Using Search Time and Regression to Estimate Abundance of Territorial Spotted Owls
Author(s): James P. Ward, Jr., Alan B. Franklin, R. J. Gutierrez
Reviewed work(s):
Source: Ecological Applications, Vol. 1, No. 2 (May, 1991), pp. 207-214
Published by: Ecological Society of America
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Ecological Applications,1(2), 1991, pp. 207-214
? 1991bytheEcological
SocietyofAmerica
USING SEARCH TIME AND REGRESSION TO ESTIMATE
ABUNDANCE OF TERRITORIAL SPOTTED OWLS'
JAMESP. WARD, JR., ALANB. FRANKLIN,
ANDR. J.GutiuRREz
Department
of Wildlife,
Humboldt
StateUniversity,
Arcata,California
95521 USA
Abstract. Usingconventional
samplingmethods,unbiased,preciseestimatesof the
numberofindividualsin a populationcan be difficult
to obtainforrare,secretive
species.
We used a Leslieregression
model(LRM) to estimatethenumber(No)and thevariance
ofthenumber(V[No])ofadultand subadultNorthern
SpottedOwls in a territorial
populationfromdirectcountswithina 292 km2 studyarea.EstimatesofNofromdaycounts
weremoreaccurateand preciseand morerobustto fluctuations
in surveyeffort
than
estimates
fromnight
counts.LRM estimates
fromdaycountswerenotsignificantly
different
fromtwodifferent
maximum-likelihood
estimates
and required30-64%lesseffort.
These
findings
suggesta less costlymethodforstatistically
comparing
SpottedOwl abundance
betweenspatialor temporalunits.
Keywords: abundance;
callsurvey;
Leslieregression
model;maximum
likelihood
estimator;
NorthernSpottedOwl;population
occidentalis
size; Strix
territorial.
caurina;
owl are poorlyunderstood(Dawson et al. 1987). A
pointforunderstanding
viabilityof
The numberofindividualsalive in a populationat logicalstarting
a giventime(N,)is a fundamental
parameter
ofmany SpottedOwl populationswouldbe to modeltheexecologicalstudies.Methodsofestimating
size of ani- istingpopulation,whichwouldrequirean abilityto
N. Anyreasonablecomparison
mal populationsare well documentedand thorough estimateand monitor
of
over
time
or
between
habitatswouldalso require
N,
reviewscanbe foundin Caughley
(1977),Seber(1982,
varianceassociatedwithNt.
1986),and Krebs(1989). However,unbiasedandpre- a measureofthesampling
nocturnal
that
predators
cise estimatesof (N,) usingconventionalsampling SpottedOwlsareterritorial,
live in old-growth
coniferforests
ofthePamethodsmaybe difficult
to obtainforsome species primarily
(Solis 1983,Forsmanet al. 1984).Be(e.g.,Burnham
etal. 1980,Reynoldsetal. 1980,White cificNorthwest
anduselarge(400-1800
etal. 1982)becausesampling
assumptions
aredifficultcausetheseowlsareterritorial
low
to meetand estimators
arenotrobustto violationsof ha) tractsofhabitat,populationsattainrelatively
assumptions.
Specifically,
speciesthatuse largeareas, densities(Forsmanet al. 1984,Franklinet al. 1990).
occurin lowdensities,
or aredifficult
to observe(e.g., The owl's nocturnalhabitand low density,coupled
prohibit
use oflinetransect
largepredators,
nocturnal
or secretive
species)cannot withsteep,ruggedterrain
et al. 1980),or variableplot(Reynoldset
be sampledadequately
without
tremendous
fieldeffort. (Burmham
theirabundance.
it is thelargeor rarepredators
Ironically,
thatmay al. 1980) methodsforestimating
However,
March
during
through
August
bothmembers
be promotedas "umbrella"(Peterson1988), "keydefenda breeding
territory
using
stone"(Norton1988),or "indicator"(Salwasseret al. ofan owlpairactively
(Forsmanet al. 1984). Young
1982,Salwasser1988) speciesin an effort
to preserve vocal advertisements
For example,in thePacificNorthwest, dependon theirparentsuntildispersaland do notdebiodiversity.
