French Research Institute for Exploitation of the Sea
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Identification of Gambierdiscus species from La Réunion and evaluation of toxicity and toxin profile
No full textFive different species of Gambierdiscus have been identified in La Réunion (G. belizeanus, G. balechii, G. pacificus, G. silvae and G. ribotype 2) by morphological observations in Scanning Electron Microscopy (SEM) and molecular identification and phylogenetic analysis. Growth rates of cultures have also been evaluated showing values from 0.09 to 0.36 d-1.
The toxicity and toxin profile of thirteen strains have been analysed by a multidisciplinary approach with Neuro-2a cell-based assay (CBA), magnetic bead-based immunoassay, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and LC coupled to high-resolution mass spectrometry (LC-HRMS). G. balechii showed the highest toxicity by CBA (∼627 fg equiv. CTX1B·cell -1) followed by G. ribotype 2 (76 to 13 fg equiv. CTX1B·cell -1), G. balechii (63 to 7 fg equiv. CTX1B·cell -1), G. belizeanus (30 to 20 fg equiv. CTX1B·cell -1) and G. pacificus with values close to LOQ but not conclusive. The toxin profile for the 13 strains was evaluated by LC-MS/MS using seven different methods and being gambierone and 44-methylgambierone the two only known compounds, found in high concentrations in all samples. Gambierone was detected from 2.05 pg ·cell-1 in G. balechii (P-0414B) to 12.91 pg·cell-1 in G. balechii (P-0414A) and 44-methylgambierone was detected from 1.93 pg·cell-1 in G. belizeanus (P-0414B) to 14.95 pg·cell-1 in G. pacificus (P-0304). These samples were analysed also by LC-HRMS, confirming gambierone and 44-methylgambierone the main compounds detected. Additionally, a potential polyether sulphur-containing compound corresponding to the novel molecular formula C62H94O23S ([M+NH4]+, m/z 1256.6234) were tentatively identified.
This study combining morphological and molecular data is the first to mention such diversity in the area. It is also the first time that toxicity and toxin profile of Gambierdiscus from La Réunion have been evaluated
Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers
No full textThe use of flow cytometry to investigate phytoplankton functional groups is rapidly expanding worldwide, using lab‐ or ship‐based instruments or autonomous environmental monitoring platforms. Automation, coupled with greater autonomy, allows for higher spatial and temporal resolution of phytoplankton groups, enhancing understanding of their dynamics and patterns, generating large datasets. The level of resolution is determined by both instrumental capabilities and optimization of its acquisition settings. Sharing these datasets with the scientific community, whether to improve global phytoplankton distribution resolution or facilitate the intercomparison of environmental indicators among monitoring laboratories, strongly relies on quality‐controlled instruments and standardized data acquisition and analysis. This article focuses on CytoSense‐type (CytoBuoy, NL) flow cytometers, which operate by recording the optical pulse shapes of particles as they pass through a laser beam. Different configurations such as laser wavelength and power, sheath fluid management, sample inlet design, and dataset output format were not considered, in order to focus on optimization and protocol standardization to resolve the whole phytoplankton size spectrum, from the smallest autofluorescing prokaryotes to colonies and chain‐forming species. In this study, coincidence, PMT voltage, trigger threshold optimization, and regular quality control procedures are considered and discussed, using datasets from three types of instruments and two contrasted marine coastal waters as case studies. The primary goal of this study is to establish a framework to guide and support the exploration and application of this type of flow cytometer, ultimately achieving a reliable and optimal resolution for sample acquisition of natural waters
Disentangling Currents and Waves: Exploitation of Polarization Diversity for Wave-Doppler Estimation
No full textSurface velocities measured by Synthetic Aperture Radar (SAR) contain contributions from both mean surface motion—referred to as total surface current (TSC)—and the often more prominent sea-state-induced wave motions. Most modern SAR systems cannot distinguish between these two phenomena, which has stifled TSC retrieval from SAR data for decades. We propose a new framework to separate TSC and wave-motion components by leveraging polarization diversity, exploiting the tendency of each phenomenon to imprint distinct signatures on orthogonal polarizations. Building on a foundational signal model, we derive four source-separation algorithms. To address the model’s theoretical limitations, we introduce empirical extensions