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Assessing Fire Effects and Burn Severity

by: Ms. Alene Howell

Assessing Fire Effects and Burn Severity FOR 434

Marketplace > University of Idaho > Natural Resource Ecology And Mgmt > FOR 434 > Assessing Fire Effects and Burn Severity
Ms. Alene Howell
GPA 3.99

Chad Hoffman

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Chad Hoffman
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This 140 page Class Notes was uploaded by Ms. Alene Howell on Friday October 23, 2015. The Class Notes belongs to FOR 434 at University of Idaho taught by Chad Hoffman in Fall. Since its upload, it has received 18 views. For similar materials see /class/227823/for-434-university-of-idaho in Natural Resource Ecology And Mgmt at University of Idaho.


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Date Created: 10/23/15
Predicting Combustion and Air Quality Chad Hoffman Zack Holden During this lecture we are going to explore the basic concepts in predicting air quality But before we begin this we need to look at combustion a bit more Predicting the amount of fuels consumed rmde strata Calagor lu 42 use l 3 1 my 7 f7 slralum Campy Snag Other aerlal hurls w W Mme Low 3 7 vegelawn a slralum Grammmds Herbs Summ man Plles laclmcts sump vucd mud andwlndmws Ground V M stratum ow Basal accumulalun Six horizontal fuelbed strata used in the F008 from Sandberg et al 2001 To predict the amount of fuels consumed for an area we need to first identify the properties of each fuelbed strata and then estimate how much of those will be consumed Specifically we want to know how much fuel the size of it the bulk density and the physical properties of it Once each part ofthe fuels complex is defined and the consumption is estimated we can add them together to look at the site as a whole In addition to this we also want to look at when the fuels are combusting In other words are they being consumed during flaming or smoldering combustion Vl th this information we can then predict the amount of emissions that are released from a fire Another look at combustion Preignition phase 0 Fuels are heated 0 Fuel moisture is driven offand water vapor is released 0 Pyrolysis begins thermal decomposition of cellulose to combustible vapors Before we move on I would like to take a brief look back at combustion I know we have covered this already and you have probably talked about it more times then you want to but it is important to think about it when we are discussing the consumption of plant material and the production of emissions from those materials So here is a quick reminder The pre ignition phase is when fuels are heated and moisture is driven offthrough the release ofwater vapor Along with this we will begin to see the thermal decomposiiton of the cellulose which will release combustible vapor into the air Another look at combustion Flaming Phase 0 Combustible vapors reach 600 F and mix with sufficient oxygen 0 Accelerates pyrolysis 0 Rapid oxidation 0 Produces primarily CO2 and H20 0 Partial oxidation causes a variety of emissions Initially when the combustible gasses are released form the heated fuels they do not have enough oxygen to burn so as they rise and mix with oxygen they create ames 39 I is caused by quot 39 p quot 39 a a heat to ignite but not having oxygen so they rst must mix with oxygen This explains why the ame is not attached directly to a burning piece offuel From a chemical stand point the process is essentially rapid oxidation and it produces 002 and water for the most part However partial oxidation causes a variety of other emissions Another look at combustion Smoldering Phase 0 Temperature and combustible vapor mixture too low to support flaming 0 Temperature drops gases condense 0 Emissions 2X flaming stage 0 Long duration lfthe temperature ofthe combustible gasses falls or ifoxygen can not suf ciently mix with these gasses you get smoldering combustion Smoldering combustion will produce much less heat and will burn for a much longer duration then aming combustion Along with this we get a host of other products released from the process In a quotquot 39 39 quotquot Iquot 39 39 2times as high as the aming stage per unit combusted Another look at combustion Glowing Phase Residual Phase 0 All volatile gases driven off 0 No visible smoke produced 0 C02 CO and ash primary products 0 Long duration As the volatile gasses are further removed from the system we move into the L t hasa r tt t L t 4 1 1 a r and co2 and co as well ash are the primary products released The rate ofspread during this phase is very slow even compared to the smoldering phase Largest Error Second Largest Error w So lets build a basic concept for how we could model combustion and emission production from a re We will start with the idea that a re has occurred or will occur represented here by black area In other words we want to know how much has burned or will burn Then we need to know how much fuel is on the site or was on the site we typically get this through fuels inventories of some sort Next we need to predict or measure how much ofthe fuel will be consumed or was consumed In addition to knowing how much fuel was or is going to be consumed 4 quot quot muchofthat 4 39g 439 phases ofcombustion Once we know this we simply multiply the amount offuel consumed by an emissions factor This leads us to an estimate ofthe emissions production For this talk we will end here but be aware that we might also want to predict where the emissions will go Note that many studies have indicated that the largest eHUI 39 39 quotquot 39 I 4 fuel loading estimates followed by the prediction of consumption and then followed by an emissions factor W1ww MN J RSAcizuuar RPTl pdf We will now take a brief look at how our theoretical model can be implemented So lets start by talking about getting an estimate of the area burned By far one of the most compelling advances in detecting the area burned over the last several years has been Remote sensing technologies The most common output from these methods is the creation of a BARC map BARC stands for Burned Area Re ectance Classi cation Key and Benson 2001 These maps can be created from a variety of sensors several of which we have already talked about in this class The choice of which sensor to use is partially dependent upon the objectives you are trying to complete of particular importance is the time frame the imagery is needed in and the spatial resolution which is required The end output of this process is the amount of area burned You should be aware that there are field sampling methods which can also provide these inputs Estimating Fuels Surface and ground fuels t Browns transects 39 Photo guides Canopy Fuels 0 Forest inventory methods and allometric equations 39 Photo guides Shrub and Grass fuels 0 Inventory methods t Photo Guides a y a y y L y of area burned or ifit is a prescribed re we can just estimate the area The next step in our model is to estimate the amount offuels present In this class we have already talked about the methods to do this so I will only brie y remind you of a few ofthe important ones 1 1 ILA T quot quot quot use either r a a in ulc vegetation on other methods To estimate canopy fuels we most often use a combination of traditional forest inventory methods such as DBH and Height along with allometric equations to estimate the amount of biomass But be aware that in some cases a fuels photo guide can be used And to get estimates ofshrub and grass biomass we can use standard inventory techniques like clipping plots or we could use fuel photo guides In any case at this point we have estimated how much area will or is going to burn and the amoutn offuels on the site Black Area Largest Error Fuel Loading Fuel consumption Second Largest Error Emission Factor smallest Error Emission Production DispersionConcentration lfwe take a look back at our model we can now see that we are at the fuel consumption part ofthe problem So before we begin this part I would like to introduce you to the First order re effects model or FOFEM This is the model you will use to do your assignment and the model we will look at to predict fuel consumption and ultimately the emission production forma re About FOFEM What does FOFEM Predict Fuel consumption 39 Smoke production 0 Tree mortality 39 Soil heating Some overall assumptions Homogeneous burn Entire area burns FOFEM is a computer system which calculates rst order re effects from very simple input parameters Remember that a rst order re effect is the immediate consequences ofa re only Fofem can predict the amount offuel consumed the smoke production tree mortality and soil heating Throughout the remainder ofthis class we will use this model as a tool to help us predict re effects But for now lets focus on the fuel consumption predictions made by FOFEM There are a few assumptions we should talk about before we look speci cally at consumption First FOFEM assumes that the entire area is burned and that it is homogeneous This meansthat FOFEM does not model patchy or discontinuous burns FOFEM Fuel Consumption Predictions Predicts Duffand litter consumption 0 Surface fuel consumption by size class and state sound or rotten t Live fuel and canopy fuel consumption Inputs required 0 Fuel load by size class 39 Fuel moisture 39 Covertype 0 Region 0 And season of burn FOFEM predicts the consumption ofduffand litter surface fuels by size class and state as well as live and canopy fuels This model relies on BURNUP which is a theoretical model for woody fuel consumption and a series ofrules and regression 1 r r r fuel consumption are fuel loadings by size class fuel moistures cover type region and season ofburn Thermal differences in fuels 4 tempera ure rises across the entire cross section of the fuel before the ames amve39 0 Flash Fuels Athermally thick fuel is one in which the a 1hr fuel interior may not be heated much before the arrival of the ame and the temperature will not rise across the entire cross section before the arrival of the 100hr ame Litter Pyrolysis zone mo er avaia e Residualavailable When we are predicting combustion we need to think about the thermal properties ofthe fuelswhic L lng 39 r 39 L39 L are thermally thin and ones which are not The concept ofthermal thickness is important for us to further develop our model as it will allow usto make assumptions about the behavior ofthe fire as well as how much material is burned during each phase of combustion Essentially ifa fuel element is thermally thin we can assume that the entire element is heated evenly and will be combusted during the aming phase However ifa fuel element is not thermally thin then only some portion of it will be combusted during the aming phase and other parts will be combusted in the other phases This concept is shown above you can see that the one and ten hour fuels are completely combusted during the aming phase where as the 100 hour fuel is combusted with a combination of aming and smoldering combustion Now notice that the larger 100 hour fules also go through aming smoldering combustion but 394 t n mm TL tc t r represent in our model to predict combustion and emissions Predicting woody fuel consumption FOFEM uses BURNUP for predicting woody fuel consumption Burnup is a theoretical model which simulates Heat transfer between fuel particles Combustion rate And fire intensity t A few assumptions oAll 1 and 10 hour fuels are assumed to be combusted Now back to how FOFEM incorporates this process FOFEM relies on the BURNUP model which is a theoretical model which predicts the heat transfer between woody fuel particles the combustion rate and the reline intensity BURNUP relies on vnlinulca uvcl time using a r 39 r Thatisit r L L 3 4 4 4 foraquot 3 moves fonvard to the next time step At each iteration the fuel consumption of each woody fuel size class is determined by modeling the heat transfer between the woody fuels and the dufflayer The re intensity is then calculated from the combustion ofthe fuels in each time step The re is assumed to go out when the overall intensity is too low to sustain further combustion In general 100 of1 and 10 hour fuels are assumed to be completely combusted The 100 and 1000 hr fuel 39 39 a orquotquot 39 39 39 at the math quot it i important to think about quot quot 1 involved in quotquot I Predicting consumption Litter Predicted using Burnup Generally 100 assumed to burn Herbaceous vegetation 100 assumed to burn generally a Ifa spring grass fire is predicted than only 90 Canopy fuels 0 User must estimate the proportion Lets now look at the litter herbaceous and canopy fuel layers In both the litter and herbaceous layers it is often assumed that 100 ofthese fuels will be consumed The only exception is for spring res in grass lands In this case it is assumed that nly 0quot quot a quot39 be consumed T quot r sumption the user must input the proportion ofthe stand affected by crown re The model then applies this proportion to the canopy foliage and one half ofthe 1 hour canopy fuels Shrub Consumption Shrub consumption is modeled with a series of rules of thumb at this time v Sagebrush Fall fire 90 consumed All other seasons 50 o Shrub dominated non SE US Consumption 80 A Non shrub dominated cover types Consumption 60 Spring and winter consumption 90 Summer and fall consumption 80 Nonpocosin cover types in the SE Rely on equations developed by Hough 1968 and 1978 FOFEM uses a series ofrules ofthumb to predict shrub combustion These rules of thumb are basically divided up by cover type region and season ofburn Two cover types sage brush and pocosin have there own rules Speci cally for sage brush 50 ofthe biomass is assumed to burn during all seasons except the fall where 90 is assumed to burn For pocosin spring and winter res are assumed to burn 90 of quot quot39 quotquot and fall 4 quot 80 Alte these rules of thumb we basically dived the remaining estimates up by the southeast which relies on equations developed by Hough 1968 and 1978 and the rest ofthe US which further gets divided up into shrub dominated cover types and ob quot4 types orquotquot quot4 typesthe nonmy nnLL consumption 39 4 I assumed to be 60 7 gulf consunlption Equation 2 DR 83 0426 EDM Brown and others 1985 m mm is mm min WWW FOFEM use when n cannm W mm mm cansmmlan algamh N w mwe M M emmwuwMMWWth mewquot summaw u 4 Equation 6 DR 08311 00095 EDM 2 0439 DPRE Brown and other 1935 NJ MM gly ar wp A ku To predict duff consumption FOFEM uses a number of different equations Theses equations are basically divided into the percent duff consumed and the duff depth consumed In general these equations are based on the duff moisture content the location and the type of fuels either activity or natural fuels There are two separate equations used for pocosin in FOFEM however we will not coverthese Overall there are about 20 equations that FOFEM relies on to make this prediction so we will not go through each one separately instead we will take a look at the default equations In particular we will look at equation 2 and equation 6 These are the two default equations used when no other equation seems to fit Equation two is used for predicting the amount ofduff consumed from the average moisture content EDM This equation is a regression function which states the dr 837 0462 times the duff moisture content Equation 6 on the other hand is used to predict the depth ofduff consumption based on the moisture content EDM and the original depth of duff DPRE Again this equation is a regression function which states thatthe duff depth is equal to 08811 00096 times the moisture content 0439 times the original duff depth Black Area Largest Error Fuel Loading Fuel consumption Second Largest Error Emission Factor Smanest Error Emission Production DispersionConcentration fwe now look at our model outline we can see that we now have the understanding to predict the amount offuel consumed in a re So next we need to convert this to an emissions product To do this we simply multiply the amount offuel consumed in each vegetation type and each phase class by a constant But before we move on I want to come back to the idea ofthermally thin fuels Remember that these fuels are assumed to be combusted completely during the aming stage So in this model we assume that all litter 1 and 10 hour fuels grasses shrubs and canopy fuels are quot 4 39 39 I So we will quot quot39pquot quot factor for all ofthis The duffand 100 hour fuels will have multiply factors based on how much was combusted in each phase Smoke production In general we can use the following equation to summarize how we predict emissions from a fire EMT Z FCp xEFp Where EMt is the total amount of emissions FCp the fuels consumed in combustion phase p EFp the emissions factorfor combustion phase p We can s 4 LI a r I 4 by each combustion phase for each fuel type In other words we need to calculate the emissions produced form the duff litter woody fuels grasses shrubs and 1 canopy by combustion rquot 4 quot a of emissions produced in any given fuel type for any stage of combustion you simply multiply