New research from the Monash University, published March 17 of this year in the journal Scientific Reports, found that drones are much more precise at monitoring the size of seabird colonies in tropical and polar environments than traditional ground counts.
The study claims to have paved the way for a veritable revolution in ecological monitoring, as evidenced by the technology’s ever-increasing precision and ability to survey hard-to-reach populations.
While drones have already been used to monitor everything from the breeding success of canopy-nesting birds to wild elephants in the past, this is the first attempt made at finding out whether drones provide any actual benefits over current techniques.
In order to do that, the team compared the precision of drone-derived image counts with those made by human counters on the ground for three types of seabird: frigatebirds, terns and penguins. The team also made sure to rule out any potential data noise caused by birds being startled by the presence of a drone.
Results indicate that counts using images captured by drones were not disruptive to the birds’ behaviour and are an order of magnitude more precise than those taken from the ground.
This could be explained by the drones’ down-facing perspective outperforming normal human vision, which can be easily obscured by other birds and the terrain itself.
Study co-author and Monash Ecologist Dr Rohan Clarke explained the significance of these research findings to ecological monitoring projects.
“It’s highly likely that in the future, drones will be used to monitor populations of birds and animals, especially in inaccessible areas where on the ground surveying is difficult or impossible. This opens up exciting new possibilities when it comes to more accurately monitoring Earth’s ecosystems,” Dr Clarke said.
The study was carried out on Ashmore Reef (tropical) and Macquarie Island (sub-Antarctic), although the authors expect the same benefits to extend to other animal groups and geographical contexts – but only after developing a method to ensure the new technique is compatible with historical data sets.