Abstract: Marine animals equipped with biological and physical electronic sensors have produced long-term data streams on key marine environmental variables, hydrography, animal behavior and ecology. These data are an essential component of the Global Ocean Observing System (GOOS). The Animal Borne Ocean Sensors (AniBOS) network aims to coordinate the long-term collection and delivery of marine data streams, providing a complementary capability to other GOOS networks that monitor Essential Ocean Variables (EOVs), essential climate variables (ECVs) and essential biodiversity variables (EBVs). AniBOS augments observations of temperature and salinity within the upper ocean, in areas that are under-sampled, providing information that is urgently needed for an improved understanding of climate and ocean variability and for forecasting. Additionally, measurements of chlorophyll fluorescence and dissolved oxygen concentrations are emerging. The observations AniBOS provides are used widely across the research, modeling and operational oceanographic communities. High latitude, shallow coastal shelves and tropical seas have historically been sampled poorly with traditional observing platforms for many reasons including sea ice presence, limited satellite coverage and logistical costs. Animal-borne sensors are helping to fill that gap by collecting and transmitting in near real time an average of 500 temperature-salinity-depth profiles per animal annually and, when instruments are recovered (∼30% of instruments deployed annually, n = 103 ± 34), up to 1,000 profiles per month in these regions. Increased observations from under-sampled regions greatly improve the accuracy and confidence in estimates of ocean state and improve studies of climate variability by delivering data that refine climate prediction estimates at regional and global scales. The GOOS Observations Coordination Group (OCG) reviews, advises on and coordinates activities across the global ocean observing networks to strengthen the effective implementation of the system. AniBOS was formally recognized in 2020 as a GOOS network. This improves our ability to observe the ocean’s structure and animals that live in them more comprehensively, concomitantly improving our understanding of global ocean and climate processes for societal benefit consistent with the UN Sustainability Goals 13 and 14: Climate and Life below Water. Working within the GOOS OCG framework ensures that AniBOS is an essential component of an integrated Global Ocean Observing System.

Abstract: Climate And Water Cycle Reconstruction Over The Last Centuries And Prediction Should Be Improved In The Southern Hemisphere (E.g. Last Ipcc Report). First, Direct Observations Are Scarce (E.g. In Antarctica, Mainly Basic Automatic Weather Station – Aws – Only Since The 50’s And Satellite Observations). As A Consequence, Climate And Water Cycle Reconstructions Are Largely Dependent On Proxy Measurements Such As Water Isotopes In Polar Ice Cores, Even Over The Last Century. Second, Climate And Water Cycle Reconstructions Using Models Should Be Improved. In Particular, Problems Have Been Identified For (1) Estimation Of Precipitation Amounts (Large Discrepancies Among Models Over The Austral Ocean And The Ice-sheet), (2) Description Of Particular Atmospheric Processes Associated With Cloud Microphysics And Exchanges Between Surface And Atmosphere In Polar Regions And (3) Seasonal To Interannual Evolution Of The Locations Of The Westerlies And Subtropical Jet And Associated Air Mass Trajectories. The Last Aspect Has Important Direct Consequences For The Atmospheric Dynamics In This Region But Also Indirect Consequences Such As The Links Between Westerlies, Co2 Outgassing And Sea Ice Extent In The Austral Ocean (Saunders Et Al. 2018; Menviel Et Al. 2018; Holland And Kwok, 2012). With The Objectives To Provide (1) A Better Description Of Water Cycle Dynamic In The Southern Ocean At Annual And Interannual Scales And (2) An Improved Transfer Function Between Climate / Water Cycle And Water Isotopes In This Region, A Bunch Of Instruments Measuring Continuously The Isotopic Composition Of Water In The Water Vapor And In The Precipitation Has Been Installed Over The Last Years Along A Transect From La Réunion To Antarctica.first Results From The Antarctic Instruments Reveal Clear Isotopic Signatures Of Large Scale Water Cycle Features Such As Atmospheric Rivers Dominating The Surface Mass Balance In Antarctica. In La Réunion, An Extensive Study Of The Drivers Of The Isotopic Composition Of The Water Vapor Showed That The Influence Of The Subtropical Westerly Jet Dominates The Water Isotopic Signal At Night. To Connect The Two Regions, An Instrument Is Running On Amsterdam Island Since November 2019 With First Results Showing A Clear Isotopic Signature During The High Pressure And Low Pressure Synoptic Events. Still, No In-depth Study Of The Data Trying To Connect The Isotopic Record In Amsterdam Island To Larger Scale Patterns Of The Water Cycle Has Been Initiated.the Goal Of This Internship Is To Provide The First Analyses Of The Isotopic (Water Vapor And Precipitation) Records On Amsterdam Island With A Comparison With Meteorological Data And Environmental Data Collected In Parallel On The Observatory Of Amsterdam Island (E.g. Gaseous Elemental Mercury). After These First Analyses Of The Data, Comparisons Will Be Performed With Water Isotopic Records In La Réunion Over Selected Events (Subtropical Jet Or Cold Fronts Intrusions). This Study Will Involve Analyses Of Meteorological Maps As Well As Backtrajectories.this Internship Requires Skills For (Python Or R Languages) And Involves Large Interactions Within A Large Research Team.

