Spatial and temporal trends of organic contaminants in sediments along the Korean coast were estimated through a nationwide environmental monitoring program from 2001 to 2007. The concentrations of organic contaminants in sediments along the Korean coast were relatively low or moderate compared with foreign studies. The mean detection frequencies of organic contaminants during the seven years were highest for PAHs and PCDD/Fs, followed by PCBs, DDTs, TBT and HCHs in decreasing order. Based on published sediment quality guidelines, the ecological risks of persistent organic pollutants in sediments along the Korean coast were low, despite exceedances of the ERL at 2–6 sites for DDTs, and the TEL at 9–18 sites for PCDD/Fs. Nonparametric tests to assess temporal trends revealed significant decreasing trends for PCBs and PCDD/Fs at four and three sites, respectively (p<0.05). These results reflect the effects of regulations on the use of those contaminants.

Pterois volitans and Pterois miles, two sub-species of lionfish, have become the first non-native, invasive marine fish established along the United States Atlantic coast and Caribbean. The route and timing of the invasion is poorly understood, however historical sightings and captures have been robustly documented since their introduction. Herein we analyze these records based on spatial location, dates of arrival, and prevailing physical factors at the capture sights. Using a cellular automata model, we examine the relationship between depth, salinity, temperature, and current, finding the latter as the most influential parameter for transport of lionfish to new areas. The model output is a synthetic validated reproduction of the lionfish invasion, upon which predictive simulations in other locations can be based. This predictive model is simple, highly adaptable, relies entirely on publicly available data, and is applicable to other species.

Antibiotic resistance in bacteria is a growing problem that is not only restricted to the clinical setting but also to other environments such as marine species that harbor antibiotic resistant bacteria and therefore may serve as reservoirs for antibiotic-resistance genetic determinants. The aim of this study was to evaluate antibiotic resistance phenotypes in enterococci isolated from fecal samples of gilthead seabream and the associated mechanisms of resistance. A collection of 118 samples were analyzed and 73 enterococci were recovered. The strains showed high percentages of resistance to erythromycin and tetracycline (58.9% and 17.8%, respectively). Lower level of resistance (<13%) was detected for quinupristin–dalfopristin, ampicillin, high-level-gentamicin, high-level-streptomycin, high-level-kanamycin, ciprofloxacin and chloramphenicol. The erm(B), tet(L) or tet(M), aac(6′)-aph(2″) and aph(3′)-IIIa genes were shown in isolates resistant to erythromycin, tetracycline, high-level gentamicin and high-level kanamycin, respectively. Antibiotic resistance in natural microbiota is becoming a concern of human and environmental health.

From 2006 to 2008, microbial water quality was monitored along the Georgian coast of the Black Sea. Temperature, pH, salinity, and dissolved oxygen were measured, along with a variety of aquatic microbial parameters, including heterotrophic plate count (HPC), total culturable bacterial count (TCBC), and chlorophyll a (Chl-a) concentration. Total and fecal coliforms and total enterococci counts were recorded as indicators of fecal pollution. Vibrio bacteria, and Escherichia coli- and Vibrio-specific bacteriophages were isolated and enumerated to determine their relationships to standard marine pollution indicators. Persistent microbial pollution was observed, particularly in the summer months, with a higher rate of contamination in estuaries. Microbial indicators generally showed seasonal dependence, suggesting that temperature may influence bacterial dynamics in this environment. No correlation was apparent between fecal pollution indicators and physical–chemical and aquatic microbial parameters, although there were significant relationships amongst the indicators themselves, as well as with the prevalence of Vibrio bacteria and phage.

Knowledge of oil-induced impacts from the literature and experts were used to develop a Bayesian network to evaluate the biological consequences of an oil accident in the low-saline Gulf of Finland (GOF). Analysis was carried out for selected groups of organisms. Subnetworks were divided into subgroups according to a predicted response to oil exposure. Two scenario analyses are presented: the most probable and the worst-case accident. The impact of the most probable accident in the GOF is rather small. In most of the groups studied oil-induced long-term effects are evaluated to be minor at least from the perspective of the whole GOF. After the worst-case accident negative effects are more likely. The model predicts that the most vulnerable groups are auks and ducks. Amphipods, gulls and to a lesser extend littoral fishes and seals may show delayed recovery after an accident. Also annual plant species may be susceptible to oil-induced disturbances.

