Compounded Heat and Fire Risk for Future U.S. Populations

Long-term exposure to wildland fire smoke PM2.5 and mortality in the contiguous United States

Despite the substantial evidence on the health effects of short-term exposure to ambient fine particles (PM2.5), including increasing studies focusing on those from wildland fire smoke, the impacts of long-term wildland fire smoke PM2.5 exposure remain unclear. We investigated the association between long-term exposure to wildland fire smoke PM2.5 and nonaccidental mortality and mortality from a wide range of specific causes in all 3,108 counties in the contiguous United States, 2007 to 2020. Controlling for nonsmoke PM2.5, air temperature, and unmeasured spatial and temporal confounders, we found a nonlinear association between 12-mo moving average concentration of smoke PM2.5 and monthly nonaccidental mortality rate. Relative to a month with the long-term smoke PM2.5 exposure below 0.1 μg/m3, nonaccidental mortality increased by 0.16 to 0.63 and 2.11 deaths per 100,000 people per month when the 12-mo moving average of PM2.5 concentration was of 0.1 to 5 and 5+ μg/m3, respectively. Cardiovascular, ischemic heart disease, digestive, endocrine, diabetes, mental, and chronic kidney disease mortality were all found to be associated with long-term wildland fire smoke PM2.5 exposure. Smoke PM2.5 contributed to approximately 11,415 nonaccidental deaths/y (95% CI: 6,754, 16,075) in the contiguous United States. Higher smoke PM2.5-related increases in mortality rates were found for people aged 65 and above. Positive interaction effects with extreme heat were also observed. Our study identified the detrimental effects of long-term exposure to wildland fire smoke PM2.5 on a wide range of mortality outcomes, underscoring the need for public health actions and communications that span the health risks of both short- and long-term exposure.

Exploring spatial heterogeneity in synergistic effects of compound climate hazards: Extreme heat and wildfire smoke on cardiorespiratory hospitalizations in California

Extreme heat and wildfire smoke events are increasingly co-occurring in the context of climate change, especially in California. Extreme heat and wildfire smoke may have synergistic effects on population health that vary over space. We leveraged high-resolution satellite and monitoring data to quantify spatially varying compound exposures to extreme heat and wildfire smoke in California (2006-2019) at ZIP Code Tabulation Area (ZCTA) level. We found synergistic effects between extreme heat and wildfire smoke on daily cardiorespiratory hospitalizations at the state level. We also found spatial heterogeneity in such synergistic effects across ZCTAs. Communities with lower education attainment, lower health insurance coverage, lower income, lower proportion of automobile ownership, lower tree canopy coverage, higher population density, and higher proportions of racial/ethnic minorities experienced higher synergistic effects. This study highlights the need to incorporate compound hazards and environmental justice considerations into evidence-based policy development to protect populations from increasingly prevalent compound hazards.

Re-framing deer herbivory as a natural disturbance regime with ecological and socioeconomic outcomes in the eastern United States

Natural disturbances are critical ecosystem processes, with both ecological and socioeconomic benefits and disadvantages. Large herbivores are natural disturbances that have removed plant biomass for millions of years, although herbivore influence likely has declined during the past thousands of years corresponding with extinctions and declines in distributions and abundances of most animal species. Nonetheless, the conventional view, particularly in eastern North America, is that herbivory by large wild herbivores is at unprecedented levels, resulting in unnatural damage to forests. Here, we propose consideration of large herbivores as a natural disturbance that also imparts many crucial ecological advantages, using white-tailed deer (Odocoileus virginianus), the only wild large herbivore remaining throughout the eastern U.S., as our focal species. We examined evidence of detrimental effects of browsing on trees and forbs. We then considered that deer contribute to both fuel reduction and ecological restoration of herbaceous plants and historical open forests of savannas and woodlands by controlling tree and shrub densities, mimicking the consumer role of fire. Similarly to other disturbances, deer disturbance 'regimes' are uneven in severity across different ecosystems and landscapes, resulting in heterogeneity and diversity. In addition to biodiversity support and fuel reduction, socioeconomic benefits include >$20 billion dollars per year by 10 million hunters that support jobs and wildlife agencies, non-consumptive enjoyment of nature by 80 million people, cultural importance, and deer as ecological ambassadors, whereas costs include about $5 billion and up to 450 human deaths per year for motor vehicle accidents, along with crop damage and disease transmission. From a perspective of historical ecology rather than current baselines, deer impart a fundamental disturbance process with many ecological benefits and a range of socioeconomic effects.

Addressing regional relationships between white-tailed deer densities and land classes

White-tailed deer (Odocoileus virginianus) populations have recovered to about 30 million animals in the United States, but land cover has changed during the interval of recovery. To address the relationship between deer densities and current land cover at regional scales, I applied random forests and extreme gradient boosting classifiers to model low and high deer density classes, at two different thresholds (5.8 and 11.6 deer/km2), and land classes in three regions during approximately 2003. For low and high deer density classes divided at 5.8 deer/km2, deciduous broadleaf forest overall was the most influential and positive variable in the central east and central regions and crop and pasture were the most influential and negative variables in the southeast region. Deer density increased with area of deciduous and mixed forests, woody wetlands, and shrub in all regions. Deer density decreased with area of crop, developed open space, and developed low and medium residential density in all regions. For density classes divided at 11.6 deer/km2, deer density had the strongest relationship with woody wetlands in the central east region, mixed and deciduous forest in the southeast region, and woody wetlands and herbaceous vegetation in the central region. Deer density increased with deciduous and mixed forests, woody wetlands, and shrub in all regions. Conversely, deer density decreased with herbaceous vegetation, crop, and developed low residential densities in all regions. Therefore, at regional scales, deer overall occurred at greater densities in forests and woody wetlands and lower densities in agricultural and residential development, which did not appear to support more deer. Deer preference for forests does result in damage to forest products, but alternatively, some may consider that deer provide important socioeconomic and ecological services by reducing number of small trees, particularly in the absence of other disturbances that historically controlled tree biomass.

Evaluation of CLDAS and GLDAS Datasets for Near-Surface Air Temperature over Major Land Areas of China

As one of the most principal meteorological factors to affect global climate change and human sustainable development, temperature plays an important role in biogeochemical and hydrosphere cycle. To date, there are a wide range of temperature data sources and only a detailed understanding of the reliability of these datasets can help us carry out related research. In this study, the hourly and daily near-surface air temperature observations collected at national automatic weather stations (NAWS) in China were used to compare with the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the Global Land Data Assimilation System (GLDAS), both of which were developed by using the advanced multi-source data fusion technology. Results are as follows. (1) The spatial and temporal variations of the near-surface air temperature agree well between CLDAS and GLDAS over major land of China, except that spatial details in high mountainous areas were not sufficiently displayed in GLDAS; (2) The near-surface air temperature of CLDAS were more significantly correlated with observations than that of GLDAS, but more caution is necessary when using the data in mountain areas as the accuracy of the datasets gradually decreases with increasing altitude; (3) CLDAS can better illustrate the distribution of areas of daily maximum above 35 °C and help to monitor high temperature weather. The main conclusion of this study is that CLDAS near-surface air temperature has a higher reliability in China, which is very important for the study of climate change and sustainable development in East Asia.