2018 status Kangerlussuaq-Sisimiut caribou West Greenland. Technical Report No. 117

1
2018 S a us
Kange lussuaq-Sisimiu ca ibou
Wes G eenland
Technical Repo No. 117, 2021
G eenland Ins i u e o Na u al Resou ces
2
Ti le: 2018 s a us Kange lussuaq-Sisimiu ca ibou Wes
G eenland
Au ho s: Ch is ine Cuyle 1, Tiago A. Ma ques2, Iú i J.F. Co eia3,
Bea iz C. A onso3, Aslak Jensen4, Pe e Hegelund1 and
Jukka Wagnhol 1
1 G eenland Ins i u e o Na u al Resou ces, P.O. Box 570,
3900–Nuuk, G eenland
2 CREEM, Uni e si y o S And ews, School o Ma hema ics
and S a is ics, Sco land
3 Uni e si y o Lisbon, Facul y o Sciences, Po ugal
4 Sol iaq 15, lej. 203, 3900–Nuuk, G eenland
Se ies: Technical Repo No. 117, 2021
Da e o publica ion: 11 May 2021
Publishe : G eenland Ins i u e o Na u al Resou ces
Financial suppo : G eenland Ins i u e o Na u al Resou ces
Co e pho o: Aslak Jensen: Th ee polled ca ibou cows and a male cal ,
wi h op o one p ong isible.
ISBN: 978-87972977-0-4
ISSN: 1397-3657
EAN: 97887972977054
Ci ed as: Cuyle , C., Ma ques, T.A., Co eia, I.J.F., A onso, B.C.,
Jensen, A., Hegelund, P. & Wagnhol , J. 2021. 2018 s a us
Kange lussuaq-Sisimiu ca ibou, Wes G eenland.
Pinngo i ale i ik – G eenland Ins i u e o Na u al
Resou ces. Technical Repo No. 117. 79 pp.
Con ac add ess: The epo is only a ailable in elec onic o ma . PDF- ile
copies can be downloaded a his homepage:
h p://www.na u .gl/publika ione / ekniske appo e
G eenland Ins i u e o Na u al Resou ces
P.O. Box 570
DK-3900 Nuuk
G eenland
Phone: +299 36 12 00
Fax: +299 36 12 12
E-mail: in o@na u .gl
www.na u .gl
3
2018 s a us
Kange lussuaq-Sisimiu
ca ibou,
Wes G eenland
By
Ch is ine Cuyle 1, Tiago A. Ma ques2, Iú i J.F. Co eia3, Bea iz C. A onso3,
Aslak Jensen4, Pe e Hegelund1 and Jukka Wagnhol 1
1G eenland Ins i u e o Na u al Resou ces, P.O. Box 570, 3900–Nuuk, G eenland
2CREEM, Uni e si y o S And ews, School o Ma hema ics and S a is ics, Sco land
3Uni e si y o Lisbon, Facul y o Sciences, Po ugal
4Sol iaq 15, lej. 203, 3900–Nuuk, G eenland
Technical Repo No. 117, 2021
G eenland Ins i u e o Na u al Resou ces
4
[Emp y page]
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Table o Con en s
Summa y...................................................................................... 7
Resume (Dansk).......................................................................... 9
Eqikkaaneq (Kalaallisu ) ....................................................... 12
In oduc ion ............................................................................ 127
Me hods ..................................................................................... 20
Resul s ....................................................................................... 27
Discussion ................................................................................. 45
Acknowledgemen s .................................................................. 50
Li e a u e ci ed ......................................................................... 50
Figu es
1.
Bo de s o he No h egion con aining KS ca ibou…
Page 17
2.
A ea co e ed by 2018 ca ibou su ey o he No h egion (23,303 km2) …
Page 23
3.
The 19 line ansec s used in he 2018 ca ibou su ey o he No h egion…
Page 24
4.
KS ca ibou su ey 2018: explo a o y analysis plo s…
Page 29
5.
KS ca ibou su ey 2018: explo a o y analysis: g oup size dis ibu ion…
Page 30
6.
KS ca ibou su ey 2018: explo a o y analysis o ca ibou encoun e a e
Page 30
7.
Obse e e ec : his og ams: de ec ed dis ances o he wo obse e s
Page 31
8.
His og am o wo binning op ions o he ca ibou dis ance da a…
Page 31
9.
Rela ionship be ween g oup size and obse ed dis ances…
Page 33
10.
The de ec ed dis ances wi h he es ima ed de ec ion unc ion o e laid…
Page 34
11.
Es ima ed p obabili ies o de ec ion o each obse ed g oup size…
Page 36
12.
Rela i e dis ibu ion o ca ibou numbe s along he line ansec s…
Page 37
13.
Ca ibou densi y es ima es wi h co esponding con idence in e als…
Page 38
14.
Plo sampling g id example o o al a ea A di ided in o smalle plo s…
Page 54
15.
Example o a pa ch o und a wi h he ansec in he middle…
Page 57
16.
Hal -no mal ( op ow) and haza d- a e (bo om ow) de ec ion unc ions…
Page 59
17.
Possible shapes o he de ec ion unc ion when cosine adjus men s a e….
Page 60
18.
A good model o he de ec ion unc ion should ha e a shoulde …
Page 63
19.
Rugged e ain wi h good sunli condi ions and excellen almos comple e…
Page 69
20.
Po ions o line ansec s lown ac oss high ele a ions, Sisimiu Sou h…
Page 70
21.
Fla ligh combined wi h g ound showing h ough hin laye o snow.
Page 71
22.
Vege a ion poking h ough hin snow laye in la ligh o wi h shadows.
Page 72
23.
Thin snow laye wi h g ound showing h ough, o ocks and ege a ion.
Page 73
24.
Thin snow laye wi h ege a ion showing h ough combined wi h…
Page 74
25.
Dead g ound o he le o a ansec line
Page 75
26.
Fog wi h la ligh and g ound showing h ough hin snow laye .
Page 75
27.
Thin snow laye combined wi h g ounds showing h ough and in la ligh .
Page 76
28.
Va iable snow co e in ugged e ain, wi h and wi hou shadows…
Page 77

6
Tables
1.
La e win e popula ion pa ame e s, KS ca ibou, 1993-2010
Page 18
2.
Summa y o unp ocessed esul s…
Page 27
3.
The 2018 ca ibou su ey obse a ions lacking eco ded dis ances…
Page 28
4.
Summa y o he coe icien cha ac e is ics o he GLM …
Page 33
5.
Model compa ison ac oss h ee Con en ional Dis ance Sampling models…
Page 35
6.
De ec ion unc ion pa ame e s’ es ima es.
Page 35
7.
Encoun e a e es ima es pe sub-a ea (s a um) o ca ibou g oups…
Page 36
8.
KS ca ibou abundance es ima es and densi ies in he No h egion…
Page 38
9.
KS ca ibou mo emen , o lack he eo , in eac ion o helicop e …
Page 39
10.
KS ca ibou de ails mo emen , o lack he eo , in eac ion o helicop e …
Page 40
11.
Demog aphics o KS ca ibou, No h egion. Ma ch 2018.
Page 41
12.
