Guide to use public biodiversity data in the private sector

Guide to using public biodiversity data in the private sector On accelerating private sector use of public biodiversityand nature-related data to measure, report, and act on biodiversity EUROPEAN PARTNERSHIP Co-funded by the European Union 2 To cite this report Bakker, Elisabeth and Teske, Donna (2025). Guide to use public biodiversity data in the private sector. Biodiversa+ report. 88 pp. https://doi.org/10.5281/ zenodo.16967410 With sincere thanks to: Koos Biesmeijer (Naturalis Biodiversity Center), Niels Raes (Naturalis Biodiversity Center) Sarah Nelson (KPMG International), Carlijn van Dam (KPMG International), Arnoud Walrecht (KPMG NL), Faiza Oulahsen (KPMG NL), Wouter Huurman (KPMG NL) Senem Onen Tarantini, MUR; Cécile Mandon, FRB; Iiris Kallajoki, MoE_FI; Romie Goedicke, UNEP FI; Jérémy Carrasco ENEDIS Ron Winkler, NWO; Gaia Felber, HUB Ocean; Alex Ross UNEP-WCMC; Guillaume Body, OFB; Larissa Leitch, Shell; Jorn Dallinga, WWF; Asger Strange Olesen, IWC Asset Management; Lara Brandes, IWC Asset Management; Martine van de Laar, Philips; Roberto Barrantes Guerrero, Philips; Luc Hoogenstein, Eneco; Blanche de Biolley, TNFD; Cathrine Armour, TNFD; Robert-Alexandre Poujade (Biodiversity lead), BNP Paribas Asset Management; Jaclyn Aliperti, DLL Group; Kyle Copas, GBIF: the Global Biodiversity Information Facility; Daan Reith, Heijmans N.V.; Harwil de Jonge, Heijmans N.V.; Gavin Edwards, Nature Positive Initiative Secretariat; Emma Marsden, Nature Positive Initiative Secretariat; Gilad Goren, Nature Tech Collective; Jen Stebbing, Nature4Climate; Lucy Almond, Nature4Climate; Nissui Corporation; Cat Hemmingsen (Senior Biodiversity Advisor), Ørsted; Felix Beckebanze, RaboResearch – Rabobank; Bob Douma, RaboResearch – Rabobank; Pjotr Tjallema (Sustainability researcher), Triodos Bank; Angela Graham-Brown, WBCSD; Branden Beatty, West Fraser; Laura Trout, West Fraser; Nathalie Houtman, WWF-NL; Natalie Rothausen (Group Lead Biodiversity), RWE Disclaimer Co-funded by the European Union, under Grant Agreement 101052342. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. Picture credits p.53; 61 figure and picture shared by Philips © Pixabay Layout Thibaut Lochu To contact Biodiversa+ [email protected] Website www.biodiversa.eu Follow us @Biodiversa.eu @BiodiversaPlus 3 What is Biodiversa+ The European Biodiversity Partnership, Biodiversa+, supports excellent research on biodiversity with an impact for policy and society. Connecting science, policy and practise for transformative change, Biodiversa+ is part of the European Biodiversity Strategy for 2030 that aims to put Europe’s biodiversity on a path to recovery by 2030. Co-funded by the European Commission, Biodiversa+ gathers 81 partners from research funding, programming and environmental policy actors in 40 countries to work on 5 main objectives: 1. Plan and support research and innovation on biodiversity through a shared strategy, annual joint calls for research projects and capacity building activities 2. Set up a network of harmonised schemes to improve monitoring of biodiversity and ecosystem services across Europe 3. Contribute to high-end knowledge for deploying Nature-based Solutions and valuation of biodiversity in the private sector 4. Ensure efficient science-based support for policy-making and implementation in Europe 5. Strengthen the relevance and impact of pan-European research on biodiversity in a global context More information at: https://www.biodiversa.eu/ 4 List of abbreviations BII - Biodiversity Intactness Index CSRD - Corporate Sustainability Reporting Directive CSDDD - Corporate Sustainability Due Diligence Directive ENCORE tool - Exploring Natural Capital Opportunities, Risks and Exposure tool ESRS - European Sustainability Reporting Standards EUDR - Regulation on Deforestation-free Products GBF - (Kunming-Montreal) Global Biodiversity Framework GBIF - Global Biodiversity Information Facility GFW - Global Forest Watch GRI - Global Reporting Initiative IBAT - Integrated Biodiversity Assessment Tool IPBES - Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services IUCN - International Union for Conservation of Nature KBA - Key Biodiversity Areas LEAP - Locate Evaluate Assess Prepare NBSAP - National Biodiversity Strategy and Action Plan OBIS - Ocean Biodiversity Information System PBAF - Partnership for Biodiversity Accounting Financials PDF - Potentially Disappeared Fraction SBTN - Science Based Targets Network TNFD - Taskforce for Nature-related Financial Disclosures WBCSD - World Business Council for Sustainable Development WDPA - World Database on Protected Areas 5 Table of contents Foreword 6 Executive summary 7 1. Introduction 8 2. Key concepts: What is biodiversity and why does it matter for a private company? 12 3. Who to contact and where to find & access biodiversity data? 24 4. What are the challenges and solutions in using public biodiversity & nature data? 30 5. How to use public biodiversity and nature-related data in practice? 48 6. Conclusion: unlocking the potential of public biodiversityand nature-related data 66 Bibliography 70 Glossary 74 Appendix I – Challenges identified in interviews and workshops explained in detail 79 Appendix II – Table with responses per data actor. 83 6 Foreword 1. The vision of the GBF is a world of living in harmony with nature where “by 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people.” The mission of the Framework for the period up to 2030, towards the 2050 vision is: To take urgent action to halt and reverse biodiversity loss to put nature on a path to recovery for the benefit of people and planet by conserving and sustainably using biodiversity and by ensuring the fair and equitable sharing of benefits from the use of genetic resources, while providing the necessary means of implementation. Link to source: https://www.cbd.int/gbf/vision Biodiversity, and more broadly nature, is the foundation of our economy and society (Stockholm Resilience Centre, 2016). Over half of the global GDP depends moderately to highly on ecosystem services such as pollination, food production, water purification, and climate regulation (World Economic Forum & PwC, 2020). Furthermore, virtually all economic activities ultimately depend on healthy and functioning ecosystems (Stockholm Resilience Centre, 2016). Biodiversity loss is ranked among the top three global risks over the next decade by the World Economic Forum (2025) and is also widely recognised as one of the most urgent threats to economic resilience, public health, and financial stability by other authoritative sources (e.g., IPBES, 2019; United Nations Environment Programme, 2024). In response, governments worldwide have adopted the Kunming-Montreal Global Biodiversity Framework (GBF), a landmark agreement to halt and reverse biodiversity loss by 2030 and with a vision of a world living in harmony with nature by 20501. Delivering on these commitments requires not only ambition, but also action. Businesses will play a critical role in achieving the GBF’s goals and targets. To do so, they need reliable and accessible biodiversity and nature data to assess risks, comply with regulations, and develop action plans that support organisational, national, regional, and global goals. A common constraint voiced by businesses is that there is ‘no biodiversityrelated data’. In reality, a lot of data exists, but what is often lacking is decision-useful data and comparability between datasets. This report aims to help close this gap by providing an overview of the current state of public biodiversityand nature-related data, identifying challenges, sharing practical examples, and offering guidance on how such data can be used to drive action and support biodiversityand nature-positive outcomes. The shift is already visible. In the 18 months since the release of the TNFD recommendations, more than 733 organisations (representing over USD 22.4 trillion in assets under management), have committed to starting to report on their nature-related issues (TNFD, n.d. a). This illustrates the growing private-sector engagement with nature-related data and accountability. It’s also in line with Target 15 of the GBF, which calls on governments to ensure that large businesses and financial institutions assess, disclose and reduce their risks, dependencies, and impacts on biodiversity (Secretariat of the Convention on Biological Diversity, n.d.). Achieving the GBF goals requires a whole-of-society approach, with the accelerated use of public natureand biodiversity-related data being one of the pieces of the puzzle. 7 Executive summary Biodiversity, and more broadly nature, is the foundation of our economy and society (Stockholm Resilience Centre, 2016). Yet businesses and financial institutions still struggle to integrate biodiversity considerations into decisions. One major barrier is the limited and uneven use of public biodiversityand nature-related data, despite its availability and relevance. Purpose and scope This report aims to guide companies and financial institutions in making more effective use of existing public datasets to inform biodiversity assessments, disclosures, and strategies. It identifies core challenges, highlights practical examples, and provides recommendations for different actor groups. The focus is on publicly available data produced outside companies and financial institutions themselves, primarily by public organisations and the scientific community, while acknowledging that meaningful action also depends on internal data on operations and supply chains. Core challenges The analysis finds that while biodiversityand naturerelated data is abundant, it remains underused. Core challenges include: }Gaps in quality, resolution, and comparability of existing datasets. }Fragmentation across platforms, tools, and standards, which hinders usability. }Limited clarity around licensing, data lineage, and appropriate applications. }Uncertainty over when public data is sufficient versus when new site-level data is needed. }Limited ecological literacy and organisational capacity within private sector organisations to interpret and apply biodiversity insights. These barriers are not only technical but also social: many stems from siloed responsibilities, limited confidence, or lack of shared understanding across teams. Recommendations The report shows that while challenges remain, the private sector is already finding ways to use and adapt public datasets in practice. Key messages include: }The private sector cannot wait for “perfect data.” They need to begin working with what is already available, building familiarity and internal capability. }Systemic support is needed to improve the quality, accessibility, and long-term sustainability of public biodiversity datasets. }Barriers are as much social as technical. Building capacity, aligning teams, and fostering a shared vocabulary are essential. }Collaboration is critical. Progress depends on joint efforts between the private sector, governments, research institutions, and civil society. }Financing biodiversity data is a shared responsibility. While most datasets are publicly funded, maintaining and updating them requires ongoing support, where the private sector also has a role to play. }Progress is already underway. New initiatives, collaborative platforms, and tool developments are emerging to make biodiversityand nature-related data more actionable. Moving forward Improving the use of public biodiversityand naturerelated data depends on two mutually reinforcing developments: 1. The private sector needs to start working with the data already available, even if imperfect, to build internal familiarity and demand. 2. Continued support, including financial support, is needed for the broader ecosystem of actors improving the quality, accessibility, and relevance of that data. Both sides of this equation are essential. Without corporate demand, there is limited incentive to improve public datasets. Without improved access and usability, the private sector may struggle to act effectively on their biodiversityand nature-related risks and opportunities. 8 1 Introduction 9 16 Use of terms in this guidance This guidance focuses primarily on biodiversity-related data, reflecting the terminology used in the Kunming– Montreal Global Biodiversity Framework (GBF), which sets global targets to halt and reverse biodiversity loss (Secretariat of the Convention on Biological Diversity, 2011). Although nature as a concept already encompasses biodiversity, the combined term “natureand biodiversityrelated data” is used in this guidance to clearly put the emphasis on integration of biodiversity data. Corporate decision-making often requires information beyond the biodiversity state alone, such as data on environmental pressures, ecosystem functions, or abiotic components like soil, water, and climate variables. In line with definitions used in science and policy, this guidance applies: }Biodiversity-related data when referring specifically to data on ecosystems, species or genes (e.g., species occurrence) }Natureand biodiversity-related data covers both biodiversity-related data (as seen above) as well as wider data on the state of nature and the pressures acting upon it (e.g., data on air, soil, water, land-use change, or pollution). While the definition of ‘nature data’ inherently encompasses biodiversity, we use the term ‘natureand biodiversity-related data’ in this report to enhance clarity and specifically reinforce the integration of biodiversity in corporate and financial contexts. Where a specific framework (e.g. TNFD, SBTN) or initiative is discussed (e.g., Nature Positive Initiative), the terminology follows that frameworks or initiative’s usage. This approach ensures precision while acknowledging differences in emphasis between science, policy, and private sector contexts. Dependencies and impacts Private sector organisations are linked to nature and biodiversity in two main ways: through what they depend on, and what they affect. Figure 3: Overview of the different types of ecosystem services that the private sector relies on (Egmond & Ruijs, 2016). }Dependencies refer to the natural systems or ecosystem services a company relies on. For example, agriculture depends on healthy soils, freshwater, and pollinators. Manufacturing may depend on stable water supply or protection from floods. These dependencies create risks if ecosystems degrade or their functions decline (Adapted from SBTN, 2023 & TNFD, 2025). 17 Figure 4: Overview of the main impact drivers of human activities causing biodiversity loss (IPBES, 2019). }Impacts occur when business activities lead to changes in nature, such as land conversion, emissions, or (over) extraction of natural resources. Impacts can be negative or positive, direct or indirect. Over time, they can reduce the very services private sector organisations depend on, and affect communities, other sectors, and nature itself (SBTN, 2023; Climate Disclosure Standards Board, 2021; Impact Management Platform, 2023; TNFD, 2025) 18 Risks and opportunities Biodiversityand nature-related dependencies and impacts translate into financial risks for businesses, such as operational disruptions, increased costs, or regulatory penalties when ecosystems degrade, or ecosystem services become less reliable. Conversely, understanding and managing these connections can create opportunities for cost savings, innovation, and competitive advantage, for instance through sustainable sourcing, naturepositive product development, or access to green finance. The ability to identify, measure, and disclose these risks and opportunities is crucial for robust business decisionmaking and resilience (SBTN, 2023; Climate Disclosure Standards Board, 2021; Impact Management Platform, 2023; TNFD, 2025). Understanding where and how a company depends on biodiversity and nature, and where it causes change, is essential for assessing risks, action planning, and using biodiversityand nature-related data effectively. Source:Guidance_on_the_identification_and_assessment_of_nature-r ela ted _Issues_The_TNFD_LEAP _appro ach _V 1.1 _Oct ob er20 23.pd f Figure 5: Connections between nature-related dependencies, impacts and risks and opportunities – Impact and dependency pathways (building on TNFD, 2023). Pathways of interaction Dependencies and impacts often follow specific chains of cause and effect. For example: }Clearing land for development may lead to habitat loss, species decline, and reduced pollination and water infiltration for nearby agriculture. }A business dependent on groundwater may face rising costs or operational disruption if local water tables fall due to climate shifts, land clearing and water run-off or overuse. These kinds of interactions, often referred to as pathways, help identify 1) impact drivers and external factors, 2) changes to the state of nature and 3) changes to the availability of ecosystem services. As such, they clarify how changes in biodiversity may affect the businesses (dependency pathway) and how, as a result of a business activity, an impact driver may impact biodiversity (impact pathway) (Natural Capital Coalition, 2016; see further definition of impact pathway from Impact Management Platform (2023); TNFD, 2025). 