Discussion
Our approach provides a science-based way to quantify the impacts of the footprint of physical assets on multiple ecosystem service and biodiversity metrics. This approach extends environment-related measures for ESG with ecosystem service metrics. It is scalable from assets to companies to portfolios, and across sectors, and thus can be used to inform a range of policy, corporate, and investor decisions. It is able to differentiate impacts based on assets’ sizes and locations.
This approach accounts for the loss of ecosystem services and biodiversity attributable to the loss of nature directly from physical assets, similar to Scope 1 carbon emissions32. For some sectors, such as mining, these direct impacts may represent a substantial portion of a company’s impact on nature. For other sectors, especially those with extensive supply chains, expanding the assessment to account for supply chain impacts will be critical to capturing the full extent of a company’s impact. Here, there is great potential to integrate our approach with methods from supply chain analysis33 and spatial Life Cycle Assessment (LCA)19.
Further refinement of our approach could also allow for differentiation in impacts among and within activity types. For example, an agricultural field and a parking lot of equal size would have different impacts due to differences in the maintenance of vegetation, soil permeability, addition of fertilizers, and so forth. In addition, assets of the same type and size may differ in their use of best management practices or nature-based solutions, and thus differ in their impacts. Utilities and energy companies, for example, are often stewards of large land areas, and the management of ecosystems in and around solar facilities and power transmission lines can lead to substantial variation in impact and even the potential to create gains relative to current conditions34,35. These differences could be accounted for within our approach by adjusting the ecosystem service or biodiversity changes attributed to assets that employ certain sustainable practices.
Finally, the sustainability field would benefit from the development of common standards for defining baseline and impact scenarios so that assessments could attribute impacts in a robust, intercomparable way. Our approach currently uses potential natural vegetation as the baseline conditions. Some urban areas have been developed for many decades, if not centuries or millennia. Attributing full loss of nature at these sites to the current asset owner could disincentivize activities in existing urban areas and perversely incentivize new greenfield development. An alternative approach could consider urban areas fixed and focus on impacts outside historically developed areas14, use sites’ restoration potential as a reference scenario36, or adjust impacts by the current population density surrounding the site, although each approach would come with its own methodological challenges and uncertainties.
We focus on accounting for impacts stemming from the loss of ecosystems, filling an important gap in existing sustainability and ESG approaches. Although accounting for pollution contributed directly by assets (e.g., fertilizer runoff from agriculture, mine tailings, the release of chemicals or air pollution) is beyond the scope of the current analysis, this would be a valuable future addition. Integrating estimates from existing LCA approaches of pollution generated by assets19,37 with the spatially explicit modeling of impacts to people in our approach here could advance this aspect.
By using open-source models and drawing on the growing accessibility of asset location data and high-resolution satellite imagery, we were able to analyze the impacts of over 2,000 companies and nearly 600,000 assets without relying on company-reported information on ecosystem service and biodiversity impacts. This approach can provide corporate ESG metrics focused on impacts to nature with greater transparency and the potential for external verification. At the same time, data availability remains a challenge: asset-level data is available primarily for publicly traded companies, which represent only a fraction of corporate activities, and even for these companies, data is incomplete38–40. Satellite imagery can capture or be used to infer many important asset-level characteristics41,42 and is continuing to drive advances in ecosystem service modeling at global and local levels43. Even so, these approaches cannot be expected to fully capture all impacts or values, and on-the-ground information will remain an important complement, especially for understanding local values. Ultimately, further improvements to the accessibility, completeness, and standardization of data will be important to extending these approaches to meet demand from consumers, investors, regulators, and companies themselves for high quality information on nature-related impacts.