The ocean is rapidly changing through warming, sea-level rise, ocean acidification, declining oxygen concentrations, and altered circulation patterns, which are reshaping marine ecosystems worldwide. These changes necessitate a complete and holistic view of affected marine ecosystems. Long-term ocean monitoring programs are crucial for understanding these changes and guiding sustainable management. The California Cooperative Oceanic Fisheries Investigations (CalCOFI)*1, initiated in 1949, is one of the world's longest-running and most comprehensive marine ecosystem observing programs. CalCOFI collects extensive ocean data across all Essential Ocean Variables in the Southern California Current four times a year (Gallo et al. 2022). This encompasses over 36 physical and chemical parameters, 2,500 biological parameters, and 50,000 environmental DNA sequences, measured simultaneously (Satterthwaite et al. 2025). These data have illuminated long-term ecosystem patterns, supported marine management, and enhanced our understanding of how climate variability and change impact the California Current. Given its long history and collaborative nature, CalCOFI's data are fragmented across more than 30 disparate datasets, managed by different entities, served in various locations, with inconsistent naming and limited integration (Fig. 1), which hinders a holistic ecosystem understanding. Thus, CalCOFI exemplifies similar challenges and opportunities of mobilizing and integrating ocean data on a global scale. Our vision has been to modernize and build an integrated data system for CalCOFI that automates dataset ingestion, integration, and serving for timely use in research and management (Fig. 1). We are developing workflows to publish these datasets into portals promoting Findable, Accessible, Interoperable, and Reusable (FAIR; Wilkinson et al. 2016) data principles. Our initial efforts focused on two core CalCOFI datasets: Conductivity, Temperature, and Depth (CTD) bottle data and larval fish data to develop a workflow for easier access, integration, and use (Fig. 2). Data providers upload processed datasets into a shared Google Drive in simple formats (e.g., .csv), with globally unique identifiers and standardized naming conventions (Suppl. material 1). Data are automatically detected and integrated into a PostgreSQL database (Fig. 2). Newly added data trigger a system rebuild and validation, checking primary keys, spatial geometry, taxonomy, and metadata. Managers are notified of errors; otherwise, the system updates production databases, records a new version, and publishes a Github release with source files and a DOI via Zenodo. Original source data files are retained for past version reconstruction. While PostgreSQL maintains relationships between data, we also produce an analytical database in DuckDB for a single, portable database with fast querying, even on remote servers (Fig. 2). CalCOFI data and observations are accessible through multiple repositories and platforms, tools, interfaces, and portals based on user needs and funder requirements (Fig. 2; Suppl. material 1). For example, some tools support flexible analysis and visualization (e.g., NOAA Environmental Research Division's Data Access Program), others provide long-term archiving with standardized metadata (e.g., Environmental Data Initiative). We are also publishing biological observations in DarwinCore (Wieczorek et al. 2012) format with Extended Measurement or Fact and uploading them to the Ocean Biodiversity Information System (OBIS) so that CalCOFI data can be integrated with global biodiversity datasets worldwide. CalCOFI program information is on the Global Ocean Observing System Biology & Ecosystem Portal, and dataset records are structured for indexing by portals like Ocean Data Information System (ODIS) and Google Dataset Search. To facilitate data access and visualization, we also developed the CalCOFI Integrated Data Viewer*2 (Fig. 3). This web app allows users to explore decades of CalCOFI oceanographic and larval fish data across space, time, and depth. We plan to integrate additional CalCOFI datasets and collaborate with other data providers to build a more complete ecosystem-level view of the California Current. Our ultimate goal is to enhance CalCOFI data findability, integration, and usability for scientific and management communities, enabling a better understanding of ocean changes and ensuring a sustainable future for marine ecosystems and human communities.

