Biodiversity risks are increasingly discussed in finance, yet links to location-specific realities and robust metrics remain limited. Current practice relies on standardized proxies, leaving investors without tools to integrate biodiversity meaningfully into portfolio management. As a result, integration is fragmented and often based on top-down exposure estimates that lack the granularity and supply chain transparency needed for actionable decisions. This session introduces a spatially explicit approach to portfolio construction that uses geospatial biodiversity data and locally grounded indicators.
By overlaying biodiversity variables of specific sites with the geographies of companies’ assets, investors can better assess localized risks. Evidence from Central Africa shows FSC-certified forest firms deliver stronger biodiversity outcomes, with measurable benefits for large mammals compared to non-certified firms (Zwerts et al., 2024). Such methods enable investors to identify biodiversity “hotspots,” improve transparency, and move beyond broad industry exclusions toward targeted, risk-adjusted strategies.
A spatial approach strengthens comparability across firms, links biodiversity risk directly to financial materiality, and creates opportunities for stewardship through local engagement. Barriers such as limited data, interoperability, and governance can be addressed via collaborative data-sharing, partnerships with local stakeholders, and alignment with disclosure standards such as TNFD.
Building on Bio-Value-at-Risk (Posth et al., 2024), this session will explore how spatial biodiversity indicators can be embedded in financial markets while ensuring just outcomes for local communities.