“Guide to using public biodiversity data in the private sector”

Published: January 2026   |  DOI: 10.5281/zenodo.16967409

Over half of global GDP depends on ecosystem services. As frameworks such as CSRD and TNFD take hold, businesses are under growing pressure to make biodiversity risks, dependencies, and impacts visible in decision-making. Many organisations cite a lack of usable biodiversity data as a key barrier. In reality, vast amounts of biodiversity and nature-related data already exist, produced by research institutions, government agencies, NGOs, citizen science initiatives, and private actors. Platforms such as GBIF alone host hundreds of millions of species records collected over centuries.

The challenge is not scarcity, but usability: knowing where to look, what data is fit for purpose, how to interpret it, and how to apply it responsibly in a business context.

This guide helps bridge that gap, explaining how companies and financial institutions can find, assess, and use public biodiversity data to inform strategy, operations, and reporting. It offers:

  • An overview of key public biodiversity data sources and what they contain
  • Guidance on assessing data quality, resolution, relevance, and limitations
  • Practical solutions to common challenges, including licensing, sensitive data, and comparability
  • Workflows and a 5-step checklist for responsible data use
  • Real-world case studies showing how organisations have turned data into action

Who is this guide for?

Different actors interact with biodiversity data in different ways. This guide is designed to support several key audiences.

Businesses

Businesses integrating biodiversity into operations, strategy or reporting

Takeaways:
  • Start now: Build familiarity and internal capability by working with available public datasets, even if they are imperfect.
  • Integrate early: Embed biodiversity data into procurement, investment, site planning, and risk processes from the outset.
  • Collaborate: Work with intermediaries and experts to tailor tools and provide feedback to data providers.
Financial institutions

Financial institutions evaluating nature‑related risks and opportunities

Takeaways:
  • Screen portfolios: Use public data and tools such as ENCORE to identify nature-related dependencies and impacts.
  • Engage investees: Use data-driven insights to inform dialogue with portfolio companies on biodiversity performance.
  • Prepare disclosure: Leverage existing data to build readiness for SFDR and CSRD reporting.
Policymakers

Policymakers shaping incentives and infrastructure for corporate biodiversity action

Takeaways:
  • Invest long-term: Treat public biodiversity datasets as critical infrastructure requiring stable funding.
  • Support monitoring: Establish regional monitoring centres and long-term observatories to fill data gaps.
  • Provide guidance: Develop reference datasets aligned with regulatory frameworks to guide corporate use.
Data providers

Data providers and intermediaries making biodiversity data more usable for decision-making

Takeaways:
  • Be transparent: Clearly document methodologies, limitations, licensing, and data lineage.
  • Standardise: Align tools and outputs with international frameworks like TNFD, SBTN, and GRI.
  • Educate: Provide training, sector-specific guidance, and applied use cases.
Standard-setting bodies

Standard-setting & reporting bodies aligning data requirements and definitions across frameworks.

Takeaways?
  • Clarify expectations: Define data requirements under disclosure frameworks to reduce uncertainty.
  • Align definitions: Agree on core metrics and taxonomies for concepts like ecosystem condition and species risk.
  • Encourage integration: Promote the use of public data in reporting platforms and audit workflows.

Understanding the basics

Core concepts

Dependencies (outside-in): The ecosystem services an organisation relies on to function. For example, agriculture depends on healthy soils, clean water, and pollinators.

Impacts (inside-out): Changes to the state of nature resulting from an organisation’s activities. These can be direct (e.g., land conversion) or indirect (e.g., supply chain pollution).

Risks & opportunities: Dependencies and impacts translate into financial risks (e.g., operational disruption, regulatory penalties) and opportunities (e.g., sustainable innovation, access to green finance).

The importance of location: Biodiversity risks and opportunities are highly location-specific. Spatially explicit data is critical for identifying sensitive ecosystems and guiding appropriate business responses.

The data landscape

From raw observations to business decisions, biodiversity data flows through several layers:

Raw data collectors
Scientific institutions, NGOs, governments, private sector, local and Indigenous knowledge holders
↓
Data aggregators
GBIF, OBIS, national platforms, regional monitoring networks
↓
Data intermediaries
Tools, dashboards, metrics (e.g., IBAT, ENCORE, WWF Biodiversity Risk Filter)
↓
Private sector users
Companies and financial institutions integrating data into decisions

The data landscape, from raw data to corporate decision-making

Why does a gap persist?
Each layer adds complexity. Data is scattered across multiple platforms with inconsistent standards, licenses, and access requirements. Tools vary in methodology, quality, and intended use. Finding data that is relevant to your specific location, sector, and business question feels difficult. And even when data is found, questions linger: Is this fit for my purpose? Can I trust it? Do I have permission to use it? How do I combine it with my internal business data?
How companies apply public biodiversity data?
ESG & Reporting

Use public data to inform double materiality assessments, contextualise site-level risks, and populate indicators for reporting.

Tip: document which datasets and versions you used; it improves auditability and reproducibility.

