Ecological M odelling 243 (2012) 1 8-32
C o n te n ts lists a v a ila b le a t S c iV e rse S c ie n c e D ire c t
Ecological M odelling
journal
ELSEVIER
^
ECO LO C.ICA l
M O D ELLIN G
1^9
homepage: www.elsevier.com/locate/ecolmodel
Incorporating behavioral-ecological strategies in pattern-oriented m odeling of
caribou habitat use in a highly industrialized landscape
C A D . S e m e n i u k ® ’*, M . M u s i a n i '^ ’^ , M . H e b b l e w h i t e ‘^’^ , S. G r i n d a l '^ "^, D .J. M a r c e a u a ,l
“ D epartm ent o f Geomatics Engineering, University o f Calgary, 2500 University Drive, Calgary, Alberta T2N 1N4, Canada
I" Faculties o f Environmental Design and Veterinary Medicine, University o f Calgary, Calgary, Alberta, Canada
' College o f Forestry and Conservation, University o f Montana, Missoula, ME 59812, United States
ConocoPhillips Canada, Calgary, Alberta T2P2EI7, Canada
A R T I C L E
I N F O
Article history:
Received 20 January 2012
Received In revised form 7 May 2012
A ccepted 5 June 2012
Keywords:
A gent-based model
Caribou
B loenergetlcs
H abitat use
Industry features
Animal m ovem ent
A B S T R A C T
W oodland caribou {Rangifer tarandus) are classified as threatened in Canada, and the Little Smoity herd
in w est-cen tral /Mberta is at im m ediate risk of extirpation due in part, to anthropogenic activities such as
oil, gas, and forestry that have altered the ecosystem dynam ics. W inter season represents an especially
ch allenging tim e o f year for this Holarctic species as it is characterized by a shortage o f basic resources and
is w h en m ost industrial d evelop m en t occurs, to w h ich caribou can perceive as increased predation risk.
To in vestigate the im pact of industrial features on caribou, w e d evelop ed a spatially explicit, agent-based
m odel (/\BM) to sim ulate the underlying behavioral m echanism s caribou are m ost likely to em p loy w h en
navigating their landscape in w inter. The ABM m odel is com p osed o f cogn itive caribou agents p o ssess­
ing m em ory and decision-m aking heuristics that act to op tim ize tradeoffs b etw een energy acquisition
and predator/disturbance avoidance. A set o f en vironm ental data layers w as used to develop a virtual
grid representing the landscape in term s o f forage availability, energy content, and predation-risk. The
m odel w as calibrated w ith caribou bio-energetic values from literature sources, and validated u sing GPS
data from thirteen caribou radio-collars deployed over 6 m onths from 2004 to 2005. Sim ulations w ere
conducted on alternative caribou hab itat-selection strategies by assign ing different fitn ess-m axim izin g
goals to agents. The m odel ou tcom es w ere evaluated u sin g a pattern-oriented m odelin g approach w ith
actual caribou data. The scenario in w h ich the caribou agent m ust trade off the m utually com p etin g goals
o f obtaining its daily energy requirem ent, conserving reproductive energy, and m inim izin g predation
risk, w as found to be the b est-fit scenario. Not recognizing industrial features as risk causes sim ulated
caribou to unrealistically reduce their daily and landscape m ovem ents; equally, having risk take prece­
d en ce results in unrealistic en ergetic deficits and large-scale m ovem en t patterns, unlike th ose observed
in actual caribou. These results elucidate the m ost likely behavioral strategies caribou use to select their
w inter habitat, the relative ex ten t to w h ich th ey perceive industry features as potential predation, and the
differential energetic costs associated w ith each strategy. They can assist future studies o f h ow caribou
m ay respond to continued industrial d evelop m en t and/or m itigation m easures.
© 2012 Elsevier B.V. /\il rights reserved.
1. Introduction
W oodland caribou (Rangifer tarandus caribou) in A lberta are cu r­
ren tly desig n ated as threatened u n d e r A lberta’s Wildlife Act due
* C orresponding author. Tel.: +1 403 220 8794; fax: +1 403 284 1980.
E-mail addresses: semenluc@ ucalgarv.ca (C.A.D. Sem enluk),
m m uslanl@ ucalgarv.ca (M. MuslanI), m ark.hebblew hlte@ cfc.um t.edu
(M. H ebblew hlte), scott.d.grlndal@ conocopbllllps.com (S. Grindal),
dm arceau@ ucalgarv.ca (D.J. M arceau).
’ Tel.:+1 403 220 8794; fax:
+1 403 284 1980.
2 Tel.:+1 403 220 2604; fax:
+1 403 284 4399.
2 Tel.:+1 406 243 6675; fax:
+1 406 243 4557.
< Tel.:+1 403 233 3261.
0304-3800/S - see front m a tte r© 2012 Elsevier B.V. All rights reserved.
bttp://dx.dol.org/10.1016/J.ecolm odel.2012.06.004
to th e ir red u ced d istribution, a decrease in th e n u m b er and size
of populations, and th re a ts of co n tin u ed declines associated w ith
h u m a n activities (ASRD, 2010). The A lberta g o v ern m en t resu itan tiy
reco m m en d s th e a ssessm en t and m an ag e m en t of cum ulative
effects on caribou, as w ell as th e id entification and provision of a d e­
q u ate h a b ita t (a m o u n t and ty p e) to allow for caribou persistence.
A su b set o f an th ro p o g en ic activities, specifically th o se of resourceex tractio n in d u stries such as forestry and oil and gas, affect caribou
h a b ita t use in th re e generally accepted w ays. First, th e y rem ove
large tra c ts of relatively io w -p ro d u ctiv ity m a tu re to old conifer
forests and forested p eatian d s (i.e., cutbiocks), w hich contain
lichens, th e p rim ary w in te r food source for caribou. Second, th ey
increase th e p red atio n risk via a p p aren t c o m p etitio n (DeCesare
et ai., 2010a), and by facilitating h u n tin g a n d /o r searching
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
efficiency of p red ato rs via linear featu res such as roads, pipelines,
and seism ic lines (D yer et al., 2001). Finally, caribou can perceive
h u m an activities and an th ro p o g en ic featu res b o th as d istu rb an ce
and p red atio n -risk events, e ith e r directly th ro u g h physical fo o t­
print, or indirectly th ro u g h sensory d istu rb an ce (Frid and Dill, 2002;
V istnes and N ellem ann, 2008). Caribou respond accordingly by
atte m p tin g to m inim ize th e ir exposure to th em , sim ilarly as th e y
w ould to n atu ral pred a to rs (Sm ith et al., 2000; Dyer et al., 2001;
Polfus et al., 2011).
Caribou are also su sceptible to h arsh e n v iro n m en tal condi­
tions. W in ter re p resen ts an especially challenging tim e of y ear as
ov er-w in terin g caribou face th e en erg etic costs of food availability,
periodically harsh en v iro n m en tal conditions, p re d a to r avoidance,
and disturbance. Specifically, th e availability o f te rre stria l lichen,
th e m ain w in te r food source, is co n strain e d to specific h ab itat
req u irem en ts (Dzus, 2001) and is energetically costly to access (i.e.,
cratering th ro u g h snow ). Next, th e m in im izatio n of en ergetic costs
in w in te r ap p ears im p o rta n t for caribou, at tim es at th e expense
of increased p red atio n risk, as fem ales are w illing to use high-risk
areas to m inim ize trav el costs (Johnson et al., 2002). Finally, w in ­
te r is th e tim e of year w h en m o st in d u strial d e v elo p m en t occurs
in th e stu d y area (Neufeld, 2006), and as caribou are sensitive to
th is form of disturbance, th e y m ay experience en erg etic costs in
in d u strial-featu re avoidance (B radshaw et al., 1998). These e n e r­
getic costs during w in te r have th e ability to affect fem ale caribou
rep ro d u ctio n since m atern al co ndition has a d irect im p act on fetal
viability and su b seq u en t calf survival (Post and Klein, 1999). T h ere­
fore, caribou, in p articu lar fem ales, need to trad e off decisions
b e tw e e n energy m an ag e m en t, foraging efficiency, and p red atio n
risk, and th ese choices influence th e ir h ab ita t selection, m o vem ent,
and reproduction.
Critical h ab itat for caribou in C anada has b ee n defined as th e
percentage of range need ed to m ain tain or re tu rn th a t h erd at or
to a self-sustaining rate (E nvironm ent Canada, 2011a). W hile th e
im pacts of hab itat change and in d u strial featu res and activities on
caribou have been stu died in te rm s of spatial d istrib u tio n (Fortin
et al., 2008), physiological stress (W asser et al., 2011), en erg etic
costs (B radshaw et al., 1997), and p o p u latio n viability (W eclaw and
H udson, 2004), th e behavioral m ech an ism s and strateg ies caribou
use w h e n navigating th e ir landscape, and h o w th e se are influ­
enced by reso u rce-ex tractio n in d u stries are less clear. M ost stu d ies
have n o t explicitly inco rp o rated how caribou co n cu rren tly m ake
behavioral trad eo ff decisions th a t are m o tiv ated by b o th th e an i­
m al’s in tern al state and ex tern al environs. Indeed, th e Canadian
g o v ern m en t’s d eterm in atio n o f critical h a b ita t is n o t restricted
sim ply to an explicit geographical d elineation, b u t in stead ties
th e designation of critical h a b itat to a geographic state th a t has a
likely probability of sup p o rtin g a local self-su stain in g p o p u latio n
(E nvironm ent Canada, 2011a).
T raditional
appro ach es
to
stud y in g
w ild life-h u m an en v iro n m en t in teractio n s do n o t typically consider individual-level
inform ation, account for com plexities, or in teg rate cross-scale
and cross-discipline d ata and m eth o d s, resu ltin g in a g re a t loss
in predictive or explan a to ry p o w er (Sem eniuk et al., 2011). By
considering th e actions o f th e individual, such in fo rm atio n aids in
quantifying a n im a l-h a b ita t relationships, describing and p red ict­
ing differential space use by anim als, and u ltim ate ly identifying
h ab itat th a t is im p o rta n t to an anim al (Beyer e t al., 2010). To
address th e issue of u n d ersta n d in g caribou h a b ita t selection in th e
face of h ig h -d en sity in d u strial develop m en t, w e have developed
a spatially explicit, ag en t-b ased m odel (ABM) to sim u late w in te r
h ab itat selection and use of caribou in w e st-c e n tra l A lberta. The use
of an ABM for our research is adv an tag eo u s since dynam ic in terp lay
b e tw e e n agents and th e ir e n v iro n m en t is readily accom m odated,
realistic conditions can be ap p ro x im ated (such as m o v em en t
costs across th e landscape), and h y p o th etical scenarios can be
19
^
s
"
' f / ef n £c f f , N
>-• * l\
M Boundary Batwaen Cantwu Ecotypes
W oodland Caribou Population R a n g e A reas
Nebonai Parke
□
(iwwntivEitirfittM]
ns
km ‘
‘
*
J lim
Fig. 1. Little Sm oky caribou range (indicated by th e arrow ) situ ated am ongst o th e r
A lbertan herds (shaded grey) w ith in th e province o f A lberta, C anada (ASRD, 2010).
sim ulated. These m odels are also am en ab le to te s ts of robustness
and sen sitiv ity (G rim m and Railsback, 2005). O ur caribou ABM
inco rp o rates tw o critical ecological th e o rie s involved in h ab itat
selection: anim al m o v em en t ecology and behavioral ecology.
A gents are given fitness-m axim izing goals (i.e., survive to re p ro ­
duce) allow ing th e m odel to be u sed to u n d e rsta n d th e processes
th a t govern an im als’ m ov em en t, d istribution, and selection, and
th erefo re to p red ict h o w th e y m ig h t resp o n d to h a b itat alteratio n
and th e presence of in d u strial features.
2. Methodology
The caribou ABM com prises tw o m ain c o m p o n ents: (1) a lan d ­
scape re p re se n ta tio n of th e caribou herd, and (2) caribou agents and
th e ir d ecision-m aking h euristics. In th is section, a d escription of the
stu d y area and d a tasets is first provided, follow ed by a p resen tatio n
o f th e m odel p aram eterizatio n , th e sim ulation fram ew ork, and the
v alidation approach.
