You can build a useful biodiversity baseline without pretending your company has complete ecological data. Treat the baseline as a documented benchmark, work through the TNFD Locate–Evaluate–Assess–Prepare (LEAP) process, rank uncertainty by its potential to change decisions, and publish both the evidence you have and a dated plan to improve it.
What a biodiversity baseline is—and is not
A biodiversity baseline is a benchmark against which changes in nature associated with business activity can be compared. TNFD’s LEAP guidance defines it as “the starting point or benchmark against which changes in the state of nature attributed to the business activity can be compared” (LEAP v1.1, Box 16).
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It is not a universal biodiversity score, a claim that nature is intact, or proof that every supplier and site has been measured. The benchmark may represent a previous condition, a desired condition, a target population, or a habitat-size proxy. The appropriate choice depends on the ecosystem, species, business activity, geography and decision the baseline must support.
Incomplete data should therefore change the way you describe the baseline, not stop the work. A defensible first version states its boundary, date, sources, methods, assumptions, limitations and confidence, then identifies which missing evidence could alter a material decision. It should be possible for a new analyst to reproduce the result, see where judgment entered the process and understand which conclusions are suitable only for screening.
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Start by fixing the decision and boundary
Write a one-page scope note before commissioning more surveys or downloading datasets. It should answer:
- Decision: Is the baseline for risk screening, site management, target-setting, financing, transition planning, regulatory preparation or external disclosure?
- Organisational boundary: Which legal entities, controlled operations, joint ventures and leased or managed sites are included?
- Value-chain boundary: Which upstream inputs, logistics steps, processing stages, customers or end-of-life activities could create important dependencies or impacts?
- Geography: Which countries, watersheds, landscapes, seascapes and facility coordinates are in scope?
- Period: What reporting year or observation window does the baseline represent?
- Activities: Which land, freshwater, ocean, extraction, cultivation, construction, manufacturing or service activities are covered?
- Output: What resolution is necessary—a portfolio screen, facility decision, procurement requirement or ecosystem restoration plan?
Do not imply that one metric or boundary fits every sector. Use the current TNFD LEAP guidance and the sector- or biome-specific guidance relevant to the business. A lender-facing portfolio screen may tolerate regional estimates, while a permit, restoration design or site impact claim may require field evidence. State that distinction at the outset so a coarse dataset is not later presented as if it answered a more precise question.
Use the current LEAP sequence
As of October 2026, TNFD identifies LEAP v2.0 as its current assessment framework. The update expands material on state-of-nature measurement across land, freshwater and ocean realms, invasive alien species, risk and opportunity assessment, environmental crime, transition planning, landscape and seascape approaches, and interoperability with SBTN. The baseline definition quoted above is from v1.1 (October 2023); use v2.0 for current technical instructions.
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Map owned and operated sites and the most important value-chain activities to ecosystems and places. For each interface, record the facility or activity, coordinates or spatial unit, ecosystem type, watershed or marine area, nearby sensitive areas, and the pressures the activity may create. Mark dependencies such as water supply, flood protection, pollination, soil formation, biomass or coastal protection.
If supplier-level data are unavailable, begin with spend, production volume, commodity origin, transport corridor or regional production data. Use those proxies to identify where potential dependencies and impacts are greatest; do not present a regional screen as a site ecological survey. Document the geographic assumption behind each proxy and the point at which it must be replaced by supplier or site information.
Location quality is often the first practical bottleneck. Reconcile facility names, addresses, leases and corporate identifiers; remove duplicate coordinates; and flag sites whose position is known only to a country or broad region. A misplaced coordinate can associate a facility with the wrong watershed or protected-area context and distort every later metric.
2. Evaluate dependencies and impacts
For each located interface, describe the business dependency and the pressure on nature. Typical pressure categories include land-use change, water withdrawal, pollution, resource exploitation, disturbance, invasive species and greenhouse-gas-related climate pressure. Connect each pressure to an ecosystem service or state-of-nature feature that could change.
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Separate what is observed from what is inferred. A facility discharge record may be direct evidence of a pressure; a modeled watershed-stress layer may indicate potential exposure; a commodity-origin assumption may only support prioritisation. Keep those statements distinct in the assessment. Also record whether an observation covers one season, a full year or an irregular sampling event. Absence in a short survey is not evidence that a species or ecological function is absent.
