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FIRE SUPPRESSTON EFFECTS O}i FUELS AND SUCCESSION IN SHORT-FIRE_INTERVAL i\'ILDERNESS ECOSYSTEUS
Jan I,J. van I'lagtendonk
ABSTRACT: Fire is a dominant force in short-fire-
interval wilderness ecosystems. A conputer sirnula-
tion model of these ecosystems was developed that
combines vegetat'ion, fueI, rvcather, and Lightning
to simulate fires that then inleract nith vegeta-
tion and fue1. The nodel predicts the effects of
no-fire, lightning-fi.re, and suppression scenarios
on iuel energy, ba.sa1 area, and density b1, species.
For Sierra Nevada mixed conifer ecosystems, the no-
fire scenario a1lows fuels to accumulate and white
fir to replace ponderosa pine. Lightning fjres
keep fuel 1eve1s loro and favor ponderosa pine. The
model can be used to design prescrihed fire programs
co reintroduce fire into i\rilderness ecosystems and
to understand the role of fire in those ecosystems.
INTRODUCTION
The concept of a wilderness ecosystem includes the
effects of natural processes. In fact, the hrilder-
ness Act specifically deflnes rvilderness as an areEl
that I'generally appears to have been affected pri-
marJly bl the forces of nature." Certainly, fire
is one of those forces.
When r,/llderness areas were first esLablished, the
concept of suppressing all fire was still prevalent.
Not until 1972, in the Selway-Bitterroot tr'lilderness,
however, \,ias a lightning fire allowed to run its
course within a prescribed management zone in r^ril-
derness (Muteh L974). Previous to that, lightning
fires rorere allowed to burn under prescribed condi-
tions in backcountry areas of Everglades, Yosemite,
and Sequoia and Kings Canyon National Parks and in
Saguaro \tational Monument (Kilgore 1983). The
rationale for establishing those programs v/as that
fire had hcen n n:ri nf cach ecosvsfem for eons
and that its exclusion had led to unnaturally high
fuel accumulations and shifts in plant succession,
Research studies had shown that this rlias partic-
ularly true in ecosystems that had evolved vtith
frequent 1ow-lntensity fires such as ponderosa
pine (Ptnus pande:r"oso,) and giant sequoia-mixed con-
ifer forests (Weaver 1959; Cooper 1960; llartesvelt
I964; Biswell 1S67), Although these and subsequent
studies documented the effects of fire suppression
on fuels and succession and described the processes
that led to the altered condltions, few were able
to relate fire frequency and intensiEy directly to
long-term ecological changes (Kilgore 1981).
Paper presented at the I{ilderness Fire Symposium,
Missoula, Mont., November 15-18, 1983.
Jan i]. van Wagtendonk is Research Scientist, U.S.
Department of the Tnterior, National Park Service,
Yosemite National Park, E1 Portal, Ca1if,
Tr,ro studies have attenpted to define this relation-
sirip. In the first study (van lJagtendonk 1972) I
used a computer model called FYRCYCL to simulate
fuel accumulations, lightning fires, and subseqrrent
fuel reductions. Bonnicksen and Stone (I982) de-
ve.loped a strucLural mode.l that predicts age, number
nf rrprtical lrvprq- end qnpcieq enmnnsiiiOn of tree
aggregatlons, A major shorEconing of ny model
(1972) was that it did not include a vegetation
subroutine. Consequently, the effects of fire on
succession and on subsequent fuel accumulation were
not consldered. On the other hand, the Bonnicksen
and Stone (L9BZ) model did not produce fire fre-
quencies and intensities,
For land managers to reintroduce fire into vilder-
ness ecosystems, it will be necessary to know what
rhe nni-rrra i f i 1. e resime is and r.rhat its ef f ects are
on fuel accumulatjons, stand structure' and species
composition, 0n11' then can we begin tr: use fire
as a tool to simulate fire in its natural role'
SHORT*FIRE-INTERVAL ECOSYSTEMS
The role of fire i.n ponderosa pine ecosystens has
been described by Kilgore (1981)' The process
sLarts rrith the germination of seeds in openings
created by the death of overstorv trees by
insecEs, disease, lightning, windthrow, or an
occaslonal crown fire. The seeds come from trees
adjoining the opening and germinate on an ash
seedbed prepared by the fires that burned the
dead trees. The small accurnulations of needles
underneath the young pines do not carry a fire and
thus protect them until they are able to survive.
Subsequent fires remove any sma11 trees underneath
the large Lrees. In such ecosystems' flre
suppression a11ows fuels to aecumulate and smal1
trees to increase in the understory until a fire
exceeding the suppression capability occurs and
the entlre stand burns.
