Publications by authors named "Jean-Olivier Irisson"

Carbon fixation is a key metabolic function shaping marine life, but the underlying taxonomic and functional diversity involved is only partially understood. Using metagenomic resources targeted at marine piconanoplankton, we provide a reproducible machine learning framework to derive the potential biogeography of genomic functions through the multi-output regression of gene read counts on environmental climatologies. Leveraging the Marine Atlas of Tara Oceans Unigenes, we investigate the genomic potential of primary production in the global ocean.

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Thriving in both epipelagic and mesopelagic layers, Rhizaria are biomineralizing protists, mixotrophs or flux-feeders, often reaching gigantic sizes. In situ imaging showed their contribution to oceanic carbon stock, but left their contribution to element cycling unquantified. Here, we compile a global dataset of 167,551 Underwater Vision Profiler 5 Rhizaria images, and apply machine learning models to predict their organic carbon and biogenic silica biomasses in the uppermost 1000 m.

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Biodiversity is studied notably because of its reciprocal relationship with ecosystem functions such as production. Diversity is traditionally described from a taxonomic, genetic or functional point of view but the diversity in organism morphology is seldom explicitly considered, except for body size. We describe morphological diversity of marine zooplankton seasonally and over 12 years using quantitative imaging of weekly plankton samples, in the northwestern Mediterranean Sea.

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Article Synopsis
  • Plankton imaging systems with automated classification have enhanced the study of aquatic ecosystems by enabling detailed tracking of plankton populations.
  • These systems capture high-resolution imaging data, offering insights not only into species abundance but also into functional traits of individual plankton.
  • The text suggests using machine learning and computer vision techniques to analyze this imaging data, proposing that these methods could be applied to other organisms in both aquatic and terrestrial environments.
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Autonomous and cabled platforms are revolutionizing our understanding of ocean systems by providing 4D monitoring of the water column, thus going beyond the reach of ship-based surveys and increasing the depth of remotely sensed observations. However, very few commercially available sensors for such platforms are capable of monitoring large particulate matter (100-2000 m) and plankton despite their important roles in the biological carbon pump and as trophic links from phytoplankton to fish. Here, we provide details of a new, commercially available scientific camera-based particle counter, specifically designed to be deployed on autonomous and cabled platforms: the Underwater Vision Profiler 6 (UVP6).

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Quantitative imaging instruments produce a large number of images of plankton and marine snow, acquired in a controlled manner, from which the visual characteristics of individual objects and their in situ concentrations can be computed. To exploit this wealth of information, machine learning is necessary to automate tasks such as taxonomic classification. Through a review of the literature, we highlight the progress of those machine classifiers and what they can and still cannot be trusted for.

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Ocean plankton comprise organisms from viruses to fish larvae that are fundamental to ecosystem functioning and the provision of marine services such as fisheries and CO sequestration. The latter services are partly governed by variations in plankton community composition and the expression of traits such as body size at community-level. While community assembly has been thoroughly studied for the smaller end of the plankton size spectrum, the larger end comprises ectotherms that are often studied at the species, or group-level, rather than as communities.

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The organic carbon produced in the ocean's surface by phytoplankton is either passed through the food web or exported to the ocean interior as marine snow. The rate and efficiency of such vertical export strongly depend on the size, structure and shape of individual particles, but apart from size, other morphological properties are still not quantitatively monitored. With the growing number of in situ imaging technologies, there is now a great possibility to analyze the morphology of individual marine snow.

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Theory and some empirical evidence suggest that groups of animals orient better than isolated individuals. We present the first test of this hypothesis for pelagic marine larvae, at the stage of settlement, when orientation is critical to find a habitat. We compare the in situ behaviour of individuals and groups of 10-12 Chromis atripectoralis (reef fish of the family Pomacentridae), off Lizard Island, Great Barrier Reef.

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Mortality is very high during the pelagic larval phase of fishes but the factors that determine recruitment success remain unclear and hard to predict. Because of their bipartite life history, larvae of coastal species have to head back to the shore at the end of their pelagic episode, to settle. These settlement-stage larvae are known to display strong sensory and motile abilities, but most work has been focused on tropical, insular environments and on the influence of coast-related cues on orientation.

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Our understanding of the internal dynamics of the Earth is largely based on images of seismic velocity variations in the mantle obtained with global tomography. However, our ability to image the mantle is severely hampered by a lack of seismic data collected in marine areas. Here we report observations made under different noise conditions (in the Mediterranean Sea, the Indian and Pacific Oceans) by a submarine floating seismograph, and show that such floats are able to fill the oceanic data gap.

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The behavior of reef fish larvae, equipped with a complex toolbox of sensory apparatus, has become a central issue in understanding their transport in the ocean. In this study pelagic reef fish larvae were monitored using an unmanned open-ocean tracking device, the drifting in-situ chamber (DISC), deployed sequentially in oceanic waters and in reef-born odor plumes propagating offshore with the ebb flow. A total of 83 larvae of two taxonomic groups of the families Pomacentridae and Apogonidae were observed in the two water masses around One Tree Island, southern Great Barrier Reef.

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Experiments were performed at lab scale in order to test the possibility to grow microalgae with CO2 from gaseous effluent of cement industry. Four microalgal species (Dunaliella tertiolecta, Chlorella vulgaris, Thalassiosira weissflogii, and Isochrysis galbana), representing four different phyla were grown with CO2 enriched air or with a mixture of gasses mimicking the composition of a typical cement flue gas (CFG). In a second stage, the culture submitted to the CFG received an increasing concentration of dust characteristic of cement industry.

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A reference collection of COI barcode (650 bp) for the Pacific Society Islands has been constituted for 22 species of Acanthuridae and 16 species of Holocentridae. Divergence between congeneric species was on average 20-fold to 87-fold higher than divergence between conspecific sequences and this set of DNA-identifiers was used to identify 40 larvae of both families. All larvae sequenced could be identified to species using DNA-barcodes.

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Like many marine organisms, most coral reef fishes have a dispersive larval phase. The fate of this phase is of great concern for their ecology as it may determine population demography and connectivity. As direct study of the larval phase is difficult, we tackle the question of dispersion from an opposite point of view and study self-recruitment.

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