Drastic interventions in an ecosystem, like deciding whether to eradicate an unwanted species, can have unforeseen, and sometimes even undesirable, consequences on the rest of the species present in that ecosystem. Just published research shows that, even if there is limited knowledge of these ecosystems, modellers should not wait any longer to start developing ecological forecasts that managers could potentially use to decide whether to implement such interventions.
What happens when you give an interesting Secret Santa maths problem to a group of mathematicians? Here's how it played out at a recent ACEMS Mathscraft workshop - thanks Dr Rheanna Mainzer, from The University of Melbourne, for writing this wonderful story in The Conversation.
ACEMS is excited to welcome three new Partner Investigators as ACEMS Members. They are Dr Juan Ortiz from the Australian Institute of Marine Sciences (AIMS), Dr Petra Kuhnert from CSIRO, and Dr Anders Holmberg from the Australian Bureau of Statistics (ABS).
ACEMS researchers at QUT have used a combination of virtual reality (VR), aerial thermal-imaging and ground surveys to build a better statistical model for predicting the location of koalas and, ultimately, protecting their habitat.
One of the biggest threats to the Great Barrier Reef is pollution from land making its way downstream by way of the many rivers and streams that flow into coastal waters along the reef. New statistical tools developed by ACEMS researchers could lead to the deployment of more low-cost sensors to monitor what is in those rivers and streams.
Well-known Mathematician Hannah Fry has called for tech and data scientists to make an ethical pledge, as medical doctors do. But the same result might be delivered by simply asking people to mind their bias. ACEMS' Lewis Mitchell and Joshua Ross explain with a story in The Conversation.
A new QUT-led study has developed a statistical toolbox to help avoid seagrass loss which provides shelter, food and oxygen to fish and at-risk species like dugongs and green turtles.
The research has been published in Methods in Ecology and Evolution describing key monitoring and management designs to maximise seagrass resilience to human activities, to better inform seagrass dredging operations and development of coastal areas.
ACEMS Chief Investigator Kate Smith-Miles led the development of a new online tool that stress-tests an algorithm, showing where an algorithm will work well, and more importantly, where it could be unreliable.