19 2.2 What are the global biodiversity policies and frameworks? In recent years, biodiversity loss has moved higher on the policy agenda, not only as an environmental concern, but as a material business and financial risk. Global commitments and EU regulation are increasingly converging on the expectation that private sector organisations understand and disclose how their activities both depend on and impact nature and biodiversity. From global ambition to national implementation The Kunming-Montreal Global Biodiversity Framework (GBF), adopted in 2022 under the UN Convention on Biological Diversity, sets the scene for biodiversity action in the next few decades. The vision of the GBF is a world of living in harmony with nature where “by 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people.” The mission of the Framework for the period up to 2030, towards the 2050 vision is: “To take urgent action to halt and reverse biodiversity loss to put nature on a path to recovery for the benefit of people and planet by conserving and sustainably using biodiversity and by ensuring the fair and equitable sharing of benefits from the use of genetic resources, while providing the necessary means of implementation.” Over 190 countries have adopted the GBF and are now required to develop or update their national biodiversity strategies and action plans (NBSAPs), outlining how they will contribute to achieving these global goals at the national level. This process is crucial to translate the global vision and mission into concrete, country-level actions and measurable outcomes. It defines 4 global goals for 2050, envisioning a world living in harmony with nature: 1. Halt the extinction of species and reduce extinction risk tenfold; 2. Protect and restore ecosystems so that biodiversity is valued and conserved; 3. Sustainably use biodiversity to maintain ecosystem services and benefits for people, ensure fair and equitable sharing of genetic resources; 4. Close financial gaps for biodiversity protection. Together, these goals provide a long-term vision for reversing biodiversity loss and ensuring a sustainable future for both people and the planet (Secretariat of the Convention on Biological Diversity, n.d.). Importantly, the GBF is not only a framework for governments but also for businesses: it sets clear expectations for how the private sector can and should contribute to its implementation, for example through assessment, disclosure, and action to reduce biodiversity impacts. Alongside the 4 global goals, the GBF sets out 23 global targets for 2030. This includes Target 15, which calls on countries to require large and transnational companies to assess and disclose risks, dependencies and impacts related to biodiversity across their operations and value chains. Beyond assessment and disclosure, the target’s core aim is to use this information to reduce negative impacts, increase positive impacts, and promote sustainable production. This target has become a key reference point for regulators, financial institutions and standardsetting bodies alike (Secretariat of the Convention on Biological Diversity, n.d.). At the same time, it is important to recognise that the successful implementation of the GBF will require business engagement across all the 4 global goals. In the EU, alignment with the GBF is reflected in the EU Biodiversity Strategy for 2030, which forms part of the wider European Green Deal. This strategy commits to expanding protected areas, restoring degraded ecosystems and integrating biodiversity into business and finance. The aim is to effectively protect nature on 30% of land and 30% of seas by 2030. It establishes the basis for an increasing set of legal requirements that incorporate biodiversity into corporate due diligence, reporting and risk assessment (European Commission, 2025). 20 Key EU regulatory developments One of the most influential pieces of European legislation is the Corporate Sustainability Reporting Directive (CSRD). Private sector organisations in scope of the CSRD are required to produce a sustainability statement applying European Sustainability Reporting Standards (ESRS). This covers two cross-cutting standards and 10 topic-specific standards: five standards for reporting in the Environmental domain, four standards in the social domain, and one standard in the Governance domain. The five standards in the Environmental domain include: }Climate change (E1), }Pollution (E2), }Water and marine resources (E3), }Biodiversity and ecosystems (E4), }Resource use and circular economy (E5) The standard that relates most strongly to this study is ESRS E4: Biodiversity and Ecosystems, which sets out detailed reporting requirements related to governance and strategy, impacts, risks and opportunities and metrics and targets. However, it is important to note that all ESRS standards are interconnected. For example, E3 is part of nature and biodiversity. E1, E2, and aspects of E5 reflect key pressures on nature and biodiversity, while other elements of E5 represent important response strategies). These requirements may be further adjusted through the forthcoming “Omnibus” amendments to the ESRS, which aim to refine and clarify certain disclosure obligations. Specific timelines, as well as some disclosure requirements, are currently under revision and may influence how biodiversity-related information is reported in practice. Double materiality A core concept of ESRS is double materiality: private sector organisations are expected to assess not only how (changes in) biodiversity and ecosystems may affect their financial performance but also how their own activities impact biodiversity and ecosystems. This dual perspective is central to determining which disclosures are required. Complementing the CSRD are other EU regulations that address specific aspects of business interaction with nature and biodiversity: }The Corporate Sustainability Due Diligence Directive (CSDDD) requires private sector organisations to identify and address adverse environmental impacts in their operations and value chains, including impacts on biodiversity and ecosystems (European Commission, n.d. a). }The EU Regulation on deforestation-free products (EUDR) obliges private sector organisations to ensure that certain commodities, such as coffee, cocoa, soy, rubber, palm oil, wood and cattle, are not linked to deforestation after 2020. It introduces due diligence, traceability and risk assessment obligations. }The EU Taxonomy for Sustainable Activities defines when economic activities can be considered environmentally sustainable. One of the taxonomy’s six objectives focuses on the protection and restoration of biodiversity and ecosystems, linking nature-related performance to access to green finance (European Commission, n.d. b). }The Sustainable Finance Disclosure Regulation (SFDR) requires financial institutions to report on how they integrate sustainability risks, including biodiversity risks, into their investment decisions. It also calls for transparency on principal adverse impacts, including those related to land use and ecosystems (European Commission, n.d. c). }Other EU environmental directives (e.g., Environmental Impact Assessment Directive, Birds Directive, Habitats Directive, Marine Framework Strategy Directive) also influence business interactions with biodiversity by requiring the assessment, monitoring, and management of impacts on species and ecosystems. These directives often drive on-the-ground conservation actions and involve collecting site-specific ecological data, which can be aligned with national, regional, and global datasets to strengthen biodiversity reporting. Together, these frameworks are reshaping corporate expectations. Where biodiversity is deemed material, they create requirements to gather and disclose information on nature and biodiversity. More broadly, they are increasing demand for spatially explicit, up-to-date and decision-useful biodiversity-related data, a topic that is explored further in the next sections of this guidance. 21 2.3 What are the additional voluntary nature-related frameworks? A growing number of voluntary frameworks are offering private sector organisations practical guidance on how to respond to nature related risks and opportunities. These initiatives provide structure, terminology, and methods that help organisations assess nature-related risks, identify opportunities, and begin integrating nature into business decisions. While not legally binding, these frameworks are shaping market norms. They inform investor expectations, influence due diligence practices, and often serve as stepping stones for private sector organisations preparing to comply with EU sustainability reporting requirements. How do frameworks relate to the use of nature data? The Taskforce on Nature-related Financial Disclosures (TNFD) has emerged as a widely used reference for private sector organisations exploring their nature-related dependencies, impacts and risks. Its LEAP approach, Locate, Evaluate, Assess, Prepare, is suggested within the ESRS standards for the assessment of natureand biodiversity-related impacts, dependencies, risks and opportunities to disclose on. It supports organisations in identifying their interactions with nature, evaluating their dependencies and impacts, assessing related risks and opportunities, and preparing a strategic response. The approach highlights the importance of geospatial data, local context, and stakeholder engagement. It also aligns closely with the EU’s double materiality perspective, offering private sector organisations a structured way to think about what to disclose under regulations like the CSRD (TNFD, 2023). Other nature-related assessment and disclosure frameworks exist as well and a comparison of the seven most used approaches can be found in the Accountability for Nature report (UNEP FI, 2025). The Science Based Targets Network (SBTN) complements this by providing a framework for setting sciencebased targets to reduce impacts and dependencies related to nature. Its guidance focuses on land, freshwater and oceans. For private sector organisations developing transition plans or long-term strategies, these targets offer a way to connect nature data to business actions (SBTN, 2024). The Nature Positive Initiative is working to build consensus around how to measure progress. Its proposed State of Nature Metrics aim to consolidate a wide range of biodiversity indicators into a core, minimum set, helping private sector organisations make sense of an otherwise fragmented landscape of measurement approaches (Nature Positive Initiative, n.d.). The metrics are designed to be embedded in a consistent manner within existing frameworks and standards, such as TNFD, SBTN and GRI. Finally, the Capitals Coalition offers foundational concepts for recognising and valuing nature in decisionmaking. Its Natural Capital Protocol and related resources support private sector organisations in identifying, measuring and valuing their impacts and dependencies across different forms of capital. This can be particularly useful for organisations at the early stages of integrating nature considerations into their operations or investment decisions (Capitals Coalition, 2025). 22 2.4 What are biodiversityand nature-related data? Effective biodiversity-related, and more broadly naturerelated assessments, rely on access to the right data. In line with the definitions provided earlier in chapter 2.1, biodiversity-related data refers to information on the diversity of life (genetic, species, and ecosystems) and the ecological interactions that sustain them. This includes data on the state and trends of biodiversity, such as species abundance, habitat extent and quality, and ecosystem integrity (IPBES, 2019). Nature-related data builds on this, covering both biodiversity (the living components) and the non-living components of ecosystems (such as soil, water, and air), as well as the functions and services they provide. It can also include pressure data (e.g. land use change, pollution, overexploitation), which are critical to understanding and addressing biodiversity loss (adapted from TNFD, 2023). The combined term biodiversityand nature-related data is used when the scope explicitly covers both biodiversity-specific information and the broader set of environmental data needed to interpret, manage, or act on biodiversity outcomes. This applies, for instance, in sections that address the full data landscape, where information on biodiversity state is considered together with pressure data, ecosystem functions, and abiotic factors. Using the combined term indicates that both dimensions are within the scope of the analysis or recommendations. Location matters! Biodiversityand nature-related risks and opportunities are inherently local. Business activities that take place in the natural environment, such as deforestation and land conversion and overfishing, can cause localised harm to biodiversity and the wider natural environment. This harm may include the loss of ecosystem integrity or the decline of certain species. The significance of these impacts depends largely on the specific ecosystems affected and the locations where the activities occur or upon which they rely. Therefore, spatially explicit data is critical for identifying areas of elevated risk or opportunity and guiding appropriate responses (TNFD, 2023). Without geographic context, organisations may overlook sensitive ecosystems, misjudge their level of exposure or apply mitigation measures in the wrong locations, thereby undermining the credibility or effectiveness of their strategies. Public, shared, and private biodiversityand nature-related data To support effective assessments and decision-making, it is important to distinguish between three categories of data, based on their accessibility: public (open) data, public data with restrictions, and private (closed) data. Each category carries distinct implications for data use, licensing, and availability (European Commission, 2023; Open Data Institute, 2019). Public (open) biodiversityand nature-related data Public data refers to data that is freely accessible to all without significant barriers. It aligns with the concept of open data, defined as data that anyone can access, use, and share freely, subject only to minimal requirements like attribution (Open Knowledge Foundation, 2015). The European Commission emphasizes that publicly funded or publicly relevant biodiversityand naturerelated data (e.g. species occurrences, climate data) should be treated as a public good and shared openly to foster transparency, innovation, and broad reuse (European Commission, 2023). In practice, public biodiversityand nature-related data are typically released under open licenses such as Creative Commons CC0 or CC-BY, which permit reuse without significant restrictions. While also allowing CC-BY-NC, which places restrictions on commercial use, GBIF encourages that species occurrence datasets be licensed under recognised open licenses to ensure global data accessibility (GBIF Secretariat, 2022a). Similarly, India’s National Data Sharing and Accessibility Policy (NDSAP) mandates that government-funded data should be open by default (Government of India, 2012). 23 Public data with restrictions Between public and private lies a significant middle category: public data with restrictions. These datasets are publicly available in principle but are subject to certain conditions, licenses, or usage restrictions that prevent them from being completely open (Open Data Institute, 2019). The Open Data Institute (2019) describes such data as shared data, which can range from access limited to specific groups (e.g. researchers) to public access under terms like non-commercial use only. A common example is data licensed under Creative Commons CC-BY-NC, which allows free use for non-commercial purposes but prohibits commercial exploitation without separate permission (GBIF Secretariat, 2022a). For instance, the UK’s National Biodiversity Network Atlas offers certain biodiversity datasets under CC-BY-NC licenses, requiring businesses to negotiate additional rights for commercial applications (NBN Trust, 2022). Public data with restrictions thus occupy a middle ground. They enable broader data use while safeguarding legitimate concerns such as privacy, commercial interests, or biodiversity protection (Open Data Institute, 2019). Private (closed) biodiversityand nature-related data Private (closed) data consists of biodiversityand nature-related data that is not publicly accessible. Such data is typically kept within organisations or shared only under specific agreements. Often, these are proprietary datasets owned by private sector organisations, consultancies, or government bodies and are protected by intellectual property rights, confidentiality, or commercial interests (U.S. Geological Survey, 2020). The U.S. Geological Survey (2020) defines proprietary data as information whose ownership rights restrict free distribution. For example, biodiversity surveys conducted for private environmental impact assessments are frequently kept confidential, accessible only through direct negotiations or legal agreements (U.S. Geological Survey, 2020). Even public authorities may withhold certain data to prevent harm, for example, concealing exact locations of endangered species to avoid poaching risks (EOSC Association, 2021). The principle remains that data should be open unless there is a strong, justified reason for restriction (European Commission, 2023). In sum, private biodiversityand nature-related data remains confidential and inaccessible to the public without explicit permission or legal obligations to disclose (U.S. Geological Survey, 2020). It represents a significant, often essential, portion of biodiversity and environmental knowledge, albeit out of reach for broader public use. Openness as a spectrum These three categories, public, public with restrictions, and private, should be understood not as rigid silos but as positions along a continuum of data accessibility (Open Data Institute, 2019). Data may shift along this continuum as legal, ethical, or commercial circumstances evolve (European Commission, 2023). For instance, proprietary data might become publicly available after embargo periods, while open data could become restricted if new privacy or ecological concerns arise. As biodiversity-related issues become more prominent, organisations are increasingly relying on open natureand biodiversity-related data to ensure transparency, sustainability reporting, and regulatory compliance. Clarity about the data’s licensing, sensitivity, and scope, is critical for its lawful and effective use. Understanding openness as a spectrum helps organisations to remain adaptable and aware of the opportunities and constraints involved in using such data for decision-making purposes. 