2.1. Description o f the study area and datasets
The Little Smoky (ISM ) h erd is located in th e foothills of
w e st-c e n tra l A lberta, ea st o f G rande Cache. Its range covers an
ap p ro x im ate area of 3100 km^ (Eig. 1). The ISM range has the
h ig h est level of in d u strial d e v elo p m en t o f any caribou h erd in
Canada, w ith 95% o f its range in p ro x im ity (500 m buffer) of
an th ro p o g en ic activities (E nvironm ent Canada, 2011b). The site of
four forestry m an ag e m en t a g reem en ts and n u m ero u s p etro leu m co m p an y o perations, a p ro p o rtio n of th e Little Sm oky h erd range
(8.6%) is com posed of 30 year-o ld (or younger) cutbiocks; it also
has th e hig h est road and pipeline d en sity o f any caribou range
in A lberta and co n tain s su b stan tial in d u strial in frastru ctu re (e.g.
w ell site, com pressor, processing plant, b a ttery ) facilities (WCCLPT,
2008). At p resen t, th e re is considerable d ev elo p m en t pressu re from
20
C.A.D. Sem eniuk e t a l .j Ecological Modelling 243 (2012) 18-32
all fronts leading to th e core of th e range and Increases In alloca­
tions to Industrial u sers w ith in caribou range (Roblchaud, 2009).
The area of In terest In th is p ro ject Is th e official political and b io ­
logical range d elineation o f th e Little Smoky h erd by th e A lberta
Fish and W ildlife Division (ASRD, 2010). Because th e Little Sm oky Is
such a dynam ically changing landscape due to Industrial practices,
w e chose to confine our stu d y to a single tim e period, and as such,
all spatial and caribou data co rresp o nd to th e w in te r 2 0 0 4 -2 0 0 5 .
All geographic d atasets u sed In th e stu d y are d escribed In detail
In H ebblew hlte et al. (2010). A m ajo r source o f d a ta consists of
radio-collared GPS location d a ta of A lberta caribou. A to tal of 5225
location p oints w ere o btain ed for 13 fem ale Individuals from th e
Little Smoky In w in te r (N ovem ber-A prll) 2 0 0 4 -2 0 0 5 . U sing cari­
bou GPS point sam ples, th e sp atlo tem p o ral d istrib u tio n of each
caribou w as b u ilt and sto red w ith in an ArcGlS d atab a se as tim e s­
ta m p s corresponding to a 4 -h Interval. A dditional d a tasets Include
v ector re p resen tatio n s of roads, pipelines, seism ic lines, and w ell
sites valid to the y ear 2005, and a raster-b ased elevation m odel
(DEM) and land-cover m ap b o th at a spatial reso lu tio n of 30 m.
The land-cover m ap Is based on Landsat 5TM Im agery of 2005 and
Includes 12 classes th a t are d eem e d to be biologically relevant
to w oodland caribou (Table 1). For Inclusion In th e ABM m odel,
all v ector layers w ere rasterized to a reso lu tio n of 45 m, w ith th e
land-cover m ap and DEM resam p le d to th e sam e resolution. The
45 m resolution chosen re p rese n ts an o p tim izatio n o f c o m p u ta ­
tional perform ance w hile reflecting th e biologically realistic size
of the foraging patch of caribou (Bailey and Provenza, 2008). Fur­
th erm o re, because actual caribou are sensitive to Industrial featu res
up to 250 m and 1 km aw ay d ep en d in g on th e ir ty p e (Dyer et al.,
2002), th is spatial resolu tio n has no m ajo r biasing effect on th e
caribou ag e n t’s ability to perceive th em .
For In tegration w ith th e ABM, four ra ste r m ap s w ere g e n ­
erated from th e geographic d ata se ts to re p re sen t th e physical
en v iro n m en t w h ere th e caribou ag en ts are located: (1) a forageavallablllty m ap, (2) an en erg etic -c o n ten t m ap, (3) a p red atlo n -rlsk
m ap, and (4) a digital elev atio n m odel. A value of lichen forage
availability w as associated to each o f th e land-cover classes, th e
ranking of w hich (0 -5 , w ith 5 rep re sen tin g th e hig h est forage) w as
d eterm in ed directly from m ultiple lite ra tu re sources (Edm onds
and Bloomfield, 1984; W eclaw and H udson, 2004; D unford et al.,
2006; N eufeld, 2006; M etsaranta, 2008). Based on th is ranking, an
energetic co n ten t w as th e n assigned to each cover class. The d es­
ignation of en ergetic co n te n t w as calculated from caribou dally
energetic Intake rates (H ollem an et al., 1979; Kum pula, 2001), and
Is described In m ore detail In th e section “M odel Im p lem e n ta ­
tio n - F” (Table 1). Equally, each land-cover class w as assigned a
p red atlo n -rlsk score, ranked from 0 -5 (w ith a score of 5 d e n o t­
ing the h ighest risk). These scores w ere also derived from th e
literatu re (Neufeld, 2006; Sm ith e t al., 2000; Dyer e t al., 2002;
W eclaw and H udson, 2004; S orensen et al., 2008; Table 1). Sim ­
ilarly to th e land-cover d ataset, th e In d u strlal-featu res d ata se t
w as assigned forage-avallablllty and e n erg etic-co n ten t, and ra n ­
dom ly allocated a m ed iu m -h ig h p red atio n risk score (I.e., a value
of eith er 4 or 5; Table 1). This m ed iu m -h ig h allocation random ly
assigned Is based on th e prem ise th a t caribou are know n to be Influ­
enced by Industrial featu res (V istnes and N ellem ann, 2008) and
respond accordingly. At th is point, how ever, w e to o k a conservative
approach, and did not differen tiate b e tw e e n th e relative Influences
of forestry vs. p etro leu m In d u stry practices. Instead trea tin g b o th
Industry ty p es sim ilarly (m edium -high). Finally, w e te rm caribou
responses as being ‘p re d a tlo n ’-sensltlve to Im ply th a t caribou are
likely to have sim ilar resp o n ses b e tw e e n landscapes th e y perceive
as risky and features th e y perceive as risky (w h e th e r It Is due to a
higher p red atio n risk, or a distu rb an ce; Frld and Dill, 2002).
To provide an en v iro n m en t to th e agents and allow th e ir m o v e­
m e n t from one cell to th e n ex t cell, a virtu al grid w as overlaid
on th e four m ap s described above. Each cell In th e ABM spatial
e n v iro n m en t th erefore possesses four values: a forage-avallablllty
score, an en erg etic content, a p red atlo n -rlsk score, and an ele­
v ation (m ). W h ereas forage-avallablllty and p red atlo n -rlsk scores
are fixed (and It Is ju s t th e a g e n t’s w illingness to respond to
th e m th a t varies), th e energy c o n te n t of th e cells Is d ep leted (and
hence varies) w h e n ag en ts forage. Sources of biological Inform ation
n ecessary for th e caribou ABM p ara m e te riz a tio n Include caribou
a g e n ts’ b lo-en erg etlc functions, spatial m em o ry (w orking and ref­
erence), and learned decision-m aking processes. The values for
th ese variables w ere e ith e r derived or o b tain ed from an extensive
lite ratu re review , and are fu rth e r described In th e follow ing section.
2.2. M odel conceptualization and param eterization
The un d erly in g p rem ise of th e m odel Is th a t an Individual’s
Internal state Influences how It perceives Its e n v iro n m en t and
hence drives Its declslon-m aklng process (H ouston and M cNamara,
1992). The m odel consists of one category of agents, th e caribou,
re p re sen ted as a cognitive entity. It has a m en tal re p re sen tatio n of
Its env iro n m en t, can plan Its activities, and has a m em o ry of prof­
itable and safe patches. Specifically, th e caribou ag en t can balance
Its n eed s to m e e t Its dally en erg etic re q u ire m e n ts against th e need
to m inim ize en erg etic loss In o rd er to m ee t Its lo n g -term goal of
rep ro d u ctiv e success. The caribou m u st also consider Its pred atio n
risk, for w h ich It m u st also balance, since relatively safer locations
are no t alw ays th e m o st profitable.
Fig. 2a Illu strates th e sequence o f step s Involved In th e cari­
bou a g e n t’s decision m aking as Im p lem en ted In th e ABM. At each
tim e step, th e ag en t first assesses Its en erg etic state: It d e te r­
m ines w h e th e r It has reach ed Its dally en erg etic re q u irem en ts and
by w h a t m agn itu d e, and w h e th e r It w ill have en o u g h energetic
reserves (and by w h a t m ag n itu d e) to have a successful b irth at the
end of th e season (‘A’ In Fig. 2a). At th is stage It also senses the
Im m ediate risk In Its e n v iro n m en t as w ell as th e forage availabil­
ity (‘B’). It th e n d eterm in es w hich fitness-m axlm lzlng goal Is m ost
Im p o rtan t to trad e off against th e others, and does so by assess­
ing w h ich goal has reach ed a m in im u m th resh o ld . Based on this
d eclslon-m aklng h eu ristic (‘C’), th e ag en t e ith e r forages, rum inates,
or m oves to a n ew location (‘D’). The ag en t th e n u p d ate s Its energy
reserves, b o th gained and lost th ro u g h Its actions (‘F’), and com ­
m its to m em o ry any profitable or safe locations e n co u n te red (‘F’).
Each step Is described In d etail below , w ith a p re se n tatio n of the
p a ra m e te r values used to p a ram eterize and calibrate th e m odel.
2.2.1. Assessing states (A)
2.2.1.1. Daily energy requirement. A caribou’s m in im u m dally e n e r­
getic re q u ire m e n t (DFR) ranges b e tw e e n 22 and 3 3 M Jd a y ^ ^
according to d ifferent literatu re sources (M cFwan and W hitehead,
1970; Boertje, 1985; Kum pula, 2001). W e th erefo re set this range
to corresp o n d to th e m in im u m and m ax im u m th resh o lds, resp ec­
tively, th a t an ag en t m u st strive to obtain. The ag en t w ill gain energy
only w h en It chooses to forage. Once 24 h have passed, DFR Is reset
to zero, regardless of w h e th e r th e m in im u m dally th resh o ld w as
m et. The ag en t can carry over u p to lOMJ o f excess energy at the
end of th e day, o r a deficit o f n o t m ore th a n - 5 MJ (as caribou
are ex cellent p ro te in recyclers and th erefo re excessive energetic
deficits are unrealistic; P arker et al., 2005). These restrictions w ere
te ste d In th e m odel and w e found th a t average dally Intake rates
fell w ell w ith in th e th resh o ld range. O ur agents do not die from
starv atio n since p re d a tio n Is th e m ain source of m ortality, w hich Is
also In accordance w ith th e survival o f all th e actual caribou used
for co m parative p u rp o ses durin g th e 2 0 0 4 -2 0 0 5 w in ter. W e do not
assum e th a t Increased en erg etic ex p en d itu re m ay re n d e r caribou
m ore vuln erab le to p red atio n (McLellan et al., 2011).
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
21
Table 1
List o f land-cover classes and industrial features in th e Little Smoky region. Each land cover and industrial feature is assigned a value for its food availability, energy content,
and pred atio n risk attrib u tes. These values are used in th e ABM, w ith risk random ly assigned e ith e r 4 o r 5 to industrial features.
Lichen availability^
Energy c ontent (MJ)*^
Predation risk*^
M ean elevation (m)
Land cover^
Closed conifer forest
O pen conifer forest
Mixed forest
Deciduous forest
M uskeg/w etland
Shrub
Herb
Barren
W ater
Glacier
Eorest cutbiocks
Burn
5
4
2
1
3
1
1
0
0
0
1
0
1.14
0.86
0.29
0.15
0.58
0.15
0.15
0
0
0
0.15
0
1
3
3
4
2
4
4
5
5
0
4 or 5
4 or 5
1178
1194
1086
1030
1139
1144
1146
1179
1158
1175
1170
1231
Industrial features^
Roads, seism ic lines, pipelines
W ell sites
1
1
0.15
0.15
4 or 5
4 or 5
1110
1000
Edm onds and Bloomfield (1984), W eclaw and H udson (2004), Dunford et al. (2006), N eufeld (2006), M etsaranta (2008). Values are fixed.
