Community-based Model for Bioenergy Production Coupled to Forest Land Management for Wildfire Control using Combined Heat and Power

With wildfires becoming more frequent and severe in North America and around the world, forest management plans have come under review in an effort to mitigate higher fire suppression costs as well as human and climate induced fire regime changes. When implementing forest management plans, small communities located deep within the wildland urban interface (WUI) are often left out of the equation for reasons largely to do with economies of scale. Yablecki et al. (2011) developed a comprehensive approach to treating fuels to minimize the threat of wildfires in remote areas while using the biomass generated from the forest treatment process for electrical generation, making the communities more sustainable and self-sufficient. Additionally this community-based model afforded long term lowered utility costs and greenhouse gas (GHG) emission reductions. The authors conclude that their proposition combines wildfire mitigation through forest treatment, power generation through use of biomass, and all other associated benefits, in a model that is entirely managed by the community. –Lindon Pronto

Yablecki, Jessica, Bibeau, Eric L., Smith, Doug W., 2011. Community-based model for bioenergy production coupled to forest land management for wildfire control using combined heat and power. Biomass and Bioenergy 35, 2561–2569.

          Using previously published work and available information, Yablecki et al. established and presented a general understanding of the wildfire threats and range of energy (acquisition) needs, and coupled them with common fuels treatment processes and costs per hectare under forest management plans in the USA and Canada. An estimated 20, 000 communities have been identified in the US as vulnerable to wildfires, many of the most severely threatened and previously impacted, lying within the Wildland Urban Interface (WUI)—the area where communities integrate into forested land. In these areas there is less access (escape routes), more dangerous fuel loading in close proximity to homes, and in more remote areas, very limited fire suppression resources. This study postulates that reactive fire management plans are no longer effective, and that in addition to other factors, proactive fuel treatment is preferred to heighten public safety, reduce the high cost of fire suppression activities, and to limit the devastating effects of home and business loss. In more remote communities, the authors propose an all encompassing model to accomplish the aforementioned goals, through community involvement and innovation in sustainable design, while addressing other community needs such as energy generation. In order to partially offset the cost of the forest treatment processes which are to occur every 15 years (in any given area), the use of onsite bioenergy generation is proposed under three models; operating scenarios are illustrated for two of them.
          The first aspect of this model was an evaluation of fuel treatment costs in threatened communities. Costs were determined to vary from a low of $130 per hectare for prescribed fire alone, to nearly $3,000 per hectare with a combination of prescribed fire and mechanical treatment. Although the cost of mechanical treatment was significantly higher, so are the secondary use options, and hence the potential for additional revenue. One commonly associated issue with mechanical treatment is the cost of transporting removed biomass to be processed offsite—something unfeasible for very remote areas. Because the proposed model makes use of biomass onsite, these costs are eliminated. Biomass that was required to meet energy needs under three energy generating system types, were based on estimates of total annual energy use within a given community. The fuels treatment plan was adjusted accordingly to produce a sufficient amount of biomass for the bioenergy systems; the preferred 15–20 year cycles (estimated time before fuel loading becomes hazardous again) was taken into account and the threat of wildfires was greatly reduced under the new management plan.
          The three proposed energy generating systems all fall under the category of combined heat and power (CHP) systems, and are best suited for small scale operations; they are therefore of the more appropriate technologies for these remote communities (most often removed from the power grid to begin with). They are the small-scale CHP steam Rankine system, the organic Rankine cycle (ORC), and the entropic cycle. The small-scale steam Rankine system produces high pressure steam for electricity generation through a direct-fired biomass conversion system that uses a boiler. This system however has the highest capital cost and requires specialized labor. The ORC system, of which there is a proven model commercially available in Europe, has a lower environmental impact and a higher operating efficiency with a 10% (electrical) energy conversion rate. However, it uses a variety of working fluids as alternatives to water, many of which are very volatile. The final approach evaluated, and found to be most suitable, was the entropic cycle. This system uses a process combination of the ORC system and small scale Rankine system to have an overall conversion efficiency of 68% with 12% representing the electrical conversion portion. The entropic cycle is the safest option, does not require specialized labor, and is a closed loop system so it does not require external cooling components and is therefore smaller in size.
Yablecki et al. chose a base case community of 100 residents expending an estimated 240kW (from three small diesel generators) for the modeling exercise; they used data from small communities in British Columbia as reference. They ran two scenarios with the selected three models. The first scenario utilized the CHP systems at 75–100% operating capacity year-round, while using some energy derived from diesel generators to offset a small portion of unmet energy needs in peak times (i.e. winter). The second scenario utilized only biomass; therefore the biomass required as well as the radius of fuel treatment needed, was greater. Between all three CHP energy systems, the entropic system proved to have the lowest capital investment, the highest return, and the lowest biomass input requirements. It therefore had the lowest need for labor intensive treatment processes and the associated costs as well.
To evaluate the GHG emission reductions as a consequence of this community based CHP bioenergy production and forest management model, the authors replaced gasoline fueled vehicles with electrical plug-in hybrid vehicles.  This new fleet of vehicles could derive all their power from the CHP system(s) while only minimally expanding the community bioenergy production model, simultaneously reducing the communities GHG emissions and their dependency on imported fuels. Finally, Yablecki et al. formulated a loose revenue model largely based on overall long term savings while highlighting the revenue streams under the two scenarios. The payback periods under the Entropic and ORC systems were 18 and 24 years, respectively. Considered for example, were the fuels treatment costs per hectare (an average of $1389), and a fuel consumption of 4.8 L per 100km for the hybrid vehicles (PHEV60).

