Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …

Both fire and predators have strong influences on the population dynamics and behaviour of
animals, and the effects of predators may either be strengthened or weakened by fire …

Bayesian network (BN) modeling is a rapidly advancing field. Here we explore new methods
by which BN model development and application are being joined with other tools and …

Abstract Knowledge of how disturbances such as fire shape habitat structure and
composition, and affect animal interactions, is fundamental to ecology and ecosystem …

In recent years, a worldwide expansion in the frequency of large, uncontrolled, and
catastrophic wildfire events has occurred, creating drastic social, economic, and …

Background Predators and fire shape ecosystems across the globe and these two forces
can interact to impact prey populations. This issue is particularly pertinent in Australia where …

Failing to communicate current knowledge limitations, that is, epistemic uncertainty, in
environmental risk assessment (ERA) may have severe consequences for decision making …

Environmental decision-making requires an understanding of complex interacting systems
across scales of space and time. A range of statistical methods, evaluation frameworks and …

Inappropriate fire regimes and predation by introduced species each pose a major threat to
Australia's native mammals. They also potentially interact, an issue that is likely to be …

Land managers around the world are increasingly under pressure to demonstrate that the
actions being used to moderate wildfire risk are effective and cost-efficient. However, little …