Discussion
With catastrophic fire events gaining global concern, realistic fire
danger assessment tools are needed more than ever. Here we present a
framework to predict fuel hazard at a fine spatial resolution that is
directly useful for operational fire management. It is based on
mechanism-informed random forest models that make use of field-based
observations of fuel hazard, gridded soil and topographic attributes,
long-term climate trends, as well as plant responses to changing
environment. Our modelling approach provides an important step towards a
mechanism-informed fire risk assessment system. The predictions could
also be used in fire behaviour models as well as to evaluate other
vegetation model projections.