The process in mixed conifer ecosystems is simllar
except that additional species are present. In
these forests an understory of shade-tolerant
species develops in the absence of fire, These
species include \nhite fir (Abdes eoncoLor") and
blue spruce (Picea glcLu.ca) in the Southrvest, white
fir and lncense-cedar (I'iboceclz'us d'ecuz't'ens) in
California, and grand ti-r (Ab{es grlndi.s) in the
T,ntermountain West, Douglas-fi-r (Pseudotsuga
menz,ies';i) is an overstory associate of DonCerosa
pine throughout the type except in.the southern
'Siurtu Nevada, where sugar p:rne (Pinus Lonbettiarca)
becomes more common and u'here oecasional groves of
giant sequoias (Sequ-oiadend.ron gLganteurn) occur'
119
The f iT'e nroctsss ir mived cnr'i r.. pcn.\/c tems is
simi l,rr to thar in ponderosa pine s),stem.s (Kiigore
l981). Periodic fires eliminate most of the shade-
tolerant understorv that develops betr.reen fir:es
r^.,^-j-^ -L^ -^-- .;te_i-nlFr4nf rinec- LOCaIldvvlr|l5Plj'c:.
variations in fi re intensiry create opcnings in
the forest, irhich i'rould become regenerated with
rl1 pvti lnhle snpe ins Fycprlf rh :t c'rr 'va-1 t:if ies
rmnnoqr qnaniaq r.rith rha:lri'l itv nf anel, spec'les
to grow under va!"ious Levels 1l^ c1'r; I jght, litLcr
depth, antl fire 'intensi r1', [oi inqtance, g ianL
qpnrrrria spcdlinrc recli*e -'inernl snil fot
germination, a condition that r,rould on1-y occur
rgirh a loca11y intense fire.
The effects of fire suppression:irr mixed conifer
forests have been ar'! increase in fuel accuinulation
and a shift in conposition toward shade*tolerant
species, Thesc cltanges have itrcreased che poLen-
tial fnr e hioh-.inte--ir,.,,-^,.,- .ly^ na1- 6nl1z la
nrovidins more avail^Lt- ^------ L"+ ^r"'bv ('reac-
ing pathways for flames tc reach the overslory
eeronieq. Srreh nrown fireq rrcrrrl lv cxeegd tlte
eanar.i rv oF slnnt-e"sion forces.
MODELING SHORT-FIRE-INTIIRVAL ECOSYSTE}'S
Tho nrrocfinnc nf fir^ €y^ai,^---, ^-,1 inra*^r
. - --c rIc(luellurv dlr.u rliLcllslL.)/ dlc
basic to understanding fire's role in wilderness
ecosystems wilh short flre intervals. Computer
nodeling is one tool that can be used to answer
f hnse d1'eqr'iers ps ruc Il as p:i vc insight :ilttJ the
o*'- -
behavior of the systen. Such a model should use
inrlerrcndent innrrf-q r'- -^^^-'-' :! -" rrclirde the
r rluuPL 'ruL.-a t.,r,ur r eu 6srrcr
effects of fires on fuel and !egetation, and
provide data on Lhe fire regime, iuel accumulat.Lons,
and stand structure and composition. In addition,
the rnodel should be able to shov the effects of
varioris rTlanagemenr srrategies. Fcr instance, the
results fron a no-f1re scenario must be compared
tn reqr'liq frnm qrrnnreqqinn end liqhtnirrq--firo
scenarios. Agee (1973) felt that the FYRCYCL
*^r^1 .-- r^11v rnst adantairle and could
PULsrrLt(lrrJ'i.u!1r- u\.uyLsurL (rrr\,
-*..'ii^ +L- L^^"^ t^r An imoroved fire nodel in
rnixed conifer ecosystems.
The orlginal FYICYCL model lncluded subsystems thac
accumulated an annual fuei increment and decomposed
frrel at a given l-ate. A jightning srrbsvstem pro-
drrccd th'rndtrrqtnrrc - I i slltr i ro stri kes. and strike
locatlons. Air teTrper-ature! relative humidity,
.l 0-hotrr time lag f uel nioisture, and w Lndspeed r,.-ere
generated by a weather subsvstem. The iirc sub-
svsfon comhineri nlrfnlts'ror ni-hor srlhc',Stenq to
nrndr:ee nr rnf rrndr,ne r fire nf r oirren inJ prrcil\r
that then reduced fuels. The model has been rnodi*
f i ed to i nc lrrde \/egetat ion gror.'ih and riurta i itv
subsystens for a mixed conifer ecosvsten. The
spcctes includcd in tirosr' suirsvstems are porrcierose
pine, sugar pine, i,'hite fir, aird incense-cedar.
Fisrrre I denicts the interactions of the various
subsystems. The model starts with an input of
seedlings to the vcgcracion grov,ch subroutine" As
the trees gror.r, fueL begi ns to accumulatc. Sonte
mortal i ty also occLrrs as r]'ees heg:n to compete
IEGE
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WEATHER LIGHTNING
FUEL
ACCUMULATION
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Fi.gl1re 1 " --Ma j or subsys tems o r cire FYRCYCI- mode I .