via symbolic regression, guided by varying levels of theoretical insight. The developed algorithms are evaluated using simulated C-band SAR data, and benchmarked against a reference geophysical model function (GMF) implementation. Our methods demonstrate comparable overall performance, with errors on the order of O(0.1ms−1), and notably outperform the GMF in resolving kilometer-scale spatial features—a domain where traditional GMFs generally struggle. Preliminary results obtained on TanDEM-X observations confirm the generalizability of our approach. These findings highlight the potential of future SAR missions with polarimetric capabilities, such as Harmony, to achieve high-resolution separation of surface-motion sources using polarization diversity
Data-Informed Inversion Model (DIIM): a framework to retrieve marine optical constituents using a three-stream irradiance model
No full textWithin the New Copernicus Capability for Trophic Ocean Networks (NECCTON) project, we aim to improve the current data assimilation system by developing a method for accurately estimating marine optical constituents from satellite-derived remote sensing reflectance. We compared two frameworks based on the implicit inversion of a semi-analytical model derived from the classical radiative transfer equation. The first approach employed an iterative Bayesian inversion with a Gaussian approximation, which provides maximum a posteriori (MAP) estimates of the optical constituents along with their associated uncertainties. To improve the model performance, we optimized the model parameters using historical in situ measurements from the BOUSSOLE buoy and a Markov chain Monte Carlo (MCMC) algorithm, which reduced the root mean square error (RMSE) between the retrieved and observed values. The second approach employed the stochastic gradient variational Bayes (SGVB) estimator, which is designed to approximate the MAP estimates of the optical constituents while simultaneously optimizing the model parameters through maximum likelihood. This method resulted in faster computations than the iterative Bayesian inversion while maintaining comparable RMSE values. While the iterative Bayesian inversion provided reliable uncertainty estimates, the SGVB estimator offered faster computations of the optical constituents. Moreover, using a dataset of in situ sea surface chlorophyll a concentrations across a broad region of the northwestern Mediterranean Sea, we compared the inversion techniques with a state-of-the-art algorithm used within the Copernicus Marine Service, finding comparable performances across methods. Notably, the SGVB estimator showed the highest correlation between in situ measurements and retrievals throughout the analyzed region. We conclude that both inversion methods achieve a performance comparable to existing state-of-the-art algorithms. The Gaussian approximation offers robust uncertainty quantification, while the SGVB estimator provides a reliable and computationally efficient alternative
Control of simulated ocean ecosystem indicators by biogeochemical observations
No full textTo protect marine ecosystems threatened by climate change and anthropic stressors, it is essential to operationally monitor ocean health indicators. These are metrics synthetizing multiple marine processes relevant to the users of operational services. In this study, we assess whether selected ocean indicators simulated by operational models can be effectively constrained (i.e., controlled) by biogeochemical observations, by using a newly proposed methodological framework. The method consists in firstly screening the sensitivities of the indicators with respect to the initial conditions of the observable variables. These initial conditions are perturbed stochastically in Monte Carlo simulations of one-dimensional configurations of a multi-model ensemble. Then, the models are applied in three-dimensional ensemble assimilation experiments, where the reduction of the ensemble variance corroborates the controllability of the indicators by the observations. The method is applied to ten relevant ecosystem indicators (ranging from inorganic chemicals to plankton production), seven observation types (representing data from satellite and underwater platforms), and an ensemble of five biogeochemical models of different complexity, employed operationally by the European Copernicus Marine Service. Our results demonstrate that all the indicators are controlled by one or more types of observations. In particular, the indicators of phytoplankton phenology are controlled and improved by merged observations of surface ocean colour and chlorophyll profiles. Similar observations also control and reduce the uncertainty of the plankton community structure and production. However, we observe that the uncertainty of trophic efficiency and particulate organic carbon (POC) increases when chlorophyll-a data are assimilated. This may reflect reduced model skill, though the unavailability of relevant observations prevents a conclusive assessment. We recommend that the controllability assessment proposed here becomes a standard practice in the design of operational monitoring, reanalysis, and forecast systems. Such standardization would provide users of operational services with more accurate and precise estimates of ocean ecosystem indicators
