6. Fire and Fuels Assessmentcwam.ucdavis.edu/Volume_2/CWAM_II_6_FireFuels.pdfmobile animals. Many insects, rodents, reptiles, and amphibians are able to shelter themselves during fires

6. Fire and Fuels Assessment

Introduction Wildfire is a natural part of many California ecosystems, particularly the conifer forests, chaparral, and oak woodlands that cover 50% of the state. Any assessment of a watershed’s condition must include the role of fires and fuels within that watershed. Although fires have burned in California for millennia, evidence shows that over the last few decades fires in California and the West in general have become larger, more costly and dangerous to suppress, and are often more severe in their effects (Chang 1996; Skinner and Chang 1996; Agee 1998; Arno and Allison-Bunnell 2002; DellaSala et al. 2004; Stephens and Ruth 2005; Stephens and Sugihara 2006). It should be noted that there has also been evidence presented to show that this trend has been exaggerated (Erman and Jones 1996). Since the early 20th century, federal and state land management policy has generally required that fires be quickly suppressed. One important result, particularly in ecosystems where fires were historically frequent, has been an increase in the flammable materials that had previously been removed by small, frequent fires (Dodge 1972; Agee 1993; U.S. GAO 1999; Noss et al. 2006). The rapidly growing field of wildfire science and its application to watershed assessment is laid out in the following chapter sections: I) the ecological role of fire, II) fire behavior and fuels, and III) the effects of fire from a hydrology and watershed perspective. Finally, sections IV) and V) of this chapter provide a summary and checklist of fire- and fuels-related considerations for a watershed assessment. I. Fire Ecology Fire ecology is the study of the role of fire in ecosystems. Far from being the disasters that the media frequently portray them to be, fires in California are essential in maintaining the state’s spectacular biodiversity. Not only do fires engender the diversity of California’s ecosystems, they directly and indirectly affect the services and products these ecosystems provide to the state’s human residents; these include clean water, timber, and recreation opportunities. This is not to say that all fires are beneficial or that they now burn as they did historically. Some fires may be disasters from both an ecological and a social perspective. Fire ecology provides guidance for appropriate fire management that balances today’s often highly complex and competing societal and environmental demands. Important topics addressed by fire ecology are fire regimes, fire’s effect on animals, and fire’s effect on vegetation. Fire effects on other topics (soils, hydrology) are discussed in section III.

Chapter Guide Introduction 1 I Fire Ecology 1 II. Fire Behavior and Fuels 5 III. Fire’s Effects on Soils and Hydrology 18 IV. Methods for Analyzing Effects of Fuels Management 23 V. Summary 25 VI. Checklist for Considering Fire and Fuels in a Watershed Assessment 28

California Watershed Assessment Manual, Volume II – Fire and Fuels Draft

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Fire Regimes The historic role of fire in a given location or vegetation type can be described by its fire regime. A fire regime quantifies when, where, and how fires burned by specifying their frequency, seasonality, size, behavior (intensity), and effects (severity). Fire regimes are usually described for pre-European settlement conditions (roughly the mid-19th century in most of the state) before fire exclusion policies reduced the frequency of fires. These historic fire regimes can be contrasted with current fire regimes. Various techniques such as dendrochronology (tree ring dating), stand structure analysis, lake sediment analysis, and researching historical records are used to describe historic fire regimes. Most fire regimes can be classified simply by frequency and severity (Table 1). Historic fire regimes of several important vegetation types in the Sierra Nevada have been categorized more specifically through modeling and literature review (Table 2). Table 1. Fire regimes (Sugihara et al. 2006).

Fire Regime Frequency Severity I 0-35 years Low (mostly surface fire) II 0-35 years High (mostly stand replacing fire) III 35-100+ years Mixed (patches of both low and high severity) IV 35-100+ years High (mostly stand replacing fire) V 200+ years High (mostly stand replacing fire)

Table 2. Fire regimes of several key Sierra Nevada vegetation types (Safford and Schmidt 2007).

Vegetation Type Mean Frequency (years)

Mean Severity Proportions (low/mixed/high)

White fir-mixed conifer 15 60/25/15 Ponderosa pine-mixed conifer 12 80/15/5

Red fir-white fir 35 50/30/20 Montane chaparral 32 0/5/95

Fire frequency, or fire return interval, is the average number of years between fires for a given location. This varies by location and by vegetation type. Some areas of California such as the mid-montane mixed conifer forests that cover substantial portions of the Sierra Nevada burned very frequently. Individual trees in those forests often contain fire scars that reflect burns as often as once every 10 or fewer years (Kilgore and Taylor 1979; Caprio and Swetnam 1995). Other locations, such as subalpine forests, burned much more rarely, roughly once every several hundred years (van Wagtendonk and Fites-Kaufman 2006). Typical fire return intervals for conifer forests range from 2-60 years, oak woodlands burned with similar frequencies, and many chaparral ecosystems experienced fires every 40 or more years. Today the vast majority of fires in all vegetation types are quickly suppressed (except subalpine), resulting in much longer fire return intervals than historically. However, in some cases, such as southern California chaparral, fire return intervals can be shorter than historically where human-caused fires are increasingly common. The seasonality of fires also varies widely between vegetation types. Climate patterns and vegetation growth patterns are the primary determinants of when fires are most likely for a given ecosystem. The historic (and current) seasonality of conifer forest fires is summer to fall, while in oak woodlands the fire season starts in the spring and lasts until fall. Chaparral fires are most common in the late summer and fall.


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Like most fire regime attributes, fire size depends not only on vegetation type but on topographic features (i.e., slope steepness, slope position, aspect, and elevation) and weather conditions (i.e., wind speed, relative humidity, and temperature). Fires in most conifer forests are generally thought to have been small to medium in size (tens to thousands of acres) historically. Fires in oak woodlands and chaparral were often larger if fuel conditions were continuous (van Wagtendonk and Fites-Kaufman 2006). Today the few fires that escape suppression may become much larger (thousands to tens of thousands of acres and occasionally more than 100,000 acres) (NIFC 2002; Finney 2005). The fire effects component of a fire regime refers to how fire directly or indirectly influences plants, animals, soils, air quality, etc. This is often referred to as fire severity (an ecological characteristic) as opposed to fire intensity (a physical characteristic of fire described in the next section). Fires can be described as low severity, moderate severity, or high severity depending primarily on the impact to vegetation. Another aspect of fire effects is fire type (ground fire, surface fire, or crown fire). For example, many surface fires- fires that consume fuels on the surface of the ground- are low intensity because they inflict little damage to vegetation. On the other hand, crown fires- fires where part or all of the canopy is engaged in burning- tend to be high severity because they kill most of the above-ground vegetation. Many of California’s conifer forest and oak woodland fires were historically low-severity surface fires where the majority of trees survived the fire. Due in large part to fuel accumulation, many of these forests currently burn with much higher severity (Skinner and Chang 1996). Chaparral fires, both historically and currently, tend to be high-severity due to both burning conditions and the flammability of the vegetation. Fires and Animals Many animals in California are either adapted to survive fires or actually depend on fires to maintain conditions necessary for their survival. Most fires do not directly kill larger or highly mobile animals. Many insects, rodents, reptiles, and amphibians are able to shelter themselves during fires. While some high-severity fires can create large areas of dead vegetation and degraded soil, most fires provide benefits to animals by creating habitat (e.g., snags) and new or improved food sources (e.g., resprouting shrubs). Some threatened animals, such as the California fisher, need fires to maintain the forest structure they require for nesting and foraging. Only where the fire regime has been highly altered or where the animal population of interest is in poor condition does a fire threaten that population’s survival (Shaffer and Laudenslayer 2006). While further research is needed to better understand the interactions between animals and fire, it is clear that altered fire regimes can significantly affect the conditions animals need to survive (Smith 2000). Fires and Vegetation Many of California’s plant species are fire adapted. Some of the most interesting adaptations occur in conifer forests and chaparral ecosystems. Ponderosa pine in particular has very thick bark that serves as excellent insulation from heat damage. Many pine trees also tend to drop their lowest branches, preventing fires from spreading into their crowns. Examples of individual ponderosa and sugar pine trees that have withstood frequent burning for several centuries have been found across California. Other pines, such as lodgepole pine and knobcone pine, are less likely to survive a fire individually, but their cones are serotinous, meaning that they remain sealed shut by resins until heated by a fire. After the fire, when competing vegetation has been removed and the soil surface has been cleared, the burned area is flooded with pine seeds. In contrast, many firs are considered to be fire-intolerant due to their low foliage and thinner bark.