in thefall(Gutierrez
beforedispersing
ofNorthern
maintenance
SpottedOwl (Strixocciden- fenda territory
taliscaurina)populations
is promoted
as a waytocon- et al. 1985). Aftertheirjuvenilemolt,subadultowls
byplumagecharacters,
serve old-growth
coniferousforests(Thomas et al. (1-2 yrold) can be recognized
1988). Proposedplansto maintainviableowl popu- and thesebirdsmay obtainand defenda territory.
adult,andsubadultSpottedOwlscan
lationsconsistof a network
of suitablehabitatareas Thus,territorial,
theircallsandelicbyimitating
(UnitedStatesForestService1988).Thesizeandstruc- be locatedconsistently
during
thebreeding
period(Forstureofthoseareasneededto maintainowloccupancy itinga vocalresponse
are becomingwelldocumented
(Solis 1983,Forsman man 1983).
We infer
frombandingstudiesthatSpottedOwlsare
et al. 1984, Ganeyand Balda 1988, 1989, LaHaye
1988,Laymon1988,Bias 1989,Careyetal. 1990,Sisco longlived and have high(0.96) annualadultsurvietal., unpublished
data).Mor1990).However,thearrangement
andnumberofhab- vorship(A. B. Franklin
in thenonadultsoccursprimarily
itatareasneededto maintainviablepopulations
ofthe talityin territorial
INTRODUCrION
breeding period (A. B. Franklin et al., personal
1 Manuscript
received22
cepted23 July1990.
January1990; revisedand ac-
Weoccasionally
birds
observation).
encounter
unbanded
duringnighttime
callingsurveysthatwe cannotrelo-
208
JAMES P. WARD, JR. ET AL.
EcologicalApplications
Vol. 1. No. 2
cateduring
theday.Sincetheseowlsareusuallywithin Foreachyear,thetime(inminutes)
devotedbyeach
to callingfor,searching
for,andlocatingowls
of a markedpair,we believethatthese observer
theterritory
We wasrecorded
separately
fornighttime
anddaytime
surmembers
ofthepopulation.
birdsarenonterritorial
willbe referred
and ecologyofnon- veysand,hereafter,
to as surveyeffort.
knowlittleaboutthedemography
did notincludetraveltimebetweencall
territorial
birds.We also do notknowaboutthenight- Surveyeffort
orsurvey
noranyadditionalfieldeffort.
birds.However, stations
timeresponserateof nonterritorial
routes,
withingeographic
thenumberofbandedbirdsdetectedwhilespot-light- Surveyswereconducted
subunits
owlsat day roostsin- ofthestudyarea.Subunitsweredelineated
ingowlsat nightor observing
byobservbirds(bothadultand sub- ers usingtopographic
and habitatfeatures,
dicatesthatnonterritorial
and reppotential
owlterritories.
home resented
haveunstable
Theseterritories
often
were
adults)do notcallfrequently,
throughoutused to assignsurveyeffort
observable
to the numberof owls
ranges,
andarenotconsistently
ofbanded counted.Oncea pairofowlswaslocatedin a territory,
a shorttimeperiod.Thus,ourobservations
birdsal- additionalowl responsesand additionalsurveyeffort
birdsindicatethatwe are locatingterritorial
or withintheterritory
mostexclusively
andthatthereis littleimmigration
wereignored.Ifonlya singlebird
emigration,
and fewbirths(e.g.,juvenileowlsare not was detectedin a territory,
additionaleffort
was dedur- votedto locatinga potentialmateuntila matewas
locatedbycalls)ordeathsin thestudypopulation
ing the censusperiod.These conditionsallow us to countedor theannualcensusended.If an area conofcatch- tainedmorethanone pair,thenumberof territories
meetsomeofthebasicbiologicalassumptions
and surveyeffort
withineach area wereadjustedaceffort
methods(Seber1982:296,Krebs1989:162).
In thispaper,weusea Leslieregression
model(LRM; cordingly.
