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Microplankton is an heterogeneous group of organisms ranging between 20 and 200 microns in size. Morphological characterization of its diversity is challenging as it includes Chromista, Protozoa, and Metazoa (adults and larvae). We characterized the composition of the microzooplankton community (heterotrophic and mixotrophic) collected with a CalVET net (50 µm mesh), in a coastal area affected by urban wastewater discharges in the N Alboran Sea (SW Mediterranean). We applied an integrative taxonomic approach, combining metabarcoding of the mtDNA cytochrome oxidase I (COI) and the V4 region of the 18S rRNA (18S) genes with morphological microscopic identification of organisms. Both methods showed differentiated coastal and offshore microzooplankton assemblages. The dominant taxa varied depending on the method used, with Dinophyceae accounting for 64-85% of the microscopy counts but Arthropoda representing up to 98% or the COI and 18S reads. When computing Protozoa and Metazoa relative abundances separately, both microscopy and metabarcoding revealed unicellular communities dominated by thecate Dinophyceae, followed by Ciliophora. Metazoa microscopy counts were dominated by eggs, followed by Copepoda nauplii in offshore waters, whilst by Appendicularia and Mollusca larvae in the shallow coastal stations. COI reads also corresponded mostly to Copepoda and Mollusca. However, 18S reads were dominated by Thecostraca and Copepoda. Despite the identification level differed among methods and taxa, the integrated approach revealed higher diversity than expected.

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Orenstein, E., Ayata, S., Maps, F., Becker, É., Benedetti, F., Biard, T., Garidel‐Thoron, T., Ellen, J., Ferrario, F., Giering, S., Guy‐Haim, T., Hoebeke, L., Iversen, M., Kiørboe, T., Lalonde, J., Lana, A., Laviale, M., Lombard, F., Lorimer, T., Martini, S., Meyer, A., Möller, K.O., Niehoff, B., Ohman, M.D., Pradalier, C., Romagnan, J.-B., Schröder, S.-M., Sonnet, V., Sosik, H.M., Stemmann, L.S., Stock, M., Terbiyik-Kurt, T., Valcárcel-Pérez, N., Vilgrain, L., Wacquet, G., Waite, A.M., & Irisson, J. Machine learning techniques to characterize functional traits of plankton from image data. Limnology and Oceanography, 67(8), (2022): 1647-1669, https://doi.org/10.1002/lno.12101., Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms., SDA acknowledges funding from CNRS for her sabbatical in 2018–2020. Additional support was provided by the Institut des Sciences du Calcul et des Données (ISCD) of Sorbonne Université (SU) through the support of the sponsored junior team FORMAL (From ObseRving to Modeling oceAn Life), especially through the post-doctoral contract of EO. JOI acknowledges funding from the Belmont Forum, grant ANR-18-BELM-0003-01. French co-authors also wish to thank public taxpayers who fund their salaries. This work is a contribution to the scientific program of Québec Océan and the Takuvik Joint International Laboratory (UMI3376; CNRS - Université Laval). FM was supported by an NSERC Discovery Grant (RGPIN-2014-05433). MS is supported by the Research Foundation - Flanders (FWO17/PDO/067). FB received support from ETH Zürich. MDO is supported by the Gordon and Betty Moore Foundation and the U.S. National Science Foundation. ECB is supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) under the grant agreement no. 88882.438735/2019-01. TB is supported by the French National Research Agency (ANR-19-CE01-0006). NVP is supported by the Spanish State Research Agency, Ministry of Science and Innovation (PTA2016-12822-I). FL is supported by the Institut Universitaire de France (IUF). HMS was supported by the Simons Foundation (561126) and the U.S. National Science Foundation (CCF-1539256, OCE-1655686). Emily Peacock is gratefully acknowledged for expert annotation of IFCB images. LS was supported by the Chair VISION from CNRS/Sorbonne Université.