24 3 Who to contact and where to find & access biodiversity data? 25 32 This chapter focuses on challenges related to the use of public biodiversityand nature-related data: datasets produced or funded by public institutions and made accessible to external users, either as open data or under specific use conditions. While private sector organisations also rely heavily on internal data, such as information on operations, asset locations, and supply chains, this guidance concentrates on external, biodiversity-related datasets such as species occurrence, ecosystem condition, and habitat maps. It is important to underscore that effective biodiversity assessment and management is only possible when public and internal data are linked, especially through spatial information. However, gaps in internal corporate data should not be confused with limitations in public biodiversityand nature-related data. This chapter focuses on the latter: helping private sector organisations to better understand and use the biodiversityand nature-related datasets that are already available. Based on interviews and literature, five cross-cutting themes are identified that shape how the private sector engages with public biodiversityand nature-related data: 1. Knowledge, capacity & culture 2. Availability, quality & affordability 3. Complexity & fragmentation 4. Policy, regulation & incentives 5. Integration & application barriers For figure 7 Data availability, quality & affordability Data complexity & fragmentation Integration & application barriers Knowledge, capacity & culture Policy, regulation & incentives Integration and application barriers include late use of biodiversity data in decisionmaking, limited alignment with internal data, difficulties in measuring and attributing outcomes, security concerns when uploading sensitive company information, cultural resistance to new approaches, and limited capacity of smaller value chain partners. Challenges of data availability, quality, and affordability include e.g., gaps in resolution and coverage, unclear licensing, misalignment with business needs, diverse and inconsistent methodologies, short-term funding risks, and hidden processing costs Data complexity and fragmentation stem from inconsistent standards, limited metadata, unclear provenance and versioning, and varying national systems, making it difficult for businesses to ensure comparability, reliability, and auditability. Uncertainty about acceptable data and methods for compliance, lack of assurance infrastructure, regulatory ambiguity, and limited integration of biodiversity into financial systems can hinder confident investment and action Core challenge Limited literacy, expertise, and shared language make biodiversity data challenging to apply in business Implications for businesses •Difficulties in understanding nature and biodiversity •Difficulty in aligning internal teams •Limited confidence to assess or act on biodiversity •Fragmented ownership and unclear responsibilities •Limited suitability of public data for site-level or value chain analysis, with unclear validation •Licensing uncertainties restrict reuse •Costs of access, cleaning, and processing can be restrictive •Reliance on short-term funding limits dataset continuity and reliability •Difficulty comparing datasets and indicators across sources •Uncertainty about data reliability and provenance •Misalignment of indicators and baselines, hindering robust target-setting •Difficulty demonstrating compliance with evolving regulations •Uncertainty around data quality expectations and audit readiness •Limited incentives for early action or strong biodiversity performance •Missed opportunities to address risks or create value •Inconsistent or non-credible monitoring of interventions •Unclear ownership of biodiversity within business units Suggested solutions •Data intermediaries: curate tools by user profile; provide guidance on required knowledge, skills, and resources •Private sector: offer crossfunctional training; promote consistent terminology; develop communities of practice •Data providers: adopt clear licensing and data standards; invest in technology and quality; support users with tools and training; secure longterm funding. •Data intermediaries: create accessible, standardised platforms; develop co-financing partnerships. •Policy makers: enhance regional monitoring and comparability; embed funding mandates in policy. •Private sector: strengthen data quality and resolution; define project-relevant needs; use literature/expert knowledge as supplementary sources; co-finance critical datasets. •Data providers: adopt metadata standards; ensure continuity and updates •Providers & intermediaries: increase transparency of tools and methods •Intermediaries: standardise/ centralise data; improve interoperability; provide user guidance; foster methodological consensus •Private sector: define clear objectives and use cases for biodiversity data •Data intermediaries: simplify regulatory complexity and guidance; promote harmonisation •Private sector: prepare for compliance; integrate biodiversity in strategy and reporting •Policy makers: build enabling infrastructure; harmonise regulations •Data providers & intermediaries: tailor data solutions with business; advance monitoring technologies. •Data intermediaries: facilitate data sharing and standardization; ensure security and confidentiality. •Private sector: integrate biodiversity data into planning and operations; collaborate beyond company boundaries Figure 7: Overview of challenges and responses to using public nature data by the private sector. 33 4.1 Knowledge, capacity & culture Why does it matter? Although many challenges are technical, they are often underpinned by foundational factors, such as how people within private sector organisations understand and relate to biodiversity, and how they can have a role in addressing issues. Several interviewees noted that confusion surrounding concepts such as biodiversity, nature, and ecosystem services can lead to internal misalignment, affecting not only different departments, but also between sustainability and operational teams. Integrating biodiversityand nature-related considerations into corporate practice takes time. Private sector organisations emphasised that progress depends not only on tools, but also on developing internal confidence, a shared understanding and a clear sense of purpose when it comes to addressing biodiversity. Core challenge A common barrier is the absence of a shared language and basic ecological literacy. Although biodiversity is a welldefined concept, it is often perceived as more abstract or complex than it really is. Much of this perceived complexity stems from the wide variety of metrics and tools available to measure biodiversity, rather than from the concept of biodiversity itself. Complexity also arises from the fact that biodiversity and its value differ across locations, making it challenging for private sector organisations to account for site-specific ecological importance within their operations. Limited in-house ecological expertise can make it more challenging to judge which data is most relevant and how to apply it correctly. Moreover, there is often no common understanding of when public biodiversity data is sufficient and when new, site-level primary data collection is needed. Therefore, building confidence through practical training and better communication is critical. Cultural factors, such as differing mindsets, ways of working, and levels of motivation across teams, can also influence how seriously biodiversity is prioritised and integrated into decision-making. These barriers can be overcome: they are the first, addressable steps in an organisation’s journey toward meaningfully integrating biodiversity considerations into business. 34 Implications for business }Difficulties in understanding and distinguishing between nature and biodiversity and why they are both important to businesses }Difficulty in aligning internal teams around biodiversity priorities }Limited confidence to assess or act on biodiversity risks and dependencies }Fragmented ownership and unclear responsibilities Suggested solutions Suggested solutions to the above challenges are organized by actor groups: data intermediaries, and data users, i.e. the private sector in this case. These responses outline how each group can contribute to accelerating the use of public biodiversityand nature-related data. For data users, the actions include both ways to apply data effectively and ways to support broader data adoption. A comprehensive list of solutions for each data actor is provided in Appendix II. For Data intermediaries }Curate biodiversity and nature data tools by user profile and maturity level »Improve clarity around biodiversity tools, datasets, metrics and indicators, tailored to varying business roles, industries, and levels of expertise. »Help users navigate the complex biodiversityand nature-related data landscape by offering curated directories, decision trees, and platform comparisons that clarify which tools are suitable for specific tasks or organisational maturity levels. »Publish clear user guidelines and ensure transparency on how data and tools are documented, including how source data is modelled and what assumptions or limitations apply. This enables organisations to interpret outputs correctly, compare between tools, and avoid misapplication. »Create clear and transparent tools which identify source data and any specific limitations around that data. This should clearly set out any assumptions they have used. }Provide guidance on required knowledge, skills, and resources »Publish guidance outlining the types of knowledge, technical skills, and organisational resources needed for effective biodiversity data management. Recognise that capacity requirements differ substantially between large corporations and small and medium-sized enterprises (SMEs). For example, larger private sector organisations may need advanced analytics teams and dedicated biodiversity specialists, while SMEs might require simpler tools and more hands-on support. Include recommendations for capacity-building pathways, training opportunities, and potential collaborations with external experts or service providers to help organisations close capability gaps. 35 For Data users – Private sector }Offer cross-functional, foundational training and practical examples »Delivering tailored, practical training sessions. Incorporate storytelling techniques, real-world case studies, and visual communication to make biodiversity concepts tangible and relatable. »Design programs for both operational staff and (senior) leadership, including boards and CEOs, to ensure commitment at all organisational levels. »Base training content on authoritative frameworks such as the TNFD Learning Lab, TNFD sector guidance, the “TNFD in a Box” toolkit, and relevant sector-specific standards like the PBAF biodiversity accounting framework for financial institutions. Where appropriate, integrate requirements from (emerging) regulations such as the CSRD to ensure both relevance and compliance (TNFD, 2025; PBAF, 2024). »Additionally, consider sector-specific biodiversity dependencies and impacts to tailor training more effectively. The TNFD sector guidance provides an initial, high-level overview of this (TNFD, n.d. b). »Embed ecological expertise within the organisation by incorporating ecologists into the organisation. This builds an internal ecological memory and provides a guiding point for the rest of the organisation, ensuring biodiversity considerations are embedded in decision-making and strategy. }Promote consistent terminology across teams and documents »Develop and disseminate a shared vocabulary for biodiversity-related concepts to reduce confusion and promote alignment across business divisions. »Standardise definitions and terminology using established references, such as the UN CBD, TNFD, and IPBES. }Develop communities of practice across sectors or industries »Foster peer-learning networks and communities of practice where organisations can exchange case studies, lessons learned, and emerging best practices. »Engage participants from different industries, NGOs, and academic institutions to facilitate cross-sector collaboration, accelerate learning, and harmonise methodologies. »Consider establishing regular forums, online platforms, or working groups focused on specific challenges, such as biodiversity data management, biodiversityand nature-positive strategies, or integration of biodiversityand nature-related risks into financial decision-making. In line with its mandate, Biodiversa+ aims to foster such exchanges by engaging stakeholders across research, policy and business, and by promoting collaborative approaches to biodiversity monitoring and data use. Examples from other initiatives include the Nature Action Dialogues by UNEP-WCMC, an annual cross-sector forum for technical exchange between businesses and biodiversity practitioners. Another is the Proteus Partnership, a long-term collaboration advancing the uptake of biodiversity data and science in business. Both foster shared learning and accelerate collective progress. 