G oup size ela i e o composi ion om demog aphics, KS ca ibou…
Page 43
13.
App oxima e ele a ions o ca ibou g oups obse ed…
Page 44
14.
Commonly used key unc ions & se ies expansions o de ec ion unc ion
Page 58
15.
Popula ion es ima es & minimum coun s ca ibou in G eenland, 1977-2018
Page 78
Appendices
1.
S a is ical me hods behind Dis ance Sampling
Page 54
2.
Dis ance Sampling Assump ions – sho summa y
Page 67
3.
Recommenda ions o imp o ing u u e su eys
Page 68
4.
Pho og aphs o KS ca ibou su ey condi ions Ma ch 2018
Page 69
5.
Pas and ecen G eenland ca ibou popula ion es ima es & minimum coun
Page 78
Raw da a may be accessed by con ac ing he G eenland Ins i u e o Na u al Resou ces, Depa men o
Mammals and Bi ds.
7
Summa y
Wes G eenland (sou h o 69°N) has six ca ibou (Rangi e a andus) egions
ha con ain se e al dis inc popula ions. This epo p esen s new
in o ma ion, om a su ey ca ied ou in 2018, abou he Kange lussuaq-
Sisimiu (KS) popula ion, which inhabi s he No h egion.
The KS ca ibou we e las su eyed in Ma ch 2010. Since hen, he e ha e been
long au umn hun ing seasons o unlimi ed ha es , as well as a win e season.
A new es ima e o abundance was o e due. Helicop e su eys in 2000, 2005
and 2010 used s ip ansec coun s. In Ma ch 2018, helicop e was again used,
and o he i s ime Dis ance Sampling me hods and analyses we e applied.
P e ious su eys ha e documen ed ha G eenland ca ibou a e
ex ao dina ily camou laged agains ypical en i onmen al condi ions in
G eenland, and how his could educe de ec ion o ca ibou p esen wi hin he
su eyed a ea. While almos anyone can de ec unning animals, s a iona y
animals can be di icul o de ec . To in es iga e he p opo ion o non-mo ing
ca ibou, he 2018 su ey eco ded ca ibou ligh esponses o lack he eo o
e e y g oup obse ed. Fligh mo emen was absen in almos 32% o all
ca ibou g oups obse ed du ing he su ey. This unde lines he impo ance
o skilled obse e s, as well as lying low and slow o make de ec ion o
ca ibou easie . The 2018 su ey’s Dis ance Sampling me hods and analyses
co ec ed o unde ec ed ca ibou and p o ided a obus es ima e o ca ibou
abundance and densi y (below). I is easonable o expec ha any su ey o
ca ibou would ha e some p opo ion o non-mo ing ca ibou p esen in he
su eyed a ea o he line ansec s. Addi ional esul s om wo G eenland
ca ibou su eys comple ed in 2019, will con i m whe he he obse ed
p opo ion in 2018, almos 1/3 non-mo ing ca ibou g oups, is a ypical o
ypical. I ypical, his sugges s ha a su ey da ase including ew
obse a ions o s a iona y ca ibou g oups would unde es ima e popula ion
size co espondingly.
In ea ly Ma ch 2018, obse ed KS ca ibou we e a ela i ely low ele a ions,
mean 361 m. A high p opo ion o polled KS cows was obse ed, 46%, which
is simila o ea lie epo s o his popula ion. Polled cows a e no likely due
o poo body condi ion, as is he common assump ion o popula ions
elsewhe e. Fo KS, polled cows may be he esul o a educed need o he
dominance con e ed by an le s, gi en hei small g oup sizes, and he xe ic
8
clima e educing he need o compe ing o eeding c a e s dug down h ough
deep snow o ob ain o age.
The Ma ch 2018 demog aphics we e imp o ed ela i e o obse ed in 2005
and 2010. Speci ically, la e win e cal (age ≤ 10-mon hs) pe cen age was ca.
21.8%, and cal ec ui men was ca. 42 cal es pe 100 cows. Howe e , 26-32%
o all cal es we e likely o phans wi hou dams. This sugges s ha he ue la e
win e alue o cal pe cen age was close o 17% and ec ui men ca. 31
cal es pe 100 cows. This le el o ec ui men is highe han he obse ed in
2005 and 2010. The Ma ch 2018 sex a io was ca. 51 bulls pe 100 cows. The
Ma ch 2018 demog aphics desc ibe a ca ibou popula ion ha appea s capable
o wi hs anding cu en ha es s, while he cal ec ui men is no high
enough o sugges he possibili y o apid popula ion g ow h. S ochas ic
ca as ophic e en s excep ed, he e appea s o be a low isk o u u e
popula ion decline, while he e is po en ial o slow g ow h.
Fo Ma ch 2018, su ey co e age was 10.6% o he s udy a ea, which is a
subs an ial imp o emen om he 1% co e age o he 2000-2010 s ip ansec
coun su eys. The No h egion’s 2018 KS ca ibou popula ion abundance
was es ima ed a ca. 60,469 ca ibou (95% CI: 51,932–70,410; CV = 0.074; SE =
4,501), wi h a densi y o ca. 2.59 ca ibou/km2 (95% CI: 2.23–3.02). This
Dis ance Sampling es ima e was p ecise (CV = 7.4%). The popula ion es ima e
is ca. 38.5% lowe han he es ima ed numbe o KS ca ibou in 2010. Be o e
concluding ha a la ge decline has occu ed, cau ion is needed because
se e al mi iga ing ac o s mus be ecognized. The 2010 su ey had low
co e age and a high Coe icien o Va iance (CV). Thus, i was likely no as
accu a e o p ecise as he 2018 su ey. Also, be e GIS mapping in 2018
esul ed in a smalle o al a ea, which means ha he 2010 es ima e was
in la ed. Fu he mo e, in 2018 su ey me hods changed o Dis ance Sampling.
This by i sel p ecludes end p ojec ions based on jus he cu en and he
2010 s ip ansec coun su eys. To p edic a somewha eliable popula ion
end, a ime se ies o a leas h ee es ima es is needed and hese mus be
ob ained wi h compa able me hods. Albei he 2018 Dis ance Sampling
es ima e o ca. 60,469 ca ibou sugges s decline in KS ca ibou abundance and
some decline could be expec ed, gi en bo h he poo cal ec ui men o he
2005-2010 pe iod and o e a decade o ha es managemen aimed a
educing KS ca ibou abundance. Rega dless, his epo ’s good la e win e cal
ec ui men o 2018 does no suppo u u e decline. Ins ead, i sugges s
possible s abili y o slow g ow h in u u e. I is also wo h men ioning ha an
9
al e na e Model-based analysis o he 2018 da ase es ima ed a somewha
highe 73,895 ca ibou (95% CI: 65,983-82,757, CV = 0.037) (Co eia 2020).
Gi en he e a e wo es ima es begs he ques ion, which is he mos accu a e
and p ecise? This is cu en ly being in es iga ed, equi es addi ional esul s
om wo o he Wes G eenland ca ibou su eys comple ed in 2019, and
conclusions ega ding Dis ance Sampling and Model-based es ima es will be
published in a pee - e iewed jou nal.
