Invasive weeds can threaten native biodiversity and negatively impact on agriculture. A group of researchers at QUT and CSIRO, including an ACEMS member, designed and implemented a new framework for rapidly modelling the invasion risk of weeds using Bayesian belief networks.
Research published in Communications reveals a considerable chance for an ice-free Arctic Ocean at global warming limits stipulated in the Paris Agreement. Scientists from South Korea, Australia and the USA used results from climate models and a new statistical approach to calculate the likelihood for Arctic sea ice to disappear at different warming levels.
ACEMS researchers have now provided a mathematical treatment that sheds light on the variance reduction properties of the reparameterization trick. The work was presented at the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) in Okinawa, Japan in April 2019, and was subsequently published in the conference proceedings. AISTATS is considered a top conference in Machine Learning.
ACEMS researcher Dr Catherine Leigh and colleagues have found that learning about the environment positively influences attitudes towards the environment, and in important ways. Their findings were published in People and Nature.
ACEMS researchers have developed new methods to evaluate the risk of invasion between geopolitical regions (e.g., states, or countries), by assessing climate similarity between the regions, and the volume of transport that occurs between them.