Spring isn't all it's quacked up to be. Pollen levels are high, magpies are terrorising cyclists and pedestrians alike, and protective duck parents are in attack mode.
Our new research unites genomic sequencing and museum collections to reconstruct the evolutionary tale of native rodents, including many extinct and elusive species – and they have a fascinating origin story.
If swooping season strikes fear into your heart, you're not alone. Fortunately, Dr Chaminda Ratnayake from the ANU Research School of Biology has the intel you need to navigate the great outdoors this spring.
To measure the speed of adaptive evolution in the wild, we studied 19 populations of birds and mammals over several decades. We found they were evolving at twice to four times the speed suggested by earlier work.
Plants synthesize an amazing diversity of volatile organic compounds (VOCs) that facilitate interactions with their environment, ranging from attracting pollinators and seed dispersers to protecting themselves from pathogens, parasites, and herbivores.
This seminar is presented by Dr Emily Stringer and Dr Jarrod Sopniewski, Postdoctoral Research Fellows from the Centre for Conservation Ecology and Genomics at the University of Canberra.
Many flowering plants have evolved diverse strategies to communicate with and attract animal pollinators. We have discovered exciting new evidence for the role of anthocyanins and terpenes in the evolution of the highly diverse terrestrial orchid subtribe Caladeniinae (Diurideae).
Using case studies from my research on black-cockatoos and a formal partnership with Bush Heritage Australia, I will discuss how bioacoustics’ focus on machine learning and analysis over the last decade has now landed us in a place to use the technology in applied conservation settings.
Dietary shifts—particularly the inclusion of animal resources—were pivotal in human evolution, yet direct evidence of meat consumption in early hominins remains limited and debated.
By addressing key modeling challenges in mass spectrometry and tissue image analysis, this research advances the scalability, precision, and applicability of deep learning in clinical genomics, computational pathology, and personalized medicine.