The biological diversity of ecosystems, species and genes across the locations where we operate is complex and varied as is the status and productivity of these assets in supporting people, nature and society. A standardised methodology for identifying important biodiversity and ecosystem features across these biogeographic regions (areas of common climate, geology, landform, native vegetation and species) is important for managing our stewardship of nature. 

Different approaches to identifying key biodiversity and ecosystem features result in varied data and methods. To address this complexity, we developed our own internal approach to provide globally consistent and scalable results using a combination of scientifically credible global datasets. We built upon initial research projects by the CSIRO and 2ROG, an environmental consultancy, to break down the methodology into simplified, repeatable steps and production-ready workflows.   

The resulting dataset adopts a definition of ‘Important Biodiversity and Ecosystems’ (IBE) and implements that definition using a spatially explicit approach to mapping these natural assets across our sites and surrounding 50-kilometre area of influence, in a consistent and repeatable format. A spatially explicit approach involves analysing spatial data through a Geographic Information System to develop interactive maps and visual analytics. 

Our 2030 Healthy environment goal is to create nature-positive¹ outcomes by having at least 30 per cent of the land and water we steward² under conservation, restoration or regenerative practices. In doing so we focus on areas of highest ecosystem value both within and outside our own operational footprint, in partnership with Indigenous peoples and local communities. Our approach to identifying opportunity areas where conservation, restoration and/or regenerative practices could be applied, is to prioritise areas based on high ecosystem value within our non-operational area, as determined from the spatial data layer on IBE. 

Methodology and configuration 

A weighted overlay analysis was used to create our spatial data layer on IBE. It combines and calibrates reputable global scale datasets representing key elements linked to ecological (biodiversity) and socio-economic (ecosystem service) outcomes, using internal subject matter expert opinion to inform the weightings of datasets that would identify the highest priority IBE locations for each geographic area. 

This standardised, simple but science-based methodology allows for continuous improvement as new datasets are developed and insights into key biodiversity and ecosystem predictors emerge. It also supports a second phase of the IBE mapping, where high resolution asset-centric datasets and geospatial intelligence can be added to the model on demand for higher resolution nature-related insights. 

Table 1: IBE input datasets and estimated update frequency 

Footnotes: 

1. Nature-positive is defined by the Taskforce on Nature-related Financial Disclosures Glossary version 1.0 as ‘A high-level goal and concept describing a future state of nature (e.g. biodiversity, ecosystem services and natural capital) which is greater than the current state’. We understand it to include land and water management practices that halt and reverse nature loss – that is, supporting healthy, functioning ecosystems. We are monitoring the evolving external nature landscape, including developments in nature frameworks, standards and methodologies and in definition of the global nature ambition.  

2. Excluding areas we hold under greenfield exploration licences (or equivalent tenements), which are outside the area of influence of our existing mine operations. 30 per cent will be calculated based on the areas of land and water that we steward at the end of FY2030. For more information refer to the BHP ESG Standards and Databook 2025.