ALBERT

Description: A slim python library to link maps and sampling data with prediction methods. PyQuickMaps can do interpolation (with scipy.interpolate.griddata), kriging (with pykrige) and random forest regression (with sklearn.ensemble.RandomForestRegressor). It also features plotting nice geographical maps with matplotlib and storing those to geotiff with rasterio. Coordinate transforms are managed internally with osgeo/gdal.

Description: The AL561 cruise was conducted in the framework of the project APOC (“Anthropogenic impacts on Particulate Organic Carbon cycling in the North Sea”). This collaborative project between GEOMAR, AWI, HEREON, UHH, and BUND is to understand how particulate organic carbon (POC) cycling contributes to carbon sequestration in the North Sea and how this ecosystem service is compromised and interlinked with global change and a range of human pressures include fisheries (pelagic fisheries, bottom trawling), resource extraction (sand mining), sediment management (dredging and disposal of dredged sediments) and eutrophication. The main aim of the sampling activity during AL561 cruise was to recover undisturbed sediment from high accumulation sites in the Skagerrak/Kattegat and to subsample sediment/porewater at high resolution in order to investigate sedimentation transport processes, origin of sediment/POC and mineralization processes over the last 100- 200 years. Moreover, the actual processes of sedimentation and POC degradation in the water column and benthic layer will be addressed by sampling with CTD and Lander devices. In total 9 hydroacoustic surveys (59 profiles), 4 Gravity Corer, 7 Multicorer, 3 Lander and 4 CTD stations were successfully conducted during the AL561 cruise.

Description: Post-processing of sonar data is a common task in ocean science. This includes the creation of bathymetric maps, the use of seafloor backscatter information to determine sediment types as well as the analysis of water column data, e.g. for the assessment of fish populations or the quantification of gas releases from the seafloor at methane seeps. Many commercial and free post processing tools for these tasks exist, but since there is a wide range of sonar manufactures with individual data formats not every format is supported by these applications. The DSM Sonar Software is a collection of software libraries and applications to facilitate access to sonar data of various formats and convert between different formats. The conversion of an unsupported format into a commonly supported one makes it possible to process sonar data with existing post processing tools. The target users for our converters are scientists and hydrographers. The different data format descriptions and sonar tool libraries are valuable for software developers in the field of automated sonar data analysis. The modular approach and structure of the DSM Sonar Software enables that developers pick only necessary components to include them in their own software project.

Description: Summary of Ilse Seibold's vita Ilse Seibold, née Usbeck, was born May 8, 1925 in Breslau, Silesia, and went to school in Halle/Saale during WW2. She started her studies of geology and paleontology at the University of Halle and at the Humboldt University in Berlin, and later at the University of Tübingen, where she received her doctorate as micropaleontologist in 1951 with Otto Schindewolf as her supervisor. She remained active as productive scientist over many decades. In 1952, she married Dr. Eugen Seibold, who in 1958 became professor at Kiel University, founded one of Europe's most important institutes for marine geology, and later became president of the German Science Foundation (DFG), and subsequently of the European Science Foundation (ESF). Being a scientist herself Ilse Seibold soon evolved to a deeply reflective insider of geological sciences. She followed her husband during his scientific career from his appointments in Tübingen, Bonn, Karlsruhe, Kiel, to Bonn and Strasbourg/Freiburg i.Br. She accompanied Eugen on his sabbatical leave at Scripps Institution of Oceanography in La Jolla, CA. She participated in countless international scientific meetings. Together with Eugen she published many papers that document her independence and autonomy as scientist. She gained deep insights into the origins of the geosciences and their historical evolution, up to the ideas of fine arts. We are happy that she documented in her publications a broad range of her scientific and distinguished-humane impressions.

Description: A Pyhton-based toolbox to remap daily runoff fields of the JRA55-do reanalysis (Tsujino et al., 2018, https://doi.org/10.1016/j.ocemod.2018.07.002) onto any ocean model grid. Runoff from the original global JRA grid is collected and redistributed to a given model coastline. A particular feature is the optional treatment of river mouths: runoff from grid nodes, which is of exceptionally large magnitude after the basic remapping, can be radially spread to ocean nodes farther offshore. The scripts were tested successfully for NEMO ocean model configurations of various resolution (global grids ORCA025 and ORC05 as well as regional nests VIKING10, ORION10, VIKING20X and INALT20X) at GEOMAR, Kiel (see Biastoch et al., 2021, https://doi.org/10.5194/os-2021-37 for an application). General instructions are provided for how to process the original JRA runoff files and also for the optional river mouth treatment. The technique is illustrated by examples of the fragmented coast of Greenland and the Amazon river mouth. While the code is versatile, examples are given for an application with the NEMO ocean model.

