Dataset of ocean vessel traffic in the North Sea.

Automatic Identification System (AIS) is a technology that allows ships to broadcast their position, course, speed, and other information to other vessels or shore-based stations. By collecting and analysing this data, it is possible to create a heatmap of ship activity in a particular region, such as the North Sea. This heatmap acts as a representation of vessel activity per class. A heatmap in a standard geoinformatics format may be preferable to scientific researchers as it would quickly allow users to overlay their own data onto the vessel density layer thus providing spatial context and an ability to compare their dataset to the distribution and intensity of ship activity in a particular region. This dataset represents ocean vessel activity in the North Sea for 2022 and was created using AIS data collected using multiple coastal receivers. The dataset was created from reported vessel positions aggregated both spatially and temporally. The end goal of this data processing is to provide a publicly available spatial layer that can be queried to provide monthly vessel traffic statistics for a region in the North Sea. The data was spatially filtered to only include AIS messages for Latitudes between 49.5 and 53.8 degrees North, and 0.2 and 7 degrees East. The bounding box was chosen as it includes Belgium canals and the Belgium part of the North Sea. The dataset has multiple uses as a collaboration dataset, some example of use-cases that this dataset has been used for include using it asa time-series of statistical priors for vessel classes in order to improve vessel classification algorithms and to visualise vessel behaviour in order to locate potential mooring sites where the risk of potential fishing net snags is low. It has also been used to locate areas of potential anchor scarring in anchorages near ports.

Marked changes in diatom and dinoflagellate biomass, composition and seasonality in the Belgian Part of the North Sea between the 1970s and 2000s.

In the last decades, the North Sea has undergone intense environmental changes which have led to regime shifts that affected all trophic levels. Since the 1970s, both increases and decreases in phytoplankton biomass and production have been reported from different parts of the North Sea. Such conflicting observations may be partly caused by methodological differences, but also reflect regional differences related to bathymetry, hydrodynamics, climate, riverine and Atlantic influence. The Belgian part of the North Sea (BPNS) is a hydrodynamically and bathymetrically complex area under strong human influence, which has been characterized by eutrophication (up to the 1980s) and de-eutrophication (1990s onwards), and pronounced long-term changes in turbidity and water temperature. We used a newly recovered and standardized historic dataset, the Belgian Phytoplankton Database (Nohe et al., 2018), to compare the biomass, composition and seasonality of diatom and dinoflagellate assemblages, two key components of the plankton in the BPNS, between the 1970s and 2000s. Diatoms, especially large-sized taxa, showed an increase from late winter to summer, resulting in a more intense and extended growing season in the 2000s. Dinoflagellates increased year-round but especially in summer. Both diatom and dinoflagellate blooms showed a clear shift towards an earlier bloom start. In addition, while in the 1970s distinct seasonal community types were present, a striking seasonal homogenization in community structure had occurred by the 2000s. Finally, we observed a pronounced increase in the abundance of harmful diatom and dinoflagellate genera. The observed changes are most likely due to an increase in sea surface temperature and water transparency, and changes in nutrient loads and ratios. Our study underscores the importance of recovering previously inaccessible historic data as they can offer unprecedented insights into long-term change in marine ecosystems, which are essential for properly evaluating the impact of human activities on these ecosystems.

Biodiversity data rescue in the framework of a long-term Kenya-Belgium cooperation in marine sciences.

The Kenya-Belgium data collection includes about 111,800 biotic observations on benthos, algae, fish, zooplankton, phytoplankton, birds and mangroves which cover more than 400 unique locations that were sampled between 1873 and 1999. The scope of this data digitization project was to recover data in theses and reports resulting from marine and coastal research activities in the Eastern African region conducted between 1984 and 1999. Data were digitized and quality checked in the frame of the Belgian LifeWatch project. The dataset provides a better insight into the different types of research conducted between 1985 and 1996 in frame of the Kenya-Belgium cooperation in marine sciences (KBP) project and can facilitate further coastal biodiversity research in Kenya.

Marine phytoplankton community composition data from the Belgian part of the North Sea, 1968-2010.

The Belgian Phytoplankton Database (BPD) is a comprehensive data collection comprising quantitative phytoplankton cell counts from multiple research projects conducted since 1968. The collection is focused on the Belgian part of the North Sea, but also includes data from the French and the Dutch part of the North Sea. The database includes almost 300 unique sampling locations and more than 3,000 sampling events resulting in more than 86,000 phytoplankton cell count records. The dataset covers two periods: 1968 to 1978 and 1994 to 2010. The BPD can be accessed online and provides high quality phytoplankton count data. The species taxonomy is updated, and the count values are quality checked and standardized. Important metadata like sampling date, sampling location, sampling depth and methodology is provided and standardized. Additionally, associated abiotic data and biovolume values are available. The dataset allows to conduct analyses of long-term temporal and spatial trends in phytoplankton community structure in the southern part of the North Sea, including changes in phytoplankton phenology and seasonality.

Fishing for data and sorting the catch: assessing the data quality, completeness and fitness for use of data in marine biogeographic databases.

