In this session, we will bring together scientists and engineers that work on or are interested in eDNA technology and its potential applications in regional to global biodiversity sampling. We will explore how to leverage the growing wealth of eDNA database resources to advance biodiversity research on a broader scale and provide reference information for effective decision-making.
Achieving global biodiversity goals requires assessing, attributing and reversing the ongoing, unprecedented biodiversity decline in aquatic ecosystems, and relies on adequate data to inform policy and action. Analysis of environmental DNA (eDNA) has become established as a novel and powerful approach to assess the state and functioning of aquatic ecosystems, and although increasingly implemented by stakeholders its potential is not yet fully tapped.
In this talk, we review the current state of aquatic eDNA research, focusing in particular on the policy relevance of eDNA and its utility in contributing towards the Global Biodiversity Framework. We first summarize key technological developments in eDNA science to measure organismal diversity and its potential for spatial and temporal upscaling to become a key reference for local to global biodiversity action. We particularly discuss methodological advances in the context of metabarcoding, reference library and species assignment, and the direct calculation of biodiversity and ecosystem state indices. We exemplify the power of the approach with examples on whole-river assessments of biodiversity in Switzerland and Thailand, respectively, particularly demonstrating the method's effectiveness in highly biodiverse, yet understudied regions globally. We also discuss how the focus should be on novel opportunities and not solely on retrofitting biodiversity estimates. Then, we outline the next steps needed to effectively implement eDNA for decision-making and reaching biodiversity targets. We specifically demonstrate the power of linking eDNA with remote sensing analyses to get an integrated understanding of biodiversity across the land-water interface.
Using eDNA to support biodiversity assessment will also benefit the understanding of understudied ecosystems and allow the direct calculation of ecological indices and implementation of FAIR and inclusive data curation. Important next steps for eDNA require proper method standardization and commonly agreed quality standards, populating reference databases, and overcoming methodological constraints in retrofitting novel eDNA-based approaches to existing biodiversity monitoring approaches.
How to cite: Altermatt, F., Couton, M., Carrari, L., Keck, F., Lawson-Handley, L., Leese, F., Zhang, X., Zhang, H., Zhang, Y., and Blackman, R.: Utilising aquatic environmental DNA to address global biodiversity targets, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-314, https://doi.org/10.5194/wbf2026-314, 2026.
Accurate biodiversity indicators are essential to track ecosystem health, detect early signs of degradation, and guide effective conservation policy. Within the EU Water Framework Directive (WFD), ecological indices such as the fish-based Index of Biotic Integrity (IBI) serve as key tools to translate monitoring data into management-relevant scores. However, conventional electrofishing, though well established, faces limitations including restricted spatial coverage, seasonal and detection biases, and increasing ethical concerns. Environmental DNA (eDNA) metabarcoding has emerged as a promising alternative, yet its integration into standardized policy frameworks requires robust validation.
We present the results of a large-scale case study across 59 Flemish lowland river sites, where eDNA metabarcoding was benchmarked against electrofishing. By comparing biodiversity detection, seasonal consistency, and resulting ecological quality ratios (EQRs), we demonstrate that eDNA consistently detects higher species richness, including rare and cryptic taxa overlooked by traditional surveys. At the same time, electrofishing provides unique insights into population structure and recruitment, underscoring the complementarity of both approaches. Importantly, eDNA-derived ecological indices proved highly comparable to abundance-based WFD assessments, and they responded sensitively to habitat pressures across the landscape.
Building on these findings, we outline two pathways for embedding molecular methods into biodiversity policy metrics: (1) recalibration of existing IBI metrics per detection method to ensure methodological fairness, and (2) development of dedicated eDNA-based indices underpinned by standardized quality controls and transparent reporting. Such approaches enable eDNA to significantly upscale monitoring networks in both spatial coverage and temporal resolution, while targeted electrofishing continues to safeguard demographic information critical for management.
This hybrid monitoring framework demonstrates how molecular biodiversity measurements can be translated into robust ecological indicators. Beyond the WFD, the approach offers a blueprint for integrating eDNA into global biodiversity observation systems and emerging legislative frameworks such as the EU Nature Restoration Law. By combining sensitivity, scalability, and policy relevance, eDNA-based indicators can help accelerate biodiversity assessment and support evidence-based decision-making in freshwater conservation.