Whe he 60,469 (95% CI: 51,932–70,410) o 73,895 (95% CI: 65,983-82,757), he
2018 KS ca ibou popula ion size emains la ge ela i e o he a ea a ailable,
23,303 km2. The KS ca ibou densi y om Dis ance Sampling was 2.6 ca ibou
pe km2. Gi en good cal ec ui men , popula ion decline is no expec ed in
he immedia e u u e. Like all es ima es since 2000, he 2018 densi y exceeds
he ecommended managemen a ge o 1.2 ca ibou pe km2. Exceeding he
a ge densi y was assumed o aise isk o o e g azing and lead o
abundance decline. In Alaska and Canada, when o e g azing played a majo
ole, ca ibou declines ook place o e 15 o 20 yea s. Ne e heless, e en a e
almos wo decades o high densi ies exceeding he a ge ha e passed, he e
is no s ong e idence o ex ensi e o e g azing o decline in he KS ca ibou.
Since in 2018 ec ui men imp o ed o a leas 31 cal es pe 100 cows, despi e
an o e all densi y o 2.6 ca ibou pe km2, i appea s ha he No h egion can
suppo a highe densi y han expec ed. Pending addi ional esul s om wo
o he Wes G eenland ca ibou su eys comple ed in 2019, he a ge densi y
o ca ibou managemen will ecei e e-e alua ion ega ding wha le el is
compa ible wi h demog aphics ha acili a e sus ainable popula ions and
ha es s in G eenland.
Resume (Dansk)
Ves g ønland (syd o 69°N) ha seks egione med ensdy (Rangi e
a andus), de indeholde le e o skellige popula ione . Denne appo
p æsen e e nye oplysninge a en unde søgelse, de ble ud ø i 2018, om
Kange lussuaq-Sisimiu (KS)-bes anden, i No d egionen.
KS- ensdy ble sids unde søg i ma s 2010. Siden da ha de æ e lange
e e å sjag pe iode med ubeg ænse angs sam en in e sæson. E ny skøn
o e bes andss ø else a på høje id. Helikop e unde søgelse i 2000, 2005
og 2010 an end e s ip ansek e il op ælling. I ma s 2018 ble de igen
16
pe iuseq so leq u suiginaa eqa ne une soq. Apeqqu akissu issa sinia lugu
maannakko piaq amanna piaq ulappu igineqa poq, assa Kalaalli Nunaa a
ki aaani 2019-imi kisi sine i ma luk sulia ineqa ma a. Taakkunannga
ine ne usu ilisima uussu sikku allaase e ia lugi
saqqummiunneqa umaa pu , aakku aamma Dis ance Sampling
naape o lugu sulia ineqa pu .
KS-imi u oqassuseq nunap u oqa i u aqu si eqa iusup 23.303 km2
angissuseqa ne a eqqa saa igalugu u u ame lassusia 60.469-galua pa a (95
% CI: 51.932 – 70.410; CV = 0,074; SE = 4.501) imaluunnii 73.895-uppa a (95 %
CI: 65.983 – 82.757; CV = 0,037) nuna uuma igisaa ame lassusiannu
sanilliullugu miki allaa poq. Dis ance Sampling a o lugu
naa so suusio i sine mi KS-imi u u 2018-imi eqimassusia
k ad a kilome e -imu 2,6-iu oq. Siunissami qani umi ikilia ule nissaa
naa so suu igineqanngilaq piaqqio luaqimma ami. Tu u eqimassusiannik
naa so suisa ne i 2000-miilli inge lanneqa ale nikuusu assigalugi 2018-imi
u u eqimassusiannik kisi si pissa sia ineqa oq aamma Aqu sinikku
anguniagaagalua oq u u k ad a kilome e -imu 1,2-junissaannik
aaliangiussaq qaange neqa uaanna inneqa sima oq. Killiliussap
qaange neqa uaanna ne a peqqu aalluni nunap ne inia iusa up
naggo lu sinnissaa nagga aagullu allaa u oqassu ip appa ia ule ne anik
kinguneqa sinnaane anik pisoqa sinnaane a e seqqissaa igineqassaaq.
Tu oqa pallaale ne a peqqu aalluni nunap ne inia iusa up
ase ugaane anik asse suu issa pippu Canadami Alaskamilu
naggo lu sikkia uaa ne a ilu igalugu u u ukiu 15-i 20-llu ako nanni
ikilia uaa simamma a. Taamaa o li KS-imi u oqa igiiaa ukiuni qulikkaani
ma lunni ame la allaa simagalua lu ik nunap naggo lu sinne anik
uppe na saa i aqa unik paasi i sisoqa neq ajo poq, aamaa umillu
oqa oqa a iaqa poq u oqa iup A annaa a u u aama ame la igisu
”ne isaqa innissaa – uuma innia nissaa ” naa so suu aanngikkalua umik
nappassinnaasima aa. Kalaalli Nunaa a ki aani u unik 2019-imi kisi sine i
ma luk sulia ineqa u naammassinissaasa ungaanu , Aqu sinikku u u
anne paamik eqimassusissaannik anguniakkap, assa u u
k ad a kilome e -imu 1,2 – junissaannik aaliangiussap nalilii igeqqinnissaa
eqqa saa igineqa sinnaa oq. Nunap saannaa isiginia lugu killissa i i aasup
sumiinnissaa pi saane paaq, piniagaane allu eqqa saa igalugi
piujua i sinia ne paaq uja o neqa a iaqa ma .

17
In oduc ion
In G eenland, mos ca ibou occu along he cen al o sou hwes coas , which
is locally known as Wes G eenland, coas al a ea sou h o ca. 76° La . In 2000-
2001, he G eenland Ins i u e o Na u al Resou ces (GINR) ga e he names
No h, Cen al and Sou h, o he egions in Wes G eenland ha oge he
con ain se e al dis inc ca ibou popula ions (Jepsen e al. 2002). This epo
ocuses on he No h egion and Kange lussuaq-Sisimiu (KS) ca ibou
popula ion (Fig. 1). The No h egion lies be ween Sukke oppen (66° N) and
No d e S øm jo d (68° N) and co esponds wi h he G eenland go e nmen ’s
ca ibou managemen hun ing a ea 2 and is wi hin he Qeqqa a municipali y
o Wes G eenland. Wi hin he No h egion is he coas al ci y o Sisimiu , and
on he eas e n side o egion nea he inland Ice Cap is he coun y’s la ges
in e na ional ci il ai po , Kange lussuaq, also p e iously known as Sønd e
S øm jo d ai po . Like elsewhe e in G eenland, he KS ca ibou a e a
inancial esou ce o local hun e s, bo h p o essional and ec ea ional, as well
as o he se ice indus ies associa ed wi h boa ing and ou doo s. Mone a y
p o i s aside, ca ibou a e he p ized game mea se ed a all majo amily
e en s and many o icial ones. Ca ibou a e undeniably in insic o he hun ing
adi ions and cul u e o all he communi ies in Wes G eenland.
Figu e 1. No h egion bo de s (ca ibou managemen hun ing a ea 2) con aining he Kange lussuaq-
Sisimiu ca ibou popula ion. Ele a ions o e 200m a e in ligh yellow, below 200m a e g een.
