Honeybees have dominated research on bee vision<\/a> for more than a century. But some of the most impressive visual performances measured in our new study<\/a> came from rarely studied, solitary species.<\/p>\n While the honeybee lives in massive colonies, most bee species are solitary<\/a> so must do everything themselves: find food, locate mates, provision their nests. In terms of vision, several of the solitary species we researched outperformed honeybee workers in a number of ways, including the sharpness of images formed by their eyes.<\/p>\n Close-up of a honeybee\u2019s eye. Understanding how these different evolutionary solutions work is important for more than just understanding bee biology. It could provide ideas for nature-inspired technologies, from compact visual sensors<\/a> to autonomous robots<\/a>.<\/p>\n How bees\u2019 eyes have adapted<\/p>\n With more than 20,000 species worldwide<\/a>, bees show extraordinary diversity in lifestyle, body size and ecological role. Some live in open environments; others forage in dense vegetation or in dim light at dawn, dusk and even at night.<\/p>\n Such remarkable diversity prompted us to ask the question: how have bees\u2019 eyes adapted to such different lifestyles and visual demands?<\/p>\n Bees see the world through compound eyes made up of thousands of tiny lenses. These odd-looking structures are their main tools to navigate, locate flowers and identify important landmarks.<\/p>\n Our new study<\/a> of some daytime-active bee species shows that even bees with similar-looking eyes can achieve impressive visual performance in surprisingly different ways.<\/p>\n Male wool carder bees (Anthidium manicatum), for example, spend much of their day patrolling territories and chasing rivals or potential mates through the air. This bee pushes visual sharpness to the limit<\/a> with its exceptionally small photoreceptors that minimise optical blur. In contrast, honeybee drones have evolved large lenses that maximise sensitivity.<\/p>\n<\/p>\n Video: David O’Carroll\/Lund University.<\/p>\n The Australian blue-banded bee (Amegilla) manages to detect small objects and see sharp images just as well without either of these extreme strategies. Instead, it achieves similar visual performance using a different combination of optical design and sampling.<\/p>\n From the outside, the eyes of these bees all look very similar. But when we looked more closely, we found the size of their visual sensors (photoreceptors) differed greatly.<\/p>\n These light-sensitive structures are a bit like the pixels in a smartphone camera. They sit behind the bees\u2019 tiny eye lenses, converting light into electrical signals. Larger pixels capture more light, improving sensitivity, while smaller ones can help preserve image sharpness.<\/p>\n The challenge \u2013 for smartphone designers and evolution alike \u2013 is balancing these competing demands.<\/p>\n Something unexpected<\/p>\n Looking at anatomy tells us how the eye is built, but not how well it performs. To answer this question, we recorded directly from individual photoreceptors in living bees.<\/p>\n We used glass microelectrodes with tips just a few tens of nanometers wide \u2013 thousands of times thinner than a human hair. That allowed us, for the first time in these species, to measure the tiny electrical signals that single cells produce when the bees were shown tiny objects on a computer display.<\/p>\n Our results revealed something unexpected. The diminutive Australian blue-banded bee lacks the enormous eyes of a honeybee drone, yet achieved a similar level of sensitivity in its photoreceptors.<\/p>\n At first glance, this seems paradoxical. How can bee eyes built so differently perform so similarly?<\/p>\n The answer is that evolution is not working towards a single ideal design. Different species have arrived at similar visual performance through different combinations of optical design, photoreceptor structure and visual sampling.<\/p>\n Our findings show why it is important to look beyond a handful of familiar species. By studying a wider range of bees, we can better understand how different senses have evolved, leading to a variety of adaptive solutions.<\/p>\n This is true not only for vision<\/a> but for other traits, including how bees respond to environmental stresses such as heat<\/a> and pesticide exposure<\/a>.<\/p>\n Unique evolutionary innovations<\/p>\n Through our research, we are just beginning to appreciate the remarkably different ways of seeing the world that bees have evolved.<\/p>\n Different bee species have evolved different solutions to the challenges of seeing their world. For example, the Australian blue-banded bee is a buzz pollinator, able to vibrate flowers to release pollen in a way that honeybees cannot. This makes it a potentially valuable pollinator of crops<\/a> such as tomatoes in Australia, where bumblebees are not naturally present.<\/p>\n Such diverse evolutionary solutions may also prove useful to engineers. Designers of cameras, robots and autonomous vehicles face many of the same challenges as bees: how to gather enough visual information while keeping sensors small, efficient and affordable.<\/p>\n Bees and other insects have been a fruitful source of inspiration for artificial vision systems<\/a>. In our previous work, we developed computational models<\/a> based on insect target motion processing that turned out to be as robust as alternative engineered solutions, with large benefits in processing efficiency.<\/p>\n We have now translated these models on to an autonomous robot that can pursue moving targets<\/a> within natural scenes and even into autonomous flying drones.<\/p>\n![\"Close-up](\"https:\/\/www.newsbeep.com\/uk\/wp-content\/uploads\/2026\/09\/file-20260827-50-xwste4.jpg\")
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