Being able to assess the quality and level of completeness of data has become indispensable in marine biodiversity research, especially when dealing with large databases that typically compile data from a variety of sources. Very few integrated databases offer quality flags on the level of the individual record, making it hard for users to easily extract the data that are fit for their specific purposes. This article describes the different steps that were developed to analyse the quality and completeness of the distribution records within the European and international Ocean Biogeographic Information Systems (EurOBIS and OBIS). Records are checked on data format, completeness and validity of information, quality and detail of the used taxonomy and geographic indications and whether or not the record is a putative outlier. The corresponding quality control (QC) flags will not only help users with their data selection, they will also help the data management team and the data custodians to identify possible gaps and errors in the submitted data, providing scope to improve data quality. The results of these quality control procedures are as of now available on both the EurOBIS and OBIS databases. Through the Biology portal of the European Marine Observation and Data Network (EMODnet Biology), a subset of EurOBIS records--passing a specific combination of these QC steps--is offered to the users. In the future, EMODnet Biology will offer a wide range of filter options through its portal, allowing users to make specific selections themselves. Through LifeWatch, users can already upload their own data and check them against a selection of the here described quality control procedures. Database URL: www.eurobis.org (www.iobis.org; www.emodnet-biology.eu/).

Improving transferability of introduced species' distribution models: new tools to forecast the spread of a highly invasive seaweed.

The utility of species distribution models for applications in invasion and global change biology is critically dependent on their transferability between regions or points in time, respectively. We introduce two methods that aim to improve the transferability of presence-only models: density-based occurrence thinning and performance-based predictor selection. We evaluate the effect of these methods along with the impact of the choice of model complexity and geographic background on the transferability of a species distribution model between geographic regions. Our multifactorial experiment focuses on the notorious invasive seaweed Caulerpa cylindracea (previously Caulerpa racemosa var. cylindracea) and uses Maxent, a commonly used presence-only modeling technique. We show that model transferability is markedly improved by appropriate predictor selection, with occurrence thinning, model complexity and background choice having relatively minor effects. The data shows that, if available, occurrence records from the native and invaded regions should be combined as this leads to models with high predictive power while reducing the sensitivity to choices made in the modeling process. The inferred distribution model of Caulerpa cylindracea shows the potential for this species to further spread along the coasts of Western Europe, western Africa and the south coast of Australia.

Climate change impact on seaweed meadow distribution in the North Atlantic rocky intertidal.

The North-Atlantic has warmed faster than all other ocean basins and climate change scenarios predict sea surface temperature isotherms to shift up to 600 km northwards by the end of the 21st century. The pole-ward shift has already begun for many temperate seaweed species that are important intertidal foundation species. We asked the question: Where will climate change have the greatest impact on three foundational, macroalgal species that occur along North-Atlantic shores: Fucus serratus, Fucus vesiculosus, and Ascophyllum nodosum? To predict distributional changes of these key species under three IPCC (Intergovernmental Panel on Climate Change) climate change scenarios (A2, A1B, and B1) over the coming two centuries, we generated Ecological Niche Models with the program MAXENT. Model predictions suggest that these three species will shift northwards as an assemblage or "unit" and that phytogeographic changes will be most pronounced in the southern Arctic and the southern temperate provinces. Our models predict that Arctic shores in Canada, Greenland, and Spitsbergen will become suitable for all three species by 2100. Shores south of 45° North will become unsuitable for at least two of the three focal species on both the Northwest- and Northeast-Atlantic coasts by 2200. If these foundational species are unable to adapt to the rising temperatures, they will lose their centers of genetic diversity and their loss will trigger an unpredictable shift in the North-Atlantic intertidal ecosystem.

Contrasting geographical distributions as a result of thermal tolerance and long-distance dispersal in two allegedly widespread tropical brown algae.

BACKGROUND: Many tropical marine macroalgae are reported from all three ocean basins, though these very wide distributions may simply be an artifact resulting from inadequate taxonomy that fails to take into account cryptic diversity. Alternatively, pantropical distributions challenge the belief of limited intrinsic dispersal capacity of marine seaweeds and the effectiveness of the north-south oriented continents as dispersal barriers. We aimed to re-assess the distribution of two allegedly circumtropical brown algae, Dictyota ciliolata and D. crenulata, and interpret the realized geographical range of the respective species in relation to their thermal tolerance and major tectonic and climatic events during the Cenozoic. METHODOLOGY/PRINCIPAL FINDINGS: Species delimitation was based on 184 chloroplast encoded psbA sequences, using a Generalized Mixed Yule Coalescent method. Phylogenetic relationships were inferred by analyzing a six-gene dataset. Divergence times were estimated using relaxed molecular clock methods and published calibration data. Distribution ranges of the species were inferred from DNA-confirmed records, complemented with credible literature data and herbarium vouchers. Temperature tolerances of the species were determined by correlating distribution records with local SST values. We found considerable conflict between traditional and DNA-based species definitions. Dictyota crenulata consists of several pseudocryptic species, which have restricted distributions in the Atlantic Ocean and Pacific Central America. In contrast, the pantropical distribution of D. ciliolata is confirmed and linked to its significantly wider temperature tolerance. CONCLUSIONS/SIGNIFICANCE: Tectonically driven rearrangements of physical barriers left an unequivocal imprint on the current diversity patterns of marine macroalgae, as witnessed by the D. crenulata-complex. The nearly circumglobal tropical distribution of D. ciliolata, however, demonstrates that the north-south oriented continents do not present absolute dispersal barriers for species characterized by wide temperature tolerances.