Spatiotemporal changes of pelagic food webs investigated by environmental DNA metabarcoding and connectivity analysis.

Environmental DNA metabarcoding (eDNA metaB) is fundamental for monitoring marine biodiversity and its spread in coastal ecosystems. We applied eDNA metaB to seawater samples to investigate the spatiotemporal variability of plankton and small pelagic fish, comparing sites with different environmental conditions across a coast-to-offshore gradient at river mouths along the Campania coast (Italy) over 2 years (2020-2021). We found a marked seasonality in the planktonic community at the regional scale, likely owing to the hydrodynamic connection among sampling sites, which was derived from numerical simulations. Nonetheless, spatial variability among plankton communities was detected during summer. Overall, slight changes in plankton and fish composition resulted in the potential reorganization of the pelagic food web at the local scale. This work supports the utility of eDNA metaB in combination with hydrodynamic modelling to study marine biodiversity in the water column of coastal systems. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Numerical investigation of the three-dimensional paths of plastic polymers in the Gulf of Naples.

The high-resolution Campania Regional Ocean Model (CROM), coupled with an online Lagrangian particle tracking algorithm, is used to investigate the horizontal and vertical behavior of different (in terms of size and density) plastic polymer types during February and August 2016 in the Gulf of Naples. The transport of passive particles is evaluated based on the three-dimensional Eulerian velocity fields provided by the ocean model. The virtual particles are released in several hot spot areas in the Gulf of Naples where most of the marine debris is supposed to come from. A sensitivity analysis on the vertical sinking for negatively buoyant particles is carried out. The sinking behavior is determined by the settling velocity, which depends on the physical properties of the individual litter item as well as on the hydrodynamical features of the marine environment. Different numerical experiments are carried out to evaluate the effect of marine dynamics on three-dimensional transport.

Numerical-ecotoxicological approach to assess potential risk associated with oilfield production chemicals discharged into the sea.

Several different chemical products are used on oil platforms to aid oil-water separation during the production process. These chemicals may enter into the sea by means of production water (PW), the main discharge derived from oil and gas offshore platforms. Consequently, toxic effects may occur in the marine environment, causing reductions in wildlife numbers, degrading ecosystem functions and threatening human health. For most of these chemicals, environmental toxicity and safety thresholds in marine ecosystems have not been fully investigated as yet. In this work, a numerical-ecotoxicological approach is proposed to assess the potential environmental risk associated with the discharge of five oilfield production chemicals (deoiler, scale inhibitor, corrosion inhibitor, catalyst, dehydrating agent) from a platform in the southern Adriatic Sea (Mediterranean Sea). Their concentrations in the seawater are numerically predicted, under different seasonal conditions, starting from the real concentrations used during the production process. The predicted concentrations are then evaluated in terms of possible toxic effects in order to assess the potential risk of oilfield production chemicals discharged into the sea.

Disentangling physical and biological drivers of phytoplankton dynamics in a coastal system.

This proof-of-concept study integrates the surface currents measured by high-frequency coastal radars with plankton time-series data collected at a fixed sampling point from the Mediterranean Sea (MareChiara Long Term Ecological Research site in the Gulf of Naples) to characterize the spatial origin of phytoplankton assemblages and to scrutinize the processes ruling their dynamics. The phytoplankton community generally originated from the coastal waters whereby species succession was mainly regulated by biological factors (life-cycle processes, species-specific physiological performances and inter-specific interactions). Physical factors, e.g. the alternation between coastal and offshore waters and the horizontal mixing, were also important drivers of phytoplankton dynamics promoting diversity maintenance by i) advecting species from offshore and ii) diluting the resident coastal community so as to dampen resource stripping by dominant species and thereby increase the numerical importance of rarer species. Our observations highlight the resilience of coastal communities, which may favour their persistence over time and the prevalence of successional events over small time and space scales. Although coastal systems may act differently from one another, our findings provide a conceptual framework to address physical-biological interactions occurring in coastal basins, which can be generalised to other areas.

On the relationship between fractal dimension and encounters in three-dimensional trajectories.

The encounter of individuals-prey, predators and mates-living in the surrounding environment is a fundamental process in the life of an organism. Along with the sensory abilities, this process will be regulated by the movement rules adopted by the individual. In this work we discuss the encounter-enhancement effect due to different natatorial modes by calculating the number of encounters realised by differently convoluted trajectories in two homogeneous distributions of particles. Using numerically generated trajectories representative of specific swimming behaviour, we demonstrate that high values of three-dimensional fractal dimension D(3D)(>1.9) are beneficial only at high concentration, whereas at low concentration less tortuous tracks (D(3D) approximately 1.5) are almost equally efficient. In the light of our results it is possible to better understand the behavioural adaptations evolved by individuals to thrive in their environment.