Supply-chain screening

Overlay supplier locations with public pressure layers to prioritise engagement and sourcing decisions.

Tip: combine coarse public layers with targeted local surveys where precision is needed.

Site selection & permitting

Use species occurrence data, habitat maps, and Earth observation data early to reduce delays and identify mitigation needs

Tip: check licence terms and sensitive-species guidance before publicising exact locations.

Innovation & product design

Apply open data to develop nature-positive products, biodiversity-linked finance, or ecosystem service assessments.

Tip: collaborate with data intermediaries to convert raw layers into business-ready indicators.

Where to find useful public data?

Some of the most relevant platforms for business include:

  • GBIF: The largest global database for species occurrence data. Essential for understanding species distribution and presence/absence in specific locations.
  • OBIS: The leading global database for marine biodiversity data. Crucial for companies with coastal or offshore operations.
  • Copernicus: Provides satellite-based geospatial data on land cover, land use, vegetation state, and water cycles across Europe. Crucial for assessing habitat extent and change.
  • IBAT: Provides access to key global datasets like the IUCN Red List, World Database on Protected Areas, and Key Biodiversity Areas. Ideal for site-level risk screening.
  • ENCORE: Helps financial institutions understand how economic sectors depend on and impact nature. Useful for portfolio-level analysis.
  • WWF Risk Filter: A free online tool that helps companies assess and prioritise biodiversity-related risks across their operations and value chains.

The guide covers a broader set of portals, tools, and intermediaries, and explains when and how to use them.

Challenges & solutions

Across sectors, organisations face recurring barriers when using biodiversity data:

Knowledge & culture

Core challenge:

Limited ecological literacy and a lack of shared language make biodiversity data challenging to apply in business contexts.

Implications for businesses:

  • Difficulty aligning internal teams
  • Limited confidence to act on biodiversity risks
  • Fragmented ownership and unclear responsibilities

Suggested solutions

Private sector:
Offer cross-functional training and develop communities of practice.

Data intermediaries:
Curate tools by user profile and provide clear guidance.

Policymakers:
Support capacity-building initiatives.

Availability & quality

Core challenge:

Public data often has gaps in resolution and coverage, unclear licensing, and is misaligned with specific business needs.

Implications for businesses:

  • Data is not always suitable for site-level analysis
  • Licensing uncertainties restrict reuse
  • Hidden costs of cleaning and processing data

Suggested solutions

Private sector:
Adopt clear licensing, invest in data quality, and secure long-term funding.

Data intermediaries:
Co-finance critical datasets and define project-relevant needs.

Policymakers:
Enhance regional monitoring and embed funding in policy.

Complexity & fragmentation

Core challenge:

Data is scattered across platforms with inconsistent standards, limited metadata, and unclear provenance, making it hard to compare and audit.

Implications for businesses:

  • Difficult to compare datasets and indicators
  • Uncertainty about data reliability and provenance
  • Misalignment of baselines hinders robust target-setting

Suggested solutions

Private sector:
Adopt metadata standards and ensure data continuity.

Data intermediaries:
Standardise and centralise data, improve interoperability, and foster consensus on methods.

Policymakers:
Define clear objectives and use cases for data.

Policy & regulation

Core challenge:

Regulatory uncertainty about what data is acceptable for compliance, combined with a lack of assurance infrastructure, can hinder investment and action.

Implications for businesses:

  • Difficulty demonstrating compliance with evolving regulations
  • Uncertainty around audit readiness
  • Limited incentives for strong biodiversity performance

Suggested solutions

Private sector:
Simplify regulatory guidance and promote harmonisation.

Data intermediaries:
Prepare for compliance and integrate biodiversity into corporate strategy.

Policymakers:
Build enabling infrastructure and harmonise regulations.

Integration & application

Core challenge:

Biodiversity data is often used too late in decision-making, and it is difficult to measure and attribute outcomes to business interventions.

Implications for businesses:

  • Missed opportunities to address risks or create value
  • Inconsistent or non-credible monitoring of actions
  • Unclear ownership of biodiversity within business units

Suggested solutions

Private sector:
Facilitate secure data sharing and standardisation.

Data intermediaries:
Integrate data into early-stage planning and collaborate on landscape-level solutions.

Policymakers:
Collaborate with businesses to tailor data solutions.

The ACT-D framework: from data to decision

Most organisations follow a similar path when integrating biodiversity into decision-making. Understanding these phases helps clarify what data is needed at each point and what barriers you’ll encounter:

Assess: Identifying risks, dependencies & opportunities

Identify where biodiversity risks, dependencies, and opportunities occur in your operations and value chains.

Common issues include:

Limited awareness of public data and available tools

Internal teams are often unaware of existing public biodiversity datasets or platforms. The landscape is vast and fragmented (e.g., GBIF, OBIS, national platforms, regional initiatives) making it unclear where to start.

How to address it? Companies like Philips and Allianz used established intermediary platforms (IBAT, ENCORE, WWF Biodiversity Risk Filter) to navigate the landscape rather than searching independently. These curated tools guide users to appropriate data sources and support early-stage risk screening.

