An artificial intelligence system designed by researchers at the University of Cambridge is able to detect pain levels in sheep, which could aid in early diagnosis and treatment of common, but painful, conditions in animals.
A study by scientists from the University of Cambridge has revealed how cooperative behaviour between insect family members changes how rapidly body size evolves – with the speed of evolution increasing when individual animals help one another.
Asian elephants are able to recognise their bodies as obstacles to success in problem-solving, further strengthening evidence of their intelligence and self-awareness, according to a new study from the University of Cambridge.
One of the most interesting facts about mole rats – that, as with ants and termites, individuals specialise in particular tasks throughout their lives – turns out to be wrong. Instead, a new study led by the University of Cambridge shows that individuals perform different roles at different ages and that age rather than caste membership accounts for contrasts in their behaviour.
By following honeyguides, a species of bird, people in Africa are able to locate bees’ nests to harvest honey. Research now reveals that humans use special calls to solicit the help of honeyguides and that honeyguides actively recruit appropriate human partners. This relationship is a rare example of cooperation between humans and free-living animals.
Over the last fifty years, long-term studies following individual animals over entire lifespans have allowed insight into the evolutionary influence of social behaviour – finally fulfilling the holistic approach to evolution first suggested by Darwin, argues the author of a new milestone work on mammal societies.
Urban birds are less afraid of litter than their country cousins, according to a new study, which suggests they may learn that litter in cities is not dangerous. The research could help birds to adapt to urban settings better, helping them to survive increasing human encroachment on their habitats.
Largest quantitative study of howling, and first to use machine learning, defines different howl types and finds that wolves use these types more or less depending on their species, resembling a howling dialect. Researchers say findings could help conservation efforts and shed light on the earliest evolution of our own use of language.