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BACKGROUND: This paper describes a phytoplankton data series generated through systematic observations in the Belgian Part of the North Sea (BPNS). Phytoplankton samples were collected during multidisciplinary sampling campaigns, visiting nine nearshore stations with monthly frequency and an additional eight offshore stations on a seasonal basis. NEW INFORMATION: The data series contain taxon-specific phytoplankton densities determined by analysis with the Flow Cytometer And Microscope (FlowCAM®) and associated image-based classification. The classification is performed by two separate semi-automated classification systems, followed by manual validation by taxonomic experts. To date, 637,819 biological particles have been collected and identified, yielding a large dataset of validated phytoplankton images. The collection and processing of the 2017-2018 dataset are described, along with its data curation, quality control and data storage. In addition, the classification of images using image classification algorithms, based on convolutional neural networks (CNN) from 2019 onwards, is also described. Data are published in a standardised format together with environmental parameters, accompanied by extensive metadata descriptions and finally labelled with digital identifiers for traceability. The data are published under a CC-BY 4.0 licence, allowing the use of the data under the condition of providing the reference to the source.
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Through regular sampling surveys, the Flanders Marine Institute is generating long term data series for the Belgian coastal water and sand bank systems, a designated site in the Long Term Ecological Research (LTER) network. The data series is built on sampling activities initiated in 2002, but gradually upgraded and extended in the framework of the LifeWatch marine observatory and the Integrated Carbon Observation System (ICOS) participation. Nine nearshore stations are sampled monthly, with additional seasonal sampling of eight offshore stations. This paper presents the generated data series for nutrients, pigments, suspended matter and turbidity. The collection, methodology and processing of the 2002-2018 dataset is described, along with its data curation, integration and quality control. Yearly versions of the data are published online in a standardized format, accompanied with extensive metadata description and labelled with digital identifiers for traceability. Data is published under a CC-BY license, allowing use of the data under the condition of providing reference to the original source.
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In this data paper, Bird tracking - GPS tracking of Lesser Black-backed Gulls and Herring Gulls breeding at the southern North Sea coast is described, a species occurrence dataset published by the Research Institute for Nature and Forest (INBO). The dataset (version 5.5) contains close to 2.5 million occurrences, recorded by 101 GPS trackers mounted on 75 Lesser Black-backed Gulls and 26 Herring Gulls breeding at the Belgian and Dutch coast. The trackers were developed by the University of Amsterdam Bird Tracking System (UvA-BiTS, http://www.uva-bits.nl). These automatically record and transmit bird movements, which allows us and others to study their habitat use and migration behaviour in great detail. Our bird tracking network is operational since 2013. It is funded for LifeWatch by the Hercules Foundation and maintained in collaboration with UvA-BiTS and the Flanders Marine Institute (VLIZ). The recorded data are periodically released in bulk as open data (http://dataset.inbo.be/bird-tracking-gull-occurrences), and are also accessible through CartoDB and the Global Biodiversity Information Facility (GBIF).
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Contextual data collected concurrently with molecular samples are critical to the use of metagenomics in the fields of marine biodiversity, bioinformatics and biotechnology. We present here Marine Microbial Biodiversity, Bioinformatics and Biotechnology (M2B3) standards for "Reporting" and "Serving" data. The M2B3 Reporting Standard (1) describes minimal mandatory and recommended contextual information for a marine microbial sample obtained in the epipelagic zone, (2) includes meaningful information for researchers in the oceanographic, biodiversity and molecular disciplines, and (3) can easily be adopted by any marine laboratory with minimum sampling resources. The M2B3 Service Standard defines a software interface through which these data can be discovered and explored in data repositories. The M2B3 Standards were developed by the European project Micro B3, funded under 7(th) Framework Programme "Ocean of Tomorrow", and were first used with the Ocean Sampling Day initiative. We believe that these standards have value in broader marine science.
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We developed generalised additive mixed models (GAMMs) to infer spatiotemporal trends of environmental PCB concentrations from an extensive dataset (n=1219) of PCB concentrations measured between 1991 and 2010 in sediments of the Belgian Coastal Zone (BCZ) and the Western Scheldt estuary. A GAMM with time, geographical zone, periodicity and the organic carbon - water partition coefficient as covariates explained 49% of the variability in the log transformed PCB sediment concentrations. The time trends unraveled two to threefold PCB concentration decreases in the BCZ during the last 20 years. However, in the Western Scheldt estuary, time trends were spatially heterogeneous and not significantly decreasing. These results demonstrate that international efforts to cut down emissions of PCBs have been effective to reduce concentrations in open water ecosystems like the BCZ but had little effect in the urbanised and industrialised area of the Scheldt estuary.