Shifting social-ecological fire regimes explain increasing structure loss from Western wildfires

Structure loss is an acute, costly impact of the wildfire crisis in the western conterminous United States ("West"), motivating the need to understand recent trends and causes. We document a 246% rise in West-wide structure loss from wildfires between 1999-2009 and 2010-2020, driven strongly by events in 2017, 2018, and 2020. Increased structure loss was not due to increased area burned alone. Wildfires became significantly more destructive, with a 160% higher structure-loss rate (loss/kha burned) over the past decade. Structure loss was driven primarily by wildfires from unplanned human-related ignitions (e.g. backyard burning, power lines, etc.), which accounted for 76% of all structure loss and resulted in 10 times more structures destroyed per unit area burned compared with lightning-ignited fires. Annual structure loss was well explained by area burned from human-related ignitions, while decadal structure loss was explained by state-level structure abundance in flammable vegetation. Both predictors increased over recent decades and likely interacted with increased fuel aridity to drive structure-loss trends. While states are diverse in patterns and trends, nearly all experienced more burning from human-related ignitions and/or higher structure-loss rates, particularly California, Washington, and Oregon. Our findings highlight how fire regimes-characteristics of fire over space and time-are fundamentally social-ecological phenomena. By resolving the diversity of Western fire regimes, our work informs regionally appropriate mitigation and adaptation strategies. With millions of structures with high fire risk, reducing human-related ignitions and rethinking how we build are critical for preventing future wildfire disasters.

Fuel connectivity, burn severity, and seed bank survivorship drive ecosystem transformation in a semiarid shrubland

A key challenge in ecology is understanding how multiple drivers interact to precipitate persistent vegetation state changes. These state changes may be both precipitated and maintained by disturbances, but predicting whether the state change will be fleeting or persistent requires an understanding of the mechanisms by which disturbance affects the alternative communities. In the sagebrush shrublands of the western United States, widespread annual grass invasion has increased fuel connectivity, which increases the size and spatial contiguity of fires, leading to postfire monocultures of introduced annual grasses (IAG). The novel grassland state can be persistent and is more likely to promote large fires than the shrubland it replaced. But the mechanisms by which prefire invasion and fire occurrence are linked to higher postfire flammability are not fully understood. A natural experiment to explore these interactions presented itself when we arrived in northern Nevada immediately after a 50,000 ha wildfire was extinguished. We hypothesized that the novel grassland state is maintained via a reinforcing feedback where higher fuel connectivity increases burn severity, which subsequently increases postfire IAG dispersal, seed survivorship, and fuel connectivity. We used a Bayesian joint species distribution model and structural equation model framework to assess the strength of the support for each element in this feedback pathway. We found that prefire fuel connectivity increased burn severity and that higher burn severity had mostly positive effects on the occurrence of IAG and another nonnative species and mostly negative or neutral relationships with all other species. Finally, we found that the abundance of IAG seeds in the seed bank immediately after a fire had a positive effect on the fuel connectivity 3 years after the fire, completing a positive feedback promoting IAG. These results demonstrate that the strength of the positive feedback is controlled by measurable characteristics of ecosystem structure, composition, and disturbance. Further, each node in the loop is affected independently by multiple global change drivers. It is possible that these characteristics can be modeled to predict threshold behavior and inform management actions to mitigate or slow the establishment of the grass-fire cycle, perhaps via targeted restoration applications or prefire fuel treatments.

Country-level fire perimeter datasets (2001-2021)

Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually.

Measurement(s)	Fire event occurrence • growth rate • size
Technology Type(s)	Satellite fire detections
Sample Characteristic - Environment	fire
Sample Characteristic - Location	global

Reimagine fire science for the anthropocene

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

U.S. fires became larger, more frequent, and more widespread in the 2000s

Recent fires have fueled concerns that regional and global warming trends are leading to more extreme burning. We found compelling evidence that average fire events in regions of the United States are up to four times the size, triple the frequency, and more widespread in the 2000s than in the previous two decades. Moreover, the most extreme fires are also larger, more common, and more likely to co-occur with other extreme fires. This documented shift in burning patterns across most of the country aligns with the palpable change in fire dynamics noted by the media, public, and fire-fighting officials.

