Description: Modern digital scientific workflows - often implying Big Data challenges - require data infrastructures and innovative data science methods across disciplines and technologies. Diverse activities within and outside HGF deal with these challenges, on all levels. The series of Data Science Symposia fosters knowledge exchange and collaboration in the Earth and Environment research community. We invited contributions to the overarching topics of data management, data science and data infrastructures. The series of Data Science Symposia is a joint initiative by the three Helmholtz Centers HZG, AWI and GEOMAR Organization: Hela Mehrtens and Daniela Henkel (GEOMAR)

Description: Humpback whale males are known to sing on their low-latitude breeding grounds, but it is well established that songs are also commonly produced ‘off-season’ on the feeding grounds or during migration. This opens exciting opportunities to investigate migratory aggregations, study humpback whale behavioral plasticity and potentially even assign individual singers to specific breeding grounds. In this study, we analyzed passive acoustic data from 13 recording positions and multiple years (2011–2018) within the Atlantic sector of the Southern Ocean (ASSO). Humpback whale song was detected at nine recording positions in five years. Most songs were recorded in May, austral fall, coinciding with the rapid increase in sea ice concentration at most recording positions. The spatio-temporal pattern in humpback whale singing activity on Southern Ocean feeding grounds is most likely shaped by local prey availability and humpback whale migratory strategies. Furthermore, the comparative analyses of song structures clearly show a differentiation of two song groups, of which one was solely recorded at the western edge of the ASSO and the other song group was recorded throughout the ASSO. This new finding suggests a common feeding ground occupation by multiple humpback whale populations in the ASSO, allowing for cultural and potentially even genetic exchange among populations.

Description: Facing an era of rapid anthropogenically induced changes in the world oceans, ocean sound is now considered an essential ocean variable (EOV) for understanding, documenting and monitoring long-term trends in anthropogenic sound and its effects on marine life, biodiversity and ecosystem health. The International Quiet Ocean Experiment (IQOE) has identified two major research interests in the context of monitoring the distribution of ocean sound in space and time: i) estimating current levels and distribution of anthropogenic sound in the ocean, and ii) assessing trends in anthropogenic sound levels across the global ocean, and recommendations on ambient noise monitoring are also part of the EU Marine Strategy Framework Directive. To facilitate addressing these research foci by international collaborative research efforts, the OPUS (Open Portal to Underwater Soundscapes) data portal, which is currently being developed by the Ocean Acoustics Group of the Alfred Wegener Institute (AWI) in Bremerhaven, Germany, financially supported by the MAREHUB initiative, is envisioned to promote the use of acoustic data collected worldwide. To this end, an Ocean Sound Software for Making Ambient Noise Trends Accessible (MANTA) is being developed to generate standardized ocean sound level data products from passive acoustic recordings according to IQOE Guidelines, and will be distributed to data owners of underwater passive acoustic data worldwide. OPUS will accept MANTA-processed data (i.e., spectral sound pressure levels at millidecade/minute resolution) together with related metadata as they become available and make them accessible under customized licensing policies via a map- and time-based selection tool and shopping basket functionality. Data products including the compiled MANTA data, parameter-naming conventions, instructions for citing the data, and other information necessary to use the data according to FAIR standards will be regularly produced by OPUS.

Description: Aim: Species distribution models (SDMs) are essential tools in ecology and conservation. However, the scarcity of visual sightings of marine mammals in remote polar areas hinders the effective application of SDMs there. Passive acoustic monitoring (PAM) data provide year-round information and overcome foul weather limitations faced by visual surveys. However, the use of PAM data in SDMs has been sparse so far. Here, we use PAM-based SDMs to investigate the spatiotemporal distribution of the critically endangered Antarctic blue whale in the Weddell Sea. Location: The Weddell Sea. Methods: We used presence-only dynamic SDMs employing visual sightings and PAM detections in independent models. We compared the two independent models with a third combined model that integrated both visual and PAM data, aiming at leveraging the advantages of each data type: the extensive spatial extent of visual data and the broader temporal/environmental range of PAM data. Results: Visual and PAM data prove complementary, as indicated by a low spatial overlap between daily predictions and the low predictability of each model at detections of other data types. Combined data models reproduced suitable habitats as given by both independent models. Visual data models indicate areas close to the sea ice edge (SIE) and with low-to-moderate sea ice concentrations (SIC) as suitable, while PAM data models identified suitable habitats at a broader range of distances to SIE and relatively higher SIC. Main Conclusions: The results demonstrate the potential of PAM data to predict year-round marine mammal habitat suitability at large spatial scales. We provide reasons for discrepancies between SDMs based on either data type and give methodological recommendations on using PAM data in SDMs. Combining visual and PAM data in future SDMs is promising for studying vocalized animals, particularly when using recent advances in integrated distribution modelling methods.