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Plankton are an important component of life on Earth. Since the 19th century, scientists have attempted to quantify species distributions using many techniques, such as direct counting, sizing, and classification with microscopes. Since then, extraordinary work has been performed regarding the development of plankton imaging systems, producing a massive backlog of images that await classification. Automatic image processing and classification approaches are opening new avenues for avoiding time-consuming manual procedures. While some algorithms have been adapted from many other applications for use with plankton, other exciting techniques have been developed exclusively for this issue. Achieving higher accuracy than that of human taxonomists is not yet possible, but an expeditious analysis is essential for discovering the world beyond plankton. Recent studies have shown the imminent development of real-time, in situ plankton image classification systems, which have only been slowed down by the complex implementations of algorithms on low-power processing hardware. This article compiles the techniques that have been proposed for classifying marine plankton, focusing on automatic methods that utilize image processing, from the beginnings of this field to the present day. [ABSTRACT FROM AUTHOR]

This paper presents a study of an automated system for identifying planktic foraminifera at the species level. The system uses a combination of deep learning methods, specifically convolutional neural networks (CNNs), to analyze digital images of foraminifera taken at different illumination angles. The dataset is composed of 1437 groups of sixteen grayscale images, one group for each foraminifera specimen, that are then converted to RGB images with various processing methods. These RGB images are fed into a set of CNNs, organized in an ensemble learning (EL) environment. The ensemble is built by training different networks using different approaches for creating the RGB images. The study finds that an ensemble of CNN models trained on different RGB images improves the system’s performance compared to other state-of-the-art approaches. The main focus of this paper is to introduce multiple colorization methods that differ from the current cutting-edge techniques; novel strategies like Gaussian or mean-based techniques are suggested. The proposed system was also found to outperform human experts in classification accuracy.

In this paper, we present a study about an automated system for monitoring underwater ecosystems. The system here proposed is based on the fusion of different deep learning methods. We study how to create an ensemble based of different Convolutional Neural Network (CNN) models, fine-tuned on several datasets with the aim of exploiting their diversity. The aim of our study is to experiment the possibility of fine-tuning CNNs for underwater imagery analysis, the opportunity of using different datasets for pre-training models, the possibility to design an ensemble using the same architecture with small variations in the training procedure. Our experiments, performed on 5 well-known datasets (3 plankton and 2 coral datasets) show that the combination of such different CNN models in a heterogeneous ensemble grants a substantial performance improvement with respect to other state-of-the-art approaches in all the tested problems. One of the main contributions of this work is a wide experimental evaluation of famous CNN architectures to report the performance of both the single CNN and the ensemble of CNNs in different problems. Moreover, we show how to create an ensemble which improves the performance of the best single model. The MATLAB source code is freely link provided in title page.

In this paper, we present a study about an automated system for monitoring underwater ecosystems. The system here proposed is based on the fusion of different deep learning methods. We study how to create an ensemble based of different Convolutional Neural Network (CNN) models, fine-tuned on several datasets with the aim of exploiting their diversity. The aim of our study is to experiment the possibility of fine-tuning CNNs for underwater imagery analysis, the opportunity of using different datasets for pre-training models, the possibility to design an ensemble using the same architecture with small variations in the training procedure. Our experiments, performed on 5 well-known datasets (3 plankton and 2 coral datasets) show that the combination of such different CNN models in a heterogeneous ensemble grants a substantial performance improvement with respect to other state-of-the-art approaches in all the tested problems. One of the main contributions of this work is a wide experimental evaluation of famous CNN architectures to report the performance of both the single CNN and the ensemble of CNNs in different problems. Moreover, we show how to create an ensemble which improves the performance of the best single model. The MATLAB source code is freely link provided in title page. [ABSTRACT FROM AUTHOR]

Bioseston is a heterogeneous assemblage of bacterioplankton, phytoplankton, zooplankton, and planktonic debris. A detailed knowledge of biosestons is essential for understanding the dynamics of trophic flows in marine ecosystems. The distributional features of seston biomass in plankton (micro- and mesoplankton) in the Southwest Atlantic Ocean (Rio de Janeiro State, Brazil) were analyzed using stratified samples gathered to a depth of 2,400 m during night time. The horizontal pattern of biomass distribution was analyzed vis-a-vis station depth during both wet and dry periods, with higher values recorded in the continental shelf than in the slope, confirming the terrestrial contribution of nutrient sources to the marine environment. This horizontal variation reinforces the occurrence of seasonal vortices in Cabo Frio and Cabo de São Tomé on the central coast of Brazil. Environmental variables reflect the hydrological signatures of the water masses along the Brazilian coast. The largest seston biomass was related to high temperatures, salinities, and low inorganic nutrient concentrations in tropical and South Atlantic central waters. The observed distribution patterns suggest that seston biomass in plankton in the region may be structured based on partitioned horizontal and vertical habitats and food resources.

Seasonal fluctuations profoundly affect marine microeukaryotic plankton composition and metabolism, but accurately tracking these changes has been a long-standing challenge. In this study, we present a year-long metatranscriptomic data set from the Southern Bight of the North Sea, shedding light on the seasonal dynamics in temperate plankton ecosystems. We observe distinct shifts in active plankton species and their metabolic processes in response to seasonal changes. We characterized the metabolic signatures of different seasonal phases in detail, thereby revealing the metabolic versatility of dinoflagellates, the heterotrophic dietary strategy of Phaeocystis during its late-stage blooms, and stark variations in summer and fall diatom abundance and metabolic activity across nearby sampling stations. Our data illuminate the varied contributions of microeukaryotic taxa to biomass production and nutrient cycling at different times of the year and allow delineation of their ecological niches., Importance: Ecosystem composition and metabolic functions of temperate marine microeukaryote plankton are strongly influenced by seasonal dynamics. Although monitoring of species composition of microeukaryotes has expanded recently, few methods also contain seasonally resolved information on ecosystem functioning. We generated a year-long spatially resolved metatranscriptomic data set to assess seasonal dynamics of microeukaryote species and their associated metabolic functions in the Southern Bight of the North Sea. Our study underscores the potential of metatranscriptomics as a powerful tool for advancing our understanding of marine ecosystem functionality and resilience in response to environmental changes, emphasizing its potential in continuous marine ecosystem monitoring to enhance our ecological understanding of the ocean's eukaryotic microbiome., Competing Interests: The authors declare no conflict of interest.

