Consistent Approach

To provide some consistency and comparability of biodiversity measures between projects, the NFS recommends use of Ecometrica’s Normative Biodiversity Metric (NBM) in addition to any other methods that a project wishes to use.  An NBM map, as described below should be developed and improved over the course of the project. In the early stages of project development a broad overview of the biodiversity status of the project area should be achieved from available vegetation maps, satellite images and local information. As the project progresses the project should improve the quality of biodiversity information to identify areas where biodiversity is under threat. This is likely to be closely related to threats to carbon stocks.

 Transparency of Evidence and Assumptions

To maintain a transparent account of the evidence and assumptions used throughout the quantification of biodiversity, methods, dates, locations and identities of people undertaking measurements and estimates should be recorded.

 Normative Biodiversity Metric

The Normative Biodiversity Metric (NBM) is a practical method used to provide an assessment of the biodiversity value of any given area under ownership or management control. The NBM is similar to the concepts of habitat hectares and mean species abundance which are also designed to provide quantified information on the biodiversity value of an area.

The NBM is designed to assess the habitat quality of all the land within the project zone, providing a quantified rating of the biodiversity value of the Natural Capital Credits. When these credits are sold on the NFS Registry, potential buyers will be able to use this information on the NBM score of the Natural Capital Credits to inform their buying decision. This assessment process may be used to verify that the project is meeting the ‘no net loss’ biodiversity commitment of NFS projects.

Step 1: Identifying Eco-Floristic Zones

The metric is based on a scale of ecosystem intactness specific to the ecosystems within the project area. The first step in the assessment process is therefore to define the eco-floristic zones in which the project is taking place and to and identify examples of pristine habitats.

The FAO (Food and Agriculture Organisation) eco-floristic zones definitions are a useful source with which to identify the different habitats present within each eco-floristic zone. Other sources which provide similar information are the ‘Bailey Eco-regions of the continent’ map, or the WWF’s terrestrial eco-regions map.

This step may also be done in conjunction with local or regional ecological knowledge. For example, within the tropical rainforest eco-zone, the FAO analysis suggests 6 different habitats which may be typical to this eco-floristic zone as a result of variations in the meteorology, hydrology or altitude within the zone.

Step 2: Defining the NBM Scale

Having characterised examples of pristine habitats within the project area, the NBM assessment scale should be produced to characterise intermediate levels of impact, down to “Artificial surface”, which is given zero in the NBM classification system. Using the generic descriptors of each category, the eco-floristic zone specific scale should be produced. Identifying the likely occurrences of habitats within the eco-floristic zone is important for simplifying the classification process.

Below is an example of a completed pristineness scale for a project operating in the ‘tropical rainforest’ eco-floristic zone:

Step 3:  Classifying Habitat Zones

The next step is to classify the habitat zones into the pristineness categories of the table above. Initially, remote sensed images may be used to identify the distinct habitat zones within the project area. Artificial areas (0) and monoculture areas (1) should be straightforward to identify from remote sensing in most cases according to the designed scale.

As a project develops, the initial habitat map should be improved by infilling gaps and uncertainties through field surveys:

  • Surveys of areas which were identified as having a high degree of ecosystem intactness at the remote imaging stage, to establish whether there are any signs of hunting, or resource harvesting in the area which has affected the ecosystem function – if these are found the area should be considered a minimal impact area (4) – if these are not present, the area should be considered a pristine area (5).
  • Surveys of areas initially thought to be impacted (3) and converted (2) to establish that the initial assessment was correct. For areas to be considered converted, the original land cover must have been removed and replaced with another land cover. An impacted area still retains the initial land cover, but human activities have significantly degraded the land – these areas should have restoration potential, whereas converted areas may be more difficult to restore, and take longer to return to a high degree of intactness.

Step 4:  Endangered Species Presence

The next stage is to assess and document presence of endangered species in project areas. The project will have more value for biodiversity if the conservation of natural forest also contributes to the protection of endangered species – the IUCN red list classifications will be used to define what is and isn’t an endangered species – initially mammals will be used, because the red list data is most complete for mammals.

For each endangered mammal species present within a distinct habitat zone, the NBM score for that area will be subject to an uplift of 0.5, up to a maximum uplift of 5. However, the NBM scores for ecosystem intactness and endangered species presence should be reported separately.

Initially, the NFS will only consider the distribution of endangered mammals (in very small project areas, the presence of amphibians may be more indicative of localised biodiversity value, because amphibians do not travel over large ranges, so can be more indicative of ecosystem function), although where a project wishes to use an alternative ‘endangered species’ indicator to mammals, justification for this can be given.

Information on which threatened, endangered, critically endangered species are present in the area may already be available if the area has been subject to regular ecological surveys from other organisations; if this data is considered reliable, it may be used to complete the NBM endangered species assessment.  If such information is not available, it is recommended that the project first uses the IUCN red list species distribution maps to get an initial impression of which endangered species are likely to be present within the project area.  However, if this data is imprecise and general, the project should then verify and evidence the presence of these endangered species within the project area. Where species which move over large areas are spotted within the project area, it can be assumed that they are present within all of the project area which is of a similar type of habitat. Only areas of degraded, converted, monoculture or artificial land should be excluded from the endangered species uplift to the NBM score in this case.

Step 5:  Monitoring NBM Scores

The project should provide information on the scores for both pristineness and endangered mammals. This information should be monitored over time with a report on progress included in the annual project report.


Alkemade, R et al. 2009. Globio3: A Framework to Investigate Options for Reducing Global Terrestrial Biodiversity Loss. Ecosystems 12(3), pp. 374-390.

Bailey, R.G. and H.C. Hogg, 1986. A world ecoregions map for resource reporting. Environmental Conservation,13, (3) pp. 195-202.

Food and Agriculture Organisation of the United Nations, 2000. Global Ecological Zones. Available at:

Jarrett, D, 2011. Assessing Organisational Biodiversity Performance. Available at:

Olson, D et al., 2001. Terrestrial Ecoregions of the World: A New Map of Life on Earth. Bioscience, 51, (11). Available at:

Parkes, D et al., 2003. Assessing the quality of native vegetation: The ‘habitat hectares’ approach. Ecological  Management & Restoration, 4.