the amount offuels combusted by an emissions factor FOFEM Emissions Predictions Estimates 0 PM 10 0 PM 25 39 CO 39 C02 0 CH4 0 NOx 39 SOx So FOFEM predicts the fuel consumption rate the emissions production rate and the re intensity over time it then simulates the proportion of lamming an smoldering combustion and applies an emissions factor based on fuels moisture and phase of combustion The end result is that for a host of emissions including particulate matter 10 and 25 carbon monoxide and dioxide as well as others it then gives you an estimate of the production Your next assignment Downloading FOFEM httpwwwfireorgindexphpoptioncom7conte ntamptaskviewampid58ampItemid131 FOFEM training 39 httpwwwfireorgindexphpoptioncom7conte ntamptaskviewampid65ampItemid31 Before we end this lecture lwant to talk brie y about your next assignment and a few future assignments As part ofthis class we will be asking you to run FOFEM analyze data and answer a series of questions You can download FOFEM from the website listed above and for those ofyou who have never run FOFEM it is fairly easy to do but there are a few training power points available for you to look over Your next assignment will be to enter the fuels data from the res we have been looking at and then to estimate how much fuel will be left after the re and then estimate how much emissions we produced As always you can view the assignment and data from the website Final Thoughts Think about assumptions Understand the predictions Communicate effectively As we end this lecture lwant to take a minute to talk about making predictions By de nition quot 4 39 a u 4 The accuracy of model is important but just as important is our understanding ofthe quot 4quot quot quot 4 quot 39 lfwe are making a decision based of a prediction we can fail for many reasons and there are examples ofboth model failure and communication failures which have cost millions ofdollars My general advise to people when we talk about models is that they are tools even a wrong model can help us Just make sure you understand the assumptions and limitations you understand the prediction its self and you communicate what all of it means effectively to others Fire Effects on Air Chad Hoffman Zack Holden In today lecture we are going to be talking about the effects of fire on air quality and smoke management techniques What is Air Pollution The presence in the atmosphere of one or more contaminants of a nature concentration and duration to be hazardous to human health or welfare Sandberg et al 999 39 May occurdirectly or indirectly by a human act or from natural sources Air pollutant emissions are often just referred to as emissions Lets begin by de ning what air pollution is Air pollution is the presence of one or more contaminants of a nature concentration and duration to be hazardous to human health or welfare Sandberg et al 1999 The term welfare in this case is quot I potential L 39 39 quot quotquot 39 quot quotJ or the comfortable enjoyment of life So that haze over the grand canyon affecting my view is considered to be a negative impact on my enjoyment of life These contaminates may be caused directly from a human act such as a prescribed re or from natural sources such as a volcano or a wild re Often times we refer to air used interchangeably with in the re literature Air pollutants Air pollutants are classified into two classes t Primary pollutants are those directly emitted into the air eg particulates hydrocarbons CO 03802 N02 Pb 0 Secondary pollutants are new substances created by chemical reactions within the atmosphere All air pollutants can be classi ed into one oftwo categories primary pollutants and secondary pollutants Primary pollutants are those substances directly emitted into e air quot r L 4 quot chemical reactions within the atmosphere Another important distinction is the classi cation of hazardous air pollutants These are a special class of air pollutants identi ed in the Clean Air Act amendment of 1990 and constitute a hazard to human health The combustion of forest fuels have the potential to release contaminants into the atmosphere 739quot r 39 4 4 quot of 39 4 quot 4 material is what composes smoke Smoke is composed ofunburned material consisting mostly ofunburned fuels particles ofash and water droplets as well as emissions such as particulates hydrocarbons carbon monoxide metals and trace ses Public Health and Smoke Lets take a few minutes to look at how the products of combustion affect the health and purity of the air we breath Of particular concern is the effects of particulate matter on human health There is not much data which speci cally examines the effects of wildland re smoke on public health We can however infer health responses from other documented effects of particulate air pollutants The effects of particulate matter are in part based on the size of the matter and in part based on the individual being affected Age past history of reparatory issues and exposure levels are all important factors in determine the effects of particulate matter on human health But of particular ncern is the size of the particulate matter The body has two pathways which defend against polluted air the upper airway nose nasal passages mouth and the lower pathway trachea bronchial tree Large particulate matter 5 microns and greater are caught in the upper pathway and can be defended against while smaller ne particles less than 25 microns can penetrate much deeper into the lungs where the body s defense mechanisms are less effective at removing them 80 to 90 percent by mass of wildland re smoke is within the ne particulate size class PM25 which is of particular concern for public health because our body has a lower defense mechanism against these particles The effects of particulate matter on human health include irritation of the eyes repertory track irritation such as asthma bronchitis reduced lung function and premature death In addition these irritants can cause persistent cough phlegm wheezing and physical discomfort when breathing Particulate matter can also affect the immune system which can prevent the removal of other irritants such as pollen from the lungs Air Quality Regulations Primary legal basis for air quality regulations is the Federal Clean Air Act Essentially a series of acts amendments and regulations beginning with the federal Air Pollution Control Act of 1955 and continuing today The emissions and impacts of res on air quality is controlled through a complex web of laws and regulations however the primary legal basis is found in the Federal clean Air Act This act is essentially a series of acts amendments and regulations An act is a series of statute that have been passed by congress an amendment is a change to the original act or statute the statutes that form this act also allow for the federal government to create committees which provide regulations Regulations provide guides for implementing the act or statute Although I suppose all ofthis is for another class Clean Air Act States have the primary responsibility of carrying out the provisions in the clean air act EPA has the task of setting air quality standards The provisions that are stated in the clean air act are primarily carried out by individual states while the EPA is responsible for setting the air quality standards 4 u la Lufuncion 4 Inn 4 r State implementation plans SlP s that de ne and describe how their programs will implement and meet the requirements ofthe Clean Air Act Aso the 4 quot 39 air act federal g 39 conformation to the SIP s This general rule prohibits Federal agencies from taking any action within a containment or maintenance area that causes or contributes to anew violation of air quality standards or increases the frequency or severity of an existing violation or delays the timely attainment ofa standard In other words you can not contribute to the air quality problem is you do not meet the standards outlined in the SIP and by the EPA Air Quality Standards National Ambient Air Quality Standards httpllwwwepagovaircriteriahtml The national ambient air quality standards are defined in the clean air act as the mount of pollutants above which detrimental effects to public health orwelfare may result The table you see he here reports the current NAAQS standards Of particular concern is the production of particulate matter since a majority of smoke is made up of these particales Other pI OVISIons of the Clean Air Act Prevention of significant deterioration PSD t Defined three air shed classes 0 Class 1 allows very little additional pollutants to 0 Class 2 allows some incremental increases in pollution and 0 Class 3 allows pollution to increase up to the NAAQS 1977 clean air act amendments and visibility 1999 regional haze rules There are three other provisions in the clean air act that lwould like to talk about before we move on First the prevention of signi cant deterioration provisions The provisions were written to prevent areas that are currently cleaner than is allowed by the NAAQS from being polluted up to the NAAQS standards Three air quality classes were developed from these provisions Class 1 allows very little additional pollutants to be added Class 2 allows some incremental increases in pollution and class 3 allows pollution to increase up to the NAAQS Another important amendment in the clean air act occurred in 1977 Under this amendment a na ional goal ofthe prevention ofany future and the remedying ofany existing impairment ofvisibility in mandatory class 1 areas in which im airment results from manmade air pollution This amendment is primarily related to the PSD 39 quot 4 39 J L g 39 39 39 J 39 effects on Visibility The nal law lwould like to discuss isthe 1999 regional haze rules These rules 4 39 J 39 I 4quot multitudeof emI 39 39 g g g rules are the rst time that the role of re in forested ecosystems is formally recognized Vl th this recognition the emissions from natura sources and anthropogenic sources are treated differently and is the rst rule which required emissions inventories form res Nonattainment iiii lLl ilML Air rm limiiiimiii urinal M will l uliiVM lHi il Ml mm minis Data will u Milli m All m w w E MN m WWW An area that is in violation of the NAAQS is labeled a nonattainment area The gure shown here locates al nonattainment areas for PM 10 as of may 2002 Alter a nonattainment area meets NAAQS it gets redesignated as a maintenance area All other areas are designated as either attainment or as unclassi ed A A Few Notes on ViSIbIIIty Affected by scattering and absorption of light by particles and gases 0 Majority of fine particle species emitted from fires are organic and elemental carbon soot secondary organic aerosol formation is poorly understood 0 Sulfates nitrates organic compounds and soil tend to scatter light elemental carbon absorbs light 6902 Denver airshed Fairbanks AK in 2004 during Hayman re gtr0425p df Visibility is primarily affected by the scattering and absorption of light by particles and gases The effects of these particles and gases obscure the clarity color texture and from of What we see Small particulate matter PM25 is more efficient per unit mass then larger PM10 particles at causing visibility impairments Rememberthat this is important since fires emit a large quantity of fine PM25 particles In addition to size the type of particle is also important The majority of fine particles emitted from fires are organic and elemental carbon soot Materials such as organic compounds sulfates nitrates and soil tend to scatter lightwhere as elemental carbon absorbs light Therefore the make up of smoke will influence how it impairs our visibility Visibility o Wildland fire contributes to the 20 worst visibility days especially in the west Current visual ranges in Eastern US are 1530 miles in Western US 6090 miles Effects of fires are significant over short periods but contribute less to longerterm averages to visibility impairments httpwwwfsfeduslnnlpubslnnrsgtr0425pdf entration microgramsm3 visibility miles 125 250 1 O r 4 500 O 5 r 2 1 These numbers only valid when RH lt 70 mrp www bugwood orgpfrresmoke hlml It is thought that the natural visibility ranges in the eastern and western US are 60 80 miles and 110115 miles respectively Currently it is estimated that the eastern US has a visibility range of between 15 and 30 miles and the western US is about 60 to 90 miles Note that the historical estimate si presented do not account for the effects of natural Wildland fires In the western US Wildland fires contribute to the 20 of worst visibility days The effects ofthese fires are significant over relatively short periods of time but contribute less to the longterm averages of visibility impairments The figure shown here in the right hand corner shows the range of visibility based on different smoke concentrations You will note that these numbers are only valid when relative humidity is below 70 why do you think relative humidity will effect visibility Characterizing Emissions From Fires Area Burned entire perimeter is used despite mosaic burn pattern therefore this number includes unburned vegetation Preburn Fuel Characteristics variations can contribute up to 80 of errors in emission predictions Peterson and Sandburg 1988 Although we will talk further about predicting smoke production and emissions form res I would like to reVIew a few general concepts rst All components of smoke form res with the exception of carbon dioxide and water are generated from inef cient combustion The amount of smo e roduced is derived by determining the fuel consumed in each combustion stage the size ofthe area burned the fuel characteristics re behavior and combustion conditions quot quot quot 4 4 39u oneof quot solets discuss each ofthese brie y Initially the area burned seems like a straightforward estimate to make however individual estimates of re size tend to be systematically exaggerated In part this is mosaic burn A t nnlmifrm 5L4 L a 39 llllcnlllcl pattern although the entire area is typically reported Another important factor in determining emissions from res is the preburn fuel characteristics Peterson and Sandburg 1988 suggested that variations in the fuels complexcan 39 quotquotquot b quot r iquot quot a 39 39 4quot They suggest that the greatest errors occur when the fuel load is inferred from vegetation type Characterizing Emissions From Fires 0 Fire Behavior influences the combustion efficacy as well as the resulting pollutant chemistry and emissions factors Cmnn var39nh39nn s n lililgl Fulhad39mg micquotqu Fmixn39nnFutix nth Flume L iThe largest errors are assoclaied wan fuel mm and fuel consummun estimateswhen delermmmg 2mm Producuon and inwactstmmwlldland nrelPetersan and Sandbag 1935 Another important aspect is fire behavior the behavior of fire influences the combustion efficiency as well as the resulting pollutant chemistry and emission factor The behavior of a fire is in part due to the fuels available for burning and in part due to the weather and topography ofthe site the combination of these variables will result in different amounts of flaming smoldering and glowing combustion The phases of combustion are important as they will have distinct combustion efficiencies related to them The figure shown here from Peterson and Sandburg 1988 shows the error associated with the different parts of making emissions predictions from wildland fires Emission Inventory Methods Pm Monitoring instruments are typically use one of the following techniques Gravimetrical or optical o Gravimetrical instruments are filter based and collect particulates on ventilated filters which are later weighed at a laboratory 0 Optical instruments measure light scattering or light absorbing characteristics of the atmosphere which is then converted into a concentration Both visibility data and particulate matter concentrations are useful to smoke management for assessing air quality conditions Particulate mater instruments typically use one of two methods gravimetrical or optical Gravimetrical instruments are lter based and collect particulates on lters which later have to be weighed and processed in a laboratory Optical instruments measure light scattering or light L L L tt L l rc Ywhich as 1 concentration Gravimetric Instruments The good Long track record 39 High accuracy The not so good 0 Labor intensive Sampling often has to last for at least 24 hours Results may not be available fordays or weeks Airflow rates and elapsed time must be very carefully monitored to ensure accurate readings The major advantage of gravimetric instruments is that they have a log track record and can give high accuracies in measurements These types of instruments are uesl suiteu for j 39g accuracy J J J quot quot 39 39 results are not an issue The down side to these instruments is that they are labor intensive Filters must be conditioned weighed be for sampling installed and J quot J 39 L J 39 quot involvedthe results from these instruments can take days to weeks to be processed In addition the air ow rates and elapsed time ofsampling must be very accurately