Niche selection and microbial dispersal are key factors that shape microbial communities. However, their relative significance varies across different environments and spatiotemporal scales. While most studies focus on the impact of these forces on community composition, few consider other structural levels such as the physiological stage of the microbial community and single-cell characteristics. To understand the relative influence of microbial dispersal and niche selection on various community structural levels, we concurrently examined the taxonomic composition, abundance and single-cell characteristics of bacterioplankton in an acidic reservoir (El Sancho, Spain) during stratification and mixing periods. A cluster analysis based on environmental variables identified five niches during stratification and one during mixing. Canonical correspondence analysis (CCA) revealed that communities within each niche differed in both, taxonomic and single-cell characteristics. The environmental variables that explained the variation in class-based ordination differed from those explaining the ordination based on single-cell characteristics. However, a Procrustes analysis indicated a high correlation between the CCA ordinations based on both structural levels, suggesting simultaneous changes in the microbial community at multiple structural levels. Our findings underscore the dominant role of environmental selection in occupying different microbial niches, given that microbial dispersal was not restricted., (© 2024 The Authors. Environmental Microbiology Reports published by John Wiley & Sons Ltd.)

The nature and extent of diversity in the plankton has fascinated scientists for over a century. Initially, the discovery of many new species in the remarkably uniform and unstructured pelagic environment appeared to challenge the concept of ecological niches. Later, it became obvious that only a fraction of plankton diversity had been formally described, because plankton assemblages are dominated by understudied eukaryotic lineages with small size that lack clearly distinguishable morphological features. The high diversity of the plankton has been confirmed by comprehensive metabarcoding surveys, but interpretation of the underlying molecular taxonomies is hindered by insufficient integration of genetic diversity with morphological taxonomy and ecological observations. Here we use planktonic foraminifera as a study model and reveal the full extent of their genetic diversity and investigate geographical and ecological patterns in their distribution. To this end, we assembled a global data set of ~7600 ribosomal DNA sequences obtained from morphologically characterised individual foraminifera, established a robust molecular taxonomic framework for the observed diversity, and used it to query a global metabarcoding data set covering ~1700 samples with ~2.48 billion reads. This allowed us to extract and assign 1 million reads, enabling characterisation of the structure of the genetic diversity of the group across ~1100 oceanic stations worldwide. Our sampling revealed the existence of, at most, 94 distinct molecular operational taxonomic units (MOTUs) at a level of divergence indicative of biological species. The genetic diversity only doubles the number of formally described species identified by morphological features. Furthermore, we observed that the allocation of genetic diversity to morphospecies is uneven. Only 16 morphospecies disguise evolutionarily significant genetic diversity, and the proportion of morphospecies that show genetic diversity increases poleward. Finally, we observe that MOTUs have a narrower geographic distribution than morphospecies and that in some cases the MOTUs belonging to the same morphospecies (cryptic species) have different environmental preferences. Overall, our analysis reveals that even in the light of global genetic sampling, planktonic foraminifera diversity is modest and finite. However, the extent and structure of the cryptic diversity reveals that genetic diversification is decoupled from morphological diversification, hinting at different mechanisms acting at different levels of divergence., (© 2024 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.)

Background: Single amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) are the predominant sources of information about the coding potential of uncultured microbial lineages, but their strengths and limitations remain poorly understood. Here, we performed a direct comparison of two previously published collections of thousands of SAGs and MAGs obtained from the same, global environment., Results: We found that SAGs were less prone to chimerism and more accurately reflected the relative abundance and the pangenome content of microbial lineages inhabiting the epipelagic of the tropical and subtropical ocean, as compared to MAGs. SAGs were also better suited to link genome information with taxa discovered through 16S rRNA amplicon analyses. Meanwhile, MAGs had the advantage of more readily recovering genomes of rare lineages., Conclusions: Our analyses revealed the relative strengths and weaknesses of the two most commonly used genome recovery approaches in environmental microbiology. These considerations, as well as the need for better tools for genome quality assessment, should be taken into account when designing studies and interpreting data that involve SAGs or MAGs. Video Abstract., (© 2024. The Author(s).)

In order to understand the stability of the zooplankton and phytoplankton communities in the Guizhou plateau reservoir environment, the process of reservoir water quality change affecting the stability of plankton was studied. The changes in the plankton community and water quality in three different nutrient reservoirs （Huaxi Reservoir, Goupitan Reservoir, and Hailong Reservoir） were studied from October 2020 to August 2021. The stability of the zooplankton and phytoplankton communities was studied using time-lag analysis （TLA）. Variance decomposition analysis （VPA） was used to explore the response of the two communities to environmental changes. The driving factors of plankton community changes in reservoirs were also revealed. The results showed that Huaxi Reservoir and Goupitan Reservoir were mesotrophic reservoirs, and Hailong Reservoir was a eutrophic reservoir. The average comprehensive nutrition indices of the three reservoirs were 44.07, 44.68, and 50.25. A total of 51 species of zooplankton rotifers, 39 species of rotifers, three species of copepods, and nine species of cladocera were identified. Among them, the abundance of rotifers was the highest, accounting for 85.96%. A total of seven phyla and 73 species of phytoplankton were identified, including 16 species in the phylum Cyanophyta , 32 species in the phylum Chlorophyta , 16 species in the phylum Diatoma, three species in the phylum Chlorophyta , four species in the phylum Euglenophyta , and one species each in the phyla Cryptophyta and Chrysophyta . Among them, the abundance of cyanobacteria and diatoms was the highest, accounting for 66.2% and 27.35%, respectively. The median absolute deviation （MAD） of the Bray-Curtis distance of zooplankton and phytoplankton community in the three reservoirs were 0.67 and 0.65 in Huaxi Reservoir, 0.80 and 0.69 in Goupitan Reservoir, and 0.85 and 0.47 in Hailong Reservoir, respectively. The larger the value, the greater the variation in the community. The absolute value of the slope of zooplankton was greater than that of phytoplankton in the TLA results, and the absolute values of the slopes were 0.018 and 0.004, respectively. The larger the absolute value of the slope, the faster the community variability. The zooplankton community in the three reservoirs was less stable than the phytoplankton community and more sensitive to environmental changes, and the degree of variation was greater. The higher the degree of eutrophication of the reservoir, the more obvious this phenomenon. VPA showed that the changes in plankton communities in Huaxi Reservoir and Hailong Reservoir were mainly influenced by water temperature and eutrophication factors. The changes in planktonic community in Goupitan Reservoir were mainly influenced by water temperature and chemical factors. The driving factors of Huaxi Reservoir were water temperature, TP, permanganate index, and SD. The driving factors of Goupitan Reservoir were water temperature, NO 3 - - N, and pH. The driving factors of Hailong Reservoir were water temperature and TP. Nutrients and water temperature were the main factors affecting the stability of plankton communities in reservoirs.

