Critical land change information enhances the understanding of carbon balance in the United States.

Large-scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine-scale processes including land use and land cover change into a large-scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1-km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

Biomass consumption by surface fires across Earth's most fire prone continent.

Landscape fire is a key but poorly understood component of the global carbon cycle. Predicting biomass consumption by fire at large spatial scales is essential to understanding carbon dynamics and hence how fire management can reduce greenhouse gas emissions and increase ecosystem carbon storage. An Australia-wide field-based survey (at 113 locations) across large-scale macroecological gradients (climate, productivity and fire regimes) enabled estimation of how biomass combustion by surface fire directly affects continental-scale carbon budgets. In terms of biomass consumption, we found clear trade-offs between the frequency and severity of surface fires. In temperate southern Australia, characterised by less frequent and more severe fires, biomass consumed per fire was typically very high. In contrast, surface fires in the tropical savannas of northern Australia were very frequent but less severe, with much lower consumption of biomass per fire (about a quarter of that in the far south). When biomass consumption was expressed on an annual basis, biomass consumed was far greater in the tropical savannas (>20 times that of the far south). This trade-off is also apparent in the ratio of annual carbon consumption to net primary production (NPP). Across Australia's naturally vegetated land area, annual carbon consumption by surface fire is equivalent to about 11% of NPP, with a sharp contrast between temperate southern Australia (6%) and tropical northern Australia (46%). Our results emphasise that fire management to reduce greenhouse gas emissions should focus on fire prone tropical savanna landscapes, where the vast bulk of biomass consumption occurs globally. In these landscapes, grass biomass is a key driver of frequency, intensity and combustion completeness of surface fires, and management actions that increase grass biomass are likely to lead to increases in greenhouse gas emissions from savanna fires.

The Science of Firescapes: Achieving Fire-Resilient Communities.

Wildland fire management has reached a crossroads. Current perspectives are not capable of answering interdisciplinary adaptation and mitigation challenges posed by increases in wildfire risk to human populations and the need to reintegrate fire as a vital landscape process. Fire science has been, and continues to be, performed in isolated "silos," including institutions (e.g., agencies versus universities), organizational structures (e.g., federal agency mandates versus local and state procedures for responding to fire), and research foci (e.g., physical science, natural science, and social science). These silos tend to promote research, management, and policy that focus only on targeted aspects of the "wicked" wildfire problem. In this article, we provide guiding principles to bridge diverse fire science efforts to advance an integrated agenda of wildfire research that can help overcome disciplinary silos and provide insight on how to build fire-resilient communities.

Using machine learning algorithms to predict groundwater levels in Indonesian tropical peatlands.

Tropical peatlands play a vital role in the global carbon cycle as large carbon reservoirs and substantial carbon sinks. Indonesia possesses the largest share (65 %) of tropical peat carbon, equal to 57.4 Gt C. Human perturbations such as extensive logging, deforestation and canalization exacerbate water losses, especially during dry seasons, when low precipitation and high evapotranspiration rates combine with the increased drainage to lower groundwater levels. Drying and increasing temperatures of the surface peat exacerbate ignition and wildfire risks within the peat soils. As such, it is critically important to know how groundwater levels in peatlands are changing over space and time. In this study, a multilinear regression model as well as two machine learning algorithms, random forest and extreme gradient boosting, were used to model groundwater level over the study period (2010-12) within a peat dome impacted by drainage canals and multiple wildfires in Central Kalimantan, Indonesia. Although all three models performed well, based on overall fit, spatial modeling of groundwater level results revealed that extreme gradient boosting (R2 = 0.998, RMSE = 0.048 m) outperformed random forest (R2 = 0.997, RMSE = 0.054 m) and multilinear regression (R2 = 0.970, RMSE = 0.221 m) near drainage canals, which are key fire ignition risk locations in the peatlands. Our study also shows that, on average, elevation and precipitation are the most important parameters influencing groundwater level spatiotemporally.

Effects of distance from canal and degradation history on peat bulk density in a degraded tropical peatland.

Over recent decades, the combination of deforestation, peat drainage and fires have resulted in widespread degradation of Southeast Asia's tropical peatlands. These disturbances are generally thought to increase peat soil bulk density through peat drying and shrinkage, compaction, and consolidation. Biological oxidation and fires burning across these landscapes also consume surface peat, exposing older peat strata. The prevalence and severity of deforestation, peat drainage and fire are typically greater closer to canals, built to drain peatlands and provide access routes for people. We compared bulk densities of 240cm peat profiles from intact forests and degraded peatlands broadly, and also assessed differences between degraded peatlands near-to-canals (50-200m from the nearest canal) and far-from-canals (300+ m from the nearest canal). The effects of vegetation type and fire frequency on bulk density, irrespective of the distance from canal, were also investigated. Mean bulk density values ranged between 0.08 and 0.16gcm-3 throughout the 240cm peat profiles. Drainage of peat near-to-canals increased bulk density of peat above the minimum water table depth. Degradation by deforestation and fire also increased bulk densities of upper peat strata, albeit with greater variability. Peat sampled further from canals experienced less intense water table drawdowns, buffering them from drainage effects. These areas were also more commonly forested and burnt less frequently. Differences in bulk densities below minimum water table levels are less clear, but may reflect lowering of the current peat surface in degraded peatlands broadly. These results clearly show that important differences in bulk density exist across degraded peatlands that are spatially dependent on distance from canals and disturbance history. These landscape features should be taken into account when designing future bulk density sampling efforts and peatland restoration programs, or when extrapolating from existing sources in order to make accurate inferences from them.