H ollem an e t al. (1979), K umpula (2001). Values change in d ep en d ently o f lichen-availability scores as th e agent consum es th e resource.
Neufeld (2006), Sm ith e t al. (2000), D y e re t al. (2002), W eclaw and H udson (2004), Sorensen et al. (2008).
Original ra ster m aps: M cDermid et al. (2009), H ebblew hlte et al. (2010).
Original v ecto r m aps: H ebblew hlte e t al. (2010).
a
- Osity Energy M$)(lml»|ion
* Seasonal Energy Conseivatian
Decfsion-I
module
Environmgnl
U pdate behav io u r rrwde
lim e ste p
VES
Slay
Fig. 2. (a) Steps involved in th e caribou ag en t’s decision m aking (m odified from Chion e t al., 2011); and (b) flow chart exam ple o f th e behavioral tradeoffs m ade by a caribou
agent w h e n it has m et its daily energetic requirem ent, is in term ed iately energetically stressed long term , and faces different levels o f p redation risk.
2.2.12. Reproductive energy requirement. Caribou lose on av er­
age 15% of th e ir a u tu m n m ass over w in ter, via fat and p ro tein
catabolism (B radshaw et al., 1998). A loss g re a ter th a n 20% of body
m ass results in reproductive failure. T herefore, assum ing a 132 kg
caribou, th e ag e n t’s energetic-loss buffer (i.e., m in im u m and m ax ­
im um th resh o ld s) is set b e tw e e n 710 and 947 MJ, respectively, for
th e w in te r (see B radshaw et al. (1998) for th e calculation of con­
verting m ass-loss to energy). At each tim e step, th e ag en t assesses
its reproductive energy re q u ire m e n t by calculating th e projected
cum ulative n et en ergetic loss over th e course of th e season:
At tim e step t:
n et en erg y = cum ulative energy lost - cum ulative energy gained
(1)
p rojected loss =
n et en erg y \
nt
)
hotal >
(2 )
w h ere nt re p resen ts th e n u m b e r of tim e step s elapsed, and
hotai is th e to tal n u m b e r of tim e step s in th e sim ulation (8640
step s = 180 days).
22
C.A.D. Sem eniuk e t a l .j Ecological Modelling 243 (2012) 18-32
This projection is a sim piified v ersion of sta te -b a se d p red ic­
tive th eo ry (M angei and Ciark, 1986; Raiisback et ai., 1999), in
w hich th e organism optim izes th e c u rre n t choice in strateg y based
on th e forecasted conditions. The ag en t’s su b seq u en t foraging
decision w iii d epend on w h ere its pred ictio n iies w ith resp ect to
th e th resh o id range, its daiiy en erg etic intake, and its p red atio n
risk (see ‘B ehaviorai Strategies’ beiow ).
2.2.2. Sensing the environm ent (B)
Two aspects are considered in th e capacity of caribou to sense its
en v iro n m en t: risk and forage. The caribou ag en t can sense th e risk­
iness of its en v iro n m en t u p to 1 km in radius, and resp o n d s to th is
risk at tw o scaies: w ith in a 500 m buffer (i.e., during in tra -p a tch
foraging), or b e tw e e n 500 and 1000 m (w h en assessing w h e th e r
adjacen t foraging areas are equaiiy or m ore safe for in te r-p a tch
travei). These buffers corresp o n d to k n o w n average avoidance d is­
tan ces of caribou to in d u striai featu res (D yer et ai., 2002; W eciaw
and H udson, 2004), and p re d a to r p ercep tio n ranges o f u n g u iates
(Laporte et ai., 2010).
Caribou ag ents can aiso perceive food avaiiabiiity in th e ir envi­
ro n m e n t at tw o scaies: in tra -p a tc h forage, co rresp o n d in g to eight
neighbouring ceiis, and w ith in a 450 m in radius for area-restricted
(i.e., in ter-p a tch ) searches (Johnson et ai., 2002). in addition, cari­
bou agents are aiso capabie of assessing th e eiev atio n o f th e ir
cu rren t iocation, as w eii as th a t of th e ir im m ed iate su rro u n d in g s
so th a t th e y m ay choose th e ceiis w ith m inim ai eievation w h en
deciding to travei at iow en erg etic cost.
2.2.3. Behavioral strategies (C)
The baseiine m odei, w hich w e te rm th e ‘Energetics and Pre­
d atio n ’ m odei, assum es th a t an a g e n t’s goai is to find an optim ai
baiance to its daiiy energetic req u irem en ts, its ionger te rm re p ro ­
ductive energy req u irem en ts, and its p red atio n -risk m inim ization.
Based on its energy caicuiations and a ssessm en t of risk, a caribou
can find itseif e ith e r at th e iow end or b eio w its en erg etic and risk
th resh o id s (iabeied as ‘io w ’), w ith in th re sh o id range (‘m ed iu m ’),
or at the high end or above its th re sh o id s (‘h ig h ’). Daiiy energy
accum uiated is considered iow w h en th e am o u n t o f gross energy
accum uiated is b eiow 25.5 MJ, m ed iu m b e tw e e n 25.5 and 29 MJ,
and high w h en above 29M Jday^^. Risk of rep ro d u ctiv e faiiure is
iow w h en th e am o u n t of p ro jected n e t-e n e rg y iost is beiow 789 MJ,
m ed iu m b e tw e e n 789 and 868 MJ, and high at g re a te r th a n 868 MJ.
N ote th a t the actuai iow er and u p p e r th re sh o id ranges rem ain inexpiicit, so as not to un d u iy influence th e a g e n t’s decision-m aking,
if th e re su ita n t agent activity cu im in ates in at ieast an average
of 22 MJ accum uiated p er day, for instance, th is b eh av io r is m ore
‘em e rg e n t’ th a n if w e w ere to teii th e ag en t th a t it m u st achieve
at ieast 22 MJ day^^. Finaiiy, w h e n sensing its en v iro n m en t, if th ere
are any features (in d u stry o r o th er) w ith in its p ercep tio n range w ith
a p red atio n risk score of 5, th e agent accords a risk of 5; otherw ise,
it assesses th e m ean p red atio n risk of its su rro u n d in g h ab itat. A risk
of 5 is considered high, 3 - 4 is m edium , and 1 - 2 is iow. The foiiow ing ruies generaiiy appiy in governing w h ich action th e ag en t w iii
u n d ertak e:
(1) if th e agent is highiy energeticaiiy stressed - sh o rt-te rm (i.e.,
daiiy), p red atio n risk becom es irreie v an t (even if high) and th e
ag en t atte m p ts to find a profltabie p atch in w h ich to forage.
(2) if th e ag en t is energeticaiiy flush, m inim izing p red atio n risk
tak es precedence, w ith th e ag en t seeking o u t as safe or safer
iocations in w hich to forage, if necessary.
(3) if th e ag en t is energeticaiiy stressed, it w iii a tte m p t to trav ei at
io w est cost (i.e., using m inim ai eievation); if th e ag ent is not
stressed, it w iii travei in reiativeiy safe iocations.
(4) The m ore energeticaiiy stressed, th e iess w iiiing an agent is to
taxi iong distances.
(5) An ag en t w iii be risk adverse at iow to m ed iu m daiiy energetic
stress u niess it is sim u itan eo u siy highiy stressed iong-term .
T hen it w iii sw itch to m ore risk -p ro n e b ehaviors (i.e., seek out
profltabie p atch es before safe p atch es in w h ich to forage).
(6) An agent w iii chose to reiy on previousiy visited sites in w hich
to forage (i.e., access m em ory) in stead of feeding im m ediateiy
w h e n eith er: (a) th e su rro u n d in g p red atio n risk is m edium
an d /o r iow, b o th th e c u rre n t and ad jacen t sites are of iow for­
age avaiiabiiity, and th e ag en t is in term e d iate iy energeticaiiy
stressed, or (b) p red atio n risk is high, no ad jacen t safer sites are
p resen t, and th e ag en t is in term ed ia te iy energeticaiiy stressed.
(7) An ag en t foraging w iii n o t oniy red u ce th e en erg etic co n ten t
of th e ceii it occupies, b u t th e ag en t w iii no ionger feed w ith in
it durin g th e sam e feeding bout, if aii n eig hbouring ceiis have
b een used, th e ag en t w iii th e n search for a ceii w ith in a 450m radius in w hich to feed th a t is of h ig h er en erg etic content,
if n one is avaiiabie, th e ag en t w iii th e n ran d o m iy recaii a high
forage-avaiiabiiity ceii from m em ory, and taxi to w a rd s it.
These strateg ies are based on b o th generai p rincipies of b eh av ­
iorai ecoiogy (e.g., fo rag in g -p red atio n risk tradeoff; Lima and Diii,
1990), and literatu re sources of u n g u late m o v em en t ecoiogy (e.g.,
m em o ry and feeding-site selection, Bailey and Provenza, 2008;
in terp lay b e tw e e n in tern al state and m o v em en t decisions. M orales
et ai., 2005; sw itches in m o v em en t m odes, O w en-Sm ith e t ai., 2010;
Fig. 2b).
2.2.4. Path m ovem ent algorithms (D)
Caribou ag en ts engage in four d ifferent ty p es o f m ovem ent,
reflecting d ifferent scaies of h a b itat selection:
(1) local, in tra -p a tc h foraging, w h ere caribou m ove one ceii at a
tim e;
(2) in te r-p a tc h foraging, aiso k n o w n as ‘area-re stric te d searching’
(up to 450 m, and u p to tw o ceiis at a tim e);
(3) ran d o m taxiing to an u n k n o w n iocation u p to 6 km in distance,
e ith e r choosing iow -risk ceiis o r iow -eiev atio n ones and tra v ­
eling b e tw e e n 2 and 4 ceiis at a tim e; and
(4) revisiting a previousiy visited p atch ran d o m iy d raw n from
m em ory, if highiy stressed, p atch chosen is at th e sam e or iow er
eievation th a n th e ag e n t’s c u rre n t position. This m o v em en t tr a ­
v erses 2 -4 ceiis p e r tim e step, and th e agent aiso chooses the
m in im u m -eiev atio n ceii in th e p a th to its u ltim a te destination.
To p re v e n t d ete rm in a te m odei runs, sto chasticity is in tro ­
duced into th e a g e n t’s m o v em en t decisions at d ifferent scaies.
W h en foraging, caribou agents ran d o m iy choose one of th e ir
eight n eighbouring ceiis; w h e n m oving b e tw e e n foraging iocations
(in ter-p a tc h travei), ag en ts aiso ran d o m iy select one ceii (satisfying
th e criteria of b eing e ith e r of th e sam e or g rea te r forage avaiiabii­
ity or safety). These m o v em en ts reflect th e to rtu o sity of m o v em en t
p ath s typical o f a re a -re stricte d searches (O w en-S m ith et ai., 2010).
F urtherm ore, ag en ts do n o t have p erfect know ledge ab o u t th e ir
landscape. A gents em ploy a co rrelated h a b ita t-d e p e n d e n t w alk
(K ram er-Schadt et ai., 2004; Borger e t ai., 2008) w h en taxiing,
w h e re b y dispersal directio n is d e p e n d e n t on previous direction
and local h a b ita t q uality (i.e., iow risk or iow eievation). The agent
has no prior know ledge of th is d estin atio n iocation; it sets out
w ith a p re -d e te rm in e d traveling distance chosen from a ran d o m ex p o n en tial d istrib u tio n th a t is m e a n t to reflect actuai caribou
traveling distance of h a b ita t selection for lichen (6 km; M ayor et ai.,
2007). Lastly, w h en ag en ts access th e ir m em ory, th e y random iy
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
pick a location th a t has b een sto red b e tw e e n 7 and 45 days prior
(see ‘M em ory’ below ).
