ALBERT

Description: Highlights • All known observations for Area of Particular Environmental Interest 6 presented. • Assess morphology, sediments, nodules, oceanography, biogeochemistry and ecology. • APEI-6 partially representative of nearby exploration areas yet clear differences. • Present scientific synthesis and management implications for Clarion Clipperton Zone. To protect the range of habitats, species, and ecosystem functions in the Clarion Clipperton Zone (CCZ), a region of interest for deep-sea polymetallic nodule mining in the Pacific, nine Areas of Particular Environmental Interest (APEIs) have been designated by the International Seabed Authority (ISA). The APEIs are remote, rarely visited and poorly understood. Here we present and synthesise all available observations made at APEI-6, the most north eastern APEI in the network, and assess its representativity of mining contract areas in the eastern CCZ. The two studied regions of APEI-6 have a variable morphology, typical of the CCZ, with hills, plains and occasional seamounts. The seafloor is predominantly covered by fine-grained sediments, and includes small but abundant polymetallic nodules, as well as exposed bedrock. The oceanographic parameters investigated appear broadly similar across the region although some differences in deep-water mass separation were evident between APEI-6 and some contract areas. Sediment biogeochemistry is broadly similar across the area in the parameters investigated, except for oxygen penetration depth, which reached 〉2 m at the study sites within APEI-6, deeper than that found at UK1 and GSR contract areas. The ecology of study sites in APEI-6 differs from that reported from UK1 and TOML-D contract areas, with differences in community composition of microbes, macrofauna, xenophyophores and metazoan megafauna. Some species were shared between areas although connectivity appears limited. We show that, from the available information, APEI-6 is partially representative of the exploration areas to the south yet is distinctly different in several key characteristics. As a result, additional APEIs may be warranted and caution may need to be taken in relying on the APEI network alone for conservation, with other management activities required to help mitigate the impacts of mining in the CCZ.

Description: Underwater images are used to explore and monitor ocean habitats, generating huge datasets with unusual data characteristics that preclude traditional data management strategies. Due to the lack of universally adopted data standards, image data collected from the marine environment are increasing in heterogeneity, preventing objective comparison. The extraction of actionable information thus remains challenging, particularly for researchers not directly involved with the image data collection. Standardized formats and procedures are needed to enable sustainable image analysis and processing tools, as are solutions for image publication in long-term repositories to ascertain reuse of data. The FAIR principles (Findable, Accessible, Interoperable, Reusable) provide a framework for such data management goals. We propose the use of image FAIR Digital Objects (iFDOs) and present an infrastructure environment to create and exploit such FAIR digital objects. We show how these iFDOs can be created, validated, managed and stored, and which data associated with imagery should be curated. The goal is to reduce image management overheads while simultaneously creating visibility for image acquisition and publication efforts.

Description: Underwater images are used to explore and monitor ocean habitats, generating huge datasets with unusual data characteristics that preclude traditional data management strategies. Due to the lack of universally adopted data standards, image data collected from the marine environment are increasing in heterogeneity, preventing objective comparison. The extraction of actionable information thus remains challenging, particularly for researchers not directly involved with the image data collection. Standardized formats and procedures are needed to enable sustainable image analysis and processing tools, as are solutions for image publication in long-term repositories to ascertain reuse of data. The FAIR principles (Findable, Accessible, Interoperable, Reusable) provide a framework for such data management goals. We propose the use of image FAIR Digital Objects (iFDOs) and present an infrastructure environment to create and exploit such FAIR digital objects. We show how these iFDOs can be created, validated, managed and stored, and which data associated with imagery should be curated. The goal is to reduce image management overheads while simultaneously creating visibility for image acquisition and publication efforts.

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉Natural history collections are leading successful large-scale projects of specimen digitization (images, metadata, DNA barcodes), thereby transforming taxonomy into a big data science. Yet, little effort has been directed towards safeguarding and subsequently mobilizing the considerable amount of original data generated during the process of naming 15,000–20,000 species every year. From the perspective of alpha-taxonomists, we provide a review of the properties and diversity of taxonomic data, assess their volume and use, and establish criteria for optimizing data repositories. We surveyed 4113 alpha-taxonomic studies in representative journals for 2002, 2010, and 2018, and found an increasing yet comparatively limited use of molecular data in species diagnosis and description. In 2018, of the 2661 papers published in specialized taxonomic journals, molecular data were widely used in mycology (94%), regularly in vertebrates (53%), but rarely in botany (15%) and entomology (10%). Images play an important role in taxonomic research on all taxa, with photographs used in >80% and drawings in 58% of the surveyed papers. The use of omics (high-throughput) approaches or 3D documentation is still rare. Improved archiving strategies for metabarcoding consensus reads, genome and transcriptome assemblies, and chemical and metabolomic data could help to mobilize the wealth of high-throughput data for alpha-taxonomy. Because long-term—ideally perpetual—data storage is of particular importance for taxonomy, energy footprint reduction via less storage-demanding formats is a priority if their information content suffices for the purpose of taxonomic studies. Whereas taxonomic assignments are quasifacts for most biological disciplines, they remain hypotheses pertaining to evolutionary relatedness of individuals for alpha-taxonomy. For this reason, an improved reuse of taxonomic data, including machine-learning-based species identification and delimitation pipelines, requires a cyberspecimen approach—linking data via unique specimen identifiers, and thereby making them findable, accessible, interoperable, and reusable for taxonomic research. This poses both qualitative challenges to adapt the existing infrastructure of data centers to a specimen-centered concept and quantitative challenges to host and connect an estimated $ \le $2 million images produced per year by alpha-taxonomic studies, plus many millions of images from digitization campaigns. Of the 30,000–40,000 taxonomists globally, many are thought to be nonprofessionals, and capturing the data for online storage and reuse therefore requires low-complexity submission workflows and cost-free repository use. Expert taxonomists are the main stakeholders able to identify and formalize the needs of the discipline; their expertise is needed to implement the envisioned virtual collections of cyberspecimens. [Big data; cyberspecimen; new species; omics; repositories; specimen identifier; taxonomy; taxonomic data.]〈/jats:p〉