Though the authors cautioned against the variability possible when applying this model to different areas on different scales, they contend that it is a valuable comprehensive community-based solution that goes beyond just mitigating the often devastating effects of wildfires within the WUI in the US and Canada. Yablecki et al. suggest that this model revitalizes communities and addresses a host of issues from public safety, preventative forest fire mitigation practices in remote areas, and maintaining forest health, while reducing GHG emissions and dependence on imported fuels. Overall, this model, suited for small communities, is a sustainability and bioenergy model that uses mechanical forest treatment as its primary support and supply mechanism to provide a wide range of community benefits.

Mapping Wildfire Evacuation Vulnerability in the Western US: the Limits of Infrastructure

In recent decades wildfire severity and occurrence has increased significantly due to a combination of climate change factors such as drought cycles, and population densities in fire prone areas. An increasing point of concern is the emergence of population centers within the wildland urban interface (WUI). This is the area where structures are integrated with or immediately surrounded by areas of moderate to high fire risk and are directly linked to fuel types and topographic features. When population centers in these areas have limited access routes, immediate egress in the event of a severe wildfire threat, becomes an additional hazard for these communities. Cova et al. (2011), focused on identifying some of these high risk communities in the eleven western states. The authors found that there was an inordinate quantity of high risk, densely populated communities with three or fewer evacuation routes in southern California as compared with the rest of the western United States. They imply that more attention should be paid during the planning and development of future communities in WUI areas, as well as taking certain fuels treatment measures to address safety in extant high risk WUI areas. –Lindon Pronto

Cova, Thomas J., Theobald, David M., Norman III, John B., Siebeneck, Laura K., 2011. Mapping Wildfire Evacuation Vulnerability in the Western US: the Limits of Infrastructure. GeoJournal, Springer Science+Business Media B.V. 2011.