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Zooplankton are the main prey for small pelagic fishes. The most common small pelagic fish species in the Alboran Sea (SW Mediterranean Sea) is the European sardine (Sardina pilchardus). Despite its commercial importance in the region, little is known about its larval trophodynamics and the role that zooplankton play in their recruitment success. Microscopic characterization of the larval gut contents is challenging as they prey mostly on partly digested microplanktonic organisms. Several molecular tools have been developed that may overcome this caveat. The gut content of sardine larvae (6 - 21 mm standard length) collected over a diel cycle in the Northern Alboran Sea was analyzed by mitochondrial COI metabarcoding, and compared with the field zooplankton community composition. Diel variability was observed in zooplankton relative abundances, both in the larval gut contents and in the field. Sardine larvae preys included several copepod nauplii, but also DNA of cladocera, euphausiid, gastropod and hydrozoa was detected, suggesting an opportunistic foraging behavior, instead of a selective diet.

Variability in composition and structure of the mesozooplankton communities in the Bay of Malaga (SW Mediterranean) were characterized during a 26 h cycle using an integrative taxonomic approach. We combined microscopic identification of organisms, with metabarcoding for the genes of the mitochondrial DNA COI and the V9 hypervariable region of the ribosomal RNA 18S. Richness and diversity obtained by microscopy were higher than those measured with COI, as COI did not detect some phyla. COI however allowed for the identification to species level of several taxa that were left at higher taxonomic rank under the microscope. 18S detected a wider range of taxa than COI and microscopy, although with lower taxonomic resolution. Differences between coastal-night and shelf-day zooplankton communities structure were detected by both microscopy and metabarcoding. The combination of these two approaches increased the known copepod species in the SW Mediterranean Sea by 9%. An integrative approach combining morphology and COI metabarcoding is proposed to further facilitate mesozooplankton biodiversity studies.

The Strait of Gibraltar (SG) is the only connection of the Mediterranean Sea with the global circulation. The SG is an outstanding marine region to explore physical-biological coupling of pelagic communities due to its hydrodynamic complexity, including strong tidal forcing and marked spatial gradients and fronts. The authors have unravelled the role of the fortnightly tidal scale (spring and neap tides) and local processes (upwelling and tidal-topographic mixing) that shape planktonic assemblages in the Strait. To do so, an oceanographic cruise was taken in early autumn 2008 with a high-resolution grid sampling and spring/neap tidal conditions. The planktonic features were captured using different automatic and semi-automatic techniques of plankton analyses (flow cytometry, FlowCAM, LOPC and Ecotaxa) that allowed covering a wide range of sizes of the community from pico- to mesoplankton. The SG was sectorized into two clusters based on the biogeochemical and main water column properties. Cluster 1 (CL1) covered shallow productive areas around Cape Trafalgar (CT). CL1 presented higher concentrations of chlorophyll and nutrients, and phytoplankton was mostly represented by Synechococcus and coastal diatoms while zooplankton had the highest percentage of meroplankton (31%). In contrast, cluster 2 (CL2) covered open ocean waters and presented more oligotrophic features, i.e. nitrogen-depleted waters with lower chlorophyll concentrations and a picoplankton community dominated by Prochlorococcus and holoplankton predominance in mesozooplankton. Under early autumn conditions with overall nutrient-depleted and stratified waters, the CT area emerges as an ecosystem where the constant tidal mixing and nutrients supply is coupled with an active production also being favored by high residence times and finally shaping a plankton community with unique features in the area.