Environmental DNA (eDNA)-derived data, particularly DNA sequences and species occurrence records, are powerful resources for various applications, including biodiversity monitoring, biosecurity, and agricultural bio-surveillance. An important part of eDNA data’s value lies in its reusability, which can be enhanced through the use of metadata that adheres to FAIR (Findable, Accessible, Interoperable, Reusable) data principles (Wilkinson et al. 2016, Abarenkov et al. 2023). While FAIR practices are gaining recognition within the eDNA community, adoption remains limited. A key barrier is that existing data standards, including Darwin Core (DwC, Darwin Core Task Group 2009) and the Minimum Information about any (x) Sequence (MIxS), lack sufficient terms to fully describe eDNA workflows, from sampling and processing to bioinformatic outputs (Takahashi et al. 2025). To address this challenge, we have initiated a collaborative eDNA Task Group supported by the Biodiversity Information Standards (TDWG) and the Genomic Standards Consortium (GSC) organisations. We build upon current standardisation efforts to develop a comprehensive and interoperable eDNA metadata checklist for formal integration into the MIxS and DwC frameworks. See the task group descriptions at TDWG*2 and GSC.*1 Our goal is to ensure compatibility with, and seamless adoption by, major biodiversity and sequence data infrastructures, such as Global Biodiversity Information Facility (GBIF), Ocean Biodiversity Information System (OBIS), and International Nucleotide Sequence Database Collaboration (INSDC). This talk will present progress of the TDWG/GSC joint eDNA initiative, including our collaborative efforts with related working groups and initiatives, such as eDNAqua-plan, the Darwin Core Data Package, DNA-derived data extension to DwC, Minimum Information about any Ancient Sequence (MInAS), and the FAIR eDNA (FAIRe) initiatives (Takahashi et al. 2025). We invite contributions and collaboration to help shape a shared metadata framework that supports the growth, reuse, and long-term utility of eDNA data worldwide.

There is an ambitious global goal to protect 30% of the ocean by 2030. However, currently, only 8.1% of the ocean is protected and over 80% of the ocean is still unexplored. We thus urgently need to collect data for evidence-based decision-making to help tackle the global climate and biodiversity crises and to support coastal communities. But mapping these areas and key indicator species like whales using ship-based and aerial surveys tend to be limited in scale/scope, time-consuming, expensive and pose safety risks to surveyors, while acoustic monitoring is difficult to convert into counts of individuals for most species. To overcome these challenges, BioConsult SH and HiDef Aerial Surveying Ltd developed the service, SPACEWHALE. Bridging technological innovation with marine conservation, SPACEWHALE monitors whales and other wildlife species from space using satellite imagery and AI. We determine where whales are, provide a minimum count and investigate when they are in certain areas—quickly and over wide cross-border areas—yet at comparable costs to traditional survey methods. The “SPACEWHALE” service uses very high-resolution satellite imagery (e.g., resolution of 0.3 m per pixel). At this resolution, we can distinguish between several large whale species as well as between juveniles and adults. In addition, we can detect a diverse range of large cetaceans down to a body length of 9 meters and smaller. By taking a snapshot of the ocean area of interest, we can capture very large and remote areas almost instantaneously. Due to licensing restrictions, we are not permitted to share satellite imagery itself, but we summarise our findings in a report that contains easily processable data, such as the locations of the whales, for further analysis. We developed a semi-automatic process to evaluate satellite images combining state-of-the-art artificial intelligence with marine mammal expertise. Artificial intelligence as applied in SPACEWHALE means that data are collected and processed in a standardized way: satellite imagery is first analysed by a convolutional neural network-based object detection algorithm. Our algorithm is highly effective: a study in collaboration with Stony Brook University in New York and HiDef Aerial Surveying Ltd from the UK showed that the algorithm correctly classified 100% of images containing whales and 94% of images containing only water (Borowicz et al. 2019). Once the automated process is complete, a large team of expert reviewers validates the outputs to ensure that misclassifications such as boats, rocks, waves or sea foam are minimized, implementing a human-in-the-loop framework for comparable and quality-checked data. Applying this semi-automatic approach in diverse ecosystems, we have already successfully monitored fin whales and other species in the Bay of Biscay and in the Pelagos Sanctuary, blue whales and other marine megafauna off Mexico, humpback whales in Hawaiian waters, and southern right whales off Argentina and New Zealand. The methodology has been validated through comparison with conventional aerial and ship-based surveys demonstrating a strong agreement (Höschle et al. 2022). Satellite snapshots can be taken over previously unexplored areas, providing baseline data for environmental impact assessments for offshore wind farm operators and contributing to the identification of Important Marine Mammal Areas and Marine Protected Areas. The service can be applied at different spatial and temporal scales, from local and regional to ocean basins and over time with repeated surveys, enabling long-term monitoring, generating robust, standardized data for marine spatial planning and complementing international efforts (e. g. Marine Strategy Framework Directive, Convention on Biological Diversity targets, United Nations Ocean Decade). We are at a step where satellite-based data informs applied conservation by providing useful guidance to find solutions that balance species conservation with human use of the seas. It has the potential to elevate conservation efforts to appropriate spatial scales for wide ranging species.

