What is the Biodiversity Intactness Index?

The Biodiversity Intactness Index (BII) measures biodiversity change using abundance data on plants, fungi and animals worldwide. The Index shows how local terrestrial biodiversity responds to human pressures such as land use change and intensification.

Biodiversity indicators such as the BII are essential tools for understanding, monitoring and communicating biodiversity changes and tracking our progress towards goals. The Index uses the most comprehensive evidence base of its kind alongside robust, peer-reviewed methodology.

How does it work?

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.

Why is understanding biodiversity important?

Earth is changing quickly in response to human activities. Biodiversity loss is one of the clearest warning signs that we are facing a planetary emergency. An estimated USD$44 trillion of economic value is threatened by biodiversity declines and ecosystem collapse – equal to over half of the world's total GDP (World Economic Forum, 2021). At the same time, moving to nature-positive investments offers opportunity. To date, there have been two major difficulties that make it hard for businesses and policymakers to think about biodiversity loss:

• How to measure something as complex as biodiversity (there is no simple, granular and universal biodiversity metric).
• How to use that evidence to inform management decisions.

The Natural History Museum's work on Biodiversity Indicators offers solutions to both these problems.

How can the BII be used?

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 and the Biodiversity Trends Explorer (BTE) 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.

What makes the BII stand out?

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.

Working with businesses and policymakers

Policymakers and businesses are already using our Biodiversity Indicators for a wide range of services. Here are just some of the applications of our work:

• Mapping BII across regions of interest.
• Producing reports of the intactness and uniqueness of a region's biodiversity.
• Inferring how BII has changed over recent years in areas of interest.
• Projecting changes in biodiversity under future land use and management.
• Modelling and projecting impacts of land usage and other pressures on biodiversity as a whole or for particular groups.
• Comparing dimensions of biodiversity, e.g., taxonomic, functional and phylogenic diversity.
• Comparing biodiversity impacts of crops.
• Screening policy options for biodiversity consequences.
• Developing goal-seeking scenarios while integrating with economic models to achieve biodiversity.
• Testing the likely impacts of specific management decisions aimed at increasing biodiversity.

To find out more, email the team.

Case Studies

Policymakers and businesses are already using our Biodiversity Indicators for a wide range of services. Here are a couple of examples of our work.

How is the BII evolving?

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.