Assessing fuel treatment effectiveness using satellite imagery and spatial statistics.

Understanding the influences of forest management practices on wildfire severity is critical in fire-prone ecosystems of the western United States. Newly available geospatial data sets characterizing vegetation, fuels, topography, and burn severity offer new opportunities for studying fuel treatment effectiveness at regional to national scales. In this study, we used ordinary least-squares (OLS) regression and sequential autoregression (SAR) to analyze fuel treatment effects on burn severity for three recent wildfires: the Camp 32 fire in western Montana, the School fire in southeastern Washington, and the Warm fire in northern Arizona. Burn severity was measured using differenced normalized burn ratio (dNBR) maps developed by the Monitoring Trends in Burn Severity project. Geospatial data sets from the LANDFIRE project were used to control for prefire variability in canopy cover, fuels, and topography. Across all three fires, treatments that incorporated prescribed burning were more effective than thinning alone. Treatment effect sizes were lower, and standard errors were higher in the SAR models than in the OLS models. Spatial error terms in the SAR models indirectly controlled for confounding variables not captured in the LANDFIRE data, including spatiotemporal variability in fire weather and landscape-level effects of reduced fire severity outside the treated areas. This research demonstrates the feasibility of carrying out assessments of fuel treatment effectiveness using geospatial data sets and highlights the potential for using spatial autoregression to control for unmeasured confounding factors.

Synergisms among fire, land use, and climate change in the Amazon.

The Amazon is being rapidly transformed by fire. Logging and forest fragmentation sharply elevate fire incidence by increasing forest desiccation and fuel loads, and forests that have experienced a low-intensity surface fire are vulnerable to far more catastrophic fires. Satellites typically detect thermal signatures from 40 000 to 50 000 separate fires in the Amazon each year, and this number could increase as new highways and infrastructure expand across the basin. Many are concerned that large-scale deforestation, by reducing regional evapotranspiration and creating moisture-trapping smoke plumes, will make the basin increasingly vulnerable to fire. The Amazon may also be affected by future global warming and atmospheric changes, although much remains uncertain. Most models suggest the basin will become warmer throughout this century, although there is no consensus about how precipitation will be affected. The most alarming scenarios project a permanent disruption of the El Niño-Southern Oscillation, leading to greatly increased drought or destructive synergisms between regional and global climate change in the Amazon.

Human exposure and sensitivity to globally extreme wildfire events.

Extreme wildfires have substantial economic, social and environmental impacts, but there is uncertainty whether such events are inevitable features of the Earth's fire ecology or a legacy of poor management and planning. We identify 478 extreme wildfire events defined as the daily clusters of fire radiative power from MODIS, within a global 10 × 10 km lattice, between 2002 and 2013, which exceeded the 99.997th percentile of over 23 million cases of the ΣFRP 100 km-2 in the MODIS record. These events are globally distributed across all flammable biomes, and are strongly associated with extreme fire weather conditions. Extreme wildfire events reported as being economically or socially disastrous (n = 144) were concentrated in suburban areas in flammable-forested biomes of the western United States and southeastern Australia, noting potential biases in reporting and the absence of globally comprehensive data of fire disasters. Climate change projections suggest an increase in days conducive to extreme wildfire events by 20 to 50% in these disaster-prone landscapes, with sharper increases in the subtropical Southern Hemisphere and European Mediterranean Basin.

Climate-induced variations in global wildfire danger from 1979 to 2013.

Climate strongly influences global wildfire activity, and recent wildfire surges may signal fire weather-induced pyrogeographic shifts. Here we use three daily global climate data sets and three fire danger indices to develop a simple annual metric of fire weather season length, and map spatio-temporal trends from 1979 to 2013. We show that fire weather seasons have lengthened across 29.6 million km(2) (25.3%) of the Earth's vegetated surface, resulting in an 18.7% increase in global mean fire weather season length. We also show a doubling (108.1% increase) of global burnable area affected by long fire weather seasons (>1.0 σ above the historical mean) and an increased global frequency of long fire weather seasons across 62.4 million km(2) (53.4%) during the second half of the study period. If these fire weather changes are coupled with ignition sources and available fuel, they could markedly impact global ecosystems, societies, economies and climate.

Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity.