         
Climate conditions are increasingly blamed for an increase in wildfire severity and occurrence which has resulted in a high loss of structures and property damage over the past couple of decades. Furthermore, there are an estimated 12.5 million homes in what is considered to be the high risk, fire prone, wildland urban interface (WUI) in the western United States. Many communities are situated in the WUI but are not safely suited or adequately designed for a scenario in which an immediate, mass evacuation would be warranted due to a sudden severe threat of an approaching wildfire. This study projects a worst case scenario where most of a communities’ population is at home (such as during night hours), and evaluates the number of egress routes (supply) against the number of households reliant upon them (demand). Cova et al. evaluated the eleven western states of AZ, CA, CO, ID, MT, NM, NV, OR, UT, WA, and WY,  but divided CA into NoCal and SoCal for a total of 12 files. Important additional factors in evaluating risk include understanding fuel loading and fuel types, localized fire regimes, and identifying topographic features that enhance fire activity. The latter elements critically influence overall computed fire danger when coupled with the identified population centers.
The approach used for identifying these at-risk communities was a combination of initial heuristic assumptions, refined US 2000 census data, geographic information systems (GIS) data for identifying road networks and topography, and a previously established integer programming model. The programming model Critical Cluster Model (CCM) combines contiguous intersections—or “nodes”, within a community (node set), with egress routes (exit links) in a pattern of arcs to extrapolate the maximum ratio of population-to-exits in a community. Constraints of the CCM were addressed through a region-growing algorithm. To acquire the initial data sets, a fire danger layer and a road network layer were applied; this resulted in the immediate removal of areas such as large cities or some desert areas where high fire danger/spread was not present, as well as all unpopulated areas. Through visual and computer generated location sorting, communities were identified that contained up to 100 contiguous intersections, had a minimum median fire hazard of 0.7 on a 0–1 scale, and had a minimum households-to-exit ration of 200 to one.
The computer generated results were grouped as communities with one, two, or three exits. These communities were then identified by state, number of nodes (intersections), and number of homes, fire hazard, and home-to-exit ratio. The highest home-to-exit ratios were then ranked within the three exit categories for identifying communities that exhibited the greatest concern for safety in an immediate egress situation.  Cova et al. found that among all the western states, Southern California consistently exhibited a disproportionately high prevalence of communities of very limited egress with high fire hazard and topographical restraints. For example, they compare a community in WA that had a home-to-exit ratio of 320.9 to 1 (3 exits, 962.7 homes), with a community in SoCal that had a home-to-exit ratio of 1,566.8 to 1 (3 exits, 4,700.3 homes).
This study provides the first rigorous analysis covering a broad geographic area, which identifies and compares low-egress communities in fire-prone areas in the West.  The authors however, strongly caution against using these results beyond the initial enumeration and ranking of fire-prone, low-egress communities in the western United States. They identified a number of significant limitations of their methods and results, largely based on outdated US census data (2000) and the potential of serious miscalculation on the basis of inaccurate GIS street network data for individual communities. This study can however be valued in terms of demonstrating cases of unchecked development in the WUI with little regard to public safety and emergency planning. It can serve as encouragement to local governments to more seriously consider this relatively new threat to public safety and property, by an environmental concern that is noticeably being exacerbated through climate change.

Interacting Disturbances: Wildfire Severity Affected by Stage of Forest Disease Invasion

The presence of disease in wildfire prone areas has generated the assumption that increased disease outbreaks result in increased fire severity. Studies suggest that this relationship is in fact more complex and empirical data show that fuel loading and disease stage are more indicative than merely the presence of disease alone. One challenge when evaluating the effects of disease on fire severity is that often no pre-fire data exist in infected areas, so mapping post-fire characteristics that are induced by pre-fire forest conditions becomes speculative. Metz et al. (2011) had the unique opportunity to observe the effects of Sudden Oak Death (SOD) on wildfire severity on the California Central Coast. They examined results from the 2008 Basin Complex [fire] that had a perimeter encompassing 98 of the 280 plots established in 2006 and 2007 to monitor the effects of SOD on the forest. They found that there was generally minimal difference in fire severity in SOD infested and non-infested plots, except that the more concentrated dead fuel loading on the ground in SOD areas did increase the effects of fire on soil characteristics. Furthermore, the minor effect of SOD on fire severity was more observable in areas that were in the early stages of SOD infections because of the high presence of dead leaves and small diameter branches in the canopy that had not yet fallen to the understory. These “light flashy fuels” can be very volatile when ignited and can increase fire severity. –Lindon Pronto

Metz, Margaret R., Frangioso, Kerri M., Meentemeyer, Ross K., Rizzo, David M., 2011. Interacting disturbances: wildfire severity affected by stage of forest disease invasion. Ecological Applications 21, 313–320.