The Darwin Core (DwC) standard (Darwin Core Maintenance Group 2023) is the most extensively adopted vocabulary maintained by the Biodiversity Information Standards (TDWG), with over 3.5 billion published records since its official ratification in 2009. TDWG strives to promote equitable participation in biodiversity informatics by participating in and facilitating broader internationalization initiatives, including making standards accessible to non-English-speaking communities. The initial comprehensive translation of the Darwin Core Terms documentation, as well as the Establishment Means Controlled Vocabulary, Degree of Establishment Controlled Vocabulary and the Pathway Controlled Vocabulary were finalized and published in the French language in May 2025. The translation was done using the Crowdin platform*1 and can be accessed on the official Darwin Core website*2. This endeavor offered a comprehensive view of the translation process, highlighting lessons learned along the way and leading to recommendations for similar efforts in the future. Some other questions are still unanswered to this day and will require further discussions, such as the treatment of deprecated terms, or finding the most effective method for integrating translations into the ongoing maintenance workflows of standards. In contrast to standards that were recently ratified such as Latimer Core (Saliba et al. (2025)), Darwin Core's extensive legacy use and maturity present specific translation challenges. During the translation process, questions emerged about adapting the language to enhance clarity and inclusivity. For French in particular, questions around linguistic purism arose, as the use of anglicisms is variable among different francophone communities. Strict translation practices might suggest avoiding borrowed terms, but privileging terminology already unanimously established in professional communities leads to pragmatic compromises to foster usability and adoption. An example is the term 'standard' itself, which should be translated as norme (e.g., une norme ISO ), but that doesn't reflect the current usage of French biodiversity information scientists who use the transparent and equally possible standard (e.g., le standard Darwin Core du TDWG ) instead. In other cases, if an official wording is used in regulatory or governmental contexts (such as espèces envahissantes , see for example Comité français de l'IUCN and Office Français de la Biodiversité (2023)), it was preferred over the alternative community-used anglicism ( espèces invasives ), as a way to reflect the normative nature of standards. French expressions are often more verbose than their English counterparts. In response, translators must balance fidelity with conciseness, occasionally rephrasing or adapting rather than rendering terms word-for-word to preserve the clarity and economy required in technical vocabularies. This is proving to be a particular challenge for the Humboldt extension, which is currently being translated. For example, the literal translation of the label 'Is Degree of Establishment Scope Fully Reported' becomes the fairly verbose label Est-ce que le Champs d’Application du Degré d’Implantation est Entièrement Répertorié . Ensuring that TDWG standards are available in French is essential to broaden participation from underrepresented communities across Africa, the Caribbean, the Pacific, and beyond. By lowering language barriers, the biodiversity informatics community can foster inclusivity, enhance data sharing, and strengthen global stewardship of biodiversity knowledge.