How to cite: Van Driessche, C., Everts, T., Neyrinck, S., Van Thuyne, G., Lommelen, E., Ruttink, T., Bonte, D., and Brys, R.: From eDNA signals to policy-relevant indices: a large-scale case study integrating molecular biodiversity monitoring into ecological quality assessment of lowland rivers, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-13, https://doi.org/10.5194/wbf2026-13, 2026.
Freshwater biodiversity is declining at a pace that far outstrips the capacity of existing monitoring approaches to provide timely or spatially comprehensive assessments. This mismatch between the speed of ecological change and the resolution of traditional survey methods underscores an urgent need for rapid, scalable, and reliable tools to evaluate biodiversity states and attribute observed changes to environmental drivers. In this context, environmental DNA (eDNA) has emerged as a promising alternative, as it enables broad biodiversity detection with minimal sampling effort. However, despite its potential, global-scale and multi-faceted evaluations remain rare. Here, we present one of the first worldwide assessments and unified analyses of riverine fish biodiversity based on eDNA samples collected from 1,818 sites across 113 major river systems. We quantified four complementary dimensions of biodiversity—species richness, functional redundancy, phylogenetic diversity, and genetic sequence diversity—and examined how each dimension relates to fundamental drainage characteristics and environmental gradients. Our analyses revealed that eDNA not only captured global biogeographic and ecological patterns with remarkable consistency but also enabled us to disentangle the relative contributions of climate and human activities in shaping biodiversity–area relationships. Catchments situated in warmer climates exhibited consistently steeper biodiversity accumulation with increasing area, whereas intensified human activities markedly dampened this scaling effect, pointing toward widespread anthropogenic erosion of freshwater ecosystems. Interestingly, different biodiversity facets displayed distinct sensitivities to human pressures. Species richness, functional diversity, and genetic sequence diversity all showed stronger negative responses to anthropogenic disturbance in larger catchments, suggesting cumulative impacts that amplify across spatial scales. In contrast, phylogenetic diversity experienced its most severe declines in smaller catchments, with the magnitude of these impacts diminishing as catchment size increased. This facet-dependent pattern highlights the complex, non-uniform, and scale-specific nature of biodiversity responses to environmental change. Overall, our findings demonstrate the power of large-scale eDNA datasets for harmonized, multi-dimensional biodiversity assessments. They provide a scalable and integrative pathway for detecting and attributing biodiversity change, ultimately delivering essential insights to inform targeted conservation strategies and guide freshwater ecosystem management under accelerating global environmental change.
How to cite: Zhang, Y., Zhang, H., Zhang, X., and Altermatt, F. and the Global meta-analysis of riverine fish eDNA project: Globally unified analysis of riverine eDNA reveals common associations of fish biodiversity with drainage characteristics, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-122, https://doi.org/10.5194/wbf2026-122, 2026.
Achieving the Kunming-Montreal Global Biodiversity Framework within our oceans requires robust and scalable biodiversity data. Yet, despite the expanding monitoring obligations under both governance and corporate acting spaces, a persistent gap between policy ambitions and monitoring methods still persists. Current methods used to monitor marine biodiversity often produce biased results, with limited spatial, temporal and/or taxonomic coverage as well as inconsistencies across programmes and methodologies that undermine data quality. Addressing these limitations requires new tools capable of generating reliable and comprehensive biodiversity data at scale. Environmental DNA (eDNA) offers a mature and validated approach that complements existing monitoring frameworks, while generating data well-suited for both governance and corporate reporting needs. In this work, we move beyond the debate and explore how eDNA can operationalise biodiversity monitoring obligations across policy levels, focusing on EU fisheries as a case analysis. We map existing governance and corporate reporting frameworks, such as the Common Fisheries Policy, the Marine Strategy Framework Directive, the European Sustainability Reporting Standard E4, or the emerging Taskforce on Nature-related Financial Disclosures requirements, together with their impact metrics and monitoring requirements to illustrate where and how eDNA can enhance compliance and data robustness. In data-deficient contexts, such as for low-value or bycatch species, or companies with extensive operational footprints, eDNA methods can substantially improve biodiversity assessments by providing finer spatial and taxonomic resolution, filling data gaps and allowing for the detection of population trends, range shifts, and changes in the community simultaneously. In the end, we outline actionable steps for integrating eDNA into governance and corporate monitoring systems, such as piloting eDNA projects in policy-relevant contexts, fostering collaborations between academia, governance bodies, and companies, co-developing tools with relevant stakeholders for bioinformatic analysis to ensure usability and impact, or direct efforts towards white papers/policy briefs to support implementation and policy uptake. On another level, involving civil society actors, such as non-governmental organizations or private certification schemes, could further accelerate adoption by advocating for eDNA integration. Integrating eDNA-based monitoring within our oceans governance could bridge the existing data gaps and accelerate our measurable progress toward global biodiversity targets.
