Invasive Alien Species in Belgian marine waters: an information platform and checklist for science and policy support

Since 2006, the ‘VLIZ Alien Species Consortium’ has collected data and information on species that were introduced by humans in marine and brackish habitats and have established reproducing populations in the study area. The consortium consists of a network of experts in marine and brackish environments in Belgium, representing more than 22 different institutions and supported by a secretariat hosted at Flanders Marine Institute VLIZ. Evidence on invasiveness is reported for 12 of the 73 alien species that are currently included in the checklist for the study area (October 2014). The network brings together scientific information from distributed sources in a central platform. It is a first step to developing an evidence-based approach to inform environmental policy objectives for Belgian marine waters and support effective measures to address invasive alien species in the study area. The information platform and species checklist are presented, approaches for collection and integration of information are described, and opportunities for collaboration between information systems at different governance levels are briefly discussed

Cyberinfrastructure Deployments on Public Research Clouds Enable Accessible Environmental Data Science Education

Modern science depends on computers, but not all scientists have access to the scale of computation they need. A digital divide separates scientists who accelerate their science using large cyberinfrastructure from those who do not, or who do not have access to the compute resources or learning opportunities to develop the skills needed. The exclusionary nature of the digital divide threatens equity and the future of innovation by leaving people out of the scientific process while over-amplifying the voices of a small group who have resources. However, there are potential solutions: recent advancements in public research cyberinfrastructure and resources developed during the open science revolution are providing tools that can help bridge this divide. These tools can enable access to fast and powerful computation with modest internet connections and personal computers. Here we contribute another resource for narrowing the digital divide: scalable virtual machines running on public cloud infrastructure. We describe the tools, infrastructure, and methods that enabled successful deployment of a reproducible and scalable cyberinfrastructure architecture for a collaborative data synthesis working group in February 2023. This platform enabled 45 scientists with varying data and compute skills to leverage 40,000 hours of compute time over a 4-day workshop. Our approach provides an open framework that can be replicated for educational and collaborative data synthesis experiences in any data- and compute-intensive discipline

The absolute abundance calibration project: the <i>Lycopodium</i> marker-grain method put to the test

Traditionally, dinoflagellate cyst concentrations are calculated by adding an exotic marker or “spike” (such as Lycopodium clavatum) to each sample following the method of Stockmarr (1971). According to Maher (1981), the total error is controlled mainly by the error on the count of Lycopodium clavatum spores. In general, the more L. clavatum spores counted, the lower the error. A dinocyst / L. clavatum spore ratio of ~2 will give optimal results in terms of precision and time spent on a sample. It has also been proven that the use of the aliquot method yields comparable results to the marker-grain method (de Vernal et al., 1987). Critical evaluation of the effect of different laboratory procedures on the marker grain concentration in each sample has never been executed. Although, it has been reported that different processing methods (e.g. ultrasonication, oxidizing, etc.) are to a certain extent damaging to microfossils (e.g. Hodgkinson, 1991), it is not clear how this is translated into concentration calculations. It is wellknown from the literature that concentration calculations of dinoflagellate cysts from different laboratories are hard to resolve into a consistent picture. The aim of this study is to remove these inconsistencies and to make recommendations for the use of a standardized methodology. Sediment surface samples from four different localities (North Sea, Celtic Sea, NW Africa and Benguela) were macerated in different laboratories each using its own palynological maceration technique. A fixed amount of Lycopodium clavatum tablets was added to each sample. The uses of different preparation methodologies (sieving, ultrasonicating, oxidizing …) are compared using both concentrations – calculated from Lycopodium tablets - and relative abundances (more destructive methods will increase the amount of resistant taxa). Additionally, this study focuses on some important taxonomic issues, since obvious interlaboratorial differences in nomenclature are recorded

Strategies to diagnose ovarian cancer: new evidence from phase 3 of the multicentre international IOTA study

Background: To compare different ultrasound-based international ovarian tumour analysis (IOTA) strategies and risk of malignancy index (RMI) for ovarian cancer diagnosis using a meta-analysis approach of centre-specific data from IOTA3. Methods: This prospective multicentre diagnostic accuracy study included 2403 patients with 1423 benign and 980 malignant adnexal masses from 2009 until 2012. All patients underwent standardised transvaginal ultrasonography. Test performance of RMI, subjective assessment (SA) of ultrasound findings, two IOTA risk models (LR1 and LR2), and strategies involving combinations of IOTA simple rules (SRs), simple descriptors (SDs) and LR2 with and without SA was estimated using a meta-analysis approach. Reference standard was histology after surgery. Results: The areas under the receiver operator characteristic curves of LR1, LR2, SA and RMI were 0.930 (0.917–0.942), 0.918 (0.905–0.930), 0.914 (0.886–0.936) and 0.875 (0.853–0.894). Diagnostic one-step and two-step strategies using LR1, LR2, SR and SD achieved summary estimates for sensitivity 90–96%, specificity 74–79% and diagnostic odds ratio (DOR) 32.8–50.5. Adding SA when IOTA methods yielded equivocal results improved performance (DOR 57.6–75.7). Risk of Malignancy Index had sensitivity 67%, specificity 91% and DOR 17.5. Conclusions: This study shows all IOTA strategies had excellent diagnostic performance in comparison with RMI. The IOTA strategy chosen may be determined by clinical preference