Nature, Biodiversity and Environmental Impact
Level 2 — Biodiversity Net Gain · SBTi FLAG Targets · EUDR Due Diligence

This unit covers the policy framework for mandatory biodiversity net gain in England and the structure of the UK BNG Metric 4.0, the standardised calculation tool for BNG assessment. The Environment Act 2021 requires all planning applications in England (with specified exemptions) to demonstrate a minimum 10 percent net gain in biodiversity units from the pre-development baseline. The BNG requirement applies to the development site itself (on-site gain) and to any off-site habitat provision (off-site gain through habitat bank purchase or statutory credits as a last resort). The 10 percent minimum applies to the overall unit total; developments that create certain habitat types may need to achieve higher percentages for those types where they are declining.

The BNG Metric 4.0 is an Excel-based calculation tool published by Natural England that calculates biodiversity units as the product of habitat area (hectares), habitat condition score (a 1 to 6 scale reflecting ecological condition), and habitat distinctiveness score (a 0 to 6 scale reflecting the rarity and ecological value of the habitat type). The metric distinguishes area habitats (measured in hectares) from linear habitats (hedgerows, measured in kilometres) and watercourse habitats (rivers and streams, measured in kilometres). The unit covers the metric structure, the data inputs required for each habitat type, and the calculation procedure, establishing the methodology foundation for the calculation exercises in Units 2.1.2 and 2.1.3.

This unit covers the pre-development habitat assessment and the baseline biodiversity unit calculation for the case development site. The habitat assessment requires a field survey following the Biodiversity Net Gain Assessment Methodology (BNGAM), which specifies the habitat classification system (Phase 1 Habitat Survey combined with UK Habitat Classification), the condition assessment approach for each habitat type (using the Natural England condition assessment criteria), and the survey timing requirements (surveys must be conducted at the appropriate season for the habitat types present).

The baseline calculation applies the BNG Metric 4.0 to the case site's habitat survey data, calculating the biodiversity unit value for each distinct habitat type: the area of each habitat (from the site plan), the condition score for each habitat (from the field survey data), the distinctiveness score for each habitat type (from the BNG Metric 4.0 habitat distinctiveness table), and the resulting biodiversity units per habitat type. The total pre-development biodiversity unit value is the sum across all habitat types. The worked example uses a case site with five distinct habitat types, including improved grassland (low distinctiveness, low condition), scrub (medium distinctiveness, moderate condition), and a fragment of ancient woodland (very high distinctiveness, good condition), providing variety in the calculation outcomes.

This unit covers the post-development biodiversity unit calculation and the net gain assessment that determines whether the on-site provision meets the 10 percent mandatory requirement. The post-development calculation applies the same BNG Metric 4.0 methodology to the proposed habitat condition after development, accounting for: habitat types lost (areas converted from natural habitat to built development, which receive a post-development unit value of zero), habitat types retained (areas of existing habitat within the development boundary that are not disturbed), habitat types enhanced (areas where the developer proposes to improve habitat condition from the baseline, increasing the condition score), and new habitats created (areas where the developer will create habitat types not present in the pre-development baseline, such as new wetland or new species-rich grassland).

The net gain calculation subtracts the total post-development unit value from the pre-development unit value to determine the net gain or deficit. If the post-development value exceeds the pre-development value by 10 percent or more, the mandatory on-site net gain requirement is met. If the net gain falls below 10 percent, the unit deficit must be met through off-site provision. The unit works through the net gain calculation for the case site, producing a scenario where the on-site provision achieves only 4 percent net gain due to the loss of ancient woodland, requiring 6 percent worth of off-site unit provision to meet the mandatory requirement. This outcome drives the habitat banking analysis in Units 2.1.4 and 2.1.5.

This unit covers the supply side of the BNG offset market, evaluating habitat banking as a mechanism for meeting the case development's off-site unit requirement. The supply analysis covers the habitat types available for off-site purchase in the case site's local strategic significance zone (the geographic area within which off-site units must be sourced for most habitat types under BNG policy, to ensure ecological connectivity benefits are delivered near the impact site). The unit covers the National Register of Off-Site Gains (maintained by Natural England), the habitat bank registration process, and the typical unit prices for the habitat types most commonly traded in the BNG market.

Additionality for habitat banks requires that the habitat enhancement would not have occurred without the BNG funding: a farmer who was already managing a field margin under an agri-environment scheme cannot register the same field as a BNG habitat bank because the conservation benefit was already funded. The permanence requirement specifies that BNG legal agreements must run for a minimum of 30 years, with monitoring and reporting obligations to verify that the habitat condition score is maintained. The unit covers the legal agreement structure, the monitoring regime (typically annual vegetation surveys and five-yearly detailed ecological assessments), and the remediation obligation if condition scores decline below the contracted level.