Plankton are effective indicators of environmental change and ecosystem health in freshwater habitats, but collection of plankton data using manual microscopic methods is extremely labor-intensive and expensive. Automated plankton imaging offers a promising way forward to monitor plankton communities with high frequency and accuracy in real-time. Yet, manual annotation of millions of images proposes a serious challenge to taxonomists. Deep learning classifiers have been successfully applied in various fields and provided encouraging results when used to categorize marine plankton images. Here, we present a set of deep learning models developed for the identification of lake plankton, and study several strategies to obtain optimal performances, which lead to operational prescriptions for users. To this aim, we annotated into 35 classes over 17900 images of zooplankton and large phytoplankton colonies, detected in Lake Greifensee (Switzerland) with the Dual Scripps Plankton Camera. Our best models were based on transfer learning and ensembling, which classified plankton images with 98% accuracy and 93% F1 score. When tested on freely available plankton datasets produced by other automated imaging tools (ZooScan, Imaging FlowCytobot, and ISIIS), our models performed better than previously used models. Our annotated data, code and classification models are freely available online. [ABSTRACT FROM AUTHOR]

Plankton are effective indicators of environmental change and ecosystem health in freshwater habitats, but collection of plankton data using manual microscopic methods is extremely labor-intensive and expensive. Automated plankton imaging offers a promising way forward to monitor plankton communities with high frequency and accuracy in real-time. Yet, manual annotation of millions of images proposes a serious challenge to taxonomists. Deep learning classifiers have been successfully applied in various fields and provided encouraging results when used to categorize marine plankton images. Here, we present a set of deep learning models developed for the identification of lake plankton, and study several strategies to obtain optimal performances, which lead to operational prescriptions for users. To this aim, we annotated into 35 classes over 17900 images of zooplankton and large phytoplankton colonies, detected in Lake Greifensee (Switzerland) with the Dual Scripps Plankton Camera. Our best models were based on transfer learning and ensembling, which classified plankton images with 98% accuracy and 93% F1 score. When tested on freely available plankton datasets produced by other automated imaging tools (ZooScan, Imaging FlowCytobot, and ISIIS), our models performed better than previously used models. Our annotated data, code and classification models are freely available online.

Winter conditions greatly alter the limnological properties of lotic ecosystems and the availability of nutrients, carbon, and energy resources for microbial processes. However, the composition and metabolic capabilities of winter microbial communities are still largely uncharacterized. Here, we sampled the winter under-ice microbiome of the Great Whale River (Nunavik, Canada) and its discharge plume into Hudson Bay. We used a combination of 16S and 18S rRNA gene amplicon analysis and metagenomic sequencing to evaluate the size-fractionated composition and functional potential of the microbial plankton. These under-ice communities were diverse in taxonomic composition and metabolically versatile in terms of energy and carbon acquisition, including the capacity to carry out phototrophic processes and degrade aromatic organic matter. Limnological properties, community composition, and metabolic potential differed between shallow and deeper sites in the river, and between fresh and brackish water in the vertical profile of the plume. Community composition also varied by size fraction, with a greater richness of prokaryotes in the larger size fraction (>3 µm) and of microbial eukaryotes in the smaller size fraction (0.22-3 µm). The freshwater communities included cosmopolitan bacterial genera that were previously detected in the summer, indicating their persistence over time in a wide range of physico-chemical conditions. These observations imply that the microbial communities of subarctic rivers and their associated discharge plumes retain a broad taxonomic and functional diversity throughout the year and that microbial processing of complex terrestrial materials persists beneath the ice during the long winter season., Importance: Microbiomes vary over multiple timescales, with short- and long-term changes in the physico-chemical environment. However, there is a scarcity of data and understanding about the structure and functioning of aquatic ecosystems during winter relative to summer. This is especially the case for seasonally ice-covered rivers, limiting our understanding of these ecosystems that are common throughout the boreal, subpolar, and polar regions. Here, we examined the winter under-ice microbiome of a Canadian subarctic river and its entry to the sea to characterize the taxonomic and functional features of the microbial community. We found substantial diversity in both composition and functional capabilities, including the capacity to degrade complex terrestrial compounds, despite the constraints imposed by a prolonged seasonal ice-cover and near-freezing water temperatures. This study indicates the ecological complexity and importance of winter microbiomes in ice-covered rivers and the coastal marine environment that they discharge into., Competing Interests: The authors declare no conflict of interest.

Phytoplankton are important drivers of aquatic ecosystem function and environmental health. Their community compositions and distributions are directly impacted by environmental processes and human activities, including in the largest estuary in North America, the Chesapeake Bay. It is crucial to uncover how planktonic eukaryotes play fundamental roles as primary producers and trophic links and sustain estuarine ecosystems. In this study, we investigated the detailed community structure and spatiotemporal variations of planktonic eukaryotes in the Chesapeake Bay across space and time for three consecutive years. A clear seasonal and spatial shift of total, abundant, and rare planktonic eukaryotes was evident, and the pattern recurred interannually. Multiple harmful algal species have been identified in the Bay with varied distribution patterns, such as Karlodinium, Heterosigma akashiwo, Protoperidinium sp., etc. Compared to abundant taxa, rare subcommunities were more sensitive to environmental disturbance in terms of richness, diversity, and distribution. The combined effects of temporal variation (13.3%), nutrient availability (10.0%), and spatial gradients (8.8%) structured the distribution of eukaryotic microbial communities in the Bay. Similar spatiotemporal patterns between planktonic prokaryotes and eukaryotes suggest common mechanisms of adjustment, replacement, and species interaction for planktonic microbiomes under strong estuarine gradients. To our best knowledge, this work represents the first systematic study on planktonic eukaryotes in the Bay. A comprehensive view of the distribution of planktonic microbiomes and their interactions with environmental processes is critical in understanding the underlying microbial mechanisms involved in maintaining the stability, function, and environmental health of estuarine ecosystems., Importance: Deep sequencing analysis of planktonic eukaryotes in the Chesapeake Bay reveals high community diversity with many newly recognized phytoplankton taxa. The Chesapeake Bay planktonic eukaryotes show distinct seasonal and spatial variability, with recurring annual patterns of total, abundant, and rare groups. Rare taxa mainly contribute to eukaryotic diversity compared to abundant groups, and they are more sensitive to spatiotemporal variations and environmental filtering. Temporal variations, nutrient availability, and spatial gradients significantly affect the distribution of eukaryotic microbial communities. Similar spatiotemporal patterns in prokaryotes and eukaryotes suggest common mechanisms of adjustment, substitution, and species interactions in planktonic microbiomes under strong estuarine gradients. Interannually recurring patterns demonstrate that diverse eukaryotic taxa have well adapted to the estuarine environment with a long residence time. Further investigations of how human activities impact estuarine planktonic eukaryotes are critical in understanding their essential ecosystem roles and in maintaining environmental safety and public health., Competing Interests: The authors declare no conflict of interest.