Thus,weusedtheassociationofan owlwith
abundanceandthe a giventerritory
to inferowl identity
Leslieand Davis 1939)to estimate
and theamount
varianceof abundanceof SpottedOwls fromdirect of time necessaryto locate an individualwithout
counts.We also compareLRM estimatesbased on knowledgeof bandingrecords.Concurrently,
we atbasedon day- tempted
to captureand markall individuals
nighttime
countsofowlswithestimates
withcolofthismethodby oredleg bandsto confirm
timecounts,andevaluatetheutility
and evaluatethis
identity
LRM estimateswithtwomaximumlike- assumption
(Franklinet al. 1990).Effort
comparing
requiredfor
was also recorded.
(Zippin1956,Jolly1965,Seber1965, marking
lihoodestimates
Whiteetal. 1982).Thismethodmaybe applicablefor
Leslie regressionmodel (LRAM)development
abundanceofotherspeciesthatbehavesimestimating
Call surveys
provideda directcountwithout
a meailarlyto theSpottedOwl.
sureof precision.An LRM (Leslie and Davis 1939)
METHODS
was used to estimatethenumberof adultsand subadultsalive at thebeginning
Studyarea
of each breedingseason
and
a
95%
confidence
interval
forNo.
(NO),
Adultand subadultNorthernSpottedOwls were
modeland works
countedin a 292.4 km2 studyareanearWillowCreek, The LRM is a closed-population
withinthisstudyareawas on thetenetthatthenumberofindividualsremoved
USA. Vegetation
California,
or Klamath by samplingfroma givenarea willdeclineovertime
forest
classified
as eithermixedevergreen
montaneforest
(Kiichler1977),andhasbeendescribed (Leslieand Davis 1939,Seber1982:296,Krebs1989:
lineoftheform
in detailelsewhere
(Solis 1983,Franklinet al. 1990). 162).Thus,a regression
43% ofthestudyareawas considered
Approximately
(1)
Y,= a + bX,
et al. 1990).
suitableSpottedOwl habitat(Franklin
elevationsand slopes can be fitto thenumberof individualscapturedper
Terrainwas steepand rugged;
(Y1),and thecumulativenumberof inranged from 150 to 1700 m and from 18? to 550, re- unitof effort
dividuals
captured
priorto eachsurveyintervali (Xi),
Studyarea boundariesweredrawnalong
spectively.
a
least
using
squares
analysis(Zar 1984:263-265).Folto minimizeoverlap
features
prominent
topographical
lowing
the
notation
of
Seber(1982:296),and usingthe
betweenthestudyareaand adjacent
ofowl territories
slope of theregression
line (b) as an estimateof the
habitat(Franklinet al. 1990).
coefficient
ofcatchability
(K), No can be calculatedas
Owlsurveys
(2)
No =X+ (Y/K).
Owls werelocatedand countedusingvocal imitationsofthespecies'callsduringsurveysat night(1/2
h The intercept
ofthex axis bytheregression
linealso
h priortodawn)andduring
theday, providesa pointestimateofNo (Seber1982:298).
priortoduskto 1/2
August,1985 to 1987 (Forsman1983,
Aprilthrough
The varianceof No,or V[NO],can be estimatedas
Franklin
etal. 1990).Nightsurveys
wereconducted
at follows:
callstations
were
established
alongroadsand,generally,
usedto locateand countowls.Day surveysconsisted
2i 1
(N- X)2]
ofmoreextensive
wereused
searchesand,specifically,
tolocateandcountowlsbyvisualobservation
atroosts.
=
May 1991
ESTIMATING OWL ABUNDANCE
where12 is themeansquareerrorfromtheleastsquares
samplesize(Seber1982:
analysisands is theregression
from
interval
canbe estimated
298).A 95%confidence
V[NO]usingthedeltamethodwhens is large(> 10),
No ? 1.96(/N01])/2,
209
DAY-1985
o
70 -~f213"
70-
(4)
C
o) 501
or by usingtheproceduredescribedby Seber(1982:
tm h 11
n.