recorded to ensure good results These types of devices are oiten used by state monitoring networks to detect violations of air quality standards Optical Instruments The good Real time readings 39 Portability 0 Low power consumption 39 And relatively low cost The not so good Less accurate Require customized conversion equations Optical 39 gravimetrical L 4 quot these instruments provide real time readings they are portable they do not require a large power quot 39 inexpensive quot instruments are best for projects where realtime or near real time data is needed or where less accurate estimates are needed Thedown 394 quot 4 39 39 aswel equations The light 39 val ice as a function of 39 quot r r quot of ne particles and course particles changes as a result the optical instrument need to be checked against a federal reference monitor in the same area A formula is then developed to properly convert scattering to a particulate mass per unit volume estimate IA39 Monitoring ViSIbIIity For visibility monitoring information is not only needed on particular matter but also on aerosol chemical composition Monitoring is typically conducted year round over long periods of time to establish trends Visibility monitoring is another important aspect that you may want to consider particularly when it may impact a Class 1 area For visibility monitoring not only do we need to know the amount of particulate matter we also need to know the aerosol chemical composition This is a challenging since these need to be analyzed with gravimetric equipment Monitoring for visibility is typically collected year round over long periods oftime to establish trends In addition to long term monitoring scene monitoring may 39 quot 4 4 quot 39 39 I 39 39 either 35mm or digital photography at one point over time This maybe particularly useful for monitoring the visual quality of one or more vistas Other monitoring issues Monitoring Locations Normally placed at smoke sensitive locations Sampling Schedules Frequency depends upon program objectives Quality Assurance 39 Every monitoring project should have a documented quality assurance plan Notjust smoke monitoring Monitoring Costs As with all monitoring programs there are many factors to consider For example the locations on 39 39 I 39 quot quot a L 4 39 mama are all major factors in developing a smoke monitoring program Cummunllv 2 class lAiea 522 Glossary m Terms Table from I u u I l One of the most dif cult things with every monitoring program is the development of the objectives Part of this dif culty is that different combinations of objectives combined with temporal and spatial scales can lead to entirely different plans methodologies and technologies In February 1997 region 6 conducted a review of monitoring objectives and rank the various combinations in order of priority The two tables you see here show the top two monitoring objectives listed from that review You can see that the top two monitoring objectives were indeed to monitor ambient ne particulate matter concentrations and visibility impairments due to ne particulate matter mm 1 new Objective Yumarmllul mm mme Almllcmmnsmr Mmmnnnu m Munilur ne particulate mum Evaluate pummel human mu impacts in communities my summit and rural lemmas PMzsan PMin pmvmeeaunackinpublicveguiaimssmukermecasim and managers Wm assumptions used in the Environmental Assessment REEulalelightingufbumsandlhelulalbumacmauelu avuidviuialiunsuflheNationaiAmhienlAirOuaiiW Standards L girime Evaluate pulen ai imm39an healin v n acls in communities and rural residences Fruvidefeedbacklu public minim and managers Wm 35mm used in the Environmental Assessment Muhil is ibi ii p iiquot Re ifrir39ne As e ssvis i39mimcunuilmnsm ciassiav as E MW quot9 PamW a E Assess visibiiiivcunmliuns in sensitive Class H areas manglemissmns Wm assumptions used in the Environmental Assessment REEulalelluhlingufbumsandlhelulalbumacreagelu avumvismlvimpamm Langime Assess whim mum insensitive Class H areas Table from wwwf fed I 39 39 dnr For both monitoring objectives our time frame for sampling will depend upon the specific application The table you see here shows the intended applications for monitoring data and the turnaround time for each of the two objectives identified Notice that in some cases the same intended use has both real time and lagtime monitoring times associated with it For example evaluating potential human health impacts requires both real time sampling and lagtime sampling 20 Writing a monitoring plan Sections in a smoke monitoring plan Summary 0 Equipment selection 0 Recommended timing duration and frequency of monitoring Equipment sitting guidelines Personnel requirements a Quality assurance measures The 39a quot4 review quot39 quotquot 1 1 region 6 ofth USDA Forest Service To view the complete document you can go to wwwfsfedusIr6aqlsmoke20moniteringdoc Both real time and lag time plans have the following sections in them a summary the equipment selection recommended timing duration and frequency of monitoring equipment sitting guidelines personnel requirements quality assurance measures Reducing the amount of emissions Reduce the area burned Note This is not the same as delaying the release of emISSIons t Techniques include 0 Burning fuel concentrations not 100 of area 0 Isolating fuels that can burn for long periods of time 0 Burning a mosaic So far we have been talking extensively about the regulations and monitoring techniques ofair quality but this raises a major question how can we reduce the mount ofemissions we produce from a burn The ability to reduce emissions from res is partially based on the combustion ef ciency with the exception ofNOx and 002 However there are other techniques that are also effective in reducing the amount ofemissions produced hem L39 tc u t 1 id id burned Note that 39 39 139 a burned In other words burning 100 acres is the same no matter how small the units are that are burned A reduction in the area burned means that not all fuels are consumed or burned A few methods you can use to achieve this include only burning fuel concentrations isolating fuels that can burn for long periods oftime such as logs and stumps and allowing the re to burn musically across a unit or landscape L l39 AAL 1 Reducing the amount of emissions Reduce the fuel loading t Mechanical removal reduces emissions proportionally to the amount of fuel removed 0 Firewood and biomass for electrical generation Grazing Reducing fuel production 0 Site conversion Land Use changes 0 Chemical treatments Another option is to attempt to reduce the fuel loading on the burn site This involves both the physical removal ofthe fuels as well as the prevention offuel uildups The removal of fuels from the site generally revolves around some form of mechanical treatment The reduction in emissions is proportional to the amount of fuel removed Be aware though that if a mechanical treatment increases surface fuels than a prescribed re will have an increase in emissions Techniques such as ymumg urquotquot L L r The material can then be processed as wood chips or shredded biomass but remember these are only effective if the material levees the site Other uses of L K a Afar t t ta option for the removal ofvegetation before burning The use of sheep cattle and goats can reduce fuels prior to burning However there are some other ecological concerns h t a K I erosion 39 ecosystems Other management techniques that shilt species composition to vegetation types that produce less biomass per year are also an option Chemical treatments land a a 1 t 1 it t anon or eliminate the need for burning Which can therefore reduce or eliminate the amount ofemissions produced Reducmg the fuel consume or Increasmg 39 39 efficiencv Reducing the fuels consumed Note This is not the same as delaying the release of emissions Increasing combustion efficiency 0 Goal is to shift fuel consumption form the smoldering phase into the flaming phase 0 NOTE Burning under dry conditions increases efficiency but also increases the amount of material available for combustion ml 4 Two nal 39 439 increasingthe combustion ef ciency We have already discussed reducing the amount offuel consumed by reducing the area of burn targeting small diameter fuels and allowing for a mosaic burn pattern The major factors in uencing this are to ensure that large fuels either have a high moisture content such that they will not burn or that they are not consumed during the re These techniques only work if the fuels are not to be burned at a later time Increasing the combustion ef ciency is another option to reduce emissions The goal ofthis is to shilt fuel consumption form the smoldering combustion phase to the more ef cient aming combustion phase One way to increase ef ciency is to burn under dry conditions Be aware however that this also increases the amount offuels available for combustion so the bene ts of increased ef ciency will have to be weighed against the amount offuel combusting Other methods such as ignition pattern and air curtain incinerators can also be used A few final thoughts I would like you to think about what emission models might look like based on your experiences and this lecture Consider what variables we will need to know and how they might be related 0 As well as what output variables we might be interested in predicting managemen we have talked about the effects health 4 quot 439 few of quot I reduce emissions from res In our next lecture we will look at how we predict the amount ofemissions from res Until then I want you to think about what these models might look like based on your experiences and this lecture Consider what variables we will need to know and how they might be related of particulate matter on human Fire Effects and Wildlife Chad Hoffman Zack Holden Direct Effects of Fire on Wildlife only a small proportion of wildlife are killed or injured during forest fires Ambient temperatures of over 145 fare reported to be lethal for small animals and often assumed to be similar for larger animals and birds Howard et al 1959 Brown et al 2000 The rst question I typically get from people when I tell them I study forest res is what effect does it have on wildlife species Most of the general public often times assumes that wild res are devastating to wildlife The short answer to this question is that in general only a small proportion ofwildlife are killed or injured during forest res als and o en or arger 59 Brown et al 2000 Vl th this in mind most res therefore have the potential to do harm to wildlife Ambient temperatures of over 145 fare reported to be lethal for small anim a wan oral Dealing with fire Resistance 0 The insulating capacity 0 The size of the organism o The duration of heat exposure Avoidance Terry Spivey USDA Forest Service wwwforestryimagesorg There are two types of ways wildlife deal with fire they can be resistant to the heat of a fire or they can avoid fire In the case of resistance to heating will be dependent upon the insulating capacity the size of the organism and the duration of exposure The other strategy of animals to deal with fire is to simply avoid the fire A note on the Howard study This study would attract a lot more attention today than it did back in 1959 during this study they placed live animals in cages spread throughout various locations in grass and shrublands and than lit fires to look at survivability Fur is a good insulator 0 Therefore given two animals one with and one without fir the one with fir will heat up more slowly Whelan 2002 Smaller body sizes will heat up quicker 0 As duration of heat increases probability of survival decreases Terry Spivey USDA Forest Service mmforestryimagesorg One of the key issues with resistance to fire is how quickly an animal will heat up As an example of this lets imagine we took two animals a mammal and a reptile one with fir and one with out fur Lets also assume that all other things are equal Due to the thermal conductive heating properties of fir the mammal will heat up at a slower rate than the reptile Furthermore there is an indication that body size will effect fur thickness which will add another disadvantage to small animals The next key property we need to investigate is body size Smaller body sizes will heat up quicker simply because there is less material to heat up For example think of it this way if you put two pieces of ice outside one that is 1 foot by 1 foot and anotherthat is a small ice cube even though the receive the same amount of heating the smaller ice cube will melt first This leads us to the next concept of fire resistance and that is that as the duration of heat increases the probability of survival decreases Think of the ice cubes again in this case even though the small ice cube melted first eventually the larger one will also melt away Avoidance of Wildfire Animals can get out of the way burrow into the ground or find areas that will not burn in a wildfire Some animals will double back through the flames relates to heat resistance characteristics 0 Seek wet areas or areas that will not burn 39 Simply move out of the way of the fire front Much like humans many wildlife species will try to avoid the re front Examples of these behavioral strategies include simply moving out ofthe way For example a bird can just y away or other mobile wildlife species will simply move Other animals will double back through the re front This will dependent partially on their ability to resist the heat ofthe aming front But there are reports ofanimals escaping the aming front usingthis method The other method is to seek areas that will not burn or heat up to a lethal temperature This has been captured in the photo that many or all have now seen ofthe ungulate standing in the stream with the hill side burning behind However other animals especially those that are not as mobecan 39 Wuy 39 39 4 quota 39 habitat type near by or in a hollow log 1 Some notes on thermoregulation and smoke 0 Even if temperatures are not lethal smoke can still kill an animal Rodents who burrow typically survive the fire if the burrow has two openings Another important consideration when investigating the effects of wildlife mortality and survival is smoke and thermoregulation Just like human fatalities in fire smoke can be a major contributor in wildlife mortality As an example ofthis one study found that rodents who used burrows to survive wildfire typically survived if the burrow had two openings which allowed adequate ventilation for survival as well as protection from the heat source Another factor affecting wildlife survival is thermoregulation of body temperature Essentially thermoregulation is sweating to help keep the body cool In the case of an animal hiding in a shelterthe ability of thermoregulation may be a critical factor in survival The ability of an animal to survive is tied to thermoregulation through vapor pressure at different relative humidity In short as relative humidity decreases animals are much more tolerant to increased temperatures Some notes on thermoregulation and smoke Thermoregulation is the use of evaporative cooling as a means of survival Dependent upon relative humidity 0 Lethal temperature decreases as relative humidity increases low humidity permits animals to tolerate much higher temperatures than if humidity is high Life History is another important factor in assisting wildlife surviving fire 0 Examples 0 Grasshoppers may survive fire since they are adults during the fire season and can flee the area Gander 1982 o The geometric tortoise lays eggs under the ground where the incubation period lasts through out the fire season then the animals avoid dense stands which are likely to burn Kruger and Bigalke 1984 Norbert J Cordeiro University of Illinois at Chicago AMANforestryimagesorg Another important consideration in animal survival is life history The stage ofthe life form can influence many factors we have already talked about However some species appearto have specific life history traits which make them less susceptible to fire For example grasshoppers are matured and mobile during the fire season thus they maybe less resistant to fire mortality Another common example used to show how life history maybe a good defense from fire injury or mortality is the geometric tortoise This animal lays its eggs underground where the incubation period lasts throughout the fire season acting as a duel defense Than the animal avoids areas with closed canopies and lots of fuels throughout its life Thus it avoids areas which are likely to burn A Effects of a post fire conditions on wildlife Removal of plant biomass o Vegetation either directly or indirectly provides a host of environmental conditions which determine a suitable habituate for an animal Changes in soil chemistry 0 Can increase forage production after fire Wayne Adklns USDA Forest Semce WWW forestrylmages org The fire survival methods we have been discussing so far allow an animal to survive the fire front only these creatures are no faced with the task of living in a altered environment The removal of plant biomass either directly or indirectly