Check for indirect pathways. A facility may have little direct land disturbance but depend on water supplied from a stressed basin. A supplier’s conversion risk may sit outside the company’s property boundary, while transport noise, lighting or invasive species may create local pressures. The baseline should show the pathway rather than assigning every effect to the nearest facility.
3. Assess risks and opportunities
Assess physical risks, transition risks, systemic risks and opportunities for the interfaces that matter most. A risk register can include the risk or opportunity, affected site or activity, dependency or impact pathway, time horizon, financial or strategic consequence, likelihood, existing controls, owner and next action.
TNFD’s register guidance says to assess risks as far as possible even when data are lacking or assumptions are significant. If the full value chain cannot be covered, start with the stage showing the greatest potential dependencies and impacts, document the exclusion and schedule expansion. Keep a distinction between a risk that is unknown and a risk assessed as low; the former needs an evidence plan, not a reassuring color code.
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4. Prepare the response and reporting
Translate the assessment into controls, targets, procurement requirements, restoration or avoidance actions, governance responsibilities and disclosure. For every material data limitation, state the reason—method, access, licensing or commercial sensitivity—and the action, owner and timing for resolving it.
Link each planned action to the evidence it is intended to improve. For example, a supplier traceability requirement can address an origin gap; seasonal fieldwork can test a modeled habitat screen; and a revised water-monitoring protocol can improve a dependency estimate. Include a decision rule for what happens if new evidence shows greater sensitivity than the initial screen.
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Build an evidence inventory before choosing metrics
Create a source register that lets another analyst understand what each item can and cannot support. TNFD’s nature-data recommendations address discoverability, metadata, quality, access, licensing and measurement comparability (Nature Data Value Chain recommendations, v1.0, November 2025).
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitches| Field | What to record | Why it matters |
|---|---|---|
| Owner and provenance | Internal owner, external publisher, collection organisation and original source | Enables verification and future handover |
| Date and period | Collection date, observation period, publication date and update frequency | Prevents an old observation being treated as current |
| Coverage | Sites, suppliers, countries, ecosystems and taxa represented | Shows where conclusions can be generalised |
| Spatial resolution | Exact coordinates, facility boundary, watershed, grid cell or national aggregate | Determines whether the evidence supports a site decision |
| Method | Field observation, laboratory result, remote sensing, model, proxy or expert inference | Clarifies uncertainty and repeatability |
| Access and licence | Public, restricted, licensed, personal-data or commercially sensitive status | Defines who may use or republish it |
| Assumptions and limitations | Missing observations, interpolation, detection limits, boundary choices and known bias | Stops a screening layer being mistaken for measured condition |
| Confidence and permitted use | Internal screening, risk assessment, target-setting or disclosure suitability | Matches evidence strength to the decision |
Keep company records separate from public or third-party nature-state information, but link them through a common location and activity identifier. Preserve the original file, processing steps, version and transformation code where applicable. Note whether a dataset can be retained, shared with an auditor or used in external reporting. Licensing restrictions and commercial sensitivity are data-quality issues as well as legal issues: a metric that cannot be inspected or reused may not support the same assurance claim as an open, documented observation.
Use a simple evidence status for internal control, such as observed, modeled, proxy-based or inferred. These labels are practical working conventions, not a TNFD-prescribed classification. Define them in the data dictionary and require an explanation whenever a conclusion moves from one status to another.
Choose a reference condition that fits the question
Write the reference condition in one sentence: “Change will be compared with [condition], for [place and period], because [decision purpose].” A prior condition may be appropriate where a reliable historical series exists. A desired condition may be appropriate for restoration or a no-net-loss objective. For a species, a target population or habitat-size proxy may be more practical than a complete abundance estimate.
Do not automatically use pristine nature as the benchmark. A working landscape, regulated river, managed forest or repeatedly disturbed industrial area may have a different relevant reference condition. Explain why the selected condition is ecologically meaningful and decision-useful, and identify what evidence would cause you to revise it. If historical records are inconsistent, preserve the original series, describe breaks in method and avoid constructing a false trend by stitching incompatible observations together.