36 4.2 Data availability, quality & affordability Why does it matter? Once private sector organisations move beyond highlevel commitments to operational action, such as site selection, supplier engagement, or impact monitoring, the limitations of public biodiversityand nature-related data become more tangible. Core challenge Key concerns include spatial and temporal resolution, thematic coverage, licensing restrictions, and hidden costs of data preparation, validation and the use of different monitoring systems. Coverage of public data tends to be stronger for terrestrial and charismatic species than for freshwater and marine systems, invertebrates, or soil biodiversity. Licensing also emerged as a recurring concern. Platforms like GBIF offer clearly defined licensing models (see definitions in Box 1), but private sector organisations are not always aware of the licensing and/or can still find it challenging to interpret their implications for commercial use or to locate relevant licensing information. Additionally, concerns exist around the scientific robustness of the data itself: the extent to which data is peer-reviewed or produced by scientifically reputable institutions defines its quality, but this information is not always easily accessible or transparent for users seeking to evaluate data credibility. Many public datasets were not originally designed for business users, but for research or conservation, which can limit their practical relevance for corporate decision-making. For example, public data often lacks the granularity needed for site-level or value chain analysis, making it difficult for companies and financial institutions to translate broad biodiversity insights into actionable decisions for specific locations or supply chain actors. In other cases, however, data providers such as GBIF provide highly detailed, geographically explicit data that can reach site-level resolution. Here, the challenge is reversed: the data may be too fine scale for businesses that rely on and focus on broad models and indicators. Similar considerations apply to tools and metrics derived from these datasets. There is considerable diversity among indicators and methodologies, each developed for specific purposes and grounded in varying assumptions and data sources. In practice, this means users must carefully evaluate whether a given tool or metric is scientifically robust, ecologically meaningful, and suitable for their business context. The rapidly evolving landscape of methods can create uncertainty, reinforcing the importance of understanding both the quality of the underlying data and the scientific credibility behind the tools being used. Box 1: Definitions of the licensing models used by GBIF (Creative Commons, 2023) • CC0: Data are made available for unrestricted use, with no requirements or conditions imposed on users. • CC BY: Data can be used freely for any purpose, provided that proper attribution is given to the data sources, following the specifications set by the data owner. • CC BY-NC: Data are available for any non-commercial use, as long as appropriate attribution is provided to the data sources, and the use is not primarily intended for commercial advantage or monetary compensation. A further underlying challenge is funding and continuity. Many public biodiversity and nature datasets depend on short-term, project-based financing, which makes it difficult to ensure regular updates, high-quality documentation, and long-term maintenance. For example, four global knowledge products (the IUCN Red List of Threatened Species, Protected Planet, the World Database of Key Biodiversity Areas, and the IUCN Red List of Ecosystems) have required about US$160 million in historic investment, plus substantial volunteer contributions. In 2013, the annual cost of maintaining three of these datasets was estimated at US$6.5 million, and achieving full baseline coverage was projected to require an additional US$103–114 million, with ongoing upkeep of around US$12–13 million per year (Juffe-Bignoli et al., 2016). These figures only cover the global aggregation layer, not the primary data collection or many national processes. For businesses, the resource needs are often even greater, since private sector organisations require finer spatial and temporal resolution and more frequent updates than those originally designed for science or policy use. Regional examples also show the effect of under-investment: in Brazil’s Amazon, biodiversity research receives a much smaller share of federal funds 37 per km², is highly concentrated in two cities, and often depends on international financing, demonstrating how unstable funding undermines data coverage where it is most needed (Stegmann et al., 2024). For private sector organisations, this means that critical datasets may not be maintained at the level needed for decision-making, underscoring both the risks of relying solely on public data and the opportunity to engage in co-financing models that ensure their continuity and business relevance. Implications for businesses }Public data is not always suitable for site-level or value chain analysis, depending on the location of the assessment. It’s also not always clear how and if the data was validated. }Uncertainty over licensing terms limits reuse }The financial cost associated with accessing data can be restrictive, especially for small and medium-sized enterprises in the early stages of integrating biodiversity considerations into their operations. }Continuity of public datasets depends on short-term project funding, limiting updates and reliability }Cleaning and processing impose hidden costs, especially for smaller firms Suggested solutions Suggested solutions to the above challenges are organized by actor groups: data providers, data intermediaries, and data users, including both policy makers and the private sector. These responses outline how each actor can contribute to accelerating the use of public biodiversityand nature-related data. For data users, the actions include both ways to apply data effectively and ways to support broader data adoption. A comprehensive list of solutions for each data actor is provided in Appendix II. For Data providers }Adopt clear licensing models and data standards »Adopt and clearly communicate a licensing model for the dataset, for example Creative Commons licenses, and specify what this means for potential commercial use. »Adopt widely used data standards, such as DarwinCore (Wieczorek et al., 2012), and, where relevant, newer extensions like the Humboldt Extension for Ecological Inventories (TDWG, n.d.), which enable more comprehensive ecological data descriptions. Using harmonised licensing frameworks helps reduce legal uncertainties for businesses and facilitates broader data sharing and integration across sectors. Where open licenses are not feasible, provide clear guidance on negotiated or tiered access to data under specific conditions. »Apply and maintain metadata standards such as Ecological Metadata Language (Jones et al., 2019) or INSPIRE (European Commission, 2025) to ensure consistent documentation of data sources, collection methods, temporal and spatial coverage, and data quality indicators. }Invest in technology and data quality »Accelerate the deployment of advanced technologies, such as satellites, drones, hyperspectral imaging, LIDAR, and Internet of Things (IoT) sensors, to monitor biodiversity over large geographic scales at high resolution efficiently and cost-effectively. »Invest in research and development to enhance the resolution, frequency, and interpretability of these advanced technologies for biodiversity applications, while remaining mindful of their current limitations (Ramilo-Henry et al., 2024). »Create rigorous validation protocols and transparent quality indicators to ensure the reliability and credibility of biodiversity datasets. Pay particular attention to the integration of citizen science data, which is a valuable addition. However, robust validation and monitoring processes are essential to ensure data quality and to strengthen confidence in the use of such datasets. }Support data users with tools and training »Encourage integration of multi-source data streams to improve biodiversity assessments, habitat mapping, and early detection of ecosystem changes. »Develop training materials and decision-support tools to help data users translate the data these advanced technologies produce into practical insights. »Provide clear documentation of data provenance and quality assessments to support traceability and build trust among users, particularly businesses and policymakers who rely on data for decision-making and compliance reporting. 38 }Ensure long-term funding stability »Secure recurring government funding by treating biodiversity data as national infrastructure. For example, the Atlas of Living Australia is fully funded through the Australian Government’s research infrastructure programme, with every AUD $1 invested estimated to return AUD $3.5 in societal and economic benefits (CSIRO, 2024). Similarly, the Netherlands is anchoring its National Database Flora and Fauna (NDFF) in law, ensuring structural financing from central and provincial governments (NDFF, n.d.). For Data intermediaries }Create accessible and standardised platforms »Create centralized platforms or biodiversityand nature-related data “hubs” that provide standardised, aggregated, and quality-assured datasets accessible to a broad range of users. »Encourage public–private partnerships to invest in shared infrastructure, including open-access portals and collaborative tools that enable peer review, user feedback, and continuous data improvement. »Provide clear documentation of data provenance and quality assessments to support traceability and build trust among users, particularly businesses and policymakers who rely on data for decision-making and compliance reporting. }Develop co-financing partnerships »Pooling resources across actors can help sustain core datasets. The UNEP-WCMC Proteus Partnership demonstrates how private sector organisations collectively fund annual work programmes to improve global biodiversity data (UNEP-WCMC, 2024a; UNEP-WCMC, 2024b). Similarly, the Global Biodiversity Information Facility is maintained by >60 governments paying GDP-linked annual contributions (GBIF, n.d.), showing how international cooperation can sustain open-data infrastructures. For Data users – Policy makers }Enhance regional monitoring and comparability »Support the development of regional biodiversity monitoring networks and national coordination centres to address spatial and thematic gaps. Particular attention is needed for under-represented ecosystems such as freshwater, soil, and marine environments. These efforts align closely with the efforts of Biodiversa+, which is working to establish transnational monitoring networks, national coordination centres, and thematic hubs to improve data coverage and interoperability (Bresadola & Bjärhall, 2025; Basille, Vihervaara, & Winkler, 2025). Ensuring data comparability across borders is essential for coordinated decision-making. »Encourage, or where appropriate require, private sector organisations to submit data collected as part of environmental impact assessment (EIA) baselines or monitoring. Methodologies used in baseline and monitoring surveys should be aligned with those applied by regional monitoring networks to ensure interoperability and strengthen the collective knowledge base. More on data sharing can be found in the Biodiversa+ report on data sharing by the private sector (Ostermann et al. 2025). }Embed funding mandates in policy »Governments can reduce reliance on project-based financing by embedding biodiversity data systems in law or national budgets. For example, the NDFF is transitioning into a legal “national nature register,” securing permanent financing through environmental legislation (NDFF, n.d.). 39 For Data users – Private sector }Strengthen data quality and resolution »Prioritise investments that increase spatial resolution and update frequency of biodiversityand nature-related data. Support technological innovations to improve the precision and timeliness of biodiversity data, e.g. higher-resolution remote sensing, drones, IoT sensors and biodiversity monitoring devices, eDNA sampling, hyperspectral imaging, and satellite inference techniques. »Share data collected as part of environmental impact assessment (EIA) baselines or monitoring and ensure that the methodologies they apply are consistent with those used by regional monitoring networks to enable interoperability and strengthen the collective knowledge base. More on data sharing can be found in the Biodiversa+ report on data sharing by the private sector (Ostermann et al. 2025). }Define project-relevant data needs »Focus data collection on biodiversity elements that are directly relevant to the potential impacts of a project. This helps reduce unnecessary effort and cost while ensuring that collected data is meaningful and fit for purpose. }Use scientific literature and expert knowledge as supplementary data sources »Use scientific literature and expert knowledge to validate whether publicly available biodiversity data is appropriate and accurate for your organisation’s specific context. »Where gaps or uncertainties remain, complement public datasets with insights from scientific studies, local ecological assessments, or expert consultations to ensure the data is fit for purpose and robust enough to inform your objectives. }Co-finance critical datasets »Private sector organisations can directly sustain the public data they depend on. By subscribing to the Integrated Biodiversity Assessment Tool (IBAT), more than 200 private entities contributed USD 2.5 million in 2024 alone, with revenues reinvested into the Red List, WDPA, and KBA datasets (UNEP-WCMC, 2024b). Likewise, Toyota’s multiyear partnership with IUCN supported ~28,000 additional Red List assessments (Toyota Motor Corporation, 2016). These examples illustrate how corporate contributions can be treated as part of sustainability commitments while delivering measurable improvements in public biodiversity data. 40 4.3 Data complexity & fragmentation Why does it matter? Public biodiversityand nature-related data is often fragmented across platforms, presented in inconsistent formats, and accompanied by limited metadata. This makes it difficult for users to assess comparability or integrate datasets into business workflows. Core challenge Without shared standards and clearer metadata, private sector organisations risk misapplying data, or falling into “data washing,” where tools serve optics more than outcomes. The lack of reliable baselines also undermines monitoring and performance tracking. This is particularly problematic for private sector organisations operating across multiple jurisdictions, where national systems vary in structure and accessibility. Users often lack clarity on the provenance of biodiversityand nature-related data, when, where, and how it was collected. This makes it difficult to assess its fitness for specific decisions. These issues are closely linked to the quality of associated metadata, which should document collection methods, temporal and spatial coverage, and update history. There is also a lack of versioning clarity, private sector organisations may unknowingly use outdated datasets or apply them inconsistently across locations, weakening auditability and comparability. Private sector organisations may use public data as a practical first step, even if it is not a perfect fit for their context. This highlights the value of knowing when to complement it with new sitelevel data. Implications for business }Datasets are often difficult to compare, depending on the format and metadata. }Similarly, (modelled) indicators can be hard to compare across different sources or contexts, depending on the monitoring protocols used to collect the underlying data. }Uncertainty around data reliability due to data provenance or assumptions }Misalignment between indicators and baselines, as well as difficulties in establishing robust, verifiable targets. Suggested solutions Suggested solutions to the above challenges are organized by actor groups: data providers, data intermediaries, and data users, i.e. the private sector in this case. These responses outline how each actor can contribute to accelerating the use of public biodiversityand nature-related data. For data users, the actions include both ways to apply data effectively and ways to support broader data adoption. A comprehensive list of responses for each data actor is provided in Appendix II. For Data providers }Adopt and mandate (meta)data standards »Encourage universal adoption of data standards such as DarwinCore (Wieczorek et al., 2012) and other taxonomies (e.g. Catalogue of Life, IUCN) to improve consistency in how biodiversity data is described, shared, and interpreted. »Mandate essential (meta)data fields (e.g. location, collection date, provenance, methodology, licensing information) for all datasets to ensure completeness and facilitate data integration. }Plan for continuity and updates »Establish multi-year funding lines and update schedules for key datasets to ensure their longterm availability, transparency, and reliability for business users. 41 For Data providers & Data intermediaries }Enhance transparency of tools and methodologies »Require biodiversity tools and data platforms to publish clear documentation of their underlying methods, assumptions, and limitations. »Ensure version control is publicly available so users can identify whether datasets or tools are outdated or have changed over time. For Data intermediaries }Standardise and centralize data »The Nature Data Public Facility (NDPF) by the TNFD is designed as an open and distributedaccess facility. It will be pilot-tested in 2025 to improve data discovery across existing naturedata sources and provide decision-useful information for corporate reporting, science-based target setting and transition planning. The pilot also proposes common data and metadata principles for providers, helping to build a more harmonised global nature data ecosystem (TNFD, 2024). }Improve interoperability and comparability of data »Intermediaries can help reduce fragmentation by promoting shared standards, methodologies, and transparent outputs. This makes biodiversity metrics, graphics, and analyses easier to compare and benchmark across private sector organisations, supporting consistency in reporting and decision-making. }Publish practical guidance for data users »Develop practical guidelines on how to handle the complexity of biodiversity data, including advice on metadata and other robustness checks, indicator selection, setting of baselines, selecting reference sites and handling regional differences in data coverage. }Foster consensus on core methodologies and indicators »o Nature Positive Initiative works as an intermediary to assess the existing biodiversity metrics landscape and build consensus on an aligned minimum set of indicators, helping businesses and financial institutions understand which indicators to focus on to start measuring nature outcomes. »o Promote alignment across global frameworks (e.g. TNFD, GBF, CSRD) to ensure private sector organisations can engage with consistent methodologies, indicators, and taxonomies, while maintaining flexibility to integrate local knowledge, values, and context-specific needs. »o Encourage sector-wide alignment on overarching biodiversity metrics and principles for disclosure and comparability, while allowing flexibility for decision-making metrics to adapt to local contexts, project scales, and evolving data quality and availability. This balance helps private sector organisations translate site-level biodiversity data into corporate-wide reporting, while ensuring that local realities and ecological outcomes remain central. For Data users – Private sector }Develop a clear understanding of the objective and specific use case for the biodiversity data »Identify what information is needed and why »Assess whether the identified data supports the objective of the use case and can be clearly linked to the actions taken; otherwise, it will be difficult to demonstrate that biodiversity improvements at the site result from those interventions. »Evaluate the scientific robustness and reliability of the data and consult available guidance on public data sources for your use case, as well as sectorspecific guidance such as that provided by the TNFD. »Validate insights through expert review and, where possible, on-the-ground verification, and supplement findings with additional literature or expert knowledge. 