Abstract: The genus Thelopsis was classified in the family Stictidaceae but its systematic position has never been investigated by molecular methods. In order to determine its family placement and to test its monophyly, fungal DNA of recent collections of Thelopsis specimens was sequenced. Phylogenetic analyses using nuLSU, RPB2 and mtSSU sequences reveal that members of Thelopsis form a monophyletic group within the genus Gyalecta as currently accepted. The placement of Thelopsis, including the generic type T. rubella, within the genus Gyalecta challenges the generic circumscription of this group because Thelopsis is well recognized by the combination of morphological characters: perithecioid ascomata, well-developed periphysoids, polysporous asci and small, few-septate ellipsoid-oblong ascospores. The sterile sorediate Opegrapha corticola is also placed in the Gyalectaceae as sister species to Thelopsis byssoidea + T. rubella. Ascomata of O. corticola are illustrated for the first time and support its placement in the genus Thelopsis. The hypothesis that O. corticola might represent the sorediate fertile morph of T. rubella is not confirmed because the species is phylogenetically and morphologically distinct. Thelopsis is recovered as polyphyletic, with T. melathelia being placed as sister species to Ramonia. The new combinations Thelopsis corticola (Coppins & P. James) Sanderson & Ertz comb. nov. and Ramonia melathelia (Nyl.) Ertz comb. nov. are introduced and a new species of Gyalecta, G. amsterdamensis Ertz, is described from Amsterdam and Saint-Paul Islands, characterized by a sterile thallus with discrete soralia. Petractis luetkemuelleri and P. nodispora are accommodated in the new genus Neopetractis, differing from the generic type (P. clausa) by having a different phylogenetic position and a different photobiont. Francisrosea bicolor Ertz & Sanderson gen. & sp. nov. is described for a sterile sorediate lichen somewhat similar to Opegrapha corticola but having an isolated phylogenetic position as sister to a clade including Gyalidea praetermissa and the genera Neopetractis and Ramonia. Gyalecta farlowii, G. nidarosiensis and G. carneola are placed in a molecular phylogeny for the first time. The taxonomic significance of morphological characters in Gyalectaceae is discussed.

Abstract: The systematics of Subantarctic and Antarctic near-shore marine benthic invertebrates requires major revision and highlights the necessity to incorporate additional sources of information in the specimen identification chart in the Southern Ocean (SO). In this study, we aim to improve our understanding of the biodiversity of Kidderia (Dall 1876) through molecular and morphological comparisons of Antarctic and Subantarctic taxa. The microbivalves of the genus Kidderia are small brooding organisms that inhabit intertidal and shallow subtidal rocky ecosystems. This genus represents an interesting model to test the vicariance and dispersal hypothesis in the biogeography of the SO. However, the description of Kidderia species relies on a few morphological characters and biogeographic records that raise questions about the true diversity in the group. Here we will define the specimens collected with genetic tools, delimiting their respective boundaries across provinces of the SO, validating the presence of two species of Kidderia. Through the revision of taxonomic issues and species delimitation, it was possible to report that the Antarctic species is Kidderia subquadrata and the species recorded in the Subantarctic islands Diego Ramirez, South Georgia and the Kerguelen Archipelago is Kidderia minuta. The divergence time estimation suggests the origin and diversification of Kidderia lineages are related to historical vicariant processes probably associated with the separation of the continental landmasses close to the late Eocene.

Abstract: The accurate prediction of tides is vital for the operation of many industries, early warning of coastal flooding and scientific understanding of ocean processes. In this paper, we describe the creation method of a global dataset of tidal harmonics using NEMO (Nucleus for European Modelling of the Ocean) for the first time and an offline objective analysis scheme. Data are assimilated as part of a post-processing step, reducing the computational resources required. A reduced ensemble of tidal harmonics is generated, where each member is run for a shorter period of time than a central background state. This ensemble is used to estimate a single background covariance state, which is used for analysis. Output is validated using an ensemble of objective analyses. For each ensemble member, random selections of observations are omitted and validation is performed at these locations. Improvements in both Mean Absolute Error (MAE) and correlation coefficients (R2) are seen across all 6 of the largest diurnal and semi-diurnal constituents. MAEs in amplitude and phase are reduced by up to 78% and 89%, respectively, and correlations by as much as 0.14. In addition, the majority of locations (between 70 and 80%) see significant improvement.