国立極地研究所

Abstract Macroscale ocean fronts aggregate significant biomass and provide critical foraging habitat for large marine predators. These frontal systems shift in response to ocean climate variation, including basin‐scale oscillations, and the degree to which marine predators track these movements affects their foraging and reproductive success. Using two decades of adult female northern elephant seal (Mirounga angustirostris) movement data, we assessed their use of the Subarctic Frontal Zone (SAFZ) in the northeast Pacific Ocean, the SAFZ's influence on their diving behavior, and its importance to their foraging success. We found that elephant seals followed the interannual movement of the SAFZ and their diel diving behavior became more extreme as they moved closer to the SAFZ, likely reflecting a different vertical distribution of prey in the region. During their short foraging trip, elephant seals that spent time north of the SAFZ, where day and night diving depths were more similar, had greater foraging success. During the long, gestational foraging trip, their geographic distribution relative to the SAFZ did not influence foraging success, but larger animals were more successful, likely due to more efficient diving. Understanding the relationship between dynamic foraging habitat and the response capacity of predator species is critical for assessing the resilience of species and ecosystems as ocean climates become less predictable.

An aerobic, Gram-stain-negative bacterium, designated strain NIPR152T, was isolated from a glacier moss ball (glacier mice; Schistidium agassizii) collected from Ellesmere Island in the Canadian High Arctic. Cells were non-motile, rod-shaped, and formed orange-pigmented colonies. The strain grew at 4–30 °C (optimum, 18 °C), at pH 5.5–8.0 (optimum, pH 7.0–7.5), and tolerated up to 1.0

The ionospheric electric field is a key parameter for understanding ionospheric electrodynamics and the magnetosphere-ionosphere coupling. Several methods have been developed to reconstruct the two-dimensional distribution of the ionospheric electric field from line-of-sight (LOS) ion velocities observed by incoherent scatter radars. Approaches tailored to the upcoming tri-static incoherent scatter radar system, EISCAT_3D (E3D), have also been proposed. In this study, we propose a new method to reconstruct mesoscale flows using a Bayesian estimation. We applied maximum a posteriori estimation to reconstruct shear flow fields with maximum velocities of 1,000 m/s at 200 km altitude. The electric field was then estimated under the assumption of drift. The reconstructed shear flows showed root-mean-square errors (RMSEs) of 57-101 m/s in the ion velocity and 3-5 mV/m in the electric field. Typical mesoscale flow structures were reconstructed with errors of less than 100 m/s within about 150-200 km centered on the magnetic zenith. These results demonstrate the feasibility of resolving mesoscale ionospheric structures. Our method will be extended to reconstruct electric current structures in future studies.

Oxidation of ferrous Fe in Fe-bearing minerals during serpentinization has a key role in the production of H2, which is an energy source for microbial communities within the oceanic lithosphere. Serpentinization of the oceanic lithosphere occurs at various stages and temperatures, and in a range of rock types. However, the temporal and spatial variations in H2 generation during alteration of the oceanic lithosphere are poorly constrained. In this study, we investigated Fe partitioning and H2 generation in the oceanic lithosphere using samples of drillcore recovered from the lower crust and upper mantle sections at the Oman Drilling Project CM site, based on bulk-rock chemistry, thermogravimetric analyses, magnetic analyses, and bulk-rock and twodimensional imaging using Fe K-edge X-ray absorption near edge structure spectroscopy. Depth profiles of loss-on-ignition values indicate there was broadly consistent extent of serpentinization of the crust-mantle transition zone (serpentinized dunite) and mantle section (serpentinized harzburgite). The bulk-rock molar Fe3+/Sigma Fe ratios show no systematic variations with depth, but vary with rock type. The twodimensional X-ray absorption near edge structure imaging revealed variations in the Fe oxidation state in relation to rock type and mineral texture. The mesh texture serpentine has a similar Fe3+/Sigma Fe ratio regardless of rock type. Serpentine near magnetite veins that cut the mesh texture in dunite and harzburgite has higher Fe3+/ Sigma Fe ratios than mesh texture serpentine. The Fe oxidation state varies with texture, indicating that the redox conditions during serpentinization changed spatially or temporally. The H2 was generated mainly in the early-stage serpentinization characterized by mesh texture. The amounts of H2 generated during the mesh-texture serpentinization in the olivine gabbro (24-307 mmol/kgrock) and wehrlite (81-366 mmol/kgrock) are comparable to that in the dunite (143-393 mmol/kgrock) and harzburgite (71-151 mmol/kgrock). In addition to the H2 generated during mesh-texture serpentinization, up to 280 mmol/kgrock of H2 may have been generated during the later-stage formation of magnetite veins in dunite and harzburgite. Brucite in the serpentinized dunite and harzburgite contains a considerable amount of ferrous Fe. If the reaction of Fe-rich brucite to magnetite could have occurred in response to the increase in the water/rock ratio (W/R) that accompanied fracturing, it could have generated a considerable amount of H2. In contrast, during the later stages of serpentinization of the olivine gabbro and plagioclase-bearing wehrlite, the supply of silica from plagioclase suppressed the formation of magnetite and H2 generation. The depth variations of the amount and oxidation state of Fe in the lower crust and upper mantle sections of the Oman Ophiolite highlight the spatial and temporal heterogeneity in H2 production during the alteration of the oceanic lithosphere.

Conservation of marine ecosystems can be improved through a better understanding of ecosystem functioning, particularly the cryptic underwater behaviours and interactions of marine predators. Image‐based bio‐logging devices (including images, videos and active acoustic) are increasingly used to monitor wildlife movements, foraging behaviours and their environment, but generate complex datasets needing efficient analytical tools. We review advances in image‐based bio‐logging technology for ecological studies on marine fauna. Emphasis is placed on the diversity of data collected, merging research questions, challenges in image processing, and integration of Artificial Intelligence (AI) methods. Image‐based system issues, such as exposure, focus, blurriness, colour balance, moving background, perspective and scale variability are even more challenging in underwater images where conditions change constantly and cannot be controlled. We list computer vision tools and algorithms available for analyses of underwater images, including enhanced tracking algorithms that recognise objects and treat images as a time series. Although AI and computer vision methods offer ample and robust analytical solutions for (semi‐) automated image processing, their uptake by marine ecologists has been slow. Collaboration among ecologists, modellers, statisticians, engineers and computer scientists is needed to integrate ecological questions, data selection and computational methodology. We propose a four‐phase framework for image data processing and analysis (video checking and manipulation, image processing, image labelling and model development) accompanied by detailed python code. We also outline the additional complications in aligning the diverse scalar movement metrics from bio‐loggers along with image‐based data, such as acceleration, depth and location, which typically are collected at different resolutions. Building analytical frameworks for on‐board image data collection (e.g. lightweight models) is also explored. We advocate for a collaborative research community at the Ecology‐AI interface, emphasising sharing and exchange of both data and tools to drive cross‐disciplinary innovation. Beyond the Ecology‐AI interface, we pave the path for the application of insights from image‐based bio‐logging technology enabling collaboration among scientists, conservation managers, and policymakers. Systematic applications of computer vision tools to image‐based bio‐logging technology will enhance the power these data hold, informing about the status of marine ecosystems, testing and developing ecological theory and aiding conservation.