Watersheds and estuaries are impacted by multiple anthropogenic stressors that affect their biodiversity and functioning. Assessing their ecological quality has consequently remained challenging for scientists and stakeholders. In this paper, we propose a multidisciplinary approach to identify the stressors in seven small French estuaries located in agricultural watersheds. We collected data from landscape (geography, hydrobiology) to estuary (pollutant chemistry) and fish individual scales (environmental signatures, proteomics). This integrative approach focused on the whole hydrosystems, from river basins to estuaries. To characterize each watershed, we attempted to determine the land use considering geographic indicators (agricultural and urbanised surfaces) and landscape patterns (hedges density and riparian vegetation). Juveniles of European flounder (Platichthys flesus) were captured in September, after an average residence of five summer months in the estuary. Analyses of water, sediments and biota allowed to determine the concentrations of dissolved inorganic nitrogen species, pesticides and trace elements in the systems. Environmental signatures were also measured in flounder tissues. These environmental parameters were used to establish a typology of the watersheds. Furthermore, data from proteomics on fish liver were combined with environmental signatures to determine the responses of fish to stressors in their environments. Differential protein abundances highlighted a dysregulation related to the detoxification of xenobiotics (mainly pesticides) in agricultural watersheds, characterized by intensive cereal and vegetable crops and high livestock. Omics also revealed a dysregulation of proteins associated with the response to hypoxia and heat stress in some estuaries. Furthermore, we highlighted a dysregulation of proteins involved in urea cycle, immunity and metabolism of fatty acids in several systems. Finally, the combination of environmental and molecular signatures appears to be a relevant method to identify the major stressors operating within hydrosystems.

In order to reduce the contamination of marine ecosystems by plastic materials, the scientific community is engaged in the development of biodegradable substitutes for conventional plastics. While certain candidates have been successfully tested in coastal marine environments, the degradation process in deep-sea environments remains poorly understood. This study examined the degradation of two industrial biopolyesters, a poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and a polybutylene-succinate (PBS), in two deep marine environments of the Middle and Eastern Atlantic, at depths of 780 and 1740 m, as well as under laboratory conditions under hydrostatic pressure and without micro-organisms. The findings reveal a considerable biodeterioration of PHBV and a pronounced influence of flax fibre reinforcement on the degradation mechanisms. Conversely, PBS exhibits minimal to no indications of degradation. Additionally, the results confirm that biotic factors are the primary determinants of the degradation processes, with no degradation observed under abiotic conditions.

International audience

International audience | Treatment Wetlands (TW) are employed in the treatment of wastewater, participating in a decentralised and sustainable urban water management. Their designs and usages vary greatly across the world, which limit the aggregation of comparable data for deeper understanding of the mechanisms ruling over water treatment. We developed a hybrid modelling methodology to combine mechanistic and empirical pre-sizing models, applied to a context of low amount of data and knowledge on Horizontal and Vertical Flow TW. We first collected data from the scientific literature and introduced a data quality validation step providing reliability weights associated with each observation. We secondly trained and compared machine-learning models on the assessed dataset. We finally tested two hybridizations with the tank-in-series model, and predicting an optimized surface with a uncertainty interval. This methodology is reproducible and we believe hybrid models can provide more accurate and reliable predictions, therefore facilitating implementations of TW in urban plannings.

Many tropical coastal ecosystems face human pressures related to tourism, land or sea use. We developed a practical procedure to involve stakeholders in an early stage of an ecological research project to map the Social-Ecological System (SES) in our case study Lac Bay, Bonaire island, as well as to identify and prioritize ecological research questions and nature management options in relation to a recent new threat: massive sargassum landings. In our procedure we used the Group Model Building methodology for identifying drivers, key variables and feedback loops in this SES. The underlying mechanisms of driving feedbacks were revealed and shared during these sessions. We identified and prioritized urgent ecological research questions for the conservation of seagrass beds and mangrove forests, and practical measures for nature management in Lac Bay. Both were used in follow-up scientific research and nature management plans, illustrating the applicability of our procedure for early science-stakeholder interaction.

