Biodiversity Intactness Index

The Biodiversity Intactness Index (BII) summarises the change in ecological communities in response to human pressures. The BII is an estimated percentage of the original number of species that remain and their abundance in any given area, despite human impacts.

The BII is averaged across areas (countries, regions or global) to give the remaining biodiversity across that area.  

The PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project calculates the BII using data from ecological studies conducted around the world. This data includes more than 54,000 species, encompassing not only birds and mammals, the groups most often used in biodiversity indicators, but also plants, fungi and insects. 

These studies have allowed us to infer a baseline of the number and diversity of species at near-undisturbed sites, and then to compare this baseline with biodiversity at sites with high human activity.

While each of these studies looked at different species groups in different areas using different sampling methods, we account for this variation in our statistical analysis.

The BII is derived from combining two models. The first model represents how human activity has influenced the total abundance of species in any one area. The second model analyses how similar each site's ecological community is to the near-undisturbed sites (this is known as the compositional similarity and includes what original species are present and what species are dominant).

Next, we combine each of these models with maps of human pressures, including land use change and intensification, human population growth and landscape simplification. This produces new maps of how abundance and compositional similarity have been affected by human pressures. Bringing these two maps together then gives us the BII: the percentage of the original ecological community that remains across an area. 

Assuming that the relationship between biodiversity and human activity does not change, stacking the human driver data from multiple years allows biodiversity projections to be made through history and into the future. 

The PREDICTS team at the Natural History Museum produced the BII by collating and analysing biodiversity data from ecological studies conducted worldwide. Using this data, we can understand how human activities - especially those related to land use change and intensification - are changing biodiversity.

The database includes around 58,000 species, encompassing birds and mammals, the groups most often used in biodiversity indicators, as well as plants, fungi, and insects. These studies have allowed us to infer a baseline of the number and diversity of species at near-undisturbed sites and compare this baseline with biodiversity at sites with high human activity.

By combining satellite imagery, data collected in the field and algorithmic modelling, PREDICTS can create a Biodiversity Intactness Index for land all around the world. The PREDICTS database is the most absolute of its kind and allows us to supply evidence-based assessments of the BII using robust, peer-reviewed methodology.

The BII is an estimated percentage of the original number of species and their abundance that remains in any given area, despite human impacts. The Index is an intuitive summary of local biodiversity and an indicator for granular and global biodiversity targets. Unlike other biodiversity indicators, we can project how BII will change in response to future management decisions. This can help businesses and policymakers to evaluate different management strategies and opportunities.

To this end, the BII has been included as an indicator within the post-2020 Global Biodiversity Framework and has been reported within the recent Living Planet Report 2022 and the IPBES: Global Assessment Report on Biodiversity and Ecosystem Services.

Biodiversity can only be managed if properly measured and modelled. The BII is an intuitive summary of local biodiversity and an indicator for global biodiversity targets. It is a rigorous approach to estimating biodiversity loss across an area using a combination of land use, ecosystem, species and population data to give a simple figure for 'intactness', that is, how much nature is left in a given area.

PREDICTS can also be used to project future global changes in BII based on varying scenarios of human impact, such as global policies on environmental regulation, technological changes, shifts in our diets, and changes in how we farm. BII can be applied consistently at all scales and capture the interaction between climate change and land-use-related drivers.

At a national or global level, BII modelling can help guide governments towards legislation or policies that create socioeconomic conditions that will help preserve or improve biodiversity. Locally, BII modelling can help organisations, businesses, or landowners to understand how different scenarios will impact biodiversity connected to specific locations, supply chains, or crops.

The PREDICTS database is the most comprehensive of its kind. It allows us to provide evidence-based assessments of BII using a robust, peer-reviewed methodology. The BII integrates information from a broader range of animal, plant and fungal groups than any other abundance indicator and is directly proportional to average abundance. The PREDICTS database is standout in its:

• Size - it includes 4.9 million data observations from over 48,000 sites in over 100 countries; and
• Taxonomic coverage - It is a taxonomically representative set of 58,000 plant, animal and fungal species

The PREDICTS database holds data from across all major terrestrial animal, plant and fungal groups. The database contains over 2% of all species named by science, with good coverage across most major groups. This broad representative coverage matters because different taxonomic groups don't respond the same way to human pressures. Most other biodiversity indicators are based on a single taxonomic group, such as vertebrates. Basing an indicator on only one group risks giving a misleading picture of the true state of nature.

Unlike other indicators, the BII stands out in that:

• It links to the Planetary Boundary Framework and can capture the interaction between climate change and land-use-related drivers.
• It is a 'leading indicator'. Unlike most other indicators, it looks forward and can model under future scenarios.
• It can be applied easily and consistently at any spatial scale, anywhere (applicability globally/nationally/at scale of company's landholding), meaning it can be used to test for adequacy of plans.
• It is a transparent, robust, peer-reviewed model.
• It places all countries fairly on the same scale, where 100% means a pristine ecosystem while 0% is entirely depleted. This contrasts with other abundance indicators that might show a stable or even improving species abundance trend, which hides the widespread historical loss of animal and plant populations in countries such as Europe and the UK.
• It can also be used as a headline indicator to monitor ecosystem intactness when modelled at a finer resolution.
• It is also a suitable headline indicator for species abundance.
• It continually improves accuracy and reliability by increasing the data it draws upon and adjusting models for specific scenarios.

The database continues to grow apace. Since the 2016 public release of the PREDICTS database, over 20,000 more sites have been added, and we are closing in rapidly on 5 million records. A bigger database allows better, richer models to be fitted, improving our ability to estimate and project BII.

The BII is continually improving its accuracy and reliability by increasing the data it draws upon and adjusting models for specific scenarios. It is also incorporating higher-resolution imagery. In addition, pilot cases and proofs of concept are underway to fine-tune use cases and further automate processes.