Sudden Oak Death is an infectious pathogen that is increasingly affecting California coastal forests with high rates of tree mortality, resulting in increased dead fuel loading and altering overall fuel type characteristics; this has varied implications for forest management practices and wildland fire suppression tactics. An extensive network of forest monitoring plots in Big Sur California was able to provide more clarity to these causal uncertainties. The 280 forest monitoring plots were selected as 500-m<!–[if gte msEquation 12]>²<![endif]–> areas, wherein a variety of measurements and classifications were made such as vegetation basal areas (from diameter at breast height) to determine fuel loading, and estimated time since death and whether infection induced or not. The network of plots was established in 2006 and 2007. In 2008 the Basin Complex burned through 35% of the study area, and 61 of the plots were measured immediately after the fire in order to compile accurate data for the pre and post-fire stages. The purpose of the comparison was to answer the following questions: (1) Did pre-fire fuel loads vary among areas that differ in pathogen presence or impacts? (2) Was burn severity higher in areas that had previously experienced higher SOD mortality? (3)Does the stage of disease progression influence burn severity because of changes in fuels through time?
The forest plots were defined under two fuel types (redwood–tanoak and mixed evergreen) and were measured on pre and post-fire occasions to determine disease incidence, mortality, amount of coarse woody debris, and other physical and biological fuel characteristics. First, Mann-Whitney U tests were used on both fuel types to determine the composite burn index (CBI) in both pathogen infested and non infested plots. Secondly, further sequences of tests were performed to find, for example, if CBI increased in areas with higher basal areas of standing dead trees in infected plots; through this process the authors set about to determine some of the relationships of SOD induced fuel characteristics on wildfire severity. The 2006–2007 plot mortality data were used as a proxy for observing an increase of new host mortality, as well as to observe the progression of longer term SOD effects (downed logs) on fuel characteristics and subsequent fire severity.
The results indicated a variety of both anticipated general assumptions as well as slightly more unforeseen overall causal relationships to fire severity. First, Metz et al. found that standing basal area and downed log volume were significantly higher in pathogen infested plots; however, there was no significant difference in abundance of live or dead non-host species between infested and non-infested plot areas. Second, despite the increase in dead woody material of SOD-associated species, no significant increase in burn severity between infested and uninfested plots was observed. Third, the authors found that it was more constructive to evaluate the relationships between burn severity and fuel abundance when two categories were created; one for recent host mortality and one representing an older SOD presence. Recent host mortality is characterized by more fine dead fuels, while longer term infection is observed by more downed heavy fuels (logs). Overall burn severity had a positive linear correlation to higher fuel loadings, as opposed to the presence of the pathogen alone; presence of the pathogen was not indicative of the overall fuel loading. However, one positive linear correlation was found—that higher standing basal areas and downed log volumes in infested plots resulted in increased soil burn severity. Furthermore, it can be assumed that elevated soil burn severity has other implications such as post-fire soil and ash erosion effects on watersheds; however these were not explored in this study. Although SOD mortality does affect a portion of these forests, a significant importance for host fuel abundance in determining burn severity, was not found when infested and uninfested plots were compared.
A similar phenomena to SOD, is the bark beetle outbreaks in many other western forests that also results in areas of high tree mortality. For both these instances it has been widely assumed that there is a positive correlation between tree mortality and fire severity. For both these instances, we now have empirical results that suggest otherwise. This study is consistent with similar studies that suggest perhaps the most significant contributing trait of tree mortality to fire severity is the relationship of time from disease or pest outbreak to time of fire occurrence. In conclusion, Metz et al. cautioned that fire severity was not consistent throughout, due to the large variance in terrain, fuel availability, and weather characteristics at the time of the fire across all of their plots. Concerns that tree mortality significantly influences fire severity are still valid, as geographic areas not explicitly covered by this study can contain a wide variety of species, topographical feature, temperature ranges, and humidity gradients. Nevertheless, this study provides a rare data set for pre and post-fire forest characteristics in SOD infested areas. Further research in this area may be helpful in guiding management and policy decisions for addressing SOD and fire hazards in California forests.

Interacting Disturbances: Wildfire Severity Affected by Stage of Forest Disease Invasion

The presence of disease in wildfire prone areas has generated the assumption that increased disease outbreaks result in increased fire severity. Studies suggest that this relationship is in fact more complex and empirical data show that fuel loading and disease stage are more indicative than merely the presence of disease alone. One challenge when evaluating the effects of disease on fire severity is that often no pre-fire data exist in infected areas, so mapping post-fire characteristics that are induced by pre-fire forest conditions becomes speculative. Metz et al. (2011) had the unique opportunity to observe the effects of Sudden Oak Death (SOD) on wildfire severity on the California Central Coast. They examined results from the 2008 Basin Complex [fire] that had a perimeter encompassing 98 of the 280 plots established in 2006 and 2007 to monitor the effects of SOD on the forest. They found that there was generally minimal difference in fire severity in SOD infested and non-infested plots, except that the more concentrated dead fuel loading on the ground in SOD areas did increase the effects of fire on soil characteristics. Furthermore, the minor effect of SOD on fire severity was more observable in areas that were in the early stages of SOD infections because of the high presence of dead leaves and small diameter branches in the canopy that had not yet fallen to the understory. These “light flashy fuels” can be very volatile when ignited and can increase fire severity. –Lindon Pronto

Metz, Margaret R., Frangioso, Kerri M., Meentemeyer, Ross K., Rizzo, David M., 2011. Interacting disturbances: wildfire severity affected by stage of forest disease invasion. Ecological Applications 21, 313–320.

