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GEOMAR Library Ocean Research Information Access

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  • 1
    Publication Date: 2021-03-19
    Description: Optical imaging is a common technique in ocean research. Diving robots, towed cameras, drop-cameras and TV-guided sampling gear: all produce image data of the underwater environment. Technological advances like 4K cameras, autonomous robots, high-capacity batteries and LED lighting now allow systematic optical monitoring at large spatial scale and shorter time but with increased data volume and velocity. Volume and velocity are further increased by growing fleets and emerging swarms of autonomous vehicles creating big data sets in parallel. This generates a need for automated data processing to harvest maximum information. Systematic data analysis benefits from calibrated, geo-referenced data with clear metadata description, particularly for machine vision and machine learning. Hence, the expensive data acquisition must be documented, data should be curated as soon as possible, backed up and made publicly available. Here, we present a workflow towards sustainable marine image analysis. We describe guidelines for data acquisition, curation and management and apply it to the use case of a multi-terabyte deep-sea data set acquired by an autonomous underwater vehicle.
    Type: Article , PeerReviewed
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  • 2
    Publication Date: 2021-04-23
    Description: Prochlorococcus and Synechococcus are the dominant primary producers in marine ecosystems and perform a significant fraction of ocean carbon fixation. These cyanobacteria interact with a diverse microbial community that coexists with them. Comparative genomics of cultivated isolates has helped address questions regarding patterns of evolution and diversity among microbes, but the fraction that can be cultivated is miniscule compared to the diversity in the wild. To further probe the diversity of these groups and extend the utility of reference sequence databases, we report a data set of single cell genomes for 489 Prochlorococcus, 50 Synechococcus, 9 extracellular virus particles, and 190 additional microorganisms from a diverse range of bacterial, archaeal, and viral groups. Many of these uncultivated single cell genomes are derived from samples obtained on GEOTRACES cruises and at well-studied oceanographic stations, each with extensive suites of physical, chemical, and biological measurements. The genomic data reported here greatly increases the number of available Prochlorococcus genomes and will facilitate studies on evolutionary biology, microbial ecology, and biological oceanography.
    Type: Article , PeerReviewed
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  • 3
    Publication Date: 2021-02-08
    Description: Mitigating the detrimental effects of climate change is a collective problem that requires global cooperation. However, achieving cooperation is difficult since benefits are obtained in the future. The so-called collective-risk game, devised to capture dangerous climate change, showed that catastrophic economic losses promote cooperation when individuals know the timing of a single climatic event. In reality, the impact and timing of climate change is not certain; moreover, recurrent events are possible. Thus, we devise a game where the risk of a collective loss can recur across multiple rounds. We find that wait and see behavior is successful only if players know when they need to contribute to avoid danger and if contributions can eliminate the risks. In all other cases, act quickly is more successful, especially under uncertainty and the possibility of repeated losses. Furthermore, we incorporate influential factors such as wealth inequality and heterogeneity in risks. Even under inequality individuals should contribute early, as long as contributions have the potential to decrease risk. Most importantly, we find that catastrophic scenarios are not necessary to induce such immediate collective action.
    Type: Article , PeerReviewed
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