18
Since 1977, he KS popula ion has been moni o ed o abundance wi h
deba able esul s ha we e o en in alida ed by ha es da a (Bo n e al 1998,
Cuyle e al. 2005, Cuyle 2007). In he pe iod 1993-1996, su eys employed
ixed-wing ai c a , high al i ude, high speed, long sys ema ic ansec s,
dis ega ded obse e a igue and we e unable o main ain a cons an al i ude
o e G eenland’s moun ains and ugged e ain. The su eys o 1993 and
1996 esul ed in la e win e p e-cal ing popula ion es ima es o ca. 3,788 and
7,727 espec i ely (Table 1, Ydemann & Pede sen 1999 unpublished epo o
GINR). Despi e Dis ance Sampling analyses o he da a se , hese we e
unde es ima es (Cuyle e al. 2005; Cuyle 2007) caused by unde ec ed ca ibou
a all dis ances, speci ically on he ansec ’s 0-line (cen eline o s ip lown).
The la e iola es he p ima y assump ion o Dis ance Sampling, i.e., all
animals/objec s-o -in e es on he ansec ’s 0-line a e de ec ed. To inc ease
de ec ion o ca ibou, beginning in 2000, ae ial su eys employed helicop e
lying slowly a low cons an al i ude and sho leng h andom ansec lines
wi h a na ow s ip wid h while a oiding sola gla e and conside ing
obse e a igue. Consequen ly, mo e animals p esen on he ansec s lown
we e de ec ed. The new logis ics o he pos -2000 su ey op imized sample
size, a iance, de ec abili y, obse e concen a ion and wi h he esul ha
es ima es o popula ion size a exceeded p e-2000 es ima es. Fo he No h
egion helicop e su eys we e epea ed in 2005 and 2010. Fu he
backg ound as well as de ailed desc ip ions o design and me hods o he
ae ial su eys om 2000 o 2010 ollow Cuyle e al. (2002, 2003, 2005 & 2011).
Since 2000, he KS ca ibou (Rangi e a andus g oenlandicus) popula ion has
been documen ed as he la ges in G eenland (Cuyle e al. 2011).
Table 1. La e win e popula ion pa ame e s o he Kange lussuaq-Sisimiu ca ibou popula ion o he
No h egion, Wes G eenland, aken om ae ial su eys o 1993 o 2010 (Cuyle e al. 2002, 2005,
2011; Ydemann & Pede sen 1999 unpublished).
Pa ame e
1993
1996
2000
2005
2010
Popula ion size es ima e
3,788
7,727
51,600
90,464
98,300
90% Con idence In e al (CI) – lowe
-
-
40,400
70,276
71,500
90% Con idence In e al (CI) – uppe
-
-
62,800
113,613
132,400
Coe icien o Va iance (CV)
-
-
-
-
0.19
S anda d E o (SE)
-
-
-
-
18,500
Mean g oup size  SD
1.95  0.33
2.5  0.48
2.8
4.63  3.4
2.96  2.14
Max g oup size
-
-
17
17
17
Densi y pe sq km
0.16
0.33
1.2 o 2.8
2 o 6
2 o 7
Cal pe cen age
1.3 %
17.2 %
26.6 %
11 %
15.2 %
Rec ui men (Cal /100 Cow)
-
-
68
16.2
27.7
Sex a io (Bull /100 Cow) *
-
-
87
33
54
*Age classes; cal es (age ≤ 10-mon hs), adul s (age > 1-yea )
19
Su ey me hods al e ed somewha om 2000 o 2005 (Cuyle e al. 2005).
Fu he , he 2000 su ey had signi ican ly (p < 0.001) lowe ca ibou de ec ion
on one side o e e y ansec (Cuyle e al. 2002). The o me makes i
impossible o di ec ly compa e he 2000 and 2005 abundance and densi y
alues and he la e sugges s he possibili y ha he 2000 su ey
unde es ima ed bo h. The abundance and densi y o KS ca ibou appea s o
ha e emained unchanged in he 2005-2010 pe iod (Table 1). Simul aneously,
cal pe cen age and ec ui men inc eased a e an ini ial d op in he 2000-
2005 pe iod.
Gi en he la ge numbe and ela i ely high densi y o KS ca ibou in he 2000-
2010 pe iod, densi y-dependen o age limi a ion was conside ed a isk,
which could cause popula ion size ins abili y and possibly decline. The e o e,
wildli e managemen aimed a educing ca ibou abundance and densi y o a
a ge s ocking a e o 1.2 ca ibou pe sq km (Cuyle e al. 2007). The a ge
densi y was based on s udies elsewhe e ha documen associa ions be ween
obse ed densi ies and changes in 1) ca ibou p oduc i i y, 2) dispe sal, and 3)
condi ion o he ange, as desc ibed in Cuyle e al. (2007). The e o e, ini ially
he e we e highe quo as ollowed by unlimi ed ha es s. The au umn season,
which was o iginally 1-mon h was leng hened se e al imes o e he yea s. A
win e hun ing season wi h quo a was added and i became pe missible o
ha es all sexes and ages. De ails a e a ailable in Cuyle e al. (2016). Despi e
hese managemen measu es, by 2010 he e was no educ ion in KS
abundance o densi y. Today, unlimi ed au umn ha es ing con inues, and in
2019 he au umn hun ing season became he longes e e (01 Augus – 31
Decembe ). Meanwhile, he win e ha es was ecen ly discon inued,
howe e , no p io o he Ma ch 2018 su ey.
P esen su ey
The in e na ional ne wo k o ca ibou knowledge holde s, CARMA
(Ci cumpola Rangi e Moni o ing & Assessmen ne wo k), ad ises
moni o ing ca ibou popula ion abundance e e y h ee yea s. Gi en he las
su ey o he KS ca ibou popula ion was in Ma ch 2010, and he e ha e since
been eigh unlimi ed au umn ha es s, had abundance, densi y, o
demog aphics o he Kange lussuaq-Sisimiu ca ibou popula ion changed? In
ea ly Ma ch 2018, GINR again examined he Kange lussuaq-Sisimiu ca ibou
popula ion in he No h Region o Wes G eenland by ae ial helicop e
su ey. The 2018 su ey me hods o collec ing he d s uc u e da a emained
unchanged om ea lie su eys. The 2018 su ey, howe e , eplaced he
20
mul iple sho leng h andom ansec lines s ip me hod used o KS ca ibou
in 2000, 2005 and 2010, wi h sys ema ic ansec lines and Dis ance Sampling,
in which dis ances om a line o animals de ec ed a e eco ded and om
hose dis ances, abundance and densi y o animal popula ions a e es ima ed
(Buckland e al. 2001, Thomas e al. 2010).
This epo in es iga es he Dis ance Sampling da a se collec ed du ing
GINR’s 2018 ca ibou su ey o he KS popula ion in he No h egion. I hen
p esen s he 2018 p e-cal ing ca ibou abundance and densi y. Fu he , his
epo p esen s in o ma ion on he mo emen o lack he eo o ca ibou
de ec ed. The he d s uc u e da a se is also in es iga ed, and we epo he
p e-cal ing demog aphics o he KS ca ibou popula ion.