In palaeontological studies, groups with consistent ecological and morphological traits across a clade's history (functional groups) 1 afford different perspectives on biodiversity dynamics than do species and genera 2,3 , which are evolutionarily ephemeral. Here we analyse Triton, a global dataset of Cenozoic macroperforate planktonic foraminiferal occurrences 4 , to contextualize changes in latitudinal equitability gradients 1 , functional diversity, palaeolatitudinal specialization and community equitability. We identify: global morphological communities becoming less specialized preceding the richness increase after the Cretaceous-Palaeogene extinction; ecological specialization during the Early Eocene Climatic Optimum, suggesting inhibitive equatorial temperatures during the peak of the Cenozoic hothouse; increased specialization due to circulation changes across the Eocene-Oligocene transition, preceding the loss of morphological diversity; changes in morphological specialization and richness about 19 million years ago, coeval with pelagic shark extinctions 5 ; delayed onset of changing functional group richness and specialization between hemispheres during the mid-Miocene plankton diversification. The detailed nature of the Triton dataset permits a unique spatiotemporal view of Cenozoic pelagic macroevolution, in which global biogeographic responses of functional communities and richness are decoupled during Cenozoic climate events. The global response of functional groups to similar abiotic selection pressures may depend on the background climatic state (greenhouse or icehouse) to which a group is adapted., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Abstract Background Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Results Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system outperforms state-of-the-art plankton image classification systems in terms of accuracy and robustness. Conclusions This study demonstrated automatic plankton image classification system combining multiple view features using multiple kernel learning. The results indicated that multiple view features combined by NLMKL using three kernel functions (linear, polynomial and Gaussian kernel functions) can describe and use information of features better so that achieve a higher classification accuracy.

Importance: Single-celled eukaryotes play ecologically significant roles in the marine environment, yet fundamental questions about their biodiversity, ecological function, and interactions remain. Environmental sequencing enables researchers to document naturally occurring protistan communities, without culturing bias, yet metagenomic and metatranscriptomic sequencing approaches cannot separate individual species from communities. To more completely capture the genomic content of mixed protistan populations, we can create bins of sequences that represent the same organism (metagenome-assembled genomes [MAGs]). We developed the EukHeist pipeline, which automates the binning of population-level eukaryotic and prokaryotic genomes from metagenomic reads. We show exciting insight into what protistan communities are present and their trophic roles in the ocean. Scalable computational tools, like EukHeist, may accelerate the identification of meaningful genetic signatures from large data sets and complement researchers' efforts to leverage MAG databases for addressing ecological questions, resolving evolutionary relationships, and discovering potentially novel biodiversity., Competing Interests: The authors declare no conflict of interest.

Abstract Plankton are the most fundamental components of ocean ecosystems, due to their function at many levels of the oceans food chain. Studying and monitoring plankton distribution is vital for global climate and environment protection. Currently, much research is concentrated on the automated recognition of plankton and several imaging-based technologies have been developed for collecting plankton images continuously using underwater image sensors. In this paper, we present a study about an automated plankton recognition system, which is based on the fusion of different deep learning methods. In this work we study both the fine tuning of several deep learned models and transfer learning from the same models with the aim of exploiting their diversity in designing an ensemble of classifiers, we deal with: (i) the ability of fine-tuning pre-trained CNN for plankton classification, (ii) the possibility of using pre-trained CNN for transfer learning, (iii) the possibility of coupling pre-processing to CNN in order to improve their feature extraction capability. The combination of such different descriptors/methods in a heterogeneous ensemble grants a substantial performance improvement with respect to other state-of-the-art approaches based on feature selection and classification. The experimental evaluation on three large publicly available datasets demonstrates high classification accuracy and f-measure of our ensemble with respect to other classifiers on the same datasets. One of the main contributions of this work is a collection of classification models and a wide experimental evaluation to report performance of both single CNN and ensemble of CNNs in different available plankton datasets with a given testing protocol. Moreover, we show how to combine different CNN in order to improve the performance. To encourage future comparisons the MATLAB source code is available in the GitHub repository: https://github.com/LorisNanni. Highlights • Applied deep learning to classify plankton images • Transfer learning and fine-tuning of pre-trained models • Assessing the importance of coupling pre-processing to CNN • Ensembles of deep learning models improve performance with respect to single model • Experiments on 3 datasets proves high classification performance of our ensemble [ABSTRACT FROM AUTHOR]

Determining biodiversity responses to environmental change, such as acidification, is critical for ecosystem projections under future global change scenarios. Here, we analyzed three plankton communities of phytoplankton, crustaceans and rotifers in 28 lakes in the Adirondack Park, USA, during 1994-2012, and examined the spatiotemporal trends in their alpha and beta diversity during recovery from acidification. For all plankton assemblages, Shannon diversity increased towards recent years and high lake pH, and there was an increasing community dissimilarity with pH changes. The spatial mean Bray-Curtis dissimilarities across all lakes decreased over time for phytoplankton and rotifers leading to an increase in spatial homogenization. Such a homogenization cooccurred however with the overall increasing diversity in this region, which contrasts with the previous classic view that homogenization is mainly driven by loss of species and results in biodiversity loss. We further observed lower temporal mean beta diversity in low-pH lakes for crustaceans and rotifers, but not for phytoplankton. Generally, spatial and temporal mean beta diversity of the three taxonomic groups were primarily driven by lake-water ion variables, and rotifers were also constrained by nutrients and climate. Collectively, our results show how and why plankton community compositions vary over space along with acidification recovery, and further highlight the importance of spatiotemporal studies combined with long-term monitoring programs in assessing biodiversity change during the recovery of disturbed ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

