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This project intends to use the Mount Denali ice core archive to develop the most comprehensive suite of North Pacific fire and summer climate proxy records since about 2500 years before present. Wildfire is a key component of summer climate in the North Pacific where wildfires are projected to increase with continued summer warming. Studies that combine paleorecords of summer climate and wildfire are therefore critically needed, especially in the North Pacific region where fire recurrence rate and decadal-to-centennial scale climate fluctuations occur over longer time periods than are covered by direct observations. The goal of the proposed research is to improve our understanding of relationships between summertime climate and wildfire activity, focusing especially on the Medieval Climate Anomaly (MCA), when regional temperatures were perhaps as warm as the 20th century. Recent advances now permit the measurement of new fire-related (pyrogenic) compounds in ice cores, enabling the development of a robust fire record capable of rigorous comparison with regional paleoclimate reconstructions. 

Abstract The determinants of fire-driven changes in soil organic carbon (SOC) across broad environmental gradients remains unclear, especially in global drylands. Here we combined datasets and field sampling of fire-manipulation experiments to evaluate where and why fire changes SOC and compared our statistical model to simulations from ecosystem models. Drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Many ecosystem models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in savannah–grassland regions may have gained 0.64 PgC due to net-declines in burned area over the past approximately two decades. Consequently, ongoing declines in fire frequencies have probably created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models. 

Abstract Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012–2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models. 

Abstract. Fire is the dominant disturbance agent in Alaskan and Canadianboreal ecosystems and releases large amounts of carbon into the atmosphere.Burned area and carbon emissions have been increasing with climate change,which have the potential to alter the carbon balance and shift the regionfrom a historic sink to a source. It is therefore critically important totrack the spatiotemporal changes in burned area and fire carbon emissionsover time. Here we developed a new burned-area detection algorithm between2001–2019 across Alaska and Canada at 500 m (meters) resolution thatutilizes finer-scale 30 m Landsat imagery to account for land coverunsuitable for burning. This method strictly balances omission andcommission errors at 500 m to derive accurate landscape- and regional-scaleburned-area estimates. Using this new burned-area product, we developedstatistical models to predict burn depth and carbon combustion for the sameperiod within the NASA Arctic–Boreal Vulnerability Experiment (ABoVE) coreand extended domain. Statistical models were constrained using a database offield observations across the domain and were related to a variety ofresponse variables including remotely sensed indicators of fire severity,fire weather indices, local climate, soils, and topographic indicators. Theburn depth and aboveground combustion models performed best, with poorerperformance for belowground combustion. We estimate 2.37×106 ha (2.37 Mha) burned annually between 2001–2019 over the ABoVE domain (2.87 Mhaacross all of Alaska and Canada), emitting 79.3 ± 27.96 Tg (±1standard deviation) of carbon (C) per year, with a mean combustionrate of 3.13 ± 1.17 kg C m−2. Mean combustion and burn depthdisplayed a general gradient of higher severity in the northwestern portionof the domain to lower severity in the south and east. We also found larger-fire years and later-season burning were generally associated with greatermean combustion. Our estimates are generally consistent with previousefforts to quantify burned area, fire carbon emissions, and their drivers inregions within boreal North America; however, we generally estimate higherburned area and carbon emissions due to our use of Landsat imagery, greateravailability of field observations, and improvements in modeling. The burnedarea and combustion datasets described here (the ABoVE Fire EmissionsDatabase, or ABoVE-FED) can be used for local- to continental-scaleapplications of boreal fire science. 

Abstract BackgroundThe global human footprint has fundamentally altered wildfire regimes, creating serious consequences for human health, biodiversity, and climate. However, it remains difficult to project how long-term interactions among land use, management, and climate change will affect fire behavior, representing a key knowledge gap for sustainable management. We used expert assessment to combine opinions about past and future fire regimes from 99 wildfire researchers. We asked for quantitative and qualitative assessments of the frequency, type, and implications of fire regime change from the beginning of the Holocene through the year 2300. ResultsRespondents indicated some direct human influence on wildfire since at least ~ 12,000 years BP, though natural climate variability remained the dominant driver of fire regime change until around 5,000 years BP, for most study regions. Responses suggested a ten-fold increase in the frequency of fire regime change during the last 250 years compared with the rest of the Holocene, corresponding first with the intensification and extensification of land use and later with anthropogenic climate change. Looking to the future, fire regimes were predicted to intensify, with increases in frequency, severity, and size in all biomes except grassland ecosystems. Fire regimes showed different climate sensitivities across biomes, but the likelihood of fire regime change increased with higher warming scenarios for all biomes. Biodiversity, carbon storage, and other ecosystem services were predicted to decrease for most biomes under higher emission scenarios. We present recommendations for adaptation and mitigation under emerging fire regimes, while recognizing that management options are constrained under higher emission scenarios. ConclusionThe influence of humans on wildfire regimes has increased over the last two centuries. The perspective gained from past fires should be considered in land and fire management strategies, but novel fire behavior is likely given the unprecedented human disruption of plant communities, climate, and other factors. Future fire regimes are likely to degrade key ecosystem services, unless climate change is aggressively mitigated. Expert assessment complements empirical data and modeling, providing a broader perspective of fire science to inform decision making and future research priorities. 

Abstract. Global fire-vegetation models are widely used to assessimpacts of environmental change on fire regimes and the carbon cycle and toinfer relationships between climate, land use and fire. However,differences in model structure and parameterizations, in both the vegetationand fire components of these models, could influence overall modelperformance, and to date there has been limited evaluation of how welldifferent models represent various aspects of fire regimes. The Fire ModelIntercomparison Project (FireMIP) is coordinating the evaluation ofstate-of-the-art global fire models, in order to improve projections of firecharacteristics and fire impacts on ecosystems and human societies in thecontext of global environmental change. Here we perform a systematicevaluation of historical simulations made by nine FireMIP models to quantifytheir ability to reproduce a range of fire and vegetation benchmarks. TheFireMIP models simulate a wide range in global annual total burnt area(39–536 Mha) and global annual fire carbon emission (0.91–4.75 Pg C yr−1) for modern conditions (2002–2012), but most of the range in burntarea is within observational uncertainty (345–468 Mha). Benchmarking scoresindicate that seven out of nine FireMIP models are able to represent thespatial pattern in burnt area. The models also reproduce the seasonality inburnt area reasonably well but struggle to simulate fire season length andare largely unable to represent interannual variations in burnt area.However, models that represent cropland fires see improved simulation offire seasonality in the Northern Hemisphere. The three FireMIP models whichexplicitly simulate individual fires are able to reproduce the spatialpattern in number of fires, but fire sizes are too small in key regions, andthis results in an underestimation of burnt area. The correct representationof spatial and seasonal patterns in vegetation appears to correlate with abetter representation of burnt area. The two older fire models included inthe FireMIP ensemble (LPJ–GUESS–GlobFIRM, MC2) clearly perform less wellglobally than other models, but it is difficult to distinguish between theremaining ensemble members; some of these models are better at representingcertain aspects of the fire regime; none clearly outperforms all othermodels across the full range of variables assessed. 

Abstract 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 towards 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.