Nine recommendations for improving biodiversity measurement

What the study found: The authors say biodiversity measurement is changing rapidly because of advances in citizen science, image recognition, acoustic monitoring, environmental DNA, genomics, remote sensing, and artificial intelligence (AI). They outline nine recommended changes for improving biodiversity measurement and monitoring.
Why the authors say this matters: The study suggests that better biodiversity information is needed to assess environmental change, identify areas for biodiversity protection or ecosystem services, judge whether actions are effective, and support decision-making for a sustainable planet. The authors conclude that new, rigorous, resilient, and accessible biodiversity information systems are needed to underpin policies and practices for maintaining and restoring ecological systems.
What the researchers tested: This is a perspective article, not an experimental study. The authors synthesize recent developments in biodiversity measurement and monitoring and present nine key recommendations.
What worked and what didn't: The abstract reports that novel technologies offer opportunities to integrate data sources, standardize data collection, calibrate new technologies with existing data, fill data gaps, and increase capacity, especially in the tropics. It also says challenges remain, including the risk of AI hallucinated or false information, the need to value data generation, respect Indigenous Knowledge, measure the effectiveness of actions, and make global datasets more resilient to technical and societal change.
What to keep in mind: The abstract does not provide experimental results, quantitative comparisons, or evidence for the nine recommendations. It also does not describe limitations beyond noting the challenges associated with the new technologies and data systems.

Key points

• Biodiversity measurement is changing rapidly because of new technologies such as AI, remote sensing, genomics, and environmental DNA.
• The authors propose nine changes for improving biodiversity measurement and monitoring.
• The study says better biodiversity data are needed to assess environmental change and support policy and practice.
• Challenges include false AI-generated information, data gaps, and the need to respect Indigenous Knowledge.
• The abstract describes a perspective article, not an experiment with quantified results.