Sudden Oak Death is an infectious pathogen that is increasingly affecting California coastal forests with high rates of tree mortality, resulting in increased dead fuel loading and altering overall fuel type characteristics; this has varied implications for forest management practices and wildland fire suppression tactics. An extensive network of forest monitoring plots in Big Sur California was able to provide more clarity to these causal uncertainties. The 280 forest monitoring plots were selected as 500-m<!–[if gte msEquation 12]>²<![endif]–> areas, wherein a variety of measurements and classifications were made such as vegetation basal areas (from diameter at breast height) to determine fuel loading, and estimated time since death and whether infection induced or not. The network of plots was established in 2006 and 2007. In 2008 the Basin Complex burned through 35% of the study area, and 61 of the plots were measured immediately after the fire in order to compile accurate data for the pre and post-fire stages. The purpose of the comparison was to answer the following questions: (1) Did pre-fire fuel loads vary among areas that differ in pathogen presence or impacts? (2) Was burn severity higher in areas that had previously experienced higher SOD mortality? (3)Does the stage of disease progression influence burn severity because of changes in fuels through time?
The forest plots were defined under two fuel types (redwood–tanoak and mixed evergreen) and were measured on pre and post-fire occasions to determine disease incidence, mortality, amount of coarse woody debris, and other physical and biological fuel characteristics. First, Mann-Whitney U tests were used on both fuel types to determine the composite burn index (CBI) in both pathogen infested and non infested plots. Secondly, further sequences of tests were performed to find, for example, if CBI increased in areas with higher basal areas of standing dead trees in infected plots; through this process the authors set about to determine some of the relationships of SOD induced fuel characteristics on wildfire severity. The 2006–2007 plot mortality data were used as a proxy for observing an increase of new host mortality, as well as to observe the progression of longer term SOD effects (downed logs) on fuel characteristics and subsequent fire severity.
The results indicated a variety of both anticipated general assumptions as well as slightly more unforeseen overall causal relationships to fire severity. First, Metz et al. found that standing basal area and downed log volume were significantly higher in pathogen infested plots; however, there was no significant difference in abundance of live or dead non-host species between infested and non-infested plot areas. Second, despite the increase in dead woody material of SOD-associated species, no significant increase in burn severity between infested and uninfested plots was observed. Third, the authors found that it was more constructive to evaluate the relationships between burn severity and fuel abundance when two categories were created; one for recent host mortality and one representing an older SOD presence. Recent host mortality is characterized by more fine dead fuels, while longer term infection is observed by more downed heavy fuels (logs). Overall burn severity had a positive linear correlation to higher fuel loadings, as opposed to the presence of the pathogen alone; presence of the pathogen was not indicative of the overall fuel loading. However, one positive linear correlation was found—that higher standing basal areas and downed log volumes in infested plots resulted in increased soil burn severity. Furthermore, it can be assumed that elevated soil burn severity has other implications such as post-fire soil and ash erosion effects on watersheds; however these were not explored in this study. Although SOD mortality does affect a portion of these forests, a significant importance for host fuel abundance in determining burn severity, was not found when infested and uninfested plots were compared.
A similar phenomena to SOD, is the bark beetle outbreaks in many other western forests that also results in areas of high tree mortality. For both these instances it has been widely assumed that there is a positive correlation between tree mortality and fire severity. For both these instances, we now have empirical results that suggest otherwise. This study is consistent with similar studies that suggest perhaps the most significant contributing trait of tree mortality to fire severity is the relationship of time from disease or pest outbreak to time of fire occurrence. In conclusion, Metz et al. cautioned that fire severity was not consistent throughout, due to the large variance in terrain, fuel availability, and weather characteristics at the time of the fire across all of their plots. Concerns that tree mortality significantly influences fire severity are still valid, as geographic areas not explicitly covered by this study can contain a wide variety of species, topographical feature, temperature ranges, and humidity gradients. Nevertheless, this study provides a rare data set for pre and post-fire forest characteristics in SOD infested areas. Further research in this area may be helpful in guiding management and policy decisions for addressing SOD and fire hazards in California forests.

