Evaluating Biodiversity Credits Using Metacommunity Modelling

Abstract Enhancing global biodiversity is one of the key pillars of the UN’s Sustainable Development Goals, widely acknowledged as necessary to mitigate climate change. Nevertheless, an annual additional of US 700 billions of funding is required to reach the ‘30 by 30’ target set out in the Kunming-Montreal Global Biodiversity Framework. The proposed voluntary biodiversity credit market aims to bridge this funding gap via a market-based mechanism by assigning financial value to biodiversity and ecosystem services. To capitalise on this nascent market, several voluntary biodiversity credits are emerging from independent start-ups, internationally respected NGOs, and established carbon credit companies. Projects which are primary funded by credit sales must align their objectives with their credit issuance methodology to avoid underdelivering on their commitments. In this pioneering study, the diderences in behaviour between six diderent well-established credits were investigated, to highlight the impact of methodology choice and evaluate their accuracy on representing ecosystem level changes. Our results indicate that all six credits are suitable for tracking basic restoration edorts, however there are significant diderences in their methodologies and thus their responsiveness to interventions. Furthermore, not one credit was suitable to successfully track all six distinct nature-positive or nature-loss experiments simulated, suggesting that a universal biodiversity credit remains unattainable.