influences the ability of an animal to survive in a given area For example the loss of hiding cover nesting sites and food are direct effects where as changes in temperature and wind or changes in soil properties are examples of indirect effects As you might guess being able to predict 39Imphes recent mummy 1mm me 11 5 years A a v M www M Na Wt Snag Decay Classes M Emu Dun mm cum Claus mummy M ai 4 u Table and Flgures from USDA Forest Servlce Common Stand Exam Users Gulde The major fire effect that influences wildlife populations is the alteration of the vegetative structure of particular importance is snag and course woody debris creation and destruction by fire As trees die and decay the species that use the tree change In addition changes in forest structure through ecological succession influence the function of snags Animal species that may use a given snag in one structural stage may be different than the animal species which use the same type of snag in another structural stage Many factors influence the use of a snag by animals including the diameter height and decay class The above diagram shows the snag decay classification used in the USDA Forest services common stand exam This method of classifying snags is very beneficial in wildlife management as different decay classes are used by different species For example bats generally roost communay behind loose bark on snags Using the classification scheme above you can see that snag classes 1 and 2 may be good habitat for bats An understanding of the habitat required by individual species is needed to manage the distribution of snags However Scott et al 1977 state that snags less than 10 cm in diameter are of little or no value as nest sites for primary cavity nesters Snag pynamics Recent SnugK LooseBurk Snags rim Snags of Snags Wkquot Smgs Fuller15mg x mum Imm r mm Hypunmmu chuugm in mg decuv mum we um mnmug 4 were wild re The decay claw Lire mm 39rmmm 31 ul mm luver Rrhml 6WD imunemnum c n l Amount of CW1 T rin Time since Fire Fig 2 lhcnrcliml puumu or WD qpcs and immlnls nnzr time after 2 disturbance mm mm 1 am m pmlrdislurbdmc uuuuxnuluuun 39nm area quotMerlinl1in ruprcwnb the autumn urcwu After lluinnm m ul mm md Spie at all mm Thomas et al 1979 thought that snags would progress through time in a step wise fashion from one class to the next Once a snag has progressed through Thomas s theoretical step wise model the snags will become woody debris Only a few studies have reported post fire fuel loadings in the western US To look at changes in fuel loadings over time after sever wildfires Passavoy and Fule 2006 collected data on seven wildfires covering a chrnosequence from 3 to 27 years post fire in northern Arizona There results found that snag densities declined rapidly up to about 9 years post re following the pattern that Thomas had suggested However broken snags decreased with time which was in contrast to the theoretical model Sound course woody debris was dominant in all fires except the oldest one 27 years post fire and peaked at about 8 years since the fire The results of this study tend to agree with the theoretical models presented in the slide Course woody debris as plant habitat Many taxa use course woody debris as plant habitat 0 Dennis and Batson 1974 found 11 species of herbs which were restricted to floating logs and stumps in a North Carolina swamp o KcKee et al 1982 found that 9498 of tree seedlings in P5itchensisT heterophyla forests were growing on CWD Course woody debris can also provide refuge si e The impedance eiceeise needy depns as a sepsiiaie nas peen ieceenized iei seineiiine Them aie manylaxa nnicn naye peen asseciaied niin ceeise needy depiis inciedine aieae iicnens inessesieins ceniieis and naidneeds Many eiineseiaxa anacn in ine senace eiine ceeise needy depns as epiphyles neneyeiseineyasceiai planls inaysend ineii ieeis inie ine ieiiine need in exiiacinaiei and neiiienisinniie siiii eineis inay ieei in a mad ei decayine nne iiiiei en ine seiiace eiine ceeise needy depiis These iniee piecesses aie nei mulually exciesiye and a indiyideai planl inay ee inieeen aiiiniee siaees eyeiiiine Time is idle inlmmalmn enine piepenien nlplanls asseciaiednnn ceeise needy and en inese nnicn naye a iaceiiiye ei epiieaieiyese in eeneiaineipsiaieiyappeaiiesiiiciedieceeiseneedydepiisHanneneiai i985 HeneyeiDennis and Eaisen i974 ieendinai ineie neie ii species eineipsnnicn neie dependeni epeniieaiine legs and sieinps in a nenn aie ine snainp siiniiaiiyiensiedies neieine impedance eiceeise needy depiis in ienns eiiiee iecieiiineni Haimnn ei ai was siaieinai s diiiiceiiieiedee iiiiees ieeied en ceeise needy depns aie iime ineieinan due in ine lack eiscieniinc nneniedee Heneyeiineie aie seyeiaiexainpiesinnnicn ceeiseneedydepiisseeinsie eyeiyiinpenani Fniexample KcKee ei ai 9332 ieend lhalBAVBEWe eiiiee seedlings in Psdcnanssi naiaiepnyiiaieiesis inine pacinc neiinnesi neie eienine en en ineeen ll eniy nyeied ere eiine ieiesiiieei Oinei siediesiiein ine pacinc nennnesi naye aise ieend inai ceeise needy depns is an iinpenani seedped asneii ei example cniisiyand Mack i984 ieend WWWe an li yele39ipplsilyl39l a seedlings in Deeeiiiniieiesi neie ieend eienine en ceeise needy depns eyen ineeen ll eniy ceyeied5 ei e eie eei in addiiien in pieyidin napiiai ceeise needy depiis inay aise pieyide ieieee siiesiei pianisinai aie piene in neipiyeies nnen eienin en ine meslllimi pecaese p anls en iaiee legs and sieinps may be ineie diinceii in ieacn in addiiien a iaiee cenceniiaiien eiceeise needy depns can ienn a naluial exclusinn aiienine paicnes eiyeeeiaiien in ee eneiazed Fianklm and Dyiness i973 One eiine inaiei eses ei legs as napnai is pyienei pacieiia and aiueuae Many species eiieneiiei example aie asseciaied niininedeca piecesseidennediees Gipeiisendiamyieend 2 speciese pasidieinyceies en pendeiesa pine in Anzena and en Maxim nnicn caese decay an eniynii inese eieanisins ese ine leg as napiiaiiney aise niii iniieence is use pyniidiiie species Fire Effects on Wildlife Communities Community responses to fire 0 Increasers predominate 0 Decreasers predominate 0 Most populations change 0 Few populations change 0 Intermediate change Terry Spwey USDA Forest Senme err Wojcrech Pohsh Forest Research nshtute WWW roresrryrrnages org WWW roresrryrrnages org Based on Rowes 1983 classification of plant responses to fire Huff and Smith 2000 developed the following guidelines for the effects of fire on animal communities Mean changes in abundance before and the first few years following a fire or in unburned versus burned areas can be classified into one of these six categories Possible community response patterns using the six categories based on abundance Fire Effects on Wildlife Communities Response categories Invader tYEfCaHJ hvaders are not detected before the re and can be de ecte aft he re Exbfofter TybfcaHy detected before the re and have an hcrease of 50 or more after me re Resfster Detected before the re and have a decrease offess than 50 after the re Eh urer tDhete cted before the re and a greater than 50 decrease after a re Avofder Detected before the re and not detected or has ow pOpUiaUOn numbers after the re VacfHator Shows Wfde UCtUaUOHS both before and after the re hcohsfsteht Fire Effects on Wildlife Communities Increasers predominate Invaders and exploiters o Decreasers predominate Avoiders and endurers 0 Most populations change Proportion of invader and or exploiter responses and of avoider and or endurer responses 0 Few populations change High proportion of resister responses and a low proportion of at er responses Intermediate change A high proportion of resisters endurer and exploiter rsponses with a low proportion on invader and avoider responses Lets now return to look at the different community responses that were presented by Rome 1983 and modi ed by Huffand Smith 2000 The rst class of community r 39 39 I 4 39 In 39 a quot39 typically see an increase in the invader population and or exploiter populations The next community r 394 39 quot I 39 this type of community response we will see an increase in the avoiders and endurers with in the area The 339 type ofcommunity response is that most populations will change This type of community response consists of a proportion quot 4 4 r39 quot quot 394 ln otherwords it isa combination ofthe rst two community responses The forth type of community WNW at 44 t L inta t W r r r 1 r Jr see a high proportion of resisters and a low proportion of other responses Last we can get a intermediate change within the community In this response type we tend to see a high proportion of resisters endurers and exploiters and a low proportion of invaders and avoiders Tools to predict the effects of fire on wildlife 0 Wildlife Habitat Response Model Pilliod and Velasquez 2006 0 Relationships based on over 450 peer reviewed articles Wildlife Habitat Response Model Treatments to Be Compared You must select at least one IE age Cunlmue Earlier in this lecture we noted that snag and course woody debris dynamics were tow important wildlife habitat components that are directly related to fire In addition to these there are many other vegetation structural characteristics that are important One tool that you can use to help asses the effect of fire on wildlife is the wildlife habitat response model or WHRM WHRM predicts qualitative changes in the suitability for a given species in response to the effects of fire It uses species habitat relationships from the scientific literature to predict how changes in habitat elements may affect the life history requirements of a given species The model was designed to predict the effect of habitat changes on life history traits of each species Although the model was designed to assess fuel treatment effects and compare alternatives if the effects of fire on habitat characteristics is known then the effects of a wildfire may be considered A Mechanics of running WHRM 0 Select Treatments Wildfire Thinning and Pile burn thinning and broad cast burn and prescribed fire 0 Note WHRM does not predict the effects of fire or forest operations on vegetative structure you must input these variables 0 Input cateqorical changes in habitat elements WHRM is a pretty basic model the first step is to select between two to four treatment options Next you need to select a species The model can only run one species at a time and is limited to species occurring in the dry interiorforests of the western US After selecting the species you need to fill in the habitat elements for each treatment option you selected These measures are dependent upon each species and the relationship reported in the literature The figure show here indicates the habitat relationships known to be importantfor Canadian lynx Once you have filled in the approiate data you can run the model WHRM Outputs Moderately Negative Highly Negative Slightly Negative Moderately Negative Other information includes a summary of the analysis Background information a summary of speci c studies The model provides the user a qualitative response of the effects for three life history traits reproduction foraging and cover In the example shown here you can see that the effects of ourwildfire had a negative impact on all three traits In addition to the qualitative predictions made by the model it also reports a summary of the analysis provides background information about the species and gives a summary of the specific studies used to develop the relationships Assumptions of WHRM o Assumptions A Relationships reported in the literature are correct Habitat relationships are linear o For example a 1140 increase in a positive habitat element is equal to a 11 40 increase in habitat suitab39i o Species abundance or probability of occurrence is correlated with habitat suitability 0 Limitations Does not account for climatic patterns and in uences following fire o Only predicts stand level habitat relationships Predictions maybe less informative if species use more a one stand to meet habitat requirements WHRM allows you to see what parts of an animals life history are going to be most effected by some treatment or wild re As with all models the information provided isonly 4 in ut L l Ll or 4 rlc model The primary assumption ofthis model is that the relationships reported in the literature are correct The major issue with this assumption is that most eld studies are untested so there is a general risk with using them to make predictions about species responses to changes in the habitat Another assumption of this model is that there is a linear 1 to 1 relationship between habitat elements and suitability In other words when a particular habitat element has a positive relationship and it is increased by 11 to 40 then the model assumes that the habitat suitability also increased by 1140 The nal assumption ofthe model is that species abundance or probability of occurrence is correlated with habitat suitability This assumption is based on a the idea that most ofthe relationships use i RM relate s ecies abundance to a habitat element however high abundance does not necessarily mean high quality habitat is present In addition to the assumptions ofWHRM it has several limitations that should be considered during its use First the predictions in WHRM do not account for any adverse effects due to climatic conditions such as drought In addition the model only I I I I r levels This limitations also means that for species which use multiple stands to meet hahitat 39 I 39 39 39 39 39 In add39tion it should be noted that this model does not produce quantitative predictions or measures for prediction con dence Summary Most wildlife species present some strategy for survival of the fire front Wildfire wildlife populations mostly through changes in food and plant composition Wildlife communities can respond in several ways depending upon the life traits of the individuals within the community and the changes in post fire plant structure and composition Fuels and Fire Effects Chad Hoffman Zack Holden The effects of fire on resources results from its effects on fuels The way that fuels burn determines the heat regime created by a fire The nature of fuel consumption determines the peak temperatures reached the duration of heat and the stratification of heat above and belowthe surface During this lecture we will talk about how fuels are described and their properties What is fuel Fuel is all living and dead organic material that can be ignited by a fire c Total fuel entire biomass c Potential fuel part oftotal fuel that could burn in the hottest fires 0 Available fuel what actually can burn in a given situation The rst question we should be asking ourselves is what are fuels Fuels are organic materials that burn in a re Vegetation is the primary fuel during most res however structures may also be considered fuels especially in the u 4 L l T icanytt it w u 4 t a total fuel potential fuel and available fuel Although these three terms are all related there are small differences in what they mean For example Thetotal quot quot quot quot39 a iven area vegetation dead wood needles homes snags etc Where as the potential fuel isthe part ofthe total biomass which could burn during the hottest possible re here we may expect only some of the vegetation and needles to burn part ofa home The potential fuel will never be more then the total fuel and in most cases will be signi cantly less especially in forested landscapes The available fuel is the amount offuel which will burn in a given situation That is given certain weather conditions fuel moistures etc how much ofthe fuel will burn In this case the available fuel will almost always be less then the total fuel or the potential fuel particularly in forested landscapes For example a site may have 48 tons per acre oftotal fuel but the potential fuel may only be 26 tons per acre while the available fuel for a prescribed re in April may be only 10 tons per acre but a wild re in June may have 22 tonsacre of available Ecological Roles of Fuel Wildlife habitat Nesting sites 0 Foraging sites 0 Refuge sites Nutrient storage Plant and insect habitat 0 Provides substrate forgermination of plants 0 Habitat for insects which may be prayed upon by wildlife species Soil stability The characteristics ofthe fuels complex is important to understand how re behave and the heat regime produced by a re as well as to develop managemen g39 quot j quot l39 39 L llllpUlldlll 39 an ecosystem They provide habitat for both terrestrial and aquatic species they act as nutrient stores and provide habitat for plants and insects Describing fuels Fuels are described by type of fuel and state Fuel components ground surface ladder and canopy 0 Physical properties size shape loading and arrangement 0 Chemical properties heat content flammability c Fuel moisture live and dead fuels Now that we have discussed what fuel is lets talk about how we can describe fuels We can describe fuels by the type and state ofthe fuel Some common descriptors 39 quot quot 4 or strata the physical U I properties chemical properties and the moisture content