SlXn jndicaces the nature of the relat ionship
L^-"-^^-,-..L-",^+^-- buurysLcruo.
t"'ith each other for Ij.ght, moisture, aird space.
Increased fuel accumulation incteases the energy
avallabie for a f ire and the elir.ount of fuel
avpi lahle f n. decom6n<itinn- lleen f rrpls alSO
ilnraaco m^?t'iitv hrr inhihitino ceoJi ir
-^---'- - ' i ^- --r ^-^-'th. The simultaneousarru 5!u\a
occurrence of farrorable rn'eather, a lightning
..-..ir.- _-J -r^-..^-t frrel penerates n fife that
>L!rr\sr drru au!-quc"
reduces fuels and increases tree mortality.
Iinal 1y, increaseC mortal i ty decreases grovtlr,
Vegetation GroroLh
The vegetation gro\fth subsystem calculates new
basal areas and densities for each specles and
rL ^ -..1- .r'rnrrrq are f he 1-ntr1- number ofdBc, rrrs ruurlrLrLrL !..yu-
nor.r caa.l 1inoc rha h^^-1 --^- ^f - -i-^1o eparlIino
'rr6ru r!Lvr rr,b
^t -^^L --^^i^^ ^-l the nronnrrion nf fhe total
uI edLrL sPcL f,tr, drrL L'rg
basal area atrributed to each species. Basal
ar-eas were determined fron field studies in
Yosemite lhat::elated height to age and to
diarneter at breasL heigirt. After the initlal
rh^ -',-l'av ^t:,'-yeoq nf oach roe rnri qnocie<
Parn ' L'rc
'i s spf errra l tc f he nrrmbe* nrpspnf Af lhe end of
rho nrorri ^r1c \7arr \r^!., +y^^- - F- ^^,\^yrro.l h\Z
L"c Prc!
--..',,r..- L^-^t --^^ npT.enfpges hv sneci-eS ffOm
yL. uLrr L uSLJ
che pl'evious year to the constanE seed'ing input.
Fuel. AccumulaLion And Decomposition
Each year a ne\'J laver of fuel is deposited on che
forest floor in the fonn of needles and woody
branches. The amount of each yearrs increment
dpnenrts nn iho fi3ss1 area nf each qnecies and was
determined from field studies in Yosemite National
Park. Heat yield values from Agee and others
(1978) rrrere used to derir.'e the annual accumulation
of fuel energv,
LZ{)
Ih6.la^^mn^cjfi^,1 -,.utines are iienLj-ca1 to those
in van Iiagtendonk (197?), r.rhi,ch r.rere based on earl-
ier r'iork 1.v Jenny and oLhers (L9&9). Cutputs f ron
this subsystem are Lhe total- amount of fuel energy
nn fhp qrnr:nd et tlle l)epinnins of the vear and the
depth of Ehat fr"rel . Regressior equations '.evel opeci
by Agee (1973) r,rere used Lo deterrnine fuel riepth.
Lightnr'-ng
Tho rri.mher of I irl.i-rr iro ct- jlr c '.ar no,.rh ricA caL-
culated fro:n thunderstorm actlviiv 1eve1s using a
Poisscn distribution. Because not all lighl-ning
strilces are Dotential f.ire sterEers, the total,
number of strikes r,'as multrpLied by 0.25 lc reflect
the number: that actt1a11y ignite ilres (Arilold
1964). The location of the lightning strjke rela-
Live to the area of concern determines the spread
direction. Data f rorn Kornare.k { i967) r\,ere used to
delermine the probability of a strike hitting a
ridgetop ol the uppea, middle, or lotrer third of
the s1ope.
I{e aLher
Hull and others (1966) evaluated critjcal fire
ueefher n, rrnrns assnei afcd rri fh svnnnt ic weattter
types, These data, whlch includeri data fr:om a
stai j,on in the Sierra Nevada, \,Jel:e used tc deter-
mine the probab,lity of a r,'eather type in a given
rnonth, For eacb tnonth and r,iealher type, rninitrun,
ma>limurn, {uanti1e, and mean values r+ere listecl for
air tcmperature. rcl.at j' e hurrid i i-;', i0-hour rime Lag
fuel moisLur:e, and r+lndspeed, These velues \tere
useC lo construct cumulative frequency tables based
on a normal distribuclon. Speciflc values for Lhe
four \reather variables make up ahe output from this
subs_vste;n.
Fire
Lrhen a I !shhnirrs str.ike occurs, the fire subsystem
t- ^^11-; rn it inclrrde qn-e"d direcfion,
uL JH- u"u
i^r-1 t,,^1 -rd r,reather variable values.
Based on daLa from van Iiagtendonk (1972) and
Rothermel and Anderson (1966) rate of spread, fire
ljne incensity, heat per rrnit arca, and flar'e length
are calculated as funclions of the j,nput variabl.es.
