Seagrass meadows provide food and habitat for everything from dugongs and birds to fish and tiny crabs. Globally we’re losing over 100 sq. km per year due to dredging, coastal developments and runoff. That’s bad news for the animals they support, and bad news for us too, as seagrass supports healthy coastal fisheries as well as acting as a carbon store. To see how seagrass can be given a fighting chance, Dr Paul Wu at the ARC Centre of Excellence for Mathematical and Statistical Frontiers and collaborators have put an extended modelling technique to new use, predicting seagrass health and suggests how some modified human activities could reduce the damage. Dynamic Bayesian Networks allow modelling of cumulative effects and feedback loops—for example, as seagrass habitats are degraded, they affect the rate of further degradation. The team hopes their work will help inform dredging management, new port development and maintenance. “In a real-world application like this, with all these complex variables and processes, modelling helps managers and policymakers better understand the impact of decisions,” says Paul, who is based at the Queensland University of Technology. For example, the modelling predicts that putting time restrictions on when dredging can occur could greatly reduce the loss of seagrasses and improve their recovery time. The knowledge is being shared between biologists out in the field and mathematicians sifting through statistics. “This combination of expertise allows us to predict information that would take years to gather in the field. This model is our current best understanding of nature,” says Paul. Read about more work from the Centre here. Banner image credit: Professor Gary Kendrick, Western Australian Marine Science Institution.