicated by the validation results, especially when the quantile for predictions is tuned to match management requirements. The Quantile Random Forests method was selected, as it allows for greater flexibility in the generated predictions, thus making this model suitable as a tool for coastal management. The application of this approach is novel, as no other models or tools that are adaptable to this degree are currently available. The model presented here was developed for a single species over a limited geographical extension, but its methodological basis appears flexible enough to be applied to the prediction of HABs in general and it could also be extended to the case of other ecological phenomena that are strongly dependent on meteorological drivers, that can be independently modeled and potentially globally available

Heavy metals in coastal sediments of the Ligurian sea off Vado Ligure

This paper combines data from a survey on heavy metal contamination of surficial sediments and the analysis of a short sediment core (30 cm) carried out in 1999 and 2001, respectively. Heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn) and Al were analysed by AAS after complete dissolution of the samples. Surficial sediments are particularly rich in Cr, Cu, Hg and Pb, which reach concentrations of 322, 47.0, 5.85 and 145 mg kg$^{-1}$, respectively. While most metals show high concentrations close to the built-up area, the maximum values of Cr characterise offshore samples, thus suggesting a different origin. Sediment accumulation rates and chronologies were calculated on the basis of both $^{137}$Cs and $^{210}$Pb activity-depth profiles. The depth distribution of Al is peculiar, showing several peaks (from ca. 17 to ca. 106 mg g$^{-1}$) that are not justified by changes in sediment grain size and mineralogical composition. Very recent inputs of Cr and Ni are accounted for by surficial peak values, whereas Hg and Cu reach high concentrations at depth in core (before the early 1960s) and then decrease. Cu shows also a recent peak. Sediment grain size as well as organic carbon content do not seem to be correlated and significantly influence the metal distributions. Hg concentrations exceed the ERM guidelines all over the study area, whereas Cr is higher than the ERM at the top of the core. Only Cd is always lower than the ERL guidelines

Simulations of dredged sediment spreading on a Posidonia oceanica meadow off the Ligurian coast, Northwestern Mediterranean

The sandy deposits from dredging can have negative effects on the environment such as increase in suspended solids in the water column and their consequent transport. An experimental study was conducted to characterize water masses, dynamics, and sedimentation rates on the Ligurian continental shelf (Italy), where both a sand deposit, that could be used for beach nourishment, and a nearby Posidonia oceanica meadow coexist. The environmental plan provides a mathematical simulation of the sediment-dispersion to evaluate the possible impact on the meadow. It has been calculated that the dredging could double the concentration of suspended particles, but its scheduling will preclude a sediment accumulation. All the information obtained from this work will be used to study the environmental feasibility of the sand deposit exploitation and as starting point for drawing up the monitoring plan in case of dredging