This unit covers the design of a habitat bank project for a landowner seeking to generate biodiversity units for sale to developers, and the comparative analysis of the UK BNG Metric 4.0 methodology against emerging EU biodiversity credit approaches. The habitat bank project design covers: the baseline habitat survey (same methodology as Unit 2.1.2, applied to the habitat bank land parcel), the enhancement intervention plan (specifying the habitat creation and management activities that will improve the condition score from baseline to target), the target condition score calculation (the biodiversity units that will be generated by the enhancement, which determines the revenue potential of the project), the legal agreement structure (the 30-year habitat enhancement and maintenance agreement between the landowner and the local planning authority or BNG registration body), and the monitoring programme design (the annual and five-yearly surveys required to verify condition score maintenance).

The EU comparison covers the EU Nature Restoration Law's binding national restoration targets, the EU's work on developing a biodiversity metric for use in offsetting contexts (referenced in the EU Biodiversity Strategy for 2030), and the emerging national BNG frameworks in EU member states (Germany, France, and the Netherlands each have habitat compensation systems with different methodologies). The comparison identifies the structural similarities across approaches (habitat-based unit calculation, additionality test, permanence obligation, and monitoring requirement) and the differences (metric calibration, governance architecture, and market structure). The capstone deliverable is the complete BNG calculation for the case development site, the off-site unit requirement specification, and the habitat bank project design document.

This unit covers the identification and scoping of FLAG emissions and the assessment of whether a company meets the 20 percent threshold requiring FLAG-specific targets. FLAG emissions are defined by the SBTi as the GHG emissions from Agriculture, Forestry, and Other Land Use (AFOLU) activities, including: deforestation and land conversion (CO2 from the conversion of natural land to agricultural or industrial use), enteric fermentation from ruminant livestock (CH4 from cattle, sheep, and other ruminants), manure management (CH4 and N2O from the treatment and storage of livestock manure), rice cultivation (CH4 from flooded paddy fields), agricultural soil management (N2O from synthetic and organic fertiliser application and crop residue decomposition), and net CO2 flux from managed forests (emissions from harvesting minus sequestration from forest growth).

The 20 percent threshold assessment requires a complete Scope 1, 2, and 3 GHG inventory that includes AFOLU emissions. The unit covers the calculation approaches for each AFOLU category at the inventory level: Tier 1 and Tier 2 approaches from the IPCC 2019 Refinement to the 2006 Guidelines for National Greenhouse Gas Inventories provide the default emission factors applicable to company-level AFOLU inventories. For most food and agriculture companies, the threshold assessment will confirm that FLAG applies; the exercise is most complex for diversified conglomerates where AFOLU activities are one of several business segments. The unit works through the threshold assessment for the case agribusiness and food processing company.

This unit covers the SBTi FLAG guidance structure and the three target types available. The mandatory FLAG target covers land-use change emissions (the largest source for most agricultural companies) and biogenic methane and nitrous oxide from agricultural production. The target is expressed as an absolute emission reduction or, for companies using the sector-specific pathway approach, as an emission intensity reduction benchmarked to the SBTi FLAG sector pathway for the company's primary agricultural activity. The mandatory target must be aligned to limiting global warming to 1.5 degrees Celsius, requiring a minimum absolute emission reduction consistent with the SBTi FLAG modelling.

The optional land sequestration target covers biological carbon removals from improved land management: agroforestry expansion, grassland management improvements, soil organic carbon enhancement, and reforestation of degraded agricultural land. The land sequestration target must meet the SBTi's additionality and permanence requirements for removal targets: the removals must be additional to what would have occurred without the target, and the sequestration must be permanent (not subject to easy reversal through deforestation or land degradation). The optional food security target allows companies with significant food production exposure to demonstrate that their emission reduction targets do not compromise food security in the markets where they operate, using the SBTi's food security assessment methodology. The unit covers the conditions under which each optional target type is warranted and the workbook submission requirements for each.

This unit covers the land-use change target-setting calculation using the SBTi FLAG workbook's Annex B land management scenario modelling. Land-use change emissions arise when natural land (forest, grassland, or wetland) is converted to agricultural or other productive use, releasing the carbon stored in the vegetation and soil. Conversely, the restoration of agricultural land to natural vegetation sequesters carbon. The Annex B modelling tool calculates the net land-use change emission trajectory for the company's sourcing geography under different deforestation rate scenarios.

