For decades, conservation has depended on a deceptively simple act: counting. Scientists tally birds along migration routes, measure forest cover from satellites, or track wildlife populations through camera traps. These numbers underpin the decisions that shape environmental policy, from protected-area planning to international biodiversity targets. Yet the system that produces them is changing quickly, and not always coherently. A recent PNAS perspective led by William Sutherland and dozens of collaborators argues that biodiversity measurement is entering a pivotal moment. The tools used to monitor nature have expanded dramatically, while demand for reliable data has grown across governments, businesses and international agreements. The authors argue that making use of this expanding stream of biodiversity data will require changes not only in technology but also in how evidence is organized, shared, and interpreted. Nine changes needed to deliver a radical transformation in biodiversity measurement. Adapted from Sutherland et al (2026) The scale of data collection alone illustrates the shift. Global biodiversity databases now incorporate millions of observations from citizen scientists, museum collections, environmental DNA sampling and automated sensors. The Global Biodiversity Information Facility (GBIF), for example, adds hundreds of millions of species records each year, drawn from sources as varied as birdwatching apps and environmental impact assessments. In principle, this abundance opens new possibilities. Environmental DNA allows researchers to detect species from traces left in soil or water. Acoustic sensors can record entire soundscapes, with machine-learning systems identifying species calls automatically. Remote sensing tracks deforestation and habitat change in near real…This article was originally published on Mongabay

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