Fires that burned with intensities less than i00
Btu/f t1s r+ere c.l.assif ied as surf ace f ires. For more
int.trnqF iircs- onpr-t,- ^r-;' 'e .'^^4 tO detef-
!rlLrdY LI LLrr I
mine lf the fire rernained on the surface and burned
under'story [ucls or if ii reachet] crowtt firc potcn-
tial. That point is recognized uhen lhe energy
^nnay.id.l rr-. *ha .irn ar^oa/c fha onnroV in fhe rrind
envj.ronrnenl (Davis 1959) "
luel Reductlon
fucl recluction is calculatcd by srrbtracting rhe heat
per unit area from the total fuel energ-v per unit
area. Ior understory fires, 75 perceni of tlie sur-
face fuels rcere said to be consumeci, r"hereas cro\tn
fires burned all surface fuels.
\a,--.^!^+l ^- r^t,--!^1 i F-,
\ -EsL-rLruL,
Eour nortalit_y factors are considered in this sr.rb-
sl/sten" The first is nortalitl' causeci by the
fire. In a 1983 study, I related this facror to
ilama lensth jn under:slory trees less that 20 ft
(:6 m) hlgh (van Lragtendonk l983), The equations
l derir,ed vpre caoable of rredicf inc fl'p tree
hoiolrf f hrf Fnrrld ernpfli en.e 50 nercenr rrortr'l irv
,rur6 rL ^ rr^-^ '^-^th for each of the four rnixed
g,IVeIr LlrE lrdlllu rc11ts
conife:: species. Fot all trees, mortaliLy w-as 100
nnr.trrl ir 11'p ccorrl. heisrr as crlcrrlafei br. \ran,..-.o,.'
T,'aonnr f1q71) ovcccricd flro tlop hpiohi-
\ | -'l // v?.
\irrrrelitrr ne,rcnr"l hv chrda.rnd drrff rlnrrrh mnrtnlitv
r,,iere deterinined from data on natural regeneration
a Ff er I oqsirp in the Sie:rra r-evatla (Stark i965) ,
"- -" '_ -
Duff depth iaas obtained from the fuel accumulation
subroutine, and shade 'u;as d::ived f ron total basal
area anci t1.re percentage of snal.1-crowned trees
(lrtellner 1948),
]1or:cal ity orher than thac caused by l"ire, shade,
nr drrf f dpnf h r.zas ter:ned normal inortalit\.', Tt r.tas
cal.culated from data collected in the fte.l-d and
from numerous sources in the lite::aiure lhat
reLateC number of trees to height, Equations
.lp.,n I nrerl 1-rnr -hcse rlri-r n.e rl i e r rl,a l.fmal
nprcertnee redlrction in numbers cf treeg from year
_*o- _
to year,
;\li of those factors riere applieci to the tree
n' rrro-q oenerared bv rhp l,eunraiinn r'ot'th suL'-
c"ertrr fo nrnrri,le nc--r'--'1 ^-^^ -^*^^'rt basai
^-j i^--ir,, L.
dr'ea ) Jl.u Llu.i5l L-\ uY SpeCIeS .
Suppression Capabilitl'
At the beginner-rg of each rttn it is possible to
snoeifl ilre srrnn.esci-* ^--^r'j ri!'- r- "rrms of che
rFLL|r LdP<'ur rrL,\
:intensi.ty the suppression force could contain.
Setf, jng the capabilit-v at zero r,roul d produce the
li.hfnino fire leqinre wirhorrt q1r)nrpssiorr- r.'hereps
a high capabllity (i00,000 ?'tu/i.t/s) rorould pr:oduce
resrilts for a system without fire, Fire sup-
pression scenarios can sct the capabilitv a! anY
1evel betveen these extremes, depenciing on the
crrnnreqc'nn {o-ce atail aL .: ,
Prescribed Burning
Tlre nodei also has the capabilit;, of r-unning
r.arious prescr:ihed burrr.i ng scer:arios. For
instance, it is possible to speciFv the number of
years from the beginning of Lhe run to the start
of a prescribcd hurning progrdm, This featurc
r,orrld model thc initiacirt, nf presct-ibcC'rupn;pg
after a specific perlod of successful suppression.
Otirer options include speciffing t.he nunber vears
between fires, the brLrning directi.on, the months
rlrrrino ','h ieh rrcscriherl hrrln jrro uor,ld lre lccom-
'''b "'' _ "'
plished, and a desired ievel of fuel energy accu-
mulation indicating tlre point vhen the prescribed
burning pr0gran vould end.
l2l
SIIruLATION RESULTS
Initial nodel runs tested the validitv of the model
and input data. Historical fire records and field
data rsere compared to model results to determine
their reasonableness. This process often 1ed to
closer investigation of the nodel to find sources
of error or erroneous assumptions. After testing
was completed, repeated runs liere made to incorp-
orale random variation. AI1 runs had identical
initial conditions and ran for 200 vears.
