Thanks to our experts: Jacob Bedford (UNEP-WCMC) and Bianca Nijhof (Anthesis Group) for providing these answers below.
How can we reconcile external database analyses (e.g., IUCN, Aqueduct) with actual on-the-ground observations? Is there a repository of up-to-date databases?
Refer to the TNFD (Taskforce on Nature-related Financial Disclosures) for guidance and access to relevant data repositories.
What are the recommended packages for large-scale geospatial data analysis?
We recommend using QGIS, a free and open-source platform widely used for geospatial data analysis.
What modelling techniques could help predict risks, especially financial risks?
Currently, there are no standardized scenario models for nature similar to those used for climate. However, you can explore the Nature Futures Framework for inspiration.
Another useful approach is mapping ecosystem services (see ESVD) and monitoring the state of nature quality — deteriorating conditions indicate potential risks for your company.
Translating nature data into natural capital valuation is another option; for example, explore Nature on the Balance Sheet Initiative
Beyond flagging “sensitive locations,” how can we prioritize assets when many are classified as sensitive?
There are two main approaches you may consider:
- Start with areas of highest ecological sensitivity; or
- Start with areas representing the largest business risks (dependencies/impacts).
You can bring in additional information such as the magnitude of impact or scale of operations to rank areas. “The most sensitive” sites can be further prioritized when they meet multiple criteria. Refer to SBTN Step 1 for guidance on prioritization using multiple metrics.
Can AI tools that combine different nature-assessment frameworks simplify the work or improve accuracy? What role does collaboration play in scaling this approach?
A combination of AI tools can help achieve the best results. However, sole reliance on AI carries risks — regular ground-truthing of AI-generated data is essential, as well as having the right expertise to interpret it.
Cross-sector and within-sector collaboration are also key to scaling up these approaches effectively.
What tools or instruments are available for nature integration?
This depends on what you mean by “nature integration.” The Integrated Decision-Making Framework from the Capitals Coalition provides step-by-step guidance: Integrated Decision-Making Framework
How can we access the EII (Ecosystem Integrity Index)?
While under review, the EII layer is available on request from UNEP-WCMC.
Is there a repository or catalog of existing spatial nature-related datasets?
Yes. Several compilations exist, including:
- TNFD and SBTN Toolboxes
- The A-Track Handbook for applying spatial datasets and metrics to assess locations and tailor nature strategies, which provides a curated list of global datasets with practical details across different aspects of nature.
What is your perspective on ground-testing geospatial data before making decisions?
The need for ground-truthing depends on the type of decision and use case.
While it increases accuracy and robustness, it may not be necessary for high-level screening. More detailed, site-level monitoring will usually require a mix of ground-based and secondary data.
How should we use the Biodiversity Intactness Index (BII)?
Integrity indices such as BII, MSA, or EII should be used cautiously at the site level due to limited spatial precision and accuracy.
They are better suited for screening and understanding broader landscape patterns — e.g., whether a site is within a degraded or intact area.
Use ranges and averages to capture local variation in integrity.
The WDPA shows overlapping protected areas. How should we handle this when prioritizing sites?
Some locations fall under multiple legal designations through different conventions, often indicating high ecological or regulatory importance.
However, fewer designations don’t necessarily mean lower importance — interpretation should be case-by-case. See this resource for more context: Risk Management in Protected Areas (ShareAction Report).
What should we do when spatial datasets show contradictory findings?
This likely depends on whether the datasets are measuring different aspects of nature- or whether the datasets measure the same variables but with different results. For the first, this is expected and represents the real tradeoffs that can occur in different values of nature. For the second, it is great to not rely on one data source, take averages between two, or flag areas for more in-depth review if screening datasets are not giving clear results.
How can organizations prioritize different elements when designing operations across multiple location-specific factors?
Trade-offs are inevitable and depend on company priorities and targets.
Some formal methodologies for combining criteria exist, such as SBTN Step 1, which supports structured prioritization using multiple variables.