Forests and savannas are largest and diverse ecosystems. They house some of the largest agricultural frontiers. The rapid expansion of agriculture in such regions is responsible for the production and export of agricultural commodities as well as releasing enormous amounts of carbon to Earth's atmosphere. Many of these agricultural achievements have come at a high environmental cost: deforestation and vegetation degradation. Over the next few decades, agricultural pathways will determine the distribution of forests and savannas and whether they retain the capacity to sustain key global ecosystem services or enter a downward spiral with accelerating disturbances that severely degrade native ecosystems, with global consequences. This study will quantify how disturbance regimes may shift as agriculture intensifies and the environment changes. The hypotheses are that (1) fire suppression associated with ongoing agricultural intensification will change the likelihood of catastrophic wildfires, and (2) projected changes in climate may results in more frequent, high-intensity fires. The project outcomes could inform regional land and fire management, particularly the development of new strategies to avoid catastrophic wildfires that can damage infrastructure; negatively impact human health and well-being; and release large amounts of carbon to the atmosphere.
This proposal will apply remote sensing imagery, statistical analyses, and numerical modeling to build a clearer understanding of the spatially varying synergies between climate, land use, and fire regimes in forests and savannas at a global scale. It will evaluate how burned area and fire frequency change as a function of environmental change and agricultural intensification, as well as how fire suppression and future environmental changes may alter the probability of widespread wildfires. Through remote sensing analyses, this project will advance understanding of fire disturbance regimes in forests and savannas worldwide, providing new insights into the unquantified thresholds that may lead to large-scale ecosystem change under future climate and land-use changes. To do so, the study focuses on four key components. First, reconstructing fire histories in forests and savannas using standard remote sensing products (e.g. Landsat, MODIS). Second, quantifying uncertainties inherent to the existing maps of land-use transitions in the agricultural frontier. Third, building a statistical model of changes in fire regime metrics as a function of land-use change, agriculture intensification, and climatic extremes. Fourth, improving the spatially explicit fire model (FISC) that will be used to simulate potential trajectories of fire regimes, and will also be applicable to forest-savanna areas in the rest of the globe, under scenarios of land-use and environmental change.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