The first scenario simulated a no-fire situation,
From these runs it was possible to shor+.the effects
of having al1 fires eliminated from the ecosystem,
A I i qhtn'l ns-f i re resine ltaS simulated l*'ith the
second scenario. The third scenario assumed a
suppression capacity of up !o 1,000 Btu/ft/s, a
1eve1 considered by Roussopolous and Johnson (1975)
to be at the llmits of control. Fina11y, a scen-
ario was run that simulated prescribed burning
after a 94-year period of successful fire sup-
pression, Results from Lhese scenarios are
d i scrrssed aq t.hev a f fpei fi re hehnrr i nr - fuel
accumulation, "nd vegetaEion succession,
Fire Behavior
The mean fire interval for lightning fires r.ras
8.9 years, wlth surface fires occurring every
10.2 years and understory fires everlz 50.3 years,
This interval corresponds closely with the 9.Z-year
interval for southwest-facing slopes of a mixed-
conifer forest in Kings Canyon National ?ark
(Kilgore and Taylor 1979) and the 8- to lO-year
interval for the central Sierra Nevada (Wagener
i961), The first flre did not occur until after
34 years.
Table I shows values for intensity, rate of
spread, heat per unit of area, and flarne length
fhat occurred for 22 fires from a typical run.
Fire line intenslties averaged 91.8 Btu/ft/s;
backing fires averaged 23.6 Btulf.t/s and head
fJrec - 160- I Btrr lfr /s. The most intense fj-re
(177,1 Btu/ftls) burned during Ju1y.
Only two fires occurred during the suppression
scenario. Both were cror{ming head fires burning
in June and Ju1y. The first one burned after 135
years of successful suppression efforts. It had
an intensity of 1,609.3 Btu/ftls wlth corresponding
flarne length at 13.4 ft, Its race of spread was
2.0 ftlmin, and it burned 14,538.8 Btu/f.tz of fue1.
The second fire was less intense at I,240.6 Btu/ft/s
but spread at 2,2 ft/min. The flame lengrh was
i1.9 ft and the heat per uni! was 10,174.0 Btulft2.
Fuel Effects
The accumulatlons of fuel under the no-fire,
lightning-fire, and suppression scenarios are
shor,m in figure 2. In each scenario, fuels star!
to build up slowly until the basal area is
sufficient tc produce significant anounts of fue1.
tr{ithout fires the accumulation increases to a
maximum of 13,000 Btu/fEz at lL4 years. After
that point fuel decreases because the basal area
of the more prolific fuel-producing pines has
started to decrease ro'hi1e white fir basal area has
been rising. DecomposiEion exceeds the reduced
accumulation but would reach an equilibrium after
several nore years. The average accumulation
without f ire r,ras 9 ,511 Btu/f t 4.
5
o80 00 r?0 r40 160 r80 ?oo
YEARS
Figure 2.--Total fuel energy accumulation under
no-fire, lightning-fire, and suppression scenarios
for 200-years runs of the FYRCYCL modef.
Table l. --lire behavior
fires during afor 22 simulated lightning
200-year run
Yoer Tf,f onci i\7 Flame
Heat/ area length
Rate of
^--^^l
34
4l
47
52
59
65
72
82
BB
91
100
111
Ll6
t33
144
i53
162
t67
t75
lBl
r93
198
Ft
2.4
1.8
7.r
2.4
3.0
10
?q
?.0
9.6
7.6
10
10
I.B
10
3.8
2.0
'1 0
2.r
2.0
Btulft/s
24 .3
2r .6
29 .6
39.2
63.3
35. 9
2r.8
57 .6
25.4
777.1
47r.5
58.5
84. r
22.4
')) )
22,2
42.2
L02. I
24 .7
,? R
29,2
') /, "\
Ft /min
0.6
.5
.B
1.1
?c
.B
.5
3.6
7.4
6.9
3.6
4.4
{
.4
,4
.8
4.8
q
A
t
Btn/ ftz
2 ,602.6
2,431 .5
2,275.1
2,063,4
1 ,000. s
2,720.0
2,422.6
954 .7
2,965.9
6,341.0
4,090,8
962.3
1,153.0
2 ,449 ,7
2,889 ,2
3,042.0
3,202, B
|,269.6
2,930,7
2 ,495 .2
3,263.2
2,592.6
('
z-
i!F
L^
3o
F-
o
F
SUPPRESSION
LIGHTNING FIRES
122
Fue1s continued !o build up under the lightning-
fire scenario until the first flre occurred during
the 34th vear. Until that time insufficient fuel
had accumulated to sustain a fire in given rveather
and lightning pr:obabllities,
Qrrhconrrant fila.. L6^t the aCcumulation dorrn to an
average of. 2,495 Bt:u/ftz. The lowest 1evel reached
r,'as after the 52d year i+hen a fire reduced a 4-vear:
accumulation dor.rn ro 849 Btu/fx2. The maxjnum
accumulation r..'as in vear 193 aftet a fire-free
intcrval of J I years. A lthough rl)ere \,.'ere J onger
illtervals, b1' this time the stand rvas atrnost pure
ponderosa pine near iLs maximum basal area.
