Bee more specific: New radar tech could improve identification and tracking of key pollinators

Scientists from Trinity and Technical University of Denmark have developed a new radar-based technique that could address a critical gap in global conservation efforts, by transforming how we identify and track the insects that are actually responsible for pollinating plants.

by Trinity College Dublin

edited by Gaby Clark, reviewed by Alexander Pol

While pollinator declines have received widespread attention in recent years, most monitoring efforts focus on counting insect numbers rather than the diversity of species.

This distinction is vital. Not all flower-visiting insects contribute equally to pollination, while identifying and tracking the variety of species that visit different plants—especially food crops and endangered flora—has remained a major scientific challenge.

The new method was developed as a proof-of-concept under controlled lab conditions but is now being trialed in real-world, outdoor environments, where insects can be monitored freely. It uses a detailed analysis of insect "wingbeat signatures" (derived from radar reflections of millimeter-wave electromagnetic waves), which can distinguish species with high precision.

"Crucially, the approach means we can accurately identify different species, even telling apart very closely related insects. That is very hard to do visually, or via other existing technological tools," explained Trinity's Prof. Ian Donohue, senior author of the research article that has just been published in the journal PNAS Nexus.

"And unlike large-scale monitoring systems, this technique can also operate cheaply and effectively over a small spatial range, making it particularly suited to studying insect activity directly in and around flowers."

This enables researchers to pinpoint which insects are genuinely acting as pollinators in real time, rather than simply passing through an area. And it offers the potential to then track the numbers of various species across discrete time periods, to provide a far more accurate assessment of how those species are faring.

Exemplary reflected micro-Doppler spectrograms from wing flapping of five different pollinating insect species, computed from the unfiltered radar signals to illustrate the full micro-Doppler structure, including low-frequency components. Credit: PNAS Nexus (2026). DOI: 10.1093/pnasnexus/pgag096

What are the potential implications of this research?

The implications for conservation and agriculture are significant, because policymakers and scientists have long struggled to determine the most important pollinators in different habitat types and at different times of year. By identifying the variety of species that visit specific plants, this approach could help direct targeted conservation strategies and direct and improve ecosystem restoration efforts.

Prof. Jane Stout, another senior author of the research, and Vice-President for Biodiversity & Climate Action at Trinity, said, "The need for such innovation is urgent as pollinator populations continue to decline across Europe, including in Ireland, where even common species are showing worrying downward trends.

"According to the EU Red List of Bees (2025), 10% of assessed wild bee species are now threatened with extinction, which is more than double the number identified in 2014. Meanwhile, Ireland's National Biodiversity Data Centre reports a 3.5% annual decline in bumblebee populations since 2012."

Despite these alarming trends, major policy frameworks, including the EU Nature Restoration Regulation, still largely overlook the question of pollination effectiveness at the species level.

In brief, this technology could provide an unprecedented window into pollination dynamics and help to answer one of the more pressing ecological questions of our time.

Next steps and future developments

The team now plans to increase its insect radar signature database to include more species and seeks to detect changes in insect behavior by analyzing unusual alterations in wing-beat patterns, which may be linked to changes in variables such as temperature or humidity.

The tech can be integrated into emerging millimeter-wave communication and sensing infrastructures, such as 5G/6G and IoT, which means scalable, networked, continuous biodiversity monitoring should be achievable—in theory, making it useful in multiple settings.