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A network of European organisations is coordinating a workshop in New York (USA) on September 26, 2024, as part of the Science Summit 2024 at the 79th Session of the UN General Assembly (UNGA79). This network represents active communities from the fields of biodiversity, ecology, and engineering. It aims to strengthen science, technology, and innovation efforts to achieve the UN Sustainable Development Goals (SDGs). These communities, through European initiatives like the European Research Infrastructures, the European Open Science Cloud (EOSC), and Digital Twin projects, have selected the Kunming-Montreal Global Biodiversity Framework (K-M GBF) as a testbed for contributing to the SDGs. Their collective focus is on the network shared impact rather than individual projects. By examining a common approach to the K-M GBF, they aim to enhance their contributions to the framework's strategic goals, particularly its 2030 and 2050 targets. In this direction, the network: Recognises the contribution and rights of indigenous peoples and local communities as custodians of biodiversity and holders of traditional knowledge for the conservation, restoration, and sustainable use of ecosystems. By adhering to the Open Science principles of "Findable Accessible Interoperable Reusable" (FAIR) and "Collective Benefit, Authority to Control, Responsibility, Ethics" (CARE), and by being consistent with the practices adopted by the scientific community, the members of the network promote traceability of their work and of the materials they use, including those provided by indigenous peoples. Implements a variety of approaches to improve biodiversity monitoring, management, and protection. It promotes multi- and cross-disciplinary, integrative approaches to enhance its contribution to many of the Framework objectives. Its members support research on biodiversity at all levels of the biological organisation, from single-celled organisms, through collections and specimen data and up to the scale of ecosystems, as well as on how biodiversity responds to climate change. A key role in this process is already being played by the biodiversity Research Infrastructures, both in the EU and globally, through bi- and multi-directional linking and an increased interoperability of their data holdings, the provision of advanced access to semantically structured FAIR data, the provision of single points of access to federated data discovery from different data domains, thus supporting multi-disciplinary research addressing questions of high complexity and importance to society. All organisations in the network are committed to the three principal objectives of the Convention on the Biological Diversity, namely conservation, sustainable use, and fair sharing of benefits derived from the utilisation of natural resources. They contribute significantly to the three above principal objectives of the CBD, by: (a) making biodiversity information readily available and developing systems to support decision making and conservation efforts that directly contribute to our ability to live sustainably with nature, as concerns the first of the principal objectives above; (b) identifying priorities and targets and raising awareness of the need to streamline efforts among scientific and societal actors, are critical elements towards the second objective; (c) developing technologies to enable the sharing of data, services and other products related to genetic resources, which are used in combination with any other type of resource or product (e.g. taxonomic, literature, environmental, etc.), are included among the activities to achieve the third principal objective. Contributes to the achievement of the K-M GBF objectives through science, technology and innovation, based on scientific evidence, traditional knowledge, and innovative practices. This support is translated into activities such as: (a) providing solutions for research, data sharing and management, and scientific computing solutions to researchers, learners, policy makers, public administrations and businesses; (b) developing standard operating procedures, implementing standards, and promoting open science principles to enhance research integrity, accuracy and accountability in science; (c) providing federated research services, resources, and other research products to promote multidisciplinary knowledge and innovation; (d) creating models (e.g. of climate and human activity related land-use changes in biodiversity dynamics and ecosystem services), automated data flows (from sensors to data systems) and integration (e.g. biodiversity data flows combined with environmental and human activity variables; (e) building digital twins for informed decision making, such as the European Digital Twin of the Ocean (European DTO), with assured connectivity to newly collected high quality environmental and biodiversity data; (f) providing training and capacity building services for innovative tools. Supports the consideration of the ecosystem approach principle in the implementation of the K-M GBF, with a number of activities being developed by the network: (a) providing virtual representations of the ocean and land, integrating observations, modelling, and digital infrastructures, and creating digital twins that allow the scientific community to simulate and study "what if" scenarios; (b) developing and implementing technologies that enable a cross-domain, multidisciplinary approach to the study of biodiversity and ecosystems; (c) promoting ecosystem-based approaches