• Energy Research

Zooplankton plays a major role in ocean food webs and biogeochemical cycles, and provides major ecosystem services as a main driver of the biological carbon pump and in sustaining fish communities. Zooplankton is also sensitive to its environment and reacts to its changes. To better understand the importance of zooplankton, and to inform prognostic models that try to represent them, spatially-resolved biomass estimates of key plankton taxa are desirable. In this study we predict, for the first time, the global biomass distribution of 19 zooplankton taxa (1-50 mm Equivalent Spherical Diameter) using observations with the Underwater Vision Profiler 5, a quantitative in situ imaging instrument. After classification of 466,872 organisms from more than 3,549 profiles (0-500 m) obtained between 2008 and 2019 throughout the globe, we estimated their individual biovolumes and converted them to biomass using taxa-specific conversion factors. We then associated these biomass estimates with climatologies of environmental variables (temperature, salinity, oxygen, etc.), to build habitat models using boosted regression trees. The results reveal maximal zooplankton biomass values around 60°N and 55°S as well as minimal values around the oceanic gyres. An increased zooplankton biomass is also predicted for the equator. Global integrated biomass (0-500 m) was estimated at 0.403 PgC. It was largely dominated by Copepoda (35.7%, mostly in polar regions), followed by Eumalacostraca (26.6%) Rhizaria (16.4%, mostly in the intertropical convergence zone). The machine learning approach used here is sensitive to the size of the training set and generates reliable predictions for abundant groups such as Copepoda (R2 ≈ 20-66%) but not for rare ones (Ctenophora, Cnidaria, R2 < 5%). Still, this study offers a first protocol to estimate global, spatially resolved zooplankton biomass and community composition from in situ imaging observations of individual organisms. The underlying dataset covers a period of 10 years while approaches that rely on net samples utilized datasets gathered since the 1960s. Increased use of digital imaging approaches should enable us to obtain zooplankton biomass distribution estimates at basin to global scales in shorter time frames in the future.

Frontiers in Marine Science, 4 ISSN:2296-7745

Data and scripts used for the paper 'Global census of the significance of giant mesopelagic protists to the carbon and silicon cycles' authored by: Manon Laget, Laetitia Drago, Thelma Panaïotis, Rainer Kiko, Lars Stemmann, Andreas Rogge, Natalia Llopis-Monferrer, Aude Leynaert, Jean-Olivier Irisson, Tristan Biard

The Mediterranean Sea is a region threatened by fast environmental changes and high coastal human impacts. Over the last decade, recurrent blooms of the harmful dinoflagellate Ostreopsis cf. ovata have been recorded in many Mediterranean beaches. Here we investigate whether the spatial-temporal distribution of this microalga and the frequency of its blooms could be altered in future regional climate change scenarios, with a special focus in the Western basin. An ecological niche model forced by physical and biogeochemical high-resolution climate change simulations under the strong greenhouse gas emission trajectory (RCP8.5) was used to characterize how O. cf. ovata may respond to projected conditions and how its distribution could shift in this plausible future. Before being applied to the niche model, the future climate change simulations are further refined by using a statistical adaptation method (Cumulative Distribution Function transform) to improve the representativity of the environmental parameters. Our results depict that O. cf. ovata abundances are driven by temperature (optimum 23-26 °C), high salinity (> 38 psu) and high inorganic nutrient concentrations (nitrate > 0.25 mmol N·m-3 and phosphate > 0.035 mmol P·m-3). Future projections suggest no changes in bloom intensity for mid- and end-century. Nevertheless high spatial disparities in future abundances are observed.. Namely, O. cf. ovata abundances could increase in the Mediterranean coasts of France, Spain and the Adriatic Sea while a decrease is expected in the Tyrrhenian Sea. The bloom period could also be enlarged, starting earlier and extending later in the year, which could have important consequences on marine ecosystems, human health and economy. From a methodological point of view, this study highlights good practices of ecological niche models in the context of climate change to identify sensitive areas for current and future harmful algal blooms.

The Paris Agreement target of limiting global surface warming to 1.5-2°C compared to pre-industrial levels by 2100 will still heavily impact the ocean. While ambitious mitigation and adaptation are both needed, the ocean provides major opportunities for action to reduce climate change globally and its impacts on vital ecosystems and ecosystem services. A comprehensive and systematic assessment of 13 global- and local-scale, ocean-based measures was performed to help steer the development and implementation of technologies and actions toward a sustainable outcome. We show that (1) all measures have tradeoffs and multiple criteria must be used for a comprehensive assessment of their potential, (2) greatest benefit is derived by combining global and local solutions, some of which could be implemented or scaled-up immediately, (3) some measures are too uncertain to be recommended yet, (4) political consistency must be achieved through effective cross-scale governance mechanisms, (5) scientific effort must focus on effectiveness, co-benefits, disbenefits, and costs of poorly tested as well as new and emerging measures.