Abstract. Marine particulate organic carbon stable isotope ratios (δ13CPOC) provide insights into understanding carbon cycling through the atmosphere, ocean and biosphere. They have for example been used to trace the input of anthropogenic carbon in the marine ecosystem due to the distinct isotopically light signature of anthropogenic emissions. However, δ13CPOC is also significantly altered during photosynthesis by phytoplankton, which complicates its interpretation. For such purposes, robust spatio-temporal coverage of δ13CPOC observations is essential. We collected all such available data sets and merged and homogenized them to provide the largest available marine δ13CPOC data set (https://doi.org/10.1594/PANGAEA.929931; Verwega et al., 2021). The data set consists of 4732 data points covering all major ocean basins beginning in the 1960s. We describe the compiled raw data, compare different observational methods, and provide key insights in the temporal and spatial distribution that is consistent with previously observed large-scale patterns. The main different sample collection methods (bottle, intake, net, trap) are generally consistent with each other when comparing within regions. An analysis of 1990s median δ13CPOC values in a meridional section across the best-covered Atlantic Ocean shows relatively high values (≥-22 ‰) in the low latitudes (<30∘) trending towards lower values in the Arctic Ocean (∼-24 ‰) and Southern Ocean (≤-28 ‰). The temporal trend since the 1960s shows a decrease in the median δ13CPOC by more than 3 ‰ in all basins except for the Southern Ocean, which shows a weaker trend but contains relatively poor multi-decadal coverage.
Earth System Sciences have been generating increasingly larger amounts of heterogeneous data in recent years. We identify the need to combine Earth System Sciences with Data Sciences, and give our perspective on how this could be accomplished within the sub-field of Marine Sciences. Marine data hold abundant information and insights that Data Science techniques can reveal. There is high demand and potential to combine skills and knowledge from Marine and Data Sciences to best take advantage of the vast amount of marine data. This can be accomplished by establishing Marine Data Science as a new research discipline. Marine Data Science is an interface science that applies Data Science tools to extract information, knowledge, and insights from the exponentially increasing body of marine data. Marine Data Scientists need to be trained Data Scientists with a broad basic understanding of Marine Sciences and expertise in knowledge transfer. Marine Data Science doctoral researchers need targeted training for these specific skills, a crucial component of which is co-supervision from both parental sciences. They also might face challenges of scientific recognition and lack of an established academic career path. In this paper, we, Marine and Data Scientists at different stages of their academic career, present perspectives to define Marine Data Science as a distinct discipline. We draw on experiences of a Doctoral Research School, MarDATA, dedicated to training a cohort of early career Marine Data Scientists. We characterize the methods of Marine Data Science as a toolbox including skills from their two parental sciences. All of these aim to analyze and interpret marine data, which build the foundation of Marine Data Science.
Abstract. Marine particulate organic carbon-13 stable isotope ratios (δ13CPOC) provide insights in understanding carbon cycling through the atmosphere, ocean, and biosphere. They have been used to trace the input of anthropogenic carbon in the marine ecosystem due to the distinct isotopically light signature of anthropogenic emissions. However, δ13CPOC is also significantly altered during photosynthesis by phytoplankton, which complicates its interpretation. For such purposes, robust spatio-temporal coverage of δ13CP OC observations is essential. We collected all such available data sets, merged and homogenized them to provide the largest available marine δ13CPOC data set (Verwega et al., 2021). The data set consists of 4732 data points covering all major ocean basins beginning in the 1960s. We describe the compiled raw data, compare different observational methods, and provide key insights in the temporal and spatial distribution that is consistent with previously observed patterns. The main different sample collection methods (bottle, intake, net, trap) are generally consistent with each other when comparing within regions. An analysis of 1990s mean δ13CP OC values in an meridional section accross the Atlantic Ocean shows relatively high values (≥ −22 ‰) in the low latitudes (< 30°) trending towards lower values in the Arctic Ocean (∼ −24 ‰) and Southern Ocean (≤ −28 ‰). The temporal trend since the 1960s shows a decrease of mean δ13CPOC by more than 3 ‰ in all basins except for the Southern Ocean which shows a weaker trend but contains relatively poor multi-decadal coverage.
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