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The Arctic mid-ocean ridge system is one of the two main representatives of the particular class of ultraslow spreading ridges with spreading rates of less than 20 mm/y full rate. The formation of new ocean lithosphere at these ridges strongly deviates from any other ocean basin. Typical properties of ultraslow spreading ridges are alternating rift sections with magmatic and amagmatic spreading. At 3°E on Gakkel Ridge, a prominent boundary exists. Here magmatic spreading in the Western Volcanic Zone with basaltic seafloor and numerous axial volcanic ridges is sharply cut off from the amagmatically generated lithosphere of the Sparsely Magmatic Zone, characterized by a deeper rift valley and seafloor made up of mantle rocks. We analysed the teleseismic earthquake record of ultraslow spreading ridges and collected local earthquake data at various ridge locations both at Gakkel Ridge and the Southwest Indian Ridge (SWIR). We found a marked contrast in seismicity across the 3°E boundary. Magmatic spreading in the west is connected with increased seismicity and frequent strong earthquakes often organized in earthquake sequences. Amagmatic spreading, in contrast, produces less and weaker earthquakes. By analogy with an amagmatic spreading segment at the SWIR where we analysed 10 months of local earthquake data, we can show that amagmatic spreading produces a thick lithosphere whose mechanical thickness may reach 30 km. Serpentinisation down to depths of 15 km below seafloor effectively reduces the strength of the lithosphere and results in a lack of seismicity. Magmatic sections show a brittle lithosphere throughout that is dramatically thinned beneath sites of volcanic activity. We postulate that across the 3°E boundary at Gakkel Ridge a major change in lithospheric thickness and composition occurs. This boundary has potentially been very long-lived as it can be traced off-axis in the Eurasian Basin by marine magnetic anomalies. Differences in isotopic compositions of the mantle to either side of the boundary further support this theory. We further present our plans to test this hypothesis with a dedicated field experiment.

Spatial management of commercial resources is becoming an effective measure to be broadly implemented in the European Seas. However, it is currently unconnected from the population dynamics and the temporal assessment. Indeed, it is known that species abundance can be influenced by the environmental features of its own habitat and/or by biotic process that are spatially structured (e.g. reproduction, predation, among others). Usually, this variability is assumed to be implicitly in the abundance trends used as inputs of the stock assessment models and it is not explicitly taken into account. Within this context, in this study we propose a novel methodological approach for an effective implementation of spatial and ecological knowledge that could help to embrace species spatial management in an operational way, providing a more holistic and ecosystem-based approach. As case study we used the European hake (Merluccius merluccius) in the northern continental shelf of the Iberian Peninsula. Hake data in functional groups by size collected during the scientific survey series “DEMERSALES” by the “Instituto Español de Oceanografía” (IEO) from 1993 to 2017 were analyzed using Bayesian hierarchical spatial-temporal models (B-HSTMs), considering as environmental variables Sea Temperature, Sea Salinity, bathymetry and rugosity of the seabed. B-HSTMs link spatially information on hake abundance to environmental variables to estimate and predict where (and how much of) this species is likely to be present in the studied area in a specific year. Indices of abundance obtained as outputs from B-HSTMs, performed with the innovative integrated nested Laplace approximation (INLA) methodology and software, are then used as inputs for the GADGET (Globally applicable Area Disaggregated General Ecosystem Toolbox) stock assessment model. Finally, a comparative analysis of the results obtained with the GADGET model using the B-HSTMs abundance indexes and the ones commonly used in stock assessment evaluations is performed. We argue that the analytical framework proposed in this study allowed to (1) assess which environmental factors influence the different size groups of the hake in the northern continental shelf of the Iberian Peninsula, (2) identify the areas in which the different functional groups are more aggregated and their spatial-temporal fluctuations, and (3) could be a decisive step to improve habitat-based standardization abundance indexes and stocks’ management in European Seas IMBeR Future Oceans 2, 17-21 June 2019, Brest, France Peer reviewed

An array of fluid flow sensors can be used to detect and track underwater objects via the fluid flow field these objects create. The sensed flows combine to a spatio-temporal velocity profile, which can be used to solve the inverse problem; determining the relative position and orientation of a moving source via a trained model. In this study, two training strategies are used: simulated data resulting from continuous motion in a path and from vibratory motion at discrete locations on a grid. Furthermore, we investigate two sensing modalities found in literature: 1D and 2D sensitive flow sensors; all while varying the sensor detection threshold via a noise level. Results show that arrays with 2D sensors outperform those with 1D sensors, especially near and next to the sensor array. On average, the path method outperforms the grid method with respect to estimating the location and orientation of a source.

La bioactivité des toxines du phytoplancton qui s’accumulent dans les coquillages est presque toujours évaluée sur modèle animal (test souris). Malgré ses avantages, la capacité de ce test à expliquer la nature de cette bio-activité reste limitée. Par ailleurs, le contrôle sanitaire actuellement basé sur une méthode ciblée d’identification et de quantification d’un ensemble de toxines connues ne permet pas de détecter des toxines encore inconnues. Afin de répondre à ce besoin de caractérisation de substances toxiques inconnues, une nouvelle approche de profilage chimique différentiel et non ciblé, de type métabolomique, a été proposée. Les 2 extraits sélectionnés sont ceux ayant montré une toxicité positive chez la souris, sans que les substances potentiellement responsables de cet effet toxique n’aient été révélées par des mesures ciblées.

The current development of biodiversity indicators adopted as common in the North East Atlantic (Under OSPAR Regional Sea Convention) is missing some elements necessary for their application as food-web indicators. The Mean Trophic Level (MTL) indicator is based on species biomass and their trophic level (TL). These metrics are commonly used in the food-web holistic approach of interactions in an ecosystem. Species TL, giving the position of an organism in the food web, is influenced by spatiotemporal variability and ontogeny of species. MTL is also shaped by the species biomasses and their data source (i.e. landings or survey data). The aim of the present study was to propose a methodology (1) considering a better regionalisation of the indicator (i.e. using local TL estimations and ecosystem survey data), (2) looking at the MTL sensitivity regarding ecosystem species and compartments and (3) discussing the food web approach of the indicator. Different scenarios were thus tested on MTL indicator with EVHOE survey data (i) using various data sources of TL and (ii) applying several cut-offs to focus on different compartments in the ecosystem. Species influence on each scenario was also investigated. Two species were found to be highly influencing the MTL indicator trend. Capros aper, a low TL species catching the bottom up effect in the food-web, was strongly acting on MTL when considering all species in the ecosystem. Meanwhile, Merluccius merluccius was driving the indicator when low trophic level species were cut-off. This high predator reflected more the top down effect on the ecosystem. This work concluded the need to assess the MTL indicator using three TL cut-offs (TL= 2, 3.25 and 4) to capture a holistic view of changes in the ecosystem. Furthermore, scientific surveys and local estimations of TL are crucial in order to reduce uncertainty around the MTL estimation.