No e ha an ea lie analysis o 2018 ca ibou abundance and densi y was un
on he same da a (Ma ques 2018), howe e , he hen known a ea (km2) was
inco ec . Ma ques’ (2018) is an in e nal CREEM (Cen e o Resea ch in o
Ecological and En i onmen al Modelling (S . And ews, Sco land)) epo ,
which is a ailable upon eques .
Me hods
S udy a ea
The No h egion is wi hin he Qeqqa a municipali y. Al hough he Qeqqa a
municipali y has a 2020 human popula ion o ca. 9,400 no all li e wi hin he
bounda ies o he No h egion. The only la ge se lemen wi hin he egion is
he ci y o Sisimiu , wi h ca. 5,600 inhabi an s, ollowed by he ca. 500 esiding
a he Kange lussuaq in e na ional ai po . Toge he , he hamle s o I illeq and
Sa anngui con ain a u he 200-300 people.
The No h egion is seasonally ice- ee. Imp o emen s in Geog aphic
In o ma ion Sys em (GIS) excluded lakes, i e s, sand, glacie s, and islands
o a mo e accu a e land a ea o 23,303 km2. P e ious su eys epo ed a less
p ecise land a ea o ca. 26,000 km2 (Cuyle e al. 2002, 2005, 2011). Loca ed
be ween 66-68° N La , he A c ic Ci cle passes h ough i s middle. The
no he n bo de is p o ided by he No d e S øm jo d, which has nume ous
u bulen maels oms and hin, eache ous, incomple e win e ice. The
sou he n bo de is amed by a combina ion o he G eenland Ice Cap, he
Sukke oppen Ice Cap, and he ou e po ion o he Kange lussuaq jo d. The
21
la e is ice- ee yea - ound and domina ed by cli s o ca. 1000 m. The wes e n
bo de is he pe manen ly ice- ee seacoas o he Da is S ai , and eas e n
bo de is he G eenland Ice Cap.
The wes coas opog aphy is moun ainous wi h peaks whose ele a ion can be
1000 o 1800 m and glacie s a e common. Mo ing eas wa d he moun ains
g adually gi e way o ugged e ain gene ally anging 10-900 m ele a ion.
The wide and ypically cli sided Kange lussuaq jo d pene a es he egion
s opping jus sho o he G eenland Ice Cap. I e ec i ely sepa a es he No h
egion in o wo hi ds abo e i and one hi d below i . In he sou he n hi d,
he e ain immedia ely no h o he Sukke oppen Ice Cap is gene ally ba en
highlands >1000 m ele a ion. Mo ing no h owa ds he Kange lussuaq
ai po he e ain includes lowland alleys unde 400 m ele a ion and
highlands o gene ally unde 1000 m ele a ion.
Common o Wes G eenland, he No h egion exhibi s a clima e g adien on
a wes -eas axis. The wes e n seacoas is we ma i ime; howe e , he clima e
becomes d y con inen al as one mo es eas owa ds he G eenland Ice Cap.
Clima e and wea he in he wes a e in luenced by he ice- ee Da is S ai
and he low-p essu e oceanic s o m sys ems ha sweep in om he
sou hwes . The clima e in he inland o he No h egion is in luenced by he
Sukke oppen Ice Cap a i s sou he n bounda y. Sukke oppen’s ele a ion
ac s as a ba ie o he oceanic s o m sys ems abo e, c ea es a p ecipi a ion
shadow on i s no heas e n side, and in combina ion wi h he domina ing
high p essu e o e he G eenland Ice Cap c ea es he inland’s xe ic
con inen al clima e. Loess/sands o ms a e common in he icini y o he
G eenland Ice Cap and a e caused by ka aba ic winds (o en gale o ce and
d y) descending o he Ice Cap (Cuyle e al. 2005).
The No h egion may be desc ibed as open o alpine und a. A lowe
ele a ions, ege a ion in ol es low a c ic species o mainly dwa sh ub
hea h, which changes o p edominan ly s eppe and g assland when mo ing
eas owa ds he G eenland Ice Cap (Tams o e al. 2005). Lichen hea hs a e
a e, and u he , highe ele a ions a e o en ell ield, ab asion pla eaus and
ba e g ound (Tams o e al. 2005).
Aside om he ca ibou, he only na i e wild mammals p esen in he No h
egion a e a c ic ha e (Lepus a c icus Rhoads) and a c ic ox (Vulpes lagopus
Linnaeus). La ge mammalian p eda o s a e absen . In he ea ly/mid 1960’s,

22
muskoxen (O ibos moscha us Zimme mann), we e ansloca ed om NE
G eenland o a loca ion close o he Kange lussuaq in e na ional ai po .
Muskoxen a e now i mly es ablished in he sou he n hi d o he No h
egion. The bo de s o he No h egion a e semi-pe meable pe mi ing
limi ed animal mo emen be ween adjacen egions, i.e., Na e naq egion o
he no h (abo e No d e S øm jo d) and Cen al egion o he sou h (below
Sukke oppen Ice Cap). Ne e heless, he bo de s a e likely e ec i e ba ie s
p e en ing mass ca ibou mo emen s (Linnell e al. 2000).
Field me hods
Since 2000, ea ly Ma ch has been he chosen pe iod o su eys because
ca ibou dispe sion is high, g oup size is small wi h low a iabili y and daily
mo emen is a he annual minimum (Cuyle e al. 2007, 2011, 2016; Poole e al.
2013). The o me wo educe a iance among ansec s, diminish coun ing
e o , and maximize p ecision, while he la e lowe s mo emen be ween o
along ansec s. Meanwhile, snow co e is highly a iable, and he e ain
ugged (Appendix 4). Fu he , e a ics (glacial boulde deb is) a e common
and appea simila o ca ibou in size and colou . Singula ly o in combina ion,
hese a ibu es o he habi a p o ide small g oups o ca ibou wi h
ou s anding backg ound camou lage and educe de ec abili y (Cuyle e al.
2005, 2011). Failu e o de ec ca ibou (o en s a iona y, speci ically e en when
on he 0-line) mus be ecognized as a sou ce o nega i e bias (inaccu acy) o
ca ibou su eys in G eenland. To mi iga e he combina ions o condi ions ha
lowe de ec abili y o ca ibou, a helicop e is necessa y o enable a cons an
al i ude abo e g ound le el while lying low (40 m, ca. 120 ee ) and slow (ca.
65 km/hou ). The ae ial su ey o he KS he d occu ed 01-15 Ma ch 2018 and
a helicop e AS350 was he pla o m o obse a ion.
Pa icipan s included h ee obse e s, all wi h p e ious su ey expe ience:
GINR’s senio scien is Ch is ine Cuyle , GINR’s p ojec coo dina o Pe e
Hegelund, and p o essional hun e Aslak Jensen (G eenland Associa ion o
P o essional Hun e s (KNAPK)) om Nuuk. Jensen and Hegelund we e
sea ed in he ea o he helicop e and obse ed animals o all dis ances om
he side hey we e si ing, which al e na ed. Cuyle always sa in on ,
obse ed he 0-line, including dis ances o ei he side up o 100 m, and was
he da a eco de . Ve bal con ac among he obse e s pe mi ed he digi al
audio eco ding o all obse a ions. Two audio de ices (SONY IC eco de ,
ICD-SX712) we e used o eco d sepa a ely he obse a ions speci ic o he le
and igh side o he line ansec . Audio eco ding de ices we e on con inual
23
eco ding o each line ansec . A he end o each su ey day, audio da a
was downloaded o compu e o s o age and back-up. Obse a ions we e
la e pai ed wi h Global Posi ioning Sys em (GPS) coo dina es o he
helicop e a he ime o obse a ion. The audio eco ding included dis ance
o, size, beha iou o each ca ibou g oup obse ed and name o he obse e .