The spread of Aoroides longimerus Ren & Zheng, 1996 across the Mediterranean and the Atlantic: genetic diversity, anthropogenic transport, and ecological implications
No full textAccurate knowledge of the global distribution of non-indigenous species (NIS) is essential for understanding their invasion dynamics and for implementing timely management measures. This study reports the first records of the marine amphipod Aoroides longimerus, putatively native to the East Asian coast, in Italy (2018), Spain (2019) and Tunisia (2022) and provides the earliest documented record of the species in its introduced European range (Portugal, 2011). Furthermore, it expands the species’ known distribution in mainland Portugal (including the northernmost record), Macaronesia (with first records in the Canary Islands and Madeira), and confirms its presence along the Atlantic coasts of France and the Netherlands. Aquaculture facilities, particularly those associated with oyster farming, are probably the primary vector of introduction, while recreational boating may have contributed significantly to secondary dispersal. In comparison to other exotic amphipods, A. longimerus remains absent from many marinas, ports and/or aquaculture facilities in the Mediterranean Sea and adjacent regions, such as the Red Sea. This suggests that the species may still be in the early stages of expansion, or that its dispersal ability across marinas and ports is more limited than that of other amphipods. The present study, however, highlights several key ecological traits of A. longimerus: (i) it can survive year-round despite seasonal fluctuations, and reach high local densities, (ii) it exhibits strong colonisation capacity, as shown by its rapid establishment on settlement plates, and (iii) it displays opportunistic feeding behaviour, primarily consuming detritus. These characteristics underscore the importance of continuous surveillance and effective communication with stakeholders to prevent further expansion of this species
Guidance for Estimating Mean Winds in Tropical Cyclone Using SAR-Derived Winds
No full textIn recent years, high-resolution sea surface wind speed estimates in tropical cyclones (TCs) have been provided by Synthetic Aperture Radar (SAR) retrievals. Since SAR provides only instantaneous wind speeds an appropriate spatial averaging is needed to estimate time-mean wind speeds relevant for operational use. Currently operational centers use 3 × 3-km averaged products to estimate 1-min mean wind speeds, assuming a representative wind speed of 50 m s −1 . This study presents and evaluates two additional methods: a dynamic-box averaging and annular-sector averaging. The dynamic-box averaging adjusts the averaging box size based on estimated winds, while the annular-sector averaging samples over a dynamic wind speed-based annular-sector area taking advantage of the high degree of axisymmetry in TCs while minimizing contamination from more distant radii. Comparisons with in-situ GPS dropsonde observations show that SAR retrievals agree better with the dropsonde-based 1-min mean winds rather than instantaneous winds at a 10m altitude. All three averaging methods yield consistent 1-min mean wind estimates with small root mean square errors (∼4 m s −1 ) and high cross-correlations (∼0.96). However, positive biases (∼10%) emerge at high wind speeds. The study also examines the statistical validity of all three methods for estimating 10-min mean wind speeds and finds that the annular-sector method performs best. The relationship between the maximum wind speeds of 1-min and 10-min mean winds is also discussed. These findings demonstrate that, with appropriate averaging, SAR-derived winds can provide reliable and operationally useful TC diagnostics
Precession-forced asymmetric continental heating shapes ENSO variability