Carbon Loss from an Unprecedented Arctic Tundra Wildfire High-severity Wildfire Effects on Carbon Stocks and Emissions in Fuels Treated and Untreated Forest

Forests contain the planet’s largest terrestrial carbon stocks. Wildfires, by burning forests, release a significant amount of this stored carbon into the atmosphere extremely rapidly. This release interrupts a longer cycle where carbon is sequestered by growing trees and then is finally rereleased during the decomposition of the vegetation. Under forest management practices, forests have in many places been “treated” to lessen the effects of wildfires on tree mortality and to be better positioned to have higher survival during dangerous fires. In a study by North and Hurteau (2011), the short term effects of wildfire on carbon stocks were reviewed using field measurements, comparing treated and untreated forest areas in recent burn scars. The authors found that carbon emissions (during a fire) were more than double in treated areas. They further discovered that when the carbon release from the treating process was added to the emissions of wildfire in those same treated areas, the carbon emissions were significantly higher than untreated burned areas (93% tree mortality rate). This however is over a short time period, and that other studies suggest carbon emissions could be up to three times higher over an extended time of natural decomposition as opposed to the instantaneous carbon release induced by wildfire.  –Lindon Pronto
North, Malcolm P., Hurteau, Matthew D., 2011. High-severity wildfire effects on carbon stocks and emissions in fuels treated and untreated forest. Forest Ecology and Management 261, 1115–1120.

This study collected data from 12 fire sites in California (Region 5), mostly from recent burn scars in the northern Sierra Nevada. The area was chosen for its extensive use of fuels treatment practices by the U.S. Forest Service, which provided the necessary comparison basis for evaluating carbon emissions for treated and untreated fuels during wildfire events. The objective of this comparison was to assess differences in (1) carbon stocks, (2) carbon loss from treatments and wildfire, and (3) tree survival, mortality, and changes in live tree sizes and species composition. The selection areas were constrained to areas that fell under the practice of ‘thin from below’ prescription, through the use of machinery which creates ‘machine piles’ of slash (often discarded from logging operations) which are burned during favorable weather conditions. The study identified 20 treatment areas that had been treated within the past 5 years; the dominant fuel type was mixed-conifer. Areas where fuel treated projects had not been concluded by the onset of the wildfire (such as unburned machine piles), were excluded from the data.
          Using the boundary of fuels treatment projects, 3–6 plots of 0.05 ha for ≥5 cm diameter at breast height (dbh) and 0.1 ha for trees ≥50cm dbh, were selected in both burned/treated and burned/untreated areas, usually measured within 200m from each other for consistency in fuel characteristics. Through a variety of methods, carbon content in treated and untreated stands was calculated as accurately as possible to best represent (estimate) carbon content before the fire to be paired with actual results after the fire. The study assumed that carbon concentration was 50% in woody material and 37% in duff and litter. It was determined that carbon emissions of the fire were 11% of the total stored carbon in treated areas while 25% in untreated areas. North and Hurteau found that on average, fuel treatment removed about 34% of total stored carbon. Additionally tree mortality as a result of the fire was on average 43% and 97% in treated and untreated stands, respectively. The authors determined that if the carbon emitted during the process of treating fuels (i.e. prescribed fire) were added to the wildfire emissions, the treated/burned fuels produced a higher mean net carbon loss (80.2Mg C ha‾1) than the untreated/burned fuels (67.8Mg C ha‾1). However, this is in the context of short term carbon releases, and the same fuels decomposing over an extended period of time will generally produce significantly higher overall carbon emissions. However, if logging operations were used in the treatment process, a part of that carbon store could be subtracted from the overall emissions for that area.
          In treated areas wildfire intensity decreased significantly, and carbon loss and tree mortality was lower. Although the authors found that 75% of the forest carbon stocks still remained onsite after severe wildfires, up to 70% of ecosystem carbon became decomposing pools in untreated areas, with only 19% in treated areas. The overall effect was that regardless of fire severity, carbon sinks become carbon pools until the carbon sequestering of the re-growth process became greater than the carbon emissions from the decomposing stocks in the following decades.
          In summary, North and Hurteau found that treated areas significantly reduced fire severity and consequent mortality and reduced the carbon emissions during the fire event specifically. However, when the emissions from the treatment process were added to those of the fire, carbon emissions were significantly higher than those produced by severe fire in untreated stands (logging excluded). This study was not intended to be extrapolated to entire fire perimeters due to the extremely variable burn conditions of these different fires; the pairs (treated/untreated) were matched to very small areas of each respective burn. Overall, fuels treatment was found to likely shorten the time until carbon was re-sequestered by stand growth, due to higher survivability. This study suggests that fuels treatment projects that reduce wildfire intensity, successfully reduce carbon emissions during wildfire events and over the long term, by reducing the amount of carbon emitting stocks in long term decomposing stages. 