299) whens is small.
ourvocalimitations
To usetheLRM, weconsidered
as "bait" to enticeowls to respond.Owls thatwere Z 30w
I
detected,eitherby sightor sound,wereconsidered
as
"captured."We calculatedcatchperuniteffort,
Yi,
thenumberofowlsdetected(n,)dividedbytheasso10
ciatednumberofhoursofsurveyeffort
(f),in eachof
s sampling
periods.The latterwerecreatedbysystem250
100
150
200
50
0
surveyresultsfroma givenyearwith
aticallygrouping
CUMULATIVEHOURS SURVEYED
an arbitrary
windowof time,m hourslong(Fig. 1).
becausetheamount FIG. 1. Procedureforgrouping
Groupingof data was necessary
SpottedOwl call survey
model,wherem is the
of effort
devotedand the numberof owl territoriesdataforinputintoa Leslieregression
in
(time)interval,
niis thenumberofowlsdetected
sampledduringanygivensurveyweresmallrelative grouping
timegroupi, andf is thetimein hoursrequiredto locate
to totalsurveyeffort
(Fi) and thetotalnumberofowl and countn,
Without
territories
sampledeach year,respectively.
thedata over time,too fewowl territories
grouping
werequantified
wouldhave been sampledand the numbersof owls inputintotheLRM. Theabovecriteria
detectedduringeach sampling
periodwouldnothave and evaluatedusinga chi-squaregoodness-of-fit
test,
declinedthrough
time,a requisiteforusingtheLRM. a Student'st test,and thestandarderroroftheregresthe cumulativenumberof sion dividedby Y, respectively.
For example,grouping
Statistical
testswere
devoted deemedsignificant
owls detectedforeverym = 23 h of effort
at the5% level(a = .05). A BASIC
in 1985givesY1= 0.708 owls computer
was developedto keepthisproceprogram
duringdaytimesurveys
detectedperhourand X1wouldequal 0 owlsdetected durestandardized
amongdata setsand users.
Becausethe
periodI (Appendix).
previousto sampling
LRM estimates
ofNowerecomparedto (1) theminLRM imumnumberofindividualsknownto be alive (Nm)
selectionof m mighthave influenced
arbitrary
werecalculated based on markingresults(Franklinet al. 1990), (2)
X and Y valuesforall surveys
results,
every maximumlikelihoodestimatescalculatedusingthe
1) h, incremented
byvaryingm from2 to (F1/1
1 h. The latterterminus
was usedto ensurethatcon- generalizedremovalmodel (Mbh) of programCAPfidenceintervalswerecalculatedusings > 10 (Seber TURE (Zippin 1956, Otis et al. 1978, Whiteet al.
modelD estimatesfrom
1982),and (3) Jolly-Seber,
1982:12,Krebs1989:164).
JOLLY(Jolly1965,Seber1965,1982,FrankThedatasetthatbestadheredtomodelassumptions program
was selectedforestimating
No,foreach surveytype, lin et al. 1990).
owls
surveys
represented
The n,talliedfromdaytime
oftheLeslie
foreachyear.Therearethreeassumptions
and demo- foundat a roost.Becausedaytimeroostsofindividual
method:thepopulationis geographically
fromroostsinadjacentowl
ofan individualbe- owlswerespatially
distinct
closed;theprobability
graphically
owlscouldbe countedand effecroosting
throughoutterritories,
Pi) is constant
ingcaptured(i.e.,detected;
are equal tively"removed"fromthepopulation.Hence,then,
and detection
theexperiment;
probabilities
datathatbestfitmodelassumptions
inthepopulation
(Krebs1989).De- fromthedaytime
amongindividuals
can be consideredconstantand weretreatedas removaldataand inputintotheCAPtectionprobabilities
estimateswereindeequal ifsamplingis a Poissonprocesswithrespectto TURE Mbhmodel.Jolly-Seber
results
effort(Seber 1982:296). The generalizedremoval pendentlycalculatedfrommark-recapture
et al. 1990).
