A New Picture of Fire Extent, Variability, and Drought Interaction in Prescribed Fire Landscapes: Insights From Florida Government Records

Diverging trends in aerosol sulfate and nitrate measured in the remote North Atlantic in Barbados are attributed to clean air policies, African smoke, and anthropogenic emissions

Sulfate and nitrate aerosols degrade air quality, modulate radiative forcing and the hydrological cycle, and affect biogeochemical cycles, yet their global cycles are poorly understood. Here, we examined trends in 21 years of aerosol measurements made at Ragged Point, Barbados, the easternmost promontory on the island located in the eastern Caribbean Basin. Though the site has historically been used to characterize African dust transport, here we focused on changes in nitrate and non-sea-salt (nss) sulfate aerosols from 1990-2011. Nitrate aerosol concentrations averaged over the entire period were stable at 0.59 μg m-3 ± 0.04 μg m-3, except for elevated nitrate concentrations in the spring of 2010 and during the summer and fall of 2008 due to the transport of biomass burning emissions from both northern and southern Africa to our site. In contrast, from 1990 to 2000, nss-sulfate decreased 30% at a rate of 0.023 μg m-3 yr-1, a trend which we attribute to air quality policies enacted in the United States (US) and Europe. From 2000-2011, sulfate gradually increased at a rate of 0.021 μg m-3 yr-1 to pre-1990s levels of 0.90 μg m-3. We used the Community Multiscale Air Quality (CMAQ) model simulations from the EPA's Air QUAlity TimE Series (EQUATES) to better understand the changes in nss-sulfate after 2000. The model simulations estimate that increases in anthropogenic emissions from Africa explain the increase in nss-sulfate observed in Barbados. Our results highlight the need to better constrain emissions from developing countries and to assess their impact on aerosol burdens in remote source regions.

Estimated Impacts of Prescribed Fires on Air Quality and Premature Deaths in Georgia and Surrounding Areas in the US, 2015-2020

Smoke from wildfires poses a substantial threat to health in communities near and far. To mitigate the extent and potential damage of wildfires, prescribed burning techniques are commonly employed as land management tools; however, they introduce their own smoke-related risks. This study investigates the impact of prescribed fires on daily average PM2.5 and maximum daily 8-h averaged O3 (MDA8-O3) concentrations and estimates premature deaths associated with short-term exposure to prescribed fire PM2.5 and MDA8-O3 in Georgia and surrounding areas of the Southeastern US from 2015 to 2020. Our findings indicate that over the study domain, prescribed fire contributes to average daily PM2.5 by 0.94 ± 1.45 μg/m3 (mean ± standard deviation), accounting for 14.0% of year-round ambient PM2.5. Higher average daily contributions were predicted during the extensive burning season (January-April): 1.43 ± 1.97 μg/m3 (20.0% of ambient PM2.5). Additionally, prescribed burning is also responsible for an annual average increase of 0.36 ± 0.61 ppb in MDA8-O3 (approximately 0.8% of ambient MDA8-O3) and 1.3% (0.62 ± 0.88 ppb) during the extensive burning season. We estimate that short-term exposure to prescribed fire PM2.5 and MDA8-O3 could have caused 2665 (95% confidence interval (CI): 2249-3080) and 233 (95% CI: 148-317) excess deaths, respectively. These results suggest that smoke from prescribed burns increases the mortality. However, refraining from such burns may escalate the risk of wildfires; therefore, the trade-offs between the health impacts of wildfires and prescribed fires, including morbidity, need to be taken into consideration in future studies.

Can restoration of fire-dependent ecosystems reduce ticks and tick-borne disease prevalence in the eastern United States?

Over the past century, fire suppression has facilitated broad ecological changes in the composition, structure, and function of fire-dependent landscapes throughout the eastern US, which are in decline. These changes have likely contributed mechanistically to the enhancement of habitat conditions that favor pathogen-carrying tick species, key wildlife hosts of ticks, and interactions that have fostered pathogen transmission among them and to humans. While the long-running paradigm for limiting human exposure to tick-borne diseases focuses responsibility on individual prevention, the continued expansion of medically important tick populations, increased incidence of tick-borne disease in humans, and emergence of novel tick-borne diseases highlights the need for additional approaches to stem this public health challenge. Another approach that has the potential to be a cost-effective and widely applied but that remains largely overlooked is the use of prescribed fire to ecologically restore degraded landscapes that favor ticks and pathogen transmission. We examine the ecological role of fire and its effects on ticks within the eastern United States, especially examining the life cycles of forest-dwelling ticks, shifts in regional-scale fire use over the past century, and the concept that frequent fire may have helped moderate tick populations and pathogen transmission prior to the so-called fire-suppression era that has characterized the past century. We explore mechanisms of how fire and ecological restoration can reduce ticks, the potential for incorporating the mechanisms into the broader strategy for managing ticks, and the challenges, limitations, and research needs of prescribed burning for tick reduction.

