After a more than a century of fighting to keep fire out of forests, reintroducing it is now an important management goal. Yet changes over the past century have left prescribed burning with a big job to do. Development, wildfire suppression, rising global temperatures, extended droughts, exotic species invasions, and longer fire seasons add complexity to using this practice.
Managers must consider how often, how intensely, and what time of year to burn; for insights they often look to how and when fires burned historically. However, attempting to mimic historical wildfires that burned in hot, dry conditions is risky. Burning in fall or spring when temperature and humidity are low reduces the risk of prescribed fires becoming uncontrollable, but does it have the intended effects? How do forest ecosystems that historically were adapted to fire respond when fire is reintroduced after so much time without it?
Forest Service researchers Becky Kerns and Michelle Day conducted a long-term experiment in the Malheur National Forest, Oregon, to assess how season and time between prescribed burns affect understory plant communities in ponderosa pine forests. They found that some native plants persisted and recovered from fire but didn’t respond vigorously, while invasive species tended to spread. These findings may help forest managers design more effective prescribed-fire treatments and avoid unintended consequences.
Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, > 37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to > 4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., > 1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America.
Wildland fire is a major producer of aerosols from combustion of vegetation and soils, but little is known about the abundance and composition of smoke’s biological content. Bioaerosols, or aerosols derived from biological sources, may be a significant component of the aerosol load vectored in wildland fire smoke. If bioaerosols are injected into the upper troposphere via high-intensity wildland fires and transported across continents, there may be consequences for the ecosystems they reach. Such transport would also alter the concept of a wildfire’s perimeter and the disturbance domain of its impact. Recent research has revealed that viable microorganisms are directly aerosolized during biomass combustion, but sampling systems and methodology for quantifying this phenomenon are poorly developed. Using a series of prescribed fires in frequently burned forest ecosystems, we report the results of employing a small rotary-wing unmanned aircraft system (UAS) to concurrently sample aerosolized bacteria and fungi, particulate matter, and micrometeorology in smoke plumes versus background conditions. Airborne impaction-based bioaerosol sampling indicated that microbial composition differed between background air and smoke, with seven unique organisms in smoke vs. three in background air. The air temperature was negatively correlated with the number of fungal colony-forming units detected. Our results demonstrate the utility of a UAS-based sampling platform for active sampling of viable aerosolized microbes in smoke arising from wildland fires. This methodology can be extended to sample viable microbes in a wide variety of emissions sampling pursuits, especially those in hazardous and inaccessible environments.
Ecological disturbance is a key agent shaping the spatial and temporal landscape of food availability. In forests of western North America, disturbance from fire can lead to resource pulses of deadwood-associated arthropods that provide important prey for woodpeckers. Although the foraging strategies among woodpecker species often demonstrate pronounced differences, little is known about the ways in which woodpeckers exploit and partition prey in disturbed areas. In this study, we employed DNA metabarcoding to characterize and compare the arthropod diets of 4 woodpecker species in Washington and California, USA—Black-backed Woodpecker (Picoides arcticus), Hairy Woodpecker (Dryobates villosus), Northern Flicker (Colaptes auratus), and White-headed Woodpecker (Dryobates albolarvatus)—primarily using nestling fecal samples from burned forests 1–13 years postfire. Successful sequencing from 78 samples revealed the presence of over 600 operational taxonomic units (OTUs) spanning 32 arthropod orders. The nestling diets of two species in particular—Northern Flicker and Black-backed Woodpecker—proved to be much broader than previous observational studies suggest. Northern Flicker nestlings demonstrated significantly higher diet diversity compared to other focal species, all of which displayed considerable overlap in diversity. Wood-boring beetles, which colonize dead and dying trees after fire, were particularly important diet items for Black-backed, Hairy, and White-headed woodpeckers. Diet composition differed among species, and diets showed limited differences between newer (≤5 yr) and older (>5 yr) postfire forests. Our results show mixed evidence for dietary resource partitioning, with three of the four focal species exhibiting relatively high diet overlap, perhaps due to the pulsed subsidy of deadwood-associated arthropods in burned forests. Woodpeckers are frequently used as management indicator species for forest health, and our study provides one of the first applications of DNA metabarcoding to build a more complete picture of woodpecker diets.
The Joint Fire Science Program (JFSP) and the Environmental Security Technology Certification Program (ESTCP) initiated the Fire and Smoke Model Experiment (FASMEE) (https://fasmee.net) by funding JFSP Project 15-S-01-01. This nationwide, multiagency effort identifies and collects critical measurements that will be used to advance fire and smoke science and modeling capabilities, allowing managers to 1) increase the use of managed fire, 2) improve firefighting strategies, 3) enhance smoke forecasts, 4) better assess carbon stores and fire-climate interactions and improve our understanding of other fire effects such as vegetation response. FASMEE also provides unparalleled opportunities to introduce new technology and the next generation of fire researchers in the largest coordinated fire project to date. The core leadership portioned FASMEE into three phases including analysis and planning (Phase 1), data collection (Phase 2), and future improvements (Phase 3). Phase 1 is complete, with the study plan as the main deliverable and a final report submitted and accepted by the JFSP in 2020. The plan includes science questions, data measurements and specifications, and burn recommendations that serve to guide planning. The plan has been published in the scientific literature.
The Joint Fire Science Program (JFSP) and the Environmental Security Technology Certification Program (ESTCP) initiated the Fire and Smoke Model Experiment (FASMEE) by funding Project 15-S-01-01 to identify and collect a set of critical measurements that will be used to advance wildland fire science knowledge and fire and smoke modeling capabilities. The project provided core leadership that developed a robust study plan and costing for a field campaign that would gather a novel set of observations, evaluate a selected set of models and use this information to advance operationally used fire and smoke modeling systems. FASMEE, with the support of the JFSP, leveraged several agency resources including the US Forest Service, National Science Foundation (NFS), National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) to successfully initiate the western wildfire campaign, the first of three data collection campaigns identified in the FASMEE study plan.
This document presents the study plan for the Fire and Smoke Model Evaluation Experiment (FASMEE). FASMEE is a large-scale interagency effort to (1) identify the critical measurements necessary to improve operational wildland fire and smoke prediction systems, (2) collect observations through a coordinated field campaign, and (3) use these measures and observations to advance science and modeling capabilities. FASMEE is aimed at operational modeling systems in use today as well as the next generation of modeling systems expected to become operationally useful in the next 5 to 10 years.