method(Whiteet al. 1982:109)also can be used to (Franklin
ofvariationforNo werecalculatedas:
Coefficients
evaluateconstancyand equalityof pi. Thereare no
simpletestsforpopulationclosure(Whiteetal. 1982:
(5)
cv(NO)= {[V(No)]'2/NN}x 100.
are valid thedata
162). However,ifall assumptions
willfita straight
line and thevarianceaboutthere- Expectedestimatesof No thatdeviatefromtruepagressionlinewillbe constant(Krebs 1989:162-164). rametervaluesare biased.Becausewe did notknow
Thus,datathat(1) providednimostlikelydistributed thetruepopulationsize we couldnotestimatestatisas a Poisson,(2) resultedin a regression
slope least ticalbias. However,we couldevaluateeachestimator
numrelativetotheminimum
estimates
likelyto equal0, and (3) providedthelowestvariance bycomparing
wereused as berofowlsknowntobe alive,Nm,usingthecalculation:
of observedvaluesabouttheregression
ni
0
JAMES P. WARD, JR. ET AL.
210
EcologicalApplications
Vol. 1,No. 2
1. Surveyeffort
devotedto locating,
and recapturing
marking,
Northern
SpottedOwls,Aprilthrough
August,1985
to 1987,nearWillowCreek,California.
TABLE
Hoursofeffort
Year
1985
1986
1987
Nightsurvey
%*
h
208.5
95.5
122.1
31.0
12.8
10.7
Day survey
%*
h
266.3
199.4
286.6
39.5
26.6
25.0
Mark-recapture
%*
h
Total
survey
al
recapture
No.
owlst
198.8
453.3
474.8
294.9
673.6
748.2
65
65
736.3
29.5
60.6
64.3
736.3
1145.0
67
* Percent
oftotalhoursdevotedto surveyand mark-recapture
effort.
knownto be alivein a 292.4 km2areabasedon bandingdata.
t Numberofadultand subadultindividuals
[(No- Nm)/Nm]x 100. Negativeresultswould indicate (1987 nightLRM, P < .05; all otherLRMs,P < .001;
rangedfrom
ofNo.Costs Fig.2). Standarderrorsofall regressions
thattheLRM providedan underestimate
modelD estimates 29 to 68% ofthemeanYvalue fromeachsurveytype.
to produceLRM and Jolly-Seber
detection
ofconstant
and the Thus,theassumption
probability
of surveyeffort,
wereconsidereda function
All
regressions.
re- was violatedfor4 ofthe6 bestfitting
effort,
and mark-recapture
sum of surveyeffort
otherassumptions
appearedvalid forselectedregresspectively.
removalmethod
sionmodels.Additionally,
thegeneral
RESULTS
ofprogramCAPTURE testedforand selectedan esAnnualdirectcountsofadultand subadultSpotted timatorofNo assumingequal detectionprobabilities
during1985 to 1987,even fordaysurveydata collectedin 1985and 1986.Nine
Owls variedonlyslightly
wereassumedin esthrough different
detectionprobabilities
fluctuated
thoughnightand daysurveyeffort
time(Table 1). On average91% of theowlscounted timating
No fromdiurnalcountstalliedin 1987.
withinthestudyarea eachyearwerebandedafterdePopulationestimates
tection.
Estimates
ofthenumberofterritorial
adultandsubTests of assumptions
adultSpottedOwls in thestudyarea variedwiththe
testsfrom methodof estimation
limitscalforthePoissongoodness-of-fit
(Fig. 3). Confidence
Probabilities
bynightsur- culatedusingtheprocedure
data setsgenerated
forsmallsamplesizes(i.e.,
thethreebestfitting
Seber1982:299)wereasymmetveyswere,P < .25,.001,and.001during1985through a quadraticformula;
andP < .001,.10,and .001 forday rical,and upperlimitswereconsistently
greater
than
1987,respectively,
>0 confidence
Allregression
lineslopesweresignificantly
limitscalculatedusingthe delta method
surveys.
intervals
for1985 nightand day sur(e.g.,confidence
veyswere71-692 and 51-71,respectively).