48 5 How to use public biodiversity and nature-related data in practice? 49 50 Public biodiversity data is increasingly used by private sector organisations to assess risks, define strategy, respond to regulation, and drive operational change. However, public datasets rarely provide a full solution on their own. Instead, private sector organisations combine them with internal data, partnerships, or tailored tools to make biodiversityand nature-related data actionable. This chapter presents practical examples of how organisations across sectors are using, and adapting, public data to support their decision-making, even in the face of gaps, uncertainty, or complexity. A structured lens: the ACT-D framework To organise these examples, the ACT-D framework developed by the Capitals Coalition is used. ACT-D describes four typical phases in a company’s nature journey: }Assess: identifying where biodiversity risks and dependencies occur }Commit: setting goals, targets, and internal governance structures }Transform: integrating nature, including biodiversity, into core operations, sourcing, or business models }Disclose: reporting performance under regulatory or voluntary frameworks These phases reflect how organisations translate data into action over time. While not always linear, the ACT-D structure helps clarify how data needs, and barriers, evolve at different stages of decision-making (Capitals Coalition, 2024). Each section of this chapter includes: }A brief overview of the relevant decision context and typical data needs }A link to the most common data-related barriers (as identified in Chapter 4) }A series of real-world use cases showing how private sector organisations are responding }A mapping of each use case to the data landscape described in Chapter 3, indicating which types of data sources and services were used (e.g. raw observations, aggregated datasets, decision-support tools) Visuals are used to highlight which parts of the data landscape were activated in each case, offering a clearer view of how public biodiversity data flows into practice. Rather than restating the full set of barriers or generic response strategies from Chapter 4, this chapter focuses on how organisations are navigating those challenges in real-world contexts, and what can be learned from these examples. 51 5.1 Assessing biodiversity impacts, dependencies, risks and opportunities The first step in integrating biodiversity into business decision-making is to understand in which locations the most material biodiversity impacts, dependencies, risks and opportunities occur. This typically involves spatial screening and hotspot mapping, helping private sector organisations identify priority locations for further analysis, stakeholder engagement, or intervention. This stage is especially relevant for private sector organisations in the early phases of their journey towards sustainability, or that operate in sectors with geographically dispersed supply chains. Public biodiversityand nature-related data often forms the basis of these assessments. Typical data needs in this phase include: }Species occurrence and habitat data (e.g. GBIF, OBIS, IUCN Red List of Threatened Species, National or Regional protected species lists) }Ecosystem extent and condition maps (e.g. Copernicus Land Monitoring, Copernicus Marine Data Store, UN Biodiversity Lab, Nature Map Explorer) }Boundaries for biodiversity sensitive areas (e.g. Natura2000 sites (included in the WDPA via IBAT), Key Biodiversity Areas (via IBAT), Ecologically or Biologically Significant Marine Areas (EBSAs), Protected Seas) (EFRAG, 2022). }Internal site or asset location data (e.g. companyowned GIS, asset registries, supplier locations) Relevant barriers in this phase, as discussed in Chapter 4, often include: }Limited awareness of public data and tools (Knowledge, capacity & culture): Internal teams are often unaware of existing public biodiversity datasets or tools that can support early-stage risk screening. }Gaps in spatial or thematic coverage (Data availability, quality & affordability): Public biodiversityand nature-related data may lack sufficient detail for ecosystem types or geographies relevant to company operations. }Internal data–nature data mismatch (Integration & application): Internal asset or procurement data often lacks the spatial, temporal, or ecological resolution needed to combine effectively with public biodiversityand nature-related data. 52 Use case 1: Enedis (energy distribution company) – risk screening and hotspot mapping Purpose of the data use Identify sensitive areas for birds linked to the overhead power lines network. Outcome Sensitivity heatmaps of collision and electrocution for bird species. How the outcome is used Used to prioritise which overhead lines to modify or place underground, and to target mitigation during maintenance activities. Data used – mapped to the data landscape (Chapter 3) • Raw data collectors: Bird occurrence records collected by Ligue de la Protection des Oiseaux (LPO) • Intermediaries: Bespoke sensitivity overlay tool developed by LPO for the company’s GIS team • User input: Internal asset maps and grid line coordinates used to overlay sensitivity zones Service providers & products (these entities build products / develop metr ics/models from nature and biodiversity data for corporate and financial end users) End users (entities that apply nature and biodiversity data directly from data or service providers for decision-making, i nvestment or compliance. Some are also raw data collectors) Dashboards and Tools Sensitivity overlay tool developed by LPO for the GIS team at Enedis Private sector: Companies (Modelled) metrics and methods e.g., Potentially Disappeared Fraction (PDF), Biodiversity Intactness Index (BII) Private sector: Financial institutions (includes banks, investors, insurance companies etc) Others (e.g., Public sector, non-profit, scie nce, policy makers etc) Nature-and Biodiversity-data providers (Entities that collect and generate nature and biodiversity data) Nature-and Biodiversity-data intermediaries (Entities that add value to nature o r biodiversity data before it reaches end users) Nature-and Biodiversity-data users (Entities that apply nature and biodiversity data for decision-making, investment, or compliance. Some are also raw data collectors.) Raw data collectors (entities that generate and collect nature and biodiversity data directly from the field / laboratory) Scientific institutions e.g., Naturalis Biodiversity Center employs novel monitoring techniques, producing research papers and accompanying datasets as outputs. NGO’s Ligue de la Protection des Oiseaux (LPO) Citizen science platforms e.g., iNaturalist Local and Indigenous knowledge holders Local French NGO named LPO Governments & (environmental protection) agencies e.g., PBL in the Netherlands Private sector and consulting firms e.g., any private sector company that performs biodiversity monitoring Earth Obs data e.g., ESA satellite images Aggregated data (aggregated and standardised data that are further dispersed amongst users by several entities or platforms, mostl y focused on a specific type of data seen in the categories below) Ecosystem extent and condition e.g., Global Forest Watch, Corine Land Cover -Community composition -Ecosystem condition (functioning, structure and composition) -Ecosystem services -Ecosystem thresholds -Ecosystem classification / land cover Protected and conservation areas e.g., KBA, WDPA, Natura2000 Species data, e.g., GBIF, OBIS, IUCN -Genetic composition -Species tr aits -Species occurrence -Species distributions and abundances Impact drivers of biodiversity loss data e.g., Copernicus, G lobal Forest Watch, ESA -Land and sea use change -Overexploitation -Pollution -Climate change -Invasive species & diseases -Other anthropogenic pressures Barriers encountered • Data sensitivity limits access to species-level data; only aggregated sensitivity zones are provided (Data availability, quality & affordability) • Data ownership (Data availability, quality & affordability) Benefits • Avoids need for direct access to sensitive species data, respecting conservation confidentiality. • Saves time and resources by outsourcing ecological analysis to a trusted partner. • Helps build a consensus around the legitimacy of the maps, thanks to the help of experts. What was learned • Partnering with NGOs can enable use of public, semi-public or private data without overburdening internal capacity. • Even generalised data, when spatially explicit, can meaningfully inform operational decisions. • NGO’s can help build a solid methodology that is validated by field experts. Source: According to information provided by Enedis in July 2025. 53 Use case 2: Philips – Performing nature-related disclosure through the LEAP framework Purpose of the data use To assess and disclose biodiversity-related dependencies, impacts, risks and opportunities (DIROs) in direct operations using publicly available and internal nature data in line with the LEAP approach. Outcome The second Taskforce on Nature-related Financial Disclosures (TNFD) report, which applies the LEAP approach, considers manufacturing sites and upstream value chains concerning material flows. The disclosure also integrates ESRS requirements for E5 concerning resource use and the circular economy. The process identifies and addresses risks and opportunities, supporting the Natural Capital program strategic planning. How the outcome is used Nature-related risks and opportunities supports internal business continuity management system, aligning with ESRS E5 Resources use and circular economy compliance. The LEAP approach supports the Natural Capital program strategy guiding focus topics and locations. The outcome also provides insights for investors monitoring biodiversity risks and opportunities. Data used – mapped to the nature data landscape (see Chapter 3) • Raw data collectors: Expert judgement and qualitative assessments employed where data was inconclusive or did not fit their expectations. • Data aggregators: Global Impact Database (Impact Institute), World Database on Protected Areas (WDPA), IUCN Red List of Threatened Species, others. • Intermediaries: ENCORE, Aqueduct tool, IBAT, GLOBIO, WWF Biodiversity Risk Filter, Ecometrix. • User input: Internal databases and IT tools including Philips EP&L. 54 Service providers & products (these entities build products / develop metrics/models from nature and biodiversity data for corporate and financial end users) End users (entities that apply nature and biodiversity data directly from data or service providers for decisionmaking, investment or compliance. Some are also raw data collectors) Dashboards and Tools IBAT, WWF Biodiversity Risk Filter, ENCORE, Aqueduct, Ec omet rix Private sector: Companies Internal databases and IT tools including Philips EP&L (Modelled) metrics and methods GLOBIO Private sector: Financial institutions (includes banks, investors, insurance companies etc) Others (e.g., Public sector, nonprofit, science, policy makers etc) Nature-and Biodiversity-data providers (Entities that collect and generate nature and biodiversity data) Nature-and Biodiversity-data intermediaries (Entities that add value to nature or biodiversity data before it reaches end users) Nature-and Biodiversity-data users (Entities that apply nature and biodiversity data for decision-making, investment, or compliance. Some are also raw data collectors.) Raw data collectors (entities that generate and collect nature and biodiversity data directly from the field / laboratory) Scientific institutions Expert judgment and qualitative assessments employed where data was inconclusive or did not fit their expectations. NGO’s e.g., Royal Society for the Protection of birds Citizen science platforms e.g., iNaturalist Local and Indigenous knowledge holders e.g., Karen people of Thailand and Myanmar Governments & (environmental protection) agencies e.g., PBL in the Netherlands Private sector and consulting firms e.g., any private sector company that performs biodiversity monitoring Earth Obs data e.g., ESA satellite images Aggregated data (aggregated and standardised data that are further dispersed amongst users by several entities or platforms, mostly focused on a specific type of data seen in the categories below) Ecosystem extent and condition e.g., Global Forest Watch, Corine Land Cover -Community composition -Ecosystem condition (functioning, structure and composition) -Ecosystem services -Ecosystem thresholds -Ecosystem classification / land cover Protected and conservation areas WDPA, others Species data IUCN Red List of threatened species, others Impact drivers of biodiversity loss data Global Impact Database (Impact Institute), others Barriers encountered • Difficulty of defining a standard procedure for impact and dependencies analysis, given intermediaries use multiple methodologies to show results (Complexity & fragmentation). • Unclarity in interpreting the results at company level due to data allocation by general sectors that may differ at company level. (Complexity & fragmentation). • Gaps between available biodiversity risk assessment layers and the actual locations of manufacturing sites (Integration & application). For example, a site located in an industrial park could be classified as high-risk for biodiversity depending on the tool or data layer used. Benefits • Developing a general nature assessment at the sector level using public available data can be done as a starting point for identifying relevant company topics. • Combining available public data and internal nature data is a critical element for delivering a better analysis of impact, dependencies, risks and opportunities. • Creating internal capabilities to develop a nature-related risk assessment, defining the strategy and relevant aspects for continuous improvement process What was learned • Nature-related assessment can effectively begin with available public data supplemented by internal data. The combination of both aspects is a good point to start companies’ nature journey. • A continuous improvement approach using both public and internal data to develop the LEAP approach is critical for achieving high quality results. • Improved understanding of intermediaries’ methodologies supports internal teams in validating analysis results and provide better inputs for a nature-related risk assessment. • Translating nature-related impact, dependencies, risks and opportunities analysis into business language is key for embedding nature in the company strategy. Source: According to information provided by Philips in August 2025. 55 5.2 Committing to biodiversity-related goals and internal alignment Once initial biodiversity impacts, dependencies, risks and opportunities are identified, many organisations formalise their commitment through strategic goals, internal governance, or performance targets. This phase, the “Commit” stage in the ACT-D framework, involves setting direction, integrating biodiversity into corporate planning, and prioritising action areas. Credible commitments require alignment between sustainability, risk and operational teams. They also require consistency in how private sector organisations define and track progress. Public biodiversityand naturerelated data, especially when adapted or combined with internal insights, can provide a foundation for prioritisation and target setting. Typical data needs in this phase include: }Ecosystem extent and condition data (e.g. Copernicus, UNBL, ENCORE) }Global and national species trends and pressures data (e.g. IUCN Red List, Global Forest Watch Pro) }Geospatial overlays with operational or investment portfolios }Relevant thresholds or reference values for ecosystems (e.g. GLOBIO, SBTN materiality guidance) }Relevant barriers in this phase include: }Uncertainty about appropriate thresholds or baselines (Complexity & fragmentation): Public data often lacks reference values or temporal depth to determine what constitutes a meaningful or credible target. }Internal KPIs not aligned with ecological relevance (Integration & application): Business metrics do not always reflect biodiversity outcomes, such as habitat quality or species trends. }Inconsistent biodiversity goal-setting practices (Knowledge, capacity & culture): Private sector organisations lack a shared language or framework for setting biodiversity goals, making alignment across sectors or peer comparison difficult. 