As this class goes on we will talk about the methods for describing the physical properties offuels in different fuel layers You should be aware that for many situations the chemical properties of fuels are not measured but assumed to be constant this is especially true when we talk about fuel models Classic terminology Fuels Complex the amount and arrangement of all the fuel in an ecosystem IGround fuel include the duff roots and rotten 095 o urface fuels includes the litter downed logs seedlings shrubs and grasses and forbs Canopy fuels includes overstory trees and large shru s s gwen area or ecosystem When descrrbrng the amount and arrangement offuer rn an area rt ma be benefrcrar o report thrsb fuer rayer CrassrcaHy fuers have been dwrded rnto three ra ers based on yertrca drstrrbutron sometrmes ca red fuer beds orfuer strata ground fuers surface fuers an canopy fuers sorr no ron er has a substantrar amount of organrc materrar Thrs materrar rs often caHed the duff rayer and consrsts o humus and son wood from burred rogs and decomposrng roots Frres burnrng rn the ground fuers produce persrstent and harmfur smoke and can rergnrte surface fuers Surface fuers consrst of the We and dead yegetatron above the duff and berow the canopy trees Thrs fuer rayer rs yery dryerse contarnrng the forest rrtter downed rogs smaH preces ofwoody materrar wrng and dead grasses Canopy fuers consrst of rarge trees and shrubs whrch make u the forest canoEy TyprcaHy when we referto canopy fuers we onry are ta krng about the needres twr s an smaH branches ecause they are commonr consumed rn a forestfrre The term canopy bromass or otar canoEy fuer road typrcaHy rncrude aH prant ma errar rn the canopy The receptwrty of the canopy fuers to crown frre rs ased prrmarrry ont ree factors canopy base her ht canopy burk densrty and to a resser degree forrar morsture content Canopy base herght rerates the bo om of the oyerstorytree crowns to the to o the understory fuer bed and radderfuers Canopy burk densrty rs a measure of the amount of fuer contarne rn a unrt yorume of the canopy and forrar morsture content rs the morsture content of rwrng forrage reported on a drywerght basrs Anotherterm that rs commonry used rs radderfuers radderfuers LadderFuer are fuers whrch royrde yertrcar contrnur between fuer strata thereby aHowrng frre to carryfrom one strata to another We o en thrnk of radder fuers tha connectthe surface fuers and cano yfuers Common radderfuers are shrubs and sm aH trees so we mus consrderlhese erements when we conduct fuers rnyentory or mapprng projects 39 WFCC S LT IEt ra t a 7 77 7 7 wZOOH 7777 Fnulbud wan Calcgonvs slmlum Czn v Snag Olhcrzenal fuzls Nam drape 5 GramvmidE Herb swims E x I Swim Railsquot Plies lankpols sums wucd wand andwmm 5mm Moss m g 13 WE lie E slrzlum Muss Lichen Lille Ground luel l WWquot Dull Bez al accumulaluii 0 Six horizontal fuelbed strata used in the FCCS from Sandberg et al 2001 Other approaches to describing the fuel layers have been developed for example the Fuels Characteristic Classi cation System Ottmar 2003 takes the classical three layers of fuels and breaks them down into 6 layers Under this system each fuelbed layer also represents a different combustion environment which contains one or more fuel types For example the litter fuel bed contains litter and lichens and moss as fuel types Each fuel type 16 in all can than be described by physiognomic and gradient variables thus allowing the user to include or exclude as much information as needed for a particular purpose By including more layers this approach allows us to describe the fuels complex in more detail and therefore allow us to look at the re behavior and effects of re in a more meaningful way Finure pastime sum have Photo taken from Graham et al 2004 This picture shows the relationship between different fuel bed strata on a site You will notice that each strata is labeled in the picture I want you to begin to think about how we describe the properties of each strata in terms of fire behavior and in terms of ecological function Are the same properties in each strata important or do we need to describe the fuels strata differently depending upon our management concern For example do we need to have the same information about the surface fuel strata to manage wildlife as we do for predicting re behavior Describing fuels Within a fuel laye Intrinsic properties Chemical properties Extrinsic properties 0 Quantity Size and shape 0 Compactness arrangement All fuel in a fuel layer can be described by its intrinsic properties such as the mineral content and amount ofvolatile waxes and oils or by extrinsic properties such as the quantity and arrangement ofthe fuels fuel burning well increased levels ofvolatiles can increase the spread rate of re We typically do not measure intrinsic properties of fuel during eld inventory and mapping procedures Instead we assume these properties from published literature The key point to remember about intrinsic fuel properties is that they do not change where as extrinsic fuel properties do ChemicalI quot l ashigh 39 39 quot quot quot quot ofthe IIJ quot1 a a The most common measured extrinsic properties are the quantity and size of fuels We olten report the quantity of fuels by a size class Other important variables are the compactness or bulk density ofthe fuels and the vertical and horizontal arrangement The arrangement and compactness of fuels will effect both the probability of ignition and re spread characteristics Intrinsic Fuel Properties Lignin 9H3 Hgo IZH OH 9H2 quot2H 930 CH2 CH HCOH cusp CH30 H0 0 H H3 http www eng rpl edudeplchemr engBlotechrEnvlronFUNDAMNThgmn mm Cellulose Intrinsic fuel properties are inherent characteristics like chemistry and density Plants consist of organic compounds of carbon oxygen and hydrogen These compounds make up 50 44 and 5 of plant material by weight Plant compounds can be divided into 4 types cellulose hemicelluloses lignin and extractives Cellulose is a sugar which forms linear structures giving structural strength and rigidity to cell walls Cellulose goes through pyrolisis rapidly and leads to flaming combustion Hemicelluloses are carbohydrates and are structurally similar to cellulose Lignin is an aromatic polymer which gives wood its stiffness Lignin is more resistant than cellulose to decay So the ratio of lignin increases as wood decays Lignin does not go through pyrolysis well and leads to smoldering combustion and therefore dirtier smoke Extractives are various other compounds such as alcohols hydrocarbons waxes and oils which all volatilize and affect fire behavior The point here is that the intrinsic fuel properties will effect the combustion process smoke production and fire behavior These properties are generally not measured but assumed based on species decay classification and other factors Extrinsic fuel properties 0 Quantity dry weight of fuel tonsacre or kgmz In depth typical of the forest floor Density or biomass typical of the canopy fuels The quantity of fuel can be reported in differentways For example we can report the weight of the fuels the depth or the density or biomass When we discuss the surface fuels we often report the weight in tonsacre where as the forest floor is often reported as a depth and the canopy fuels are reported in tonsacre or as a bulk density We have several techniques to measure or estimate the quantity of fuels such as field sampling transects photo series statistical correlations And remote sensing techniques Throughout this class we will talk about how these methods differ and are related in our quest to describe the fuel complex Extrinsic fuel properties Fuel particle Size affects o ignition o combustion 0 And fuel moisture t Timelag classes 01 hr 014quot diameter 0 10 hr 4 1quot 0100 hr 13quot 1000 hr 3quot duff Fuel size is one of the most important fuel characteristics affecting combustion and re behavior Large particles have high heat capacities requiring more heat to ignite and combust the particle Smaller particles have low heat capacities so they require smaller amounts of heat energy for ignition and combustion For dead fuels particle 39 39 39 39 4 quot which 39 quot n es andtherefore size classes of fuels are also referred to as timelag classes Different timelag classes burn differently 1hour fuels needle litter hardwood leaves ignite quickly and combust at rapid rates Progressiver larger particles 10 100 1000hour and larger fuels require more heat for ignition and combustion Fires usually start and spread in dead nes fuels lt in diameter which ignite increasingly larger size classes offuels If ne fuels are reduced or missing a re may not ignite or spread Timelag size classes are assigned based on the time needed for a fuel particle to adjust 39 quot 3 Speci cally it39 39 39 4 39 439 initial 39 So a fuel particle with a diameter of 18 quot an inch will take approximately 1hr to reach 39 39 39 quot 39 a 39 39 quot for re behavior 39 39 or me hazard 39 a important when for determining the dead fuel moisture content We will talk more about fuel moisture later in this lesson AI39A AA Extrinsic fuel properties Fuel shape or Surface area to volume ratio cm2m3 ft2ft3 or ft Fuels with high surface areatovolume ratios pine needle litter most foliage fuels have lower heat capacities and require less pre heating for ignition IAJA r Fuel quot r 39 quot 39 r 39 The smaller the size of a fuel particle the larger the surface area to volume ratio For example the surface area to volume ratio ofa inch diameter twig is 200 feet while the surface area to volume ratio ofa 6 inch diameter log is 8 It The increased surface area of e 394 K t 394 t 4 L t or Increased surface are to volume ratios also allows fuels to dry out and ignite more rapidly Extrinsic fuel properties Compactness is spacing between fuel particles 0 Compact fuels burn slower because oxygen is more limiting Example Duff vs litter Arrangement horizontal and vertical continuity Fuel continuity is necessary for fire spread o In our fire models we often assume that fuels are homogenous across the study area Fuel 39 quot 39 fuel particles P quot a quot 39 measure ofthe compactness ofthe fuel bed It is expressed as a percentage ofthe fuel bed composed of fuel with the remainder being air space Densely packed fuels prevent moisture evaporation and oxygen diffusion into the fuelbed thereby suppressing ignition and aming combustion Conversely loosely packed fuels allow rapid evaporation and oxygen diffusion and hence rapid ignition and aming combustion However fuels that are very open can burn slowly because little heat is trans erred among widely spaced particles For every size offuel particle there is an op imum packing ratio at which heat transfer and oxygen produce the most ef cient combustion Fuel bulk density is a related measure of the compactness ofa fuel or fuel bed It is calculated by dividing the weight per unit area by the fuel bed depth and is expressed as gcm3 or Iblt3 In general the higher the bulk density offuel is the higher the spread rate Fuel arrangement includes the horizontal and vertical continuity Horizontal and vertical distribution offuels can be described by fuel placement and fuel continuity Fuels with horizontal andor vertical continuity preheat adjacent fuels Conversely fuels lacking continuity do not transmit heat to adjacent fuels Horizontal continuity is a critical factor for surface re and crown re spread bare patches and patches of sparse vegetation act as fuelbreaks Where as vertical continuity facilitate crown ignition Changes in the fuels complex over time Changes in the fuels complex occur on multiple time scales 0 Diurnal change Seasonal changes 0 Annual change t Successional changes Abrupt changes in the fuel complex occur due to disturbance Changes in the fuels complex occur at multiple time scales Diurnal changes are primarily concerned with changes in fuel moisture Seasonal and annual changes in the fuel complex quot 39 39 I 39 39 39 39 chemistry in spring than begin to cure and become litterfall in autumn Other seasonal and annual factors such as decay rates seasonal weather patterns spring drought and long timelag response of large fuels all affect the fuels complex during this time period Successional changes include changes in vegetation and occur over long periods of t t n L Hatsit 1 1 1 climate change Abrupt changes in the fuels complex are olten times associated with a disturbance Disturbances can be either human or natural Human disturbances include silvicultrual treatments and land clearing Natural disturbances include insects and diseases Different types of disturbances affect the fuels complex in different ways Diurnal Changes ir mlfndwhigum 1mm 1m uman Aztznusl on Pea s mucus u mw l 139 l l W viiquot Willlwyyfy yl l 1n rug mam v l W Vlu yjl lr3pl Jm 1 Ju116 Jity Mill Mann Dr Ralph Nelson rnelson0115 red us Mantras mimmjmmmwss mm 3 Imus Forest Service Research Scientist Man Fa saw quot114w Him Fuel Mainre 391 Diurnal changes in fuels are due to the daily cyclic changes in temperature and relative humidity The amount of change that takes place is dependent upon the fuel characteristics weather and season Fuels with different sizes and composition respond differently to wetting and drying The is the concept behind the fuel timelag classes The point here is that fuels are constantly changing in moisture content in response to weather conditions As an example of this lets look at the gure shown here The top graph shows 1 hr fuel moisture content and the bottom shows 10hr fuel moisture content If you choose any given date lets say the big peak right before august 18th you will notice that the 1 hr fuel moisture spikes off the graph while the 10hr fuel moisture spikes but not as high This spike is a response ofthe fuel to the environmental conditions Agents of mortality W nd I Generates woody debris by uprooting snapping trees and braking branches Can cause large increases in woody debris over large areas think of a hurricane Can also cause small scale increases in woody debris down bursts We will now cover several common disturbance agents which can drastically change the fuels complex Understanding different agents ofmortality is important to us as mangers because it will be one ofthe major factor in uencing the amount and the spatial and temporal distribution of fuels Lets begin by discussing wind as an agent of mortality Wnd can increase woody quot 439 39 39 uy 39 ofliving trees In some cases such as during a hurricane wind can cause large increases in woody debris over large areas however many times wind acts on a small scale causing mortality to a few trees in a small area In general wind will cause an increase in downed logs into an ecosystem the spatial distribution of increased fuel from wind throw will tend to be clumpy ifthe disturbance occurs on a small scale but can be more evenly distributed in the case of a hurricane Although it may seem apparent that the process ofwind throw is simple there are many factors which cause wind throw For example the wind speed crown size crown density and mass stem and wood properties and soil properties all effect the ability of a tree to overcome the effects of high winds A hazard rating has been developed by Stathers et al 1994 to help assess windthrow hazard GRAVEYARD FIELDS Winorvnnow m Wunxs CDVERED mm NEEDLES wss we saw LOOKED LIKE A cmmn m MS a mum nzsraovm av m ELEV 5120 Phulu by RanuycychEEmREE Technulugies wwwfureshyimages mg Phulu by Giquiciech Pulish Furesl Research insmme WWW fureslryimages mg Phulu by Juseph O Brien USDAFures1 Servicewwwfureslryimages mg Here are a few examples of the types of damage wind can cause The picture on the left was taken in Poland this wind event destroyed over 30000 ha of forest in 15 mins You can see from the photo that the fuels complex has greatly changed how do you think the fire behavior has changed due to this wind event The middle picture show an area that is recovering from a combination of a wind event and a wildfire along the blue ridge parkway In this picture you can see that the combination ofthese disturbance agents has shaped a small patch of the landscape What effects do you thinkthe wind throw had on the ability of fire to spread in this area and how do you think these two disturbances effected the vegetation Ok the picture on the right has nothing to do with natural landscapes but it does show that not only is wind a majorfactor in ecological terms but also in economic terms Plus I like the picture Left Photo Damage in Pisz Forest Division Northeast Poland Strong winds on Jul 4th 2002 destroyed over 30000 ha of forest in 15 minutes Poland Middle Photo Catastrophic winds spruce and fir forest Blue Ridge Parkway NC Right Photo Blue spruce that failed at the roots in high winds Agents of Mortality Fire Fire can directly and indirectly effect mortality Direct effects of fire include mortality due to stem girdling crown scorch and lose of root systems Indirectly fire can cause basal wounds weaken tree defenses and expose survivors to increased winds Fire can eitiieiuiieui Ul