Evaluating Impacts of Climate Change on Fire Regimes, Landscape Dynamics, and Fire Management Using the Simulation Model Fire-BGCv2
Fire management faces some challenging issues in the future and none are more important than how to deal
with effects of climate change in fire management. Fire-BGC, a mechanistic ecosystem dynamics model, was
used to examine ecological responses to future climates, fire regimes, and fire management within a forested
landscape at Glacier National Park. We used a full factorial experimental design including climate (historical,
current, and predicted future scenarios) and fire (historical fire return and varying levels of fire suppression) as
factors to simulate potential effects of disturbance on wildfire dynamics, landscape composition and
configuration, and ecosystem function for a 500-year simulation period. Simulation results indicate that the
interactions among climate changes and disturbance processes stimulate vegetation species conversions
and amplify fire dynamics, and that landscapes show increased homogeneity and contiguity and reduced leaf
area index (LAI) and proportion of late seral species under future climates. The project and its results
demonstrate the importance of climate and fire in structuring mountainous ecosystems, and provide a method
for evaluating potential management responses for climate change mitigation and adaptation.
Changes in Fire Regime Catalyze Ecological Responses to Climate Change in Boreal Forests
The boreal forests of western North America are experiencing rapid directional changes in climate that are predicted to continue into the next century. The responses of boreal forest plant communities to climate change may be constrained over the short term by factors that create resistance to change, such as slow population turnover rates and strong plant-environment interactions. In this situation, disturbance may act as a key catalyst for ecosystem change. However, important disturbance agents such as fire are also sensitive to climate, and climate-induced changes in disturbance regime are likely to have direct effects on ecological communities. Our research focuses on how changes in different components of the fire disturbance regime, such as fire frequency and severity, may drive forest ecosystem responses to climate change. This research focuses on spruce-dominated boreal forests of Alaska and Yukon, and their potential to shift to deciduous-dominated forests. A combination of experimental, observational, and modeling approaches provide information on how interactions between reproductive traits and disturbance characteristics influence the long-term resilience of boreal systems. Recent research in the widespread 2004 burns in Alaska aims to understand the combinations of abiotic conditions and fire effects that shape forest resilience across heterogeneous landscapes. Our data suggest that shifts to increasing severity or frequency of fire in northern boreal forests will stimulate an increase in deciduous landscape cover, and that these changes in forest cover may feedback to mediate climate effects on fire regime.
Quantifying wildland fire emissions at landscape to continental scales
The basic approach to estimating biomass burning emissions was developed over 25 years ago. Since then, refinements in emissions modeling have progressed with techniques developed to look at spatial and temporal (seasonal) patterns at multiple scales. Much of what has been developed has been to understand the impact of wildland fire on carbon dynamics. This research has shown that a substantial proportion of the carbon moving from the terrestrial biosphere to the atmosphere is through fire. Also of interest has been improved quantification of the impact of these natural events on air quality. Pollutants, including CO, ozone, and VOCs, from fire have been shown to rival levels of anthropogenic emissions during some fire events. Smoke from forest fire can be transported vast distances to impact air quality thousands of miles from its origin. Over the past two decades research on refining fire emission estimations at several spatial scales and quantifying the uncertainly in these measures has shown that we still have more to learn. In this presentation we describe the methods of quantifying carbon and pollutant emissions from fire at the North American continental scale using basic information derived from local and landscape scale data and models. We present a review of the tools and science used to improve our understanding of the impact of wildland fire emissions for continental and global carbon cycle modeling and review progress on a current NASA-funded project to provide easy access to the most up-to-date fire emissions estimates for North America.
Controls on Organic Layer Combustion Severity During Wildfire in Boreal Bogs
Wildfires are the dominant natural disturbance to western Canadian peatlands, affecting an average of 1870 km2 annually and releasing 3.5 Tg of carbon (C) to the atmosphere through partial combustion of the extensive surface organic layer (peat) found therein. Combustion severity within fire-affected peatlands is variable, ranging from unburned islands and lightly burned "Sphagnum sheep" to deeply charred areas with >10 cm of surface fuel combustion. Spatial heterogeneity in combustion may be due to variation in moss community composition and corresponding variability in fuel condition due to interspecific differences in water retention ability and peat bulk density. However, the controls on surface organic layer combustion severity are poorly understood. We conducted a laboratory combustion experiment to examine the influence of peat type and soil moisture on the occurrence and depth of peat consumption. The soil moisture profiles of replicate monoliths of the three prevalent western Canadian bog peat types (Sphagnum fuscum hummocks, Pleurozium schreberi hummocks, and multi-species hollows) were manipulated to simulate field, moderately dry, and severe drought moisture conditions. Following manipulation and assessment of initial fuel conditions (bulk density, soil moisture, and surface topography), the monoliths were instrumented with soil moisture (TDR) probes and thermocouples and exposed to a constant radiative heat source, monitoring changes in soil moisture, temperature, and surface elevation from ignition to the extinction of combustion. We found bulk density and soil moisture interactively influenced depth of combustion through controls on peat thermal properties. Stratigraphic variation in bulk density and soil moisture created barriers to the downward propagation of combustion, which varied within and among monoliths. From these results, we developed a one-dimensional heat transfer model capable of predicting the depth of peat consumption based on peat bulk density and soil moisture stratigraphy. This model provides a framework for assessing current and future vulnerability of the peat organic layer to combustion losses during wildfire.