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Fires in oak woodlands are typically surface fires that consume grasses and oak woody debris. Mature oaks survive these low-intensity fires and the grass quickly resprouts. Many, if not most, of California’s chaparral species either resprout after a fire or depend on seeds in the seed bank (Keeley et al. 2005a, b). Because chaparral fires are usually both high-severity and high-intensity fires in which the aboveground foliage is consumed by the fire, chaparral species must be highly fire-adapted. They also tend to have an abundance of highly flammable compounds in their foliage, further promoting high-intensity fires. Many Manzanita species resprout after a fire while many Ceanothus species produce seeds that rely on fire for germination. Chemise, on the other hand, is both a resprouter and a fire-dependent seeder. Altered fire regimes can profoundly impact vegetation composition and structure. In many conifer forests where pines were favored by frequent, low-severity fires, lengthened fire return intervals have resulted in firs filling in below the pines. When these areas burn, they tend to experience high fire severity due to the altered species composition. Chaparral ecosystems are susceptible to type conversion to grasses where the fire regime has been highly altered, although Keeley et al. (2005c) found that post-fire recovery of long-unburned chaparral stands was indistinguishable from that of younger stands. When fires are more frequent than they were historically, individual plants may be either unable to store the necessary resources to allow later resprouting or unable to produce enough viable seed to ensure that species’ local persistence. Another consequence of altered fire regimes is shifted distributions of vegetation structure across the landscape. Unique combinations of plant species, size, age, and canopy cover- termed seral stages- have been defined for a variety of vegetation types. Examples include early seral stage stands where fire has essentially reset the vegetation back to some starting point and mid-seral closed canopy stands composed of dense medium-sized trees, typically less than 30 years old. Fire ecologists are able to estimate typical historic percentages of these seral stages within a given watershed. Fire suppression, in conjunction with other human activities such as timber harvest, has altered seral stage distributions in many lower- to mid-elevation forests in the Sierra Nevada (Kilgore 1973; Miller and Urban 2000). These current conditions can be compared to historic reference

010

2030

4050

Earlyseral

Mid-seral

dense

Mid-seralopen

Late-seral

dense

Late-seralopen

010

2030

4050

Earlyseral

Mid-seral

dense

Mid-seralopen

Late-seral

dense

Late-seralopen

Figure 1. The graph on the left shows a scientific estimate of the historic distribution (percent of landscape) of white fir-mixed conifer seral stages under an unaltered fire regime. On the right is the current seral stage distribution across the Eldorado National Forest. Dense and open refer to more than 50% canopy cover and less than 50% canopy cover respectively (Safford and Schmidt 2007).


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conditions and a measure of departure can then be determined. Maps and reports of a watershed’s departure from reference conditions are useful for fire and restoration planning as well as assessing watershed health. For example, fire ecologists have shown that seral stage distributions within white fir-mixed conifer forest stands on the Eldorado National Forest are significantly altered from historic distributions (Safford and Schmidt 2007). This is a result of fire suppression as well as logging and other disturbances (Figure 1). In addition to negative impacts on biodiversity, habitat, and fire regimes, these seral stage distribution changes can alter hydrology (see section III) (Gruell 2001). II. Fire Behavior and Fuels An assessment of wildfire risk provides information as to treatments, management practices, and conditions that would reduce or minimize wildfire extent, severity, and damage to ecosystem resources, homes, and communities. Understanding fire ecology as a natural part of watershed processes is key to protecting watershed and community values from severe fire and from excessive management of vegetation. The effort and information that go into the Fire and Fuels Assessment section of a watershed assessment could also be used in the development of a Community Wildfire Protection Plan (CWPP; http://www.cafirealliance.org/cwpp/), which in turn can be used to develop specific fuels treatments and management actions to address wildfire issues and to apply for grants to implement those plans. A CWPP is a community based planning document to reduce the risk of wildfire. In many communities fire plans have been developed. They can provide valuable source of information on fuel hazards and provide an existing planning framework for prioritizing fuel reduction projects and lowering the risk of wildfire. The California Fire Alliance website contains a listing and links to existing CWPPs. The nature of wildfires and wildfire behavior Fires need oxygen, heat, and fuel (defined as any combustible material- typically live or dead vegetation) to continue burning. Therefore, fire suppression consists of removing one or more of those three elements of the fire triangle. It is difficult to effectively smother a fire, so suppression efforts usually focus on removing heat via the application of water or chemical retardants and removing fuels by establishing a fireline or conducting burning operations. A fire’s behavior (i.e., how fast it spreads and how intensely it burns) is constrained by three requirements commonly known as the fire environment triangle: fuel, weather, and topography (Figure 2). In addition, the fire itself has the potential to influence fuel (e.g., pre-heating) and weather (e.g., convection columns).

http://www.cafirealliance.org/cwpp/


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Figure 2. The fire environment triangle consists of fuel, weather, and topography. Source: Gary Nakamura

Weather and topography are the components of the fire environment triangle that lend themselves the least to human manipulation. Key weather conditions that influence fire behavior are wind speed and direction, air temperature, relative humidity, and fuel moisture content. Predictions of wildfire behavior and the effectiveness of fuels and fire hazard reduction actions are qualified by the given fire weather conditions. Fuel breaks are not typically designed to be effective under the most extreme fire weather conditions (e.g., high wind, low relative humidity) because they would likely be more extensive and/or intensive than would be socially, economically, or environmentally acceptable. Often, wildfire control requires a change in the weather conditions. Topographic features such as chimneys (steep, narrow drainages), aspect, and hillslope can critically intensify fire behavior. Rugged topography makes fire suppression more costly, dangerous, and ineffective. Topographic alterations are not feasible on the scale necessary to influence fires. That leaves fuels as the only element of the fire environment triangle that can be readily manipulated ahead of or during a fire. Important fuel properties include type (e.g., chaparral or light logging slash), quantity (tons/acre), compactness (density), arrangement (horizontal or vertical orientation), and condition (live or dead vegetation). These are discussed in further detail below. Wildfire intensity is typically described in terms of the fire’s average flamelength. Reducing fire intensity with fuel reduction treatments will create defensible spaces- areas of low fire intensity where ground resources (firefighters, engines, bulldozers, etc.) can safely and effectively work. Fuel types To the extent that fuels drive fire behavior, surface fuels (fuels on the ground surface or within six feet of it) control wildfire behavior. In forest ecosystems, surface fuels consist of live and dead foliage and branches that may still be intact or may have fallen on the ground naturally or due to timber harvest or other activity. Ladder fuels are the small trees, brush, and lower limbs of the larger, overstory trees in the forest. These fuels are important because they can move a surface fire into the canopy. Crown fuels are the upper foliage, limbs, and branches of overstory


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trees. Most forest wildfires are controlled by surface fuels and fire conditions. Crown fires occur where there are sufficient surface and ladder fuels to carry a surface fire into the crowns of trees and where the canopy is dense enough to allow a fire to continue burning through the canopy. Crown fires not only frequently kill even large, mature trees, but they are also the source of most fire brands and can be extremely difficult to control. Because fuels are such an important aspect of fire behavior, the US Forest Service and other agencies have invested decades of research in developing standard fuel models that can aid in predicting fire behavior. A fuel model is a set a parameters that describes the amount, size distribution, and other aspects of common fuel types. These fuel models can be used in charts or software to predict fire behavior for given conditions. One commonly used collection consists of 13 fuel models (Table 3), although recently a new set of 40 fuel models has been developed that allows more flexibility in its fuel parameters (Scott and Burgan 2005). Several fuel models are especially important in California. These are the chaparral fuel model (Anderson FM 4), the timber with grass and understory fuel model (Anderson FM 2) which is used for oak woodlands, and three timber litter models (Anderson FM 8, 9, and 10) which are used for conifer forests. The reader may wish to refer to “Aids to Determining Fuel Models for Estimating Fire Behavior” (http://www.fs.fed.us/rm/pubs_int/int_gtr122.html) for specific details and example photographs of these fuel models.