How to cite: Silva, M. I., Pinto da Silva, A., Miller, D., S. Paulo, O., Mariani, S., and Vieira, A. R.: Beyond the Debate: Integrating eDNA monitoring into governance and business frameworks, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-407, https://doi.org/10.5194/wbf2026-407, 2026.
The interconnected triple planetary crisis—climate change, biodiversity loss, and pollution—demands systemic, knowledge-driven solutions. This report proposes Ecological Intelligence (EI) as a forward-looking strategic framework to effectively tackle these tightly linked challenges rather than addressing them in isolation. Grounded in the vision of ecological civilization and aligned with the Kunming-Montreal Global Biodiversity Framework, EI seeks to drive a paradigm shift in environmental governance through deep technological integration, harmonizing human development, economic transformation, and nature conservation.
At the heart of EI lies a closed-loop system of “Monitoring-Annotation-Modeling-Decision”. It leverages disruptive technologies such as environmental DNA (eDNA) for dynamic, non-invasive biomonitoring, providing high-resolution, near real-time insights into ecosystem health and ecological processes. Furthermore, by integrating artificial intelligence with multi-source data from satellite remote sensing, in situ sensor networks, citizen science, and traditional field surveys, EI enhances causal modeling, pattern recognition, and predictive capabilities. This supports precise, adaptive management decisions for issues such as pollution source tracing, harmful algal bloom forecasting, invasive species surveillance, and ecological restoration planning, thereby shifting governance from fragmented, passive response to anticipatory, proactive foresight.
Looking ahead, initiatives like a proposed “Global Major Rivers eDNA Observation Network” exemplify the transition from static, one-off assessment to continuous, automated environmental monitoring at basin to planetary scales. Their success depends on early, collaborative engagement from governments, scientists, local communities, Indigenous Peoples, and the private sector, as well as robust data-sharing mechanisms, ethical safeguards, and capacity-building efforts in the Global South.
In conclusion, Ecological Intelligence offers an integrated, action-oriented approach to the global environmental crisis by converging cutting-edge technologies like eDNA, AI, and sensor networks within an inclusive governance framework. Through strategic collaboration and sustained investment, it holds strong promise for contributing to the global vision of “halting and reversing biodiversity loss by 2030” and advancing a climate-resilient, equitable, sustainable, and thriving future for all.
How to cite: Zhang, X. and Zhang, Y.: Ecological Intelligence: An Integrated Pathway to Address the Triple Planetary Crisis, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-569, https://doi.org/10.5194/wbf2026-569, 2026.
Life in the sea provides immense benefits to humans, from the food we eat, to the air we breathe, to the climate we live in. And because of human activities, the once seemingly vast and inexhaustible seas are changing – they are increasingly threatened by impacts on a global scale, such as warming and acidification, as well as those that are more localized like overfishing and pollution. Many of the species that live in the sea, meanwhile, are still unknown. Even for the known species, our understanding of their roles in the ecosystem is still limited. Now more than ever, increased observation of life in the sea is required to find and describe unknown species, observe shifts in species abundance and distribution, identify adaptability and resilience to climate change, and understand vital roles that species play in our marine systems. New and emerging technologies promise to enable observation over the required temporal and spatial scales. And emerging data systems will allow development of critical ecological understanding, while informing responsible use of marine natural resources. Environmental DNA is an emerging technology that eventually may be used to scale observations of biodiversity to similar time and space scales as those for ocean physics. Here we report on using environmental DNA to observe life in the California Current though a broad partnership with observing programs that span the region from the Mexico to the Oregon California borders. This joint partnership is supported by funding provided by the US Marine Biodiversity Observation Network (MBON) program. Biological productivity in the California Current is driven by seasonal upwelling that is perturbed on interannual to multidecadal time scales. Observations made to date capture these seasonal to multidecadal variations in marine biodiversity across multiple trophic levels. The observations also pick up harmful algal blooms and the presence /absence of endangered/invasive species.
