From environmental DNA into actionable biodiversity data: Towards the implementation of the Kunming-Montreal Global Biodiversity Framework

Biodiversity is declining at an alarming rate due to ongoing habitat destruction, climate change, pollution, the spread of invasive species, and unsustainable use of natural resources. In response, the Kunming-Montreal Global Biodiversity Framework (KMGBF), adopted in 2022, outlines a transformative goal to reverse biodiversity loss by 2030. The framework focuses on three main pillars: mitigating biodiversity threats, advancing implementation, and ensuring fair and sustainable use of biological resources. Meeting these objectives requires the adoption of innovative, adaptable, and inclusive monitoring strategies. Among these, environmental DNA (eDNA) has gained recognition as a non-invasive biodiversity assessment method that detects trace genetic material in environmental samples like sediment, soil, water, and air. Compared to conventional survey techniques, eDNA offers improved accuracy, sampling flexibility, and a non-destructive approach to monitoring ecosystems. Herein, we examine eDNA's role in achieving KMGBF goals to enable fulfilment of the Convention on Biological Diversity's vision of living in harmony with nature by 2050. We discuss its use in meeting several KMGBF targets including early detection of invasive species, enhancing biosecurity, monitoring species recovery, assessing pollution impacts, and supporting climate resilience. The standardization of eDNA protocols and alignment with FAIR (Findable, Accessible, Interoperable, Reusable) data principles ensure that results are transparent and interoperable across regions and platforms. Integrating eDNA into existing biodiversity monitoring networks enhances conservation planning, restoration efforts, and the management of protected areas. Additionally, eDNA facilitates inclusive conservation by supporting Indigenous-led and community-based monitoring, promoting stewardship, and enabling equitable access to biodiversity data worldwide.