No full textGeologic and modelling evidence reveals that the ENSO is strongly affected by the precession of the Earth’s rotation axis, yet the mechanisms remain unclear due to interactions among multiple forcings. Using high-resolution model simulations reconstructing the ENSO activity across a full precessional cycle, we find that ENSO is strongest during austral summer perihelion, as today. This behavior arises from asymmetric continental heating: austral summer perihelion introduces strong warming on Australia, east of the Indo-Pacific ITCZ. Because deep convection favors the warmest areas, this causes the ITCZ and the Warm Pool to shift eastwards. As a result, the Pacific’s east-west thermal contrast is reduced, lowering the threshold for oscillations of convection and amplifying ENSO activity. In contrast, boreal summer perihelion warms Afro-Eurasia, shifts the ITCZ westward and weakens ENSO. Proxy records across the Indo-Pacific support this changes in climate state. Understanding asymmetric continental heating helps us link astronomical modulation to ENSO behavior and improve long-term predictions of tropical climate change
Two decades of pHT measurements along the GO-SHIP A25 section
No full textThe North Atlantic (NA) GO-SHIP A25 OVIDE-BOCATS section is a long-term repeat hydrographic transect extending from Portugal to Greenland. Since 2002, physical and biogeochemical measurements have been carried out biennially along the OVIDE-BOCATS section, contributing to a better understanding of water mass properties, mixing, circulation, carbon storage, and climate change impacts such as ocean acidification (OA) in the NA. In particular, the high-precision pH measurements on the total hydrogen ion scale (pHT) from the OVIDE-BOCATS program represent a key milestone in monitoring OA in this particularly climate sensitive region. The method used for pHT determination relies on adding meta-cresol purple (mCP) dye to the seawater sample and spectrophotometrically measuring its absorbances at specific wavelengths. The OVIDE-BOCATS program has used unpurified mCP dye, which impurities have been proven to bias pHT values. Here we quantified the bias induced by these impurities in pHT measurements. We found that measurements carried out using the unpurified mCP dye tend to be, on average, 0.011 ± 0.002 pHT units higher than those obtained using the purified mCP dye, with this difference slightly decreasing at higher pHT values. Moreover, we tested independent methods to correct the effect of impurities in both the historical and recent OVIDE-BOCATS pHT data, demonstrating that the correction is consistent across methods. The long-term pHT dataset has been updated to include newly acquired data and absorbance measurements, and to standardize corrections for mCP dye impurities. This effort results in a twenty-year dataset of pHT corrected for mCP dye impurities, that demonstrates the possibility of a global effort to improve the reliability and coherency of spectrophotometric pHT measurements made with unpurified mCP dye. The corrections applied to our pHT dataset have negligible implications for the OA rates previously reported, but they do affect the depth of the aragonite saturation horizon, implying a shoaling of approximately 150 m
When species are lost but functions persist: a trait‐based perspective on Wadden Sea bird diversity dynamics
No full textBiodiversity faces several global threats and communities are likely to show complex delayed responses. Accurately measuring these lags is critical to properly understand diversity dynamics. Here, we investigated these delays with minimal data availability and found critical mismatches between the temporal dynamics of taxonomic and functional diversity in Wadden Sea bird communities. By analysing 17 long‐term time series spanning an average of 30+ years, we quantified the net imbalance between colonisations and extinctions (NICE) to measure delays in taxonomic (tNICE) and functional (fNICE) diversity. Our approach used empirically measured (trophic and morphological) traits, and in parallel, traits inferred through diffusion maps, allowing to quantify species traits only based on their co‐occurrence patterns over time. First, we found that diffusion maps are a relevant tool to quantify species traits when trait data are scarce. Moreover, we found that, while initial colonisations outnumbered extinctions, the taxonomic balance shifted dramatically toward local species losses, deviating significantly from neutral expectations. Yet despite this concerning trend, functional diversity was stable. This stability likely stems from functional redundancy among declining species, temporarily preventing functional changes. However, despite current functional resilience, the on‐going loss of taxonomically distinct species threatens to erode unique functional roles, potentially triggering abrupt shifts and/or collapse in ecosystem functions. Most critically, our study show how seemingly stable functional diversity can mask accelerating taxonomic losses, highlighting the urgent need for multi‐faceted biodiversity monitoring. As global changes intensify, combining taxonomic and functional assessments through advanced analytical methods becomes essential for detecting early warning signals of ecosystem deterioration and implementing effective conservation strategies