56 Use case 3: ASN Bank – Biodiversity footprint target for financed activities Purpose of the data use Support the goal of achieving a net positive impact on biodiversity by 2030 for all investments. Outcome A quantified biodiversity footprint of ASN’s loans and investments, enabling the bank to monitor progress against its long-term biodiversity target. How the outcome is used The data informs portfolio decisions, client engagement, and external reporting. It also enables ASN to align its financial strategy with the ambition to halt biodiversity loss. Data used – mapped to the biodiversityand nature-related data landscape (see Chapter 3) • Data aggregators: Species occurrence and habitat data from GBIF and other sources; Aggregated biodiversity state and pressure indicators used within the BFFI model • Intermediaries: CREM/PRé’s Biodiversity Footprint for Financial Institutions (BFFI) tool • User input: Portfolio composition and financial exposure per sector or client Aggregated data (aggregated and standardised data that are further dispersed amongst users by several entities or platforms, mostly focused on a specific type of data seen in the categories below) Ecosystem extent and condition Habitat data and species occurrence data from GBIF and other sources Protected and conservation areas e.g., KBA, WDPA, Natura2000 Species data Habitat data and species occurrence data from GBIF and other sources Impact drivers of biodiversity loss data e.g., Copernicus, Global Forest Watch, ESA -Land and sea use change -Overexploitation -Pollution -Climate change -Invasive species & diseases -Other anthropogenic pressures Nature-and Biodiversity-data providers (Entities that collect and generate nature and biodiversity data) Nature-and Biodiversity-data intermediaries (Entities that add value to nature or biodiversity data before it reaches end users) Nature-and Biodiversity-data users (Entities that apply nature and biodiversity data for decision-making, investment, or compliance. Some are also raw data collectors.) Raw data collectors (entities that generate and collect nature and biodiversity data directly from the field / laboratory) Scientific institutions e.g., Naturalis Biodiversity Center employs novel monitoring techniques, producing research papers and accompanying datasets as outputs. NGO’s e.g., Royal Society for the Protection of birds Citizen science platforms e.g., iNaturalist Local and Indigenous knowledge holders e.g., Karen people of Thailand and Myanmar Governments & (environmental protection) agencies e.g., PBL in the Netherlands Private sector and consulting firms e.g., any private sector company that performs biodiversity monitoring Earth Obs data e.g., ESA satellite images Service providers & products (these entities build products / develop metrics/models from nature and biodiversity data for corporate and financial end users) End users (entities that apply nature and biodiversity data directly from data or service providers for decisionmaking, investment or compliance. Some are also raw data collectors) Dashboards and Tools e.g., IBAT, WWF Biodiversity Risk Filter, ENCORE, HUB Ocean's Ocean Sensitive Ar eas (OSA) Private sector: Companies Portfolio composition and financial exposure per sector or client (Modelled) metrics and methods CRE M/ PRé’s Biodiversity Footprint for Financial Institutions (BFFI) tool Private sector: Financial institutions Portfolio composition and financial exposure per sector or client Others (e.g., Public sector, nonprofit, science, policy makers etc) Barriers encountered • Difficulty aligning biodiversity metrics with financial KPIs and reporting structures (Integration & application) • Limited spatial resolution of available biodiversity data for certain asset classes (Data availability & quality) Benefits • First mover advantage in biodiversity disclosure across a financial portfolio • Structured approach to tracking progress toward a net-positive goal What was learned • Portfolio-level biodiversity metrics can inform strategy and engagement • Collaboration with expert intermediaries helps overcome technical and data gaps Source: ASN Bank, 2022 57 Use case 4: Nature Positive Initiative – Piloting “State of Nature Metrics” Purpose Pilot a core set of universal biodiversity indicators, measuring ecosystem extent, condition, and species trends, to support corporate tracking of “nature-positive” outcomes. Intended projected outcome A streamlined and credible suite of science-based metrics that can be embedded into corporate strategies and external reporting frameworks. Pilot results are expected by late 2025 or early 2026. Intended use • Provide participating organisations with measurable insights into ecosystem health and species trends • Support adoption in existing frameworks, like TNFD’s LEAP, GRI, and SBTN, for strategic planning, disclosure, and target-setting Data sources (indicative only) Note: Specific data sources have not yet been confirmed, this mapping is based on the types of indicators described in the draft design. Final data types used will depend on pilot methods and context. • Raw data collectors: field surveys, monitoring networks, citizen science • Data aggregators: datasets like GBIF, IUCN Red List, Copernicus ecosystem layers • Intermediaries: modelling and interpretation support from institutions or consultancies • User input: site definitions, land-use change info, and internal operational data Relevant barriers (Chapter 4 themes) • Uncertainty about baselines or thresholds: Difficult to find reference states for assessing ecosystem condition and historical baseline data to assess progress (Complexity & fragmentation) • KPIs not aligned with ecological reality: The initiative aims to ensure state of nature metrics are both credible and practical for private sector organisations across diverse habitats (Integration & application) • Lack of shared target definitions: Harmonising metrics across sectors supports better comparability, shared understanding and cross-sector nature action (Knowledge, capacity & culture) Anticipated benefits • Create clear links between the state of nature and business performance • Enable standardised biodiversity performance tracking across organisations • Foster early consensus on practical biodiversity metrics What will be learned • Practical feasibility of applying state-of-nature metrics across diverse sectors and locations • Key data types and partnerships required for operationalisation • How biodiversity indicators can effectively support corporate decision-making Sources: Nature Positive Initiative, 2025a; Nature Positive Initiative, 2025b 64 5.5 Overcoming persistent gaps across the corporate nature journey While public biodiversityand nature-related data is already being used in corporate decision-making, the journey from first assessments to strategic transformation is rarely linear. Use cases in this chapter have shown how private sector organisations can start applying biodiversity data at each phase of their broader nature journey, from identifying impacts and dependencies to setting goals, improving disclosure, and adjusting operations. However, these examples also reveal persistent gaps and constraints that continue to affect the effective use of public biodiversityand nature-related data. A few cross-cutting barriers deserve particular attention: }Uncertainty about thresholds and reference states (Complexity & fragmentation): Private sector organisations struggle to define what constitutes a healthy ecosystem, a meaningful change, or a “biodiversitypositive” outcome. Lack of consensus on reference values makes it difficult to set credible baselines, targets, and metrics. }Mismatch between ecological and business classification systems (Integration & application): Company KPIs or reporting categories often do not align with ecological units or pressure-state-response frameworks, complicating the integration of biodiversity into mainstream management systems. }Low capacity among key actors (Knowledge, capacity & culture): Even when data is available, many private sector organisations, especially SMEs and upstream suppliers, lack the skills, staff time, or confidence to use it effectively. }Data usability issues remain (Availability, quality & affordability): High-quality data may exist, but be difficult to access, costly to process, or poorly documented. This limits uptake beyond frontrunners with specialised in-house teams. To address these barriers, several promising practices have emerged across sectors: }Pairing data use with internal capability-building: Leading organisations combine spatial analysis or disclosure pilots with targeted training, guidance materials, or cross-team collaboration. This helps embed data use in everyday decisions, not just specialist roles. }Clarifying decision context and fitness-for-purpose: Rather than trying to use one dataset for all purposes, frontrunners identify specific data needs for each step in the decision process, such as scoping, supplier engagement, or restoration design, and tailor data choices accordingly. }Collaborating to create shared approaches: Initiatives like the Nature Positive Initiative, SBTN, or TNFD sector pilots provide a platform for private sector organisations to co-develop indicators, reference states, or disclosure templates that can improve comparability and reduce duplication. }Advancing hybrid data models: A growing number of cases combine public biodiversityand nature-related data with internal business data, such as asset locations, procurement flows, or investment portfolios to create more actionable insights. This hybrid approach is key to scaling biodiversityand nature-related data use beyond initial screening. The shift from exploratory pilots to systemic integration requires continued investment, not only in data quality and availability, but also in the broader ecosystem of enablers: skills, platforms, methodologies, and incentives. The next chapter explores how these enablers can be strengthened to unlock further uptake. Bridging back to systemic enablers The use cases presented in this chapter illustrate that private sector organisations can already take meaningful steps by combining public biodiversity data with internal insights, partnerships, and tailored tools. These examples highlight practical ways of navigating current challenges: from working with NGOs to overcome access restrictions, to pooling data through intermediaries, or piloting new biodiversity metrics in collaboration with peers. Yet, as the cases also demonstrate, such practices are often resource-intensive, fragmented, and dependent on frontrunners willing to experiment. To enable broader and more consistent uptake across sectors, the systemic enablers identified in Chapter 4 (Suggested solutions) remain crucial. The continuity of public datasets requires stable financing mechanisms beyond project cycles; the interoperability of datasets depends on harmonised licensing and data standards; and usability at scale calls for accessible platforms, training, and decision-support tools. These are structural issues that individual private sector organisations cannot resolve alone, but which determine whether public biodiversity data becomes a mainstream input for decision-making. In this sense, Chapter 5 has shown what is possible under current conditions, while Chapter 4 provides the roadmap for making these practices scalable, reliable, and accessible to all actors, not just pioneers with specialised capacity. Together, the two chapters underline that both immediate, pragmatic action and systemic, collective solutions are needed to unlock the full potential of public biodiversityand nature-related data. 65 66 6 Conclusion: unlocking the potential of public biodiversityand nature-related data 67 68 Biodiversityand nature-related data is no longer a niche concern. As private sector organisations face growing expectations to assess, manage, and disclose their impacts and dependencies on biodiversity, the role of public biodiversityand nature-related data has become both more visible and more critical. This report has shown that while challenges remain, public datasets are already being used, and adapted, to inform decision-making across sectors. This report has shown that while challenges remain (Chapter 4), private sector organisations are already finding ways to use and adapt public datasets in practice (Chapter 5). Together, these findings suggest a dual message: }Private sector organisations cannot wait for “perfect data”, they need to begin working with what is already available, building familiarity and internal capability. }At the same time, systemic support is needed to improve the accessibility, quality, and long-term sustainability of public biodiversity datasets. Key takeaways from this guidance include: }Public biodiversityand nature-related data is foundational but underused. Many private sector organisations still struggle to access, interpret, or apply these datasets effectively. Yet the examples in this report demonstrate that meaningful use is possible, even with current data, when the right capabilities, tools, and partnerships are in place. }Barriers are as much social as they are technical. Challenges related to data quality, fragmentation, or licensing are real. But often, the greatest hurdles stem from limited organisational capacity, siloed responsibilities, or uncertainty about how to translate data into action. }The private sector cannot address these issues in isolation. Progress depends on collaboration between private sector organisations, governments, research institutions, and civil society. Public investments in data infrastructure, clearer standards, and long-term maintenance are essential to ensure that biodiversityand nature-related data becomes more discoverable, usable, and relevant for corporate use. }Financing biodiversityand nature-related data is a shared responsibility. While many datasets are publicly funded, maintaining and updating them requires ongoing support. As corporate reliance on public biodiversityand nature-related data grows, there may also be a role for the private sector in supporting the long-term availability, quality, and accessibility of these resources, for example through participation in collective initiatives, licensing models, or support for open data partnerships. }Progress is already underway. From collaborative platforms to tool development, new initiatives are emerging that aim to make biodiversityand naturerelated data more actionable. These efforts benefit from alignment, continuity, and integration into broader systems for disclosure, assessment, and performance tracking. Improving the use of public biodiversityand naturerelated data depends on two mutually reinforcing developments: 1. Private sector organisations will need to begin working with data that is already available, even if imperfect, to build internal familiarity and demand. 2. Continued support is needed for the broader ecosystem of actors working to improve the quality, accessibility, and relevance of that data. Both sides of this equation are essential. Without corporate demand, there is limited incentive to improve public datasets. Without improved access and usability, private sector organisations may struggle to act effectively on their biodiversityand nature-related risks and opportunities. Stakeholder-specific recommendations To unlock the full value of public biodiversityand naturerelated data, coordinated action is needed across the data ecosystem: Private sector organisations and data users }Work with available datasets to build internal capabilities and familiarity, with a focus on understanding their appropriate use, including what public datasets are and are not suitable for, and developing the ability to assess new data sources accordingly. }Embed biodiversity data early in decision processes, including procurement, investment screening, and site planning. }Collaborate with data intermediaries to tailor tools and indicators to specific operational or regional needs. }Provide feedback to data providers, contribute financial or other resources (e.g., funding for dataset updates or platform maintenance), and participate in pilots to inform tool development and data improvements. 