The Mediterranean Sea is subjected to strong anthropogenic pressures that may be causing important ecosystem changes, particularly in coastal areas under high anthropogenic pressure. We characterized the composition of the microzooplankton community in a coastal area in the N Alboran Sea (SW Mediterranean) highly impacted by urban wastewater pollution. Two offshore outfalls release urban wastewater to the sea at a 40 m bottom depth, from a nearby town. We applied an integrative taxonomic approach, combining metabarcoding of the mitochondrial COI and the 18S rRNA genes with morphological microscopic identification of organisms, collected with a CalVET net (50 µm mesh). Hydrology was notably affected near the bottom at the vicinity of the submarine emissaries exit, presenting increased temperature and turbidity, and decreased salinity due to the urban freshwater discharge. Nutrient concentrations exceeded the Water Framework Directive limits; however, chlorophyll a concentrations were not very high, due to strong water column stratification. Microzooplankton communities (50-200 µm) were dominated by dinoflagellates (50-80% relative abundance), followed by copepods (copepodites and nauplii), eggs and cysts. We found significant differences in communities’ composition between the coastal shallow area and the offshore waters, driven by pollution and stratification.

Variability in the spatial and temporal distribution of the mesozooplankton abundance in the N Alboran Sea (SW Mediterranean) was assessed intermittently from 2010 to 2020, and compared with 1992–2000 historical time series data. Total abundance of mesozooplankton was significantly higher in the coast than in the shelf and slope waters. There were significant differences in mesozooplankton abundance between 1992–2000 and 2010–2020 at the three zones. Copepods dominated the mesozooplankton during winter and spring, but cladocerans and doliolids also became important components of the community in summer and autumn. We found significant increases between the first and the second decadal periods in the abundance of copepods, appendicularians, holoplanktonic gastropods and siphonophores in the shelf. However, in the coast, copepod nauplii, doliolids, gastropods and siphonophores increased, while euphausiids abundance decreased significantly. These trends contrast with the ongoing decline of the sardine stocks in European waters. Increasing temperature and decreasing predation pressure are suggested to be the main drivers of mesozooplankton variability.

The diversity of protists was researched in the Alboran Sea (SW Mediterranean Sea) by means of high-throughput sequencing technologies based on the amplification of the V9 region of 18S rRNA. Samples were collected at different depths in seven stations following an environmental gradient from a coastal upwelling zone to the core of an oligotrophic anticyclonic gyre (AG). Sampling was performed during summer, when the water column was stratified. The superphyla Alveolata, Stramenopila and Rhizaria accounted for 84% of the total operational taxonomic units (OTUs). The most diverse groups were Dinophyceae (21% of OTUs), Marine Alveolates-II (MALV-II; 20%), Ciliophora (9%) and MALV-I (6%). In terms of read abundance, the predominant groups were Dinophyceae (29%), Bacillariophyta (14%), MALV-II (11%) and Ciliophora (11%). Samples were clustered into three groups according to the sampling depth and position. The shallow community in coastal stations presented distinguishable patterns of diatoms and ciliates compared with AG stations. These results indicate that there was a strong horizontal coupling between phytoplankton and ciliate communities. Abundance of Radiolaria and Syndiniales increased with depth. Our analyses demonstrate that the stratification disruption produced by the AG caused shifts in the trophic ecology of the plankton assemblages inducing a transition from bottom-up to top-down control.

To assess the likely economic outcomes to fishing fleets of the Landing Obligation (LO), bioeconomic models covering seven European fisheries, ranging from the North East Atlantic to the Mediterranean, have been applied to estimate the economic performance of fleets before and after implementing the LO. It is shown that for most of the analysed fisheries, their economic outcome will be negatively affected in the long term by the LO, when compared to the expected outcome with no LO. Efficient mitigation strategies (exemptions, quota uplifts, improved selectivity, effort reallocation and others) may, for some of the analysed fisheries, reduce the negative economic effect of the LO. Moreover, the possibility to trade quotas, both nationally and internationally, may also reduce the economic losses caused by the LO. However, even with mitigation strategies and/or quota trade in place, most of the analysed fisheries are worse off under the LO than what could be expected if the LO was not implemented.