The delta
method
was
used
to
evaluate
differences
among
estibetween directcounts and esTABLE 2. Percentdifference
matorsbecause(1) theupperlimitcalculatedfor1985
timatesof the numberof territorialSpottedOwls (No) in a
292.4 kM2 stuidyarea near Willow Creek, Califomia, and night-based
estimates
usingthequadraticformula
apprecisionof N,
pearedbiologically
unrealistic,
(2) all sampleswere> 10
(Seber1982:12,Krebs1989:164),and (3) Noappeared
Percent
cv[No]
to be normally
distributed
(Seber1982:12).
difference (%)
Model*
nt
Year
LRM estimates
ofNobasedonnightsurveys
differed
+70.7
34.5
19
1985
NightLRM11
< .05) fromLRM estimates
significantly
(P
based
on
12
-10.8
6.9
Day LRM23
in
and
from
maximum
day
surveys
1986,
likelihood
12
-6.2
7.5
Day CAP.Mbh
in 1986and 1987(Fig.3). Duringthe1styr
4.7
estimates
0
Jol-SebD
in an overestimate
ofsampling,
resulted
nightsurveys
14
9.8
-20.0
1986
NightLRM7
17
7.8
+7.7
Day LRM12
of Nmby as muchas 71%, whereasnightsurveysin
17
+13.8
9.8
Day CAP.Mbh
Nm(Table2). Annual
subsequent
yearsunderestimated
+7.7
2.6
Jol-SebD
LRM estimatesbased on nightsurveysappearedto
12
-9.0
9.2
1987
NightLRM1
fluctuate
withannualsurveyeffort.
proportionally
12
+6.0
7.0
Day LRM24
In
contrast,
LRM
estimates
based on day surveys
12
+1.5
4.9
Day CAP.Mbh
2.6
+13.4
Jol-SebD
weregenerally
consistent,
withtheexception
ofthe1st
by 11% (Table 2).
* LRM = Leslie regression model, CAP.Mbh= Program yrwhenNmwas underestimated
CAPTURE removal model, Jol-Seb= Jolly-Sebermodel D;
LRM estimates
ofNobasedon daysurveys
wereequal
subscriptsrepresenttheinterval,m hourswide,used to group to or lessthanmaximum-likelihood
on 3 of
estimates
the data priorto model input.
6
All
occasions.
but
the
estimates
1985
night-based
t LRM n = numberofx, y coordinates;CAP.Mbh= number
wereprecise(cv[NO]< 10%;Table 2). LRM estimates
of samplingsessions.
May 1991
ESTIMATING OWL ABUNDANCE
NIGHT SURVEYS 1985
Y 0.741 - 0.007X
3-
211
DAY SURVEYS 1985
Y- 0.612 - 0.OO IX
1.5
21
0
Li..
1
.5 -
*
0
t
CL
w
0
20
60
80
NIGHT SURV/EYS1986
Y:I.1823 -0.036 X
3
tk
40
2
-
20
1.5 *Y:~0.735
a:
oH
0
40
60
80
DAY SURVEYS 1986
-.0.010OX
1\
.
35
U
03
U
0*0
I-.
0
0
U
20
60
80
NIGHT SURVEYS 1987
Y- 1.132-0.019X
X
3
z
40
20
60
40
80
DAY SURVEYS 1987
Y 0.551 -0.008X
1.5
2
1
O '_
0
0
0
.5
20
*
g
40
55033
60
80
U
0
20
40
60
80
OWLS PREVIOUSLY DETECTED
ofthenumberofindividualSpottedOwlsdetectedperhourofsurveyeffort
FIG. 2. Regression
againstthecumulative
withina 292.4 km2areanearWillow
detectedduringnighttime
and daytimesurveys
numberofindividualowlspreviously
Creek,Califomia,1985 to 1987.
based on day surveyswere less precisethan the JollySeber estimatesbut more precise than the LRM estimatesbased on nightsurveysduringall years,and more
precise than the general removal model of program
CAPTURE during1985 and 1986.