69 Intermediaries and tool developers }Clarify methodologies, licensing terms, and data lineage to build user trust. }Contribute to standardisation efforts by aligning tools with international frameworks and taxonomies (e.g. TNFD, Science Based Targets Network (SBTN), Global Reporting Initiative (GRI), the Global Biodiversity Framework Target 15, EU Taxonomy). }Create modular, interoperable platforms that can accommodate both public and internal company data. Security and accreditation are critical for ensuring company trust in these systems and enabling broader uptake. }Provide training, use case examples, and sectorspecific guidance to accelerate responsible use. Governments and public funders }Invest in the maintenance and improvement of public biodiversity datasets, including spatial resolution, thematic coverage, and ecosystem-level indicators. }Support regional monitoring centres and long-term biodiversity observatories. }Establish reference datasets and guidance aligned with regulatory and due diligence frameworks (e.g. EU Corporate Sustainability Reporting Directive (CSRD), Corporate Sustainability Due Diligence Directive (CSDDD), and national biodiversity strategies). Standard-setting and reporting bodies }Clarify data expectations under disclosure and due diligence frameworks (such as CSRD, CSDDD, and emerging guidance under TNFD). }Align on core definitions, metrics, and taxonomies, such as ecosystem condition classifications (e.g. GLOBIO, IUCN), species extinction risk categories (e.g. Red List), and sector classification systems (e.g. ISIC, NACE, NAICS), to reduce confusion and enhance comparability. }Encourage integration of public biodiversityand nature-related data into reporting platforms and auditready workflows. By recognising this shared responsibility, and shared opportunity, stakeholders across the value chain can help make public biodiversityand nature-related data a more reliable and practical foundation for decision-making, contributing to more robust biodiversity and nature strategies, credible reporting, and resilient business models. 70 Bibliography Access to Biological Collection Data task group. (2007). 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A roadmap for upgrading market access to decision-useful nature-related data. https://tnfd. global/wp-content/uploads/2024/10/Discussion-paper_ Roadmap-for-enhancing-market-access-to-nature-data. pdf TNFD. (2025). Glossary (Version 3.0). https://tnfd.global/ wp-content/uploads/2023/09/TNFD-Glossary-of-termsV3.0-January-2025.pdf TNFD. (2025). TNFD in a box. https://tnfd.global/ workshop/tnfd-in-a-box/ TNFD. (n.d. a). TNFD adopters. https://tnfd.global/engage/ tnfd-adopters/ TNFD. (n.d. b). TNFD publications: TNFD recommendations and additional guidance. https://tnfd.global/ tnfd-publications/ Toyota Motor Corporation. (2016). Toyota supports the IUCN Red List of Threatened Species. https://global. toyota/en/detail/11927806 UK Government, Department of Agriculture, Environment and Rural Affairs (DAERA), Scottish Government, & Welsh Government. (2025). Blueprint for halting and reversing biodiversity loss: The UK’s National Biodiversity Strategy and Action Plan for 2030. 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Global resources outlook 2024: Bend the trend – Pathways to a liveable planet as resource use spikes. International Resource Panel. https://wedocs.unep. org/20.500.11822/44901 U.S. Geological Survey. (2020). USGS proprietary and sensitive data policy. https://www.usgs. gov/products/data-and-tools/data-management/ proprietary-and-sensitive-data Vanegas, G. (2024, November 3). COP16: Landmark biodiversity agreements adopted. UN News. https:// news.un.org/en/story/2024/11/1156456 Wallenius Wilhelmsen. (2025). Enhancing maritime biodiversity considerations: Wallenius Wilhelmsen’s LEAP approach. https://www.walleniuswilhelmsen.com/ storage/images/WW-TNFD_LEAP_Use-Case.pdf Wieczorek, J., Bloom, D., Guralnick, R., Blum, S., Döring, M., et al. (2012). Darwin Core: An evolving communitydeveloped biodiversity data standard. PLoS ONE, 7(1), e29715. https://doi.org/10.1371/journal.pone.0029715 World Economic Forum. (2025). The global risks report 2025 (20th ed.). https://www.weforum.org/publications/ global-risks-report-2025/ World Economic Forum. (2020). The future of nature and business: New Nature Economy Report II. https://www3. weforum.org/docs/WEF_The_Future_Of_Nature_And_ Business_2020.pdf World Economic Forum, & PwC. (2020). Nature risk rising: Why the crisis engulfing nature matters for business and the economy. World Economic Forum. https:// www3.weforum.org/docs/WEF_New_Nature_Economy_ Report_2020.pdf WWF. (2022). The biodiversity data puzzle. https://www. wwf.org.uk/our-reports/biodiversity-data-puzzle Yue, M., & Nedopil, C. (2025). China green finance status and trends 2024–2025. Green Finance & Development Center, Fanhai International School of Finance, Fudan University. https://greenfdc.org/wp-content/ uploads/2025/03/Yue-and-Nedopil-2025_China-greenfinance-status-and-trends-2024-2025-final.pdf 80 Data availability, quality & affordability #Challenge Explanation 8 Resolution of the data Public nature data lacks sufficient spatial or temporal resolution to support site-level decision-making. This limits its use in project screening, restoration design, or monitoring of ecological change. 9 Data gaps in marine/offshore contexts Marine and offshore ecosystems are underrepresented in global nature databases. This is a barrier for sectors such as offshore energy and fisheries. 10 Outdated or static datasets Several commonly used nature datasets are not regularly updated or lack seasonal variation. This restricts their usefulness for tracking trends or monitoring project outcomes over time. 11 Licensing Licensing conditions are not always clear or adapted to commercial use. Some public nature datasets are restricted to non-commercial applications, limiting their usability for private sector actors. 12 Affordability While nature data is often labelled as public or open, costs can arise from data cleaning, spatial resolution upgrades, access to interpreted layers, or licensing fees for tools. 13 Limited ecosystem-level data Public data tends to focus on species occurrences, rather than providing information on ecosystem condition, functionality, or resilience. This constrains its application for nature-positive strategies. 14 Reliability of the data Nature data can vary in quality, methods, and coverage. Inconsistent standards, outdated surveys, or citizen science data of uncertain accuracy create doubts about reliability for decision-making and reporting. 15 Entities who collect data do not share their data Data collected by private companies, consultancies, or research projects often remains proprietary or inaccessible. This limits data availability, creates duplication of effort, and leaves key gaps in public biodiversity knowledge. 16 All potential for data and no measures for outcomes Many datasets focus on pressures, risks, or habitat presence but lack clear links to ecological outcomes. This makes it hard to track whether actions taken improve biodiversity condition or resilience. 81 Data complexity and fragmentation #Challenge Explanation 17 Data is complex and scattered Nature data is spread across multiple platforms, formats and initiatives, while often drawing from a similar set of core sources. New tools or combinations do not necessarily reflect new underlying data. This makes it difficult for companies to identify overlaps, compare sources, or efficiently combine datasets. 18 Lack of interoperability of datasets Nature datasets often use inconsistent structures, classifications, or taxonomies, which limits their ability to be combined or compared. For example, species data may be reported using different names or formats across platforms. 19 Lack of metadata / easy insight into reliability Users cannot always assess the reliability, quality, or completeness of nature datasets. Metadata is missing or insufficiently standardised. This limits trust and appropriate application of the data. 20 Fragmentation across countries and systems National and regional nature data platforms vary widely in their accessibility, licensing, language, and structure. This limits crossborder comparisons and hinders multinational companies. 21 Misuse of generic data & tools (‘data washing’) Tools that are not context-appropriate are sometimes applied broadly, leading to oversimplified conclusions or the appearance of action (“data washing”). For example, overlaying generic biodiversity heatmaps on project areas without assessing underlying drivers. 22 Incompatibility with asset data Internal business systems are not always compatible with nature datasets in terms of data format, spatial resolution, or classification (e.g. administrative units vs. ecological zones). In tools like ENCORE, sector classifications may not reflect the ecological relevance of an activity (e.g. a printer might be classified under agriculture). Furthermore, companies and databases use different classification systems (e.g. NACE, NAICS, ISIC, GICS), and harmonised crosswalk tables are lacking. This hampers the extraction of sector-related biodiversity impacts and dependencies from public data platforms. 23 Lack of data to make a baseline Organisations often cannot establish a reliable biodiversity baseline due to missing historical data or insufficient detail at relevant scales. This makes it difficult to measure changes over time or set credible targets. 24 Fragmentation in time as well as in space Nature data is unevenly collected across both geographic areas and time periods. Gaps in temporal coverage make it hard to detect trends, while spatial inconsistencies hinder comprehensive assessments across landscapes or jurisdictions. 25 How to define your impact buffer is different for everyone and between business activities There is no standard method for defining how far business impacts extend beyond direct project boundaries (“impact buffers”). Different sectors apply varying assumptions, leading to inconsistencies in risk assessment, footprint calculations, and reporting. Policy, regulation & incentives #Challenge Explanation 26 Uncertainty about future reporting requirements Companies are unclear about what will be required under emerging regulations and frameworks such as CSRD, CSDDD, the EU Taxonomy, TNFD and SBTN, especially regarding scope, indicators, value chain expectations, and materiality thresholds. This creates uncertainty around which data to prioritise and how to align internal systems. 27 Limited financial or ESG incentives Biodiversity performance is rarely reflected in ESG scores, lending criteria, or investment risk assessments. This reduces the motivation for companies to prioritise biodiversity relative to more financially material topics like carbon or water. 28 Too much focus on compliance Biodiversity action often centres on meeting minimum legal or reporting requirements rather than driving genuine positive outcomes. This compliance-driven mindset limits ambition, stifles innovation, and can lead to box-ticking instead of integrating biodiversity into core business strategy. 82 Integration and application barriers #Challenge Explanation 29 Lack of integration of biodiversity considerations early-on in decision making processes Biodiversity is often considered too late in investment or procurement processes, after key project parameters are already fixed. This limits opportunities to avoid or reduce negative impacts through design choices. 30 Lack of standardised (impact) metrics There is no agreed-upon way to quantify or compare biodiversity impacts across companies or projects. This makes it difficult to set targets, track progress, or benchmark performance. 31 Challenge to track change over time which requires additional monitoring efforts Public datasets often lack the spatial or temporal resolution needed to detect whether restoration or mitigation efforts are having a meaningful ecological effect. Satellite data can be used for some purposes, but monitoring of some aspects of the state of nature over time (e.g., ecosystem integrity) is required to understand what actions to take. 32 Attribution challenge It is unclear how much of a biodiversity impact, dependency or restoration outcome can be credibly attributed to a specific company or intervention. This complicates target-setting, disclosure, and claims of progress. 33 Baseline uncertainty There is no clear standard for how companies should define a biodiversity baseline, including what reference state, timeframe or metric to use. This makes it difficult to determine whether progress has occurred, or targets have been met. 34 Company internal IT infrastructure challenges (financial sector) Financial institutions often lack IT systems capable of handling spatial, ecological, or geospatial data. Existing infrastructures are designed for financial data and cannot easily integrate biodiversity datasets, limiting analysis, reporting, and risk assessment. 35 Resources and conventional thinking Companies may lack the resources, capacity, or internal mandate to prioritise biodiversity, while established business practices favour short-term financial metrics over ecological considerations. This limits innovation and delays integration of biodiversity into decision-making. This also links to knowledge, capacity & culture. 36 Gap between what large companies can do, and large companies will ask Even when large corporations have the resources and tools to act on biodiversity, they may not translate these expectations into practical demands on suppliers or partners. This creates a gap between corporate commitments and supply chain action. 37 Competition barrier Companies may hesitate to share biodiversity data, methodologies, or lessons learned due to concerns about competitive advantage. This limits collective progress, learning, and the development of sector-wide best practices. 38 There is no standard for what good restoration is + how can you measure this Clear, shared standards are lacking for defining and measuring successful ecological restoration. Metrics, methodologies, and success criteria vary widely, making it hard to evaluate outcomes, report progress, or compare projects. 83 Appendix II – Responses per data actor. Data providers Adopt clear licensing models and data standards }Adopt and clearly communicate a licensing model for the dataset, for example Creative Commons licenses, and specify what this means for potential commercial use. }Adopt widely used data standards, such as DarwinCore (Wieczorek et al., 2012), and, where relevant, newer extensions like the Humboldt Extension for Ecological Inventories (TDWG, n.d.), which enable more comprehensive ecological data descriptions. Using harmonised licensing frameworks helps reduce legal uncertainties for businesses and facilitates broader data sharing and integration across sectors. Where open licenses are not feasible, provide clear guidance on negotiated or tiered access to data under specific conditions. }Apply and maintain metadata standards such as Ecological Metadata Language (EML; Jones et al., 2019) or INSPIRE (European Commission, 2025) to ensure consistent documentation of data sources, collection methods, temporal and spatial coverage, and data quality indicators. Invest in technology and data quality }Accelerate the deployment of advanced technologies, such as satellites, drones, hyperspectral imaging, LIDAR, and Internet of Things (IoT) sensors, to monitor biodiversity over large geographic scales at high resolution efficiently and cost-effectively. }Invest in research and development to enhance the resolution, frequency, and interpretability of these advanced technologies for biodiversity applications. }Create rigorous validation protocols and transparent quality indicators to ensure the reliability and credibility of biodiversity datasets. Pay particular attention to the integration of citizen science data, which can be valuable but variable in quality depending on the way it was collected and the expertise of the people gathering the data. Effective validation and monitoring processes are therefore critical to strengthen confidence in such datasets. Support data users with tools and training }Encourage integration of multi-source data streams to improve biodiversity assessments, habitat mapping, and early detection of ecosystem changes. }Develop training materials and decision-support tools to help data users translate the data these advanced technologies produce into practical insights. }Provide clear documentation of data provenance and quality assessments to support traceability and build trust among users, particularly businesses and policymakers who rely on data for decision-making and compliance reporting. Ensure long-term funding stability }Secure recurring government funding by treating biodiversity data as national infrastructure. For example, the Atlas of Living Australia is fully funded through the Australian Government’s research infrastructure programme, with every AUD $1 invested estimated to return AUD $3.5 in societal and economic benefits (CSIRO, 2024). Similarly, the Netherlands is anchoring its National Database Flora and Fauna (NDFF) in law, ensuring structural financing from central and provincial governments (NDFF, n.d.). Adopt and mandate data standards }Encourage universal adoption of data standards such as DarwinCore (Wieczorek et al., 2012) and other taxonomies (e.g. IUCN) to improve consistency in how biodiversity data is described, shared, and interpreted. }Mandate essential (meta)data fields (e.g. location, collection date, provenance, methodology, license) for all datasets to ensure completeness and facilitate data integration. Plan for continuity and updates }Establish multi-year funding lines and update schedules for key datasets to ensure their long-term availability, transparency, and reliability for business users. }Enhance transparency of tools and methodologies }Require biodiversity tools and data platforms to publish clear documentation of their underlying methods, assumptions, and limitations. }Ensure version control is publicly available so users can identify whether datasets or tools are outdated or have changed over time. }Collaborate with business to tailor data solutions }Participate in collaborations with businesses to tailor biodiversity data products and services for operational decision-making. }Support development of contribution-based reporting metrics and landscape-level initiatives to bridge gaps between scientific data and business reporting needs. Advance biodiversity monitoring technologies and methods }Invest in the advancement of new biodiversity monitoring technologies such as eDNA sampling, IoT biodiversity monitoring devices, drone surveys, and highresolution satellite imagery. }Engage in pilot studies and partnerships to test innovative tools and integrate them into standard monitoring protocols. 