Interannual climate variability mediates changes in carbon and nitrogen pools caused by annual grass invasion in a semiarid shrubland

Exotic plant invasions alter ecosystem properties and threaten ecosystem functions globally. Interannual climate variability (ICV) influences both plant community composition (PCC) and soil properties, and interactions between ICV and PCC may influence nitrogen (N) and carbon (C) pools. We asked how ICV and non-native annual grass invasion covary to influence soil and plant N and C in a semiarid shrubland undergoing widespread ecosystem transformation due to invasions and altered fire regimes. We sampled four progressive stages of annual grass invasion at 20 sites across a large (25,000 km² ) landscape for plant community composition, plant tissue N and C, and soil total N and C in 2013 and 2016, which followed 2 years of dry and wet conditions, respectively. Multivariate analyses and ANOVAs showed that in invasion stages where native shrub and perennial grass and forb communities were replaced by annual grass-dominated communities, the ecosystem lost more soil N and C in wet years. Path analysis showed that high water availability led to higher herbaceous cover in all invasion stages. In stages with native shrubs and perennial grasses, higher perennial grass cover was associated with increased soil C and N, while in annual-dominated stages, higher annual grass cover was associated with losses of soil C and N. Also, soil total C and C:N ratios were more homogeneous in annual-dominated invasion stages as indicated by within-site standard deviations. Loss of native shrubs and perennial grasses and forbs coupled with annual grass invasion may lead to long-term declines in soil N and C and hamper restoration efforts. Restoration strategies that use innovative techniques and novel species to address increasing temperatures and ICV and emphasize maintaining plant community structure-shrubs, grasses, and forbs-will allow sagebrush ecosystems to maintain C sequestration, soil fertility, and soil heterogeneity.

Fusion neural networks for plant classification: learning to combine RGB, hyperspectral, and lidar data

Airborne remote sensing offers unprecedented opportunities to efficiently monitor vegetation, but methods to delineate and classify individual plant species using the collected data are still actively being developed and improved. The Integrating Data science with Trees and Remote Sensing (IDTReeS) plant identification competition openly invited scientists to create and compare individual tree mapping methods. Participants were tasked with training taxon identification algorithms based on two sites, to then transfer their methods to a third unseen site, using field-based plant observations in combination with airborne remote sensing image data products from the National Ecological Observatory Network (NEON). These data were captured by a high resolution digital camera sensitive to red, green, blue (RGB) light, hyperspectral imaging spectrometer spanning the visible to shortwave infrared wavelengths, and lidar systems to capture the spectral and structural properties of vegetation. As participants in the IDTReeS competition, we developed a two-stage deep learning approach to integrate NEON remote sensing data from all three sensors and classify individual plant species and genera. The first stage was a convolutional neural network that generates taxon probabilities from RGB images, and the second stage was a fusion neural network that “learns” how to combine these probabilities with hyperspectral and lidar data. Our two-stage approach leverages the ability of neural networks to flexibly and automatically extract descriptive features from complex image data with high dimensionality. Our method achieved an overall classification accuracy of 0.51 based on the training set, and 0.32 based on the test set which contained data from an unseen site with unknown taxa classes. Although transferability of classification algorithms to unseen sites with unknown species and genus classes proved to be a challenging task, developing methods with openly available NEON data that will be collected in a standardized format for 30 years allows for continual improvements and major gains for members of the computational ecology community. We outline promising directions related to data preparation and processing techniques for further investigation, and provide our code to contribute to open reproducible science efforts.

