MOSAiC und weiter: Digitalisierung und nachhaltige Nutzung von Forschungsdaten in der Polarforschung

Die MOSAiC-Expedition war die größte Polarexpedition, die je durchgeführt wurde. Mehr als ein Jahr driftete das Forschungsschiff Polarstern durch den Arktischen Ozean und erhob dabei unzählige Forschungsdaten. Die Umsetzung stellte große logistische und technische Herausforderungen. Gleichzeitig setzte das Projekt Meilensteine in der Digitalisierung der MOSAiC-Daten. Das vorhandene Datenrepositorim PANGEA wurde als Datenbasis für die Abspeicherung der erhobenen und gewonnenen Daten genutzt. Das Datenmanagement hatte ein frühestmögliches Teilen der Daten zum Ziel. Außerdem stand von Anfang an das Datenmanagement als ein Teil von open science und einer frühen Datenzitierbarkeit. Ab 2023 sollen alle MOSAiC-Daten im Repositorium frei verfügbar sein. MOSAiC ist der bisher größte Anwendungsfall für das Projekt Nationale Forschungsdateninfrastruktur (NFDI).The MOSAiC expedition was the largest polar expedition ever conducted. For more than a year, the research vessel Polarstern drifted through the Arctic Ocean collecting countless research data. The implementation posed major logistical and technical challenges. At the same time, the project set milestones in the digitization of MOSAiC data. The existing data repositoryim PANGEA was used as a database for storing the collected and acquired data. Data management aimed at sharing the data as early as possible. In addition, from the beginning, data management stood as a part of open science and early data citability. Starting in 2023, all MOSAiC data should be freely available in the repository. MOSAiC is the largest use case to date for the National Research Data Infrastructure (NFDI) project

MOSAiC und weiter: Digitalisierung und nachhaltige Nutzung von Forschungsdaten in der Polarforschung

Die MOSAiC-Expedition war die größte Polarexpedition, die je durchgeführt wurde. Mehr als ein Jahr driftete das Forschungsschiff Polarstern durch den Arktischen Ozean und erhob dabei unzählige Forschungsdaten. Die Umsetzung stellte große logistische und technische Herausforderungen. Gleichzeitig setzte das Projekt Meilensteine in der Digitalisierung der MOSAiC-Daten. Das vorhandene Datenrepositorim PANGEA wurde als Datenbasis für die Abspeicherung der erhobenen und gewonnenen Daten genutzt. Das Datenmanagement hatte ein frühestmögliches Teilen der Daten zum Ziel. Außerdem stand von Anfang an das Datenmanagement als ein Teil von open science und einer frühen Datenzitierbarkeit. Ab 2023 sollen alle MOSAiC-Daten im Repositorium frei verfügbar sein. MOSAiC ist der bisher größte Anwendungsfall für das Projekt Nationale Forschungsdateninfrastruktur (NFDI)

Variability in the organic carbon stocks, sources, and accumulation rates of Indonesian mangrove ecosystems

Mangrove ecosystems are an important natural carbon sink that accumulate and store large amounts of organic carbon (Corg), in particular in the sediment. However, the magnitude of carbon stocks and the rate of carbon accumulation (CAR) vary geographically due to a large variation of local factors. In order to better understand the blue carbon sink of mangrove ecosystems, we measured organic carbon stocks, sources and accumulation rates in three Indonesian mangrove ecosystems with different environmental settings and conditions; (i) a degraded estuarine mangrove forest in the Segara Anakan Lagoon (SAL), Central Java, (ii) an undegraded estuarine mangrove forest in Berau region, East Kalimantan, and (iii) a pristine marine mangrove forest on Kongsi Island, Thousand Islands, Jakarta. In general, Corg stocks were higher in estuarine than in marine mangroves, although a large variation was observed among the estuarine mangroves. The mean total Corg stock in Berau (615 ± 181 Mg C ha−1) is twice as high as that in SAL (298 ± 181 Mg C ha−1). However, the Segara Anakan Lagoon displayed large within-system variation with a much higher Corg stock in the eastern (483 ± 124 Mg C ha−1) than in the central lagoon (167 ± 36 Mg C ha−1). The predominant accumulation of autochthonous mangrove organic matter likely contributed to the higher Corg stocks in Berau and the eastern SAL. Interestingly, the CAR distribution pattern in SAL is opposite to that of its Corg stocks. The central SAL that receives high sediment inputs from the hinterland has a much higher CAR than the eastern SAL (658 ± 311 g C m−2 yr−1 and 194 ± 46 g C m−2 yr−1, respectively), while Berau has one of the highest CAR (1722 ± 183 g C m−2 yr−1) ever measured. It appears that these large differences are driven by the environmental setting and conditions, mainly sediment dynamics and hydrodynamics, landform, and vegetation conditions. It is inferred that quantifying carbon accumulation in sediments is a useful tool in estimating the present-day carbon storage of mangrove ecosystems. This is a precondition for taking measures under REDD+ (Reducing Emissions from Deforestation and Forest Degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries) schemes