O en ligh and en i onmen al condi ions we e eco ded. Manual click-
coun e s, logging he numbe o ca ibou seen by each obse e , p o ided low-
ech back-up o he digi al audio obse a ions om each line segmen .
Figu e 2. A ea co e ed by he 2018 ca ibou su ey o he No h egion (23,303 km2). Th ee di e en
colou s illus a e he h ee sub-a eas, designa ed as Sisimiu (blue), Sisimiu Sou h (o ange) and
Angujaa o iup (pu ple). The e m ’Bye bygde ’ iden i ies he ou human se lemen s.
Su ey design
The 2018 su ey di e ed in design om he 2000-2010 andom ansec line
s ip-coun s. The su eyed No h egion a ea, 23,303 km2, was di ided in o
h ee sub-a eas, a bi a ily named Sisimiu (12,658 km2), Sisimiu -Sou h (3,512
km2) and Angujaa o iup (7,133 km2) (Fig. 2). The sampling design o he
2018 su ey conside ed 19 sys ema ic pa allel line ansec s o a iable leng h
sepa a ed by 15 km and placed o e he h ee sub-a eas (Fig. 3). Those
ansec s p o ide he maximum a ea co e age possible gi en he inancial
esou ces a ailable. An ini ial line ansec was compu e gene a ed a
andom, and he o he s ollowed 15 km apa . Aligning line ansec s
pe pendicula o known g adien s wi hin he su eyed a ea can maximize
p ecision o he esul ing es ima e by lowe ing he encoun e a e a iance
24
(Buckland e al. 2001). Thus, he ansec axis di ec ion was chosen as
pe pendicula o p e iously known animal dis ibu ion g adien s in Ma ch.
Lines 1 o 13 ollowed a wes -eas axis, which also e lec s he clima e g adien
om we ma i ime o d y con inen al. Line ansec s 14 o 19 ollowed a
no h-sou h axis, e lec ing animal, clima e, and opological g adien s
be ween Sukke oppen Ice Cap and he Kange lussuaq In e na ional ai po .
Figu e 3. The 19 line ansec s used in he 2018 ca ibou su ey o he No h egion, illus a ing end
poin s, and numbe ing o line ansec s and employing he same h ee colou s as applied o he h ee
sub-a eas in abo e igu e 2: Sisimiu (blue), Sisimiu Sou h (o ange) and Angujaa o iup (pu ple).
Ele a ions be ween 0 and 200 m a e pale g een, while any abo e 200 m a e pale yellow.
Dis ance collec ed was he pe pendicula dis ance om he helicop e ’s lown
0-line o a ca ibou g oup (objec -o -in e es ). A ca ibou g oup was a ela i ely
igh agg ega ion o animals. Since ligh esponse o he app oach o he
helicop e was common, dis ance collec ed was he dis ance o he cen e o
he ca ibou g oup om he 0-line be o e any mo emen by he ca ibou
occu ed. Exac dis ance measu emen s we e no possible p ima ily because
imp ac ical, e.g., main aining ligh speed, numbe o ca ibou g oups
encoun e ed wi hin a sho ime, he ange inde oo ime consuming o use
wi h e o s occu ing, plus ime cons ain s on audio eco dings, which could
c ea e con usion as o which dis ance applied o which g oup obse a ion.
Addi ionally, helicop e ime was limi ed by inancial cons ain s, which
p e en ed s opping and lying ou o indi idual g oups be o e e u ning and
con inuing along he 0-line. Ins ead, dis ance measu emen used he ollowing
25
dis ance bins: 0, 50, 100, 200, 300, 400, 500, 750 and 1500 me e s pe pendicula
o he line ansec . These alues co espond o he uppe limi o a speci ic
bin ha he ca ibou obse a ion was included in. Fo analysis, hese we e
ecoded o he mid dis ance o a speci ic bin. No e, binning accu acy elies
hea ily on obse e abili y o co ec ly es ima e dis ance o he obse ed
animals. Thus, be o e s a ing he su ey he helicop e ho e ed a he 40m
al i ude used du ing line ansec s, while each obse e used a Leica lase
ange inde 1600 o gauge dis ances. Then hey ma ked hei window wi h
masking ape delinea ing he app oxima e dis ances o each bin. When
possible while lying line ansec s, he lase ange inde s we e used o
double-check epo ed bin dis ances o de ec ed ca ibou.
Dis ance sampling
The ca ibou g oup was he selec ed sample uni o he Dis ance Sampling
analysis o he 2018 su ey. Nei he he indi idual ca ibou wi hin a g oup,
no indi idual line ansec s we e conside ed as he sample uni .
The eco ded dis ances o he ca ibou g oups obse ed we e used o es ima e
a de ec ion unc ion, hen es ima e he de ec ion p obabili y and inally o
es ima e he densi y o he ca ibou wi hin he su eyed a ea (Buckland e al.
2001). The de ec ion unc ion, 𝑔(𝑦), desc ibes he p obabili y o de ec ing an
objec o in e es (ca ibou g oup) gi en ha i is a a dis ance 𝑦, om he
cen eline (0-line), hus being a non-inc easing unc ion o 𝑦 (Buckland e al.
2015). Fo line ansec s, 𝑦 is he pe pendicula dis ance om he 0-line o he
de ec ed objec . Wi hin Dis ance Sampling me hods, he p obabili y o
de ec ion is explained ecu ing o hese obse ed dis ances (Buckland e al.
2001).
P io o Dis ance Sampling analysis, he aw da a was i s p ocessed o
inconsis encies. Then ex ensi e explo a o y da a analysis was comple ed,
including e alua ion o obse ed dis ances, be o e p oceeding o de e mining
he de ec ion unc ion h ough model i ing and selec ion, as pe
ecommenda ions by se e al au ho s (Buckland e al. 2001; Ma ques e al.
2011; Thomas e al. 2010). To de e mine he de ec ion unc ion, se e al models
we e conside ed, since his is he s anda d app oach in oduced by Buckland
(1992) and popula ized by being a ailable in he so wa e Dis ance (Thomas e
al. 2010). The model p esen ing he lowes AIC alue was chosen. The
subsequen analysis was based on Ma ques (2018). De ails ega ding Dis ance
Sampling heo y, me hods and analysis a e a ailable in Buckland e al. (2001,
32
Dis ance Sampling analysis
Be o e conduc ing any modelling, an analysis o he obse ed dis ances was
made o e alua e whe he any majo assump ion iola ion occu ed o o he
da a- ela ed issue, as s a ed in p e ious sec ions. These analyses a e om
Co eia (2020). The his og am o obse ed dis ances wi h no de ined
unca ion dis ance is simila o ypical Dis ance Sampling da a, pe haps
showing some o e -dispe sion, wi h no -equally-spaced bins (Fig. 8). Gi en
he his og am o binned dis ances, a s ip hal -wid h o 𝑤 = 0.75 km was
selec ed (i.e., all obse a ions a dis ances beyond 750 me e s we e disca ded).