Impacts of Sugarcane Fires on Air Quality and Public Health in South Florida

BACKGROUND

Preharvest burning of sugarcane is a common agricultural practice in Florida, which produces fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5)] that is associated with higher mortality.

OBJECTIVES

We estimated premature mortality associated with exposure to PM2.5 from sugarcane burning in people age 25 y and above for 20 counties in South Florida.

METHODS

We combined information from an atmospheric dispersion model, satellites, and surface measurements to quantify PM2.5 concentrations in South Florida and the fraction of PM2.5 from sugarcane fires. From these concentrations, estimated mortalities attributable to PM2.5 from sugarcane fires were calculated by census tract using health impact functions derived from literature for six causes of death linked to PM2.5. Confidence intervals (CI) are provided based on Monte Carlo simulations that propagate uncertainty in the emissions, dispersion model, health impact functions, and demographic data.

RESULTS

Sugarcane fires emitted an amount of primary PM2.5 similar to that of motor vehicles in Florida. PM2.5 from sugarcane fires is estimated to contribute to mortality rates within the Florida Sugarcane Growing Region (SGR) by 0.4 death per 100,000 people per year (95% CI: 0.3, 1.6 per 100,000). These estimates imply 2.5 deaths per year across South Florida were associated with PM2.5 from sugarcane fires (95% CI: 1.2, 6.1), with 0.16 in the SGR (95% CI: 0.09, 0.6) and 0.72 in Palm Beach County (95% CI: 0.17, 2.2).

DISCUSSION

PM2.5 from sugarcane fires was estimated to contribute to mortality risk across South Florida, particularly in the SGR. This is consistent with prior studies that documented impacts of sugarcane fire on air quality but did not quantify mortality. Additional health impacts of sugarcane fires, which were not quantified here, include exacerbating nonfatal health conditions such as asthma and cardiovascular problems. Harvesting sugarcane without field burning would likely reduce PM2.5 and health burdens in this region. https://doi.org/10.1289/EHP9957.

Hotspots of Predictability: Identifying Regions of High Precipitation Predictability at Seasonal Timescales From Limited Time Series Observations

Precipitation prediction at seasonal timescales is important for planning and management of water resources as well as preparedness for hazards such as floods, droughts and wildfires. Quantifying predictability is quite challenging as a consequence of a large number of potential drivers, varying antecedent conditions, and small sample size of high-quality observations available at seasonal timescales, that in turn, increases prediction uncertainty and the risk of model overfitting. Here, we introduce a generalized probabilistic framework to account for these issues and assess predictability under uncertainty. We focus on prediction of winter (Nov-Mar) precipitation across the contiguous United States, using sea surface temperature-derived indices (averaged in Aug-Oct) as predictors. In our analysis we identify "predictability hotspots," which we define as regions where precipitation is inherently more predictable. Our framework estimates the entire predictive distribution of precipitation using copulas and quantifies prediction uncertainties, while employing principal component analysis for dimensionality reduction and a cross validation technique to avoid overfitting. We also evaluate how predictability changes across different quantiles of the precipitation distribution (dry, normal, wet amounts) using a multi-category 3 × 3 contingency table. Our results indicate that well-defined predictability hotspots occur in the Southwest and Southeast. Moreover, extreme dry and wet conditions are shown to be relatively more predictable compared to normal conditions. Our study may help with water resources management in several subregions of the United States and can be used to assess the fidelity of earth system models in successfully representing teleconnections and predictability.