The Annex B modelling inputs cover: the company's sourcing geography (the countries and regions from which it sources agricultural commodities), the current deforestation rate in each sourcing geography (from the SBTi-provided Global Forest Watch deforestation rate data), the commodity linkage to deforestation (the proportion of deforestation attributable to the commodities the company sources), and the deforestation reduction commitment (the company's commitment to reduce deforestation in its supply chain to zero by a specified date, typically 2025 or 2030). The model calculates the cumulative CO2 reduction from achieving zero deforestation, which forms the land-use change component of the FLAG target. The unit works through the modelling for the case company sourcing palm oil and soy from high-deforestation-rate regions.

This unit covers the target-setting calculation for biogenic agricultural emissions (enteric fermentation, manure management, rice, and agricultural soils) using the SBTi FLAG sector pathway benchmarks. The sector pathways specify the required emission intensity trajectory for each agricultural sub-sector, expressed as GHG emissions per unit of agricultural output (for example, kg CO2e per kg of beef protein, or kg CO2e per hectare of cropland). The intensity targets allow agricultural companies to grow their output while reducing emission intensity, rather than requiring absolute emission reductions that would constrain food production.

The unit covers the intensity target calculation for three agricultural sub-sectors: cattle rearing (using the SBTi FLAG cattle pathway benchmark, which requires a 30 percent reduction in emission intensity per kg of beef protein by 2030 from a 2018 baseline), rice cultivation (using the wetland rice pathway benchmark, which requires a 30 percent reduction in CH4 emissions per tonne of rice by 2030), and synthetic fertiliser use (using the cropland pathway benchmark, which requires a 50 percent reduction in N2O emissions per tonne of crop nitrogen applied by 2030). The worked calculation produces the science-based target statement for each sub-sector and integrates them into the complete FLAG target framework for the case company.

This unit covers the design of the data collection and monitoring programme for tracking FLAG target progress and the interaction between FLAG targets and ESRS E1 and E4 disclosure obligations. The monitoring programme covers three data streams: land-use change monitoring (using satellite-based deforestation alert systems such as Global Forest Watch Pro or Earthworm Foundation's supply chain traceability tools to track deforestation events in the company's sourcing geography on a near-real-time basis), agricultural emission accounting (annual calculation of enteric fermentation, manure, rice, and soil N2O emissions using the IPCC Tier 1 or Tier 2 approach applied to the company's agricultural production data), and sequestration monitoring (annual measurement or modelling of carbon sequestration from improved land management activities under the optional land sequestration target).

The ESRS E1 interaction covers the reporting of FLAG target progress in the ESRS E1-4 target disclosure: the FLAG target must be disclosed with the same mandatory data points as any other ESRS E1 GHG target (base year, base year emissions, target year, reduction percentage, methodology reference, and science-based alignment evidence), with the additional FLAG-specific note that the target covers AFOLU emissions. The ESRS E4 interaction covers the biodiversity co-benefits of FLAG target delivery: zero deforestation commitments contribute directly to ESRS E4 material topic disclosures on land-use change and biodiversity loss in agricultural supply chains, and the company can cross-reference its FLAG target commitment in the ESRS E4 action section. The capstone deliverable is the complete FLAG workbook submission for the case company, covering the land-use change and agricultural emission target sections, the monitoring programme design, and the ESRS interaction mapping.

This unit covers the EUDR regulatory architecture, the definitions of operator and trader, and the scope of obligations for each. Operators are natural or legal persons who place regulated products on the EU market for the first time or export them; they bear the full due diligence obligation. Traders are natural or legal persons in the supply chain other than operators who make regulated products available on the EU market; they have simplified obligations (collecting and retaining information about who supplied the product and to whom it was sold, and verifying that the supplier has completed due diligence). The unit covers the practical determination of operator versus trader status for a commodity trading company operating at different stages of the supply chain.

The due diligence obligation for operators covers three steps: information collection (collecting the geolocation, volume, country of production, and supplier details for every consignment), risk assessment (assessing the risk that the product was produced on deforested or degraded land after 31 December 2020, using the country benchmarking and the commodity-specific risk criteria), and risk mitigation (implementing measures to reduce the risk to negligible before placing the product on the market). The due diligence statement is submitted to the EU Information System before the product is placed on the market; the reference number must be included in all commercial documents accompanying the product through the supply chain. The unit covers the EU Information System access and submission process and the enforcement powers of competent authorities.

This unit covers the geolocation data requirement, which is the most operationally complex element of EUDR compliance for commodity traders with large, fragmented supply chains. EUDR requires that operators collect the geolocation (GPS coordinates or polygon) of all plots of land where the regulated commodities were produced. For cattle, this means the farm coordinates and the coordinates of all grazing areas used; for cocoa and coffee, the smallholder farm plot coordinates; for soy, the field-level coordinates; for timber, the forest management unit boundaries. The precision requirement is sufficient to verify against satellite imagery that the land was not deforested after 31 December 2020 and the production date of the specific consignment.