Introduction: Oceans cover over 70% of Earth’s surface (Cael et al. 2023). An estimated 2.2 million marine species exist, yet nearly 80% remain undescribed (Mora et al. 2011). Around 370,000 species are accepted in the World Register of Marine Species (WoRMS), but open-access occurrence data exists for only about 200,000 in the Ocean Biodiversity Information System (OBIS). Documenting marine biodiversity is vital for making evidence-based policy and management decisions in order to maintain ecosystem stability and planetary health. Initiatives such as the Census of Marine Life and open-access databases like OBIS continue to transform understanding and support the UN Decade of Ocean Science. Through data sharing and global collaboration, we can better estimate and conserve marine biodiversity by first identifying data and knowledge gaps. Methods: In two underrepresented areas, the South-West Pacific (SWP) and the Indian Ocean (IO), the current biodiversity patterns of fauna were mapped to identify the knowledge gaps and distribution patterns by depth zones. All occurrence data (Animalia) were extracted from the OBIS and the Global Biodiversity Information Facility (GBIF). The occurrence records were quality-controlled in accordance with the OBIS data quality guidelines (OBIS 2025). Only accepted marine taxa were retained after cross-referencing species names with the WoRMS. In total, 5,441,962 occurrence records in the SWP and 7,768,826 occurrence records in the IO were used in this study (Suppl. material 1). Results: The number of occurrence records decreased with depth in all taxa in both oceans. More than 60% of the occurrence records with available depth information were from shallow waters (0–200 m), highlighting significant knowledge gaps in deep-sea biodiversity. Still, more than 11 million km² of the SWP and IO had fewer than 50 occurrence records after data cleaning in the shallow waters. Based on 5-degree latitudinal bands, the higher latitudes of the SWP (0–25°S) were less sampled or the data were not reported, compared to the lower latitudes. Mid-latitudes of the SWP (30–45°S, eastern and western Australia) had the greatest distribution records, mostly related to Chordata, followed by Arthropoda and Mollusca. However, 10–25°S latitudes of the SWP had the highest number of reported species, mostly associated with Chordata, followed by Mollusca and Arthropoda. The mid-latitudes of the IO (5–30°S) were less sampled, or the data were not reported, compared to the upper and lower latitudes. Chordata occurrence records were the exception, with a peak at 10–25°S latitudes showing the highest distribution records, followed by Arthropoda. Also, 10–20°S latitudes of the IO had the greatest number of species, mostly related to Chordata, followed by Arthropoda and Mollusca (Suppl. material 2) and (Suppl. material 3). Application: The generated knowledge is crucial for strengthening biodiversity monitoring and ensuring rapid, accessible information for policymakers through science-policy interfaces such as the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), thereby supporting the development of urgent conservation strategies for underrepresented and threatened marine ecosystems, such as the SWP and the IO, before it is too late.

The exactness, fitness-for-purpose (FFP) and reliability of primary biodiversity data can be enhanced by additional data beyond the basic taxon-location-date triad (Hill et al. 2010). Often, the only available data are the labels in legacy specimen collections. The digitization process is most efficient if all available information can be collected at once in a single event of specimen handling, rather than in separate phases. There is, however, a compromise between producing a faster catalogue for immediate use and housekeeping, and an accurate, wider-FFP database where all data have been thoroughly checked. Recognizing potential sources of error at digitization time may help making choices. During a dataset integration procedure, the quality and reliability of the data capture was analyzed. The dataset consisted of transcribed label data of over 58K pinned insects of agriculturally-relevant groups in XXth-century collections at six institutions in Spain, that resulted in almost 6000 collector strings. But collector names could be unidentified; misread; ambiguous, duplicated under variants; or misplaced or misattributed to/from another entity, e.g. a location. unidentified; misread; ambiguous, duplicated under variants; or misplaced or misattributed to/from another entity, e.g. a location. This resulted in a high entropy level where one collector could be databased in multiple ways, artificially inflating the corresponding catalogues. The entropy was much higher in collections where collectors contributed few specimens, which is the case for university-based collections. By using simple indexing and cross-referencing techniques, the roster of names was significantly reduced, but full disambiguation of collectors required mining ancillary sources and consulting with people with long-standing knowledge of the collections. Overall, 42% of collector names were in error, resulting in excess entropy. METHODS Specimen data were collated from the TETTRIS INC-STEP Project of Spanish pollinators complemented by some agriculturally-relevant groups in six collections deposited at five academic and research institutions in Madrid, Barcelona, Valencia and Pamplona (see Suppl. material 1 for full details). MCNB, MNCN, MUVHN were chiefly historical and created by researchers over long careers, while MZNA-R, MZNA-Z, UCME came mainly from academic coursework