To improve the effectiveness of oil spill mitigation, we developed a rapid, logistically simple protocol to detect petrochemical stress on seagrass. Sections of leaf blades from Zostera muelleri subsp. capricorni were exposed to the water accommodated fraction (WAF) of non-dispersed and dispersed Tapis crude oil and fuel oil (IFO-380) for 5h. Photosynthetic health was monitored by assessing changes in effective quantum yield of photosystem II (ΔF/Fₘ ′) and chlorophyll a pigment concentrations. Loss of total petroleum hydrocarbons (TPH) was measured using an oil-in-water fluorometer, whilst GC–MS analyses quantified the hydrocarbon components within each treatment. Few significant differences were detected in the chlorophyll a pigment analyses; however, ΔF/Fₘ ′ appeared sensitive to petrochemical exposure. Dispersing both types of oil resulted in a substantial increase in the TPH of the WAF and was generally correlated with a greater physiological impact to the seagrass health, compared with the oil alone.

The environmental characteristics of Ahe deep lagoon (Tuamotu Archipelago, French Polynesia) were studied over 3years with the aim of explaining the spatial and temporal variability of the natural food available for pearl oysters with a special focus on phytoplankton biomass and global photosynthesis/respiration ratio of the lagoon. Chlorophyll averaged 0.34±0.01μgL⁻¹ and our findings did not confirm increased phytoplankton biomass in deep lagoonal waters. Phytoplankton production appears to be limited firstly by nitrogen and respiratory processes overpass photosynthetic processes at least in the north-eastern edge of the atoll. Grazing by pearl oysters in culture seems to decrease the POC concentration but not the phytoplankton biomass. Oysters graze mainly on non chlorophyllian particles.

Photo-acclimatisation by the algal endosymbionts of scleractinian corals to changes in environmental conditions may influence their density and/or the concentration of photosynthetic pigments, and hence coral brightness, on short time-scales. To examine coral pigmentation as a bioindicator of water quality, the brightness of massive corals was quantified using colour charts, concentrations of the pigment chlorophyll a and reflectance spectrometry in the field and with manipulative experiments. Along a water quality gradient, massive Porites became progressively lighter as nutrients decreased and irradiance increased. A laboratory experiment showed that Porites nubbins darkened within 25days following exposure to reduced water quality. The results of a transplantation experiment of Porites nubbins in a manipulation incorporating multiple depths and zones of water quality confirmed colony brightness as a simple tool to monitor changes in marine water quality, provided effects due to other influences on pigmentation, e.g. seawater temperatures, are taken into consideration.

The dispersion of ¹³⁷Cs released from Fukushima nuclear power plant to the sea after the March 11th 2011 tsunami has been studied using numerical models. The 3D dispersion model consists of an advection/diffusion equation with terms describing uptake/release reactions between water and seabed sediments. The dispersion model has been fed with daily currents provided by HYCOM and JCOPE2 ocean models. Seabed sediment ¹³⁷Cs patterns obtained using both current data set have been compared. The impact of tides and of atmospheric deposition has been evaluated as well. It has been also found that a 2-step kinetic model (two consecutive reversible reactions) for describing water/sediment interactions produces better results than a 1-step model (one single reversible reaction).

In north Western Australia coral reefs occur near ports being developed to support rapidly expanding resources industries. Dredging for port construction is required to stop during significant mass coral spawning events due to the sensitivity of gametes and larvae to increases in turbidity and sedimentation, but the timing of this event can vary between seasons and years so monitoring is used to predict when spawning is imminent. Here we used simulations to mimick sampling strategies currently used in some coral spawning monitoring programmes in Western Australia, to assess the ability of these programmes to be able to predict multi-specific mass spawning events. We found that current practices may sometimes miss spawning events that are likely to be considered large enough to warrant stopping dredging. Generally, sampling fewer individuals in a large number of species is a better way of monitoring for upcoming spawning than sampling a large number of individuals in a small number of species, but overall, greater sampling efforts than are currently undertaken are needed if moderately sized events are to be detected reliably. Determining exactly how many samples are needed, however, depends on having a clearer definition of what actually constitutes a “significant mass spawning” event in the first place.

