International audience | <div><p>Aquaculture is crucial in meeting global seafood demand; however, intensification often leads to bacterial diseases that threaten productivity. Dicentrarchus labrax, a key species in European aquaculture, is highly vulnerable to vibriosis, primarily caused by Vibrio harveyi. This study investigates genetic profiles associated with vibriosis by analyzing V. harveyi strains from a seabass farm during 2022 vibriosis outbreaks. Sampling from biofilm and water environments yielded 946 bacterial isolates, of which 56 were identified as V. harveyi using MALDI-TOF MS. ERIC-PCR genotyping revealed four distinct profiles. Despite observing variability in the presence of the 80 tested virulence genes, the overall genetic variation among these profiles was not pronounced. Notably, no single genotypic profile was linked to vibriosis. These findings suggest that the presence of virulence genes alone may not predict disease outbreaks, thus highlighting the need for future research on environmental and transcriptional factors to improve disease control in aquaculture systems.</p></div>

International audience | A considerable proportion of marine plastic pollution consists of abandoned, lost, or otherwise discarded fishing gear (ALDFG). Whether still intact or break down into fragments, ALDFG is a widespread, enduring problem, and as such, it represents an ideal case for the use of citizen science. The Fish&amp;Click program proposes a mobile application and website to enable non-specialist observers, such as walkers, divers, or sailors, to record their sightings of ALDFG. The simple interface allows the user to characterize found gear without any expert knowledge, and an analysis of these data can shed light on the magnitude and spatio-temporal composition of the ALDFG phenomenon. This report presents the results and feedback from the first two years of Fish&amp;Click, from May 2020 to June 2022, in the north of the Bay of Biscay, Celtic Sea, and English Channel. In addition to a database cleaning procedure, we defined an ad hoc methodology for analyzing these non-standardized data. Using this, we found that the types and quantities of found gear differ between sea and shore locations and were also different from one region to another. We discuss the pros and cons of this citizen-science program, as well as the potential for improvements that might help to mitigate pollution by ALDFG.

International audience

International audience | Cassino Beach, on the southernmost coast of Brazil, is especially vulnerable to plastic pollution due to its 220 km-long coastline and proximity to the Patos Lagoon Estuary, which is influenced by urbanization, industrial activities, and intense coastal fishing. This study investigates the aquatic origin (lagoon or ocean) of stranded macroplastics during the summer and winter of 2016 at two sites: one located 3-5 km from the estuary mouth and another approximately 40 km away. A backward particle tracking approach was applied, combining the TELEMAC-3D hydrodynamic model with the TrackMPD model. Model validation using a buoy experiment showed a maximum difference of less than 500 m between real and virtual particle trajectories. A total of 100 virtual particles (0.8 m LDPE sheets, ρ = 0.94 g•cm⁻³) were released per site and season. At the near-estuary site (S1), most particles (75% in summer, 68% in winter) originated from the central region of Patos Lagoon, while an additional 6% (summer) to 25% (winter) came from the São Gonçalo Channel. At the remote site (S4), particles mainly originated from marine regions: 98% (winter) and 43% (summer: 30% SW + 13% NE coastal domain) Simulated transport times ranged from 4.7 to 83 days, with shorter durations during winter due to stronger coastal currents. These results highlight the dominant role of estuarine outflow in transporting macroplastics to areas near the Patos Lagoon mouth, whereas remote areas are influenced by long-distance marine transport, particularly from fishing zones. The integration of numerical modeling with field data is the main contribution of this study to improve our understanding of debris sources and support more effective management strategies.

International audience | The reuse of treated wastewater (TWW) for irrigation is widely applied to alleviate pressure on freshwater resources. However, TWW contains antibiotics that once in soils, can exert selective pressure, promoting the emergence and spread of antimicrobial resistance (AMR) in the environment. Current environmental risk assessments for antibiotic residues rely on indicators such as Predicted No Effect Concentrations (PNECs), usually determined in liquid media. These PNECs aim to predict antibiotic concentrations that may promote resistance in the environment. Given the complexity of soil matrices, few studies have established PNEC values for soil, which likely differ significantly from aquatic environments.To address this gap, we developed a simplified experimental model using soil microcosms irrigated with TWW and the antibiotic sulfamethoxazole (SMX) to estimate threshold concentrations favouring resistance transfer or/and emergence within the soil microbiome. We identified SMX concentrations between 0.01 and 0.1 mg/kgdry soil that likely increased the abundance of sulfonamide resistance genes in soil. A time window of 1 to 7 days post-exposure showed a temporary rise in sul1 and intl1 gene abundance (over 1 log/soil 16S rDNA), the appearance of SMX transformation products, and an increase in some Rhodocyclaceae. After 1.5 months of incubation and complete SMX transformation, the relative abundance of sul1 and intl1 remained about 0.5 log higher than in SMX-free controls and soils with SMX levels below 0.1 mg/kg dry soil. A persistent transformation product, 4-N-glucuronide-SMX, was also observed.Here, the estimated PNEC for SMX in soil, between 0.01 and 0.1 mg/kg, exceeds typical SMX concentrations found in soils exposed to TWW. This may suggest low impact on resistance selection for this compound in the context of TWW exposure. However further studies on other soils, water, and antibiotics need to be conducted to expand our knowledge on soil PNECs.