LRM estimatescost 30-64% less than mark-recapture estimates, considering the additional time required to markand capturethe birds (Table 1). More
timewas devoted to mark-recaptureactivitiesin 1986
and 1987 to marktrap-shyowls withcolor bands. Resightingowls, ratherthan physicallyrecapturingowls,
in subsequentyearsbutat least
would requireless effort
owls,becausethe
thanonlycounting
30% moreeffort
used to lureowlscloseenoughto
and methodseffort
colorbandsare similarto thoseusedforcapidentify
birds,as was thecase in
unmarked
turingpreviously
however,is thefact
1985 (Table 1). Mostimportant,
thatLRM estimatescan be generatedwith 1 yr of
ratherthana minimumof 3 yrof data
surveyeffort
estimatesofpopulationsize.
requiredforJolly-Seber
DIsCUssIoN
the
manyofthetestedassumptions,
Despitemeeting
modelwas a poor estimatorof No
Leslie regression
JAMES P. WARD, JR. ET AL.
212
1985
EcologicalApplications
Vol. 1, No. 2
personalobservation).
Also,homerangesize forindi210
vidualsduringthisperiodrangedfrom0.6 to 2.3% of
(11,19)
129
thestudyarea (Solis 1983),indicating
thatfewhome
rangeswouldbe intersected
by studyarea boundaries
150(e.g.,see Whiteet al. 1982:122).Furthermore,
study
area boundarieswereestablished
to minimizemove112
mentsbyowlsacrossthem(Franklin
etal. 1990).Thus,
90immigration
and
emigration
were
considered
negligi(23,12)
71
70
63
165
~65
ble.
By
was
not
affected
61
definition,
by
and
births,
No
I58
5
54
52
mortality
duringthecensusperiodwas assumedto be
95
C/)
30
closetozerobasedon radiotelemetry
(Solis 1983)and
bandingdata(A. B. Franklin
et al., unpublished
data).
O >
1986
However,immigration
could be "mimicked,"and
o o 100
L1J4
henceclosureviolated,whenindividualsare counted
morethanonce.This sourceoferrorwas morelikely
o
~~~~~~~~~~~~89
(12,17)
02.
at
night
whenowlsweremobile(i.e.,hunting
ormoving
176
C/)c
80HQ4)
' 74
73
towardan observer
whowascalling),
itdifficult
making
7
forobservers
to inferowlidentity.
70
60
67
65
(7,14)
Moreover,thenumberof owls countedduringall
60
65
59
58
was >80% ofNo.Also,considering
home
daysurveys
U)06
rangesize forpairedowls(X = 676.8 ha),theproportionofhomerangeoverlapbetweenneighboring
owls
O
40
D
(X = 0.39) and thetotalamountofhabitatpotentially
used by SpottedOwls withinthe studyarea (12 626
1987
LL 3
ha; Solis 1983,Franklin
et al. 1990),we wouldexpect
O 0^ 100roughly({12626/[(1 - 0.39) x 676.8]} x 2) or 62
z_
adultandsubadultowlsinthestudypopulation.
There(24,12)
fore,theportionofthepopulationsampledappeared
76
80 79
75
(11,12)
76
adequate.Thisledus toconcludethattheoverestimate
67
71
67
producedby nightsurveysduring1985, and subseofNo in 1986and 1987werelikely
quentfluctuations
61
66
61
60 causedbyovercounting.
55
Regressionestimators
are notoriousforunderestimatingNo (Van Ettenet al. 1965,Lewis and Farrar
40
1968,Whiteetal. 1982,Schnute1983)and,underthe
JOL
COUNT
CAP
LRM
LRM
SEB
NIGHT
MBH
are infeDAY
assumptionof constantcaptureprobability,
riorto maximumlikelihoodestimators
(Whiteet al.
FiG. 3. Annualestimatesof the numberof territorial 1982:115).In addition,estimation
of V[NO]usingEq.