In the Bay of Algeciras (BA), intensive urban and industrial activityis underway, which is potentially responsible for the release of significant quantities of nutrients. However, the assessment of the impact of these discharges is complex. Nutrient concentration in the surface layer is per se strongly variable due to the variability associated with the upwelling of nutrient-enriched deep Mediterranean water (MW), which in turn is regulated by atmospheric forcing. The aim of this study is to determine the effects of changes in the upwelling intensity on the load of nitrate and phosphate in the BA and to appraise their impact on chlorophyll a variability. Based on this analysis, the possible influence of the nutrients released from land-based sources is indirectly inferred. Data and samples collected during nine research cruises carried out in different seasonal cycle periods between 2010 and 2015 in the BA were analysed. The vertical variation of temperature and salinity indicates that the MW upwelling was favoured in spring, as occurred in other coastal areas of the northern Alboran Sea. However, principal component analysis conducted on physical and chemical data reveals that shifts in nutrients and chlorophyll a in the euphotic layer are poorly explained by changes in the upwelling intensity. Furthermore, during some of these research surveys (particularly in summer), chlorophyll a concentrations were higher in the BA as compared to a nearby coastal area also affected by MW upwelling. Scarce information about land-based pollution sources precludes quantitative analysis of the impact of nutrient loads on water quality; however, the available data suggest that the main source of allochthanous inorganic nitrogen over the period 2010–2015 in the BA was nitrate. Therefore, it is reasonable to hypothesize that the high concentrations of nitrate and chlorophyll a in BA in summer are a consequence of those discharges. Our study highlights the need of more exhaustive inve

The distribution of marine productivity in the Alboran Sea responds strongly to its hydrodynamics, shaped by the influence of the Atlantic jet that enters through the Gibraltar Strait. This stream originates an oligotrophic western anticyclonic gyre (WAG) that dominates the western basin of the Alboran Sea. We studied vertical (0–900 m) diel changes in zooplankton biomass, potential respiration (electron transport system activity, ETS) and growth rates (aminoacyl-tRNA synthetases activity, AARS), to assess their variability in relation to the WAG structure. Zooplankton biomass was distributed in distinctive layers and we observed strong diel vertical migrations in the open sea. Diel vertical migrants (DVM) biomass, production and respiration rates doubled within the WAG core. The active carbon flux to mesopelagic waters mediated by DVM, estimated from respiration and mortality at depth, increased from the coast (2.0–5.7 mg C m−2 d−1) towards the gyre core (27.1–76.7 mg C m−2 d−1). The WAG enhanced the carbon export to deep waters, reinforcing the role of the Alboran Sea as sink of atmospheric carbon.

The Alboran Sea is highly dynamic from a hydrographical point of view. Depending on the strength of the currents and the direction of the wind the surface coastal water masses can be either of Atlantic or Mediterranean origin. This variability affects both the phytoplankton and zooplankton components of the community inhabiting the Bay of Málaga. In addition, fish larvae distribution varies with the diel cycle, affecting zooplankton distribution in shallow waters. In order to provide a first insight into the variability of the planktonic community composition in the area during a 24 hour cycle, we applied an integrative approach combining morphological and molecular tools.

The seasonal changes in structure and functioning of the pelagic trophic web in Málaga Bay (NW Alboran Sea) are related to the annual hydrological cycle. However, time series analyses have shown that the relationship between interannual hydrological variability and the plankton community composition is weak. This might be due to different human-induced pressures (nutrient pollution, coastal fisheries) acting on different compartments of the trophic web. The net effect of all these factors would depend on how the ecosystem channels changes in the composition and abundance of each trophic level. Interactions of phytoplankton-ciliates-zooplankton might have a central role in the regulation of the trophic web in Málaga Bay, although the trophic relations of the dominant groups remain still undefined. In order to identify the dominant trophic relationships we aimed to characterise the diet of key ichthyo- and mesozooplankton species in the field. Given that gut content preys (phyto- and microplankton) are fragile and not easy to identify visually, we developed species-specific molecular markers to detect their presence/absence within the predators gut.