2.2.5. Gaining and losing energy (E)
2.2.5.1. Energetic intake per tim e step. Caribou consum e an y w h ere
b e tw e e n 0.88 and 3.52 kg of lichen p e r day (H ollem an et al., 1979;
K um pula, 2001). Because caribou sp en d b e tw e e n 50% and 88% of
th e ir day actively foraging (R o m in g eret al., 1996; Kum pula, 2001),
th is corresponds to caribou consum ing, on average (i.e., 69%, or
16.5 h day^^), 0.027-0.1 0 6 kg/30 m in. (th e m o d el’s tim e step).
Using a 10.8 MJkg^^ conversion rate of m etabolizable en erg etic
c o n ten t of lichen (K um pula, 2001), caribou are assu m ed to o btain
b e tw e e n 0.29 and 1.14 MJ of energy p e r foraging bout. The a m o u n t
gained w as linked to h a b ita t type, so th a t th e h a b itat ranked w ith
th e highest forage availability (i.e., o pen conifer forests) received
an energy co n ten t of 1.14 MJ; forage availability (FA) o f4 = 0.86 MJ,
FA 3 = 0.58, FA 2 = 0.29, etc. (Table 1).
In addition, a caribou agent m odifies its e n v iro n m en t as it for­
ages. Specifically, after com pleting a ‘forage’ action at a location,
it p erm an en tly reduces th e en erg etic c o n te n t of th e cell so th a t it
becom es eq uivalent to a h a b itat ty p e w ith forage availability = 3
(if originally ranked 4 o r 5), or 2 o r 1 (if originally ranked 3 or
2, respectively). N ote th a t th e cell’s c o n te n t does n o t d ep lete to
zero, as it is u n realistic for a caribou to consum e th e en tire lichen
availability in a 45 m x 45 m area in one h alf hour. The d ep letio n is,
how ever, p erm an en t, since lichen re -g ro w th ra te s are slow, and can
take up to 4 m o n th s to recover, doing so durin g su m m e r m o n th s
only (Gaio-Oliveira et al., 2006).
2.2.5.2. Energetic loss per tim e step. At each tim e step, reg a rd ­
less of th e action und ertak en , th e caribou ag en t ex p end s energy
on its m etabolism (see ‘M odel C alibration’ for details). W hen
m oving from cell to cell, th e ag en t fu rth e r expends energy on
locom otion, w ith various costs a ttrib u te d to: (1) an increased
o r decreased change in elevation, and (2) th e absolute elevation
o f th e cu rren t position (h ig h er elevation im plies g re ate r snow
d epth, w hich incurs a g re a ter trav elin g cost; S tuart-S m ith e t al.,
1997). W h en foraging, th e ag en t su stain s an additio n al cost of
cratering th ro u g h snow (w hich rem ain ed a c o n sta n t th ro u g h w in ­
ter; see Table 2 for values). These losses are additive, and th e ir
cum ulative value drives caribou re p ro d u ctiv e-m o tiv ated h ab itat
selection.
2.2.6. M em ory (E)
The caribou agent is able to store h a b itat a ssessm en t in fo rm a­
tio n into a variable list resu ltin g in tw o ty p es of m em ory: reference
and w orking. The reference m em o ry sto res locations for profitable
feeding and low -risk areas (as w ell as th e ir associated elevation),
w h ereas th e w orking m em o ry is used to avoid backtracking on
recently d ep leted p atch e s (Van M oorter et al., 2009). Caribou agents
store th ese patch locations for u p to 45 days (reference m em ory) as
a m oving w indow , and subsam ple locations no few er th a n 7 days
after initial visit (w orking m em ory; m ed ian = 13 days). These val­
ues w ere derived from actual caribou-GPS d a ta th a t w ere u sed to
d eterm in e th e tim e interval of a caribou re tu rn in g to a previously
visited site (i.e., ‘tim e -to -re tu rn ’; u n p u b lish ed d ata). These data
closely coincide w ith a stu d y o f elk {Cervus elaphus) site fidelity,
w hich found a m ean re tu rn tim e of 11 days (W olf et al., 2009).
C aribou agents only access th e ir m em o ry w h e n no suitable forage
and safe areas are available at b o th th e in tra - and in ter-p a tc h levels
and w h en th e y are energetically stressed . This rule accom m odates
m em ory-based m ovem ent, k n o w n to play a role in u n g u late sys­
tem s in w hich resources are pred ictab le in tim e and space (M ueller
and Fagan, 2008). It is also based on th e info rm atio n prim acy m odel
o f ex ploratory and foraging behavior, w hich p osits th a t if h u n g er
is great, th e anim al w ill choose to search fam iliar locations th a t
23
have in th e p ast reliably yielded food ra th e r th a n explore unfam iliar
locations (Inglis et al., 2001).
The ABM w as calibrated using conserved ratios of th e costs
o f differen t caribou activities th a t are considered stan d ard in
caribou en erg etic studies. For instance, th e en erg etic cost of for­
aging (w hich in co rp o rates costs of sm all m ovem ents, rum inating,
ingesting) is 1.44 tim es th e value used for lying dow n; w alk­
ing costs (n o t accounting for th e additio n al ex p en d itu re due to
uphill m o v em en t a n d /o r in snow ) are 1.81 tim es higher (Fancy
and W hite, 1985). U sing th ese estab lish ed ratios, w e u sed a
variety of en erg y values in th e calibration process to re p re ­
sen t th e restin g m etabolic rate. The final values chosen for all
scenarios in th e ABM w ere based on w h e th e r each produced
sim u lated en erg etic o u tp u ts co n sisten t w ith th re e criteria: (1)
th e daily energy gain by th e agent is w ith in know n rep o rted
ranges (2 2 -3 3 MJ d a y ^ ^ McEwan and W h iteh ead , 1970, Boertje,
1985); (2) th e daily en erg etic e x p en d itu re app ro aches th a t w hich
has b e en re p o rted for free-living R. tarandus during w in te r
(28.7M Jday^^; Gotaas e t al., 2000); and (3) th e p ro p o rtio n of
tim e sp e n t foraging (i.e., ingestion and ru m in atio n com bined
w ith area -restric te d searching) is b e tw e e n 50% and 85% of the
a g e n t’s daily activity b u d g e t (R om inger et al., 1996; Kumpula,
2 0 0 1 ).
In each o f th e scenarios, agent caribou had a m ed ian daily energy
intake o f 2 2 -2 8 MJ day^^ (w ith in re p o rted lite ra tu re values), and
ex p erien ced a daily loss of en erg y b e tw e e n 26 and 28M Jday^^.
These values of intake and e x p en d itu re are sufficient for body m ain ­
ten an c e at th e sta n d a rd m etabolic rate (SMR: 403 kj kg“°-^^ day ^^;
Fancy and W hite, 1985; Barboza and Parker, 2006). Lastly, th e aver­
age p ro p o rtio n of tim e ag en ts sp e n t foraging ranged from 65% to
77% (Table 3). Because th ese criteria w ere n o t im posed as to p -d o w n
rules (i.e., ag en ts w ere n o t in stru cted to a tta in th ese values explic­
itly), and because th ese m ultiple p a ra m e ters fell w ith in th e range
o f validity for each scenario tested , w e felt confident th a t o u r m odel
w as sufficiently calibrated.
2.3. Sim ulation fram ew ork
Because energy acquisition, en erg y conservation, and
p red atio n -risk m in im izatio n are issues w hich research ers deem
im p o rta n t to caribou in w in te r (e.g., P arker et al., 2005; C am eron
et al., 1993; B radshaw et al., 1998), w e have chosen to te s t five
m ain b ehavioral strateg ies w ith altern ativ e h y p o th eses in the
caribou ABM, beginning w ith th e ‘E nergetics and P redation’ m odel
and th e n d ecom posing th e fram ew o rk into biologically relevant
altern ativ e strategies:
(1 )T h e caribou a g e n t’s goal is to find an optim al balance
b etw e e n its daily energ etic re q u ire m e n ts (D), its lo n g er-term
rep ro d u ctiv e energy re q u irem en ts (R), and its p red atio n -risk
m in im izatio n (P). K nown as th e ‘E nergetics and P red atio n ’ sce­
nario (DRP);
(2) L ong-term
rep ro d u ctiv e
re q u ire m e n ts
are
irrelevant.
R esponses to perceived p re d atio n risk are u n ch anged. Known
as th e ‘Energy A cquisition’ scenario (DP);
(3) R eproductive req u ire m e n ts take preced en ce w h en th e risk of
rep ro d u ctiv e failure is high, regardless of daily req u irem en ts.
R esponses to perceived p re d atio n risk are u n ch anged. Known
as th e ‘Energy C onservation’ scenario (RP);
(4) Industrial featu res are n o t d elib erately avoided. K nown as the
‘P red atio n -in sen sitiv e’ scenario (DR);
(5) M inim izing risk tak es preced en ce over m axim izing daily
energy and m inim izing rep ro d u ctiv e energy loss. K nown as the
‘P red atio n -h y p ersen sitiv e’ scenario (P).
C.A.D. Sem eniuk e t a l .j Ecological Modelling 243 (2012) 18-32
24
Table 2
Values for param eterizing an d calibrating th e caribou ag en t in th e ABM.
Caribou agent p aram eters
Value
Source
W eight
Daily energy req u irem en ts
132 kg
2 2 -3 3 MJ
Expected reproductive energy loss
Daily energy e x p en d itu re in w in te r
7 1 0 -9 4 7 MJ
738kJkg-o-75 day-1
B radshaw et al. (1998)
McEwan and W hitehead
(1970), Boertje (1985),
K umpula (2001)
B radshaw et al. (1998)
G otaas e t al. (2000)
Percent tim e sp en t foraging
50-88%
R om ingeret al. (1996),
K umpula (2001)
Fancy and W hite
(1985), Boertje (1985),
F ancy(1986)
Incremental costs o f activities over
resting metabolic:
Foraging
W alking
A dditional m ovem ent costs:
Uphill
D ownhill
H orizontal high elevation
(> 1185m )
H orizontal low elevation
Notes
1.44
1.81
3.640 kJ k g -i k m -i
1.293 k jk g -i k m -i
2 .6 4 k jk g -i
M emory:
Reference
W orking
Range perception:
Forage - in trap atch
Forage - in terp atch
Boertje (1985), G ustine
et al. (2006)
”
3.5 kJ k g -i X h
1.9 kJ k g -i X h
F ancy(1986)
45 days
7 -4 5 days, m edian
13
U npublished d ata
W o lfe t al. (2009),
unpublished data
45 m
450 m
Johnson e t al. (2002)
Forage - taxi
Predation - intrapatch
Up to 6 km
500 m
Predation - interpatch
1km
28.7 M jday-^ fo ra
132kg caribou; used
for verification of
m odel calibration.
Used for verification of
m odel calibration.
Model calibrated w ith
5 2 0 k jk g -° ‘^^day-^ for
foraging.
653 kj kg“°-^^ day-^ for
w alking.
G ustine e t al. (2006)
“
1 .7 2 k jk g -i
C ratering costs:
High elevation
Low elevation
Used for verification of
m odel calibration
Known as ‘area
restricted search’.
M ayor e t al. (2007)
Dyer et al. (2002), W eclaw
and H udson (2004)
Laporte e t al. (2010)
Table 3
C om parison o f calibration p aram eters b e tw ee n literatu re-so u rced caribou bio-energetic values and th e sim ulated ou tp u t of five alternative behavioral-strategy scenarios.