It is well-established that environmental variability and cyanobacterial blooms have major effects on the assembly and functioning of bacterial communities in both marine and freshwater habitats. It remains unclear, however, how the ciliate community responds to such changes over the long-term, particularly in subtropical lake and reservoir ecosystems. We analysed 9-year planktonic ciliate data series from the surface water of two subtropical reservoirs to elucidate the role of cyanobacterial bloom and environmental variabilities on the ciliate temporal dynamics. We identified five distinct periods of cyanobacterial succession in both reservoirs. Using multiple time-scale analyses, we found that the interannual variability of ciliate communities was more strongly related to cyanobacterial blooms than to other environmental variables or to seasonality. Moreover, the percentage of species turnover across cyanobacterial bloom and non-bloom periods increased significantly with time over the 9-year period. Phylogenetic analyses further indicated that 84 %-86 % of ciliate community turnover was governed by stochastic dispersal limitation or undominated processes, suggesting that the ciliate communities in subtropical reservoirs were mainly controlled by neutral processes. However, short-term blooms increased the selection pressure and drove 30 %-53 % of the ciliate community turnover. We found that the ciliate community composition was influenced by environmental conditions with nutrients, cyanobacterial biomass and microzooplankton having direct and/or indirect significant effects on the ciliate taxonomic or functional community dynamics. Our results provide new insights into the long-term temporal dynamics of planktonic ciliate communities under cyanobacterial bloom disturbance., Competing Interests: Declaration of competing interest The authors declare no competing financial interests. The authors alone are responsible for the content and writing of this article., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The geographic ranges of marine organisms, including planktonic foraminifera 1 , diatoms, dinoflagellates 2 , copepods 3 and fish 4 , are shifting polewards owing to anthropogenic climate change 5 . However, the extent to which species will move and whether these poleward range shifts represent precursor signals that lead to extinction is unclear 6 . Understanding the development of marine biodiversity patterns over geological time and the factors that influence them are key to contextualizing these current trends. The fossil record of the macroperforate planktonic foraminifera provides a rich and phylogenetically resolved dataset that provides unique opportunities for understanding marine biogeography dynamics and how species distributions have responded to ancient climate changes. Here we apply a bipartite network approach to quantify group diversity, latitudinal specialization and latitudinal equitability for planktonic foraminifera over the past eight million years using Triton, a recently developed high-resolution global dataset of planktonic foraminiferal occurrences 7 . The results depict a global, clade-wide shift towards the Equator in ecological and morphological community equitability over the past eight million years in response to temperature changes during the late Cenozoic bipolar ice sheet formation. Collectively, the Triton data indicate the presence of a latitudinal equitability gradient among planktonic foraminiferal functional groups which is coupled to the latitudinal biodiversity gradient only through the geologically recent past (the past two million years). Before this time, latitudinal equitability gradients indicate that higher latitudes promoted community equitability across ecological and morphological groups. Observed range shifts among marine planktonic microorganisms 1,2,8 in the recent and geological past suggest substantial poleward expansion of marine communities even under the most conservative future global warming scenarios., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

The latitudinal diversity gradient (LDG) is a prevalent feature of modern ecosystems across diverse clades 1-4 . Recognized for well over a century, the causal mechanisms for LDGs remain disputed, in part because numerous putative drivers simultaneously covary with latitude 1,3,5 . The past provides the opportunity to disentangle LDG mechanisms because the relationships among biodiversity, latitude and possible causal factors have varied over time 6-9 . Here we quantify the emergence of the LDG in planktonic foraminifera at high spatiotemporal resolution over the past 40 million years, finding that a modern-style gradient arose only 15 million years ago. Spatial and temporal models suggest that LDGs for planktonic foraminifera may be controlled by the physical structure of the water column. Steepening of the latitudinal temperature gradient over 15 million years ago, associated with an increased vertical temperature gradient at low latitudes, may have enhanced niche partitioning and provided more opportunities for speciation at low latitudes. Supporting this hypothesis, we find that higher rates of low-latitude speciation steepened the diversity gradient, consistent with spatiotemporal patterns of depth partitioning by planktonic foraminifera. Extirpation of species from high latitudes also strengthened the LDG, but this effect tended to be weaker than speciation. Our results provide a step change in understanding the evolution of marine LDGs over long timescales., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

The ocean-atmosphere exchange of CO 2 largely depends on the balance between marine microbial photosynthesis and respiration. Despite vast taxonomic and metabolic diversity among marine planktonic bacteria and archaea (prokaryoplankton) 1-3 , their respiration usually is measured in bulk and treated as a 'black box' in global biogeochemical models 4 ; this limits the mechanistic understanding of the global carbon cycle. Here, using a technology for integrated phenotype analyses and genomic sequencing of individual microbial cells, we show that cell-specific respiration rates differ by more than 1,000× among prokaryoplankton genera. The majority of respiration was found to be performed by minority members of prokaryoplankton (including the Roseobacter cluster), whereas cells of the most prevalent lineages (including Pelagibacter and SAR86) had extremely low respiration rates. The decoupling of respiration rates from abundance among lineages, elevated counts of proteorhodopsin transcripts in Pelagibacter and SAR86 cells and elevated respiration of SAR86 at night indicate that proteorhodopsin-based phototrophy 3,5-7 probably constitutes an important source of energy to prokaryoplankton and may increase growth efficiency. These findings suggest that the dependence of prokaryoplankton on respiration and remineralization of phytoplankton-derived organic carbon into CO 2 for its energy demands and growth may be lower than commonly assumed and variable among lineages., (© 2022. The Author(s).)

DNA viruses are increasingly recognized as influencing marine microbes and microbe-mediated biogeochemical cycling. However, little is known about global marine RNA virus diversity, ecology, and ecosystem roles. In this study, we uncover patterns and predictors of marine RNA virus community- and "species"-level diversity and contextualize their ecological impacts from pole to pole. Our analyses revealed four ecological zones, latitudinal and depth diversity patterns, and environmental correlates for RNA viruses. Our findings only partially parallel those of cosampled plankton and show unexpectedly high polar ecological interactions. The influence of RNA viruses on ecosystems appears to be large, as predicted hosts are ecologically important. Moreover, the occurrence of auxiliary metabolic genes indicates that RNA viruses cause reprogramming of diverse host metabolisms, including photosynthesis and carbon cycling, and that RNA virus abundances predict ocean carbon export.

Abstract: Plankton recognition plays an important role in the ocean environmental research. In this paper, we propose a random subspace based algorithm to classify the plankton images detected in real time by the Shadowed Image Particle Profiling and Evaluation Recorder. The difficulty of such classification is multifold because the data sets are not only much noisier but the plankton are deformable, projection-variant, and often in partial occlusion. In addition, the images in our experiments are binary, thus are lack of texture information. Using random sampling, we construct a set of stable classifiers to take full advantage of nearly all the discriminative information in the feature space of plankton images. The combination of multiple stable classifiers is better than a single classifier. We achieve over 93% classification accuracy on a collection of more than 3000 images, making it comparable with what a trained biologist can achieve by using conventional manual techniques. [Copyright &y& Elsevier]

Nutrient dynamics function globally, flowing from rivers to the ocean (estuarine-coastal zone), and are vulnerable to climate change. Microbial habitats can be affected by marine nutrient dynamics and may provide a clue to predict microbial responses to environmental heterogeneity in estuarine-coastal zones. We surveyed surface seawater in Gwangyang Bay, a semi-enclosed estuary in Korea, from 2016 to 2018 using a metabarcoding approach with prokaryotic 16S and eukaryotic 18S rRNA genes. Bacterial and microeukaryotic communities in these waters showed distinct local communities in response to environmental heterogeneity and community transition at spatiotemporal scales in the estuarine-coastal zone. The relative abundance of prokaryotic and eukaryotic operational taxonomic units suggested a microbial trophic interaction in the Gwangyang Bay waters. We found that the community assembly process in prokaryotic communities was primarily influenced by biological interaction (immigration-emigration), whereas that in eukaryotic communities was more affected by environmental stress (habitat specificity) rather than by biotic factors. Our findings in the Gwangyang Bay waters may provide information on underlying (biotic or abiotic) factors of the assembly process in microbial communities in the estuarine-coastal zone., (© 2022. The Author(s).)