How to cite: Chavez, F., Pitz, K., Baker, J., Truelove, K., Blum, M., and Messie, M.: Observing life in the California Current using environmental DNA: Links to remote sensing, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-420, https://doi.org/10.5194/wbf2026-420, 2026.
Effective biodiversity policy depends on precise, high-volume data to characterise, monitor, and protect natural capital. Genomic technologies, along with taxonomic expertise, offer the resolution and scalability required to meet these legislative and management needs, with DNA barcoding enabling rapid species identification and whole-genome sequencing allowing for comprehensive assessment of genetic diversity. While these tools hold great promise for routine monitoring, their integration into policy frameworks has been limited..
The Biodiversity Genomics Europe (BGE) project was established in 2022 to accelerate the deployment of an integrated framework of genomic and taxonomic expertise. Through close collaboration among iBoL Europe, ERGA and CETAF networks, the initiative has connected distributed communities of taxonomists and genomic researchers. This cooperation has aligned European scientific output with global initiatives such as the International Barcode of Life and the Earth BioGenome Project, fostering a unified community of practice across the continent.
Significant obstacles, however, currently hinder widespread adoption. Divergent sampling strategies, wet-lab protocols, and data curation practices fragment the landscape and reduce interoperability. A particularly prominent challenge is the lack of comprehensive and standardised reference libraries for barcodes and genomes. As long as these baselines remain incomplete, genomic data cannot be interpreted with the confidence required for decision-making.
The BGE initiative addresses these issues by proposing to shift from simple European-wide coordination to a structural consolidation model. We argue for the need for a European research infrastructure to supply the services, tools, and standards needed to scale up operations. By organising a coordinated and inclusive system for knowledge production and application, we aim to muster the unique value of research groups, laboratory facilities and innovation hubs to reliably sustain the provision of high-quality biodiversity data necessary for evidence-based policy. In this talk, we summarise the work already carried out in the context of the BGE project and outline the steps ahead to raise the readiness levels of actors and stakeholders toward a distributed research infrastructure for biodiversity genomics and a genomically enabled biota in Europe.
How to cite: Koureas, D., Casino, A., Waterhouse, R., Ciofi, C., Hollingsworth, P., Lawniczak, M., Mazzoni, C., Alonso, J., and Dankova, G.: Scaling up Biodiversity Genomics in Europe: From Fragmented Efforts to a Unified Infrastructure, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-724, https://doi.org/10.5194/wbf2026-724, 2026.
Ongoing research and development projects worldwide aim to build capacity towards implementing eDNA and other molecular methods (e.g. single species assays, eDNA / DNA metabarcoding, metagenomics) in routine biodiversity monitoring, either for the monitoring of species of conservation interest or the status of habitats and ecosystems based on their community composition. We synthesize recent mappings of the biodiversity policy landscape (with emphasis on EU policies), gap analyses of existing biodiversity monitoring programs and reviews of the technological readiness of molecular monitoring methods to identify DNA-based possibilities for biodiversity monitoring in policy implementation.
Our preliminary results indicate that gaps that could be targeted by molecular methods include more comprehensive monitoring of arthropods and other invertebrates, fungi and lichens as well as applying molecular community monitoring to assess the structure and functions of ecosystems. For freshwater systems, zooplankton is among the most important poorly known taxa. Small lakes, streams and springs are the most important poorly known habitats.