Potential impacts of prescribed fire smoke on public health and socially vulnerable populations in a Southeastern U.S. state

Prescribed fire is an essential tool for wildfire risk mitigation and ecosystem restoration in the Southeastern United States. It is also one of the region's largest sources of atmospheric emissions. The public health impacts of prescribed fire smoke, however, remain uncertain. Here, we use digital burn permit records, reduced-complexity air quality modeling, and epidemiological associations between fine particulate matter concentrations and multiple health endpoints to assess the impacts of prescribed burning on public health across Georgia. Additionally, we examine the social vulnerability of populations near high prescribed burning activity using a demographic- and socioeconomic-based index. The analysis identifies spatial clusters of burning activity in the state and finds that areas with intense prescribed fire have levels of social vulnerability that are over 25% higher than the state average. The results also suggest that the impacts of burning in Georgia can potentially include hundreds of annual morbidity and mortality cases associated with smoke pollution. These health impacts are concentrated in areas with higher fractions of low socioeconomic status, elderly, and disabled residents, particularly vulnerable to air pollution. Estimated smoke-related health incidence rates are over 3 times larger than the state average in spatial clusters of intense burning activity, and over 40% larger in spatial clusters of high social vulnerability. Spatial clusters of low social vulnerability experience substantially lower negative health effects from prescribed burning relative to the rest of the state. The health burden of smoke from prescribed burns in the state is comparable to that estimated for other major emission sectors, such as vehicles and industrial combustion. Within spatial clusters of socially-vulnerable populations, the impacts of prescribed fire considerably outweigh those of other emission sectors. These findings call for greater attention to the air quality impacts of prescribed burning in the Southeastern U.S. and the communities most exposed to fire-related smoke.

COVID-19 lockdowns drive decline in active fires in southeastern United States

The coronavirus pandemic, COVID-19, led to strict social-distancing guidelines that severely impacted human livelihood and economic activity. Workplace closures reduced travel, and early in spring 2020, improvements in air and water quality, reduced seismic activity, and reductions in greenhouse gas emissions were observed. COVID-19–related shutdowns emerged at the beginning of the prescribed fire season in the southeastern United States, where 80% of fires are human caused. Using active fire satellite observations and fuel treatment statistics, we estimated a 21% reduction in active fires from March to December 2020 (up to 40% on federal lands). This reduction in active fire may increase fire risk in the future and is detrimental to biodiversity and other ecosystem services inherent to fire-dependent ecosystems.

Fire is a common ecosystem process in forests and grasslands worldwide. Increasingly, ignitions are controlled by human activities either through suppression of wildfires or intentional ignition of prescribed fires. The southeastern United States leads the nation in prescribed fire, burning ca. 80% of the country’s extent annually. The COVID-19 pandemic radically changed human behavior as workplaces implemented social-distancing guidelines and provided an opportunity to evaluate relationships between humans and fire as fire management plans were postponed or cancelled. Using active fire data from satellite-based observations, we found that in the southeastern United States, COVID-19 led to a 21% reduction in fire activity compared to the 2003 to 2019 average. The reduction was more pronounced for federally managed lands, up to 41% below average compared to the past 20 y (38% below average compared to the past decade). Declines in fire activity were partly affected by an unusually wet February before the COVID-19 shutdown began in mid-March 2020. Despite the wet spring, the predicted number of active fire detections was still lower than expected, confirming a COVID-19 signal on ignitions. In addition, prescribed fire management statistics reported by US federal agencies confirmed the satellite observations and showed that, following the wet February and before the mid-March COVID-19 shutdown, cumulative burned area was approaching record highs across the region. With fire return intervals in the southeastern United States as frequent as 1 to 2 y, COVID-19 fire impacts will contribute to an increasing backlog in necessary fire management activities, affecting biodiversity and future fire danger.

Growth, proportion, and distribution pattern of longleaf pine across southeastern forests and disturbance types: A change assessment for the period 1997-2018

The long-term decline of longleaf pine-dominated forests has received considerable attention among land managers and conservation professionals in the last few decades. The objective of this study was to investigate the change in and the variation of the proportion, density, growth, and dominance of longleaf pine across the longleaf pine ecosystems for the 1997–2018 period. We used two sets of measurements of 1,432 plots from the Forest Inventory and Analysis (FIA) dataset covering the entire current longleaf pine range. The relationship between disturbances and longleaf pine basal area ratio and basal area growth were analyzed using linear mixed modeling. Change detection maps were produced using the Inverse Distance Weighted (IDW) interpolation method. The total basal area and aboveground biomass per hectare increased in 64% and 72%, but decreased in 30% and 28% of the study area, respectively, between the first and last inventory intervals. Species richness and diversity generally decreased across the studied plots. Longleaf pine tree density and importance value percent increased during the period. However, longleaf basal area ratio and aboveground biomass ratio in the stands decreased on average by 5% during the period, although these ratios increased in some locations in southwest Georgia and near the west coast of Florida. The longleaf pine basal area ratio and aboveground biomass ratio decreased equally in 37%, and increased in 19% and 21% of the study area, respectively. There was about 79% variation in the ratio of longleaf pine basal area among plots. When compared to the natural control of no disturbance, fire disturbance was significantly associated with greater longleaf pine basal area ratio and basal area growth. Understanding the change in growth and distribution patterns of longleaf pine across its range over time is vital to restore these critical ecosystems.