Table 3. Description of fuel models used in fire behavior as documented by Albini (1976) Source: Anderson (1982).

Fuel model Typical fuel complex 1 hour 10 hours

100 hours Live

Fuel bed depth

Moisture of extinction dead fuels

Tons/acre Feet Percent

Grass and grass-dominated

1 Short grass (1foot) 0.74 0.00 1.00 0.00 1.0 15

2 Timber (grass and understory) 2.00 1.00 0.50 0.50 1.0 15

3 Tall grass (2.5 feet) 3.01 0.00 0.00 0.00 2.5 25

Chaparral and shrub fields

4 Chaparral (6 feet) 5.01 4.01 2.00 5.01 6.0 20 5 Brush (2 feet) 1.00 0.50 0.00 2.00 2.0 20

6 Dormant brush, hardwood slash 1.50 2.50 2.00 0.00 2.5 25

7 Southern rough 1.13 1.87 1.50 0.37 2.5 40 Timber litter

8 Closed timber litter 1.50 1.00 2.50 0.00 0.2 30 9 Hardwood litter 2.92 0.41 0.15 0.00 0.2 25

10 Timber (litter and understory) 3.01 2.00 5.01 0.00 1.0 25

Slash 11 Light logging slash 1.50 4.51 5.51 0.00 1.0 15

12 Medium logging slash 4.01 14.03 16.53 0.00 2.3 20

13 Heavy logging slash 7.01 23.04 28.05 0.00 3.0 25

http://www.fs.fed.us/rm/pubs_int/int_gtr122.html


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In chaparral ecosystems, the brush comprises the surface, ladder, and crown fuels. Wildfires are almost always crown fires in chaparral. Chaparral fuel treatments remove entire plants, often converting the vegetation to grass, non-woody plants, or bare ground, in which wildfire is then more easily suppressed. Chaparral fires tend to be extremely fast moving, high intensity, and very dangerous. Unlike many other fuel types, the age of chaparral does not strongly influence its propensity to burn (Moritz et al. 2004). In oak woodlands, grass and brush constitute the surface and ladder fuels. The oak trees tend to be sparsely distributed rather than forming a dense, continuous canopy. These trees typically survive the fire either because the foliage was not consumed or because they are capable of resprouting. Fires in oak woodlands can move quickly because of the grass fuel component but are usually more easily suppressed. Fires in conifer ecosystems can be highly variable depending on fuel amounts, ladder fuels, canopy density, etc. In some cases these fires are low-intensity surface fires that are easily suppressed and ecologically beneficial, but conifer ecosystems can also produce high-intensity fires as well, which will have less-predictable benefits to watershed processes. Note that the ladder and crown fuels of forest ecosystems are not considered in these models, underscoring the overriding importance of surface fuels and conditions in determining wildfire behavior. Thus, these models are limited in their ability to predict the fire behavior effect of ladder and crown fuel treatments in forest ecosystems. Fire managers must rely on their own field observations to calibrate the output from these models. Fuel treatments Fuel treatments to reduce wildfire rate of spread and intensity consist of breaking up the vertical and/or horizontal fuel continuity, as well as reducing the overall amount of fuel. Fuel treatment objectives include reducing the risk of high intensity or high severity fires, reducing the threat to structures, reducing the threat to valuable natural resources, and maintaining vegetative cover in important municipal watersheds. Fuel treatments that simulate the effects of natural fire can also have the ecological benefits of increasing understory plant diversity and improving wildlife habitat and food sources (Wayman and North 2007). Treatments can be designed to move ecosystems closer to historic, long-term sustainable seral stage distributions. Fuel treatments can be broadly classed as either structural treatment, in which mechanical means are used first to change stand structure and species composition, or process modification, in which fire-based treatments are emphasized with the goal of allowing fire to function as an ecological process (Stephenson 1999). In chaparral, oak woodland, and conifer forest ecosystems, common treatment methods are prescribed fire, mastication, biomass removal, hand cutting and piling, and commercial thinning. The most common chaparral fuel treatments are mastication or plowed fuel breaks. More options exist for forested ecosystems. Agee and Skinner (2005) proposed guidelines for the development of “fire-resilient” forests: 1) manage surface fuels to reduce surface fire intensity, 2) retain fire-tolerant trees (large diameter trees of fire-adapted species), and 3) manage aerial fuels to minimize the potential for crown fire initiation and/or crown fire spread (remove ladder fuels, decrease canopy cover). Treatments must be tailored for individual locations, vegetation types, past management history, and especially fire regimes (DellaSala et al. 2004; Noss et al. 2006). An example fuel treatment in a forest ecosystem is shown in Figures 3 and 4. All fuel treatments are tradeoffs. Costs and benefits that must be considered include ecological effects, erosion, visual appeal, cost, effectiveness, duration of effectiveness, etc. (Figure 5).


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Figure 3. Pre-treatment forest fuels: surface fuels on or near the ground, ladder fuels (small trees and the lower branches of the overstory trees), and canopy fuels (top branches and needles of the overstory trees). Source: Gary Nakamura

Figure 4. The same view as 3 following a thinning of the ladder fuels and some of the overstory trees. Mastication of the surface fuels created by the thinning was the final step. Source: Gary Nakamura


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Figure 5. Comparison of forest fuels treatments. Source: Gary Nakamura

Prescribed fires are intentionally ignited under pre-specified weather and fuel conditions that will create a rate of spread and intensity sufficient to consume surface and perhaps ladder fuels, while ideally leaving overstory trees undamaged (Figure 6). Many of California’s conifer forest ecosystems were historically subject to frequent, low-intensity fires that naturally reduced fuel loads. The last several decades of fire suppression have resulted in such high fuel accumulations that prescribed fire cannot be safely used in some areas. Other methods such as mastication or thinning can be used to pre-treat the fuels before the application of prescribed fire. Prescribed fire is uncommon in chaparral fuel types.

Figure 6. Prescribed fire conducted in a forest stand that has had the ladder fuels and some of the crown fuels removed in a biomass harvest. Flame length (fire intensity) is low. The post-treatment fuel condition would be considered defensible space. Source: Gary Nakamura


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astication is the mechanical reduction of brush, small trees, woody vegetation, and fallen trees Mand logs to small chips that are then scattered as soil mulch. Although the fuel is not removed from the site, it is changed from a more flammable, upright, and well-aerated fuel structure to densely packed chips on the forest floor which will burn much more slowly and less intensely and can serve as mulch to improve soil conditions (Figure 7).

Figure 7. Manzanita and poison oak brushfield after

th

ffects of fuels treatment on fire behavior rimarily intended to reduce fuels in the immediate

g

mastication. Fuel on the ground is a few inches in depand less flammable than standing brush. Source: Gary Nakamura

ELocalized fuel treatments around homes are pvicinity of the structure (Figure 8). The effects of stand-level (tens of acres) treatments on fire behavior can be modeled with a wide variety of software. Pre- and post-treatment fire behavior(e.g., rate of spread, flamelength, probability of crown fire inititation) can be compared for a number of potential treatment outcomes such as reductions in total amount of fuel, increasinthe density of fuels, or removing ladder fuels. In reality, the effectiveness of the treatment depends on how well it was designed and executed.