Coastal ecosystems globally are exposed to the most pervasive anthropogenic activities, caused by a suite of human infrastructure and enterprises such as shipping ports, aquaculture facilities, fishing, and tourism. These anthropogenic activities may lead to changes in ecosystem biodiversity, followed by loss of ecosystem functioning and services. Shipping industry and aquaculture have also been recognized as the main vectors for introduction of marine non-indigenous species (NIS) worldwide. In this study, we used DNA metabarcoding-based methods to investigate plankton biodiversity under varying anthropogenic pressures (shipping and bivalve aquaculture) along the eastern Adriatic coast (the northernmost part of the Mediterranean Sea). Our comparative assessment revealed similar community structures among investigated coastal locations (Northern, Central and Southern Adriatic). When the whole plankton communities were considered, they did not differ significantly between port and aquaculture sites. However, the proportion of the unique zOTUs in the port samples was remarkably higher than that in aquaculture sites (40.5% vs 8.2%), indicating that port areas may receive higher abundance and species richness of NIS than aquaculture sites. Further important difference between the two types of anthropogenically impacted habitats was a high abundance of three notorious invaders - M. leidyi, M. gigas, and H. elegans in late summer at the aquaculture site in Northern Adriatic. Therefore, the plankton community of the area is under pressure not only from aquaculture activities, but also establishment of NIS. Port areas are probably under greater introduction pressure from NIS, but aquaculture sites may experience greater community changes due to their establishment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Evidence increasingly suggests planktonic fungi (or mycoplankton) play an important role in marine food webs and biogeochemical cycles. In order to better understand their ecological role and how oceanographic gradients from the coastal to open ocean shape the mycoplankton community, molecular approaches were used to study fungal dynamics along a repeatedly sampled, five-station transect beginning at the mouth of an estuary and continuing 87 km across the continental shelf to the oligotrophic waters at the boundary of the Sargasso Sea. Similar to patterns in chlorophyll a , fungal 18S rRNA gene abundance showed a sharp decrease from nearshore to offshore stations. While Shannon's diversity was not statistically different across the transect, nonmetric multidimensional scaling (NMDS) ordination revealed that fungal communities at the nearshore station were significantly different from those at other stations. Even though spatial gradients were consistently strong, the shelf mycoplankton were more similar to those of the offshore communities when temperature was high (>20°C) and while they shifted toward the nearshore communities when temperature was low (<19°C), suggesting a role for additional seasonal factors (such as temperature) in shaping mycoplankton distributions. However, overall phylotype distributions were patchy with few taxa observed at all stations and the majority observed at a single station with the nearshore station exhibiting the largest number of exclusive phylotypes. Overall, our findings revealed the patchy spatial distributions and distinct niche partitioning of mycoplankton populations across a nearshore to open ocean gradient, which improved our understanding of fungal ecology in coastal waters. IMPORTANCE Fungi are an important, but understudied, group of heterotrophic microbes in marine environments. Traditionally, fungi in the coastal ocean were largely assumed to be derived from terrestrial inputs. Yet here we find many fungal taxa are endemic to the open ocean environment but are rare or absent in nearshore waters, suggesting they are not washed into the ocean from the land. As observed for the bacterioplankton, coastal oceanographic gradients can function as habitat barriers to partition fungal communities. Compared to the bacterioplankton, however, the mycoplankton exhibit a much patchier distribution pattern, suggesting differential drivers and the potential for spatially/temporally limited habitats or strong density-dependent selection. Therefore, our results show that mycoplankton in the coastal ocean may play a significant but complementary role to that of the bacterioplankton.

Microorganisms attached to aerosols can travel intercontinental distances, survive, and further colonize remote environments. Airborne microbes are influenced by environmental and climatic patterns that are predicted to change in the near future, with unknown consequences. We developed a new predictive method that dynamically addressed the temporal evolution of biodiversity in response to environmental covariates, linked to future climatic scenarios of the IPCC (AR5). We fitted these models against a 7-year monitoring of airborne microbes, collected in wet depositions. We found that Bacteria were more influenced by climatic variables than by aerosols sources, while the opposite was detected for Eukarya. Also, model simulations showed a general decline in bacterial richness, idiosyncratic responses of Eukarya, and changes in seasonality, with higher intensity within the worst-case climatic scenario (RCP 8.5). Additionally, the model predicted lower richness for airborne potential eukaryotic (fungi) pathogens of plants and humans. Our work pioneers on the potential effects of environmental variability on the airborne microbiome under the uncertain context of climate change., (© 2021. The Author(s).)

Ocean dynamics in the equatorial Pacific drive tropical climate patterns that affect marine and terrestrial ecosystems worldwide. How this region will respond to global warming has profound implications for global climate, economic stability and ecosystem health. As a result, numerous studies have investigated equatorial Pacific dynamics during the Pliocene (5.3-2.6 million years ago) and late Miocene (around 6 million years ago) as an analogue for the future behaviour of the region under global warming 1-12 . Palaeoceanographic records from this time present an apparent paradox with proxy evidence of a reduced east-west sea surface temperature gradient along the equatorial Pacific 1,3,7,8 -indicative of reduced wind-driven upwelling-conflicting with evidence of enhanced biological productivity in the east Pacific 13-15 that typically results from stronger upwelling. Here we reconcile these observations by providing new evidence for a radically different-from-modern circulation regime in the early Pliocene/late Miocene 16 that results in older, more acidic and more nutrient-rich water reaching the equatorial Pacific. These results provide a mechanism for enhanced productivity in the early Pliocene/late Miocene east Pacific even in the presence of weaker wind-driven upwelling. Our findings shed new light on equatorial Pacific dynamics and help to constrain the potential changes they will undergo in the near future, given that the Earth is expected to reach Pliocene-like levels of warming in the next century., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Marine phytoplankton and zooplankton form the basis of the ocean's food-web, yet the impacts of climate change on their biodiversity are poorly understood. Here, we use an ensemble of species distribution models for a total of 336 phytoplankton and 524 zooplankton species to determine their present and future habitat suitability patterns. For the end of this century, under a high emission scenario, we find an overall increase in plankton species richness driven by ocean warming, and a poleward shift of the species' distributions at a median speed of 35 km/decade. Phytoplankton species richness is projected to increase by more than 16% over most regions except for the Arctic Ocean. In contrast, zooplankton richness is projected to slightly decline in the tropics, but to increase strongly in temperate to subpolar latitudes. In these latitudes, nearly 40% of the phytoplankton and zooplankton assemblages are replaced by poleward shifting species. This implies that climate change threatens the contribution of plankton communities to plankton-mediated ecosystem services such as biological carbon sequestration., (© 2021. The Author(s).)