In Tolo Harbour, Hong Kong, where hypoxia occurs periodically, a large amount of benthic epifauna was found to be absent in the summer but become abundant again in the winter. This observation may indicate that some species are sensitive in detecting low dissolved oxygen (DO) levels and are able to escape from the harbour to more oxygenated, open waters when conditions deteriorate and return when DO levels are improved. Analysis of biological traits of these animals showed that 58% of the categories showed significant differences between the community structure in summer and winter. The significant biological traits of the few species, which remained in the harbour under the summer’s hypoxic conditions suggested adaptation rather than opportunism to the low DO levels. Our data also showed that trawling can increase DO at the bottom and may benefit the less sensitive species that remained in the habitat during the summer.

Herein we present results from one of the first extensive bay-wide oceanographic surveys of Manila Bay, wherein 31 stations were sampled during the northeast monsoon (cold and dry season). A band of hypoxic bottom water (dissolved oxygen <2.8mg/L) spanned the midsection of the bay from east to west. Bottom nitrate concentrations (5.7–16.8μM; avg. 11.1μM) and total organic carbon values in sediments (1.7–3.1%; avg. 2.4%) were high in the midsection, which coincided with the band of hypoxic bottom water. Physical processes and site-specific accumulation of organic material likely lead to hypoxic conditions in Manila Bay, even during the northeast monsoon period when the water column is relatively well mixed. The results of this study complement the previously reported widespread hypoxia that occurs during the rainy season. Thus, hypoxia may be pervasive in the bay throughout the year, although it varies in intensity and spatial extent.

Phytoplankton diversity, primary and bacterial production, nutrients and metallic contaminants were measured during the wet season (July) and dry season (March) in the Bach Dang Estuary, a sub-estuary of the Red River system, Northern Vietnam. Using canonical correspondence analysis we show that phytoplankton community structure is potentially influenced by both organometallic species (Hg and Sn) and inorganic metal (Hg) concentrations. During March, dissolved methylmercury and inorganic mercury were important factors for determining phytoplankton community composition at most of the stations. In contrast, during July, low salinity phytoplankton community composition was associated with particulate methylmercury concentrations, whereas phytoplankton community composition in the higher salinity stations was more related to dissolved inorganic mercury and dissolved mono and tributyltin concentrations. These results highlight the importance of taking into account factors other than light and nutrients, such as eco-toxic heavy metals, in understanding phytoplankton diversity and activity in estuarine ecosystems.

Due to increasing global population, salt marshes have been subjected to multiple stressors such as increasing nutrient loadings and historical contamination. In order to better understand how does the salt marsh plants auto-remediation capacity (phytoaccumulation of metals) is affected by cultural eutrophication, an experiment was performed under controlled conditions. Plants were exposure to equal metal concentrations (Zn, Cu, and Ni – micronutrients, and Cd – class B metal) simulating historical contamination and three different concentrations of nitrogen (nitrate) simulating steps of cultural eutrophication. According to our study, under the tested concentrations, cultural eutrophication does not seem to affect Zn, Cu and Ni phytoremediation of H. portulacoides, but the ecosystem service of Cd phytoremediation seems to be promoted. Nevertheless, Cd high toxicity and bioaccumulation should be taken into account, as well as the vulnerability of salt marsh ecosystems, whose reduction will have drastic consequences to the ecosystem health.

Combining GIS with neuro-fuzzy modeling has the advantage that expert scientific knowledge in coastal aquaculture activities can be incorporated into a geospatial model to classify areas particularly vulnerable to pollutants. Data on the physical environment and its suitability for aquaculture in an Irish fjard, which is host to a number of different aquaculture activities, were derived from a three-dimensional hydrodynamic and GIS models. Subsequent incorporation into environmental vulnerability models, based on neuro-fuzzy techniques, highlighted localities particularly vulnerable to aquaculture development. The models produced an overall classification accuracy of 85.71%, with a Kappa coefficient of agreement of 81%, and were sensitive to different input parameters. A statistical comparison between vulnerability scores and nitrogen concentrations in sediment associated with salmon cages showed good correlation. Neuro-fuzzy techniques within GIS modeling classify vulnerability of coastal regions appropriately and have a role in policy decisions for aquaculture site selection.