Carbon Loss from an Unprecedented Arctic Tundra Wildfire

As increased frequency and severity of wildfires in historically fire-prone areas pose one set of threats to our ever-more concerning climate situation, scientists have identified a new threat to rising global atmospheric CO₂ levels. Not since the early Holocene epoch has there been any significant wildfire activity or the presence of typical fire regimes within the Arctic tundra biome. As global temperatures rise, changing climatic conditions have introduced wildfire-induced carbon (C) releases in the Arctic tundra that have not been observed in many millennia (perhaps 10,000 years or more). Mack et al. (2011) examined the Anaktuvuk River fire that burned 1,039 km2 of Arctic tundra on the North Slope of the Brooks Range in Alaska, USA, in 2007; this single fire burned more than double the cumulative area burned in the region over the past half-century. They concluded that the C released from this one fire supports the hypothesis that tundra fires have the potential to significantly amplify global warming through the release of concentrated C pools into the atmosphere that in some cases are thousands of years old. –Lindon Pronto
Mack, Michelle C., Bret-Harte, M. Syndonia, Hollingsworth, Teresa N., Jandt, Randi R., Schuur, Edward A. G., Shaver, Gaius R., Verbyla, David L., 2011. Carbon Loss from an Unprecedented Arctic Tundra Wildfire. Nature 475, 489–492.

Mack et al. report that the Anaktuvuk River fire burned 1,039 km² removing 2,016±435 g Cm−2 and 64gNm−2 (or about 400 years of N accumulation) from the ecosystem, an amount they say is two orders of magnitude larger than annual net C exchange in undisturbed tundra. Furthermore they report that “the approximately 2.1 teragrams of C [released] into the atmosphere, was an amount similar in magnitude to the annual net C sink for the entire Arctic tundra biome averaged over the last quarter of the twentieth century.” Approximately 60% of this C loss was from soil organic matter. Radiocarbon dating of residual soil layers showed the maximum age of soil C that was lost in the fire, was 50 years old.
The study area was underlain by permafrost and had a mean annual temperature of –10°C and an average yearly precipitation of 30 cm. The pre-fire vegetation composition of the study area was 54% moist acidic tundra (MAT), 15% moist non-acidic tundra, and 30% shrubland. The study focused on the MAT classification because of its wide distribution and because it had a higher immediate survivability than the other fuel types and therefore was able to provided a benchmark of pre-fire soil organic matter depth and plant biomass. Eleven MAT sites outside the burn area and 20 MAT sites within the burn were sampled. Sites were tested in order to compare pre-fire soil organic layer depth and depth versus bulk density, C or N concentrations and to determine the radiocarbon date of the post-fire soil surface to see whether the fire burned into old and likely irreplaceable soil C pools. The objective was to observe the soil C and N content approximated at pre and post-fire locations to determine the emissions of the particular fire event and to put the results in context with a broader understanding of tundra biome historical norms and characteristics of the climate.
Independent of the transfer of C from the tundra soils to the atmosphere is the threat that any significant disturbances by wildfire have the potential to change local thresholds and alter the ecosystems structure and function through the alteration of surface reflectance (albedo) and energy balance of landscapes that are underlain by permafrost. For example, lake sediment cores showed that there was no observable wildfire activity within the study area over the past 5,000 years. A wildfire event of the magnitude of the Anaktuvuk River fire, has the potential to destabilize the underlying permafrost allowing it to release additional C into the atmosphere during the subsequent decomposition process (as a result of exposure), and adding significant potential for contributing to positive feedback to high-latitude warming. An additional important consideration are the increased concentrations of C stored at increased depths in peat soils, for when drying does occur in this fuel type, the fire doesn’t only burn in a greater radius but can do more vertical damage as well in the semi-combustible soils; an image of the burn scar conveys this phenomenon very well. In this study in particular, though there were areas that had a soil depth range of 12.3–43.3 cm, the maximum burn scar areas were no greater than 15 cm in depth.
Mack et al. conclude that even a single surficially burning wildfire in the Arctic tundra biome can offset or even reverse biome-scale C uptake. Furthermore, C released into the atmosphere from fire occurs at a rate of 30–50 times greater than C release through natural decomposition mechanism such as, for example, stimulated soil organic matter decomposition from a 5°C increase in mean annual temperature. One possible implication raised by the authors is that changing local thresholds may lead to succession patterns that replace the current biome organic soil and vegetation composition with more shrubs. Such a shift would have the potential to …“trigger additional positive feedbacks to climate warming because shrub-dominated ecosystems have higher productivity and plant biomass offset by lower soil C stocks.” Although scientific knowledge and experience with the effects of fire in the Arctic tundra biome are very limited, an increase in this phenomenon has led studies such as this one to conclude that the possible near-future effects of fire in the Arctic can have catastrophic implications for atmospheric carbon levels as well as terrestrial carbon capturing and storing. As seen in the last 20 years, this dangerous positive feedback system of climate change is accentuated—from the high latitude warming resulting in melting snowpack and permafrost, retreating sea ice, to the drying-induced fire having varying consequences from albedo loss to instantaneous mass C releases from age old stocks. 