Planktonic foraminifera are a major constituent of ocean floor sediments, and thus have one of the most complete fossil records of any organism. Expeditions to sample these sediments have produced large amounts of spatiotemporal occurrence records throughout the Cenozoic, but no single source exists to house these data. We have therefore created a comprehensive dataset that integrates numerous sources for spatiotemporal records of planktonic foraminifera. This new dataset, Triton, contains >500,000 records and is four times larger than the previous largest database, Neptune. To ensure comparability among data sources, we have cleaned all records using a unified set of taxonomic concepts and have converted age data to the GTS 2020 timescale. Where ages were not absolute (e.g. based on biostratigraphic or magnetostratigraphic zones), we have used generalised additive models to produce continuous estimates. This dataset is an excellent resource for macroecological and macroevolutionary studies, particularly for investigating how species responded to past climatic changes.

Plankton samples have been routinely collected and preserved in formalin in many laboratories and museums for more than 100 years. Recently, attention has turned to use DNA information from formalin-fixed samples to examine changes in plankton diversity over time. However, no molecular ecological studies have evaluated the impact of formalin fixation on the genetic composition of the plankton community structure. Here, we developed a method for extracting DNA from archived formalin-preserved plankton samples to determine their community structure by a DNA metabarcoding approach. We found that a lysis solution consisting of borate-NaOH buffer (pH 11) with SDS and proteinase K effectively cleaved the cross-link formed by formalin fixation. DNA was extracted from samples preserved for decades in formalin, and the diatom community of the extracted DNA was in good agreement with the microscopy analysis. Furthermore, we stored a plankton sample for 1.5 years and demonstrated that 18S rRNA gene community structures did not change significantly from non-formalin-fixed, time-zero samples. These results indicate that our method can be used to describe the original community structure of plankton archived in formalin for years. Our approach will be useful for examining the long-term variation of plankton diversity by metabarcoding analysis of 18S rRNA gene community structure., Competing Interests: The authors have declared that no competing interests exist.

Physicochemical variables limit and control the distribution of microbial communities in all environments. In the oceans, this may significantly influence functional processes such the consumption of dissolved organic material and nutrient sequestration. Yet, the relative contributions of physical factors, such as water mass variability and depth, on functional processes are underexplored. We assessed microbial community structure and functionality in the Prince Edward Islands (PEIs) using 16S rRNA gene amplicon analysis and extracellular enzymatic activity assays, respectively. We found that depth and nutrients substantially drive the structural patterns of bacteria and archaea in this region. Shifts from epipelagic to bathypelagic zones were linked to decreases in the activities of several extracellular enzymes. These extracellular enzymatic activities were positively correlated with several phyla including several Alphaproteobacteria (including members of the SAR 11 clade and order Rhodospirillales) and Cyanobacteria. We show that depth-dependent variables may be essential drivers of community structure and functionality in the PEIs.

Planktonic microorganisms play a key role in the biogeochemical processes of the aquatic system, and they may be affected by many factors. High-throughput sequencing technology was used in this study to investigate and study the bacterioplankton community of water bodies in the upper reaches of the Heihe River Basin in Qinghai Plateau. Results showed that Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria are the predominant phyla in this river section, while the main genera are Thiomonas, Acidibacillus, Acidocella, Rhodanobacter, Acidithiobacter and Gallionella, which are autochthonous in the acid-mine drainage. Additionally, total nitrogen, total phosphorus, permanganate index and pH are significantly correlated with the bacterioplankton abundance and are the main limiting factors for the spatial distribution of the bacterioplankton. PICRUSt inferred that the mainstream microbial assemblages had a higher abundance of KOs belong to metabolism of terpenoids and polyketides, while the tributary had higher abundance of KOs belong to the immune system. The relationship between bacterioplankton community composition and environmental factors in the Heihe River basin was discussed for the first time in this study, which provides a theoretical basis for the healthy, orderly development of the water environment in the Heihe River Basin., (© 2020 Society for Applied Microbiology and John Wiley & Sons Ltd.)

Background: Freshwater ecosystems are inhabited by members of cosmopolitan bacterioplankton lineages despite the disconnected nature of these habitats. The lineages are delineated based on > 97% 16S rRNA gene sequence similarity, but their intra-lineage microdiversity and phylogeography, which are key to understanding the eco-evolutional processes behind their ubiquity, remain unresolved. Here, we applied long-read amplicon sequencing targeting nearly full-length 16S rRNA genes and the adjacent ribosomal internal transcribed spacer sequences to reveal the intra-lineage diversities of pelagic bacterioplankton assemblages in 11 deep freshwater lakes in Japan and Europe., Results: Our single nucleotide-resolved analysis, which was validated using shotgun metagenomic sequencing, uncovered 7-101 amplicon sequence variants for each of the 11 predominant bacterial lineages and demonstrated sympatric, allopatric, and temporal microdiversities that could not be resolved through conventional approaches. Clusters of samples with similar intra-lineage population compositions were identified, which consistently supported genetic isolation between Japan and Europe. At a regional scale (up to hundreds of kilometers), dispersal between lakes was unlikely to be a limiting factor, and environmental factors or genetic drift were potential determinants of population composition. The extent of microdiversification varied among lineages, suggesting that highly diversified lineages (e.g., Iluma-A2 and acI-A1) achieve their ubiquity by containing a consortium of genotypes specific to each habitat, while less diversified lineages (e.g., CL500-11) may be ubiquitous due to a small number of widespread genotypes. The lowest extent of intra-lineage diversification was observed among the dominant hypolimnion-specific lineage (CL500-11), suggesting that their dispersal among lakes is not limited despite the hypolimnion being a more isolated habitat than the epilimnion., Conclusions: Our novel approach complemented the limited resolution of short-read amplicon sequencing and limited sensitivity of the metagenome assembly-based approach, and highlighted the complex ecological processes underlying the ubiquity of freshwater bacterioplankton lineages. To fully exploit the performance of the method, its relatively low read throughput is the major bottleneck to be overcome in the future. Video abstract.

