Plankton form the base of marine food webs, making them important indicators of ecosystem status. Changes in the abundance of plankton functional groups, or lifeforms, can affect higher trophic levels and can indicate important shifts in ecosystem functioning. Here, we extend this knowledge by combining data from Continuous Plankton Recorder and fixed-point stations to provide the most comprehensive analysis of plankton time-series for the North-East Atlantic and North-West European shelf to date. We analysed 24 phytoplankton and zooplankton datasets from 15 research institutions to map 60-year abundance trends for 8 planktonic lifeforms. Most lifeforms decreased in abundance (e.g. dinoflagellates: -5 %, holoplankton: -7 % decade^-1), except for meroplankton, which increased 12 % decade^-1, reflecting widespread changes in large-scale and localised processes. K-means clustering of assessment units according to abundance trends revealed largely opposing trend direction between shelf and oceanic regions for most lifeforms, with North Sea areas characterised by increasing coastal abundance, while abundance decreased in North-East Atlantic areas. Individual taxa comprising each phytoplankton lifeform exhibited similar abundance trends, whereas taxa grouped within zooplankton lifeforms were more variable. These regional contrasts are counterintuitive, since the North Sea which has undergone major warming, changes in nutrients, and past fisheries perturbation has changed far less, from phytoplankton to fish larvae, as compared to the more slowly warming North-East Atlantic with lower nutrient supply and fishing pressure. This more remote oceanic region has shown a major and worrying decline in the traditional food web. Although the causal mechanisms remain unclear, declining abundance of key planktonic lifeforms in the North-East Atlantic, including diatoms and copepods, are a cause of major concern for the future of food webs and should provide a red flag to politicians and policymakers about the prioritisation of future management and adaptation measures required to ensure future sustainable use of the marine ecosystem.

The recent development of biological sensors has extended marine plankton studies from conducting laboratory bench work to in vivo and real-time observations. Flow cytometry (FCM) has shed new light on marine microorganisms since the 1980s through its single-cell approach and robust detection of the smallest cells. FCM records valuable optical properties of light scattering and fluorescence from cells passing in a single file in front of a narrow-collimated light source, recording tens of thousands of cells within a few minutes. Depending on the instrument settings, the sampling strategy, and the automation level, it resolves the spatial and temporal distribution of microbial marine prokaryotes and eukaryotes. Cells are usually classified and grouped on cytograms by experts and are still lacking standards, reducing data sharing capacities. Therefore, the need to make FCM data sets FAIR (Findability, Accessibility, Interoperability, and Reusability of digital assets) is becoming critical. In this paper, we present a consensus vocabulary for the 13 most common marine microbial groups observed with FCM using blue and red-light excitation. The authors designed a common layout on two-dimensional log-transformed cytograms reinforced by a decision tree that facilitates the characterization of groups. The proposed vocabulary aims at standardising data analysis and definitions, to promote harmonisation and comparison of data between users and instruments. This represents a much-needed step towards FAIRification of flow cytometric data collected in various marine environments.

The variability of phytoplankton distribution has been unraveled by high‐frequency measurements. Such a resolution can be approached by automated pulse‐shape recording flow cytometry (AFCM) operating at hourly sampling resolution. AFCM records morphological and physiological traits as single‐cell optical pulse shapes that can be used to classify cells into phytoplankton functional groups (PFGs). However, the associated manual post‐processing of the data coupled with the increasing size and number of datasets is time‐consuming and error‐prone. Machine learning models are increasingly used to run automatic classification. Yet, most of the existing methods either present a long training process, need to manually design features from the raw optical pulse shapes, or are dedicated to images only. In this study, we present a convolutional neural network (CNN) to classify several PFGs using AFCM pulse shapes. The uncertainties of manual classification were first estimated by comparing experts' recognition of six PFGs. Consensual particles from the manual PFG classification were used to train and validate the CNN. The CNN obtained competitive performances compared to other models used in the literature and remained robust across several sampling areas, and instrumental hardware and settings. Finally, we assessed the ability of this classifier to predict phytoplankton counts at a Mediterranean coastal station and from a cruise in the South‐West Indian Ocean, providing a comparison with the manual classification over 3‐month periods and a 2h frequency. These promising results strengthen the near real‐time observation of PFGs, especially required with the increasing use of AFCM in monitoring research programs.

Global change is known to exert a considerable impact on marine and coastal ecosystems, affecting various parameters such as sea surface temperature (SST), runoff, circulation patterns and the availability of limiting nutrients (like nitrogen, phosphorus and silicon), with each influencing phytoplankton communities differently. This study is based on weekly to fortnightly in vivo fine-spatial-resolution (∼ 1 km) phytoplankton observations along an nearshore–offshore gradient in the French waters of the Eastern English Channel in the Strait of Dover. The phytoplankton functional composition was addressed by automated “pulse-shape recording” flow cytometry, coupled with the analysis of environmental variables over the last decade (2012–2022). This method allows for the characterization of almost the entire phytoplankton size range (from 0.1 to 800 µm width) and the determination of the abundance of functional groups based on optical single-cell signals (fluorescence and scatter). We explored seasonal, spatial and decadal dynamics in an environment strongly influenced by tides and currents. Over the past 11 years, the SST has shown an increasing trend at all stations, with nearshore waters warming faster than offshore waters (+1.05 °C vs. +0.93 °C). Changes in nutrient concentrations have led to imbalances in nutrient ratios ($\mathrm{N}:\mathrm{P}:\mathrm{Si}$ ) relative to reference nutrient ratios. However, a return to balanced ratios has been observed since 2019. The phytoplankton total abundance has also increased over the aforementioned decade, with a higher contribution of small-sized cells (picoeukaryotes and picocyanobacteria) and a decrease in microphytoplankton, particularly near the coast. Based on an analysis of environmental parameters and phytoplankton abundance, the winters of 2013–2014 and 2019–2020 were identified as shifting periods in this time series. These changes in the phytoplankton community, favoring the smallest groups, could lead to a reduction in the productivity of coastal marine ecosystems, which could, in turn, affect higher trophic levels and the entire food web.

To study changes in phytoplankton community composition on different timescales, an automated flow cytometer (CytoSub, CytoBuoy b.v.) was deployed at the MAREL Carnot automated monitoring station in Boulogne-sur-Mer (eastern English Channel, France) during spring (2021 and 2022) and summer (2022), following an Eulerian approach. Phytoplankton dynamics were recorded every 2 h, distinguishing 11 phytoplankton functional groups (PFGs) based on optical and fluorescence properties. This enabled detailed characterization of PFG successions, including MicroRED (mostly diatoms) and NanoRED (mostly haptophytes of the species Phaeocystis globosa) transitions in spring, as well as a summer dominance by PicoORG (picocyanobacteria, mostly of the genus Synechococcus) and PicoRED. Four rare events, including a salinity drop (April 2021), strong winds (May 2021 and April 2022), and a marine heat wave (July 2022), caused rapid shifts in phytoplankton community assemblage. Empirical mode decomposition (EMD) and Lomb–Scargle periodogram (LSP) analyses revealed that 85±10 % of variability in total phytoplankton abundance, red fluorescence (a proxy of chlorophyll a), and Shannon diversity occurred on relatively short timescales (9 h to 11 d) for time series of several months, highlighting the value of high-frequency monitoring in capturing ecological dynamics under macrotidal conditions in the eastern English Channel.