F caused by stern glfdllfig tiui lll tuitn Ul lU Ul tiie lUUt teiii F lllUltdllt orplantor p g aiii many facto including the type of llfe fire intensity and the species composition and structure Fire typically tiie iuei tuiiipie as time goes on H al a t a a J J l l l l tllllE lt d s fuels from the ecosystem during the combustion process The effect of fire on fuel loading characteristics is a dynamic process which is dependent upon the type of mortality For example if t canopyf c u l filter for uel now have an increase in dead flasliy fuels in the canopy iepuiieu u i iueeii mortality nritl39ielanrl cane Hill is m course Woody time iiigiiei 4 L 4 L the same time period Phulu By Billy Humpmies Fureis esuurce cunsuiiams in WWWVEIVESUylmagES mg Phulu By Dave PuWeii USDA Forest ServicE WWW fureslryimages mg Phulu By Dung Page USDl Bureau quand Management WWW furestryimages mg Here are a few pictures of the effects fire can have In the left hand picture you can see a large fire scar fire scars can reduce a tree s vigor and allow for diseases and insects to successfully invade a tree However in many cases a fire scar is not needed to allowa successful attack on a tree as shown in the middle picture In this case Dougfir beetles successfully attacked and killed a tree after a prescribed fire Note the pitch tubes and frass in the photo In the right hand picture you can see that the fuels complex was drastically changed following the fire What do you think the effects of fire are on the fuels complex and what do these effects depend on Left Photo Large fire scar in tree from many old fires Tower fire Middle Photo Douglasfir beetle induced tree mortality following a management ignited fire Note pitch tubes and frass Right Fork White River prescribed fire October 2001 photo July 2002 Uinta National Forest Right Photo Yellowstone National Park fire Agents of mortality Insects Like fire insects also can directly and indirectly cause mortality Insect epidemics may add large amounts of course woody debris over large areas 39 quot39 39 quot the most 4 39 g quoti in the united states Like fire insects can directly or indirectly cause mortality The direct effects occur as a result ofthe insect attack while the indirect effects are due to a lowering inplantvigor quot 39 439 4 quot 39 oher4quot quot a as diseases to cause mortality Generally insect attacks occur at endemic levels causing mortality in small areas however it is possible for insect attacks to cause tn L it L m M 1 1 1 native insect populations For example mountain pine beetle outbreaks a native species in the western quot 4 mi linn acres in quotquot quot quot emerald ash borer has killed more than 20 million trees in the great lake states since its discovery in 2002 USDA Forest Service 2004 Generally when insect cause tree mortality the result is an increase in snags and dead foliage in the canopy fuels As time goes on the foliage will fall to the surface followed by the branches and tree stem Thus the effect of insect mortality on fuel 39 439 39 4 39 4 quot a 39 39me In mostra e in ert 39 ispatch causing increased fuels in small clumps however in some cases particularly during outbreaks fuels may be distributed somewhat evenly over large areas TA geint siof r ri Bria I Ity insects e v a nunvssaox Phutu Ely Mtnneseta Department at Photo by William M Ciesla Furest Health Natural ResuurcesArchives Mtnneseta Management international Department at Natural Resources 39 vwvvvfurestryirnages urg m quot Wyvvvfurestryirnagesurg Phutu Ely Ternel Gukturk anvin fDrES L faculty Wrurestrytmages mg The effects of insects on the fuels complex can be quite variable depending upon many factors In the left hand picture we see a small group of red pine that were killed by bark beetles On the middle picture we can see a landscape which has been drastically altered by spruce beetle How do you think the fuels complex have changed in these two situations both in the near term and over time In the left hand photo you can see two adult Pandora Moths which are native insects which cause defoliation A current outbreak in California has seen light defoliation over 40000 acres how do you think this will change the fuels complex will it be different then the two bark beetle pictures Left Photo bark beetle damage in red pine Middle photo European spruce bark beetle Atila National Park Turkey Right Two female adult Pandora moths on a ponderosa pine 21 Agents of mortality s Disease There are a large number of diseases which can generate fuels in forested ecosystems Typically diseases generate small amounts of fuel However exotic diseases may generate large amounts of fuel over large areas 1 1 t t m fuel m nu tlEtUE lyynlcn unlterl ate l h h h thelr larne area p nun ru tWHlLH w my um pm 1 up tU percent of the butternuts ln North Carollne and Vlrglnla and currently sudden oak death Whlch has Oregon fuel loadlngs cyertlme The effect of dlseases on fuel loadlngs l5 dependent upon many factors lncludlng the speclflc dlsease the host and stand condltlons For example a dwarf mlstletoes kllled t u u t r4 5 5 rnurelmel T r Ul ea e l um trump urpatur muyv lJu Hm wrmlnsectsan t L 5 large scale outbreaks partlcularly Wrth lnyaslye specles Emma University or Georgia VWWV furestryimages org thu by Chad Huffman F39hutut by Jane Taylor USDA Forest Service vwwvfurestryirnages org The effects of diseases on the fuels complex is dependent upon both the type of disease and the level of infection In the left hand picture you see a large Dougfir infected with dwarf mistletoe you can see from the picture that the witches brooms have changed the fuels complex in the crown of this tree In the middle picture you see a 25 year old plantation infected by a root rot Notice the wind thrown trees You can see that these two diseases have influenced the fuels complex very differently In the right hand picture you can see increased surface fuels under a severely infested dwarf mistletoe stand How do you think these diseases will in uence the fuels complex as time goes on Left picture V tches brooms often indicate dwarf mistletoe infection Brooms result from a proliferation of small twigs on a branch Douglasfir is a species which generally form large distinct brooms in response to dwarf mistletoe infections Infection tend to be most severe in the lower portions of the crowns Middle picture root rot in a 25 year old plantation note the wind thrown trees Right picture surface fuels under a severely infested dwarf mistletoe stand a recent study Hoffman et al 2007 found that fuels in severely infested stands may be up to 5 times higher then in areas with no mistletoe in the southwest 23 Agents of mortality Comgetltlon Competition can cause mortality through suppression of other plants Mortality caused by suppression occurs most often in forests with closed canopies The 32 power law Yoda et al 1963 has been used to predict mortality caused by suppression Suppression is the death of a tree due to slow growth caused by the competition of neighbors Typically mortality caused by suppression occurs in the smaller trees within a stand Although suppression caused mortality can occur in any stand it is most olten found in forest with closed canopies The 32 power law along with yield tables have been used to predict suppression based mortality in many areas Unlike the other agents of mortality we have talked about the spatial distribution of suppression caused mortality may be much more eve 439 quotL 4 scape Tquot 39 I 39 uueif 39 4 r 39 very homogenous Fuel Moisture 0 Moisture affects every stage of the combustion process which affects smoke production fuel consumption and fire effects ANNUAL RING mpm39wwwmsci pllieduljmainibSSBVVebpagesxylem htm Asl mentioned earlier in this lecture we describe fuels by their characteristics as well as by their state of moisture condition Moisture affects every stage of the combustion process which affects smoke production fuel consumption and fire effects With sufficient moisture fire can not burn butwhen moisture is absent fire can burn intensely Moisture content also affects the available fuels Relatively more or less of the same fuels complex will be able to burn depending upon the moisture content All plants are designed to hold water with almost all living material containing a water based solution In particularthe xylem s major physiological function is water transport In more technical terms plant materials are hygroscopic that is they are capable of attracting and holding water This relates to how we measure fuel moisture Fuel moisture is measured as a percentage of dry weight Fuel moistures can range from 2 to 3 percent in dry dead fuels to over 300 in rotten fuels In live fuels moisture content is typically between 50 to 300 25 Fuel Moisture II Relative humidity Precipitation Eva poration Evaporation Ground moisture Figure 312 Factors influencing moisture exchange in wildand fuels Fuel Moisture is a dynamic process Fuels gain moisture from liquid water or water vapor and they lose moisture through evaporation There are many factors which can affect live and dead fuel moistures Live fuel moisture is tied more to seasonal patterns than short term weather changes In general there is a high moisture content associated with fresh foliage this declines over the season as the climate becomes drier and eventually drop upon curing or frost An example of this process is cheat grass which cures early in the season This is also why it is such a fire threat Dead fuel moistures are affected much more by short term weather conditions as well as by their characteristics arrangement and topography For example wind typically enhances evaporation however the cooling effect of wind can counteract solar heating topography is related to solar radiation and humidity fuel arrangement can affect exposure to solar radiation There are many more examples you can probaly think of but for now let move on 26 Timelag Size Classes Timelag is the time needed for a fuel to adjust to moisture change the rate at which a fuel approaches the equilibrium moisture content Timlag Classes 1 hr 0 4 diameter c 10 hr 4 1 diameter 0 100 hr 1 3 diameter c 1000hr 3 and the duff Timelag is the time needed for a fuel to adjust to moisture change the rate at which a L t t in L mtre e I oIsu content is the moisture content that a fuel would reach if exposed to a constant external moisture level It is important to recognize that fuels will never reach the quot 39 quot quot 39 39 quot 39 quot L 39 quot 39isthetime and EMCat 39 quot quot described r z 1 1 at an a 1quot a initial t aconstant 4 39 quot quot 39 quot 39 as the timelag fuel classes These values are just a simpli cation ofthe dynamical fuels environment You should only use the timlag size classes as a general guide to look at the relative differences between fuel moistures These classes are olten far off for example Anderson 1990 found that conifer litter generally took between 2 and 34 hours to reach 63 ofthe EMC and grasses mosses and lichens took between 2 and4 hours A few final thoughts As we move on through this course I would like you to keep in mind the following o The processes that are affecting fuel loadings The effect of different disturbance agents on spatial distribution of fuels and on changes to the fuels complex The ecological function and importance of fuels in natural resource management c The role fuels play in determining a fire39s heat regime and their role in post fire conditions I vvuulu line uu u 39 I are effectin 39 a different scales and about the effects of different disturbance agents have on the fuels complex both in terms ofthe amount and type offuels present and on the spatial variability offuels Try to think about how the fuels complex in uences the heat regime a re produces as well as their role in the recovery of burned areas Predicting fire effects on soils Chad Hoffman Zack Holden During this lecture we are going to look at the concepts involved with predicting soil heating and than review FOFEM to see how it predicts soil heating Figure adapted mm Sale and Rubinquot 1994 Lets begin by setting up our conceptual model for predicting soil heating The first thing we need is some form of combustion of the surface fuels From this point we next want to assess if a duff layer is present and if this will ignite If a duff layer is not present than the heat generated by the combustion of the surface fuels will heat the mineral soil directly If a duff layer is present however we will need to assess if combustion will occur in that layer and than predict the amount of heat generated After this stage we need to know some soil properties such as moisture content After this we can develop a soil temperature profile over time for the soil So now lets talk about the processes Which are controlling each of these stages and begin to develop a mathematical representation Heat transfer downward Fuel characteristics Loading Size Arrangementand Composition Moisture content Envrronmental Conditions Temperature in e Relativehumidity Fire behavror characteristics Rate ofspread Rate ofheat production The heat produced by the combustion ofthe surface fuels can be transferred downward to either the mineral soil or the duffif present The amount ofheat transferred downward during combustion depends upon the fuels present and the re behavior Speci c fuel properties such loading size the arran emen composition and moisture content will affect the total amount of heat generated In addition quot 39 39 439 quot I 39 39 humidity will effect combustion and the heat generated by a re All ofthis leads to re behavior characteristics such the rate of spread intensity ame length residence time and the rate of heat production which will in uence the amount of heat that is transferred downward Heat transfer mechanisms and radiative heat flux Heat transfer is by Radiation 39 Convection o Conduction probably the least important ofthe three Radiative heat flux described the rate of heat transfer The heat produced by quot quot ofthe surface 39 39 4 4 4 by radiation convection and conduction It is thought that radiation and convection are the primary modes ofheat transfer although little is know about the amount of heat transferred by the three classes Conduction is most likely a minor contributor to heat transfer between the surface fuels and dufflayer or mineral soil because the fuels are generally not in contact with the mineral soil or duff surface unless large logs or other concentrated fuels are present Emissivity form the combusting fuels temperature of the heat distance of the surface form the heat r quot quot 4 39 quot radiative heat ux 7quot 439 quot quot ux is a 4 4 quot quot quot transfer between the combusting fuels and the heat sink Duff Heating and Combustion 0 Duff can act either as a insulator ora heat source depending on weather or not combustion occurs Duff ignition combustion and heat production v Packing ratio o Inorganic content Moisture content lfthere is no dufflayer present than the heat input to the soil is much simpler However in most cases a duff layer will be present so we will review the heat transfer involved during duffheating and combustion Duffcan act as an insolating layer for the soil when it does not combust or as a heat source when it is combusted Although the addition of duff into our model complicates things we do know some ofthe features which control duffignition Duff Combustion and Heat Transfer Ash layer caused by 4 smoldering combustion can prevent the upward dissipation of heat form the V Mmeraklraysvs soi I ll lbw 4 It has been estimated that 40 to 73 of the heat Mmmym generated by the 51 combustion of organic layers can be transferred into the underlying soil lltl Q 11 lgmllan Polm mam Mmlgr Pyrolysis Zane may Iona 0 am Mailer Mmeral Layers Cl Haunt 25 A Mm mew 7 Ihe smoldevlng mm m lli lgnillon pawl yscmumdblhe usmgmrmm ve re rmdsmr umvimllylmmlheign mu l p s l pa m A divelopx mam lama m a and mm devulops m a large bmdw area icy Adcpled rm mam ml vws cwigm r W75 tall hubn Rr N Slaw It is thought that ignition in the duff layer occurs at a single point or in several locations within the duff by material which burns into orthrough the duff layer The re than spreads concentrically from the ignition point before developing into a large burned out area as shown in the gure here The combustion ofthe duff layer as described here generally involves a smoldering reaction The combustion of duff can transfer large amounts of heat into the underlying soil In addition to creating a heat source the combustion process can create an ash layer which can prevent or limit heat dissipation upwards thereby causing more heat to penetrate into the soil As a result ofthe creation of the heat source and the effects of ash on heat transport it has been estimated that between 40 and 73 ofthe heat produced by the combustion ofduff can be transferred into the mineral soil Figure adapted mm Sale and Rubinquot 1994 If we return to our theoretical model we are using we can see that we have now discussed the heat transfer mechanisms to get the heat