Figure 8. Fuels treatment around a home. Brea the horizontal fuel continuity of the brush and surface fuels to fire reduce rate of spread and intensity. Source: John Aziz, Wrightwood Fire Safe Council

k


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At the landscape, o veness of a given stand-level treatme ome fires, such as the McNally Fire (20 large that they simply burn through or

round stand-level treatments. Thus, fire modeling and possible fuel treatments need to be

e-ability

igned

of

d into areas of the Blacks Mountain Experimental Forest that had been reviously treated (Figure 9). In areas that had been thinned and prescribed burned, what had

at

e 1999

r watershed, scale (thousands or more acres), the effectint becomes essentially irrelevant to overall fire behavior. S02) or Cedar Fire (2003), can be so

adesigned at the landscape scale when possible. In California, the US Forest Service has developed a workshop that allows each National Forest to plan for its hypothetical “problem fire” using a sophisticated spatial fire behavior modeling approach (Bahro et al. 2006; see also Stratton 2004). Modeling simulations have predicted that about 30% of a hypothetical dry, firprone forest would need to be treated to be “fireproof” (low risk of crown fire and high probof suppression success) if the treatments are spatially arranged randomly. However, that threshold decreased to 18% of the landscape treated if the treatments are strategically des(Loehle 2004). The effectiveness of landscape-level fuel treatments has been demonstrated by a numberreal-world fires (Martinson and Omi 2003; Graham et al. 2004; Finney et al. 2005). In 2002 the Cone Fire burnepbeen a crown fire dropped out of the crown and became a much lower intensity surface fire theventually stopped burning altogether. In the older thin-only treatment areas the fire continued to burn but as a much lower intensity surface fire (Skinner et al. 2004). Similarly, when thMegram Fire (Six Rivers National Forest) encountered fuel treatments, it changed from a high intensity crown fire to a much lower intensity surface fire (Agee and Skinner 2005). In addition, research has shown that previous wildfires in Sierra Nevada mixed conifer reduce subsequent fire severity and can essentially prevent later reburning within their perimeters for up to nine years in all but the most extreme weather (Collins 2007; Collins et al. 2007).

Figure 9. The 2002 Cone Fire spread diagonally across the photo from the upper left to lower right under extreme fire weather conditions of moderate winds and very low humidity. The white ash is evident on the ground. Source: Carl Skinner


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Characterizi There are ma cribe wildfire risk (t the negative impacts of a fire) within

watershed. Several products are described below that support the assessment of wildfire IS data layers which can serve as a baseline for

escribing wildfire conditions, and can be augmented with more detailed localized data as

ti-e perimeter GIS layer for public and private lands throughout the state. The data cover

00 acre or larger CDF fires back to 1950, and 10 acre or larger USFS fires back to 1910. ated annually. Whenever possible, CDF and USFS obtain additional fire

erimeter data from other federal agencies (e.g., NPS, BLM, BIA, DOD) or local and county e

ce in ic

r surface fuels that crosswalks vegetation data into surface fuels by translating formation on plant species, crown cover, and tree size into 13 standard and seven custom fire

. The crosswalk process uses other factors, such as watershed boundaries, lope, aspect and elevation, to further refine vegetation-fuel model relationships. Annual fire

, ulated from fire history data where land

reas are grouped into similar types of fire environments called strata. The Fire Rotation map erived from fire perimeters, based on 50 years of fire history data, and

ugmented by fire ignition points. The fire rotation interval is then computed within geographic

ng Wildfire Risk and Hazard

ny different environmental and climatic factors that can be used to deshe probability of a fire occurring) and hazard (

aconditions. CDF has developed statewide Gdneeded. Fire History Data CDF-FRAP and USDA Forest Service Region 5 Remote Sensing Lab jointly maintain a mulagency fir3These data are updpagencies for incorporation into the fire perimeter layer. To support watershed assessments, firhistory data have been summarized by major watershed units (HUC 8). CDF-FRAP also collects information on prescribed burns. These data are useful in assessing previous fire disturbanthe watershed, which will have consequences for plant community succession and geomorphprocesses. Surface Fuels Surface fuels can be inferred in part from existing vegetation data. CDF-FRAP has developed a GIS layer foinbehavior modelssperimeter data are used to update fuel model characteristics based on "time since last burned" to account for both initial changes in fuels resulting from fuel consumption by the fire and forvegetation regrowth. USFS Region 5 produces a similar product for National Forest lands. Spatial distribution of surface fuels can be used in a watershed assessment to identify areas with high fuel hazards that may burn in the near future. Fire Rotation Fire rotation is defined as the expected number of years it would take, based on past fire ratesto burn a given area. Fire rotation class intervals are calca(Figure 10) is dazones defining areas of similar environmental factors relevant to fire occurrence (vegetation, weather, development status, and extreme elevation). The Fire Rotation map provides a basis for comparing current rates of fire occurrence with fire occurrence rates expected under more natural fire regimes, as reflected in the pre-settlement era. These data are useful for understanding where in the watershed you might expect the highest frequency of fires and the greatest rates of change and dynamicism.


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Figure 10. Fire Rotation. Source: CDF Fire and Resource Assessment Program

On a statewide ba are clearly urning less freque nder the pre-settlement regimes (Stephens and ugihara 2006). Distribution of fire is biased to southwestern California, especially the South

lues

d fire behavior. An example of

ency is much lower in most areas than prior to European settlement 006), many of California’s wildlands have the fuel and slope

onditions to support high or very high potential fire behavior under severe weather scenarios.

re .

e

sis, much of the dry forest and woodland areas of Californiantly than was typical ub

SCoast interior, interior areas of the North Coast mountains, and the Sierra foothills. Low vain the desert reflect yearly variation in herbaceous fuel crops.

Where suppression has increased the time between fires, significant ecological and public safety concerns should be raised. This is particularly true where the absence of fire alters fuel bed characteristics, resulting in significant increases in expectethis type of change is the lower elevation ponderosa pine/mixed-conifer ecosystems where FRAP has calculated fire rotation for the Sierra bioregion conifer under CDF protection to be 618 years. The expected fire frequency under the natural fire regimes would have likely been between five and 15 years (Skinner and Chang, 1996).

Fire Behavior Potential While modern fire frequ(Stephens and Sugihara 2cOf California’s 85 million vegetated acres, 51 percent is classified in these conditions (FRAP,2002, Figure 11). Many areas of moderate potential fire behavior, such as grasslands, ainterspersed into areas of higher potential fire behavior and may often act as fire spread vectorsExtensive areas of very high potential fire behavior often border population centers such as th


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lt of Los Angeles Basin, while the western flank of the Sierra Nevada also forms a continuous behigh fuel densities.

Figure 11. Potential Fire Behavior. Source: CDF Fire and Resource Assessment Program

Fire Threat

ire threat can be used to estimate the potential for impacts on various assets and values o fire. Impacts are likely to occur with increased severity in higher threat classes.

ire threat combines potential fire behavior (hazard) with the expected fire frequency (risk). The

.

Fsusceptible tFindex values represent both the likelihood of a fire occurring and the potential fire behavior.These index values are then grouped into classes representing moderate to extreme fire threatThirty five percent of California is mapped in the high threat class, 18 percent is in the very high class, and two percent is in the extreme threat class (Figure 12).


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Figure 12. Threat of Wildfire. Source: CDF Fire and Resource Assessment Program

Wildfire Condition Class Unnaturally severe wildfire can cause serious and long-lasting damage to ecosystems. The concept of a fire regime condition class was developed as a way to describe the degree of departure from the pre-settlement fire regime (Hann and Bunnell 2001). Depending on how it is calculated, these classes are assigned based on current vegetation type and structure, an understanding of its pre-settlement fire regime, current conditions, expected fire frequency, and potential fire behavior. For fire-adapted ecosystems, much of their ecological structure and processes are driven by fire, and disruption of fire regimes leads to changes in plant composition and structure, uncharacteristic fire behavior and other disturbance agents (such as insects), altered hydrologic processes, and increased smoke production (Figure 13). CDF-FRAP developed a GIS layer for Condition Class that is based on the methods described in the National Fire Plan (http://www.frcc.gov/). Three condition classes are used to describe the degree to which the current vegetation has departed from the assumed natural fire regime (Table 4).

http://www.frcc.gov/


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Figure 13. Condition Class. Source: CDF Fire and Resource Assessment Program

Table 4. Description of Wildfire Condition Classes.