Molecular data would be well suited for increasing the taxonomic and spatial coverage of in situ monitoring data to support and complement remote sensing -based modelling, assessing short-term temporal trends and revealing pressures and threats behind biodiversity patterns and trends. Our results shows that the majority of molecular methods have yet to reach the highest levels of technological readiness. However, in many cases the bottleneck for upscaling are not technological shortcomings but rather the fragmentation of the field and lack of joint collaborative effort towards widely shared best practices and international standards in this fast-developing field.
At the same time, biodiversity loss is accelerating, and more comprehensive, internationally compatible biodiversity data is urgently needed for timely decision making and for monitoring the impact conservation and restoration actions. We conclude that while further research and development of methodology is needed, the pressing knowledge needs of biodiversity policies motivate launching large-scale molecular monitoring programs sooner rather than later. This could help improve the likelihood that the ambitious targets set up by policies are reached. Further, we stress that international cooperation and standards are key to avoid unnecessary plurality of methods and incompatible results.
How to cite: Laamanen, T., Meissner, K., Snåre, H., Sirkiä, P., Ahola, A., Tanhuanpää, T., Kujala, K., Siegenthaler, A., Vihervaara, P., and Norros, V.: Standardized molecular methods in biodiversity monitoring for the implementation of international policies, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-798, https://doi.org/10.5194/wbf2026-798, 2026.
Biodiversity is declining globally, yet our ability to monitor these changes remains limited by methods that are labor-intensive, taxonomically narrow, and slow to detect emerging shifts. Environmental DNA (eDNA) has become a powerful tool in aquatic ecosystems, but its use on land remains constrained by the difficulty of collecting representative and integrated samples.
Airborne eDNA offers a promising solution. Air carries biological material from organisms across the tree of life and can be sampled anywhere using simple, robust devices. Because airborne eDNA can be collected autonomously and at high frequency, it enables biodiversity assessment at scales and resolutions that traditional approaches cannot achieve. This opens the possibility of measuring the Earth’s biological layer much as we measure the physical atmosphere today—using networks of ground-based “satellites” that continuously sense airborne biological signals and support models with the mechanistic understanding and predictive power of today’s weather and climate models.
At DNAir, we are developing the methods and technology to realise this vision. Our goal is to unlock airborne biological information as a new stream of global biological intelligence, with applications in biodiversity monitoring, agriculture, and human health. By combining autonomous air sampling with standardized laboratory and bioinformatic workflows, we aim to generate frequent and comparable biodiversity signals across sites, seasons, and ecosystems.
In this presentation, I will share early results from pilot studies demonstrating the potential of airborne eDNA in diverse environments -from multi-taxon monitoring campaigns in Switzerland and France, where airborne eDNA captures plants, fungi, insects, and vertebrates simultaneously to vertebrate surveys in eastern Africa and tests of airborne eDNA sampling for coastal marine monitoring in the North Sea. I will also outline our assessment for where airborne eDNA stands today and discuss key scientific and practical challenges on the path ahead.
How to cite: Roger, F.: Airborne eDNA as a Frontier for Scalable, Automated, Multi-Taxon Biodiversity Monitoring, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-855, https://doi.org/10.5194/wbf2026-855, 2026.
Environmental DNA (eDNA) has rapidly become a powerful method for large-scale biodiversity assessment and monitoring. Yet the reliability of eDNA data depends on high-quality reference material that can verify detections, resolve taxonomic uncertainty, and correct spatial or temporal biases. This is where global natural science collections, curated in natural history museums, herbaria, and other collection-holding institutes, play an essential role. These collections preserve centuries of information on species, traits, and ecological contexts, providing the authoritative baseline needed to interpret molecular observations and understand biodiversity change over time.
Harnessing this potential requires that collection data be open, reusable, and integrated with emerging molecular approaches. Advances in imaging, computational methods, and molecular analysis have made it possible to link specimen-based knowledge with large-scale datasets. To support such integrated, data-driven research and adaptive conservation strategies, robust infrastructure is needed.
The Distributed System of Scientific Collections (DiSSCo) – a European Research Infrastructure collaborating with more than 300 institutions across 23 countries – addresses this challenge by representing each specimen as a FAIR (Findable, Accessible, Interoperable, and Reusable) Digital Object. Building on existing standards, each specimen and its associated data are made FAIR, with provenance and trust explicitly encoded. Users can explore connections across data types and contribute annotations, corrections, or additional information, with AI-assisted services such as automated georeferencing, OCR, and morphology detection further enhancing data quality and completeness.