Characterization of Wildfires in Portugal

An increase in forest fires in Portugal supports climate change models suggesting that the two phenomena are linked. In recent decades the occurrence of wildfires, their severity, and the area burned, have all increased. In an effort to help in formulating a fire management plan, Marques et al. (2011) conducted a study to characterize wildfires in Portugal. The object of the study was to demonstrate trends in fire activity and examine how fuel type, fuel load, elevation, and socioeconomic factors have bearing on fire severity. What the authors found was that fire behaved selectively based on fuel type, slope and elevation, and proximity to roads and populated areas. Furthermore, they established that shrubs displayed the most significant fire activity potential, especially at higher elevations on slopes greater than 5% and further away from socioeconomic influences. –Lindon Pronto
Marques, S.,  Borges, J. G. J., Garcia-Gonzalo, Moreira, F.,  Carreiras, J. M. B., Oliveira, M. M., Cantarinha, A.,  Botequim, B., Pereira, J. M. C., 2011. Characterization of wildfires in Portugal. European Journal of Forest Research 130, 775–784.

Using historical fire information data, a 33-year-long period from 1975 to 2007 was used as a basis for observing trends in fire occurrence, proximity, and severity. Burned area mapping was established through the use of high-resolution remote sensing data by the Remote Sensing Laboratory of Instituto Superior de Agronomia. The study was broken down into three separate 5 year sub-periods (1987–1991, 1990–1994, and 2000–2004) in an attempt to minimize the effects of land cover changes over time. From land cover maps the authors were able to identify fuel types and distribution. In addition to devising 10 classes of cover types for the purpose of the study, Marques et al. identified altitude, slope, proximity to roads, and population density as four additional variables for modeling purposes. Altitude and slope data were obtained from the country’s digital terrain model (DTM); GIS overlays from the Instituto Nacional de Estatística provided data on road proximities and population density. Relationships between Ecological and socioeconomic variability and fire occurrences during the three sub-periods were largely based on statistical models.
Over the 33 year period fire perimeter data show that there were 35,194 wildfires which were greater than 5 ha in size. Area burned per year ranged from 15,500 ha in 1977 to 440,000 ha in 2003, where a single fire was responsible for 58,000 ha alone. The first sub-period (1987–1991) had 7,672 starts; the second sub-period (1990–1994) exhibited significantly calmer fire activity with 5,703 starts. The third and final sub-period (2000–2004), was characterized by a significant increase in fire occurrence and size; while the period had 7,383 starts, the area burned was over 43% greater than the first sub-period and 182% for the second sub-period respectively. Most notably the final period exhibited the occurrence of four very large fires being greater than 20,000 ha each in size. There were no fires greater than 20,000 ha during the first 25 years of data.
Weighted generalized linear models (WGLM) proved that the number one high risk fuel was shrubs, followed by mixed stands, softwoods and hardwoods; individual species added variance based on fuel loading, resin, and foliage essential oil content. Marques et al. also observed that fires occurred more frequently at higher elevations, which was attributed to higher lightning activity levels (LAL) and escaped pastoral burns. An additional factor found more generally at higher elevations was that of greater slope which contributed to faster rate of spread. In populated areas in Portugal, although human activity is the number one cause of wildfires, their proximity to roads and population centers allows for a very quick response time from firefighters who are often able to extinguish the fires when they are still small. When fires occurred away from populated areas where there was limited or no access, data show that these fires tend to become very large, especially in mountainous areas where slope accelerates rate of spread. There was a positive correlation between distance from populated areas and the area burned.
Through this study, Marques et al. were able to characterize wildfire in Portugal with special attention to socioeconomic influences, fuel type, and landscape specific variability. The technique which made this approach possible was the use of weighted generalized linear models which highlighted the relationships of ecological and socioeconomic factors. This study is intended to provide a starting point for policy makers to develop an appropriate and effective fire management plan that is current with wildfire activity trends and congruent with the possible effects of climate change. It provides a context for developing fire prevention practices and policies; furthermore, it suggests continued work in this subject area to translate these results into functioning fire prevention and suppression models for the country of Portugal.