This unca ion educed he sample size om 2079 o 1640 ca ibou g oups o
he Dis ance Sampling analysis. Da a unca ion is a common p ocedu e
because o he wise ex a adjus men e ms may be needed o i he long ail o
he de ec ion unc ion. Fu he , li le in o ma ion is los by unca ion, since
da a obse a ions loca ed mo e han 0.75 km om each side o he line make a
minimal con ibu ion o he abundance es ima e.
The al e na i e binning Op ion 2, less bins, educes he in luence o po en ial
measu emen e o s in he obse ed dis ances. This al e na i e binning op ion
includes bin cu poin s o 0, 0.10, 0.30, 0.50 and 0.75 km (Fig. 8).
Wi h he o iginal binning op ion, he e seem o be less han expec ed
obse a ions on he 0.10-0.20 km and 0.30-0.40 km in e als, when compa ed
o he 0.20-0.30 km and he 0.40-0.50 km bins. This migh be e idence o
heaping. This phenomenon occu s when obse e s end o eco d some
p e e ed alues o e o he s (Buckland e al. 2001). He e, he heaping would
ha e occu ed o dis ances 0.25 km and 0.50 km, which a e ound dis ances
ha a e easily chosen in he absence o a igo ous dis ance measu ing me hod.
Bo h binning op ions we e conside ed in model i ing, albei only Op ion 2
minimizes he e ec o measu emen e o induced by heaping. Since binning
Op ion 1 was no sui able o g ouping, only he analyses whose i ed models
conside he second binning op ion a e illus a ed below. The ad an age o
choosing he second binning op ion is ha i esul s in mo e eliable de ec ion
unc ions. Howe e , owing o ewe deg ees o eedom, he small numbe o
bins a ec s he 𝜒2 Goodness-o -Fi es s ollowing model i ing.
A sca e plo , wi h a GLM i ed be ween wo a iables, obse ed dis ance as
explana o y a iable, and g oup size as esponse a iable, sugges ed a ain
endency o la ge g oups being associa ed wi h g ea e dis ances (Fig. 9).

33
No e ha he maximum g oup size is no longe 20 as his da a se has been
unca ed, conside ing a s ip wid h o 𝑤 = 0.75 km, he e o e, he mos
dis an obse a ions, which co esponded o la ge g oup sizes, we e
excluded. This eg ession analysis sugges s ha dis ance is a s a is ically
signi ican a iable explaining g oup size (Table 4). G oup size also seemed
ma ginally ela ed wi h he spa ial coo dina es (Co eia 2020).
Table 4. Summa y o he coe icien cha ac e is ics o he GLM be ween obse ed dis ance and he
g oup size while conside ing a Poisson dis ibu ion.
Pa ame e
Es ima e
S anda d
E o
z- alue
p- alue
In e cep
0.747
0.029
26.20
0.00000
Dis ance
0.311
0.080
3.88
0.00011
No e: AIC = 5613.7, Null De iance = 1361.4, Residual De iance = 1346.4.
Figu e 9. Rela ionship be ween g oup size and obse ed dis ances and espec i e eg ession i using
GLM.
De ec ion unc ion models i ed wi h he i s binning op ion did show poo
i ing, including he bes i wi hin his g oup, since hese p esen ed se e al
adjus men e ms, due o he heaping phenomena. Below, he de ec ion
unc ions a e i ed o he da a conside ing he second binning op ion.
Fo hese models, e e y combina ion o key unc ion and adjus men e ms
was es ed. The only addi ional co a ia es assessed we e obse e and g oup
size, conside ing 𝑤 = 0.75 km. A summa y o he in o ma ion om each
34
model i ed o he da a (Table 5) p o ides a simple o e iew o se e al
models, and includes he espec i e key unc ions, adjus men e ms, model
o mula, 𝜒2 Goodness-o -Fi es p- alue, es ima es o he de ec ion
p obabili y, espec i e s anda d e o (se (𝑃
a)), and Δ𝐴𝐼𝐶 compa ison be ween
each model and he model wi h he lowes AIC. The bes model i ed o he
da a possesses he lowes change in AIC alue (Δ𝐴𝐼𝐶 = 0). Fo he 2018
ca ibou su ey da a, his model has he haza d a e unc ion as a key unc ion,
no adjus men e ms added and only g oup size as co a ia e (AIC = 4414.52).
The haza d a e key unc ion was selec ed because i was he mos lexible
key.
The second-bes model includes he hal -no mal key wi h g oup size as a
co a ia e (AIC = 4422.17, i.e., Δ𝐴𝐼𝐶 = 7.66). This s ongly sugges s ha g oup
size is a ele an co a ia e in de ec abili y. The bes i ed de ec ion unc ion
pa ame e s’ es ima es indica e a sligh posi i e ela ionship be ween g oup
size and de ec abili y, supe imposed wi h he obse ed dis ances’ his og am
(Table 6, Fig. 10). The es ima ed a e aged p obabili y o de ec ion o he
No h egion was 𝑃
a = 0.541 (se = 0.025, Table 5). Remaining de ec ion
unc ions and summa y able a e ound in Co eia (2020). I is an a e aged
es ima e since g oup size is included in he model. Consequen ly, each g oup
size has i s sepa a e de ec ion unc ion, co esponding o di e en es ima es
o he p obabili y o de ec ion (Fig. 11).
Figu e 10. The de ec ed dis ances wi h he es ima ed de ec ion unc ion o e laid, conside ing he
binning op ion ha educes he e ec o heaping.
35
Table 5. Model compa ison ac oss he h ee Con en ional Dis ance Sampling models and models conside ing g oup size and obse e as co a ia es.
Key unc ion
Fo mula
𝒙𝟐 p- alue
𝑷
a
se (𝑷
a)
∆AIC
Haza d- a e
G oup size
NA
0.541
0.025
0.000
Hal -no mal
G oup size
0.000
0.603
0.013
7.658
Hal -no mal wi h cosine adjus men e ms o o de 2,3
1
NA
0.512
0.026
8.582
Uni o m wi h cosine adjus men e ms o o de 1,2,3
NA
NA
0.513
0.025
8.582
Haza d- a e wi h cosine adjus men e m o o de 2
1
NA
0.519
0.025
8.647
Haza d- a e wi h simple polynomial adjus men e m o o de 2
1
NA
0.533
0.032
10.123
Haza d- a e
Obse e
NA
0.544
0.025
10.672
Haza d- a e wi h He mi e polynomial adjus men e m o o de 4
1
NA
0.535
0.032
10.679
Uni o m wi h simple polynomial adjus men e ms o o de 2,4,6
NA
NA
0.577
0.029
15.371
Hal -no mal
Obse e
0.000
0.605
0.013
15.635
Hal -no mal
1
0.001
0.606
0.013
19.097
Uni o m wi h He mi e polynomial adjus men e m o o de 4
NA
0.000
0.643
0.010
30.245
No e: Unde Fo mula, explana o y a iables: G oup size = g oup size as a iable, 1 = o Uni o m key, NA = no explana o y a iables, Obse e = obse e as a iable.