Description: Nowadays underwater vision systems are being widely applied in ocean research. However, the largest portion of the ocean - the deep sea - still remains mostly unexplored. Only relatively few image sets have been taken from the deep sea due to the physical limitations caused by technical challenges and enormous costs. Deep sea images are very different from the images taken in shallow waters and this area did not get much attention from the community. The shortage of deep sea images and the corresponding ground truth data for evaluation and training is becoming a bottleneck for the development of underwater computer vision methods. Thus, this paper presents a physical model-based image simulation solution, which uses an in-air texture and depth information as inputs, to generate underwater image sequences taken by robots in deep ocean scenarios. Different from shallow water conditions, artificial illumination plays a vital role in deep sea image formation as it strongly affects the scene appearance. Our radiometric image formation model considers both attenuation and scattering effects with co-moving spotlights in the dark. By detailed analysis and evaluation of the underwater image formation model, we propose a 3D lookup table structure in combination with a novel rendering strategy to improve simulation performance. This enables us to integrate an interactive deep sea robotic vision simulation in the Unmanned Underwater Vehicles simulator. To inspire further deep sea vision research by the community, we release the source code of our deep sea image converter to the public (https://www.geomar.de/en/omv-research/robotic-imaging-simulator).

Description: Since the sunlight only penetrates a few hundred meters into the ocean, deep-diving robots have to bring their own light sources for imaging the deep sea, e.g., to inspect hydrothermal vent fields. Such co-moving light sources mounted not very far from a camera introduce uneven illumination and dynamic patterns on seafloor structures but also illuminate particles in the water column and create scattered light in the illuminated volume in front of the camera. In this scenario, a key challenge for forward-looking robots inspecting vertical structures in complex terrain is to identify free space (water) for navigation. At the same time, visual SLAM and 3D reconstruction algorithms should only map rigid structures, but not get distracted by apparent patterns in the water, which often resulted in very noisy maps or 3D models with many artefacts. Both challenges, free space detection, and clean mapping could benefit from pre-segmenting the images before maneuvering or 3D reconstruction. We derive a training scheme that exploits depth maps of a reconstructed 3D model of a black smoker field in 1400 m water depth, resulting in a carefully selected, ground-truthed data set of 1000 images. Using this set, we compare the advantages and drawbacks of a classical Markov Random Field-based segmentation solution (graph cut) and a deep learning-based scheme (U-Net) to finding free space in forward-looking cameras in the deep ocean.

Description: Seagrass meadows deliver important ecosystem services such as nutrient cycling, enhanced biodiversity, and contribution to climate change mitigation and adaption through carbon sequestration and coastal protection. Seagrasses, however, are facing the impacts of ocean warming and marine heatwaves, which are altering their ecological structure and function. Shifts in species composition, mass mortality events, and loss of ecosystem complexity after sudden extreme climate events are increasingly common, weakening the ecosystem services they provide. In the west coast of Australia, Shark Bay holds between 0.7 and 2.4% of global seagrass extent (〉4300 km2), but in the austral summer of 2010/2011, the Ningaloo El Niño marine heatwave resulted in the collapse of ~1300 km2 of seagrass ecosystem extent. The loss of the seagrass canopy resulted in the erosion and the likely remineralization of ancient carbon stocks into 2–4 Tg CO2-eq over 6 years following seagrass loss, increasing emissions from land-use change in Australia by 4–8% per annum. Seagrass collapse at Shark Bay also impacted marine food webs, including dugongs, dolphins, cormorants, fish communities, and invertebrates. With increasing recurrence and intensity of marine heatwaves, seagrass resilience is being compromised, underlining the need to implement conservation strategies. Such strategies must precede irreversible climate change-driven tipping points in ecosystem functioning and collapse and result from synchronized efforts involving science, policy, and stakeholders. Management should aim to maintain or enhance the resilience of seagrasses, and using propagation material from heatwave-resistant meadows to restore impacted regions arises as a challenging but promising solution against climate change threats. Although scientific evidence points to severe impacts of extreme climate events on seagrass ecosystems, the occurrence of seagrass assemblages across the planet and the capacity of humans to modify the environment sheds some light on the capability of seagrasses to adapt to changing ecological niches.

Description: Cruise AL534/2 is part of a multi-disciplinary research initiative as part of the JPI Oceans project HOTMIC and sought to investigate the origin, transport and fate of plastic debris from estuaries to the oceanic garbage patches. The main focus of the cruise was on the horizontal transfer of plastic debris from major European rivers into shelf regions and on the processes that mediate this transport. Stations were originally chosen to target the outflows of major European rivers along the western Europe coast between Malaga (Spain) and Kiel (Germany), although some modifications were made in response to inclement weather. In total, 16 stations were sampled along the cruise track. The sampling scheme was similar for most stations, and included: 1) a CTD cast to collect water column salinity and temperature profiles, and discrete samples between surface and seafloor, 2) sediment sampling with Van Veen grab and mini-multi corer (mini-MUC), 3) suspended particle and plankton sampling using a towed Bongo net and vertical WP3 net, and 4) surface neusten sampling using a catamaran trawl. At a subset of stations with deep water, suspended particles were collected using in situ pumps deployed on a cable. During transit between stations, surface water samples were collected from the ship’s underway seawater supply, and during calm weather, floating litter was counted by visual survey teams. The samples and data collected on cruise AL534/2 will be used to determine the: (1) abundance of plastic debris in surface waters, as well as the composition of polymer types, originating in major European estuaries and transported through coastal waters, (2) abundance and composition of microplastics (MP) in the water column at different depths from the sea surface to the seafloor including the sediment, (3) abundance and composition of plastic debris in pelagic and benthic organisms (invertebrates), (4) abundance and identity of biofoulers (bacteria, protozoans and metazoans) on the surface of plastic debris from different water depths, (5) identification of chemical compounds (“additives”) in the plastic debris and in water samples.