Can we measure biodiversity?
Can we measure biodiversity impacts at company level? Some argue that measuring biodiversity is too complex, claiming we are doomed to rely on qualitative frameworks and that quantifying Nature is unachievable. At darwin, we see things differently. Let's explore why this is the case.
What does “measuring” biodiversity impacts mean for a company?
Aligned with the definition of the planetary boundary for biodiversity, the state of nature has to be measured considering at least two of its three main dimensions: Ecosystems and Species. Genetic diversity is still hardly accounted for.
The condition and extent of ecosystems
Extent: the area coverage of a particular ecosystem, usually measured in terms of spatial area (hectares or km2).
Condition: the quality of an ecosystem measured by its living and non-living characteristics.
Species population and extinction risk
Population size: changes in the number of individuals of a species within an area.
Extinction risk: threat status of a species and how activities/pressures may affect the threat status.
Source: Components of State of Nature measurement - darwin
Therefore, an impact on biodiversity can be defined as a change in the state of nature. Those changes in state affect both ecosystems and species. These changes can be positive (a gain in biodiversity) or negative (a loss of biodiversity).
How have businesses been measuring their impacts on biodiversity so far?
Historically, approaches have been confined to “direct” measurement based on field data: it involves measuring biodiversity impacts by counting species and individuals in a location, which, despite its accuracy, is costly, time-consuming, and may be influenced by external factors such as weather and season. Due to these limitations, this approach only includes impacts on direct operations (Scope 1) and thus sectors with high direct impacts (e.g. Mining).
However, the landscape is rapidly evolving. Recent years have seen the development of new footprint tools enabling more scalable assessments, based on quantitative modeling, to gauge a biodiversity footprint, including Scope 3 (mostly upstream).
The footprint is determined through evaluating the potential impact. This frequently stems from how an economic activity contributes to “pressures” leading to biodiversity decline. The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) refers to 5 main pressures, namely ecosystems use change, pollution, climate change, direct exploitation of resources and invasive species. These pressures are expressed in metrics such as m² of land used or tons of pollutant emitted. These pressure points can be collected directly or estimated with models when data access is limited. Pressures are then converted into "state indicators" of biodiversity via a sequence of models.
In most footprint approaches, pressure points are aggregated into only single ecosystem condition metric such as the 'Mean Species Abundance' (MSA) based on the GLOBIO model and the 'Potentially Disappeared Fraction of Species' (PDF) used in most Life Cycle Analysis models such as RECIPE.
Source: Simplified biodiversity footprint model - darwin
What metrics can businesses use to measure their biodiversity impacts - aggregated or not?
Can we truly envision an aggregated indicator like tonnes of CO2 equivalent for biodiversity? As discussed, this approach is considered by some footprint tools where biodiversity is measured in MSA.km2 or PDF.km2. Essentially, both metrics reflect the changes in ecosystem integrity relative to a pristine / undisturbed reference state.
These aggregated metrics hold value because they standardise results, facilitating benchmarking of a company's performance within a sector or potentially arbitrating between two technical options for a new project - yet this remain very theoretical.
However, institutionalising such indicators also poses risks and might result in misguided decisions:
Business owners may find these aggregated metrics difficult to understand and connect with actionable steps.
The models have low spatial precision due to their use of global pressure–impact relationships.
At darwin, we recognise that there is no one-size-fits-all metric. It’s important to assess which metrics are most appropriate for a given use case: it’s all about considering trade-offs between practicality, completeness, detail and scaleability (according to the Taskforce on Nature-related Financial Disclosures framework).
As many companies do not yet have traceability to the production sites for the commodities they use, in these cases, pressure-based approaches can provide approximate, first-tier assessments of risk, albeit with caveats, as mentioned before. Yet they need to be combined with species metrics such as STAR (from the IUCN) as they only capture ecosystem condition.
The entire aim of our data model is to modelise the 5 IPBES pressures for a given business, and to assess core indicators per pressure (= actionnable factor that provides a simple way to measure performance). As of now, we have decided to remain agnostic when it comes to aggregated metrics (i.e. MSA, or could be other such as ESII, PDF, BII, etc.).
At darwin, we assist companies & developers in measuring and managing biodiversity impacts and dependencies. Interested in learning more? Contact us.