activities. Our procedures agreed with the overall strategy of Groom et al. (2022), while devising a specific workflow. Disambiguation and attribution included a number of steps (Suppl. material 1). First, names were normalized to facilitate grouping and sorting (7 steps). Then, ambiguous names were (whenever possible) attributed to actual persons by internal checks (clustering of names, matching localities and dates), consultation with external references (e.g. student lists), or consultation with collection curators (5 steps). Names were finally given a four-level identity qualification resulting from the disambiguation exercise (see Suppl. material 1). For further analyses, “very low” and “low” levels were considered a poor attribution, while “medium” and “full” levels were deemed good attribution. RESULTS The disambiguation exercise reduced collector names from 5939 to 3473 (a 41.5% decrease). The total entropy, measured as Shannon’s H’, decreased by 8% while Simpson’s dominance D increased by 29%, as expected (merging names created larger collections for some collectors). However, there were differences among collections. The three academic collections had both higher diversity and higher diversity reduction than the historical collections (Fig. 1). Historical collections tended to be much more concentrated (30 specimens per collector, 25% single-specimen collectors) than the academic collections (8 and 61%, respectively). These differences can be tracked to how the collections were formed. Historical collections tended to be well documented and created by researchers spanning longer careers, while academic collections were often linked to works created during coursework. Fig. 2 shows the career spans of collectors. The abrupt end of collection at the turn of the century for academic collections can be linked to the introduction of restrictive legislation in Spain (a mandatory reduction of course loads, and unaffordable permission requirements). Full disambiguation often requires manual, time-consuming verifications against a variety of external sources. Automated disambiguation procedures elevated good identification from an initial 21% to 47% in MZNA-R, but it was not possible to use manual checking against sources for this dataset. In contrast, the similar MZNA-Z collection could be checked against coursework lists, which resulted in a 80% good attribution rate (Fig. 3). Overall, 57% of the collector names across collections had a good attribution. CONCLUSION Doing disambiguation exercises by people with contemporary knowledge of the collections appears to be critical to avoid losing much information from the collections. Curators have an invaluable knowledge of the collections, could locate relevant documents about them, and are the ones able to reduce collection entropy by at least 32%. Their early retirement would negate a significant way to disambiguate names that left little or no trace in the literature record.

iNaturalist*1 is a digital citizen science platform that allows the presence of species to be identified and geolocated. In Chile, it was adopted by the Ministry of the Environment*2 and is widely used by academics, students and the public. This platform has become a valuable educational tool at the Catholic University of the Most Holy Conception (USCS)*3, allowing students to experience being protagonists in the generation of knowledge, which is made instantly available to a community of millions of naturalists around the world. In the process, students learn to recognize the various species that exist in a given study site, a fundamental step to value and promote the conservation of biodiversity. The objective of this work is to share the progress made with 14 projects created since 2021 to the present, brought together under the umbrella project "Naturalists in Action"*4 (Fig. 1), with its concrete application to the registration of biodiversity on the main university campus, and moving forward into projects that involve community organizations. One hundred and eighty-three students from 23 undergraduate and graduate programs at UCSC (Fig. 2) have participated in these projects, with more than 6400 observations, 1190 species registered and identified, with the online collaboration of more than 800 specialists and naturalists in general (Fig. 1). Nearly 70% of the students who learned to use the application in curricular activities at UCSC have remained active on iNaturalist (Fig. 3), showing the interest generated by the knowledge of local biodiversity. In agreement with Di Cecco et al. (2021), a few of them stayed very active (Fig. 3). The most recent actions involve the creation of collection projects for areas delimited by a .kml file, such as the one created for the San Andrés Campus*5. In addition, students and academics have collaborated with citizen organizations that wish to promote the conservation of nature, in places of interest, by virtue of the biodiversity they host, or for the cultural value they represent. Emblematic iNaturalist projects are the ones generated to accompany the conference cycles created in alliance with the Museo de Historia Natural de Concepción (2024), Museo de Historia Natural de Concepción (2025a), Museo de Historia Natural de Concepción (2025b), entitled “Luciérnagas en Concepción”*6 and “ Puya chilensis Santuario de la Naturaleza Península de Hualpén”*7. Both include lectures at the Museum and registration of people interested in sighting the organisms of interest in the field. Fireflies and P. chilensis are two types of charismatic organisms that help to promote the conservation of habitats and biodiversity on a local scale.

