Bi-decadal variability in physico-biogeochemical characteristics of temperate coastal ecosystems: from large-scale to local drivers

International audienceCoastal marine ecosystems, which play a crucial role in the biogeochemical and ecological functioning of the Earth, are highly sensitive to the combined effects of climate and human activities. Because of their location, coastal ecosystems are directly influenced by human activities, but it remains challenging to assess the spatial and temporal scales at which climate influences coastal ecosystems. We monitored 12 sampling stations, distributed in 8 ecosystems in France, over 2 decades for physico-biogeochemical parameters (temperature, salinity, concentrations of dissolved oxygen, nutrients and particulate material). The study encompasses a large diversity of temperate coastal ecosystems with respect to e.g. geomorphology, trophic status, tidal regime, river influence and turbidity. Time-series analysis coupled with standardised 3-mode principal component analyses, partial triadic analyses and correlations were used to assess bi-decadal variability and ecosystem trajectories, and to identify large-scale, regional and local drivers. Our results highlighted 2 abrupt changes in 2001 and 2005. The bi-decadal changes were related to changes in large-scale and regional climate, detected through proxies of temperature and atmospheric circulation, as well as through river discharge. Ecosystem trajectories tended to move towards an increase in temperature and salinity, and/or a decrease in chlorophyll a , nutrients and particulate matter. However, the magnitude of change, the year-to-year variability and the sensitivity to the 2001 and 2005 changes varied among the ecosystems. This study highlights the need for establishing long-term time series and combining data sets as well as undertaking multi-ecosystem and local studies to better understand the long-term variability of coastal ecosystems and its associated drivers

Dynamics of particulate organic matter composition in coastal systems: Forcing of spatio-temporal variability at multi-systems scale

International audienceIn costal systems, particulate organic matter (POM) results from a multiplicity of sources having their respective dynamics in terms of production, decomposition, transport and burial. The POM pool experiences thus considerable spatial and temporal variability. In order to better understand this variability, the present study employs statistical multivariate analyses to investigate links between POM composition and environmental forcings for a panel of twelve coastal systems distributed along the three maritime regions of France and monitored weekly to monthly for 1 to 8 years.At multi-system scale, two main gradients of POC composition have been identified: a 'Continent-Ocean' gradient associated with hydrodynamics, sedimentary dynamics and depth of the water column, and a gradient of trophic status related to nutrient availability. At local scale, seasonality of POC composition appears to be station-specific but still related to part of the above-mentioned forcings. A typology of systems was established by coupling spatial and temporal variability of POC composition. Four groups were highlighted: (1) the estuarine stations where POC composition is dominated by terrestrial POM and driven by hydrodynamics and sedimentary processes, (2) the oligotrophic systems, characterized by the contribution of diazotrophs due to low nutrient availability, and the marine meso/eutroph systems whose POC composition is (3) either deeply dominated by phytoplankton or (4) dominated by phytoplankton but where the contribution of continental and benthic POC is not negligible and is driven by hydrodynamics, sedimentary processes and the height of the water column.Finally, the present study provides several insights into the different forcings to POM composition and dynamics in temperate coastal systems at local and multi-system scales. This work also presents a methodological approach that establishes statistical links between forcings and POM composition, helping to gain more objectively insight of forcings

Dynamics of particulate organic matter composition in coastal systems: a spatio-temporal study at multi-systems scale

International audienceIn coastal systems, the multiplicity of sources fueling the pool of particulate organic matter (POM) leads to divergent estimations of POM composition. Eleven systems (two littoral systems, eight embayments and semi-enclosed systems and one estuary) distributed along the three maritime façades of France were studied for two to eight years in order to quantify the relative contribution of organic matter sources to the surface-water POM pool in coastal systems. This study was based on carbon and nitrogen elemental and isotopic ratios, used for running mixing models. The POM of the estuary is dominated by terrestrial material (93% on average), whereas the POM of the other systems is dominated by phytoplankton (84% on average). Nevertheless, for the latter systems, the POM composition varies in space, with 1) systems where POM is highly composed of phytoplankton (≥ 93%), 2) systems characterized by a non-negligible contribution of benthic (8 to 19%) and/or riverine (7 to 19%) sources, and 3) the Mediterranean systems characterized by the contribution of diazotroph organisms (ca. 14%). A continent-to-ocean gradient of riverine and/or benthic POM contribution is observed. Finally, time series reveal 1) seasonal variations of POM composition, 2) differences in seasonality between systems, and 3) an inshore-offshore gradient of seasonality within each system that were sampled at several stations. Spatial and seasonal patterns of POM composition are mainly due to local to regional processes such as hydrodynamics and sedimentary hydrodynamic (e.g. resuspension processes, changes in river flows, wind patterns influencing along-shore currents) but also due to the geomorphology of the systems (depth of the water column, distance to the shore). Future studies investigating the link between these forcings and POM composition would help to better understand the dynamics of POM composition in coastal systems

Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT

International audienceIntroduction While crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented. Methods With a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (<20 laboratories) and multivariate datasets. Finally, the expanded uncertainty of measurement for 20 environmental variables routinely measured by SOMLIT from discrete sampling—including Essential Ocean Variables—is provided. Results, Discussion, Conclusion The examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets

Table_1_Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT.xls

IntroductionWhile crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented.MethodsWith a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (Results, Discussion, ConclusionThe examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.</p

DataSheet_1_Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT.docx

IntroductionWhile crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented.MethodsWith a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (Results, Discussion, ConclusionThe examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.</p