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Select metrics by material issue, not by availability alone
TNFD’s metrics architecture distinguishes core global metrics, sector metrics, additional metrics and assessment metrics for internal analysis (TNFD Metrics). Use the smallest set that answers the decision, then add measures where a material dependency or impact would otherwise be hidden.
For state of nature, TNFD encourages consideration of ecosystem condition by ecosystem type and business activity, and species extinction risk as a placeholder indicator. It does not prescribe one metric for every company: no single state-of-nature metric captures every relevant dimension, and measurement consensus is still developing. Ecosystem-service measures should be specific to the service and location—for example, water-flow regulation for a watershed-dependent facility rather than a generic biodiversity score.
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TNFD reports that an initial 2022 survey found more than 3,000 unique nature-related indicators and metrics in corporate reporting, with inconsistent definitions and uneven coverage. That variety is a reason to define terms, units, boundaries and calculation methods in your own register. A metric that looks precise but lacks a stated denominator, spatial unit or time period is not comparable across sites. Record why each selected metric is material, what it is intended to measure and what it cannot capture.
Evidence options and their proper use
| Evidence type | Strengths | Limits to state explicitly | Best initial use |
|---|---|---|---|
| Company monitoring | Usually close to the activity; may provide operational frequency and control data | May cover only regulated pollutants, selected taxa or a few sites | Pressure measurement and control performance |
| Field survey | Direct, location-specific observation with a defined protocol | Cost, seasonal bias, detection limits and incomplete taxonomic coverage | Material site decisions and validation of screens |
| Remote sensing or spatial layer | Broad geographic coverage and repeatable updates | Resolution, classification error and inability to observe every species or function | Portfolio screening and locating change hotspots |
| Modelled or proxy data | Can fill gaps where direct observations are sparse | Depends on assumptions, calibration and transferability to the site | Prioritisation and scenario analysis |
| Public species or ecosystem records | Independent context and historical information | Uneven sampling, licensing restrictions and uncertain observation effort | Context, sensitivity screening and hypothesis generation |
Compare alternatives by spatial resolution, geographic and taxonomic coverage, time period, update frequency, field-versus-model basis, method transparency, licensing, sector relevance and proportionality to the decision. Cost should be assessed as total effort, not just a dataset price: include specialist review, access fees, field logistics, data cleaning, repeat sampling, staff time and assurance. A cheaper coarse layer can be appropriate for triage but inadequate for approving a site-specific impact claim. Conversely, an intensive survey can be disproportionate for a low-sensitivity portfolio screen.
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Prioritize incomplete data with a gap log
Do not rank gaps only by ease of collection. Rank them by the chance that resolving the gap would change a material impact, dependency, risk, opportunity or management action. Add ecological sensitivity, location, legal or lender relevance and the feasibility of obtaining better evidence.
For each gap, record:
- the unanswered question;
- the affected site, supplier, ecosystem or activity;
- why the answer could change a decision;
- the current proxy, assumption or conservative treatment;
- uncertainty and its possible consequence;
- the evidence-gathering action and method;
- the accountable owner and budget;
- the target review date and trigger for recalculation.
Use staged improvement. First resolve gaps at high-sensitivity locations and high-pressure activities. Next improve data that affects financial exposure, controls or target credibility. Leave low-consequence refinements for later, but keep them visible rather than silently excluding them. If two plausible assumptions lead to different priorities, show both scenarios and explain which one governs interim action.
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Describe the baseline’s confidence by location, metric and conclusion. A portfolio may have high-confidence facility coordinates, medium-confidence ecosystem classification and low-confidence supplier species information. That is more informative than assigning one confidence label to the entire company.
TNFD applies its core disclosure metrics on a “comply or explain” basis and states that not all organisations are expected to report all core metrics immediately. Where a relevant and material metric cannot be measured because of methodology, data access or commercial sensitivity, explain the constraint and the plan for future reporting (TNFD Metrics). Never convert “not measured” into “no impact.”
A clear limitation statement identifies the boundary, missing evidence, interim proxy, decision affected, potential direction of error and improvement date. If confidentiality prevents publication, retain the underlying evidence for assurance and disclose the limitation and governance process at the level permitted. Avoid false precision: rounding a modeled estimate to several decimal places does not make its underlying assumption more certain.