The demand for natural products that promote sustainable production chains is growing worldwide. Honey, while not a staple for food security due to its limited nutritional contribution, represents a valuable resource to foster dietary diversity, responsible consumption, and forest conservation. Its production depends directly on access to diverse flora with low pesticide exposure and requires minimal soil transformation or external inputs, making it a low-impact practice. Beekeeping also contributes to the maintenance of pollinator populations, which are key for biodiversity and sustainable agriculture. Consumer interest in the origin and authenticity of honey has grown in recent years, especially for Apis mellifera products (Escuredo and Seijo 2024, Mascarello et al. 2024). Less known is the diversity and economic potential of stingless bees (Meliponini). Across tropical and neotropical regions, nearly 500 species have been described (Grüter 2020), many of which produce honey and act as key pollinators. In Colombia, about 34 species are reportedly used in meliponiculture (Nates-Parra and Rosso-Londoño 2013). This practice is expanding in rural areas, where it complements agriculture and is compatible with family-centered management. Traditional knowledge attributes medicinal properties to stingless bee products (Sgariglia et al. 2010, Rosales 2012). Although clinical validation remains limited, biochemical studies of their honeys have identified distinctive compositions rich in phenolic compounds and other bioactive molecules, providing preliminary evidence of antioxidant and anti-inflammatory properties that warrant further research (Gomes et al. 2022). These properties are linked to microbial communities naturally present in stingless bee honeys. Fermentative yeasts and lactic acid bacteria shape these products, creating unique ecological niches with potential probiotic and bioactive value (da Silva et al. 2024). Microbial assessment is also essential to detect possible pathogens, as not all stingless bee species are recommended for meliponiculture: Trigona species, for example, may incorporate feces or dead animal tissue into nests, raising sanitary concerns (Gómez et al. 2023) Developing markets for stingless bee products requires robust methodologies for authentication and safety. We propose environmental DNA (eDNA) as a tool to address three dimensions of traceability and diversity assessment: Entomological origin of honey. Despite vast bee diversity, taxonomic expertise has declined, limiting our ability to monitor wild bees. DNA-based approaches, particularly metabarcoding, enable verification of the bee taxa involved in honey production—critical in regions with limited expertise. Challenges include primer selection for non- Apis bees, expanding reference databases, and training in molecular methods. Incorporating eDNA and metabarcoding into product traceability could democratize biodiversity monitoring and inform public policy. Botanical foraging spectrum. DNA from bee pollen and honey reveals floral visitation patterns, offering a proxy for ecosystem health. Progress is constrained by incomplete plant reference libraries. Diversity indices—borrowed from microbiome studies—can help characterize floral communities, though interpretation must account for variable foraging behavior across bee species. Microbial diversity and bioprospecting. Stingless bee honeys act as natural “filters,” concentrating microbial communities with industrial, probiotic, or antibiotic potential. Although generally safe, rigorous biosafety evaluation is needed to balance opportunities with risks. Reliable isolation and cultivation methods will be key to characterize diversity, establish reference libraries, and develop pipelines for future bioprospecting. Entomological origin of honey. Despite vast bee diversity, taxonomic expertise has declined, limiting our ability to monitor wild bees. DNA-based approaches, particularly metabarcoding, enable verification of the bee taxa involved in honey production—critical in regions with limited expertise. Challenges include primer selection for non- Apis bees, expanding reference databases, and training in molecular methods. Incorporating eDNA and metabarcoding into product traceability could democratize biodiversity monitoring and inform public policy. Botanical foraging spectrum. DNA from bee pollen and honey reveals floral visitation patterns, offering a proxy for ecosystem health. Progress is constrained by incomplete plant reference libraries. Diversity indices—borrowed from microbiome studies—can help characterize floral communities, though interpretation must account for variable foraging behavior across bee species. Microbial diversity and bioprospecting. Stingless bee honeys act as natural “filters,” concentrating microbial communities with industrial, probiotic, or antibiotic potential. Although generally safe, rigorous biosafety evaluation is needed to balance opportunities with risks. Reliable isolation and cultivation methods will be key to characterize diversity, establish reference libraries, and develop pipelines for future bioprospecting. Our pilot project, in the Magdalena Medio region of Colombia, applies eDNA analyses to bees, honey, pollen, and associated microorganisms. The study focuses on three genera of stingless bees maintained in boxes derived from colonies collected in situ in the El Silencio nature reserve of Fundación Biodiversa Colombia, ensuring foraging in a pesticide-free environment with high floral diversity. As one of the first efforts to apply DNA-based tools to stingless bee biodiversity surveys and product authentication, this initiative highlights the need for stronger collaboration, standardized data frameworks, and investment to unlock the potential of eDNA for conservation and bioeconomic development.

