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The development of effective fire management for biodiversity conservation is a global challenge. The highly dynamic nature of fire, the difficulty in replicating ‘real‐world’ fire experiments and the need to understand population changes at large spatiotemporal scales make computer simulations particularly useful for identifying optimal fire management regimes for biodiversity conservation. We aimed to develop a flexible modelling approach with which to investigate how the spatiotemporal application of fire (i.e. management scenarios) influences savanna biodiversity. We used existing data from a landscape‐scale fire experiment to develop population simulations for the common brushtail possumTrichosurus vulpecula, grassland melomysMelomys burtoniand northern brown bandicootIsoodon macrourusacross the Kapalga area of Kakadu National Park in northern Australia. We simulated how populations were expected to change between 1995 and 2015 in response to the fire patterns observed at Kapalga over this period, and under a hypothetical management scenario of extensive prescribed burning. Our models predicted a substantial decline in all three species in response to the observed fire regime at Kapalga, suggesting that the fire patterns observed at Kapalga, with the associated mechanisms and interactions with other ecological processes, were not conducive with the persistence of native mammal populations. Our prescribed burning scenario had little effect on the predicted population trajectory of the common brushtail possum and grassland melomys, but markedly improved the population trajectory of the northern brown bandicoot. These inconsistencies highlight the need for a nuanced approach to fire management across northern Australian savannas, that is tailored to local conditions and management objectives. Synthesis and applications. The modelling approach outlined here provides a basis for identifying fire patterns that are beneficial for conserving biodiversity, ther

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.