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Common failure modes to catch in review
- Calling a screening map a baseline measurement: explain its grid size, classification method and intended use.
- Using one score for unlike ecosystems: retain ecosystem-specific context and disclose what the aggregate hides.
- Treating missing supplier data as benign: record the omission and prioritize the value-chain stage with the greatest potential dependencies and impacts.
- Mixing years without explanation: show each observation period and state why combining them is appropriate.
- Ignoring licensing or access limits: note who can inspect the data and whether external assurance is possible.
- Changing methods without preserving history: keep prior versions and explain any break in trend.
- Reporting a gap without an owner: assign responsibility, budget and a review trigger.
Set rules for updating the baseline
Put the baseline date, observation period, source versions and recalculation triggers on the front page. Recalculate when a site is acquired or closed, a material supplier changes, a new survey changes the reference condition, a method is superseded, or a previously excluded pressure becomes material.
Annual refresh is a useful operating practice where feasible, especially for pressure and land-cover measures, but it is not a universal legal duty established by the guidance. Use a shorter interval for rapidly changing sites and a longer, justified interval for slow-changing ecological indicators. Keep prior versions so trends are not created by silently changing the method. A change log should identify the editor, date, reason, affected metrics and whether historical values were restated.
A practical first-year work plan
- Weeks 1–4: Approve the decision, boundary, reporting period, location list and data dictionary.
- Weeks 5–8: Build the source register, map interfaces with nature and identify dependencies, pressures and sensitive areas.
- Weeks 9–12: Select reference conditions and metrics; classify each conclusion as observed, modelled, proxy-based or inferred.
- Months 4–6: Create the risk and opportunity register, rank gaps and commission targeted fieldwork or improved datasets for the highest-priority interfaces.
- Months 7–9: Test the baseline with operational, procurement, finance and environmental specialists; document assumptions and quality checks.
- Months 10–12: Publish the baseline boundary, methods, findings, limitations and improvement plan; assign owners and dates for the next update.
The result is a working baseline that is transparent about what is known, useful for prioritising action and designed to become more precise as evidence improves. It is not a claim that the company has measured all biodiversity everywhere it operates.
Frequently Asked Questions
How do I build a biodiversity baseline when company data is incomplete?
Define the decision and boundary, locate sites and priority value-chain interfaces through TNFD LEAP, inventory internal and external evidence, choose a context-appropriate reference condition, label observations and assumptions, rank gaps by their potential to change decisions, and publish an improvement plan with owners and dates.
What data do I need for a biodiversity baseline?
At minimum, collect locations and activities, reporting period, ecosystem context, dependencies, pressures, available species or ecosystem observations, methods, spatial resolution, provenance, access conditions, assumptions and limitations. Add sector-specific metrics only where they answer a material question.
How should a company report biodiversity data gaps?
State the affected boundary or metric, why the evidence is unavailable, whether the interim result is observed, modeled, proxy-based or inferred, how the limitation could affect the decision, and what action, owner and date will address it. Do not report an unmeasured impact as zero.
How do I measure biodiversity when there is no single metric?
Use a small, decision-focused set. Consider ecosystem condition by ecosystem type and activity, species extinction risk as a placeholder where relevant, and ecosystem-service measures tied to the location and dependency. Explain definitions, units and boundaries because no single metric captures every dimension.
Should I commission field surveys immediately?
Not necessarily. First use existing company records and suitable spatial, modeled or public data to locate high-potential dependencies and impacts. Commission targeted surveys where uncertainty could change a material site decision, target, control or disclosure; compare their cost and proportionality with the decision at stake.
How often should the baseline be updated?
Set a justified interval based on the rate of ecological and operational change. Annual refreshes are useful where feasible, particularly for pressure and land-cover measures, but the guidance does not establish one universal legal timetable. Recalculate sooner after acquisitions, major supplier changes, new evidence or method changes.
The Bottom Line
A defensible biodiversity baseline is explicit about its benchmark, boundaries and uncertainty. Use TNFD LEAP to locate and assess the interfaces that matter, match metrics to material decisions, preserve provenance and access conditions, and turn every consequential gap into an owned, dated improvement action.
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