International audience | Halong Bay (northern Vietnam) is heavily affected by human activities. Metals and metalloids (e.g., Al, Cu, Hg, Ni, Sb, Pb, V; MM) were used as proxies to assess the origin and transport of anthropogenic inputs. The chronology of inputs was examined according to different particle transport pathways using two sediment cores, one from coastal waters (HL) exposed to both atmospheric deposition and the Red River drainage, and the other from a small isolated lake on an islet (HT) receiving only atmospheric deposition. Higher accumulation rates were observed in HL (0.449 g cm -2 year -1 ) than in HT (0.069 g cm -2 year -1 ). In both cores, all anthropogenic MM fluxes are controlled by sedimentation processes regardless of their origin and transport pathways. Results show that coastal waters are strongly influenced by Red River drainage with specific events recorded in 1947 (Indochina War), 1960 (first five-year plan), 1974 and 1985 (flash flooding) and 2002 (Tuyen Quang Dam landslides). In HL core, the highest variabilities were observed for Cr, Hg, Ni, Pb and V with surface maxima of 67.7, 0.107, 26.0, 31.4, 82.2 µg g -1 , respectively. Geochemical ratios (Pb/Hg and V/Ni) showed specific signatures related to fossil fuel combustion. Estimated Pb deposition fluxes follow the increase in CO 2 emissions in the region.

International audience | The increase of anthropogenic noise in the ocean presents a threat to marine ecosystems. To assess underwater noise pollution effects, acoustic propagation models are commonly used. These models differ in complexity and computational requirements. This study aims to find the optimal trade-off between accuracy and computational efficiency of propagation models in marine coastal environments. We evaluated six models by assessing their accuracy and computational demands to identify the most suitable model. The models' accuracy was determined through the comparison of their estimated received levels with measured received levels. Acoustic measurements were conducted in two areas. Both geometric spreading and Energy flux models were effective across low-frequency bands when compared to field measurements. At 1 kHz, they had high agreement and overlap with the field measurements (geometric spreading: ∼74.1 % & ∼39.7 %, Energy flux: ∼77.3 % & ∼40.3 %), while other models performed poorly. In terms of computational efficiency, geometric spreading model was the fastest, followed by Energy flux model, while Bellhop required significantly more time. Ultimately, geometric spreading and Energy flux models were found to be effective for estimating propagation loss across low-frequency bands in coastal environments. Geometric spreading required minimal computational effort while providing reasonable accuracy in an environment with low variation. However, in highly variable environments, Energy flux model was more accurate but needed substantial computational resources for large datasets. This study emphasises the need to carefully evaluate the complexity of the environment, the quality of the input data and the computational resources available to select the most suitable propagation model.

International audience | The French Moss Survey employs forest mosses as indicators to monitor the deposition of atmospheric substances, notably focusing on cadmium (Cd), a known carcinogenic and contributor to respiratory illnesses. This comprehensive study encompasses 55 variables to understand Cd accumulation in terrestrial mosses in France. These variables include moss species, tree cover, biogeographical markers, land use area, proximity to road and rail networks, soil concentration of Cd and atmospheric concentration and deposition of Cd using a physical model. The response variable undergoes a complementary log–log transformation to constrain prediction values within the maximum Cd content in mosses. We have built a regression model to improve predictions, considering the impacts of covariates in France. This model retains biogeographical effects, leading to data segmentation into four distinct biogeographical zones: Atlantic, Continental, Mediterranean and Alpine. Subsequently, zone-specific regression models are explored to refine predictions and consider the impacts of covariates specific to each region, such as those related to railways and roads of the Mediterranean zone. Our biogeographical models effectively mitigate spatial correlation issues and yield accurate predictions, as evidenced by the leave-one-out cross-validation assessment. Compared to ordinary kriging map, the regression prediction maps highlight the contributions of certain covariates, such as the EMEP atmospheric transport model, to areas with high Cd concentrations. Furthermore, these maps exhibit new areas with high (resp. low) Cd concentrations due to high (resp. low) values of the covariates.