84 Data intermediaries Curate biodiversity and nature data tools by user profile and maturity level }Improve clarity around biodiversity tools, datasets, metrics and indicators, tailored to varying business roles, industries, and levels of expertise. }Help users navigate the complex biodiversityand nature-related data landscape by offering curated directories, decision trees, and platform comparisons that clarify which tools are suitable for specific tasks or organisational maturity levels. }Publish clear user guidelines and ensure transparency on how data and tools are documented, including how source data is modelled and what assumptions or limitations apply. This enables organisations to interpret outputs correctly, compare between tools, and avoid misapplication. }Create clear and transparent tools which identify source data and any specific limitations around that data. This should clearly set out any assumptions they have used. Provide guidance on required knowledge, skills, and resources }Publish guidance outlining the types of knowledge, technical skills, and organisational resources needed for effective biodiversity data management. Recognise that capacity requirements differ substantially between large corporations and small and medium-sized enterprises (SMEs). For example, larger companies may need advanced analytics teams and dedicated biodiversity specialists, while SMEs might require simpler tools and more hands-on support. Include recommendations for capacity-building pathways, training opportunities, and potential collaborations with external experts or service providers to help organisations close capability gaps. Create accessible and standardised platforms }Create centralized platforms or biodiversityand nature-related data “hubs” that provide standardised, aggregated, and quality-assured datasets accessible to a broad range of users. }Encourage public–private partnerships to invest in shared infrastructure, including open-access portals and collaborative tools that enable peer review, user feedback, and continuous data improvement. }Provide clear documentation of data provenance and quality assessments to support traceability and build trust among users, particularly businesses and policymakers who rely on data for decision-making and compliance reporting. Develop co-financing partnerships }Pooling resources across actors can help sustain core datasets. The UNEP-WCMC Proteus Partnership demonstrates how companies collectively fund annual work programmes to improve global biodiversity data (UNEP-WCMC, 2024a; UNEP-WCMC, 2024b). Similarly, the Global Biodiversity Information Facility is maintained by >60 governments paying GDP-linked annual contributions (GBIF, n.d.), showing how international cooperation can sustain open-data infrastructures. Enhance transparency of tools and methodologies }Require biodiversity tools and data platforms to publish clear documentation of their underlying methods, assumptions, and limitations. }Ensure version control is publicly available so users can identify whether datasets or tools are outdated or have changed over time. Standardise and centralize data }The Nature Data Public Facility (NDPF) by the TNFD is designed as an open and distributed-access facility. It will be pilot-tested in 2025 to improve data discovery across existing nature-data sources and provide decision-useful information for corporate reporting, science-based target setting and transition planning. The pilot also proposes common data and metadata principles for providers, helping to build a more harmonised global nature data ecosystem (TNFD, 2024). Improve interoperability and comparability of data }Intermediaries can help reduce fragmentation by promoting shared standards, methodologies, and transparent outputs. This makes biodiversity metrics, graphics, and analyses easier to compare and benchmark across companies, supporting consistency in reporting and decision-making. Publish practical guidance for data users }Develop practical guidelines on how to handle the complexity of biodiversity data, including advice on metadata and other robustness checks, indicator selection, setting of baselines, selecting reference sites and handling regional differences in data coverage. Foster consensus on core methodologies and indicators }Nature Positive Initiative works as an intermediary to assess the existing biodiversity metrics landscape and build consensus on an aligned minimum set of indicators, helping businesses and financial institutions understand which indicators to focus on to start measuring nature outcomes. }Promote alignment across global frameworks (e.g. TNFD, GBF, CSRD) to ensure companies can engage with consistent methodologies, indicators, and taxonomies, while maintaining flexibility to integrate local knowledge, values, and context-specific needs. }Encourage sector-wide alignment on overarching biodiversity metrics and principles for disclosure and comparability, while allowing flexibility for 85 decision-making metrics to adapt to local contexts, project scales, and evolving data quality and availability. This balance helps companies translate sitelevel biodiversity data into corporate-wide reporting, while ensuring that local realities and ecological outcomes remain central. Simplify regulatory complexity and enhance guidance }Translate complex legal texts (e.g. CSRD, CSDDD, EUDR, EU Taxonomy) into practical checklists, guidance, and tools tailored for different sectors and company sizes. }Provide clear interpretative guidance, reference datasets, and curated resources to help businesses understand, navigate, and comply with regulatory requirements. }Address misaligned incentives within ESG and financial systems that may hinder effective biodiversity action. }Develop mechanisms where datasets are tagged to specific use cases (e.g., TNFD’s Nature Data Public Facility). This would help users assess whether a dataset is fit for purpose and aligned with regulatory expectations. Promote harmonisation of data }Promote harmonisation of methodologies, taxonomies, and indicators to enable consistent and comparable biodiversity assessments across sectors and geographies. Collaborate with business to tailor data solutions }Participate in collaborations with businesses to tailor biodiversity data products and services for operational decision-making. }Support development of contribution-based reporting metrics and landscape-level initiatives to bridge gaps between scientific data and business reporting needs. Advance biodiversity monitoring technologies and methods }Invest in the advancement of new biodiversity monitoring technologies such as eDNA sampling, IoT biodiversity monitoring devices, drone surveys, and highresolution satellite imagery. }Engage in pilot studies and partnerships to test innovative tools and integrate them into standard monitoring protocols. Facilitate data sharing and standardisation }Develop shared disclosure platforms to facilitate data sharing, reduce the reporting burden on smaller companies, and enable consistency across value chains. }Promote standardised protocols and baselining pilots to create consistent reference points for long-term monitoring efforts. }Ensure security and confidentiality standards }Build trust by ensuring that biodiversity platforms and tools meet strong data security and confidentiality requirements, enabling companies to safely integrate sensitive internal data with public biodiversity datasets. Data users – Private sector Offer cross-functional, foundational training and practical examples }Delivering tailored, practical training sessions. Incorporate storytelling techniques, real-world case studies, and visual communication to make biodiversity concepts tangible and relatable. }Design programs for both operational staff and (senior) leadership, including boards and CEOs, to ensure commitment at all organisational levels. }Base training content on authoritative frameworks such as the TNFD Learning Lab, TNFD sector guidance, the “TNFD in a Box” toolkit, and relevant sector-specific standards like the PBAF biodiversity accounting framework for financial institutions. Where appropriate, integrate requirements from (emerging) regulations such as the CSRD to ensure both relevance and compliance (TNFD, 2025; PBAF, 2024). }Additionally, consider sector-specific biodiversity dependencies and impacts to tailor training more effectively. The TNFD sector guidance provides an initial, high-level overview of this (TNFD, n.d. b). }Embed ecological expertise within the organisation by incorporating ecologists into the organisation. This builds an internal ecological memory and provides a guiding point for the rest of the organisation, ensuring biodiversity considerations are embedded in decisionmaking and strategy. Promote consistent terminology across teams and documents }Develop and disseminate a shared vocabulary for biodiversity-related concepts to reduce confusion and promote alignment across business divisions. }Standardise definitions and terminology using established references, such as the UN CBD, TNFD, and IPBES. Develop communities of practice across sectors or industries }Foster peer-learning networks and communities of practice where organisations can exchange case studies, lessons learned, and emerging best practices. }Engage participants from different industries, NGOs, and academic institutions to facilitate cross-sector collaboration, accelerate learning, and harmonise methodologies. 86 }Consider establishing regular forums, online platforms, or working groups focused on specific challenges, such as biodiversity data management, biodiversityand nature-positive strategies, or integration of biodiversityand nature-related risks into financial decision-making. In line with its mandate, Biodiversa+ aims to foster such exchanges by engaging stakeholders across research, policy and business, and by promoting collaborative approaches to biodiversity monitoring and data use. Examples from other initiatives include the Nature Action Dialogues by UNEP-WCMC, an annual cross-sector forum for technical exchange between businesses and biodiversity practitioners. Another is the Proteus Partnership, a long-term collaboration advancing the uptake of biodiversity data and science in business. Both foster shared learning and accelerate collective progress. Strengthen data quality and resolution }Prioritise investments that increase spatial resolution and update frequency of biodiversityand naturerelated data. Support technological innovations to improve the precision and timeliness of biodiversity data, e.g. higher-resolution remote sensing, drones, IoT sensors and biodiversity monitoring devices, eDNA sampling, hyperspectral imaging, and satellite inference techniques. }Share data collected as part of environmental impact assessment (EIA) baselines or monitoring and ensure that the methodologies they apply are consistent with those used by regional monitoring networks to enable interoperability and strengthen the collective knowledge base. More on data sharing can be found in the Biodiversa+ report on data sharing by the private sector. Define project-relevant data needs }Focus data collection on biodiversity elements that are directly relevant to the potential impacts of a project. This helps reduce unnecessary effort and cost while ensuring that collected data is meaningful and fit for purpose. Use scientific literature and expert knowledge as supplementary data sources }Use scientific literature and expert knowledge to validate whether publicly available biodiversity data is appropriate and accurate for your organisation’s specific context. }Where gaps or uncertainties remain, complement public datasets with insights from scientific studies, local ecological assessments, or expert consultations to ensure the data is fit for purpose and robust enough to inform your objectives. Co-finance critical datasets }Companies can directly sustain the public data they depend on. By subscribing to the Integrated Biodiversity Assessment Tool (IBAT), more than 200 private entities contributed USD 2.5 million in 2024 alone, with revenues reinvested into the Red List, WDPA, and KBA datasets (UNEP-WCMC, 2024b). Likewise, Toyota’s multi-year partnership with IUCN supported ~28,000 additional Red List assessments (Toyota Motor Corporation, 2016). These examples illustrate how corporate contributions can be treated as part of sustainability commitments while delivering measurable improvements in public biodiversity data. Develop a clear understanding of the objective and specific use case for the biodiversity data }Identify what information is needed and why }Assess whether the data you have identified is suitable to help achieve the objective of the specific use case in mind. }Evaluate the scientific robustness and reliability of the data and consult available guidance on public data sources for your use case (e.g. guidance provided by TNFD). }Validate insights through expert review and, where possible, on-the-ground verification, and supplement findings with additional literature or expert knowledge. Prepare for regulatory compliance }Take proactive action and engage in thorough preparation to reduce risks associated with regulatory uncertainty. Integrate biodiversity into corporate strategy and reporting }Put nature on the balance sheet: Begin integrating biodiversity-related risks, dependencies, and impacts into financial and accounting processes to ensure nature is recognised as a factor with tangible business value. }Integrate biodiversity systematically into corporate strategy and reporting, treating biodiversity as a finite, material resource. Integrate biodiversity data into planning and operations }Embed biodiversity considerations into early-stage planning tools and procurement processes, such as feasibility studies and site selection, to identify potential impacts and dependencies upfront. }Develop long-term biodiversity monitoring protocols and integrate them into biodiversity management plans to ensure consistent tracking over time. }Tailor existing biodiversity metrics and monitoring methods to specific sectors, leveraging guidance from TNFD, WBCSD, PBAF, and Nature Positive Initiative. Collaborate beyond company boundaries }Engage in landscape-level collaborations to share monitoring costs, data, and management solutions for ecosystems beyond individual sites. }Collaborate with NGOs and local communities early to gain context-specific insights and build social license to operate. 87 Data users – Policy makers Enhance regional monitoring and comparability }Support the development of regional biodiversity monitoring networks and national coordination centres to address spatial and thematic gaps. Particular attention is needed for under-represented ecosystems such as freshwater, soil, and marine environments. These efforts align closely with the efforts of Biodiversa+, which is working to establish transnational monitoring networks, national coordination centres, and thematic hubs to improve data coverage and interoperability (Bresadola & Bjärhall, 2025; Basille, Vihervaara, & Winkler, 2025). Ensuring data comparability across borders is essential for coordinated decision-making. }Encourage, or where appropriate require, private sector organisations to submit data collected as part of environmental impact assessment (EIA) baselines or monitoring. Methodologies used in baseline and monitoring surveys should be aligned with those applied by regional monitoring networks to ensure interoperability and strengthen the collective knowledge base. More on data sharing can be found in the Biodiversa+ report on data sharing by the private sector. Embed funding mandates in policy }Governments can reduce reliance on project-based financing by embedding biodiversity data systems in law or national budgets. For example, the NDFF is transitioning into a legal “national nature register,” securing permanent financing through environmental legislation (NDFF, n.d.). Build Enabling Infrastructure and Harmonised Regulations }Direct public funding towards building authoritative reference datasets and shared infrastructures for biodiversity data, ensuring these resources align with regulatory requirements. }Develop harmonised regulations and disclosure requirements and publish regulatory roadmaps to help businesses anticipate upcoming requirements. Co-funded by the European Union For more information Contact [email protected] Website www.biodiversa.eu Follow us on Biodiversa+ @biodiversaplus.eu EUROPEAN PARTNERSHIP