produced by a surface fire into the duff layer if present or into the mineral layer if no duff is present as well as the processes of combustion and ignition in the duff layer The next step is therefore to look at heat transport within mineral soil Heat Transfer Through Mineral Soil Factors effecting heat transfer through mineral soil Soil moisture content t Chemical soil properties Physical soil properties Once heat nally reaches the mineral soil its transport through the soil is dependent upon the soil moisture content and the chemical and physical properties ofthe soil For example the speci c heat bulk density and thermal conductivity ofthe soil will act together to effect the rate of heat ow Other factors such as parent material porosity water content temperature gradient hydraulic conductivity will all indirectly affect the rate heat ow isbul Mlneral li ropertles o Vapor flux accounts for TABLE 22 Speci c Haul nml Thermal Conducliwhas cl Soil Mulerials a s m u C h a s 6 0 00 of Speri z Heal ThermalCandudiviiy h ea t t ra n s fe r Ca m p b e H Fully My et al 1995 Oven Dry Salumled Oven Dry Snlumred Maleriul aIgper C lmlKma CH x 1074 o qu u Id fl u x co nt n bu tes m4 no on w W about 1000 or less of um um um mm mm heat transfer MI I l All 7 Al N 7 hynyj ml U x UH 1W llll and w w W llu um convection account for Mm 7 mu 7 Hm the remaining amount mm 4 mum v mum w 39l l h mm ml H wmm m m lulnwl hm lm in mm Wm 3 was Mm mum m lunmuwvu Ml mm Mm mm m The simplest case of heat transfer through mineral soil occurs when we have completely dry soils In such a case the history of the heat input must be known to predict a soil temperature profile However when moisture is added to the soil system the heat transfer process gets complicated This is because the presence of water increases both the heat capacity and the heat conductance values ofthe soil The increase in in heat capacity allows soil to absorb more heat without a rise in temperature while the increase in thermal conductivity allows for more rapid heat transfer The table show here shows the specific heat and thermal conductivity of soil minerals The bottom line is that when moisture is present in the soil we first need to heat the soil up to vaporize the water about 95 to 100 degrees c and than further heating takes place as in a dry soil Although conduction and convection are important in the transfer of heat within soils Campbell estimated that as much as 60 of heat transfer may be due to the movement of water vapor it is also estimated that liquid flux accounts for 10 or less of the heat transfer f L A A conceptual model of heat transfer in soils o Fourier s law the law of heat conduction 5Q i c f VT 13 6t 5 Where Q l5 the amount of heat transferred its the tlrne taken tr u u h tau temperatures for some common materials t 5 l5 the surface through which the heat l5 flOWll ig 7 l5 the temperature Before we move on to a more complex model lets begin with a conceptual model of heat transfer through soil The basic equation for calculating the amount of heat transferred is called Fourier s law or the law of heat conduction This law states the time rte of heat transfer through a material is proportional to the negative gradient in the temperature and the area Note that the k term is the conductivity of the material Fourier slaw continued When this equation is integrated with a few assumptions we get AQ AT A At A A1 where A l5 the cross sectlohal surface area ATlS the temperature dlfferehce between the ehds Ax ls the dlstahce betweeh the ehds When the above differential equation is integrated and we assume a uniform temperature across the material we get the following Where a is the cross sectional area deltat is the temperature difference between the two ends and delta x is the length between the two ends Fourier39s law continued Q UA AT TABLE 82 Thermal properties of typical sail materials MnerIl Density Speci c ennui Volumetric Mg m Hm Canaucuviiy hell caplclly JquotKquot Wm 1Kquot quotl Sm mincmls 255 7 25 amine 254 082 30 215 Qumz 256 000 32 213 Glass 1 004 00 2 23 Organic mam L30 1 92 02 WW I 00 4 056 000101 2 U 18 418 Ice 092 21 000737 222 I 01 T 193 00671 Air 101 kPa 129 000417 101 0024 000007T 13 001le X10J x 0quot Ifwe divide the materials conductivity k by the distance in the two ends we calculate the conductance value forthe material being looked at With this in mind we can further simplify Fourier s law such that the amount of heat transferred is equal to the conductance value times the area times the temperature difference between the ends The table shown here includes the thermal properties of several common soil materials Notice the changes in thermal conductivity across this list A more complex model and FOFEM FOFEM soil heating model predicts time temperature depth profiles If a duff layer is present and does not consume it uses the duff as an insulator for the soil where as consumed duff is a heat source If duff layer is not present the surface fire drives soil heating We have no looked at a basic conceptual model for heat transfer through soil However as we mentioned earlier the vaporization and condensation of soil moisture will play important roles in the transfer ofheat through a soil during a re As such more advanced models which account for the not only heat but moisture transport within quot quot 4 39 4Of quot 4 39 4 39 4 1 I n tc I J I 39 r J 1 models have been incorporated into FOFEM to predict a soil temperature pro le FOFEM predicts a time temperature and depth pro le Fofem uses either the heat generated by the burning ofduffas the main input for predicting soil heating or the energy produced by a surface re ifno duffis present Assumptions for the duff fire model Assumes that temperature gradients in the horizontal direction are small compared to those in vertical direction oThis allows us to use a onedimensional model to approximate downward heat flow Assumes a heat generated from the burning duff is transferred into the soil Uniform stand conditions Fofem has several assumptions we should talk about before we use it First lets look at the duff model in some detail Given that re spreads horizontally at rates of around 13 cm per hourwe have a very dif cult task in modeling this For starters it means that the simple one dimensional model we went over earlier needs to be expanded to a 2d model in addition the differential equations become nonlinear and are very dif cult to solve There fro we need to make some assumptions So if we assume that the temperature gradients in the horizontal direction are very small r 39 the 39 39439 39 cau39a s aone dimensional model and only look at the heat pulse going down into the soil Our next problem is calculating how much ofthe heat from the burning ofthe duffis actually g 39 g quot quot Here we can 39 4 that all ofit 100 is going into the soil So we are ignoring the idea that part ofthe heat produced by the re is being radiated and convected away from the soil In addition to all ofthis it is known that the duff layer is highly variable across a stand however quot 4 quot spatially explirit L L 39 conditions and soil and duff properties within the unit A interesting feature ofthe duff re model is that is some proportion ofthe duffis not consumed the model will account for this acting as a heat sink during predictions There for the amount of heat received by the soil accounts for both the heat generated by the burning duff and the amount of heat that is absorbed by the duffwhich does not get consumed Assumptions for the zero duff model Essentially the same assumptions Differences between the two models Relies strictly on the heat generated by the surface uels 0 Uses BURNUP to model heat generation over time for a fire There are very few differences between the zero duff model and the duff model in t at it opium e major zero duff model relies strictly on the heat generated by surface fuels to predict soil heating It uses the BURNUP model which we looked at already to estimate the amount ofheat produced by the combustion ofsurface fuels Running the soil heating model in FOFEM musty met mm m m n n w quot Strutswen gum Always imam l l H Llllev um 1m 13 3 my Hevh 5mm Fallageranch TnAcve lTan yTzn y W W W yTan J m W W 5 M m j meg z W l an W W tngaauenz W yn sn Dunnelean W x LagLaadnglsluhulmn M j m Summam 7 W a N o In p u ts Fuel loading by size class 10hr 1000hr and duff moisture Time of burn season Vegetation code Soil type Soil moisture content Locationregion of rotten logs The soil heating model in FOFEM is fairly simple to run You will be required to input the fuel loading by size class the 10 hr 1000 hr and duff moisture content as well as soil moisture content the vegetation code region rotten logs and the soil type Basically the inputs are the same as the consumption and smoke inputs with the addition of soil type and moisture content Cover Type see5m e m 21 e pm DEPCh ppeeme 2 5A e l Eelsxusl nepeh u 1 2 3 A 5 s 7 p 5 m Temp 273 215 17m 123 5 75 7m 65 55 53 5 Tune 12 13 cm 21 257 1 11 3S m m 256 255 m 255 272 277 m m 25 255 0 Results Temperature time profile by soil depth Fuel combustion Duff consumed and depth Once your inputs are entered you can run a report in FOFEM The report will give you the fuel consumption table and duff consumption tables since it is using BURNUP to calculate the amount of heat produced In addition to these tables you will also see a soil heating table This table tells you the temperature and time that different depths of soil experience during the fire In this case you can see that temperatures reached over 60 degrees at 7 cm down into the soil probably 8 would count You can also see that at no place did soil temp go above 275 degrees Running the SOII heating model In FOFEM Gml mva T 501 a l P llJ a I 25D 4 t m H D l l l x l l l l I l mmutlz lllU VUll Jilll lUll illll 600 lllll lllll iUll 39llllll Max my lilcl Post the Buff Depth 00mm Boll l lmst15l l lyl parser ilt me teptesent temperatures at 1 Penmetet mtemls startlml a stul mince Another option you have is to create a graph of your run This is the example we were just talking about notice that the point at which each depth reaches 60 degrees c the lethal temperature for most living things is outlined in red In the graph each line represents an increase in 1 cm soil depth starting atthe soil surface The nice part of these graphs are you can see howthe heat transfer model is taking place overtime Notice that each 1 cm line reaches the lethal temperature at different points along the X axis iR ti 39tlme temperature curves ti ecosfstem function 0 Soil Chemical Characteristics v c 51 Soil characlerlsllc Threshold temperature Source quotF C Organic manor 22 100 Hosking 1935 Nitrogen 4 4 200 White and others 1973 s l 707 275 Tredamarrn 1987 Phosphorus and potassium r425 774 Raison and others 1935ab Mag 2025 L107 DeBano 991 Calcium 2703 1484 Ralson and olhers 1985313 Manganese 3564 LEE Raison and others lQESab As we end begin to come to the end ofthis lecture I want to take a few minutes to talk about how to relate these soil temperature profiles back to ecosystem function and fire effects As we have all ready talked about there are many chemical characteristics of the soil which are affected by re Primarin the most important chemical properties effected are organic matter nitrogen sulfur and phosphorus As you can see from the table here many soil chemical properties such as manganese calcium and magnesium require extremely high temperatures to be effected however other properties such as nitrogen require fairly low temps Using a soil temperature profile we could estimate the depth at which particular soil properties were being effected In the example I should for example we would expect that soil nitrogen would have been effected in the rst 1 cm of soil REla 9 me temperature curves to ecosystem function 0 Soil Biology p A 199i Neary and others 1999 Biological component Temperature Reierence Pram roots Hare 1961 Small mammals 120 49 Lyon and oihers 197B 1 Protein coagu aiion 140 so Prechl and others 1973 Fungliwet sail 140 so Dunn d others i975 Seedsiwet Soil 158 70 Martin and olhers 1975 Funglww soil 76 BO Dunn and olhers i975 lVIIaso anas spp bacterlaiwet soil 76 so Dunn and DeBano 1977 Mrrasamonas spp bacteriagdry soil 94 91 Dunn and DeBano 1977 Seedsgdry soil 194 90 Martin and others 1975 VA mycorrhizae 201 94 Klopatek and others 1999 As we move on to see what kind of effects the fire might have on soil biology we notice that the temperature thresholds for living organisms are generally much ower You can see that all of the components listed in the table have thresholds less than 95 degrees In our example we have been looking at all of these components would have experienced lethal temps up to 4 cm into the soil Some components such as plant roots would have been killed up to 10cm deep into the soil 0 Soil Properties 7 L 0 4 Soil characteristic Source F c Soil weltnbiliiy 482 250 DeBnno and Kmmmes 1966 Soil structure 572 sun DeBnno i990 Calcite leimartian 572932 3007500 lglesias and others r997 Clay 9604 796 4mm 0 1990 Sand quartz 2577 m Important physical characteristics of the soil such texture mineral content structure and porosity can all be effected by fire The threshold temperatures of forwettablitity and structure are effected at relatively low temperatures while sand an c contents which influence texture are affected at much higher temperatures If we focus on soil texture here you can see that both sand and clay have high threshold temps so we would expect that these properties would not be affected except in the most extreme cases and than only for the rst few centimeters of the mineral soil In our example only soil wetability would have been affected and only in the top 1 cm ofthe soil 21 Relating time temperature curves to ecosystem function Water Repellency t Little change when heat is below 176 degrees C DeBano 1981 o Intense repellency is formed when heating is between 176204 degrees C DeBano 1981 39 Repellency is destroyed when temps are over 288 degrees C Savage 1974 DeBano 1976 As we end lwould also like to talk for a minute about the relationship between temperature and water repellency Recall that the combination ofcombustion and heat transfer lead to a large temperature gradient developing within the soil pro le Lquot of 39 quot39n 39 blcnlca 39 39 a z 1 1 4 he soil 3 r g 439 until they reach the cooler areas ofthe soil and condense These particles than coat the minerals in the soil and form a hydrophobic layer This process appears to not occur much however when temperatures are below 176 degrees c and is destroyed when heating reaches over 188 degrees c So when we have temperatures between 176 and 204 appears to be where the most intense water repellency layers are formed In our example this would occur some where around 1 cm into the soil asuuming that the organic material present is capable of producing the hydrophobic substances Concluding thoughts Time temperature curves provide an important link between soil ecosystem properties and fire However they only tell you what might be affected and not what that effect means in terms of long term vegetation or site productivity As we end this lecture lwould like to suggest that the ability to predict time temperature curves does provide a means to link re behavior to its effects on soil ecosystem function However this method only provides a mean to estimate the potential effects on the soil properties It does not give any indication on how these affects will in uence longterm vegetation responses or site productivity So we must use our understanding of plant physiology and ecosystem function to make these connections l 7 A FOR 434 Assessing Fire Effects Fire Regimes and Burn Severity Chad Hoffman and Zack Holden 4E Hi my name is Zack Holden In today s lecture I ll be talking about re severity Presentation Overview Review common attributes of fire regimes Define and discuss the terms burn severity and fire severity Learn methods for broadly describing and classifying burn severity within the context of fire regimes In this lecture we will brie y review attributes that describe res role in ecosystems or re regimes We will then focus attention on re severity or burn severity as descriptors of re regimes Finally we will learn how bum severity can be characterized both theoretically and quantitatively for different ecosystems and vegetati on types Fire itedimes o The generalized role that fire plays in an ecosystem Agee 1993 o A summary of the kind of fire history that characterized an ecosystem Heinselman 1981 iihdr Thode iihdr Thode Fire regimes provide a system or framework by which we can describe and quantify the way re burns through an ecosystem In early work on this subject Heinselman referred to re regimes as the kind of re history that characterized an ecosystem James Agee described them as the generalized role that re plays in an ecosystem A A Fire Regime Attributes 0 Temporal seasonality Fire Return Interval when how often Fire Rotation 0 Spatial Fire Exten How Lar e Spatial complexity Shapepatch size 0 Magnitude