Such linked and verified data provide the critical bridge between historical collections and modern eDNA workflows. Digital specimens data ground eDNA detections in validated reference material, strengthening taxonomic resolution and enabling more accurate interpretation of biodiversity patterns across spatial and temporal scales. Sequencing historical specimens enriches this further by revealing long-term population and ecosystem dynamics.
By establishing an infrastructure capable of linking billions of historical specimen records with emerging molecular and environmental data, DiSSCo creates the conditions for future integration that will support predictive biodiversity assessments and global eDNA efforts.
How to cite: Islam, S.: Futures of Biodiversity Monitoring: Linking eDNA with high-quality reference materials, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-924, https://doi.org/10.5194/wbf2026-924, 2026.
Environmental DNA (eDNA) metabarcoding offers a sensitive, non‑invasive alternative to conventional biomonitoring, yet its integration with predictive modelling remains underexplored. This study combines eDNA datasets collected during an ADB‑funded Strategic Environmental and Social Assessment (2024-2025) with supervised machine learning (ML) to evaluate ecological condition across eight rivers on Guadalcanal, Solomon Islands.
eDNA samples from 47 sites identified 861 taxa at species level, spanning native forest species, disturbance‑tolerant fishes, invasive plants and animals, and microbial indicators of pollution. Classifiers (decision tree, logistic regression, random forest, eXtreme gradient boosting) were trained on species profiles contextualised by land‑use intensity and buffer zone scales (100–1000 m). Stratified 5-fold cross-validation and permutation testing ensured robust evaluation. Random forest performed best, achieving AUCs up to 0.94 ± 0.04 (p < 0.001) and accuracy of 0.83 ± 0.05 at the 1000 m buffer, with significant AUCs (p < 0.05) across six additional model configurations. Broader buffers improved classification by integrating cumulative landscape disturbances such as logging, agriculture, and urban runoff.
Feature‑importance and SHAP analyses identified ecologically coherent predictors. Sentinel gobies (Sicyopterus stiphodonoides, Rhyacichthys guilberti) and native forest taxa (Fagraea berteroana, Nephrolepis biserrata) were indicative of reference conditions, while disturbance‑tolerant fishes (Giuris margaritaceus, Crenimugil cf. heterocheilos), invasive species (Rhinella marina, Lissachatina fulica, Megathyrsus maximus), and cultivated plants (Oryza sativa) signalled impacted sites. Some taxa showed context‑dependent behaviour: Intsia bijuga predicted both impact and reference depending on scale, reflecting its dual role as a native forest tree and a species under logging pressure, while Areca catechu shifted from reference at broader scales to impact at smaller ones, consistent with cultural cultivation and naturalisation. Unexpected detections (Piper methysticum, Diplarpea paleacea, Conium maculatum, Phyllanthus talbotii) highlight both the potential for novel biogeographic insights and the need for expanded eDNA reference libraries.
Our findings demonstrate that eDNA‑ML frameworks capture spatially coherent disturbance classifications with greater taxonomic resolution than conventional bioassessment. This approach provides a scalable, data-driven basis for freshwater management, enabling agencies to prioritise restoration, delineate scientifically defensible buffer zones, and monitor ecosystem change where field capacity is limited. The findings underscore the transformative potential of eDNA-ML integration for evidence-based river management and policy development in tropical island nations.
How to cite: Annandale, D., Steel Pascual, L., Fehling, M., Annandale, D., and Ricciardi, F.: Decoding Ecological Condition in Solomon Island Rivers with eDNA and Machine Learning, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-202, https://doi.org/10.5194/wbf2026-202, 2026.
