Biodiversity research requires more motors in air, water and on land

Résumé fourni par la source

Abstract Human activities have accelerated species extinctions, driving rapid biodiversity decline. Simultaneously, advancements in Artificial Intelligence (AI) and autonomous systems offer transformative potential for biodiversity research. Uncrewed vehicles—drones (aerial systems) and other robots (ground and underwater platforms)—equipped with high‐resolution sensors enhance ecosystem monitoring with unprecedented efficiency and scale. Ecologists must examine how these technological advancements can be used to monitor, understand and protect ecosystems more effectively. Here, we review studies published in Web of Science (1930–2023) using uncrewed vehicles for ecological monitoring and explore how these applications could be extended to further biodiversity research. We found drones dominate vegetation mapping, species monitoring and habitat assessment; underwater vehicles focus on benthic surveys and water quality monitoring; and ground robots are primarily used for sample collection. A greater use of drones reflects their commercial availability, lower costs and ease of deployment and management rather than technological maturity compared to other robots. Despite these applications, key gaps remain: research overwhelmingly targets plants (46%) and animals (44%), with minimal focus on microbes (10%) reflecting the limited use of uncrewed vehicles for specimen or environmental material sampling. Biodiversity hotspots, including South Africa, Central America and South America, are underrepresented, largely reflecting disparities in national research and economic capacity. Moreover, although uncrewed vehicles are technically capable of sample collection and real‐time surveillance, these functions remain underexploited—representing a promising avenue to unlock their full potential in biodiversity research. To maximise the impact of these technologies, taxonomic and biogeographic coverage must expand alongside functional applications. We argue that integrating uncrewed vehicles, advanced payloads and AI‐driven real‐time data analysis through collaborations among ecologists, roboticists and AI researchers will enable cost‐effective, autonomous ecological monitoring, advancing biodiversity conservation and addressing pressing knowledge gaps in the Anthropocene.

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