Two centuries of settlement and urban development in the United States

Over the past 200 years, the population of the United States grew more than 40-fold. The resulting development of the built environment has had a profound impact on the regional economic, demographic, and environmental structure of North America. Unfortunately, constraints on data availability limit opportunities to study long-term development patterns and how population growth relates to land-use change. Using hundreds of millions of property records, we undertake the finest-resolution analysis to date, in space and time, of urbanization patterns from 1810 to 2015. Temporally consistent metrics reveal distinct long-term urban development patterns characterizing processes such as settlement expansion and densification at fine granularity. Furthermore, we demonstrate that these settlement measures are robust proxies for population throughout the record and thus potential surrogates for estimating population changes at fine scales. These new insights and data vastly expand opportunities to study land use, population change, and urbanization over the past two centuries.

All-hazards dataset mined from the US National Incident Management System 1999-2014

This paper describes a new dataset mined from the public archive (1999-2014) of the U.S. National Incident Management System/Incident Command System Incident Status Summary Form (a total of 124,411 reports for 25,083 incidents, including 24,608 wildfires). This system captures detailed information on incident management costs, personnel, hazard characteristics, values at risk, fatalities, and structural damage. Most (98.5%) of the reports are fire-related, followed in decreasing order by other, hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use due to multiple record formats, inconsistent free-form fields, and no bridge between individual reports and high-level incident analysis. Here, we describe this improved dataset and the open, reproducible methods used, including merging records across three versions of the system, cleaning and aligning with the current system, smoothing values across reports, and supporting incident-level analysis. This integrated record offers the opportunity to explore the daily progression of the most costly, damaging, and deadly events in the U.S., particularly for wildfires.

Invasive grasses increase fire occurrence and frequency across US ecoregions

Fire-prone invasive grasses create novel ecosystem threats by increasing fine-fuel loads and continuity, which can alter fire regimes. While the existence of an invasive grass-fire cycle is well known, evidence of altered fire regimes is typically based on local-scale studies or expert knowledge. Here, we quantify the effects of 12 nonnative, invasive grasses on fire occurrence, size, and frequency across 29 US ecoregions encompassing more than one third of the conterminous United States. These 12 grass species promote fire locally and have extensive spatial records of abundant infestations. We combined agency and satellite fire data with records of abundant grass invasion to test for differences in fire regimes between invaded and nearby "uninvaded" habitat. Additionally, we assessed whether invasive grass presence is a significant predictor of altered fire by modeling fire occurrence, size, and frequency as a function of grass invasion, in addition to anthropogenic and ecological covariates relevant to fire. Eight species showed significantly higher fire-occurrence rates, which more than tripled for Schismus barbatus and Pennisetum ciliare. Six species demonstrated significantly higher mean fire frequency, which more than doubled for Neyraudia reynaudiana and Pennisetum ciliare Grass invasion was significant in fire occurrence and frequency models, but not in fire-size models. The significant differences in fire regimes, coupled with the importance of grass invasion in modeling these differences, suggest that invasive grasses alter US fire regimes at regional scales. As concern about US wildfires grows, accounting for fire-promoting invasive grasses will be imperative for effectively managing ecosystems.

Prolonged tropical forest degradation due to compounding disturbances: Implications for CO2 and H2 O fluxes

Drought, fire, and windstorms can interact to degrade tropical forests and the ecosystem services they provide, but how these forests recover after catastrophic disturbance events remains relatively unknown. Here, we analyze multi-year measurements of vegetation dynamics and function (fluxes of CO₂ and H₂ O) in forests recovering from 7 years of controlled burns, followed by wind disturbance. Located in southeast Amazonia, the experimental forest consists of three 50-ha plots burned annually, triennially, or not at all from 2004 to 2010. During the subsequent 6-year recovery period, postfire tree survivorship and biomass sharply declined, with aboveground C stocks decreasing by 70%-94% along forest edges (0-200 m into the forest) and 36%-40% in the forest interior. Vegetation regrowth in the forest understory triggered partial canopy closure (70%-80%) from 2010 to 2015. The composition and spatial distribution of grasses invading degraded forest evolved rapidly, likely because of the delayed mortality. Four years after the experimental fires ended (2014), the burned plots assimilated 36% less carbon than the Control, but net CO₂ exchange and evapotranspiration (ET) had fully recovered 7 years after the experimental fires ended (2017). Carbon uptake recovery occurred largely in response to increased light-use efficiency and reduced postfire respiration, whereas increased water use associated with postfire growth of new recruits and remaining trees explained the recovery in ET. Although the effects of interacting disturbances (e.g., fires, forest fragmentation, and blowdown events) on mortality and biomass persist over many years, the rapid recovery of carbon and water fluxes can help stabilize local climate.