The fuel accumulation for the suppression scenario
followed the no-fire rate until the firsc crorvn
flre reduced it to zero. The subsequent buildup
\^ras more rapid, however, because the surviving
proportion of ponderosa pines was greaCer than it
had been under initial conditions. The second
crorvn fire also reduced fuels to zero.
Vegetation Effects
The effects of the tirree scenarios on basal area
percentage and density are shor,rn for each species
in flgures 3 and 4. Tnitially, ponderosa pine is
tcoi-rn-Tl
.^ NO FIRES
able to increase its proportion of the basal area
because it gror,rs f aster anc is abl e Eo surr.,ive
be-st in open conditions vith shallor,r litter. As
the stand becomes denser and white fir pro1iferates
and grows, a shift in basal area percentage occurs.
In the I55th 1'ear, r+hite fir finally overtakes
ponderosa pine. Sugar pine and incense-cedar
renain minor participants in the shlft because they
are inLermediate in their shade Lolerance (Baker
1949), The density distribution \,'irhour iire
follows the same pattern. The apparent aberrations
betr.reen vears 107 and I27 are caused bv changes in
the shade and litter rnortality factors that are
near boundary values for those factors.
The lightning-fire scenario increases the basal
area percentage for ponderosa pine at the expense
of white fir, Sma11 fluccuations occur as the
fires e1iminale trees. The density plot dramati-
cally sho\*'s the effecLs of fire on each species.
Because of its initial survival and groi+th advan-
lage and its subsequenE higher fire tolerance,
ponderosa plne is able to domlnate the ecosvscem.
The Ewo crown fires from the suppresslon scenario
reduce basal area and density to nearly zero, A
fer'r individuals of each species survive, but pon-
derosa pine survivors are the largest and most
numerous.
20oor SUPPRESSION
lr,l
(J
trl
lrl
UJ
F
>
L
z
lrl
o
;e
<
ir,
tr
J
o
SUPPRESSION
r 20 40 60 80 roo r20 r40 r50 lao 200
YEARS
Figure 3.--Percent basal area effecls under no-
fire, lightning-fire, and suppression scenarios
for 200-year runs of the FYRCYCL mode1.
I5OOF
roootr
| 20 40 60 80 tOO 120 t40 160 t80 200
YEARS
Figure 4.--DensiEy effects under no-fire, lightning-
fire, and suppression scenarios for 200-vear runs of
the FYRCYCL modeI.
LIGHTNING
'.:.7,,);;t.yrn
t23
Effects 0f Prescribed Fires
Prescribed burns were simulated to reduce fuel
accumulations resulting from suppression. The
burning program r.ras initiated after 94 years of
suppression to indicate r,rhat might happen if
suppression efforts had been in effecc since 1890.
Burn.ing vras done every B years until the fuel
accumulation ruas red.ucecl to 3,500 Btu/ft2. Strip
head fir-es r,Jere prescribed unless the estimated
intensity exceeded l2O Btvlftls when backing fires
r+ere used. Burning \ras !o be done under the first
seE of favorable weather conditions during the
months of Apri1, l,{ay, September, or October.
Fottr n-escrihed hr'rns \,,FTF redrr ired n' er a nerinrl
of 27 years to bring the fuel accumulation dorvn co
the desired 1eve1, T1-re first two r.Iere head fires
fhat hrrrned drrrino (ontamhor fh6 thr'r,l d k.^L{--
udL^rtlx
flre during October, and Lhe last an April head
flre, The intensiries ranged from 47,1 Btu/ft/s
for the October fire to 1i7.1 Btu/ftls for the
April fire. Rates of spread ranged from 0,5
ft/nin to 5.2 ft/min, and flame lengths were 2.5
ft and 4,0 ft for the same tr{o fires,
The Iirst lighting fire occurred during the 1 l25th
year. Subsequent fires had a mean fire interval of
5.9 years. The rnost intense fire ttas 7l,q
Btu/ft/s and burned 24 vears after orescribed
burnlng ended.
The effects of the prescribed fire scenario on
fue1s, basal area perceutage, and densitl' are
shor,'n in f igure 5. The fuel builds ttp to 12,247
Btu/ft2, and che four prescribed burns reduce it
to 3,477 Btu/1t2, Atrer rhat lightning fires keep
the fuel down to an average of 2,687 Btu/ftz,
The basal area percentage graph shoru's ponderosa
pine increasing until the TBth year, r,'hen r.rhite
fir starts to exert its influence. The prescribed
fires reinstate ponderosa pine, and it continues
lo lncrease its percentage ihrough the prescribed
:nd I iohtnino f iro r
- eglmes.