A ctual values
M edian daily energy
gain (MJ, quartiles)
M ean daily energy loss
(MJ, ±SD)
Percent tim e spent
foraging (%, range)
2 2 -3 3
-2 8 .7
5 0 -8 8
Energetics and
Predation (DRP)
Energy A cquisition
(DP)
Energy
C onservation (RP)
P redation-insensitive
(DR)
Predation hypersensitive (P)
25.8
(25.5-25.9)
-2 8 .1
(0.65)
76.9
(6 2 -9 5 )
25.5
(24.3-25.7)
-2 8 .1
(0.64)
69.6
(58-84)
25.6
(23.6-25.7)
-2 6 .4
(0.16)
71.2
(61 -9 3 )
29.2
(29.1-29.4)
-2 5 .9
(0.55)
74.6
(63 -9 4 )
22.2
(21.9-22.4)
-2 7 .8
(0.51)
64.9
(54-85)
For sim plicity, w e use th e te rm ‘p re d atio n ’ to d en o te caribou
p ercep tio n of landscapes and featu res perceived to be of high
risk and of disturbance, as resp o n ses are assu m ed to be sim ilar,
in th e scenario ‘Energy A cquisition’, th e agent does n o t consider
its reproductive energy at all, and a tte m p ts to m axim ize its daily
energetic req u irem en ts w hile m inim izing its risk. Essentially, th e
ag en t ignores th e cum ulative energy lost th ro u g h o u t th e sim u la­
tion, and its actions are dev o ted to foraging in its im m ed iate or
adjacen t environs, or taxiing to n ew locations, d ep en d in g on th e
q uality of th e su rro u n d in g area an d /o r perceived risk, in th e ‘Energy
C onservation’ scenario, m inim izing rep ro d u ctiv e failure tak es
p recedence. Accordingly, a high rep ro d u ctiv e failure value (i.e.,
a projected value of g rea te r th a n a 868 MJ loss) w ill d efault th e
ag en t into the im m ediate action of e ith e r foraging straightaw ay,
o r m oving to an adjacen t area to forage d ep en d in g on th e degree
o f p red a tio n risk, regardless of th e c u rre n t daily energy already
accum u lated, in th ese tw o scenarios, p red a tio n risk is given con­
sid eratio n dep en d in g on th e in teractio n o f th e level o f risk and how
energetically stressed th e ag en t is. W ith th e ‘P red atio n -in sen sitiv e’
scenario, th e ag en t does n o t perceive in d u strial featu res as being
any m ore risky th a n th a t of th e su rro u n d in g en v iro n m ent. As such,
in d u strial featu res take on th e p red atio n risk value o f th e ir im m e­
d iate n eighbours: a cutblock rev erts to a p red atio n risk score of
1 (equ iv alen t to closed conifer forest) b u t retain s its low forage
availability, and a linear featu re (one pixel w ide, b u t m any pixels
iong), tak es on th e m ajo rity value of its eight neighbours). A gent
rules rem ain u nchanged. Lastly, in th e ‘P red atio n -h y p ersen sitiv e’
scenario, th e agent concerns itself w ith m inim izing p red atio n risk
only, and assu m es th a t a m inim al d aily-energy gain is sufficient
and th a t repro d u ctiv e loss is n o t an issue: R esuitantiy, th e agent
is driven to reach its daily m in im u m en erg etic re q u irem en t only.
Once having accu m u lated 22 MJ o r m ore, it concerns itself w ith
m inim izing risk. H owever, if th e degree of risk is high, th e agent
w ill ignore its c u rre n t energy level (unless it is excessively low).
D espite th e d ifferent w eig h t an ag en t accords to a behavioral s tra t­
egy and w hich one tak es precedence, in all o f th e scenarios tested
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
th e ag en t w ill have access to th e four p a th -m o v e m e n t behaviors
th a t are available In the ‘Energetics and P red atio n ’ scenario, If n ec­
essary: local foraging, area -re stricte d search, ran d o m taxiing, and
accessing m em ory.
The m odel Is ru n w ith one agent. The drastically red u ced p o p u ­
lation of LSM Is cu rren tly estim ate d at 78 Individuals (ASRD, 2010),
and so w e have assum ed th a t conspeclfic attrac tio n Is n o t a driving
force In o u r system unlike In o th e r u n g u late herds. A dditionally,
w hile gro u p ed Individuals m ay benefit from th e dilu tio n effect, w e
do n o t expect conspeclfics to have a large Im pact on th e carib o u ’s
a n ti-p re d a to r b ehavior since th e ir d o m in an t p red ato r-av o ld an ce
strateg y Is spatial separatio n . Each caribou agent Is assum ed to be
132 kg In w eight, pregnant, and ex p ected to lose m ass over th e
course of w in te r (B radshaw et al., 1998). Accordingly, at th e sta rt
o f sim ulation, th e ag en t’s cum ulative en erg etic loss Is set at 0. The
sim ulation Is also begun w ith th e ag en t at a dally energy Intake of 0.
Because caribou have d istin ct su m m er and w in te r h a b itat re q u ire ­
m en ts (Including forage), th e ag en t also begins th e sim ulation w ith
no w in te r locations sto red In Its m em ory, as It w o u ld be evolutlonarlly costly to rem em b e r locations long te rm w h ich th e anim al u ses
only If energetically or risk stressed . Lastly, th e sta rt coordinates
for th e ag en t correspon d s to one o f th e th irte e n Initial locations of
th e actual GPS-collared LSM caribou. To acco u n t for e n v iro n m e n ­
tal stochasticity and for variability In th e m odel o u tp u ts, ru n s are
replicated five tim es p e r 13 ‘carib o u ’, for a to tal of 65 ru n s p e r sce­
nario. The sim ulation resu lts co rresp o n d to th e average and m edian
o f th e values obtained In th ese replicates.
The m odel has a rep o rtin g m ech a n ism describing th e Instances
o f various events at each tim e step o f 3 0 m ln . on a 3100 km^
grid surface (1786 x 1619 (45-m ) cells). The tim e and areal step
are ap p ro p riate tem p o ral and spatial reso lu tio n s to cap tu re th e
variability of foraging b ehaviors ch aracteristic of u n g u lates at th e
spatial level of th e food p atch (O w en-Sm ith et al., 2010). Im por­
ta n t o u tp u ts of th e m odel Include th e spatial d istrib u tio n of th e
agent, w hich are rep rese n te d as a series of p o in t locations (x, y
coord inates and tim e stam p). This allow ed com parison w ith th e
observed d ataset for GPS-collared caribou, w hich Is also com prised
o f p o in t locations. Eor th is purpose, p o in t locations for sim u lated
caribou w ere su b-sam p led at 4 -h Intervals sim ilar to th e te m p o ­
ral reso lu tio n for GPS-collared caribou. The m odel also rep o rts th e
cum ulative am o u n t of energy lost at th e end of th e sim ulation. The
ABM sim ulates over a period of 180 days, th e sp an of w in te r In
Alberta.
The sim ulation m odel w as d eveloped using th e p latform
NetLogo V. 4.1.2 (W llensky, 1999; freely d o w nloadable from
h ttp ://ccl.n o rth w estern .e d u /n e tlo g o /d o w n lo a d .sh tm l), and v eri­
fied for p ro p er program m in g functioning th ro u g h progressive
debugging and u n ce rta in ty testing.
2.4. M odel validation
Our ABM Is validated using a p a tte rn -o rie n te d app ro ach th a t
Involves com paring m odel o u tp u ts w ith observed d ata using m u l­
tiple p a tte rn s across different scales. This p rotocol Is based on th e
assu m p tio n th a t p a tte rn s are b o th th e defining characteristics of
a system and are Indicators of essen tial un d erly in g stru c tu re s and
processes (G rim m et al., 1996). By observing m u ltiple p a tte rn s at
different hierarchical levels and sp atlo tem p o ral scales, POM eval­
u ates m odel b ehavior and red u ces p a ra m e te r u n certain ty . The
g re a te r th e n u m b er of real w o rld p a tte rn s th e m odel can p redict
sim ultaneously th e g re ate r th e confidence In th e m odel (G rim m
and Railsback, 2005; Topping et al., 2010).
Several m etrics w ere u sed to com pare sim u lated and observed
p a tte rn s for validation purposes. These w ere a com bin atio n of (1)
sp atlo tem p o ral p attern s, and (2) spatial d istrib u tio n p a tte rn s at dif­
feren t scales. The sp atlo tem p o ral p a tte rn s w e ex tracted from th e
25
Table 4
S patiotem poral p attern s observed in actual caribou used for com parison w ith the
m odel outputs. Early w inter: m onths o f N ovem ber and D ecember. Late winter:
m onths o f M arch and April.
S patiotem poral p a tte rn used
D escription
Overall ranked land-cover
usage (m ost to least) in w in te r
Closed conifer
M uskeg/w etland
O pen conifer
M ixed forest
Cutblocks/burns
Deciduous forest
Shrub/herb
Barren
W ater
(C C -47.7% )
(MW - 29.6%)
(OC - 8.9%)
(M F-5.1% )
(C B -3.7% )
(D F - 1.7%)
(S H - 1.7%)
(BA - 1.5%)
(W -0 .1 % )
Differences in m ajor
land-cover classes used (>85%)
be tw ee n early and late w inter.
CC - slight decrease
MW - increase
OC - decrease
(48.8-45.3%)
(24.2-34.9%)
(15.0-2.7%)
Change in use o f low er
elevation
decreased elevation
used in late w in te r
(1 2 1 1 -1 1 8 6 m )"
decreased step length
in late w in te r (m edian
1.9-1.2 km day-1 )b
Daily single peak of
increased movement*^
Change in m ean daily distance
traveled
Daily step length pattern
“ S tudent’s t-test assum ing unequal variances: t= - 1 3 .2 5 , p < 0 .0 0 f,
—2215, H i a j e .w i n t e r —2213.
I" M ann-W hitney t/= -9 .4 3 , P < 0.001, I I e a r l y . w i n t e r = 1931, I l i a t e .w i n t e r = 1990.
' Significant (p < 0.001) negative polynom ial fit to th e second d egree o f daily cari­
bou m ovem ent displaced over a 4 -h interval.
t t e a r l y .w i n t e r
caribou G PS-telem etry d a ta are described In Table 4. The spatial d is­
trib u tio n p a tte rn s w e u sed for co m p ariso n com prise: (1) th e m ean
100% m in im u m convex polygons (MCPs) for Individuals (I.e., spatial
e x te n t of Individuals), (2) th e to tal MCP (I.e., for h erd range), and (3)
th e degree o f overlap In areal coverage b e tw e e n actual herd MCP
and sim u lated h erd MCPs (to com pare a g re e m e n t In space used).
These v alidation m etrics w ere g en e ra te d from p o in t location data
o f sim u lated and real caribou and analyzed for land cover and eleva­
tio n usage In ArcGlS 9.2. M inim um convex polygons and dally step
d istrib u tio n s w ere calculated using H aw th ’s Tools In ArcGlS 9.2.
All o th e r sim u lated o u tp u ts w ere g e n e ra te d by NetLogo’s reporting
m ech an ism and analyzed In JMP 8.0 (SAS Inc.).
Eor ev aluating th e d ifferent scenarios tested , th e sp atlo tem p o ral
p a tte rn s w ere com pared to those o f th e actual caribou by a sim ple,
su m m ed ranking of th e degree to w hich p a tte rn s w ere m atched.
To com pare th e sp atial d istrib u tio n p attern s, w e u sed a m odified
distance m ethod, th e ro o t m ean sq u are deviance (RMSD) to com ­
p are actual field d ata w ith sim u lated o u tp u t, and a ranking m ethod
to evaluate th e overall b est-fit scenario based on a to ta l Indicator
function (Plou et al., 2007). The to ta l Indicator (Tl) for each scenario
Is:
Tl =
E
lActual - Slm ulatedpl
IA ctual - Slmulatedgestl ’
(3 )
P=i
w h ere p Is th e p a tte rn for com parison, and Best Is th e p a tte rn w hose
deviance from th e actual value Is th e sm allest.
3. Results and discussion
In th is section w e p re se n t th e blo-energetlc, sp atlo tem poral, and
spatial d istrib u tio n p a tte rn s th a t em erg ed from o u r a ltern ate sce­
narios, com pare and c o n trast th e results, and discuss th e m In light
o f w h a t Is k n o w n ab ou t LSM caribou specifically, and boreal caribou,
generally.
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
26
1400 '
t/i
+1
—I 1200 ■
2 7%
llI
a;
4-7
c
a;
Q.