Spatiotemporal prediction of wildfire size extremes with Bayesian finite sample maxima

Wildfires are becoming more frequent in parts of the globe, but predicting where and when wildfires occur remains difficult. To predict wildfire extremes across the contiguous United States, we integrate a 30-yr wildfire record with meteorological and housing data in spatiotemporal Bayesian statistical models with spatially varying nonlinear effects. We compared different distributions for the number and sizes of large fires to generate a posterior predictive distribution based on finite sample maxima for extreme events (the largest fires over bounded spatiotemporal domains). A zero-inflated negative binomial model for fire counts and a lognormal model for burned areas provided the best performance. This model attains 99% interval coverage for the number of fires and 93% coverage for fire sizes over a six year withheld data set. Dryness and air temperature strongly predict extreme wildfire probabilities. Housing density has a hump-shaped relationship with fire occurrence, with more fires occurring at intermediate housing densities. Statistically, these drivers affect the chance of an extreme wildfire in two ways: by altering fire size distributions, and by altering fire frequency, which influences sampling from the tails of fire size distributions. We conclude that recent extremes should not be surprising, and that the contiguous United States may be on the verge of even larger wildfire extremes.

Impacts of fire on sources of soil CO2 efflux in a dry Amazon rain forest

Fire at the dry southern margin of the Amazon rainforest could have major consequences for regional soil carbon (C) storage and ecosystem carbon dioxide (CO₂ ) emissions, but relatively little information exists about impacts of fire on soil C cycling within this sensitive ecotone. We measured CO₂ effluxes from different soil components (ground surface litter, roots, mycorrhizae, soil organic matter) at a large-scale burn experiment designed to simulate a severe but realistic potential future scenario for the region (Fire plot) in Mato Grosso, Brazil, over 1 year, and compared these measurements to replicated data from a nearby, unmodified Control plot. After four burns over 5 years, soil CO₂ efflux (R_s ) was ~5.5 t C ha^-1  year^-1 lower on the Fire plot compared to the Control. Most of the Fire plot R_s reduction was specifically due to lower ground surface litter and root respiration. Mycorrhizal respiration on both plots was around ~20% of R_s . Soil surface temperature appeared to be more important than moisture as a driver of seasonal patterns in R_s at the site. Regular fire events decreased the seasonality of R_s at the study site, due to apparent differences in environmental sensitivities among biotic and abiotic soil components. These findings may contribute toward improved predictions of the amount and temporal pattern of C emissions across the large areas of tropical forest facing increasing fire disturbances associated with climate change and human activities.

Scenarios in tropical forest degradation: carbon stock trajectories for REDD

BACKGROUND

Human-caused disturbance to tropical rainforests-such as logging and fire-causes substantial losses of carbon stocks. This is a critical issue to be addressed in the context of policy discussions to implement REDD+. This work reviews current scientific knowledge about the temporal dynamics of degradation-induced carbon emissions to describe common patterns of emissions from logging and fire across tropical forest regions. Using best available information, we: (i) develop short-term emissions factors (per area) for logging and fire degradation scenarios in tropical forests; and (ii) describe the temporal pattern of degradation emissions and recovery trajectory post logging and fire disturbance.

RESULTS

Average emissions from aboveground biomass were 19.9 MgC/ha for logging and 46.0 MgC/ha for fire disturbance, with an average period of study of 3.22 and 2.15 years post-disturbance, respectively. Longer-term studies of post-logging forest recovery suggest that biomass accumulates to pre-disturbance levels within a few decades. Very few studies exist on longer-term (>10 years) effects of fire disturbance in tropical rainforests, and recovery patterns over time are unknown.