Using GatorEye UAV-Borne LiDAR to Quantify the Spatial and Temporal Effects of a Prescribed Fire on Understory Height and Biomass in a Pine Savanna

In the pine savannas of the southeastern United States, prescribed fire is commonly used to manipulate understory structure and composition. Understory characteristics have traditionally been monitored with field sampling; however, remote sensing could provide rapid, spatially explicit monitoring of understory dynamics. We contrasted pre- vs. post-fire understory characteristics collected with fixed area plots with estimates from high-density LiDAR point clouds collected using the unmanned aerial vehicle (UAV)-borne GatorEye system. Measuring within 1 × 1 m field plots (n = 20), we found average understory height ranged from 0.17–1.26 m and biomass from 0.26–4.86 Mg C ha−1 before the fire (May 2018), and five months after the fire (November 2018), height ranged from 0.11–1.09 m and biomass from 0.04–3.03 Mg C ha−1. Understory heights estimated with LiDAR were significantly correlated with plot height measurements (R2 = 0.576, p ≤ 0.001). Understory biomass was correlated with in situ heights (R2 = 0.579, p ≤ 0.001) and LiDAR heights (R2 = 0.507, p ≤ 0.001). The biomass estimates made with either height measurement did not differ for the measurement plots (p = 0.263). However, for the larger research area, the understory biomass estimated with the LiDAR indicated a smaller difference after the burn (~12.7% biomass reduction) than observed with in situ measurements (~16% biomass reduction). The two approaches likely differed because the research area’s spatial variability was not captured by the in-situ measurements (0.2% of the research area measured) versus the wall-to-wall coverage provided by LiDAR. The additional benefit of having spatially explicit measurements with LiDAR, and its ease of use, make it a promising tool for land managers wanting greater spatial and temporal resolution in tracking understory biomass and its response to prescribed fire.

Wildfire and prescribed burning impacts on air quality in the United States

Air quality impacts from wildfires have been dramatic in recent years, with millions of people exposed to elevated and sometimes hazardous fine particulate matter (PM _2.5 ) concentrations for extended periods. Fires emit particulate matter (PM) and gaseous compounds that can negatively impact human health and reduce visibility. While the overall trend in U.S. air quality has been improving for decades, largely due to implementation of the Clean Air Act, seasonal wildfires threaten to undo this in some regions of the United States. Our understanding of the health effects of smoke is growing with regard to respiratory and cardiovascular consequences and mortality. The costs of these health outcomes can exceed the billions already spent on wildfire suppression. In this critical review, we examine each of the processes that influence wildland fires and the effects of fires, including the natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry, and human health impacts. We highlight key data gaps and examine the complexity and scope and scale of fire occurrence, estimated emissions, and resulting effects on regional air quality across the United States. The goal is to clarify which areas are well understood and which need more study. We conclude with a set of recommendations for future research.

IMPLICATIONS

In the recent decade the area of wildfires in the United States has increased dramatically and the resulting smoke has exposed millions of people to unhealthy air quality. In this critical review we examine the key factors and impacts from fires including natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry and human health.

Extreme Drought Events over the Amazon Basin: The Perspective from the Reconstruction of South American Hydroclimate

The Amazon basin has experienced severe drought events for centuries, mainly associated with climate variability connected to tropical North Atlantic and Pacific sea surface temperature anomalous warming. Recently, these events are becoming more frequent, more intense and widespread. Because of the Amazon droughts environmental and socioeconomic impacts, there is an increased demand for understanding the characteristics of such extreme events in the region. In that regard, regional models instead of the general circulation models provide a promising strategy to generate more detailed climate information of extreme events, seeking better representation of physical processes. Due to uneven spatial distribution and gaps found in station data in tropical South America, and the need of more refined climate assessment in those regions, satellite-enhanced regional downscaling for applied studies (SRDAS) is used in the reconstruction of South American hydroclimate, with hourly to monthly outputs from January 1998. Accordingly, this research focuses on the analyses of recent extreme drought events in the years of 2005 and 2010 in the Amazon Basin, using the SRDAS monthly means of near-surface temperature and relative humidity, precipitation and vertically integrated soil moisture fields. Results from this analysis corroborate spatial and temporal patterns found in previous studies on extreme drought events in the region, displaying the distinctive features of the 2005 and 2010 drought events.