The dominance of ponderosa pine after prescri.bed
fire is introduced is vividly shovn in the density
graph. As ponderosa pine increases in number
with each fire, the other species subside and
pracrically <iisappear.
D ISCUSS IOi\'
The results of the simulation have ecological
implications and can be applieri to r,rj.lderness
fire managernent, Iuture development of Che model
i+i I I enhance i ts use -
Ecological Irnplications
hlithout fire wtrite fir r,/ou1d obrriously replace
pcnderosa pine in r+il.derness ecos)'stens rqith short
fire intervals because hs31,y shade and deep litter
SUPPRESSION \PRESCRIBED/ LIGHTNING
F1RES i
t
UJ.i
zi,
ui<
l-
l!^
so
F
-I.'-..-
0
roo
"e
r!
tr
J
a
6
a
U
U
E
F
t
a
z
L!
c
1500!
rooor
500!
) 20 40 60 80 100 120 t40 t60 t80 200
Y EARS
Figure 5.--Tota1 fuel energy, percent basal area,
and densily effects under the prescribed fire
scenario for a 200-year run of the FYRCYCL mode1.
jn rhoco sir.e t-he firs n.onnetitive
4 r!r q LVULP
adrrantage. Fire has always been a part of Lhese
ecosystems and wi1l. continue to be regardless of
human efforts to incercede. Favorable rveather
conditions, sufficient fue1, and lightnlng
ignitions simultaneously occur often enough to
produce periodic fires that maintaln an ecologi-cal
state dif f erent from that r,'hlch r+ould occur
r!'ithout f lres.
As seedlings, each of the species is susceptible
ts^ Fi-^ D^-l^-^^-
LU r .Le. ronuerosa pinc soon gains an advantage
b)' naving a higher survival rate in open conditions
and by gror,ring faster. The pines also develop
thicker bark at a younger age and have higher
cro\,rns. The interrral betr.;een f ires is long enough
to a11or.' the seedlings to become established and
grow out of the reach of lo\.r-intensity fires. The
34.lears before the first fire in the lightning-
fire scenario shows the mechanism by which the
sLands becone established. A longer interval would
al1or+ too much fuel. to accurnulate, leading to the
possibilit.y ot a lrigh-intensirl, Iire.
124
The simulation shor".ed that sorne fires burned in
!L^ ^--r-^ ^-r '^11 These fires r!'ere no!
Lrrc DPr f rrE drru !aia.
uniform, nor rvould they burn every spot with equal
intensity. Because some areas did not burn, some
lrees of different sizes and species l,rere sti1l
able to reproduce. A mosaic of groups of trees
similar to the aggregaticns described b1r Bonnicksen
and Sfone (1982) will be perpetuated in these
areas.
0ver tlne, ecosystems reach a point of stability
ca11ed a steady state. Fluctuations occtlr ai-ound
a relatively stable average condltion. Itlithout
c:-^ !L^ ^!^-r.. -.^te for mixeri conifer
lMt LLtc -Lvduy DLa
ecosystems changes from ponderosa pine to tuhite
fir because it is able to reproduce in its o\nn
shade. Fire acts as a perpetuating mechanism in
these ecosystems for ponderosa pine, The steady
state ls reached around the average condition as
shown in the fuel and density graphs (tig, 2, 4).
Fire also prevents complete alteration of the
ecosystem. hTlren smal1 accumulations of fuels
burn, heat energy is 1ost. There is a cycle of
1^^^ --l ^^^retion enrresnnndinp tO tlfe
interval belr.'een fires. hrithout periodic energy
loss there rvould be an energy buildup of con-
siderable proportions. The inevitable fire tvould
reduce the fuels raith such irrtensily thaL the
ecosystem r.rould be pernanently changed. Lor,r-
'iotcnsil-v fires in thesc trcnqvstems incrg69g
stability by reducing lhe magnitude of the
flu c tuat ions .
The model is useful because it shor"s the condi-
tions necessary to perpetuate short-fire-interval
ecosystems. Its value lies not in iEs ability to
predict future events, but rather in its abilitl'
to show the inherent behavioral characferistics of
such ecosystems.
Management Applicat ions
I,lilderness managers are charged r.rith preserving and
protecting wilderness areas in thej.r natural condi-
tion. It is coTrunonly accepted to include meadols,
1^1.^^,,i1JlJF^ -1^*+^
, rcALJ, wrruJ.lrtie pLanLS, mounLalns,
glaciers, rain, and many other componenLs. Less
well accepted as natural are fue1s, llghtning fires,
and insect and disease infestations; yet it makes
no more sense to exclude fire from the r.rilderness
than it does to exclude snow or sunshine.