Description: 〈jats:title〉Abstract〈/jats:title〉 〈jats:p〉This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusable) data principles in a large distributed bioinformatics infrastructure. We address the challenge of heterogeneity of wet lab technologies, data, metadata, software, computational workflows and the levels of implementation and monitoring of FAIR principles within the different bioinformatics sub-disciplines joint in de.NBI. On the one hand, this broad service landscape and the excellent network of experts are a strong basis for the development of useful research data management plans. On the other hand, the large number of tools and techniques maintained by distributed teams renders FAIR compliance challenging.〈/jats:p〉

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: The information system PANGAEA provides targeted support for research data management as well as long-term data archiving and publication. PANGAEA is operated as an open access library for archiving, publishing, and distributing georeferenced data from earth and environmental sciences. It focuses on observational and experimental data. Citability, comprehensive metadata descriptions, interoperability of data and metadata, a high degree of structural and semantic harmonization of the data inventory as well as the commitment of the hosting institutions ensures the long-term usability of archived data. PANGAEA is a pioneer of FAIR and open data infrastructures to enable data intensive science and an integral component of national and international science and technology activities. This paper provides an overview of the recent organisational, structural, and technological advancements in developing and operating the information system.

Description: Ex situ diffusive oxygen uptake (DOU) at the sediment water interface was assessed on the Northeast Greenland shelf with R/V Polarstern during PS109 between September and October 2017 using a camera-equipped multiple corer (TV-MUC; core area 0.007 m²). Upon arrival on deck, part of the overlying water of three MUC cores was collected and stored separately at in situ temperature. The remaining overlying water was adjusted to 10 cm above the sediment by gently pushing the sediment upwards while avoiding a disturbance of the surface sediment. The cores were then placed in a temperature-controlled water bath in the ship-board laboratory which had been adjusted to the in-situ temperature at the seafloor (information was retrieved from ship-board sensors). A mangetic stirrer was deployed in order to homogenise the overlying water, and a small air pump gently aerated the water. DOU was assessed with 2 oxygen optodes (Pyroscience, Firesting; tip size 50 µm) mounted on an autonomous microprofiler module. Each core was measured with two microprofilers simultaneously, usually within 2h of sampling (except for stations 139, 85, 84 and 76, where the measurement times were 〉24h). The sensors were two-point calibrated using on-board signals recorded in air saturated surface sea water and anoxic, dithionite-spiked bottom water at in situ temperature. Ex situ DOU fluxes across the sediment-water interface obtained were calculated from running average smoothed oxygen profiles using Fick's first law (Glud et al. (1994, doi:10.1016/0967-0637(94)90072-8).

Description: Samples for single cell abundances as an estimate for the abundance of benthic bacteria on the Northeast Greenland shelf have been collected with R/V Polarstern during PS109 between September and October 2017 using a camera-equipped multiple corer (TV-MUC; core area 0.007 m²). Upon arrival on deck, the upper 5 cm of three MUC cores were sliced into 1 cm layers with a 10 ml cut-off syringe. 2 ml of each slice was transferred into a scintillation vial and fixed with 2 % filtered formaldehyde-seawater solution. In the laboratory, the samples were diluted, filtered through polycarbonate filters (0.2 µm, Whatman Nucleopore Track-Etch Membrane) and stained with a 0.001 % acridine orange solution after Hobbie et al., 1977 (doi:10.1128/aem.33.5.1225-1228.1977). Cells were counted on at least 30 grids (125 µm * 125 µm area) for 2 replicate filters per sample each with a Zeiss Axiophot microscope (Germany) and a 100x oil immersion objective lens (Zeiss Plan-Apochromat, Germany).

Description: Sediment porewater chemistry (nutrient, DIC, sulfide and sulfate) on the Northeast Greenland shelf were assessed with R/V Polarstern during PS109 between September and October 2017 using two cores with pre-drilled holes mounted on a multiple corer (MUC) a camera-equipped multiple corer (TV-MUC; core area 0.007 m²). Upon arrival on deck, Rhizon samplers were inserted carefully into the holes with intervals of 1 cm until 10 cm sediment depth, and 2 cm intervals until 20 cm sediment depth to extract the sediment porewater. To get a total of 9 ml/l porewater for each depth interval, the porewater from both cores was pooled for each depth. For the analysis of DIC, 2 ml/l porewater from each depth was transferred to a glass vial which had been pre-treated with HgCl₂ and stored at 4°C. DIC concentrations were measured using a flow injection system equipped with the Spark Optimas auto-sampler (model 820, Ambacht, Netherlands). For the determination of porewater nutrients, 4 ml/l of porewater was sampled with acid-washed Sarstedt Vials and stored at -20°C. In the laboratory, 4 ml/l was subsampled for phosphate, silicate and ammonium, while 1 ml/l was subsampled for nitrate and nitrite, and subsequently analyzed with a Continuous Segmented Flow Analyser (QuAAtro39, SEAL Analytical, Norderstedt, Germany).