to biodiversity management and habitat conservation in innovative publications venues (e.g. Nature Conservation, Biodiversity Data Journal, One Ecosystem, etc.). Promotes collaboration and synergies between the Convention on Biological Diversity and its Protocols, as well as with other biodiversity-related conventions, relevant multilateral agreements and international organisations and processes, as this will facilitate the implementation of the K-M GBF. The network is developing a variety of work, including: (a) collaborating with bodies and organisations responsible for the implementation of the CBD and its Protocols (e.g. IUCN, IPBES, European Commission) to co-design and co-develop research resources and products to support their mandates; (b) establishing strong links with policy actors such as the European Commission and the European Parliament, the JRC and others. Participate in social, scientific and technical initiatives in the European arena, such as the European Green Deal, the EU Knowledge Centre for Biodiversity and its Science Service for Biodiversity, the Biodiversity Knowledge Hub, the EU Pollinators Initiative and the EOSC. Developing links with the private sector through the Science/Business initiative, cooperation with the European Environmental Bureau (EEB), and the EOSC Digital Innovation Hub (EOSC DIH); (c) integrating and sharing of computational resources and expertise will not only advance the frontiers of scientific knowledge, but also ensure that data-driven research initiatives around the world are well supported. Contributes to the understanding and researching of the links between biodiversity and health. Particular emphasis will be placed on the following activities: (a) participating in initiatives and projects such as the EOSC Health Cluster, a platform for interdisciplinary research, EC projects such as B4Life, B-Cubed and BioAgora by publishing research that investigates how biodiversity affects human health; (b) using data from multiple sources to numerically demonstrate the links between human and environmental health, in the context of the One Health concept; (c) using digital twins to create Virtual Research Environments (VREs) that generate knowledge on how biodiversity patterns derived from taxa and habitats interact with patterns derived from data and information on their health; (d) publishing the results of the research, such as studies on zoonotic diseases, biodiversity and mental health, and the benefits of ecosystem services for public health. During the workshop, the participants will present their collective contribution to the implementation of the K-M GBF and invite international and regional stakeholders to present their expectations on the above topic. Based on stakeholder input, the network will publish a white paper outlining its approach. Finally, these communities will issue an open call to forge an international alliance to further integrate biodiversity conservation into the priorities of the UN Summit of the Future agenda priorities and the post-SDG agenda. [ABSTRACT FROM AUTHOR]

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.

Marine phytoplankton biomass dynamics are affected by eutrophication, ocean warming, and ocean acidification. These changing abiotic conditions may impact phytoplankton biomass and its spatiotemporal dynamics. In this study, we used a nutrient-phytoplankton-zooplankton model to quantify the relative importance of bottom-up and top-down determinants on phytoplankton biomass dynamics in the Belgian Part of the North Sea. Using four years (2014-2017) of monthly observations at nine locations of nutrients, solar irradiance, sea surface temperature, chlorophyll-a and zooplankton biomass, we disentangled the monthly, seasonal and yearly variation in phytoplankton biomass dynamics. To quantify how the relative importance of determinants changed along a near-offshore gradient, the analysis was performed for three spatial regions, i.e. nearshore region (< 10 km to the coastline), midshore region (10-30 km), and offshore region (> 30 km). We found that from year 2014 to 2017, phytoplankton biomass dynamics ranged from 1.4 to 23.1 mg Chla m-3. Phytoplankton biomass dynamics follow a general seasonal cycle as in other temperate regional seas, with a distinct spring bloom (5.3-23.1 mg Chla m-3) and a modest autumn bloom (2.9-5.4 mg Chla m-3). This seasonal pattern was most expressed in the nearshore region. The relative contribution of factors determining phytoplankton biomass dynamics varied spatially and temporally. Throughout a calendar year, solar irradiance and zooplankton grazing were the most influential determinants in all regions, i.e. explained 38 %-65 % of the variation in the offshore region, 45 %-71 % in the midshore region, and 56 %-77 % in the nearshore region. In the near- and midshore regions, nutrients are most limiting the phytoplankton production in the month following the spring bloom (44 %-55 %). Nutrients are a determinant throughout the year in the offshore region (27 %-62 %). During winter, sea surface temperature is a determinant in all regions (15 %-17 %). The findings of this study contribute to a better mechanistic understanding of the spatiotemporal dynamics of phytoplankton biomass in the southern North Sea. The parameterized causal relationships allow estimating how the base of the southern North Sea food web will change under future climate change and/or blue economy activities that affect one or more determinants of the phytoplankton biomass dynamics. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]