Condition Class

Description

1 Fire regime within or near historical range. Low risk of losing key ecosystem components.

2 Fire regime moderately altered from historical range. Moderate risk of losing key ecosystem components.

3 Fire regime significantly altered from historical range. High risk of losing key ecosystem components.

9 Non-Wildlands

Wildland Urban Interface (WUI) With increasing population growth, the threat of wildland fire to homes is a significant concern in many watersheds throughout California. Recent demographic patterns are showing an increasing concentration of homes in or adjacent to wildlands. This can greatly increase the risk associated with catastrophic wildfires and the likelihood that vegetation will be removed to reduce fire risk. Identifying the current extent of WUI can be an important component of watershed planning. Most interpretations of WUI are based on housing density, defined by CDF as areas where housing density is at least one house per 20 acres. CDF-FRAP developed a GIS layer that represents fire risk associated with WUI areas. These data describe relative risk to areas of significant population density from wildfire by intersecting


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residential housing unit density with proximate fire threat. This provides a relative measure of potential loss of structures and threats to public safety from wildfire. These data are consistent with general National Fire Plan ideals, but the approach is more refined both in terms of mapping extent and in terms of quantification of risk. Within California, both wildfire risk and asset characteristics can vary in the same area. See the CDF-FRAP website for a more detailed description. Sources of Fuel and Wildfire Risk Assessment Information Incorporating fire ecology information into a watershed assessment can be facilitated by the data layers discussed above. There are many ongoing planning efforts such as the National Fire Plan, LANDFIRE, the CDF Fire Plan, individual CDF Ranger Unit Fire Plans, the Forest Plans developed by each National Forest, and the Community Wildfire Protection Plans (CWPPs) being developed by local communities and Fire Safe Councils. These planning documents typically include a detailed assessment of existing fire hazards, an evaluation of assets at risk, and an evaluation of the existing level of wildland fire protection. The fuel model, fire history, fire regime, condition class, and fire weather information that goes into these fire risk assessments is available in map and GIS format at California Fire Mapping and Planning Tools, http://wildfire.cr.usgs.gov/FirePlanning. Further information, including customizable GIS maps of fuels, topography, and other information, is available from the following sources:

o CDF FRAP website http://frap.cdf.ca.gov/ o CERES (California Environmental Resources Evaluation System)

http://www.ceres.ca.gov/ o ICE (UC Davis Information Center for the Environment) http://ice.ucdavis.edu o USDA Forest Service National Forests http://www.fs.fed.us/r5/forest-offices.html o Community Wildfire Protection Plans (http://www.cafirealliance.org/cwpp/ ) o National Fire Plan (www.fireplan.gov ) o LANDFIRE (www.landfire.gov)

III. Fire’s Effects on Soils and Hydrology Fire, as well as the fuel treatment methods described above, plays an important role in the state’s hydrological processes. Edaphic (soil-related) fire effects are included in this section because soils significantly influence hydrologic patterns and processes. Although many fire effects, when considered from the perspective of soils or hydrology, could be seen as problematic, it should be remembered that fire regimes that are within the natural range of variation are an integral landscape-scale process. These fires may seem detrimental at small temporal or spatial scales, but may be beneficial when considered over longer timeframes or larger areas. Of course, the opposite may be true when fires burn outside the parameters of their historic fire regimes. Fire effects on soils can be divided into physical and chemical effects. Effects on Soil Physical Characteristics The range of soil temperatures that occur during a fire, while highly variable both spatially and temporally, strongly influences physical soil properties. A fast-moving fire that generates extremely high temperatures but only for a short duration and only to shallow depths will have much different effects than a slower-moving fire which may heat soils longer and deeper.

http://wildfire.cr.usgs.gov/FirePlanning

http://frap.cdf.ca.gov/

http://www.ceres.ca.gov/

http://ice.ucdavis.edu/

http://www.fs.fed.us/r5/forest-offices.html

http://www.cafirealliance.org/cwpp/

http://www.fireplan.gov/

http://www.landfire.gov/


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Another important physical characteristic of soil is its texture. Heating via fire typically aggregates soil particles by fusing or melting them. On the other hand, burning removes organic structures that help bind soil particles, reducing soil aggregation. Soil texture helps determine its bulk density and porosity which in turn influence how easily it erodes and its permeability to water (Wohlgemuth et al. 2006). Hydrophobicity, a soil’s tendency to repel water, is both a physical and a chemical property. Although this phenomenon can occur wherever the vegetation produces water repellent chemical compounds like waxes and resins, it is most common in chaparral stands. Fire volatilizes these compounds and drives them below the soil surface where they bind to soil particles at a depth that depends on characteristics of the fire and the vegetation (e.g., temperature, depth of vegetative debris, soil moisture). This hydrophobic layer impedes water penetration and can greatly influence erosion (Wohlgemuth et al. 2006). Effects on Soil Chemical Characteristics The most important chemical effect of fire on soils is nutrient cycling. Fire, by oxidizing organic material, frees bound nutrients for use by other organisms. This typically results in a flush of new growth after a fire even though many of the released nutrients are removed from the site by leaching, runoff, or volatilization. Fire plays a major role in the cycling of nitrogen, the chemical most likely, when deficient, to limit plant growth. Combustion converts organic nitrogen to gaseous forms. Much of this is lost to the atmosphere as nitrous oxides or molecular nitrogen but what remains is in a form more available for plant uptake. Some chaparral species, such as Ceanothus, are early colonizers of burned areas and are able to convert atmospheric nitrogen into forms more readily available for plant uptake. Most of a site’s phosphorus, like nitrogen, is lost during combustion. However, what remains has been rendered more available to plants. Ash remaining after a fire also increases levels of plant-available nutrients such as potassium, magnesium, and calcium (Wohlgemuth et al. 2006). Hydrology As with edaphic fire effects, fire’s hydrologic effects can be both positive and negative. This depends on the historic and current fire regimes, the watershed’s vegetation, the geomorphology of the watershed, and weather events during and after the fire. Spatial and temporal scale must also be considered when evaluating a fire’s potential or actual effects. What may appear to be a disaster in the short term or within a relatively small region may in fact be well within the range of expected variability when viewed more broadly. Three important hydrologic impacts of fire are discussed here- water balance, flooding and erosion, and air and water quality. Water Balance Assessing a watershed’s water balance is a method of summarizing how water moves through the system. Water balance assessment can be complex, so only the fire-influenced processes that determine water balance are addressed here. The effects of logging on water balance have been studied since at least the 1950’s (see North et al. 2002). Although studies of the effects of fire on water balance are less common, timber harvest replicates fire in some ways. The fire-influenced processes considered here are evapotranspiration (water lost to the atmosphere via evaporation and plant transpiration), interception, infiltration, and snow melt and accumulation patterns.