Predicting Stand-Level Fire Behavior From Forest Community Data in Former Prairie and Savanna
As development pressures continue to expand the extent of the wildland-urban interface (WUI), the ability to predict fire regimes there becomes increasingly important. Such predictions will be particularly valuable to land managers who seek to reduce wildfire risk and to restore imperiled ecosystems within the WUI. Our study focused on remnant and former upland prairie and oak savanna ecosystems in the southern Willamette Valley, Oregon, which were widespread prior to Euro-American settlement but now occupy less than 2% of their historic range. Prairie and savanna grasslands provide habitat for several endangered species, as well as important ecosystem services, such as the regulation of fire regimes. We sampled over 250 plots from seven sites that were grasslands with few to no trees circa 1850 but now have markedly different communities, ranging from prairie to dense forest. We collected data on community composition, topography and fuel loadings. With the BehavePlus fire model, we calculated surface and crown fire parameters. We built two classification and regression trees (CARTs) that used plant community data to group plots on the basis of their surface-fire and crown-fire behavior, respectively. Fuel loads differed significantly by community type, although trends in fuel loadings were neither monotonic across communities nor intuitive. Fuel characteristics were extremely sensitive to topography, and may result from successional history and the presence of exotic invasive species. Though the CARTs were statistically significant, they generally had poor predictive power, which is indicative of the amount of variability inherent in wildland fire. There was greater variability in fire behavior for more intense fires, indicating that land managers can improve the precision of their predictions by managing for less intense fire regimes. The CARTs suggested that surface fires differed among nine different community types and crown fire behavior differed among five different community types. There was poor agreement among definitions of communities as determined by the CARTs based upon fire behavior, and communities based on stand density and species composition. The CART community classifications are significantly better at predicting surface and crown fire behavior than conventional vegetation classification systems. A fire-behavior-based classification system will therefore give land managers a better understanding of potential fire behavior on their lands. Our results provide a quantitative basis for determining the relative benefits of different land management options, including oak savanna restoration, in attenuating surface or crown fire behavior.
Measuring Wildland Fire Radiant Power, Energy Release and Gas Evolution at 'Intermediate Scale'
Wildland fire has been observed and studied at the laboratory scale (~ 1m) and Landscape scale (~100m) but little effort has been made to compare and correlate data taken at these differing scales. We have undertaken a comprehensive program of investigation of wildland fire radiant energy release at all scales. In this paper we discuss experiments that check the basic assumptions relating radiant energy release to fuel consumption at an 'intermediate scale' of ~ 5m. We measured the vertical radiant flux and total fire radiant energy release (FRE) from wildland fuel material in addition to gaseous combustion products. For this experimental series, and other experiments performed at laboratory and landscape scale, we developed a suite of fire measurement apparatus including an inexpensive two-band infrared radiometer, a combustion gas concentration monitor and a 3-axis orthorectified videography system. The experiments in this study were conducted at a spatial scale of ~5m and a temporal scale of 5s in outdoor plots using prepared, previously collected wildland fuels characteristic of the hardwood oak-hickory-maple forest of the Eastern United States. We measured a linear increase in radiant energy output with fuel loading over a range of fuel loadings from 0.16 kg/m2 to 3.36 kg/m2. The proportion of energy produced radiantly was relatively constant at around 20%. It is envisioned that this work, combined with other investigations at differing spatial scales currently under way by our group, will allow correlation of various fire effects to radiant energy release in a 'dose-response' relationship.
Empirical Evidence for Self-Organized Patterns in California Wildfire Sizes: Implications for Landscape Resilience
Wildfires are an important disturbance in many western US ecosystems and are integral in shaping spatial and temporal vegetation patterns. Ecological resilience has been described as the amount of disturbance that an ecosystem could withstand without changing self-organized processes and structures. Inherent in resilient systems are observable self-organized patterns in vegetation and processes on the landscape. It is theorized that self-organized systems are capable of withstanding a large range of disturbance sizes and intensities without significantly changing the resultant distribution of vegetation patch sizes over time. Past research has used power-law statistics to describe self-organization in wildfire behavior, and we extend this research using several different methods to identify evidence for landscape resilience over a large geographic area. We used a catalogue of California wildfires (>1ha; 1950-2007) grouped at multiple levels within Bailey's hierarchy of ecoregions to (1) identify self-organized patterns in wildfire size distributions across the state, (2) identify lower and upper limits on self-organized behavior, and (3) find links between these patterns and top-down and bottom-up processes. Within most ecoregions we found reliable evidence for self-organized behavior in wildfire size distributions. Evidence included good fits of: (1) 2-3 parameter statistical distributions within the Pareto and Generalized Beta II (P/GB2) family of distributions over the entire range of fire event sizes; these distributions all have in common a power-law tail, (2) the Pareto I (power-law) distribution to the right-tail of the fire-size distributions, and (3) broken-stick regression models to the inverse cumulative distribution functions for fire sizes. For most ecoregions, self-organized properties were generally limited to fires within 100 to 10000 ha, indicating that meso-scale processes controlling fire sizes likely are acting at this scale. Scaling parameters for wildfires in this region averaged 1.7 for most ecoregions, which are well within prior estimates for fires in other regions of the country. Potential bottom-up drivers, including topographic features such as aspect and slope patches, also fit well to power-law distributions, and scaling parameter estimates matched closely with fire-size distributions. Significant differences in fire size distributions among ecoregions likely indicate top-down controls from broad-scale geological and climatic factors. These results suggest that ecosystems within California are likely resilient to wildfire disturbances <10000 ha, and are best modeled with P/GB2 statistical distributions. Likewise, wildfires across this range likely respond to topographic and broad-scale climate influences.