Microbial communities are central to forest ecosystem functioning, acting as key drivers of ecosystem health, structure, and sustainability. Once largely overlooked, these communities are now increasingly incorporated into biodiversity assessments, driven by advances in environmental DNA (eDNA) techniques that enable monitoring of this previously invisible world. However, large-scale assessments of these communities remain limited as they require extensive sampling efforts to generate data with sufficient spatial coverage and resolution. To overcome this limitation, rapid advances in remote sensing technologies, combined with in-situ data and machine learning, are transforming biodiversity science by enabling consistent monitoring of ecosystem features from local to global scales. Here, we present a novel approach to modelling microbial diversity by coupling image spectroscopy data with eDNA profiling using machine learning models such as Gaussian Process Regression and Partial Least Squares Regression. By integrating point-based in-situ eDNA metabarcoding data (including open-access datasets) with Earth Observation data, we demonstrate that microbiome biodiversity can be reliably modelled, mapped, and evaluated across diverse ecosystems and spatial scales in European temperate forests. Our results show that hyperspectral remote sensing effectively captures habitat features that shape microbial diversity, including belowground communities. Additionally, we revealed that microbiological community structure signals underlying ecological relationships in temperate forests in Europe. Our methods enable scalable biodiversity and ecosystem monitoring and supporting research across broader taxonomic and spatial scales. By integrating the strengths of these state-of-the-art research fields, we can gain deeper insights into the spatial dynamics of microbial communities and their drivers of change. Due to the key role of microbial communities in ecosystem functioning, this interdisciplinary approach also opens new opportunities for predictive ecosystem monitoring and early detection of environmental degradation. By providing a scalable framework that enhances the integration of local observations within large-area assessments, this study supports more informed conservation and land management strategies to achieve regional and global biodiversity conservation targets.
How to cite: Siegenthaler, A., Abdullah, H., Skidmore, A., and Martinez, M.: Utilising Remote Sensing Technologies to Upscale Microbial Environmental DNA Point Data for Large Scale Biodiversity Assessment, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-174, https://doi.org/10.5194/wbf2026-174, 2026.
The Kunming-Montreal Global Biodiversity Framework (KMGBF) Targets 4 and 13 place genetic diversity and Digital Sequence Information (DSI) benefit-sharing at the center of implementation. However, DSI-related datasets and indicators remain biased toward a narrow set of well-studied taxa; those are crops and model species. Parasitic plants exemplify this imbalance: abundant genomic resources are available for a few agronomic pests—Cuscuta, Striga, and Orobanche/Phelipanche spp.—yet most parasitic lineages are among the least represented angiosperm groups in public DSI and are absent from GBF implementation guidance and case studies. Closing DSI gaps for threatened parasitic plants is a recognition of the need for GBF implementation, not merely a research gap.
Threatened parasitic plants meet IUCN risk profiles driven by restricted ranges, fragmentation, and host dependence (Criterion B; Cytinus hypocistis, Orobanche pancicii, Sapria himalayana) and/or very small populations (Criterion D; Hydnora triceps, Rafflesia philippensis, Pilostyles thurberi), which are often assessed as endangered or critically endangered. Nonetheless, many parasitic taxa lack reference genomes, population genomic surveys, and openly accessible DSI, and some remain unevaluated on the IUCN Red List. This disparity undermines conservation assessment and genetic monitoring, obscuring cryptic diversity. It also hampers sequence-based identification in some parasites with highly reduced vegetative structures that are often distinguishable only from flowers. Broadly, conservation genomics remains underused for threatened plants. Moreover, parasite-focused sequencing, barcoding, and dedicated genomic initiatives are still limited.
As a way forward, we outline priority actions to align biodiversity conservation with responsible ABS-consistent open DSI for parasitic taxa: (i) minimally invasive sequencing of threatened parasites and host–symbiont networks, linked to validated vouchers; (ii) use of herbarium and historical material with provenance metadata to fill spatial and temporal gaps; and (iii) deposition of sequences in open repositories with transparent access conditions and ABS-relevant metadata, alongside targeted capacity building in biodiversity hotspots to support just and effective implementation.
In summary, we call for the GBF process to address genomic inequities as a practical implementation gap and to enable responsible, ABS-consistent open DSI for threatened parasitic plants, translating current blind spots into actionable knowledge for conservation and sustainable use.
How to cite: Acar, P., Kim, W., Jost, M., and Wanke, S.: Blind Spots in KMGBF Implementation: Threatened Parasitic Plants Missing from DSI Evidence, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-849, https://doi.org/10.5194/wbf2026-849, 2026.