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Fire affects evapotranspiration in two ways. Evaporation typically increases after a fire because removing canopy shading results in higher surface temperatures. On the other hand, removing or damaging a significant portion of a watershed’s vegetation can dramatically decrease transpiration. The reduction in transpiration can be directly proportional to the fraction of vegetation lost or damaged. Unless the fire severity is light, the decrease in transpiration will outweigh the increase in evaporation, thus increasing soil moisture (Wohlgemuth et al. 2006). Interception is the process of water, in the form of rain or snow, being stored on the surface of vegetation without ever reaching the ground. A significant amount of moisture can be lost to evaporation through interception. Interception can decrease the adverse effects of raindrop impact on soils. By removing vegetation, a fire decreases interception and increases the amount of moisture reaching the soil. Depending on how a fire physically affects a particular soil, infiltration- the amount of water penetrating the soil surface- can be increased or decreased. For example, if a fire decreases soil aggregation, raindrop impact may form a surface seal that in turn reduces infiltration. A hydrophobic layer can also greatly decrease infiltration, as will removing the litter and duff that store moisture. However, infiltration may increase if a fire increases soil aggregation (Wohlgemuth et al. 2006). Fire can also change snow melt and accumulation patterns. Removing canopy cover exposes snow to solar radiation that causes it to melt both earlier in the season and faster. Relatively more snow is likely to accumulate where the vegetation has been removed. A high severity fire that removes a significant amount of canopy cover may result in more local snow accumulation than previously (Wohlgemuth et al. 2006). Changes in timing and amount of water availability can lead to deleterious environmental and human impacts. Flooding and Erosion Fires in California are frequently associated with flooding and erosion, particularly in the chaparral-covered southern parts of the state. Often these problems do not manifest themselves until extreme weather events. Fires, flooding, and erosion can be considered in the geographic context of hillslopes and stream channels. Overland flow (runoff) occurs on hillslopes when rain falls faster and in greater amounts than can be stored via infiltration. While overland flow is rare in unburned watersheds, post-fire conditions in chaparral ecosystems have been reported where 40% of precipitation was converted to overland flow (Wohlgemuth et al. 2006). Similarly, overland flow in burned Sierra Nevada watersheds was reported to have increased by 31 or more times the unburned rate (cited in Wohlgemuth et al. 2006). Overland flow often results in surface erosion, particularly in watersheds where a strong hydrophobic soil layer has been created. Post-fire landscapes are susceptible to erosion, particularly during extreme rainfall events, due to the removal of vegetative cover and soil alteration. Often the first erosion occurs as soil and rock (dry ravel) slides or rolls downhill once a fire removes barriers such as downed logs and branches. This dry ravel then accumulates in the upper reaches of stream channels. Rain-driven erosion often follows and creates a network of small channels called rills. Studies have shown that surface erosion increased 17 times over pre-burn levels in southern California chaparral and from two-239 times in the Sierra Nevada (cited in Wohlgemuth et al. 2006). A study of Arizona chaparral showed that surface erosion depends more on litter cover, which increases infiltration, than slope steepness (Brock and DeBano 1982). Erosion rates can return to pre-fire levels within several years (Wohlgemuth et


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al. 2006). The magnitude of post-fire surface erosion depends on fire severity, soil properties, slope steepness, and rainfall intensity. Another form of hillslope erosion is mass erosion such as landslides or mudflows. While fire can indirectly encourage mass erosion by weakening tree roots, most mass erosion is a result of extreme rain events that exceed both burned and unburned soil moisture capacity. Post-fire mass erosion in mountainous areas occurs even without human disturbance (Spittler 2005). Potential for storm-driven hillslope debris flows actually decreases in the year after a fire due to decreased infiltration (Spittler 2005). Fire also plays a role in stream channel erosion, sedimentation, and water yield and quality. Erosion and sediment deposition are processes that naturally, continuously occur; fires can significantly accelerate the process and alter stream channel geomorphology. Stream channel erosion and sedimentation depends on existing channel geomorphology and on post-fire conditions on the hillslopes that drain into them. Erosion and debris flows are more likely in steep channels within steep watersheds than lower-gradient areas (Spittler 2005). As described above, fires, particularly high severity fires, often result in increased overland flow and hillslope erosion. Subsequent rain and dry ravel deliver colluvial material that is deposited in stream channels. The first post-fire storms tend to fill stream channels with sediment, while subsequent storms scour the channels and move debris further downstream. Sediments transported downstream can fill lower reaches of the stream and increase flood potential. Post-fire sediment load can be estimated with a US Forest Service model that takes into account soil, geology, slope, and burn intensity (Rowe et al. 1949; Keller et al. 1997). Post-fire erosion potential can be calculated with tools such as the Erosion Risk Management Tool (Robichaud et al. 2006). Post-fire erosion and sedimentation in chaparral systems can be minimized by the rapid reestablishment of strips of vegetation along stream channels (Heede et al.1988). Frequent, low severity fires, where that was the historic fire regime, tend to maintain erosion and sedimentation levels, and in turn water yield and quality, within the natural ranges of fluctuation necessary for healthy ecosystem function (Robichaud et al. 1999). Riparian vegetation provides functions important to hydrology such as soil stabilization, the moderation of water temperature via shading, and woody debris for aquatic habitats. This vegetation is typically composed of more shrubs and deciduous trees than in upland forests. Riparian vegetation produces live and dead fuels characterized by higher fuel moisture levels. Except during droughts or extremely intense burning, fires do not typically burn these areas. In fact, the vegetation in many riparian areas can function effectively as a barrier to fire spread due to its higher moisture content (Skinner 2001). Riparian management guidelines often emphasize fire exclusion, but that policy may be more harmful than beneficial to both vegetation and hydrologic characteristics (Kobziar and McBride 2006). For example, woody debris important for aquatic habitat can be consumed during severe fires, but these fires often create the material needed for in-stream structure. Both water quantity in stream channels and watershed-level water yield increase after fires. Fires can significantly alter peak, storm, and base flows. Peak stream flow increases, especially where hydrophobic soil layers have developed. Post-fire peak flow can increase 200-800 times in southern California chaparral (cited in Wohlgemuth et al. 2006). However, this effect is less pronounced for low severity prescribed burns, where the size and amount of disturbance in the watershed is limited (Neary et al, 2005). Vegetation types with lower-severity fire regimes would likely produce lower post-fire peak flows. Storm flows (the total amount of water generated by a storm) are also elevated after fires and can remain higher than pre-fire levels for several years. Base flows (non-storm stream flow levels) will increase if much of the watershed’s vegetation has been killed or damaged. Water yield for entire watersheds can increase after fires, often for


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years, due to decreased transpiration and soil moisture. Gruell (2001) notes that water yield in the Sierra Nevada has declined as a result of fire suppression. Increased canopy density means less moisture percolates into the aquifers that sustain springs. More trees and shrubs, and decreased landscape proportions of early seral vegetation, mean more water is removed from watersheds via transpiration than before fire suppression. Fire and fuels management may also result in increased erosion or water yield due to the removal of vegetation. Depending on how much and what species of vegetation are removed, soils and slopes may become more prone to different types of erosion. Water yield may increase due to the reduction in evapotranspiration. These changes in hydrologic and geomorphic processes should be anticipated in any planning for changed fire risk and behavior. Erosion rates from prescribed fire or wildfire tend increase as the percentage of bare soils increases. Prescribed fires typically occur under much more favorable climatic conditions that results in a lower burn severity. As a result a greater percentage of the vegetative cover, litter, and duff are retained. High severity wildfires can increase runoff and erosion rates by two or more orders of magnitude, while low and moderate severity burns have much smaller effects on runoff and sediment yields (Robichaud, et al. 2007). In reviewing research studies on fire effects Robichaud, et al. (2007), found that erosion rates were acceptably low when the proportion of bare soils is less than 30 – 40%. Research studies have also shown that sediment yields increase in the first year following a wildfire or prescribed burn, but then decrease and return to background levels within 2-6 years for both high and low severity fires (see Benavides-Solorio and MacDonald, 2005). Water and Air Quality Water quality usually decreases immediately after a fire, but the magnitude of the effect is dependent of the size, intensity, and severity of the fire. Stream temperatures increase if riparian vegetation has been removed. Nutrient-containing ash is washed into streams, increasing turbidity. Post-fire sediment yield almost always increases. The timing and amount of sediment yield depends on fire severity, watershed size and geomorphology, soils, and vegetation. Post-fire sediment yield can increase by a factor of 50 in forested watersheds and a factor of 35 or much more in chaparral watersheds (Wohlgemuth et al. 2006). Although some of these effects can last for up to a decade or so, most are of shorter duration. Water quality may also be impacted by the thinning activities described in Section II. These impacts will depend on the extent and intensity of the activities, the soil, geology, geomorphology, and hydrology. There may be increased erosion into streams immediately following thinning and in subsequent years. If water yields and flows increase, then erosion and transport of sediment may increase. Like water quality, air quality is negatively impacted by the smoke produced by fires. These effects can be confined to local basins (low-intensity smoldering fires) or may reach as far as thousands of miles away if a smoke column carries pollutants high enough for atmospheric transport (high-intensity, plume-dominated fires). Smoke contains several important pollutants regulated by the Clean Air Act, namely ozone, carbon monoxide, nitrogen oxides, and particulate matter (Wohlgemuth et al. 2006). Particulate matter emissions are of particular interest due to their adverse impacts on human health and visibility. Ozone, although typically formed miles from the fire, has negative effects on photosynthesis, particularly in conifers (Wohlgemuth et al. 2006). One beneficial result of smoke is induced germination of some chaparral species.