MOSAiC goes O2A - Arctic Expedition Data Flow from Observations to Archives

During the largest polar expedition in history starting in September 2019, the German research icebreaker Polarstern spends a whole year drifting with the ice through the Arctic Ocean. The MOSAiC expedition takes the closest look ever at the Arctic even throughout the polar winter to gain fundamental insights and most unique on-site data for a better understanding of global climate change. Hundreds of researchers from 20 countries are involved. Scientists will use the in situ gathered data instantaneously in near-real time modus as well as long afterwards all around the globe taking climate research to a completely new level. Hence, proper data management, sampling strategies beforehand, and monitoring actual data flow as well as processing, analysis and sharing of data during and long after the MOSAiC expedition are the most essential tools for scientific gain and progress. To prepare for that challenge we adapted and integrated the research data management framework O2A “Data flow from Observations to Archives” to the needs of the MOSAiC expedition on board Polarstern as well as on land for data storage and access at the Alfred Wegener Institute Computing and Data Center in Bremerhaven, Germany. Our O2A-framework assembles a modular research infrastructure comprising a collection of tools and services. These components allow researchers to register all necessary sensor metadata beforehand linked to automatized data ingestion and to ensure and monitor data flow as well as to process, analyze, and publish data to turn the most valuable and uniquely gained arctic data into scientific outcomes. The framework further allows for the integration of data obtained with discrete sampling devices into the data flow. These requirements have led us to adapt the generic and cost-effective framework O2A to enable, control, and access the flow of sensor observations to archives in a cloud-like infrastructure on board Polarstern and later on to land based repositories for international availability. Major roadblocks of the MOSAiC-O2A data flow framework are (i) the increasing number and complexity of research platforms, devices, and sensors, (ii) the heterogeneous interdisciplinary driven requirements towards, e. g., satellite data, sensor monitoring, in situ sample collection, quality assessment and control, processing, analysis and visualization, and (iii) the demand for near real time analyses on board as well as on land with limited satellite bandwidth. The key modules of O2A's digital research infrastructure established by AWI are implementing the FAIR principles: SENSORWeb, to register sensor applications and sampling devices and capture controlled meta data before and alongside any measurements in the field Data ingest, allowing researchers to feed data into storage systems and processing pipelines in a prepared and documented way, at best in controlled near real-time data streams Dashboards allowing researchers to find and access data and share and collaborate among partners Workspace enabling researchers to access and use data with research software utilizing a cloud-based virtualized infrastructure that allows researchers to analyze massive amounts of data on the spot Archiving and publishing data via repositories and Digital Object Identifiers (DOI

Permafrost Organic Carbon Turnover and Export Into a High-Arctic Fjord: A Case Study From Svalbard Using Compound-specific C-14 Analysis

In a warming climate, thawing permafrost soils in the circumpolar Arctic region are subject to enhanced microbial turnover as well as mass mobilization and other erosion processes. High-Arctic settings such as Svalbard are exceptionally vulnerable to these effects, but the presence of coal deposits obscures the organic carbon (OC) signature of permafrost OC, particularly its carbon isotope composition, when studying OC turnover and export. Here, we analyze the compound-specific delta C-13 and Delta C-14 isotopic composition of alkanoic acids from permafrost soils and river and fjord sediments to assess soil turnover in the catchment of the Bayelva River near Ny-angstrom lesund and trace transport and re-burial of permafrost OC into the adjacent Kongsfjord. Our data confirm the influence of coal-derived OC on delta C-13 and Delta C-14 values of bulk soil and sedimentary OC, while alkanoic acid delta C-13 and Delta C-14 values are less affected by coal contributions. Alkanoic acid Delta C-14 values in the soil profile imply long-term residence in soils prior to deposition in river and fjord sediments, that is, multi-millennial turnover that is significantly slower than reported from other environments. Strongly C-14-depleted vascular plant-derived long-chain alkanoic acids can be found in Bayelva River and Kongsfjord sediments revealing substantial input of deep active layer/permafrost OC, particularly in the Bayelva River and off its river mouth. In the central Kongsfjord, long-chain alkanoic acid Delta C-14 values are higher either reflecting input from other permafrost areas or physical effects resulting, for example, from deposition in settings with different accumulation rates or from sediment sorting