This document describes the Portuguese Cave Monitoring Network (CaveNet), a scientific infrastructure established within the framework of the EcoSub Chair. CaveNet provides an integrated framework for the quantitative monitoring of caves in Portugal, encompassing data collection, validation, processing and storage. The document presents the architecture and objectives of the infrastructure, highlights its scientific and ecological relevance and characterises the sites selected for Long-Term Ecological Research in Portuguese caves (LTER-Grutas). These sites host monitoring stations whose long-term environmental and ecological data are integrated into CaveNet. The document further discusses the advantages of an integrated cave monitoring network and its direct applicability to the assessment and reporting of the conservation status of habitat type 8310 - Caves not open to the public - under the Natura 2000 framework, as well as to the implementation of the Nature Restoration Regulation. In addition, CaveNet has significant socio-economic value, particularly in supporting the assessment and management of occupational risks associated with exposure to environmental hazards during underground work. In the longer term, the infrastructure will enable innovative research on carbon fluxes across the atmosphere–soil–subsoil–groundwater continuum, subsurface radioactivity emissions and the implications of subterranean processes for ecosystem services. These research and monitoring activities are aligned with the United Nations Sustainable Development Goals and the One Health approach. At a global scale, CaveNet provides a unique platform for investigating the complex ecological interactions occurring at the surface–subterranean interface. By integrating standardised, long-term observations across multiple cave systems, the network will contribute to a better understanding of subterranean ecosystems, their environmental dynamics and their responses to natural and anthropogenic pressures. It will also provide a robust scientific basis for conservation, environmental assessment, risk management and the sustainable management of subterranean environments.
The MPA Europe project will map the optimal locations for Marine Protected Areas (MPA) in European seas using measures covering the range of biodiversity from species to ecosystems, including habitats. The contribution of these measures to carbon storage will be quantified and mapped. The top 10% and 30% of the area that includes most species, habitats, and ecosystems, and maximises blue carbon benefits, will be prioritised as an MPA network. The geographic scope is the Atlantic Exclusive Economic Zones of the EU and its neighbours, and all of the Mediterranean, Baltic and Black Seas. Feedback from Marine Spatial Planning (MSP) stakeholders in the regional seas on the proposed MPA network and methodology will be reported. A first data-driven classification of ecosystems in European seas will use environmental data from Copernicus and EMODnet.Environmental niche models will map thousands of species, including habitat-forming species, ranges and contribute to existing seabed habitat maps in EMODnet. Analyses of spatial relationships between biodiversity measures and evidence of carbon storage will support the prioritisation analyses. Parallel modelling of current connectivity and the velocity of climate change will map connectivity within the proposed MPA network and how it will accommodate species distribution shifts due to anthropogenic climate change. All data and maps will be freely available through EMODnet, the Ocean Biodiversity Information System, ECKnowledge Centre for Biodiversity, and the project’s online atlas. The atlas will provide transparency, traceability and enable reproducibility of the results. Its synthesis will show stakeholders (MSP, NGO, students, researchers) why areas have been prioritised. The use of decision support software will enable alternative network designs based on stakeholder preferences and could thus support wider MSP beyond the subject and study area.
This guide specifies high-level requirements for software, computational tools and resources developed for B-Cubed (referred to in the sections as “software”) to ensure that the produced software meets the intended quality, openness, portability and reusability.
Marine biodiversity is adversely affected by many human activities and their pressures which then need managing. As such, there is the need for a cause-consequence-response method to objectively address the risks associated with those adverse changes. Such a method is the ISO-accredited Bow-tie technique as an objective and structured approach giving the following elements: causes, preventative control measures, mitigation and compensation measures and consequences of changes to biodiversity. Here, the Bow-tie method, underpinned by the cause-consequence-response DAPSI(W)R(M) framework, was used and adapted to help managers map out risks to biodiversity requiring management of the human activities and their relevant pressures in specific case study areas (termed Broad Belt Transects, BBTs). Instead of using the available restrictive proprietary software, a more-flexible template framework was developed in Microsoft PowerPoint to allow a broad user base. This employed standardised lists of elements (and further adapted during the application process) allowing the development of unique, but standardised and directly comparable Bow-tie diagrams for all BBTs. The methods of developing the template and standardised lists are described together with the techniques used to help quantify this usually qualitative approach. The successful application of the Bow-tie method in case studies from European seas shows the adaptability of this approach in ways wider than the original policy-driven risk-assessment use. Although designed for European seas, the approach and standardised lists are sufficiently generic for adoption in wider areas worldwide.
Modern microbiological research generates vast quantities of data, particularly from high-throughput "omics" technologies. These datasets promise unprecedented insights into microbial diversity, function, and interactions, yet they are often deposited in unstructured formats with inadequate metadata, significantly hampering their discoverability, interoperability, and long-term reusability. Adding to this challenge is a long tail of subdomain-specific data types that typically lack a consistent structure. NFDI4Microbiota empowers microbiology researchers by transforming their research data into actionable knowledge that offers deeper insights into microbial life. The consortium makes data, software tools, analytical workflows, and machine-learning models FAIR (Findable, Accessible, Interoperable, and Reusable), ensuring they are AI-ready and openly available for efficient reuse. Key strategies include comprehensive training, developing and disseminating community-driven standards and best practices, fostering strong data stewardship, providing user-friendly data management tools and infrastructure, and promoting standardisation across the microbiology community. Building on our successful first funding phase, we will expand NFDI4Microbiota’s efforts in the next phase to enhance data accessibility and reuse while enabling AI applications. Our achievements and infrastructure from the first funding period provide a solid foundation for achieving an even greater impact across the microbiology research community and fostering a seamless flow of data. Community engagement remains vital: we will strengthen collaboration with existing stakeholders while actively reaching out to previously underrepresented groups, specifically researchers working on eukaryotic microbes such as fungi and protists, and we will work more closely with data-generating facilities to capture rich metadata early on. In addition, we will further strengthen our portfolio of services, databases, and analytical tools, ensuring that they are robust, interoperable, and tailored to evolving community needs. These enhancements will support a more comprehensive and inclusive data infrastructure for microbiological research. To help realise the One NFDI and EOSC vision of a coherent, sustainable, and collaborative research data ecosystem across all disciplines, NFDI4Microbiota will actively engage in cross-consortial initiatives, foster interoperability, and apply the unique perspectives of microbiological science to help shape the broader NFDI landscape.
