Quantifying the topographical structure of rocky and coral seabeds.

Describing the structural complexity of seabeds is of primary importance for a number of geomorphological, hydrodynamical and ecological issues. Aiming to bring a decisive insight on the long-term development of a unified view, the present study reports on a comparative multi-site analysis of high resolution topography surveys in rough nearshore environments. The nine study sites have been selected to cover a wide variety of topographical features, including rocky and coral seabeds.

SMOTE-CD: SMOTE for compositional data.

Compositional data are a special kind of data, represented as a proportion carrying relative information. Although this type of data is widely spread, no solution exists to deal with the cases where the classes are not well balanced. After describing compositional data imbalance, this paper proposes an adaptation of the original Synthetic Minority Oversampling TEchnique (SMOTE) to deal with compositional data imbalance.

Effects of Biofilms and Particle Physical Properties on the Rising and Settling Velocities of Microplastic Fibers and Sheets.

Vertical dynamics of microplastics (MPs) in the water column are complex and not fully understood due to the diversity of environmental MPs and the impact of weathering and biofouling on their dynamical properties. In this study, we investigate the effects of the particle properties and biofilm on the vertical (settling or rising) velocity of microplastic sheets and fibers under laboratory conditions. The experiments focus on three types of MPs (polyester PES fibers, polyethylene terephthalate PET sheets, and polypropylene PP sheets) of nine sizes and two degrees of biological colonization.

Microplastics in a salt-wedge estuary: Vertical structure and tidal dynamics.

The abundance and distribution of microplastics in estuaries have been barely documented, and generally without accounting for the vertical structure in the water column. This study presents the very first data on the occurrence and distribution of microplastics in the Adour Estuary, SW France. The experimental data set was complemented by numerical simulations to gain understanding of the behaviour of suspended microplastics.

Detecting Technical Anomalies in High-Frequency Water-Quality Data Using Artificial Neural Networks.

Anomaly detection (AD) in high-volume environmental data requires one to tackle a series of challenges associated with the typical low frequency of anomalous events, the broad-range of possible anomaly types, and local nonstationary environmental conditions, suggesting the need for flexible statistical methods that are able to cope with unbalanced high-volume data problems. Here, we aimed to detect anomalies caused by technical errors in water-quality (turbidity and conductivity) data collected by automated in situ sensors deployed in contrasting riverine and estuarine environments. We first applied a range of artificial neural networks that differed in both learning method and hyperparameter values, then calibrated models using a Bayesian multiobjective optimization procedure, and selected and evaluated the "best" model for each water-quality variable, environment, and anomaly type.

Behaviour of plastic litter in nearshore waters: First insights from wind and wave laboratory experiments.

Plastic litter in nearshore waters is an environmental pollutant with increasing impact on coastal environments. At present, knowledge on basic plastic particle dynamics and the interaction with complex hydrodynamics is lacking. The present laboratory study, performed under controlled wave and wind conditions, demonstrates the dispersion of plastics in shallow waters.