Fire Intensity How hot Fire Severity How much Burn Severity Change Sugilram et a1 2007 and Agee 1993 Fire regime descriptors can be grouped into three categories Temporal re regime attributes such as re return interval and seasonality describe when or how often an ecosystem is likely to burn Spatial aspects of re can be described by re size and by the spatial patterns or patchjness of a burn within a re Fire intensity and severity are terms that describe the magnitude of re effects within ecosystems Classification of Fire Reglmes Why We need a tool that can be used to explain t important ecological patterns of re occurrence c We need to understand which attributes of re regimes change and how biological systems are influenced Simple and understandable Condition Classes Priority Setting Slide courtesy of Andi Thode QE Why are systems of classifying fire regimes important As students of fire ecology or fire managers some aspects of fire regimes become second nature You s ou d already have encountered basic principles of fire regimes But perhaps now more than ever systems of classifying the current vs historic role that fire plays in ecosystems has become extremely important From a science perspective it is important that we understand patterns of fire in space and time From a management and policy perspective we are often tasked with identifying treatment areas determining the effectiveness of treatments or with understanding the current condition of vegetation relative to some desired condition Either way we need tools that allow us to quantify and describe characteristics of fires within some context National programs like Fire Regime Condition Class and Landfire are a testament to the importance of understanding fire in a changing world 9 re regimes 1 Using characteristics of the fire eg surface vs crown fire Iquot By the dominant or potential vegetation of an ecosystem 5 By fire severity effects on the dominant vegetation Agee 1993 Several different systems can be used to classify re regimes We can describe re in a ecosystem by the characteristics of the re as it typically burns For example surface re regimes were common in ponderosa pine forests prior to euroAmerican settlement while crown re is common in lodgepole pine and spruce r forests Fire regimes can also be classi ed by the dominant vegetation in an ecosystem Finally we can also classify re regimes by the severity or magnitude of effects on the dominant vegetation within an ecosystem What is severity39 Magnitude of Ecological Change 0 Fine Scale Effects Tree mortality Fine scale soil processes Plant species recovery Exoticinvasive species 0 Broadscale Effects Post fire erosion Fire Effects on fishwildlife Changes in plant species distribution Water quality 0 Global Fire Effects Air Quality and 5 39 gas emissions While these theoretical concepts offire regimes and fire severity may be simple to grasp conceptually severity is actually a complex aspect offire regimes with many measures and terms that are sometimes confusing In this course we will learn about the physical and ecological effects that fire can have on plants animals and ecosystems These effects occur at a range of scales At finer scales for example in prescribed fires or places of special concern within burned areas we might be concerned with preservation of large important trees or individual plant or animal species Broader scale effects include regional and landscapescale changes such as water quality and postfire erosion As we leam about burn severity and fire effects it is important to think about this idea of scale and how it relates to the processes we discuss Ecological De nitions Fire Intensity is a description of re behavior quanti ed by the temperature of and energy released by the fire Fire Swaity integrates active fire characteristics and immediate post re effects on the local environment Burn Severity incorporates both short and longterm post re effects on the local and regional environment Bum severity is defined by the degree to which an ecosystem has changed due to the re l M r w r l V CDDrdim ngGruupZOOS all Three main terms have been used in the re ecology literature to describe the physical characteristics of res andtheir ecological effects FIRE INTENSITY is a 39 39 n or ure uelmvim um uml u r the re FIRE SEVERITY has generally been used to describe active re I n MI immediate post re measures eg vegetation consumption vegetation mortality soil alteration BURN SEVERITY is a measure of ecological change caused by the re that incorporates both short and longterm post re effects Bum severity relates to the amount of time necessary to return to pre fire levels or function Bum 39 39 39 39 L accumulation 39 and recovery andinvasive species First Order vs Second order Effects First order effects Direct result of combustion process Vegetation mortality Fuel consumption Smoke production Second order effects Indirect effects of fire and interactions with postfire environment Postfire erosion vegetation recovery 1n the re behavior and fire modeling communities the terms rst order and second order fire effects are o en used First order re effects typically refers to direct or immediate re effects on the environment for example imme 39ate vegetation mortality fuel consumption and smoke production These effects are generally a direct result of the combustion process Second order re effects result om the indirect effects of fire and interactions with the post re environment Some second order re effects include post re erosion vegetation recovery and succession Fire Intensity FIre Seventy and Burn Seventy These terms can be thought to exist on a temporal continuum DeBano et al 1998 Jain et al 2004 The Fire Disturbance Continuum n Flle D39su mm Comimum mum um um mpnmms new In timing in i PostFive Elwimnmlml Emimnmzmal Bum setuin The hinlagical and Emimnmeuml chanmer39mics be1umdla m characteristics duringualim Envimnmznal mncwk cs physical response aim the lire m the unimnmem File inmls39lq m diamaluislics Eurn Betain Seomdnrder tire mm What is Iell Flre smmy 1mm emu Imm mm lion plums Firstalder m directs 4E Fire intensity Fire severity and burn severity occur on a temporal continuum It is quite intuitive that re severity the heat and energy produced by a re will be related to the resulting re or burn severity The lack of precision in these terms has caused some confusion and misuse of these terms Also some confusion has appeared in the understanding of rst and second order effects in the fire behavior and modeling literature They imply degrees Within a single effect or process rather than effects at different temporal locations Let s look more closely at the word Severity Severe Of a great degree or undesirableharmful extent Websters Dictionary I Value Laden Tenn I Negative Connotations I Public amp Policy Mscomrnunication What is a severe re A more accurate and precise way of describing severity is to think in terms of postfire ecological e ects Conard e a 2002 Key and Benson 2002 Kaalschke and Bruhwller 2003 Ketterings and Blgham 2000 Laes e a 2 landmaan 2003 Lemme el al ln review Lewis 9 a o Patterson and Yool1998MlHerandYool 2002 5mm and Hudak 2005 White 9 a 1996 Zhang 9 a 2003 We generally de ne re severity as the magnitude of ecological change caused by a re However use of the term severity is problematic When we contrast our general de nition of re severity with de nitions of the word severe we see why Websters new English dictionary de nes severity as the state of being severe and severe as of a great degree or harmful extent This is a valueladen term with inherently negative connotations As an example contrast a stand replacing wildi re like the 1988 Yellowstone res with recent large severe wild res in the Southwest for example the Hayman or Cerro Grande Fires While the effects of the yellowstone res were considered severe in terms of vegetation mortality they were also natural in the sense that such res have occurred in the past in these vegetation types every few hundred years In contrast the Hayrnan and Cerro Grande res were also severe in terms of vegetation mortality However such res were uncommon during the last 500 years Much of re science and management gets translated into politics and policy Therefore we must think carefully about what the term severity means and how we apply it Perhaps the best way to avoid rniscomrnunication is to be precise in our description of what we mean by severe To compound this there are environments where one can have High of FS and low How do we measure severity as a component of fire regimes o Severity Distribution The distribution of burn severity within a vegetation type 0 Spatial Complexity The spatial arrangement of burn severity within a vegetation type Spatial complexity ngn mum Pmpn lan a lumen m We have now reviewed some basic aspects of re regimes and discussed what the terms re severity and bum severity can mean But how do we measure severity as a component of re regimes Similarly how might we describe the spatial burn severity patterns within a burned area This gure shows the theoretical distribution of severe re by re severity type Clearly how much of an area burns severely is related vegetation type How can we quantify and measure severity Distributions A quick review 0 Mean What is the most Wm common value on average 0 Spread How much variability is there Many ofthe aspects of re regimes mentioned previously are generally described in terms of statistical distributions For example when we describe how often fires occur we may refer to the Mean fire return interval or the average number of years between res Here as with most measurements there is uncertainty or vari ability Therefore when quot 39 muueuicall f quot quot 39 probability distributions We will brie y review common features of probability distributions This is likely review for most students The goal of this review review istomake quot 39 quot 39 4 understand the importance of distributions as ways of visualizing and interpreting data As an example let s say I randomly selected 50 people in the United States and measured their heights Ifwe counted up the number of people at each each height and plotted those heights we might see something like this The average quot 39 39L Amalie 39 39 sures tha reel u u even Microsoft Excel will give you simple mea t describe this distribution 39quot 39 rthe most common quot measures of spread or variability like standard error or standard deviation nd More Distributions h skewed Shape u Are the data normal H skewed Bimodal i Aug usHagis quot i quot Btmodal t g 3 mm The overall shape ofhow data are distributed is also important Data are o en normally distributed which means that the spread aroundthe mean is approximately the same on both sides However in ecology we o en see data that are non normally distributed Sometimes data are skewed whose data are not well centered around some average value Sometimes have two distinct average values These are distributions are called bimodal 0 Sample points or cells within a fire Assign each cell a value based on some measure of burn severity Describe the overall severity of the fire based on it s distributional statistics quotif What if we wanted to know how some measure of severity was distributed across a re We commonly describe res as severe or moderately severe But what does that mean Is that an entirely subjective term or could we actually measure the severity of the entire re We can quantify some aspects of a res severity in the same way that we might describe the distribution of peoples heights Picture a grid of cells hovering above an area that is recently burned with each cell corresponding to an equal sized area on the ground In theory we could visit each of these cells measure some attribute of severity for example overstory vegetation mortality and then calculate summary statistics for each cell over the entire re Satellite imagery and Burn Severity Landsat TM False Color NIR MODIS NDVI 30 meter pixel size 250 meter pixel size g In reality this is often impractical given the size of many f1res but we can do this with satellite imagery Below are two images from different satellite sensors covering the same fire In the coarseresolution MODIS image individual pixels are easily visible Remote sensing techniques have been developed to infer the amount of fire caused change at each pixel Using distributions of different severity levels for all the pixels covering a burned area we can quantify the overall severity distribution for the entire f1re There are 2 important differences between this approach and our example of US heights First with remotely sensed imagery rather than selecting a subset of pixels at random we have a measurement at each pixel This abundance of data is one of the strengths of of remote sensing Second measurements we make using remotely sensed data are spatial The distances between and among pixels are known Thus we can ask questions about the patterns of severity within a fire Spatial Complexity What is the relative distribution of severity types within a fire ammonium Is a fire homogeneous eg mostly surface fire or mainly stand replacing How are severely burned patches distributed Small well distributed Patches Clustered patches A few large patches Pmpm hn a lumen Alba 1 5pm Bum i1th Another aspect of fire severity that we can quantify using this approach is spatial complexity Until recently this idea has been mainly theoretical and based on the idea that fires within vegetation types should exhibit some characteristic patterns of burn severity Using satellite data we can look at the occurrence of burn patches and answer questions about the spatial distrubution of those patches For example we might be interested in whether severely burned patches are becoming larger or how patch size varies with weather patterns Or we may simply want to monitor and understand characteristics of fires within an area that we manage Landscape metrics of spatial complexity o FRAGSTATS McGarigal and Marks 2002 Eff ib 5 Mean patch size 0 Edge to area ratio r o Contagion o Interspersion a E A variety of metrics are available for quantifying and describing patterns of spatial complexity For example using a computer and a Geographic information system we could fairly easily measure the average size and perimeter of severely burned patches on a re then calculate the average patch size or the ratio of the area within those patches to the length of their edges Contagion refers to the tendency of patch types to be spatially aggregated that is to occur in large aggregated or contagious distributions It is beyond the scope of this course to describe these in detail However FRAG STATS is a free and relatively simple software program that can be used to calcuate spatial complexity metrics on a variety of data Frequently burned reference39 SW ponderosa pine Fire dates 1909 1913 1949 1993 2003 Mesic DFPI P foret I L 1993 Brush Straw Fire Gila NF 9 I000 I500 2000 1500 I I I 500 I I I I I I 71500 71000 7500 0 500 I000 Holden unpublished data We Will now look at some actual severity distributions for several mesic ponderosa pine forests in the GilaNF New Mexico The red line in these figures denotes the threshold Where 75 or more of the aboveground vegetation was removed by the fire This data comes from a 1 year postfire landsat satellite image of the BrushstraW fire that burned in the Gila Wilderness in 1993 This site has a well documented fire history With fires that occurred midcentury prior to the occurrence of this re The stand structure of this site is likely similar to historical ponderosa pine forests With large open trees and a lush understory You ll notice in the severity distribution that very little of this fire is severe i SW ponderosa pine burned during WFU era Fire dates 1979 1985 1993 1993 Iron Fire Gila NF In His Ruluml Snmly I Iixh mllnn mmm rvn mm m r l mu m u 11 mm mm Holden unpublished data This area also in the Gila Wilderness burned in the 1993 Iron Fire Although this area had burned several time in the last 2 decades the stand structure in this area is high relative to areas that burned in the middle part of the 20 11 century You ll notice that a larger portion of this re burned as a severe re 20 Stand Structu Open re Fire Occurrence Frequent Fire lt1 severe Unburned 6 severe Holden unpublished data Dense 16 severe W M We can compare the severity distributions of these two res with other ponderosa pine forests in the GilaWildemess that experienced long periods of suppression uring this century It is interesting to note observe the in uence that prior res and stand structure have had on the resulting severity distributions of these res While severity distributions are all normally distributed they each have different mean severity values with the proportion of the re that burned severely increasing with decreasing re frequency These gures should give you a sense of how we can use quantitative measures of burn severity to understand re regimes in this and other vegetation types


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