Gaps in spatial or thematic coverage

Public biodiversity data is unevenly distributed geographically and by ecosystem type. Marine, freshwater, and soil biodiversity are underrepresented compared to terrestrial species. Coverage varies dramatically by region.

How to address it? Enedis (energy distribution company) partnered with a local NGO (Ligue de la Protection des Oiseaux) to access region-specific biodiversity data and expert knowledge. Supplementing public data with scientific literature, expert consultations, and local partnerships helps fill gaps where data is sparse.

Mismatch between internal asset data and biodiversity datasets

Company asset registries, supply chain data, and operational information are structured differently from biodiversity datasets. Spatial resolution, classification systems, and geographic boundaries don’t align, making integration difficult.

How to address it? Wallenius Wilhelmsen combined AIS vessel tracking data (their internal operational data) with marine biodiversity datasets and protected area information to identify collision risks with sensitive marine areas. Working with intermediaries or GIS specialists to overlay internal asset data with public biodiversity layers is key to making this integration work.

Commit: Setting goals, targets & internal alignment

Set goals, targets, and internal governance structures to formalise your commitment to managing biodiversity.

Common issues include:

Uncertainty about appropriate baselines and thresholds

Public data often lacks historical depth, reference values, or clear definitions of what constitutes “healthy” or “degraded” ecosystems. Companies struggle to establish what a meaningful or credible target actually looks like.

How to address it? ASN Bank used modeled biodiversity metrics (through the BFFI tool) to establish a quantified biodiversity footprint for their financial portfolio, enabling them to set and track progress toward a net-positive target. Organizations can reference existing frameworks (TNFD LEAP approach, SBTN guidance, Nature Positive Initiative metrics) as starting points, recognizing that targets will evolve as data quality improves.

Internal misalignment on biodiversity priorities and language

Sustainability, operations, and finance teams use different terminology, metrics, and definitions. There is no common understanding of what biodiversity means for the business or how it should be measured and managed.

How to address it? Build shared understanding through cross-functional training before diving into data. Develop and disseminate a shared vocabulary for biodiversity concepts across the organization. Use visual communication and real-world case studies to make biodiversity tangible and relatable to different teams.

Transform: Changing operations & measuring real impact

Integrate biodiversity into core operations, sourcing, and business models. Measure and report on effectiveness of interventions.

Common issues include:

Difficulty tracking ecological change over time

Monitoring whether business interventions actually improve biodiversity is challenging. Public datasets may lack sufficient spatial resolution, temporal continuity, or timeliness to detect meaningful ecological change. Long-term monitoring is costly and often inconsistent.

How to address it? Philips combines public monitoring data (satellite imagery, ecosystem condition indicators) with site-level observations and expert assessment to track biodiversity and ecosystem services at manufacturing sites. Start with available public data, supplement with targeted site-level monitoring where needed, and use expert validation to interpret results.

Attribution challenge: Determining what impact is your responsibility

It is unclear how much observed ecological change can credibly be attributed to a company’s specific actions versus external factors or broader ecosystem dynamics.

How to address it? Use reference or control sites for comparison. Combine public data with detailed project-level documentation of actions taken. Partner with research institutions to validate attribution. Be transparent about confidence levels and uncertainties in reporting rather than claiming certainty where it doesn’t exist.

Disclose: Reporting risks, impacts & performance

Report performance, risks, and dependencies under regulatory and voluntary frameworks to external stakeholders.

Common issues include:

Unclear expectations under evolving regulations

Regulatory frameworks (CSRD, TNFD, SBTN, CSDDD) are emerging with different requirements, timelines, and interpretations. Companies struggle to know what data and methodologies are considered acceptable for compliance, and what constitutes “decision-useful” information.

How to address it? Allianz and Philips both piloted disclosures using the TNFD LEAP approach to test interpretations and build internal confidence before formal reporting obligations take effect. Working with peer networks, industry groups, and intermediaries to align on best practices helps reduce uncertainty. Don’t wait for perfect clarity, pilot now and refine as standards mature.

Lack of consistency in metrics and indicators across sectors

Companies use different indicators, spatial boundaries, assumptions, and methodologies. This makes external comparisons, benchmarking, and credibility assessment difficult.

How to address it? Reference established frameworks (e.g., TNFD LEAP, Nature Positive Initiative State of Nature Metrics, SBTN guidance) to promote consistency. Participate in sector-specific working groups and peer networks to build shared understanding. Use standardised intermediary platforms like IBAT that apply consistent methodologies.

The ACT-D framework has been developed in a collaboration by leading organisations including the Capitals Coalition, Business for Nature, WBCSD, TNFD, Science Based Targets Network, WEF, and WWF.

Ready to start using biodiversity data?

The full guide provides detailed workflows, case studies, tools, and recommendations to help organisations move from data exploration to confident, responsible use.

Read the full guide
Download the report

  Introduction

  Basics

  Challenges

  ACT-D

This guide is part of a broader set of Biodiversa+ reports on how biodiversity data are used and shared by businesses.