X
o
>
Ef
Oi
c
(U
d;
>
'43
20.5%
1000 BOO <
GOD '
400 '
200 -
E
3
CJ
0 '
DRP
DP
RP
DR
P
Fig. 3. M ean cum ulate energy lost over w in te r for agents in each alternative sce­
nario. Values over bars correspond to p ercen t body m ass lost assum ing a 132 kg
pregnant female. Grey horizontal b a r rep resen ts range o f expected cum ulative
energy loss fo rw in ter. DRP: ‘Energetics and P redation’; DP: ‘Energy A cquisition’; RP:
‘Energy C onservation’; DR: ‘Predation-insensitive’; P: ‘P redation-hypersensitive’.
a.
Area restricted search
P atch departure
Patch immfgration
b.
Fig. 4. M ovem ent paths, (a) D iagram m atic rep resen tatio n o f typical m ovem ent
behavior, including: a re a-restricted search, p atch -d ep artu re, taxis to w ard s a new
location, and p atch im m igration (after Schick et al., 2008). (b) M ovem ent path of
an actual fem ale caribou from th e study, (c) M ovem ent p ath o f a sim ulated caribou
agent from th e Energetics and P redation scenario.
3.1.
rep ro d u ce sm all-scale high to rtu o sity m o v em en ts In tersp ersed by
stralg h t-lln e p ath s - e.g., co rrelated ran d o m w alks, Levy flights,
m u ltl-b eh av lo ral m odels (see Schick et al., 2008). W hile th ese
m o v em en t ty p es are coded Into o u r m odel, w e assigned th e m to
specific behaviors: a re a-re stric te d foraging vs. taxiing vs. re tu rn -to p revlous-slte. These b ehaviors w ere. In tu rn , driven by th e ag en t’s
Internal state and p e rcep tio n of Its e n v iro n m en t. Therefore, the
exhibition of th ese d ifferent m o v em en t behaviors, w hile available
for use by agents, w as n o t p re -d e term ln e d n o r g u aran teed.
3.1.3. Pattern 3: land-cover use
A ctual caribou did n o t use th e land cover classes In th e sam e
p ro p o rtio n as th e ir availability on th e landscape. This d en o tes th a t
caribou actively select h a b ita t for reasons o th e r th a n random . Sim ­
u lated caribou u sed land-cover classes sim ilarly to actual caribou
w ith resp ect to th e overall order, w ith th e ex ception of th e lesser
used land-cover classes. A gents In th e Energetics and Predation
(DRP), Energy C onservation (RP), and P red atlo n -sen sltlvlty (P) sce­
narios freq u en ted th e sh ru b /h erb land cover relatively m ore th a n
deciduous forest, w hile th e ag en ts In th e Energy A cquisition (DP)
scenario visited b a rre n areas m ore often th a n th e deciduous forest.
A dditionally, agents In th e P red atlo n -h y p e rsen sltlv e (P) scenario
also freq u en ted open conifer forests less often th a n th e y did m ixed
forests (Elg. 5).
Caribou ag en ts te n d e d to overuse closed conifer forests w h en
com p ared to actual caribou, due to th e b ro ad rankings of the landcover classes. H abitat rankings w ere based on landscape traits th a t
have th e g re a test and m o st co n sisten t Im pact on caribou b lo en ­
ergetlcs: forage availability, elev atio n costs, and p red atio n risk. By
Including a m ore d etailed friction m ap, for exam ple, a ttrib u te s such
as slope, aspect, and te rra in ruggedness, w e could possibly red is­
trib u te th e ag en t use of th e landscape, m aking som e areas m ore
or less a ttractiv e (e.g., som e open conifer areas can be ranked a 5
for forage availability), b u t w e could also p o ten tially obfuscate the
tru e, u n d erly in g processes driving h a b ita t selection and m ovem ent.
This Is because at presen t, th e relatio n sh ip b e tw e e n th e additional
landscape a ttrib u te s and b loenergetlcs a n d /o r p red atio n risk Is less
clear, and th e Influence o f th e se tra its on caribou reso u rce-selectlon
functions Is variable as w ell (Neufeld, 2006; H ebblew hlte et al.,
2010). N onetheless, o u r agents did use th e different LSM land cov­
ers In very sim ilar relative ord erin g th a t th e actual caribou did, b o th
of w h ich are n o t In p ro p o rtio n to th e relative availability of the landcover classes. These land-cover class choices by ag en ts w ere not due
to m o d el-d riv en guidance, b u t w ere based on a confluence of p e r­
ceived forage ability and risk and m ed iated by ag en t energetics n o t on a p reference for one land-cover ty p e over another.
Comparison o f patterns
3.1.1. Pattern 1: bio-energetic
In all scenarios, agents ex p erien ced a cum ulative en ergetic
deficit by seaso n ’s end, typical of o v er-w in terin g fem ales (Elg. 3).
This energetic d eb t did no t occur via an explicit, perfu n cto ry
Instruction (I.e., agents w ere no t given rules to m ee t a dally
energetic ex p enditure); b u t Instead It Is a consequence of agents
choosing costly dally activities w hile still satisfying th e ir dally
m ain ten an ce req u irem en ts. There w as a g re a t deal of v ariation
In th e overall am o u n t of energy lost b e tw e e n scenarios how ever,
m itigated by w h e th e r th e ag en t w as given th e fitness-m axlm lzlng
goal of conserving reprod u ctiv e energy and b y Its resp o n siv en ess
to Industrial features. This Is discussed In c o n tex t w h e n considering
sp atlal-d lstrlb u tlo n al p a tte rn s (p a tte rn 8, below ).
3.1.2. Pattern 2: m ovem ent paths
C aribou agents exhibited typical m o v em en t ty p es (ex em p li­
fied In Elg. 4a) regardless o f scenario (Elg. 4b,c). M any m odels can
3.1.4. Pattern 4: relative change in use o f m ajor land-cover
classes betw een early and late w inter
A ctual caribou, w h e th e r In early or late w in ter, use closed
canopy forests w ith th e sam e frequency (albeit slightly reduced
In late w in ter) (Elg. 6). M usk eg /w etlan d s are used m ore frequently
In late w in te r by caribou, and alternatively, th e relative use of open
conifer forests Is red u ced In late w in ter. The use of th ese landcover classes In th e sim u latio n s exhibited th e sam e tre n d w ith the
ex ception of th e open conifer class. In th e ‘E nergetics and P reda­
tio n ’ (DRP) scenario, th e use o f th e open conifer land cover did
n o t change b e tw e e n early and late w in te r (2.91 -2.96%), w h ereas In
th e Energy A cquisition (DP) scenario, th e use of th is class slightly
Increased as w in te r p rogressed (2.35-2.59%). Again, th e u n d er-u se
of th is cover class Is based on on th e b ro ad -ran k ln g s a ttrib u te d to
th e land cover categories. N onetheless, w e do n o t ex pect future
refin em en t of landscape a ttrib u te s to affect th e choice of best-fit
scenario resu lts: If anything. It w o u ld red istrib u te cells m arked as
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
27
83.0-1
,J
10.0-n
^ ■ C lo s e d Conifer
I IM jskea/W etland
d ] O p e n Conifer
Mixed Forest
I ICutbiockfBurn
o
c0)
3
O* 7.5o
IH!Z3 Deciduous Forest
Shrub/Herb
i I Barren
^
W ater
3
O 5.0*
T3
C
2.5-
0 . 0*
X .
t
T
A vailable
DP
nHn
Innfl
n fln
DRP
A ctual
DR
RP
Caribou Land C over Use
Fig. 5. Land cover used by actual caribou (‘A ctual’) com pared to th e availability o f land-cover classes on th e Little Sm oky landscape (‘A vailable’) and th e sim ulated o u tp u t of
th e alternative scenarios.
Closed Conifer
E]
I
I/)
early w in te r
I late w in te r
GO.O
3
■M
C
OI
50.0
Muskeg/Wetland
u
1_
O)
^
An n
Open Conifer
1
0.0
U sed
DRP
OP
RP
DR
P
U sed
DRP
DP
RP
DR
P
U sed
H
n
DRP
DP
ii
RP
tl
DR
m
P
Fig. 6. Use o f th e th re e m ajor land-cover classes in early and late w in te r by actual (‘Used’) and sim ulated caribou.
high forage availability w ith o u t alterin g th e un d erly in g behaviorai
strateg ies of agents.
3.1.5. Pattern 5: change in use o f lower elevations
The m odei repro d u ced th e p a tte rn th a t caribou in late w in te r use
areas significantiy iow er in elevations, regardless of th e scenario
te s te d (S tu d en t’s t-te st assum ing u n eq u al v ariances: ALL t< - 9 .0 ,
p < 0.001, ^gaf|y_v^,i^ter “ 23,400, ^|atg_v^,i^ter “ 23,400; Fig. 7a).
The use of low er elevations in late w in te r by th e caribou agents
coincides w ith w h a t w e observe in th e actuai caribou in th e Little
Smoky. U sing io w er elevations can be a function o f agents in creas­
ing th e ir use of iand-cover ty p es such as m uskeg (Table 1) since
resources in closed canopy forests w ere b eing actively reduced,
in com bin atio n w ith actively selecting io w er areas to conserve
energy ex p en d itu re as w in te r progresses, regardless of iand-cover
class. T here w ere no ruies governing agents to freq u en t iow er
elevations (or m u sk eg /w etian d s) explicitly in late w in ter. These
ecoiogicaiiy realistic m o tiv atio n s p ro d u ced very sim ilar p attern s
to actuai caribou in th e LSM. Using io w er elevations is a com m on
b ehaviorai strateg y of boreal caribou, as th e y have been observed
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
28
bO
1190
El E arly w in te r
□ L a lfr w i t i t e r
stro n g e r effect as correlates of p red atio n risk th a n th e presence
of live p re d ato rs (and associated cues; Verdolin, 2006). N ever­
theless, th e daily m o v em en t rates recorded for sim u lated caribou
w ere w ell w ith in th e range re p o rted in th e lite ra tu re for w oodland
caribou in w in te r (0.64 ± 0 .1 3 km /day: S tu art-S m ith et al., 1997;
0.9-2.5 k m d a y ^ ^ : Eerguson and Elkie, 2004; 0.4 7 -1 .2 km day^^:
G ustine e t al., 2006). M oreover, w o o d lan d caribou b o th in LSM and
elsew h ere have lo w er m o v em en t rate s in late w in te r sim ilar to our
ag en t caribou (Eerguson and Elkie, 2004; G ustine e t al., 2006). This
red u ctio n in m o v em en t rates m ay be a function of increased snow
d e p th at w in te r’s end, or, as B radshaw e t al. (1997) also suggest, it
can be an energy-saving strategy.
2000
b.
ISO O
1200
E ariy w ln lp r
Q
SO O
□ L ate w in te r
Fig. 7. (a) M ean differences in elevation used by actual and sim ulated caribou in
early and late w in ter: and (b) m edian differences in daily step lengths by actual and
sim ulated caribou in early and late w inter.
m oving across to p o g rap h y w ith low er en erg etic costs relative to
w h a t is available (i.e., caribou select te rra in th a t facilitated level or
dow nhill m o v em en ts m ore often th a n uphill m o v em en ts; Johnson
et al., 2002).
3.1.6. Pattern 6: decrease in daily distance traveled
The scenarios diverged w ith resp ect to w h e th e r m ed ian daily
distance trav eled w as lo w er in late w in te r th a n in early w in ­
te r as w as observed w ith actual caribou (Fig. 7b). The Energetics
and P redation (DRP), Energy C onservation (RP), and P redationhypersen sitive (P) scenarios rep ro d u ced th e ex p ected p attern ,
w h ereas in th e P redation-in sen sitiv e (DR) scenario, agents traveled
m ore during a late w in te r’s day. In th e Energy A cquisition (DP) sce­
nario, agents trav eled sim ilar m ed ian daily distan ces th ro u g h o u t
w in ter. Like changes in elevation, th e seasonal p a tte rn s recreated
by an agent w ere not ‘h ard -c o d e d ’ in to th e m odel. These p a tte rn s
w ere a consequence of increased cum ulative en erg etic d eb t based
on agent decisions - n o t of in stru ctio n s to b ehave differently in late
w inter.