With climate change and accelerating biodiversity decline, lawmakers have been implementing legislation to curtail the negative impact of human actors on further decline. A few noteworthy legal acts are the European Union Deforestation Regulation (EUDR, Reg. EU 2023/1115) in 2023 and the updated European Environmental Crime Directive (ECD, Dir. EU 2024/1203) in 2024. Enforcing these legal instruments requires forensic scientific services able to provide traceable, auditable evidence for provenance, habitat change, and chain-of-custody. Introduction Biodiversity loss represents a systemic risk to human well-being and planetary function; this has been synthesised in the IPBES Global Assessment (IPBES 2019) and earlier conservation science (Soulé 1985. Economic thinking incorporated ecological risk through natural-capital accounting and valuation of ecosystem services (Costanza et al. 1997), which helped motivate legal instruments that translate ecological risk into enforceable rules. The EUDR obliges companies placing forest-risk commodities (FRCs: timber, coffee, cocoa, soy, palm oil, rubber) on the EU market to exercise due diligence to exclude links to deforestation and degradation, while Member States must verify compliance using scientific evidence. Results and operational work Within the Horizon Europe GUARDEN project (https://cordis.europa.eu/project/id/101060693) we developed a decision-support application (DSA) to inform policy choices with biodiversity data. Use of DSAs in regulatory contexts raises forensic questions: who bears responsibility for decisions, how is uncertainty documented, and can DSAs be adapted to produce court-usable artefacts as evidence? Converting digital policy tools into forensic-grade outputs requires provenance capture, immutable audit trails, model-versioning, and explicit uncertainty propagation. Dr. P. Bonnet has contributed significantly to the monitoring of plants through the Pl@ntNet initiative (Lefort et al. 2024). Together with Dr. A. Joly they cary out research to access the uncertainty in biodiversity modelling and emphasise quantifying identification error, observer bias; these metrics define whether species-level inferences reach forensic viability. Model-sensitivity analyses can be inverted to identify minimal sampling density and taxonomic resolution needed to meet legal evidentiary thresholds in priority areas. Dr. Ch. Van Neste established an atomic-elemental laboratory at Meise Botanic Garden to characterise elemental fingerprints of FRCs and build reference baselines in collaboration with Dr. V. Declerck from World Forest ID (Deklerck et al. 2024). The lab was designed with forensic principles: documented Standard Operating Procedures (SOPs), instrument calibration records, and an open-source traceability platform deployed via Infrastructure-as-Code (IaC) to enable reproducible, auditable instances for other labs or corporate due-diligence systems (https://github.com/AgentschapPlantentuinMeise/MeiseCSI). Discussion A recurring concern at Living Data 2025 was incomplete metadata and sampling bias in historical and contemporary biodiversity databases; these omissions produce a “data shadow” of unseen assumptions and missing observations that undermines forensic credibility (Leonelli et al. 2017). Forensic utility demands (1) standardised metadata schemas capturing geolocation with uncertainty, timestamp, collector identity, sampling protocol identifiers, chain-of-custody tags, and Certified Reference Material (CRM) usage; (2) reference baselines (elemental, isotopic, genetic) with documented spatial coverage and measurement uncertainty; (3) accredited lab networks and inter-lab proficiency testing; (4) auditable software (immutable logs, versioned models, IaC); and (5) training for expert witnesses to communicate quantified uncertainty against legal standards of proof. Conclusion This session acted as a call to action. Decision-support tools are necessary but insufficient without forensic design: SOPs, metadata-first capture, uncertainty quantification, accredited analyses, and capacity building for experts and communities. Registering high-quality and comprehensive biodiversity metadata is a minimal requirement to enable enforcement of legal instruments such as the EUDR and the strengthened ECD; the clock is ticking.