At-sea detection of marine debris presents a difficult problem, as the debris items are often relatively small and partially submerged. However, they may accumulate in water parcel boundaries or eddy lines. The application of models, satellite radar and multispectral data, and airborne remote sensing (particularly radar) to focus the search on eddies and convergence zones in the open ocean appear to be a productive avenue of investigation. A multistage modeling and remote sensing approach is proposed for the identification of areas of the open ocean where debris items are more likely to congregate. A path forward may best be achieved through the refinement of the Ghost Net procedures with the addition of a final search stage using airborne radar from an UAS simulator aircraft to detect zones of potential accumulation for direct search. Sampling strategies, direct versus indirect measurements, remote sensing resolution, sensor/platform considerations, and future state are addressed.

This article describes design and application of feed-forward, fully-connected, three-layer perceptron neural network model for computing the water quality index (WQI)¹ for Kinta River (Malaysia). The modeling efforts showed that the optimal network architecture was 23-34-1 and that the best WQI predictions were associated with the quick propagation (QP) training algorithm; a learning rate of 0.06; and a QP coefficient of 1.75. The WQI predictions of this model had significant, positive, very high correlation (r=0.977, p<0.01) with the measured WQI values, implying that the model predictions explain around 95.4% of the variation in the measured WQI values. The approach presented in this article offers useful and powerful alternative to WQI computation and prediction, especially in the case of WQI calculation methods which involve lengthy computations and use of various sub-index formulae for each value, or range of values, of the constituent water quality variables.

UVF may occur in the aquatic environment through two principal sources: direct inputs from recreational activities and indirect wastewater- and river-borne inputs. The aim of this study was to obtain a first overview of levels of three UVF (EHMC, OC and OD-PABA) in coastal areas subjected to river inputs, untreated wastewater discharges and dumpsite leachates. We selected three eastern Mediterranean rivers that have been impacted for decades by untreated wastewater release and collected sediment in the coastal zone during the hot and humid seasons. Western Mediterranean sites receiving treated wastewaters were analyzed for comparison. The results gave an overview of sediment contamination under these two contrasted situations representative of Mediterranean coastal areas without bathing activities. The analysis of the three UVF revealed the ubiquity and high point source contamination by EHMC and OC in transition and coastal zones, with levels as high as 128ngg⁻¹d.w. OD-PABA was also frequently detected, but at lower concentrations (<LOD-17ngg⁻¹d.w.). A temporal trend was observed, with a higher sediment concentration in the dry period (August and October). Based on these results, we conclude that there is background contamination from river input that could be exacerbated by the direct contribution in coastal bathing zones.

Organotin compounds (OTs) are ubiquitous in the marine environment and high concentrations (μgg⁻¹ range) in sediments from different coastal areas around the world have been reported. However, few reports have described the OTs contamination status in the offshore and deep sea environment. This work investigated organotin levels in Nazaré canyon for the first time. Levels of monobutyltin (MBT), dibutyltin (DBT), tributyltin (TBT), diphenyltin (DPT), triphenyltin (TPT), dioctyltin (DOT) and trioctyltin (TOT) were quantified in sediment samples from the upper flanks of the canyon and from the adjacent coastal area. TBT levels detected in the canyon flanks are about two to three orders of magnitude lower than those found in the coastal area. Nevertheless, when quantifiable, TBT levels in the canyon samples were higher than the Environmental Assessment Criteria set for TBT in sediments by the OSPAR Commission indicating that at those locations negative ecological impacts are likely to occur.

Biological markers of produced water (PW) exposure were studied in Atlantic cod (Gadus morhua) in both laboratory and field experiments, using authentic PW from a North Sea oil field. In the laboratory study, the PW exposure yielded significantly elevated levels of metabolites of polycyclic aromatic hydrocarbons (PAHs) and alkylphenols (APs) in bile even at the lowest exposure dose (0.125% PW). Other biomarkers (hepatic CYP1A induction and DNA adduct formation) responded at 0.25% and 0.5% PW concentrations. In the field study, bile metabolite markers and hepatic CYP1A were clearly increased in fish caged close to the PW outfall. Induction of plasma vitellogenin was not found in laboratory or field exposures, suggesting that the levels of oestrogen agonists (such as APs) might not have been sufficient to elicit induction, under the present conditions. The applicability of the biomarkers for use in water column biomonitoring programs is discussed.