Home for thousands of species, coral reefs are one of the most productive and diverse ecosystems in the world. These habitats provide services and resources to human populations, including coastal protection, tourism, pharmacology, and seafood. However, urbanization can decrease marine genetic diversity and ecological functions. Examples of measures of anthropogenic impacts on reefs include distance from heavily populated areas or from treated wastewater input, significant fishing pressure, and coastal development (e.g., reclaimed land, road construction, artificial reefs, or dredging). Thus, it is crucial to evaluate and monitor changes in coral reef communities under distinct impact levels. A major challenge for researchers has been in quantifying diversity; traditional methods such as visual census, photoquadrats, or collection of tissues have several constraints. A very recent and revolutionary tool is environmental DNA (eDNA). For example, DNA filtered from seawater is accurate in detecting local biodiversity without the need to capture or directly observe organisms. However, eDNA surveys at large geographical scales are still missing. In this study, we used eDNA to address how urbanization affects coral reef biodiversity. Our global sampling surveys included relatively pristine to more densely populated sites, including regions of Brazil, Hawai‘i, Hong Kong, Niue, Okinawa, and Palmyra Atoll. At each location, we sampled and filtered seawater from several coral reefs. Using multiple metabarcoding markers, we characterize the diversity of microbes, invertebrates, and reef fishes. We then analyze the dissimilarity of genetic diversity and functional groups between regions and sites. Additionally, using an extensive literature review, we compile population and environmental data for these sites and build urbanization indices. We use coefficient models to evaluate the influence of urbanization levels on the biodiversity metrics. Together with collaborators from the local communities and governmental and non-governmental organizations, we aim to evaluate how eDNA surveys can support the monitoring and management of reef ecosystems.
How to cite: Santos, M. E. A., Walsh, C. A. J. W., Timmers, M. A., Viehl, K., Angulo, C., Hoban, M., Tramonte, C., Toonen, R. J., and Bowen, B. W.: Reef biodiversity and urbanization, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-827, https://doi.org/10.5194/wbf2026-827, 2026.
Globally biodiversity loss is accelerating. The agricultural sector is one of the main contributors to this biodiversity loss occupying about half of the world's habitable land area, thereby replacing natural ecosystems with human-controlled environments that can poorly support the same level of diversity. Agroecological farming systems (e.g. regenerative farming) have been promoted to support a higher level of biodiversity than conventional farming systems can. Yet, life cycle impact assessment (LCIA) methods, that are often used to quantify the biodiversity impacts of agricultural products, cannot or poorly distinguish between the biodiversity impacts caused by conventional systems versus agroecological farming systems. This can lead to poor research conclusions and thus highlights the inability of these methods to support informed decision-making when it comes to transforming the agricultural sector.
In our research we propose to enhance currently available biodiversity-focused LCIA methods by taking advantage of the latest developments in environmental DNA (eDNA). In our approach we elaborate on steps that are required to measure species richness as an indicator of biodiversity levels on-site using eDNA and how to utilize the results to enhance four of the most widely used LCIA methods (GLAM 3, LC-IMPACT, ReCiPe, and Impact World+), thus improving the biodiversity impact estimates of different agricultural farming systems using empirical data.
We applied our new approach to a case study of regenerative farming in Finland as a proof on concept using eDNA data on fungal diversity. Our case study showed the advantages of using eDNA not only by giving more accurate assessments on this previously unrepresented farming system but also by illustrating the possibility of including soil-dwelling organisms that are crucial to agricultural ecosystems but were previously ignored in LCIA methods. Although we focused solely on fungi for illustrative purposes, using eDNA would allow for the inclusion of many taxonomic groups from a single sample without the high level of expertise required in traditional species identification methods.
How to cite: Järviö, N., Uusitalo, V., and Ekroos, J.: Enhancing current Life Cycle Biodiversity Impact Assessment Methods across Farming Systems through Environmental DNA Analysis – a Proof of Concept, World Biodiversity Forum 2026, Davos, Switzerland, 14–19 Jun 2026, WBF2026-940, https://doi.org/10.5194/wbf2026-940, 2026.