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Smoke composition depends on the burning environment- weather, topography, and fuels (Wohlgemuth et al. 2006). Prescribed fire options in California are often limited because prescribed fires are considered to be man-made sources of pollution and are therefore constrained by air quality regulations. Lower-intensity smoldering fires (most prescribed fires), in comparison to higher-intensity wildfires, produce greater amounts of the small-diameter particulate matter that is especially detrimental to human health (Pyne et al. 1996). Smoke emission-related social conflicts can be minimized by avoidance (burning when wind will carry smoke away from critical areas), dilution (burning when atmospheric conditions quickly disperse smoke), and emission reduction (relying on appropriate burning techniques, weather, and fuel pre-treatment to minimize emissions) (Pyne et al. 1996). IV. Methods for Analyzing Effects of Fuels Management There are many different models that can be used to evaluate the effect of fire and fuels management on soil erosion and hydrologic response. The following provides a brief summary of several modeling techniques. See Elliot et al (2006) for additional information on models that can be used for evaluating potential impacts from fuels management. RUSLE The Revised Universal Soil Loss Equation is a simple straightforward soil erosion model. This is an empirically based model: A = RKLSCP where; A = predicted erosion in tons/acre/year R = rainfall erosivity factor (varies geographically and is a function of the

2-yr 6-hr storm rainfall amount in inches) K = soil K-factor (a measure of inherent erodibility) L = slope length S = slope steepness C = cover factor (based on amount and type of cover, fine roots, and other factors) P = conservation practice factor The rainfall factor is derived from tables and maps based on geographic and topographic location. Spatial data for rainfall amount and intensity may or may not be readily available. The National Oceanic and Atmospheric Administration, the National Weather Service, and the United States Geological Survey are common sources of these data, and with each passing year more and more data become available in spatial format. Soil K-factor must be obtained from a local soil survey. A GIS layer of soils should contain this information, along with soil texture and rock content, required inputs to other erosion models. The influence of topography is represented through the L and S parameters. Predicted erosions rates increase with longer and steeper slopes. Slope length is more difficult to estimate, but slope gradient is readily available using slope layers derived from DEMs. The cover factor is determined by overlaying pre-fire vegetation with a burn severity map. Curve Number values are adjusted based on the amount of decrease in vegetative cover. Once all the necessary input parameters are appropriately developed and linked to spatial data, the analyst can perform a series of overlays.


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WEPP (Water Erosion Prediction Project) WEPP is available at: http://forest.moscowfsl.wsu.edu/fswepp/. The USDA WEPP model is a physically-based model that can be applied to a broad range of environmental conditions for evaluating hydrology and soil erosion. The model makes predictions for individual hillslopes and can also be applied to small watersheds. The WEPP erosion model computes soil loss along a slope and sediment yield at the end of a hillslope. There are several variations of the WEPP model available that include: WEPP – Road, Disturbed WEPP, ERMiT, and WEPP FuME. WEPP FuME is a variation of the model predicts soil erosion from fuel management practices. Also, a GIS application called GeoWEPP is under development that allows the user to use GIS data to derive inputs to the WEPP model. Hydrologic Models Hydrologic models can be used to evaluate the effects of land cover and land use on watershed response. Both the KINEROS2 and SWAT models are able to process complex watershed representations to explicitly account for spatial variability of soils, rainfall distribution patterns, and vegetation. KINEROS2 KINEROS2 is available at: (http://www.tucson.ars.ag.gov/kineros/ ). Also see BASINS 4.0 (http://www.epa.gov/waterscience/BASINS/ ). KINEROS2 (K2) is an event-oriented, physically based model describing the processes of interception, infiltration, surface runoff, and erosion. Originally developed for use in small semi-arid watersheds, and is based on Hortonian overland flow theory (Smith et al., 1995). In this model, watersheds are represented by discretizing contributing areas into a cascade of one-dimensional overland flow and channel elements using topographic information. It has been shown to be well suited to describing the hydrodynamics of runoff and erosional processes on burned watersheds in the Southwest where infiltration rates are low, and rainfall is infrequent but intense. Sediment transport is treated using unsteady, one-dimensional convective-transport equations similar to those used for runoff. SWAT SWAT is available at: http://www.brc.tamus.edu/swat/. SWAT is a basin-scale water quality model developed to predict the impact of land-management practices on water, sediment, and agricultural chemical yields for large, complex watersheds with varying soils, land use, and management conditions over long periods of time (Arnold et al. 1994). The model combines empirical and physically-based equations, uses readily available inputs, and enables users to study long-term impacts. The hydrology model is based on the water balance equation:

Where; SW is the soil water content minus the 15-bar water content, t is the time in days, and R, Q, ET, P, and QR are the daily amounts of precipitation, runoff, evapotranspiration, percolation, and return flow, respectively; all the units are in millimeters. Since the model maintains a continuous water balance, complex basins are subdivided to reflect differences in ET for various crops, soils, etc. Thus, runoff is predicted separately for each sub area and routed to obtain the total runoff for the basin.

http://forest.moscowfsl.wsu.edu/fswepp/

http://www.tucson.ars.ag.gov/kineros/

http://www.epa.gov/waterscience/BASINS/

http://www.brc.tamus.edu/swat/


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Delta-Q and Forest (FORest Erosion Simulation Tools) Delta-Q and Forest are available at: http://www.warnercnr.colostate.edu/frws/people/faculty/macdonald/model.htm. The Delta-Q model can be used to predict changes in hydrologic flow that result from fuels reduction projects and other types of forest management. Delta-Q uses an empirical approach driven by curves developed from 26 paired watershed datasets to model changes to water yields from disturbed forested areas. FOREST is empirical model that can be used to estimate changes in sediment yield from hillslopes and roads. Hillslope calculations are based on user-provided data defining hillslope erosion response and recovery rates. V. Summary Because conifer forests, chaparral, and oak woodlands cover so much of California’s area, and because these are fire-dependent and fire-prone ecosystems, fire must be a major consideration when conducting a watershed assessment. Any given watershed is likely to contain a mix of these ecosystems, in addition to others not discussed here. Broadly speaking, within large watersheds, the upland headwater portions will be conifer forest with chaparral intermixed throughout (depending on geographic location), while the lowest elevations are more likely to be oak woodland and/or grassland. There are likely to be gradients in fire regimes and vegetation types both across and within watersheds that are topographically driven, whether by elevation, slope, aspect, or landform. A solid understanding of the ecosystem processes that have created the unique conditions of the watershed in question is mandatory. Topographic features of large watersheds can be explored with GIS software. Soil maps can be obtained from the NRCS. The US Forest Service, CDF, and California Native Plant Society may have vegetation information for a particular watershed. The US Geological Survey may be able to provide hydrologic information (stream flow, etc). Once this background information has been collected, the area’s current and historic fire regimes can be placed in context. It is important to have some indication of the past management and human impacts (mining, logging, grazing, etc.). Broad-scale historic fire regimes are described in Fire in California’s Ecosystems (Sugihara et al. 2006). Current fire regimes can be explored with some of the CDF data described above such as fire rotation maps. Time since last fire may be an especially important parameter in conifer ecosystems that may have experienced high-frequency, low severity fires. Chaparral age, however, has less bearing on fire risk or hazard since even young chaparral can burn at extremely high intensity. Like time since last fire, departure from historic mean fire return interval (e.g., Safford and Schmidt (2007)) provides a useful measure of a watershed’s ecological condition and its potential for severe fire. Spatial measures of seral stage departure can elucidate watersheds that may be in particularly poor ecological condition and therefore prone to severe hydrological fire effects. See Cissel et al. (1998) and Cissel et al. (1999) for examples of fire regime-based landscape-scale assessments and management plans.