The unit covers the practical data collection approaches for three supply chain types. For direct procurement from large commercial farms (common in soy and palm oil), the operator can obtain georeferenced field boundaries from the farm management system. For supply chains involving aggregators who blend product from many smallholder farms (common in cocoa and coffee in West Africa and Southeast Asia), the operator must obtain geolocation from each aggregator, who in turn collects it from each smallholder. For complex cattle supply chains (common in Brazil, where cattle may be raised on multiple farms before slaughter), the operator must trace the cattle movement records through the Brazilian SISBOV system to identify all farm coordinates in the animal's history. The unit covers the technology platforms available for each approach (Starling, Source, Earthworm Foundation's supply chain mapping tools) and the data quality requirements.

This unit covers the EUDR country benchmarking system, under which the European Commission classifies countries as low risk (where negligible risk due diligence applies), standard risk (where normal due diligence applies), or high risk (where enhanced due diligence applies including audits of suppliers). The benchmarking assessment uses deforestation rate data, the coverage and effectiveness of domestic legislation protecting forests, the use of satellite monitoring, and the country's governance quality. The unit covers the benchmarking criteria and the expected classification methodology, noting that content teams should update this unit when the benchmarking decisions are published.

The unit also covers the commodity-specific risk factors that apply within each country classification: even in a low-risk country, certain commodity types or production regions may present elevated risk based on historical deforestation patterns. The risk classification exercise uses the case commodities (soy from Brazil, cocoa from Cote d'Ivoire, and timber from a certified forest management unit in Indonesia) and applies the country classification and commodity risk factors to determine the due diligence intensity required for each. The exercise illustrates that Brazil is likely to be classified as standard risk given its deforestation monitoring capability and recent deforestation trend reversal, while Cote d'Ivoire may be classified as high risk given the documented extent of cocoa-driven deforestation in protected areas.

This unit covers the deforestation risk assessment and the risk mitigation measures required for non-negligible risks. The risk assessment evaluates whether each consignment was produced on land that was deforested or forest-degraded after 31 December 2020, using three inputs: the geolocation data from Unit 2.3.2, the satellite-derived forest cover change data (from Global Forest Watch or Copernicus Land Monitoring Service), and the country and commodity risk classification from Unit 2.3.3. The risk assessment applies a forest cover change layer to each geolocated plot to determine whether forest cover was present before 31 December 2020 and whether any forest cover loss has occurred since that date. Plots with post-2020 forest cover loss fail the EUDR compliance check and require either exclusion from the consignment or risk mitigation.

Risk mitigation covers the measures taken to reduce a non-negligible risk to negligible: supplier substitution (replacing a non-compliant supplier with a compliant one), conditional sourcing (requiring the supplier to demonstrate compliance before accepting further consignments), and satellite monitoring commitment (entering into an agreement with the supplier requiring ongoing satellite monitoring of the production area and corrective action if deforestation is detected). The unit covers the documentation requirements for each mitigation measure and the evidence that the mitigation has been effective (no deforestation detected after the mitigation measure was implemented). The risk assessment and mitigation documentation is the core of the due diligence statement.

This unit covers the preparation of the EUDR due diligence statement and the design of the ongoing compliance monitoring system. The due diligence statement covers five elements: the operator declaration (confirming that the operator has conducted due diligence in accordance with EUDR requirements), the product and consignment details (the commodity type, volume, production country, and production period), the geolocation information (the plot coordinates or a reference to the geolocation data held by the operator), the risk assessment summary (the country classification applied, the risk factors assessed, and the overall risk determination), and the mitigation measures taken (for any non-negligible risks, the specific mitigation implemented and the evidence of effectiveness). The statement is submitted through the EU Information System before the product enters the EU market.

The ongoing compliance monitoring system covers: the annual geolocation data refresh cycle (confirming that the sourcing locations have not changed and that no new deforestation has occurred since the prior year's assessment), the deforestation alert monitoring (using Global Forest Watch Pro or equivalent to receive real-time alerts when deforestation events are detected within or near the sourcing plots), the high-risk supplier audit programme (for sourcing from high-risk country classifications, requiring periodic third-party audits of suppliers to verify compliance), and the corrective action process (the procedure followed when a deforestation event is detected, covering supplier notification, investigation, and the decision to continue or suspend sourcing while the situation is investigated). The capstone deliverable is the complete EUDR due diligence statement for the case commodity and the ongoing compliance monitoring system design.