CONCLUSIONS

This review will aid in understanding whether degradation emissions are a substantial component of country-level emissions portfolios, or whether these emissions would be offset by forest recovery and regeneration.

Global combustion: the connection between fossil fuel and biomass burning emissions (1997-2010)

Humans use combustion for heating and cooking, managing lands, and, more recently, for fuelling the industrial economy. As a shift to fossil-fuel-based energy occurs, we expect that anthropogenic biomass burning in open landscapes will decline as it becomes less fundamental to energy acquisition and livelihoods. Using global data on both fossil fuel and biomass burning emissions, we tested this relationship over a 14 year period (1997-2010). The global average annual carbon emissions from biomass burning during this time were 2.2 Pg C per year (±0.3 s.d.), approximately one-third of fossil fuel emissions over the same period (7.3 Pg C, ±0.8 s.d.). There was a significant inverse relationship between average annual fossil fuel and biomass burning emissions. Fossil fuel emissions explained 8% of the variation in biomass burning emissions at a global scale, but this varied substantially by land cover. For example, fossil fuel burning explained 31% of the variation in biomass burning in woody savannas, but was a non-significant predictor for evergreen needleleaf forests. In the land covers most dominated by human use, croplands and urban areas, fossil fuel emissions were more than 30- and 500-fold greater than biomass burning emissions. This relationship suggests that combustion practices may be shifting from open landscape burning to contained combustion for industrial purposes, and highlights the need to take into account how humans appropriate combustion in global modelling of contemporary fire. Industrialized combustion is not only an important driver of atmospheric change, but also an important driver of landscape change through companion declines in human-started fires.This article is part of the themed issue 'The interaction of fire and mankind'.

Human-started wildfires expand the fire niche across the United States

The economic and ecological costs of wildfire in the United States have risen substantially in recent decades. Although climate change has likely enabled a portion of the increase in wildfire activity, the direct role of people in increasing wildfire activity has been largely overlooked. We evaluate over 1.5 million government records of wildfires that had to be extinguished or managed by state or federal agencies from 1992 to 2012, and examined geographic and seasonal extents of human-ignited wildfires relative to lightning-ignited wildfires. Humans have vastly expanded the spatial and seasonal "fire niche" in the coterminous United States, accounting for 84% of all wildfires and 44% of total area burned. During the 21-y time period, the human-caused fire season was three times longer than the lightning-caused fire season and added an average of 40,000 wildfires per year across the United States. Human-started wildfires disproportionally occurred where fuel moisture was higher than lightning-started fires, thereby helping expand the geographic and seasonal niche of wildfire. Human-started wildfires were dominant (>80% of ignitions) in over 5.1 million km2, the vast majority of the United States, whereas lightning-started fires were dominant in only 0.7 million km2, primarily in sparsely populated areas of the mountainous western United States. Ignitions caused by human activities are a substantial driver of overall fire risk to ecosystems and economies. Actions to raise awareness and increase management in regions prone to human-started wildfires should be a focus of United States policy to reduce fire risk and associated hazards.

Quantifying the human influence on fire ignition across the western USA

Humans have a profound effect on fire regimes by increasing the frequency of ignitions. Although ignition is an integral component of understanding and predicting fire, to date fire models have not been able to isolate the ignition location, leading to inconsistent use of anthropogenic ignition proxies. Here, we identified fire ignitions from the Moderate Resolution Imaging Spectrometer (MODIS) Burned Area Product (2000-2012) to create the first remotely sensed, consistently derived, and regionally comprehensive fire ignition data set for the western United States. We quantified the spatial relationships between several anthropogenic land-use/disturbance features and ignition for ecoregions within the study area and used hierarchical partitioning to test how the anthropogenic predictors of fire ignition vary among ecoregions. The degree to which anthropogenic features predicted ignition varied considerably by ecoregion, with the strongest relationships found in the Marine West Coast Forest and North American Desert ecoregions. Similarly, the contribution of individual anthropogenic predictors varied greatly among ecoregions. Railroad corridors and agricultural presence tended to be the most important predictors of anthropogenic ignition, while population density and roads were generally poor predictors. Although human population has often been used as a proxy for ignitions at global scales, it is less important at regional scales when more specific land uses (e.g., agriculture) can be identified. The variability of ignition predictors among ecoregions suggests that human activities have heterogeneous impacts in altering fire regimes within different vegetation types and geographies.