The manager needs to a1loi,r natural processes to
run their course, and in lhose cases where process
has been interrupled to reintroduce the process as
naturally as possible. For short-fire-interval
ru'ilderness ecosystems that irave been subjected to
fire suppression activities, prescribed fire is
the most natural means available. The questlon
then becomes how best to reintroduce fire. In
partjcular, it is important to knou how frequentlv
Lo burn, hor,l intensely to burn, and r+hen Lo stop
burning.
The results from the fire cycle simulatlon can ai-d
in answering these questions. Tire first step
would be Eo coLlect vegetation, fueJ, lightning,
and ieeather data for the area in question. The
simulator is then run ser.'era1 times to determine
average vallles fc.rr the mean flre incerval and the
mean fuel energy leve1, Runs are then made r,rith
tho nraenrihad firp nnt-ion in efFeni rrqi-^ *L^^^
!r!e uPLfv,r u5!rr6 Lrtusu
average values along rvith the number of years
fires have been suppressed, the burning direct.ion,
and the months when prescribed burns will be set.
The results will indicate the number of years and
nreserihed firps noc^^-^rar F^ r^f,!'h ",. Che
Pru\ae! )/ Lv !sLu!'r LU
natural fuel energy 1evel, the months l{hen con-
ditjons r.'ould be met for prescribed fires, and che
number of times backing fires r+ould have to be
used insLead of head fires. This information ls
rhon rrcorl i^ dpci on r nraq.r'ihod hrrrnino
..-..o program
for a l.rilderness area. It is also possible a
burning program will not be necessary and that
llghLning fires can be allov:ed to burn withou!
-^r..^j-- F..^1^ T- pnv trr/prl-- 1-he eimrrlatOf iS
ilti !usrr
one source of information managers can use to help
nAof rho nhel lonop nc -^r-+ --:1 t--
- I ma]'nEaan r ng \{r roerness
ecosystems.
Future DiTectlon
A11 computer simulation models are simplifications
of real-r"or1d processes. The modeler is faced
roith the dilernma of balancing these simplifications
with real-r+orld complexity. The more simplifying
assumptions ma<ie, the less Lhe model reflects the
real rvorld. The FYRCYCL model can benefit frorn
serveral modifications, hor+ever, to make it a
better management tool.
Agee (1973) pointed out Ehat precipitation and
erosion hazard subroutines should be incorporated
lnto the model, and this i'ri1l be done j,n Lhe next
version. The Rothermel (1972) rate of spread
equation will also be added to replace the
algorithms presenrly in the mode1. Other additions
r"ill include fuel generaLoas for lhe larger size
classes and the abilitl'to specifv upper and lovrer
limits to prescription parameters, 0nce those
changes harre been made, the model r'rill pror.ide
information useful in managing short-fire-interval
r+ilderness ecosystens and in understanding the
role of fire in those ecosvstems.
REFERENCES
Agee, J. K.; \^Jaklrnoto, R.H,; Biswell, H, H. Fire
and fuel dynamics of Sierr:a Nevada conifers.
For. Ecol. Manage. L: 255-265i L978,
Arnold, K. Project Skyfire lightning research.
Proc. Ta11 Timbers Fire Eco1. Conf.3: 121-130:
1964.
t25
Baker, F. S. A revised tolerance cable. J
472 179-LBI; i949.
Bist^re11, H, H. Forest fire in perspective. Proc.
Ta11 Timbers Fire Ecol. Conf.7:43-632 1967.
Ronni ekson - T- 11- : Srnno tr a' aon^nctTUCt iOn Of
a presettlement giant sequoia-mixed conifer
forest using the aggregation approach, EcoIogy.
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Cooper, C. F. Changes in vegetation, structure and
groB,th of southwestern pi-ne forests since i.'hite
settlement. Eco1. llonogr. 30: 129-164; 1960.
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Hartesvelt, R. J. Fire ecology of the giant
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fire r.reather paEterns--their frequency and
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N. L; Lotan, J. E.1 Reiners, I{. A., tech.
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Kilgore, B. M. Fire management programs in
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For.
r26
F'igure 1. Burn unjt boundaries for the propolgq 4,800 acre prescribed fire,
- Yosemite National Park, 0ctober' 1979.
Ign'ition and Burn Paltern
The prescpiption for this unit using NFFL Model 9 (Albini-1976) is listed
in Table 1, At the tine of ignition on 0ctober 28, the dry bulb temperature
was 50 degrees F, relative humidity 38 percent,,and windspeed_5 mph._ Mo'isture
va'lues toi the l-hour, lO-hour, 100-hour, and 1000-hour time-'lag fuels were 7,
11, 14, and 18 percent. Based on these values, the pre_{icted rate-of-spread
on 40 percent siopes was 4 feet per minute, pred'icted fireline'intensity was
22 BTU/foot/second, and pred'icted flame length was 2 feet.
t22