Tectonic lakes are among the most geologically fascinating and environmentally versatile hydrobiological systems found on the earth's surface. We conducted a study on the limnology of Tasek Lake, a tectonic lake located in the Indo-Burma Province of the South Asian region. Physico-chemical parameters of the lake's water along with its plankton were considered for the study. Their relationship was analysed by understanding their seasonal variations and through linear regression models. The water quality index (WQI), plankton diversity indices and canonical correspondence analysis (CCA) were computed. The ichthyofaunal diversity was also studied to get an insight into the lake's fishery potential. A preliminary assessment on the economic feasibility of converting Tasek Lake into a fishery was also completed. Results indicate moderate eutrophication in the lake and the plankton population is observed to be rich and abundant. The WQI value confirms the water to be of "very poor" quality. The CCA was done to analyze the relationships of physico-chemical parameters with months and seasons, and the relation between seasons and plankton assemblages. Results corroborate the results of WQI. Identified fish population suggest ample fishery potential of the lake. The economic assessment reveals that in order to maintain the ecological sustainability of the lake, it should be transformed into a recreational fishery, following a catch-and-release model. The study calls for urgent restoration of the lake so that not only its pristine ecology is survived but also its fishery potential is sustainably harnessed and local livelihood is improved., Competing Interests: The authors have declared that no competing interests exist.

Pteropods are a group of planktonic gastropods that are widely regarded as biological indicators for assessing the impacts of ocean acidification. Their aragonitic shells are highly sensitive to acute changes in ocean chemistry. However, to gain insight into their potential to adapt to current climate change, we need to accurately reconstruct their evolutionary history and assess their responses to past changes in the Earth's carbon cycle. Here, we resolve the phylogeny and timing of pteropod evolution with a phylogenomic dataset (2,654 genes) incorporating new data for 21 pteropod species and revised fossil evidence. In agreement with traditional taxonomy, we recovered molecular support for a division between "sea butterflies" (Thecosomata; mucus-web feeders) and "sea angels" (Gymnosomata; active predators). Molecular dating demonstrated that these two lineages diverged in the early Cretaceous, and that all main pteropod clades, including shelled, partially-shelled, and unshelled groups, diverged in the mid- to late Cretaceous. Hence, these clades originated prior to and subsequently survived major global change events, including the Paleocene-Eocene Thermal Maximum (PETM), the closest analog to modern-day ocean acidification and warming. Our findings indicate that planktonic aragonitic calcifiers have shown resilience to perturbations in the Earth's carbon cycle over evolutionary timescales., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

As an endpoint of community response to contaminants, average periodic density of populations (APDP) has been introduced to model species interactions in a community with 4 planktonic species. An ecological model for the community was developed by means of interspecific relationship including competition and predation to calculate the APDP. As a case study, we reported here the ecotoxicological effects of petroleum hydrocarbons (PHC) collected from Bohai oil field on densities of two algae, Platymonas subcordiformis and Isochrysis galbana, a rotifer, Brachionus plicatilis, and of a cladocera, Penilia avirostris, in single species and a microcosm experiment. Time scales expressing toxic effect increased with increasing levels of toxic effect from molecule to community. Remarkable periodic changes in densities were found during the tests in microcosm experiment, revealing a strong species reaction. The minimum time scale characterizing toxic effect at a community level should be the common cycle of population densities of the microcosm. In addition, the cycles of plankton densities shortened in general with increasing PHC, showing an evident toxic effect on the microcosm. Using APDP as the endpoint, a threshold concentration for the modeled microcosm was calculated to be 0.404 mg-PHC L -1 . The APDP was found to be more sensitive and reliable than the standing crops of populations as the endpoint. This indicated that the APDP, an endpoint at the community level, could be quantitatively related to the endpoints at the population level, and led to the quantitative concentration-toxic effect relationship at the community level., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Inc. All rights reserved.)

We analysed a widely used barcode, the V9 region of the 18S rRNA gene, to study the effect of environmental conditions on the distribution of two related heterotrophic protistan lineages in marine plankton, kinetoplastids and diplonemids. We relied on a major published dataset (Tara Oceans) where samples from the mesopelagic zone were available from just 32 of 123 locations, and both groups are most abundant in this zone. To close sampling gaps and obtain more information from the deeper ocean, we collected 57 new samples targeting especially the mesopelagic zone. We sampled in three geographic regions: the Arctic, two depth transects in the Adriatic Sea, and the anoxic Cariaco Basin. In agreement with previous studies, both protist groups are most abundant and diverse in the mesopelagic zone. In addition to that, we found that their abundance, richness, and community structure also depend on geography, oxygen concentration, salinity, temperature, and other environmental variables reflecting the abundance of algae and nutrients. Both groups studied here demonstrated similar patterns, although some differences were also observed. Kinetoplastids and diplonemids prefer tropical regions and nutrient-rich conditions and avoid high oxygen concentration, high salinity, and high density of algae., (© 2020 Society for Applied Microbiology and John Wiley & Sons Ltd.)

Since the discovery of high abundances of virus-like particles in aquatic environment, emergence of new analytical methods in microscopy and molecular biology has allowed significant advances in the characterization of the femtoplankton, i.e., floating entities filterable on a 0.2 µm pore size filter. The successive evidences in the last decade (2010-2020) of high abundances of biomimetic mineral-organic particles, extracellular vesicles, CPR/DPANN (Candidate phyla radiation/Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota and Nanohaloarchaeota), and very recently of aster-like nanoparticles (ALNs), show that aquatic ecosystems form a huge reservoir of unidentified and overlooked femtoplankton entities. The purpose of this review is to highlight this unsuspected diversity. Herein, we focus on the origin, composition and the ecological potentials of organic femtoplankton entities. Particular emphasis is given to the most recently discovered ALNs. All the entities described are displayed in an evolutionary context along a continuum of complexity, from minerals to cell-like living entities.

Bacterioplankton play a critical role in primary production, carbon cycling, and nutrient cycling in the oligotrophic ocean. To investigate the effect of elevated CO 2 and warming on the composition and function of bacterioplankton communities in oligotrophic waters, we performed two trace-metal clean deck board incubation experiments during the New Zealand GEOTRACES transect of the South Pacific gyre (SPG). High-throughput amplicon sequencing of the 16S rRNA gene revealed that bacterioplankton community composition was distinct between the fringe and ultra-oligotrophic centre of the SPG and changed consistently in response to elevated CO 2 at the ultra-oligotrophic centre but not at the mesotrophic fringe of the SPG. The combined effects of elevated CO 2 and warming resulted in a high degree of heterogeneity between replicate communities. Community-level protein synthesis rates ( 3 H-Leucine incorporation) and bacterioplankton abundance were not affected by elevated CO 2 alone or in combination with warming at the fringe or ultra-oligotrophic centre of the SPG. These data suggest bacterioplankton community responses to elevated CO 2 may be modulated by nutrient regimes in open ocean ecosystems and highlight the need for further investigation in expanding oligotrophic subtropical gyres., (© 2020 Society for Applied Microbiology and John Wiley & Sons Ltd.)