Testing the Amazon savannization hypothesis: fire effects on invasion of a neotropical forest by native cerrado and exotic pasture grasses

Changes in climate and land use that interact synergistically to increase fire frequencies and intensities in tropical regions are predicted to drive forests to new grass-dominated stable states. To reveal the mechanisms for such a transition, we established 50 ha plots in a transitional forest in the southwestern Brazilian Amazon to different fire treatments (unburned, burned annually (B1yr) or at 3-year intervals (B3yr)). Over an 8-year period since the commencement of these treatments, we documented: (i) the annual rate of pasture and native grass invasion in response to increasing fire frequency; (ii) the establishment of Brachiaria decumbens (an African C4 grass) as a function of decreasing canopy cover and (iii) the effects of grass fine fuel on fire intensity. Grasses invaded approximately 200 m from the edge into the interiors of burned plots (B1yr: 4.31 ha; B3yr: 4.96 ha) but invaded less than 10 m into the unburned plot (0.33 ha). The probability of B. decumbens establishment increased with seed availability and decreased with leaf area index. Fine fuel loads along the forest edge were more than three times higher in grass-dominated areas, which resulted in especially intense fires. Our results indicate that synergies between fires and invasive C4 grasses jeopardize the future of tropical forests.

Effects of high-frequency understorey fires on woody plant regeneration in southeastern Amazonian forests

Anthropogenic understorey fires affect large areas of tropical forest, yet their effects on woody plant regeneration post-fire remain poorly understood. We examined the effects of repeated experimental fires on woody stem (less than 1 cm at base) mortality, recruitment, species diversity, community similarity and regeneration mode (seed versus sprout) in Mato Grosso, Brazil. From 2004 to 2010, forest plots (50 ha) were burned twice (B2) or five times (B5), and compared with an unburned control (B0). Stem density recovered within a year after the first burn (initial density: 12.4-13.2 stems m(-2)), but after 6 years, increased mortality and decreased regeneration--primarily of seedlings--led to a 63 per cent and 85 per cent reduction in stem density in B2 and B5, respectively. Seedlings and sprouts across plots in 2010 displayed remarkable community similarity owing to shared abundant species. Although the dominant surviving species were similar across plots, a major increase in sprouting occurred--almost three- and fourfold greater in B2 and B5 than in B0. In B5, 29 species disappeared and were replaced by 11 new species often present along fragmented forest edges. By 2010, the annual burn regime created substantial divergence between the seedling community and the initial adult tree community (greater than or equal to 20 cm dbh). Increased droughts and continued anthropogenic ignitions associated with frontier land uses may promote high-frequency fire regimes that may substantially alter regeneration and therefore successional processes.

Introduced annual grass increases regional fire activity across the arid western USA (1980-2009)