NorthernSpottedOwls in a 292.4 km2area near Willow
3
may
not
be
valid
because
regression
techniques
asModelacronyms,
beneathhorizontal
Creek,California.
axis,
andequalityoferrorterms(White
inparentheses
are:LRM = Leslieregression
arethe sumeindependence
(numbers
intervalin hoursusedto groupcensusdataand samplesize et al. 1982:116).However,our LRM estimatesare
CAP-MBH = generalremoval comparableto maximumlikelihoodestimators
of regression,
respectively);
and,
methodofprogram
re- therefore,
CAPTURE; JOL-SEB= Jolly-Seber
robust
when
are
used
to
appear
day
surveys
ducedparameter
(D); COUNT = directcountofowls.
estimate
CountsofSpottedOwlsduring
Noand V[NO].
thedayprovideadequateestimates
ofNowheninput
when nightsurveyswere used. The LRM will work intotheLRM because,all otherconsiderations
equal,
only if the number of individuals captured declines it is unlikelythatindividualsare miscounted
when
over time (Krebs 1989). A plot of cumulativenumber visuallyobservedat daytimeroosts.
of individual owls detected at nightas a functionof
Relativedifferences
werecalculatedusinga total
cumulative hours expended duringnightsurveyswas count(Nm)as a reference
value.Becausedirectcounts
linearforeach year,indicatingthatthe"catch" did not invariably
resultin an underestimate
ofthetruepopdecline.The same plot forday surveyswas curvilinear, ulationsize (Caughley1977),our estimates
of differencelikelyrepresented
showingfewerowl detectionsover time.
minimum
differences
between
Capture rates will not decline if population closure Noand No. However,evaluationof therelativeperis violated or a large enough portion of the studied formance
amongmodelswas valid becausethesame
in all calculations.
population is not sampled (Zippin 1956, White et al. value was referenced
Total counts
1982). With few exceptions,Spotted Owls were site probablyrepresented
90-95% of theterritorial
popufaithfulduringthe census period (A. B. Franklinet al., lation.This judgmentwas based on the amountof
{
v
v
cD
{
52
May 1991
ESTIMATING OWL ABUNDANCE
suitable habitat presentand the number of repeated
visits to territorieswhereowls were not detectedafter
the firstvisit each year (maximum = 21 visits).
Observercharacteristicscould affectcountsof birds
(Verner 1985). Surveys in 1985 and 1986 were conducted by the same two observers,with2 and 4 yrof
experiencein callingand locatingowls at thebeginning
of the 1985 census. All observationswere verifiedby
both observers.Despite this level of observerexperience, the LRM overestimatedNmusing nightcounts
and underestimatedNm using day counts, indicating
that at least two census periods may be necessaryfor
reliableestimates.In 1987, one of the originalobserverswas replacedwithless experiencedobservers.However, priortrainingof new observerscoupled withresidual expertise of the remainingoriginal observer,
preventedany noticeable loss of information.
Our results suggestthat the LRM can be used to
estimatethe numberof territorialadult and subadult
SpottedOwls presentat thebeginningoftheirbreeding
season, and to estimatea measure of precision.Given
the same studydesign,No can be convertedto crude
or ecological density(Franklinet al. 1990). Although
nocturnalcounts should not be used forestimatingNo
with the LRM, nightsurveysare usefulforassessing
the generalvicinityof owl roost sites. Once owls are
visually observed at roosts,theycan be counted with
littleduplication;nestscan be locatedand reproductive
parameterssampled with littleextra effort(Forsman
1983, Franklinet al. 1990). Thus, day surveys,in combination with the LRM, would provide more informationforland managementdecisionsthannightsurveys alone.
We recognizethat the use of the LRM with direct
count data is not a substituteformark-recaptureexperiments,as the latterprovide informationon survivorship, recruitment,and dispersal in addition to
estimatesof N,. However, the LRM will providea less
expensive,simpleralternativeforestimatingand monitoringabundance ofterritorial
SpottedOwls and other
speciesthatbehave similarly.Additionaltestingofthis
methodis recommended,particularlyto assess effects
of observerexperience,geographicvariation,and species variationon model estimates.
213
PSW-87-001ICA), and theMcIntire-Stennis
Program
(HSU
ProjectNumber85).
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