Sargassum spp. strandings in the tropical Atlantic harm local ecosystems due to toxic sulfide levels. We conducted a mesocosm experiment to test the efficacy of iron(III) (hydr)oxides in (a) mitigating sulfide toxicity in mangroves resulting from Sargassum and (b) reducing potentially enhanced greenhouse gas emissions. Our results show that iron addition failed to prevent mangrove mortality caused by highly toxic sulfide concentrations, which reached up to 15,000 μmol l−1 in 14 days; timely removal may potentially prevent mangrove death. Sargassum-impacted mesocosms significantly increased methane, nitrous oxide, and carbon dioxide emissions, producing approximately 1 g CO2-equivalents m−2 h−1 during daylight hours, thereby shifting mangroves from sinks to sources of greenhouse gasses. However, iron addition decreased methane emissions by 62 % and nitrous oxide emissions by 57 %. This research reveals that Sargassum strandings have multiple adverse effects related to chemical and ecological dynamics in mangrove ecosystems, including greenhouse gas emissions.

Marine plastic pollution poses significant ecological, economic, and social challenges, necessitating innovative detection, management, and mitigation solutions. Spectral imaging and optical remote sensing have proven valuable tools in detecting and characterizing macroplastics in aquatic environments. Despite numerous studies focusing on bands of interest in the shortwave infrared spectrum, the high cost of sensors in this range makes it difficult to mass-produce them for long-term and large-scale applications. Therefore, we present the assessment and transfer of various machine learning models across four datasets to identify the key bands for detecting and classifying the most prevalent plastics in the marine environment within the visible and near-infrared (VNIR) range. Our study uses four different databases ranging from virgin plastics under laboratory conditions to weather plastics under field conditions. We used Sequential Feature Selection (SFS) and Random Forest (RF) models for the optimal band selection. The significance of homogeneous backgrounds for accurate detection is highlighted by a 97 % accuracy, and successful band transfers between datasets (87 %–91 %) suggest the feasibility of a sensor applicable across various scenarios. However, the model transfer requires further training for each specific dataset to achieve optimal accuracy. The results underscore the potential for broader application with continued refinement and expanded training datasets. Our findings provide valuable information for developing compelling and affordable detection sensors to address plastic pollution in coastal areas. This work paves the way towards enhancing the accuracy of marine litter detection and reduction globally, contributing to a sustainable future for our oceans.

The North Sea is one of the most industrialised marine regions globally. We integrated cetacean-dedicated aerial surveys (2015–2022) with environmental covariates and ship positions from the Automatic Identification System (AIS) to investigate the disturbance radius and duration on harbour porpoise distribution. This study is based on 81,511 km of line-transect survey effort, during which 6511 harbour porpoise groups (8597 individuals) were sighted. Several proxies for ship disturbance were compared, identifying those best explaining the observed distribution. Better model performance was achieved by integrating maritime traffic, with frequent traffic representing the most significant disturbance to harbour porpoise distribution. Porpoises avoided areas frequented distance over time improved model performance, while reasons for the lower performance of predicted ship sound levels remain unclear. This study demonstrates the short-term effects of maritime traffic on harbour porpoise distribution.

Catchment-scale plastic pollution assessments provide insights in its sources, sinks, and pathways. We present an approach to quantify macroplastic transport and density across the Odaw catchment, Ghana. We divided the catchment into the non-urban riverine, urban riverine, and urban tidal zones. Macroplastic transport and density on riverbanks and land were monitored at ten locations in December 2021. The urban riverine zone had the highest transport, and the urban tidal zone had the highest riverbank and land macroplastic density. Water sachets, soft fragments, and foam fragments were the most abundant items. Our approach aims to be transferable to other catchments globally.