A document by Gustavo Facincani Dourado. Click on the document to view its contents.

Fire regimes are influenced by both exogenous drivers (e.g., increases in atmospheric CO2; and climate change) and endogenous drivers (e.g., vegetation and soil/litter moisture), which constrain fuel loads and fuel aridity. Herein, we identified how exogenous and endogenous drivers can interact to affect fuels and fire regimes in a semiarid watershed in the inland northwestern U.S. throughout the 21st century. We used a coupled ecohydrologic and fire regime model to examine how climate change and CO2 scenarios influence fire regimes over space and time. In this semiarid watershed we found that, in the mid-21st century (2040s), the CO2 fertilization effect on vegetation productivity outstripped the effects of climate change-induced fuel decreases, resulting in greater fuel loading and, thus, a net increase in fire size and burn probability; however, by the late-21st century (2070s), climatic warming dominated over CO2 fertilization, thus reducing fuel loading and fire activity. We also found that, under future climate change scenarios, fire regimes will shift progressively from being flammability to fuel-limited, and we identified a metric to quantify this shift: the ratio of the change in fuel loading to the change in its aridity. The threshold value for which this metric indicates a flammability versus fuel-limited regime differed between grasses and woody species but remained stationary over time. Our results suggest that identifying these thresholds in other systems requires narrowing uncertainty in exogenous drivers, such as future precipitation patterns and CO2 effects on vegetation.

Although natural disturbances such as wildfire, extreme weather events, and insect outbreaks play a key role in structuring ecosystems and watersheds worldwide, climate change has intensified many disturbance regimes, which can have compounding negative effects on ecosystem processes and services. Recent studies have highlighted the need to understand whether wildfire increases or decreases after large-scale beetle outbreaks. However, observational studies have produced mixed results. To address this, we applied a coupled ecohydrological-fire regime-beetle effects model (RHESSys-WMFire-Beetle) in a semiarid watershed in the western US. We found that surface fire probability and fire size decreased in the red phase (0-5 years post-outbreak), increased in the gray phase (6-15 years post-outbreak), and depended on mortality level in the old phase (one to several decades post-outbreak). In the gray and old phases, surface fire size and probability did not respond to low levels of beetle-caused mortality (<=20%), increased during medium levels of mortality (>20% and <=50%), and remained elevated but did not change with mortality (during the gray phase) or decreased (during the old phase) when mortality was high (>50%). Wildfire responses also depended on fire regime. In fuel-limited locations, fire typically increased with increasing fuel loads, whereas in fuel-abundant (flammability-limited) systems, fire sometimes decreased due to decreases in fuel aridity. This modeling framework can improve our understanding of the mechanisms driving wildfire responses and aid managers in predicting when and where fire hazards will increase.

Extreme wind-driven autumn wildfires are hazardous to life and property, due to their rapid rate of spread. Recent catastrophic autumn wildfires in the western United States co-occurred with record- or near-record autumn fire weather indices that are a byproduct of extreme fuel dryness and strong offshore dry winds. Here, we use a formal, probabilistic, extreme event attribution analysis to investigate anthropogenic influence on recent extreme autumn fire weather events. We show that while present-day anthropogenic climate change has slightly decreased the prevalence of strong offshore downslope winds, it has increased the likelihood of extreme fire weather indices by 40%, primarily through increased autumn fuel aridity and warmer temperatures during dry wind events. These findings illustrate that anthropogenic climate change is exacerbating autumn fire weather extremes that contribute to high-impact catastrophic fires in populated regions of the western US.

Outdoor workers perform critical societal functions, often despite higher-than-average on-the-job risks and below-average pay. Climate change is expected to increase the frequency of days when it is too hot to safely work outdoors, compounding risks to workers and placing new stressors on the personal, local, state, and federal economies that depend on them. After quantifying the number of outdoor workers in the contiguous United States and their median earnings, we couple heat-based work reduction recommendations from the US Centers for Disease Control and Prevention with an analysis of hourly weather station data to develop novel algorithms for calculating the annual number of unsafe workdays due to extreme heat. We apply these algorithms to projections of the frequency of extreme heat days to quantify the exposure of the outdoor workforce to extreme heat and the associated earnings at risk under different greenhouse gas emissions mitigation scenarios and, for the first time, different adaptation measures. With a trajectory of modest greenhouse gas emissions reductions (RCP4.5), outdoor worker exposure to extreme heat would triple that of the late 20th century baseline by midcentury, and earnings at risk would reach an estimated $39.3 billion annually. By late century with that same trajectory, exposure would increase four-fold compared to the baseline with an estimated $49.2 billion in annual earnings at risk. Losses are considerably higher with a limited-mitigation trajectory (RCP8.5). While universal adoption of two specific adaptation measures in conjunction could reduce future economic risks by roughly 90%, practical limitations to their adoption suggest that emissions mitigation policies will be critical for ensuring the wellbeing and livelihoods of outdoor workers in a warming climate.