Fire has become an increasingly important disturbance event in south-western Amazonia. We conducted the first assessment of the ecological impacts of these wildfires in 2008, sampling forest structure and biodiversity along twelve 500 m transects in the Chico Mendes Extractive Reserve, Acre, Brazil. Six transects were placed in unburned forests and six were in forests that burned during a series of forest fires that occurred from August to October 2005. Normalized Burn Ratio (NBR) calculations, based on Landsat reflectance data, indicate that all transects were similar prior to the fires. We sampled understorey and canopy vegetation, birds using both mist nets and point counts, coprophagous dung beetles and the leaf-litter ant fauna. Fire had limited influence upon either faunal or floral species richness or community structure responses, and stems <10 cm DBH were the only group to show highly significant (p = 0.001) community turnover in burned forests. Mean aboveground live biomass was statistically indistinguishable in the unburned and burned plots, although there was a significant increase in the total abundance of dead stems in burned plots. Comparisons with previous studies suggest that wildfires had much less effect upon forest structure and biodiversity in these south-western Amazonian forests than in central and eastern Amazonia, where most fire research has been undertaken to date. We discuss potential reasons for the apparent greater resilience of our study plots to wildfire, examining the role of fire intensity, bamboo dominance, background rates of disturbance, landscape and soil conditions.

Quantifying responses of dung beetles to fire disturbance in tropical forests: the importance of trapping method and seasonality.

Understanding how biodiversity responds to environmental changes is essential to provide the evidence-base that underpins conservation initiatives. The present study provides a standardized comparison between unbaited flight intercept traps (FIT) and baited pitfall traps (BPT) for sampling dung beetles. We examine the effectiveness of the two to assess fire disturbance effects and how trap performance is affected by seasonality. The study was carried out in a transitional forest between Cerrado (Brazilian Savanna) and Amazon Forest. Dung beetles were collected during one wet and one dry sampling season. The two methods sampled different portions of the local beetle assemblage. Both FIT and BPT were sensitive to fire disturbance during the wet season, but only BPT detected community differences during the dry season. Both traps showed similar correlation with environmental factors. Our results indicate that seasonality had a stronger effect than trap type, with BPT more effective and robust under low population numbers, and FIT more sensitive to fine scale heterogeneity patterns. This study shows the strengths and weaknesses of two commonly used methodologies for sampling dung beetles in tropical forests, as well as highlighting the importance of seasonality in shaping the results obtained by both sampling strategies.

The human dimension of fire regimes on Earth.

Humans and their ancestors are unique in being a fire-making species, but 'natural' (i.e. independent of humans) fires have an ancient, geological history on Earth. Natural fires have influenced biological evolution and global biogeochemical cycles, making fire integral to the functioning of some biomes. Globally, debate rages about the impact on ecosystems of prehistoric human-set fires, with views ranging from catastrophic to negligible. Understanding of the diversity of human fire regimes on Earth in the past, present and future remains rudimentary. It remains uncertain how humans have caused a departure from 'natural' background levels that vary with climate change. Available evidence shows that modern humans can increase or decrease background levels of natural fire activity by clearing forests, promoting grazing, dispersing plants, altering ignition patterns and actively suppressing fires, thereby causing substantial ecosystem changes and loss of biodiversity. Some of these contemporary fire regimes cause substantial economic disruptions owing to the destruction of infrastructure, degradation of ecosystem services, loss of life, and smoke-related health effects. These episodic disasters help frame negative public attitudes towards landscape fires, despite the need for burning to sustain some ecosystems. Greenhouse gas-induced warming and changes in the hydrological cycle may increase the occurrence of large, severe fires, with potentially significant feedbacks to the Earth system. Improved understanding of human fire regimes demands: (1) better data on past and current human influences on fire regimes to enable global comparative analyses, (2) a greater understanding of different cultural traditions of landscape burning and their positive and negative social, economic and ecological effects, and (3) more realistic representations of anthropogenic fire in global vegetation and climate change models. We provide an historical framework to promote understanding of the development and diversification of fire regimes, covering the pre-human period, human domestication of fire, and the subsequent transition from subsistence agriculture to industrial economies. All of these phases still occur on Earth, providing opportunities for comparative research.

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.

Landsat still contributing to environmental research.

Landsat data have enabled continuous global monitoring of both human-caused and other land cover disturbances since 1972. Recently degraded performance and intermittent service of the Landsat 7 and Landsat 5 sensors, respectively, have raised concerns about the condition of global Earth observation programs. However, Landsat imagery is still useful for landscape change detection and this capability should continue into the foreseeable future.

Fire science for rainforests.

Forest fires are growing in size and frequency across the tropics. Continually eroding fragmented forest edges, they are unintended ecological disturbances that transcend deforestation to degrade vast regions of standing forest, diminishing ecosystem services and the economic potential of these natural resources. Affecting the health of millions, net forest fire emissions may have released carbon equivalent to 41% of worldwide fossil fuel use in 1997-98. Episodically more severe during El Niño events, pan-tropical forest fires will increase as more damaged, less fire-resistant, forests cover the landscape. Here I discuss the current state of tropical fire science and make recommendations for advancement.