Non-native, invasive grasses have been linked to altered grass-fire cycles worldwide. Although a few studies have quantified resulting changes in fire activity at local scales, and many have speculated about larger scales, regional alterations to fire regimes remain poorly documented. We assessed the influence of large-scale Bromus tectorum (hereafter cheatgrass) invasion on fire size, duration, spread rate, and interannual variability in comparison to other prominent land cover classes across the Great Basin, USA. We compared regional land cover maps to burned area measured using the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2000-2009 and to fire extents recorded by the USGS registry of fires from 1980 to 2009. Cheatgrass dominates at least 6% of the central Great Basin (650 000 km(2) ). MODIS records show that 13% of these cheatgrass-dominated lands burned, resulting in a fire return interval of 78 years for any given location within cheatgrass. This proportion was more than double the amount burned across all other vegetation types (range: 0.5-6% burned). During the 1990s, this difference was even more extreme, with cheatgrass burning nearly four times more frequently than any native vegetation type (16% of cheatgrass burned compared to 1-5% of native vegetation). Cheatgrass was also disproportionately represented in the largest fires, comprising 24% of the land area of the 50 largest fires recorded by MODIS during the 2000s. Furthermore, multi-date fires that burned across multiple vegetation types were significantly more likely to have started in cheatgrass. Finally, cheatgrass fires showed a strong interannual response to wet years, a trend only weakly observed in native vegetation types. These results demonstrate that cheatgrass invasion has substantially altered the regional fire regime. Although this result has been suspected by managers for decades, this study is the first to document recent cheatgrass-driven fire regimes at a regional scale.

Interactions between repeated fire, nutrients, and insect herbivores affect the recovery of diversity in the southern Amazon

Surface fires burn extensive areas of tropical forests each year, altering resource availability, biotic interactions, and, ultimately, plant diversity. In transitional forest between the Brazilian cerrado (savanna) and high stature Amazon forest, we took advantage of a long-term fire experiment to establish a factorial study of the interactions between fire, nutrient availability, and herbivory on early plant regeneration. Overall, five annual burns reduced the number and diversity of regenerating stems. Community composition changed substantially after repeated fires, and species common in the cerrado became more abundant. The number of recruits and their diversity were reduced in the burned area, but burned plots closed to herbivores with nitrogen additions had a 14 % increase in recruitment. Diversity of recruits also increased up to 50 % in burned plots when nitrogen was added. Phosphorus additions were related to an increase in species evenness in burned plots open to herbivores. Herbivory reduced seedling survival overall and increased diversity in burned plots when nutrients were added. This last result supports our hypothesis that positive relationships between herbivore presence and diversity would be strongest in treatments that favor herbivory--in this case herbivory was higher in burned plots which were initially lower in diversity. Regenerating seedlings in less diverse plots were likely more apparent to herbivores, enabling increased herbivory and a stronger signal of negative density dependence. In contrast, herbivores generally decreased diversity in more species rich unburned plots. Although this study documents complex interactions between repeated burns, nutrients, and herbivory, it is clear that fire initiates a shift in the factors that are most important in determining the diversity and number of recruits. This change may have long-lasting effects as the forest progresses through succession.

The Amazon basin in transition

Agricultural expansion and climate variability have become important agents of disturbance in the Amazon basin. Recent studies have demonstrated considerable resilience of Amazonian forests to moderate annual drought, but they also show that interactions between deforestation, fire and drought potentially lead to losses of carbon storage and changes in regional precipitation patterns and river discharge. Although the basin-wide impacts of land use and drought may not yet surpass the magnitude of natural variability of hydrologic and biogeochemical cycles, there are some signs of a transition to a disturbance-dominated regime. These signs include changing energy and water cycles in the southern and eastern portions of the Amazon basin.

Comment on "The incidence of fire in Amazonian forests with implications for REDD"

Aragão and Shimabukuro (Reports, 4 June 2010, p. 1275) reported that fires increase in agricultural frontiers even as deforestation decreases and concluded that these fires lead to unaccounted carbon emissions under the United Nations climate treaty's tropical deforestation and forest degradation component. Emissions from post-deforestation management activities are, in fact, included in these estimates--but burning of standing forests is not.

Fire in the Earth system

Fire is a worldwide phenomenon that appears in the geological record soon after the appearance of terrestrial plants. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle, and climate. Although humans and fire have always coexisted, our capacity to manage fire remains imperfect and may become more difficult in the future as climate change alters fire regimes. This risk is difficult to assess, however, because fires are still poorly represented in global models. Here, we discuss some of the most important issues involved in developing a better understanding of the role of fire in the Earth system.