The next step is determining the wildfire risk and hazard and which, if any, fuel treatments are appropriate. Ideally, watersheds should be managed in a way that brings the current fire regime closer to the historic fire regime. In many highly populated areas, this may not be possible. In

http://www.warnercnr.colostate.edu/frws/people/faculty/macdonald/model.htm


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this case, it may be important to understand fire ecology and plan management actions at the landscape-scale. GIS analysis can be used to pinpoint areas where fire risk is especially high (e.g., dangerous fuel conditions) or where watershed conditions may be disproportionately affected by fire (e.g., the steepest slopes) (see Keithley (1999) for an example GIS analysis). These areas can then be the focus for initial treatments. Outside these populated areas, particularly in remote backcountry watersheds where fire regimes are typically less departed and fuel conditions may not be as dangerous, natural wildfires may be allowed to burn, providing a crucial ecosystem process for much less cost than active fuel treatments. Noss et al. (2006) list management principles that are useful before, during, and after wildfires in forested ecosystems. They stress that management actions must be tailored to local conditions with the ultimate goal of restoring natural fire regimes (Figure 14).

Figure 14. Fuel treatment continuum in forested

ecosystems (from Noss et al. 2006). Finally, the hydrology of the watershed must be assessed and understood. In small, sensitive watersheds that are already only marginally functioning, fuels treatments or a fire could cause more problems than provide solutions. Larger watersheds may be able to absorb those impacts. Bringing fuels conditions back to pre-fire suppression levels may require multiple fuel treatment or natural fires before a watershed’s fire regime can be considered functionally restored. Promoting intact fire regimes is the best long-term solution for maintaining a watershed’s ecological integrity. If pre-fire watershed conditions have been assessed (e.g., measurements of water yield or water quality), these can be used as a baseline against which to compare post-fire conditions. Without quantitative data, little can be conclusively determined with respect to a watershed’s condition. However, given the appropriate data, managers can decide whether post-fire rehabilitation or restoration is desirable. If all or part of a watershed burns, it may be necessary to initiate rehabilitation action to prevent erosion, flooding, etc. These are typically short-term, rapid-implementation actions such as mulching or grass seeding. Restoration, on the other hand, may be ongoing for years and can involve replanting trees where large high-severity fire has destroyed the seed bank or led to invasion by non-native plant species (see Thode et al. 2006). VI. Checklist for Considering Fire and Fuels in a Watershed Assessment Step 1. Engage Interested Parties

Identify and convene meetings with key stakeholders to discuss known issues regarding wildfire, hazardous fuel loads, and existing hydrologic and water quality conditions within the watershed.

Step 2. Conduct Risk and Hazard Assessment


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a. Collect GIS data on topography, soils, fire history, fuels, logging history, and vegetation data within the watershed.

b. Establish a monitoring program to collect key hydrological data. c. Determine the historic and current fire regimes. d. Delineate the extent of WUI. e. Identify areas where seral stage distributions are most highly departed. f. Identify the location and extent of assets at risk (water, wildlife, structures). g. Identify how the regulatory environment impacts potential management of fuels and

vegetation with the watershed.

Step 3. Identify Priority Areas a. Based on Step 2, identify areas at risk of high severity wildfires. b. Prioritize these areas in order of importance. Triage may be necessary given time

and financial constraints. Step 4. Determine Goals and Objectives

Decide if restoring historic fire regimes is feasible or appropriate. If not, plan for continued fire suppression and consider strategic fuels treatments to protect structures. If appropriate, consider ways to restore conditions such that natural fires could burn within the watershed without causing major ecological or social problems.

Step 5. Propose Management Actions

a. Develop recommendations and specific actions for priority areas. b. Work with public agencies or private contractors to plan actions and assess

effectiveness. Step 6. Post-Fire Management

Determine whether post-fire conditions warrant rehabilitation or restoration. Rehabilitation may be necessary to maintain hydrological integrity until an area is re-vegetated. Restoration is typically only needed after very large, high severity fires.

Step 7. Adaptive Management Continue to monitor conditions and adjust management to reflect the success or failure of specific activities as well as changing environmental conditions (e.g., droughts or windstorms).


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VII. References Agee, J.K. 1993. Fire ecology of the Pacific Northwest. Island Press, Washington, D.C. Agee, J.K. 1998. The landscape ecology of Western forest fire regimes. Northwest Science 72 (Special Issue): 24-34. Agee, J.K and C.N. Skinner. 2005. Basic principles of forest fuel reduction treatments. Forest Ecology and Management 211: 83-96. Anderson, H.E. 1982. Aids to determining fuel models for estimating fire behavior. General Technical Report INT-122. USDA Forest Service, Ogden, UT. Arno, S.F. and S. Allison-Bunnell. 2002. Flames in Our Forest: Disaster or Renewal? Island Press, Washington, D.C. Bahro, B., K. Barber, L. Perrot, J. Sherlock, A. Taylor, K. Wright, and D. Yasuda. 2006. Using fireshed assessments to measure landscape performance. In First Fire Behavior and Fuels Conference on Fuels Management – How to Measure Success. March 28-30, 2006, Portland, OR. Brock, J.H., and L. F. DeBano. 1982. Runoff and sedimentation potentials influenced by litter and slope on a chaparral community in central Arizona. In C.E.C. Conrad and W.C. Oechel (eds.), USDA Forest Service General Technical Report PSW-58. Berkeley, CA. Pages 372-377. Caprio, A.C., and T.W. Swetnam. 1995. Historic fire regimes along an elevational gradient on the West slope of the Sierra Nevada, California. In Proceedings of the Symposium on Fire in Wilderness and Park Management, technical coordination by J.K. Brown, R.W. Mutch, C.W. Spoon, and R.H. Wakimoto, 173–79. General Technical Report INT-320. Ogden, UT. Chang, C. 1996. Ecosystem response to fire and variations in fire regimes. Sierra Nevada Ecosystem Project, Final report to Congress, Vol. II, Assessments and Scientific Basis for Management Options, Chap. 39. Davis, CA: University of California. 28 p. Cissel, J.H., F.J. Swanson, G.E. Grant, D.H. Olson, S.V. Gregory, S.L. Garman, L.R. Ashkenas, M.G. Hunter, J.A. Kertis, J.H. Mayo, M.D. McSwain, S.G. Swetland, K.A. Swindle, and D.O. Wallin. 1998. A landscape plan based on historical fire regimes for a managed forest ecosystem: The Augusta Creek Study. General Technical Report PNW-422. USDA Forest Service, Portland, OR. 82 p. Cissel, J.H., F.J. Swanson, and P.J. Weisburg. 1999. Landscape management using historical fire regimes: Blue River, Oregon. Ecological Applications 9(4): 1217-1231. Collins, B.M. 2007. Natural wildfires in Sierra Nevada wilderness areas. Unpublished PhD Dissertation, University of California, Berkeley. Collins, B.M., M. Kelly, J.W. van Wagtendonk, and S.L. Stephens. 2007. Spatial patterns of large natural fires in Sierra Nevada wilderness areas. Landscape Ecology 22(4): 545-557. DellaSala, D.A., J.E. Williams, C.D. Williams, and J.F. Franklin. 2004. Beyond smoke and mirrors: A synthesis of fire policy and science. Conservation Biology 18(4): 976-986.


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6. Fire and Fuels Assessmentcwam.ucdavis.edu/Volume_2/CWAM_II_6_FireFuels.pdfmobile animals. Many insects, rodents, reptiles, and amphibians are able to shelter themselves during fires