The 30 by 30 biodiversity commitment and financial disclosure: metrics matter

The Kunming-Montreal Global Biodiversity Framework commits nearly 200 nations to protect 30% of their territories. Given financial constraints, the ‘easiest’ approach to comply would be to protect the cheapest areas. But what would this mean for biodiversity conservation, and how could financial disclosure support — or undermine — success? We showcase and discuss the biological and financial consequences of area protection and restoration selected under various metrics, and highlight the potential of emerging approaches powered by artificial intelligence to guide biodiversity conservation. Through extensive simulations, we show that spatial restoration planning using the CAPTAIN model (Conservation Area Prioritization through Artificial Intelligence) can lead to substantial improvements in predicted outcomes across a wide range of biodiversity metrics. Corporate disclosure provides a common mechanism for reducing environmental damage and increasing conservation, but is often dependent on simplistic and suboptimal metrics, which can lead to significantly lower benefits to nature compared with more comprehensive approaches. Alternative methodologies, building upon technological and computational advances and developed through collaboration between economists, biologists, and data scientists, can provide more cost-effective mechanisms to improve biodiversity outcomes and support implementation of the Global Biodiversity Framework.