Aim

Chronic health effects of wildfire PM_2.5 on neurodevelopmental outcomes are largely unknown. Therefore, the effects of wildfire PM_2.5 on autism were assessed in a southern California-based pregnancy cohort using Cox proportional hazard models.

Background

We developed the WULFFSS, a stochastic monthly gridded forest-fire model for the western United States (US). Operating at 12 km resolution, WULFFSS calculates monthly probabilities of fires that burn at least 100 ha of forest area as well as the forest area burned per fire.

Accurate prediction of forest fire spread is a critical management and scientific challenge as the world adapts to rapidly changing fire regimes. We reconstructed 5,400 daily burned area progression maps for 196 U.S. Northern Rocky Mountain wildfires (2012–2021) and used machine learning to estimate daily fire growth given local weather, hydroclimate, fuels and topography.

Background

Background

Rural communities are increasingly impacted by smoke produced by wildfires and forest management activties. Understanding local influences on smoke adaptation and mitigation is critical to social adaptation as fire risk continues to rise.

Aims

Background

Background. Prescribed burning is a widely-used fire management strategy for maintaining socioeconomic and ecological resilience by mitigating the impacts of wildfires. Monitoring the effectiveness of prescribed burns on future fire spread, however, is challenged by limited data availability and quality. 

We created the first annually resolved records of historical fire occurrence coupled with precise estimates of tree establishment for the northern half of the west slope of the Oregon Cascades, a region that is home to some of the most productive forests on earth.