The overall daily m o v em en t rates of agent caribou w ere low er
th a n actual caribou in th e Little Smoky. W e believe th a t th is is
due to th e strong positive skew of step len g th s by certain in d i­
vidual caribou th a t m oved g rea t distan ces durin g a 4 -h interval
(e.g., 10 km). These events w ere restricte d to isolated occurrences
th a t m ay have been in response to a d istu rb an ce on th e la n d ­
scape or p re d a to r avoidance. W e did no t explicitly m odel p red atio n
events or indeed include w olves in th e ABM as additio n al ag en ts or
objects for tw o specific reasons: w e have no specific d ata on th e
e n co u n te r rates of w olves and caribou in LSM (for exam ple, as in
W h ittin g to n et al., 2011), and w e do n o t believe th a t in corporating
infrequent, ran d o m flight in itiatio n b eh av io r of ag en ts w ould gain
us any addition al insight into th e u n d erly in g im p etu s of caribou
m ovem ent. Secondly, a caribou’s ‘landscape of fear’ is an ex trem ely
effective o p e ra n t in shaping an in d ividual’s p e rcep tio n of risk. This
response is especially applicable in te rre stria l p re d a to r-p re y sys­
tem s in w hich h ab itat ch aracteristics have b e e n sh o w n to have a
3.1.7. Pattern 7; single peak in daily activity
D uring a 24 -h cycle, actual caribou stead ily increased th e ir step
len g th from Oh (m idnight) u n til it reach ed a peak at 8h00. This
p a tte rn w as rep ro d u ced to som e e x te n t by all scenarios as they,
too, display a circadian m o v em en t p attern , sh o w n by a significant
negative q u ad ratic fit to th e ir step len g th d ata (log tran sfo rm ed
to satisfy assu m p tio n s of n orm ality) recorded at 4 -h intervals. A
closer insp ectio n of th e m ed ian s re p o rted for each tim e interval
reveals th a t only th e Energetics and P red atio n and th e P redationinsensitive scenarios pro d u ced a single daily peak. The rem aining
scenarios exhibited tw o daily peaks se p arated by 8 h, each (Table 5).
The display of a peak in daily activity d en o tes th a t agents are
ind eed engaging in various activities; a co n stan t ste p -len g th rate
in stead w o u ld suggest th a t ag en ts w ere (1) insensitive to th e ir
in tern al sta te/a n d o r th e ir surroundings, or (2) in th e e x trem es of
e ith e r energ etic deficit or surplus. Secondly, th is z en ith in daily
activity levels is also a realistic p h en o m en o n , em u latin g actual
b ehaviors of anim als affected by circadian events. O ur m odel
th erefore d e m o n stra tes b o th in te rn a l (i.e., m odel arch itectu re) and
biological ro bustness.
By ranking each scenario b ased on th e e x te n t to w hich th ey
rep ro d u ce th e actual, g en e ra te d sp atio tem p o ral p a tte rn s in com ­
p arison to th e o th e r scenarios, and su m m in g th e se scores to
produce an overall ranking, th e b est-fit scenario is sh ared b etw een
‘Energetics and P red atio n ’ and ‘Energy C onservation’ (Table 6).
3.1.8. Pattern 8: spatial distributions
The sp atial-d istrib u tio n p a tte rn s reveal th e g re a te st p a tte rn
divergence b e tw e e n th e altern ativ e scenarios (Table 7). Individ­
ual sp atial ex ten t, h erd range, and degree of spatial overlap w ith
actual caribou w ere sensitive to th e degree in w hich caribou w ere
w illing to trad e off energetics vs. p red atio n risk. W h en risk w as
ignored, ag en ts did n o t engage in p red atio n -sen sitiv e foraging,
and w ere capable of m eetin g th e ir sh o rt- and lo n g -term e n e r­
getic needs. W hile w e know th is to be an u n realistic strategy, w e
could still ex p ect th is o utcom e in a h erd w ith a sm all industrial
footprint. Indeed, in a stu d y o f LSM th a t sp an n ed from 1979 to
1984 - before th e first cutblock a p p eared on th e landscape and
w ith v ery little oil and gas in d u strial dev elo p m en t, fem ale caribou
had a re p o rte d annu al w in te r range (km ^) of 147 ± 3 0 (Edm onds,
1988; sim ilar to o u r sim u lated 153 km^ in th e P redation-insensitive
scenario). W h en p red atio n risk w as considered in o ur ABM, cari­
bou ag en ts trav eled in w id e-ran g in g distan ces and d irections as a
m in im izatio n -strateg y , un less th e ir en erg etic need s b ecam e p ress­
ing. They w ere th e n less inclined to trav el far, and relied m ore on
retu rn in g to previously visited sites, resu ltin g in a m ore restricted
range th a t coincided w ith actual caribou (i.e., th e E nergetics and
P redation scenario). This realistic strateg y has a solid th e o re ti­
cal basis: h o m e-ran g e p a tte rn s have b een sh o w n to em erge w ith
sim u lated anim als tracking a dynam ic resource landscape using a
biologically plausible tw o -p a rt m em o ry system , i.e. a referenceand a w o rk in g -m em o ry (Van M oorter et al., 2009). O ur ABM
reach ed sim ilar conclusions, th u s em phasizing th a t th e inclusion
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
29
Table 5
M edian step lengths (m ) at 4 -h intervals. Bolding den o tes th e peaks.
Hour
Scenario
Actual
0
4
8
12
16
20
159
186
523
368
365
182
Energetics and
Predation (DRP)
Energy Acquisition
(DP)
Energy
C onservation (RP)
Predation-insensitive
(DR)
136
143
141
140
135
126
185
195
184
194
178
169
178
192
188
190
179
165
109
Predation-hypersensitive
(p)
185
193
192
204
188
173
111
113
111
103
93
Table 6
Ranking o f descriptive p attern s by how closely th e y m atch actual p attern s o f actual caribou In LSM.
S patlotem poral pattern s
Scenario
Land cover ranking
Change in
land-cover use
Increase use of
low er elevation
D ecrease in daily
distance
Peak in daily
activity
Overall ranking
(total score)
Energetics and P redation (DRP)
Energy A cquisition (DP)
Energy C onservation (RP)
Predation-insensitive (DR)
Predation-hypersensitive (P)
1
2
1
1
3
2
3
1
1
1
1
1
1
1
1
1
2
1
3
1
1
2
2
1
2
1 (6 )
4 (1 0 )
1 (6 )
2 (7 )
3 (8 )
Table 7
C om parison o f spatial d istrib u tio n p attern s. RMSD: root m ean squared deviance (w ithin scenario evaluation), and Tl: to tal indicator (b etw een scenario evaluation). The low er
th e scores for b o th RSMD and Tl, th e closer th e sim u lated scenario m atches th e real-w orld pattern s of LSM caribou.
Spatial-distribution
pattern s
Actual
Energetics and
Predation (DRP)
Energy A cquisition
(DP)
Energy
C onservation (RP)
Predationinsensitive
(DR)
Predation
hypersensitive (P)
M ean individual
MCP(km2 ±S.E.)
Herd MCP (km2)
Proportion spatial
overlap
RMSD
Total indicator
271
(38)
1867
1
297
(37)
2578
0.715
444
(55)
3257
0.573
446
(55)
3202
0.583
153
(19)
2628
0.709
458
(57)
3611
0.517
411
3.0
809
10.1
111
10.0
445
6.6
1013
11.3
of m em o ry processes can be a crucial co m p o n en t in th e stu d y of
u n gulate foraging system s w ith h o m e-ran g e behaviors.
3.2. Ecological context o f best-fit scenario
Our detailed stu dy of caribou d istrib u tio n s offered us Insights
Into th e an im al’s declslon-m aklng process as b eing th e u ltim ate
confluence of Individual behavior, physiological constraints, and
fine-scale environm ental Influences (P atterso n e t al., 2008). E stab­
lished p a tte rn s helped us to develop a m odel w ith en o u gh detail to
reproduce th e sy stem ’s essen tial dynam ics th a t w as at once based
In physiological realism , y et w ith o u t excess co m plexity (Railsback
and Johnson, 2011). W ith th e Little Sm oky region u n dergoing
rapid developm ent, w e did n o t w ish to d ilute th e stre n g th of our
com parisons w ith caribou from d ifferent years th a t w ere likely
experiencing different levels of distu rb an ce. H owever, th e p a tte rn s
w e chose are largely univ ersal p a tte rn s of e ith e r n o n -m lg rato ry
and boreal caribou or u n g u lates In general, and n o t necessarily
u nique to a specific h erd In a given year. W hile all five scenarios
w ere calibrated to faithfully rep ro d u ce dally caribou b lo e n e rg e t­
lcs and foraging tim e b u d g ets w ith little Intra-scenarlo variation,
th ere existed enough variatio n In th e se scenarios th a t w h e n w e
com pared how w ell th e y satisfied th e m ultiple p a tte rn s of actual
caribou, w e w ere able to show th a t one scenario Is th e m o st useful
for m odeling caribou o f th e Little Smoky. The scenario th a t m ost
con sisten tly produced p a tte rn s th a t coincided w ith actual caribou
data w as ‘E nergetics and P red atio n ’. In th is scenario, each of th e
th ree behavioral strateg ies - acquiring energy for dally use, con­
serving energy for repro d u ctiv e needs, and m inim izing predation.
w as given co n sid eratio n w h e n ev e r th e need arose, w ith energetic
n eed s taking precedence.
To lend fu rth e r ju stificatio n to th e ranking of th e altern ate cari­
b o u strategies. It Is helpful to In te rp re t th e m odel o u tp u ts In an
ecological context. A gents rep ro d u ced th e few est n u m b er of p a t­
te rn s exhibited by actual caribou In th e Energy A cquisition scenario,
since th e y did n o t co n sid er th e ir lo n g -te rm en erg etic reproductive
needs. A gents w ere m ore likely to ran d o m ly trav el to new locations
(as evidenced by th e ir spatial d istributions), since su rrounding
areas o f high risk b ecam e u n accep tab le and th e y w ere unw illing
to trad e off th ese costs against Increased foraging. A dditionally, at
th e end of th e sim ulation, caribou agents Incurred a cum ulative
en erg etic deficit corresp o n d in g to a m ass loss of approxim ately
27 kg (20.5%). A lthough It seem s Intuitive th a t m eetin g dally energy
n eed s w hile reducing th e risk of p red a tio n Is a likely strategy.
It Ignores th e considerable lite ra tu re w h ich states th a t relatively
sm all shifts In m ass resu lt In relatively large changes In caribou
p a rtu ritio n rate (C am eron and V er Hoef, 1994). In o th e r w ords. It Is
n o n -ad ap tlv e for a fem ale caribou to Ignore h e r rep ro ductive needs.
The second altern ativ e scenario, ‘Energy C onservation’,
acknow ledges th e en erg etic re q u ire m e n ts n ecessary to ensure suc­
cessful p artu ritio n . In th is scenario, caribou ag en ts are unw illing to
trad e off th e costs of future failed rep ro d u ctio n even th o u g h th e ir
dally n eed s have b een m et. As a result, ag en ts p erform ed w ell In
m atch in g th e p a tte rn s of real caribou, and lost a m inim al am o u n t
o f energy over th e w in te r (18.4 kg or 14% b o d y m ass). H owever,
because of th e ab u n d an ce of energy, ag en ts w ere also m ore likely
to engage In long-distance forays, and covered m ore area spatially
th a n actual caribou. In m an y anim al system s, ad aptive behaviors
30
C.A.D. Sem eniuk e t a l .j Ecological Modelling 243 (2012) 18-32
are u p d a te d as en v iro n m en tal conditions and individual state
change, and prediction is w idely accepted as essen tial to d ecision­
m aking (Levin, 1999). W hile real caribou m ay in d eed engage in
state-b a sed predictions, th e y do n o t do so at th e exclusion of
o th e r com peting strategies, in essence, th e fu n d am en tal difference
b e tw e e n the Energy C onservation scenario and th e real w orld
is th a t th e form er assum es anim als have p erfect foreknow ledge
w h e n in reality, anim als rarely do; i.e., th e ir pred ictio n s are based
on b est available assim ilated info rm atio n th a t has in trin sic error,
it is for th is reason th a t th e E nergetics and P redation scenario fits
b e tte r overall: th e agents still trad e off sh o rt- vs. lo n g -term needs,
th u s inexplicitly reflecting th e n atu rally occurring im perfection
involved in decision-m aking.
Eor th e estim ated rem ain in g 78 individual caribou, it w ould
ap p ear th a t available food is no n -lim itin g in a 31 OO-km^ range. This
occurrence provides the ability to te s t com p etin g hy p o th eses about
th e sensitivities of caribou to p red atio n , in th e first case, if caribou
are insensitive to in d u strial features, caribou should n o t m inim ize
th e ir exposure to th e m on th e landscape. And w ith food b eing in
such plentiful supply (as intraspecific co m p etitio n is a non-issue),
th e n caribou should be m ore th a n capable of m eetin g th e ir e n e r­
getic req u irem en ts over a sm all geographic area. These are indeed
th e resu lts w e observe from th e P red atio n -in sen sitiv e scenario,
w ith caribou agents reducing th e ir daily and landscape m o v e­
m en ts; how ever, th is w as a m ism atch to actual p a tte rn s produced.
M oreover, this scenario resu lted in agents losing an u n realistic esti­
m ated 0.3% in body m ass by w in te r’s end. it w ould th u s ap p ear
th a t p red atio n risk plays a significant role in influencing caribou
m o v em en t decisions. At th e o th er extrem e, how ever, if caribou are
hypersensitive to in d u strial featu res and a tte m p t to m inim ize th e ir
exposure by m oving aw ay from th e source w hile b eing capable
of m eetin g th e ir daily m in im u m en erg etic needs, th e n w e w ould
expect th e opposite outcom es. O ur resu lts confirm ed th a t having
p red atio n risk take preced en ce re su lted in highly unlikely en ergetic
deficits (a m ass loss of 27%) and th e g re a te st large-scale m o v em en t
p a tte rn s - again, a m ism atch w ith w h a t actual caribou displayed,
instead, th e E nergetics and P redation scenario provides a m ore
likely explanation: caribou resp o n d to th e pervasive p red atio n risk
of th e ir en v iro n m en t w h en th e y can afford to (and in doing so, incur
additional energetic costs) w ith en erg etic n eed s taking priority.
W hile th e re is incom plete u n d e rsta n d in g of th e m echanics b ehind
th e observed caribou avoidance of in d u strial featu res in Canada,
our m odel suggests it to be an in tuitive link to p red atio n risk, in
th is case th e source of p red atio n risk is th e in d u strial featu res th e m ­
selves, being perceived as caribou agents as e ith e r d irect or indirect
disturbance, an d /o r being associated w ith p re d a to r presence.
W hile our ABM does n o t m odel populatio n -lev el processes, w e
can infer consequences for caribou fitness based on th e b io e n er­
getics results. The p red o m in a n t energy re q u irem e n t for w in tering
caribou is m aintenance, and it m u st be m et chiefly by foraging
(A dam czew ski et al., 1993). T herefore, if a fem ale caribou ex p e­
riences b enign w in te r conditions, she can afford to increase h er
allocation of energy to rep ro d u ctio n . H ow ever, th e co ndition of
a fem ale caribou also has a d irect im p act on fetal viability and
su b seq u en t calf survival (C am eron et al., 1993; Post and Klein,
1999). if a fem ale caribou exp erien ces h arsh w in te r conditions (i.e.,
via increased snow d epth , p red atio n , a n d /o r disturbance), failed
rep ro d u ctio n can occur, m anifesting itself eith e r in th e form of
stillbirth, low b irth -w eig h t calves, or d eform ities (C am eron et al.,
1993), w ith th e la tte r tw o situ atio n s increasing calf v u lnerability
to pred atio n . W hile the absolute availability of w in te r food m ay
n o t be lim iting, th e need to m inim ize p red atio n risk an d /o r d is­
tu rb an ce can im pel fem ale caribou to a d o p t p red atio n -sen sitiv e
foraging th a t essentially resu lts in th e loss o f usable h ab ita t d espite
its u b iq u ity (W ittm er et al., 2005). Eunctional h ab itat-lo ss coupled
w ith increased ex p en d itu re of energy to m inim ize exposure to
perceived p red atio n risk can in d eed resu lt in fem ale caribou
becom ing n u tritio n ally stressed . Lastly, carry -o v er effects of previ­
ous n u tritio n al dep riv atio n m ay u ltim ate ly affect preg nancy rates
of caribou and hence p o p u latio n dynam ics if anim als are unable
to rep len ish reserves follow ing severe w in te r conditions (Parker
et al., 2009). C onsequently, b loenergetlcs can play a significant role
in caribou p o p u latio n processes.
in th e E nergetics and P redation scenario, th e m ean cum ulative
energy lost by caribou ag en ts w as eq u iv alen t to a 17% loss in body
m ass. This value is slightly h ig h er th a n th e 10-15% th a t caribou
are assu m ed to n orm ally loose of th e ir a u tu m n m ass du ring w in te r
(B radshaw et al., 1998). W hile n o t b eyond th e critical 20% loss, it
does suggest th a t acquiring en ough energy for b o th som atic and
rep ro d u ctiv e g ro w th m ay be an issue, in actuality, th e Little Smoky
herd, alth o u g h it has a high p reg n an cy rate, has one of th e low ­
est calf rec ru itm e n ts of A lberta herds, w ith a m e a n of 0.07 fem ale
calves p e r fem ale (range 0.01 -0 .1 1 ; ASRD, 2010); how ever, th e p o r­
tio n attrib u tab le to calf p red atio n vs. u nfit offspring or stillborns is
c u rren tly un k n o w n .
4. Conclusion
An unavoidable challenge in th e conservation o f endangered
species is th a t th e ir ecologies can so m etim es be poorly or only
broadly u n d ersto o d , m aking ta rg e ted conservation m an ag e m en t
particu larly difficult. ABMs as a tool can provide an sw ers w h en
know ledge is lim ited (Topping et al., 2010), and o u r cu rren t focus
on ABM v alidation by p a tte rn -o rie n te d m odeling (POM) d e m o n ­
stra te s th a t th e conclusions o u r m odel d raw s on th e behavioral
m otiv atio n s of caribou are robust. The p a tte rn s chosen in this study
refer to characteristic, n o n -ran d o m , identifiable sta tes of th e sys­
te m (G rim m e t al., 1996), and th e ro b u stn ess of th e ABM lies in
th e sim u latio n o f m ultiple p a tte rn s across d ifferent hierarchical
and sp atio -tem p o ral scales, and in th e ex p lo ratio n and co n trast of
alternative, com p etin g h y p o th eses o f h a b itat selection and m ove­
m ent. in particular, a m odel m ig h t be relatively likely to reproduce
fortuito u sly a single feature of th e system , b u t sim u ltan eous re p ro ­
d u ctio n of several system -lev el ch aracteristics is m uch less likely
(G rim m and Railsback, 2012). As such, o u r caribou ABM sheds
light on caribou behaviors, w hich can co n trib u te to discussions and
a ssessm en ts of boreal caribou recovery plans.
U nder c u rren t co n sid eratio n by th e C anadian federal go v ern ­
m e n t are four b ro ad m an a g e m e n t strateg ies pro p o sed for boreal
caribou: to u n d erta k e co o rdin ated and com p reh en siv e landscapelevel p lanning for caribou ranges, con d u ct p o p u latio n m onitoring,
and, w h ere our ABM m ay be p articu larly inform ative, to m anage
b o th caribou m o rtality and caribou h a b ita t to m e e t c u rren t and
future h a b ita t re q u ire m e n ts (E nvironm ent Canada, 2011a). Our
b est-fit scenario d e m o n strate s th a t caribou (in LSM) are sensitive
to in d u strial features on th e landscape th a t evoke a n ti-p re d a to r
resp o n ses and b io en erg etic costs even in th e absence of any explicit
p re d a to rs m odelled, in essence, m o rtality tools such as m anaging
p re d a to rs and a lte rn a te prey m ay stabilize p o p u latio n g ro w th rates,
b u t functional h a b ita t loss is still a serious issue w ith ensuing e n e r­
getic costs. M an ag em en t efforts should also en su re th a t caribou: (1)
are n o t increasingly energetically stressed by th e ir a n ti-p re d a to r
b ehaviors induced by actual p re d a to rs and in d u strial features on
th e landscape, and (2) have en ough high-forage, functionally avail­
able h a b ita t to m e e t th e ir en erg etic n eed s req u ired for som atic and
rep ro d u ctiv e g ro w th and ‘p re d a to r’ avoidance. W ith continuous
lan d -u se d ev elo p m en t in th e already highly in d u strialized lan d ­
scape, caribou m ay end u p allocating too m uch tim e and hence
energy avoiding p red atio n /d istu rb an ce, even th o u g h food avail­
ability m ay rem ain readily available. O n -th e-g ro u n d m an ag e m en t
efforts m u st th erefo re also include lim iting n ew d e v elo p m en t and
C.A.D. Sem eniuk e t al. / Ecological Modelling 243 (2012) 18-32
resto rin g old anthro p o g en ic changes in LSM. A lthough o ur focus
on LSM can be considered regional and re p re se n ts a h e rd in a
highly developed landscape, 28 local pop u latio n s of boreal cari­
bou across C anada are considered n o n -su stain in g (E nvironm ent
Canada, 2011 a). Our ABM has estab lish ed an investigative m e th o d ­
ology for establishing w h y caribou choose th e h ab itats th e y use,
and can be readily and easily a d ap te d to h erds of d ifferent ecotypes
(m o u n tain vs. boreal) experiencing varying levels of d evelopm ent.
Next, because conservation p lanning of w ildlife h a b itats also
involves th e analysis of h ab itat-lin k ed p o p u latio n d em ographics
u n d e r various land-use d e v elo p m en t scenarios, th e ABM can be
used as a scenario-plan n in g tool. By considering m u ltip le po ssi­
ble future landscapes w ith in a spatially explicit context, and th e n
m odeling caribou resp o n ses to th e changes in th e ir h a b ita t (both
sp atio tem p o ral and bio-energetic), scenario p lanning w ith ABMs
can offer m anagers a m eth o d for creating m ore resilien t co n ser­
vation policies by increasing u n d e rsta n d in g o f key u n certain ties,
incorporating altern ativ e persp ectiv es into con serv atio n planning,
and providing g reater resilience of decisions to surprise (McLane
et al., 2011). This is th e n ex t phase of o u r research focus.
Acknowledgments
This project w as funded by th e MITACS A ccelerate Program
in collaboration w ith ConocoPhillips Canada and tw o U niversity
Technologies In tern atio n al Scholarships aw ard ed to C. Sem eniuk.
Significant su p p o rt w as also p rovided by th e Schulich R esearch
Chair in GIS and E nvironm ental M odelling and a research g ran t
from GEOIDE (SSll-102), T ecterra, and ConocoPhillips Canada
a w ard ed to D. M arceau. W e w ould like to th a n k Nishad W ijisekara
for technical support, and Greg M cD erm id and Nick DeCesare for
th e ir invaluable assistance in providing d ata for th e project. Sup­
p o rt is also provided by th e A lberta D e p artm en t o f Sustainable
Resource D evelopm ent, British C olum bia M inistry of th e E nviron­
m ent, BC M inistry of Eorests, C anadian A ssociation of P etroleum
Producers, NSERC, Parks Canada, P etro leu m T echnology Alliance of
Canada, Royal D utch Shell, W e y erh au eser Company, A lberta Inno­
vates, A lberta C onservation A ssociation, and th e Y2Y C onservation
Initiative. W e also th an k M. Bradley, S. Cote, A. Dibb, D. H ervieux, N.
M cCutchen, L. Neufield, E. Schm iegelow , M. Sherrington, S. Slater,
K. Sm ith, D. Stepnisky, and J. W ittin g to n . R esearch w as con d u cted
u n d e r Alberta, BC, and Parks Canada, U niversities of M ontana, Cal­
gary and A lberta research and collection perm its.
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