Unde Chi-squa e p- alue, NA = no enough deg ees o eedom o he Goodness-o -Fi (GOF) es , hus he ‘NA’ alues. (Deg ees o eedom a e calcula ed conside ing he model
pa ame e s and hese a y conside ing which key unc ion is used and how many/which explana o y a iables a e conside ed.).
Fo each key unc ion, all h ee se ies expansions (Cosine, Simple Polynomial, He mi e (Appendix 1, Table 14) we e applied.
Table 6. De ec ion unc ion pa ame e s’ es ima es.
Es ima e
S anda d E o
In e cep
+1.681
0.154
G oup size
0.152
0.048
No e: Es ima es a e on log scale.
36
Figu e 11. Es ima ed p obabili ies o de ec ion o each obse ed g oup size ob ained wi h he i ed model.
A g oup size o 2 ca ibou p esen s an es ima ed p obabili y o de ec ion o 0.533, while a
g oup size o 10 has an es ima e o 0.909 (Fig. 11). Wi h inc easing g oup size, he
p obabili y o de ec ion also inc eases. This is consis en wi h he au ho ’s in ui ion as
la ge g oups a e easie o de ec han smalle ones.
The es ima es o encoun e a es sugges he Sisimiu sub-a ea has he mos ca ibou, since
i s es ima e is la ge han he o he sub-a eas (Table 7). Visualiza ion o he de ec ed
ca ibou dis ibu ion shows his was almos con inuous along he line ansec s o he
Sisimiu sub-a ea, wi h a ew ‘ho ’ spo s (Fig. 12). Meanwhile, ca ibou we e seldom
obse ed a ele a ions o e 1000 m. This in ol ed much o he Sisimiu Sou h sub-a ea,
sou h end Angujaa o iup sub-a ea, and a couple o line segmen s in Sisimiu sub-a ea:
line ansec 6 o du a ion o he glacia ed Qáqapalâ (1200-1600 m); line ansec 5 o e
he Akulia use ssuaq Peninsula and associa ed Tug oqa ajôg (900-1500 m). Conce ning
he design-based es ima es o ca ibou abundance and densi y, Sisimiu is also he sub-
a ea p esen ing mo e ca ibou (Table 8, Fig. 13).
Table 7. Encoun e a e es ima es pe sub-a ea (s a um) o ca ibou g oups conside ing h ee s a a, i e bins, and a
de ec ion unc ion i ed wi h g oup size as co a ia e.
Sub-a ea
Encoun e a e
S anda d E o (se)
Coe icien o Va iance (c )
Sisimiu
1.389
0.084
0.060
Sisimiu Sou h
0.403
0.110
0.273
Angujaa o iup
0.559
0.085
0.152
TOTAL
0.997
0.120
0.120
37
Figu e 12. Rela i e dis ibu ion o ca ibou numbe s along he line ansec s. Smudge shading indica es ewes ca ibou.
This da kens un il becomes black, u ns in o pu ple- iole , shi ing o pink and ending wi h yellow, which is he mos
ca ibou. Unde lying map: ele a ions be ween 0 and 200 m a e pale g een, abo e 200 m a e pale yellow.
The 𝜒2 Goodness-o -Fi es could no be pe o med o he selec ed model because he e
we e no enough deg ees o eedom (Appendix 1: Equa ion (19), 𝑢 − 𝑞 − 1 = 4 − 3 − 1 = 0
deg ees o eedom, obse ed and expec ed alues in Co eia (2020)). Addi ionally, he
Kolmogo o -Smi no and C amé - on Mises es s (Appendix 1) could no be applied
since he dis ances we e ep esen ed as a disc e e a iable.
In Ma ch 2018, he No h egion had an es ima ed popula ion size o app oxima ely 60,469
ca ibou (95% CI: 51,932 – 70,410), wi h a CV o 7.4% (Table 8). The la e is an excep ionally
low alue, which indica es ela i ely accu a e ca ibou abundance es ima es o 2018. The
design-based densi y es ima e o he whole su ey egion was 2.59 ca ibou pe km2, wi h
95% CI: 2.23 – 3.02 (Table 8, Fig. 13). Fu he de ails in Co eia (2020).

38
Table 8. Kange lussuaq-Sisimiu ca ibou abundance es ima es and densi ies in he No h egion, Ma ch 2018,
conside ing h ee sub-a eas (s a a), i e bins and a Haza d a e de ec ion unc ion wi h g oup size as a co a ia e.
Sub-a ea
Popula ion
Es ima e
SE
CV
95% Con idence In e al
Densi y
(ca ibou / km2)
Lowe
Uppe
Sisimiu
46,724
3,745
0.080
39,392
55,422
3.7
Sisimiu Sou h
3,931
1,134
0.289
1,820
8,492
1.2
Angujaa o iup
9,814
1,502
0.153
6,758
14,252
1.4
TOTAL
60,469
4,501
0.074
51,932
70,410
2.6
No e: SE = S anda d E o , CV = Coe icien o Va iance.
Figu e 13. Ca ibou densi y es ima es wi h co esponding con idence in e als o he h ee sub-a eas, Sisimiu , Sisimiu
Sou h and Angujaa o iup, and inally o he o al No h egion.
Ca ibou de ec abili y
As no ed unde all helicop e su eys since 2000, de ec ing ca ibou was again di icul
owing o backg ound condi ions camou laging he ca ibou om iew. These included
incomple e o pa chy snow co e , subs a e (including g ass, low ege a ion, g ound)
poking o showing h ough hin snow laye , ocky e ain, og, and ligh /shadow
condi ions ypical o la i udes a ound he A c ic Ci cle in ea ly Ma ch. De ec ing ca ibou
was u he comp omised by he wes -eas o ien a ion o mos lines, which ensu ed ha
on he sou h- acing side o he helicop e in he absence o cloud co e , he sun was in
obse e eyes and e lec ing o he snow su ace causing sola gla e. Despi e obse e s
using pola ized sunglasses, his in ense sunligh in he eyes may ha e educed
de ec abili y o ca ibou. The ligh al i ude o 40 m educed he amoun o dead g ound
(land blocked om iew by e ain ea u es, e.g., Appendix 4, Fig. 25), esul ed in mo e
39
g ound o sea ch and scan o e o animals. When combined wi h a long line leng h, he
subjec i e esul was a eeling o he e no being enough ime o scan all e ain p ope ly,
and some imes diminished obse e concen a ion could occu . Bo h could lowe ca ibou
de ec ion gi en he high camou lage condi ions. Finally, he helicop e windows
some imes os ed, ha os and he ime o physical emo al (sc apping o using c edi
ca d) could ha e dec eased ca ibou de ec ion. Addi ionally, low ca ibou g oup size and
speci ically lack o mo emen by he ca ibou made sigh ing hem di icul .
Table 9. Kange lussuaq-Sisimiu ca ibou mo emen , o lack he eo , in eac ion o helicop e lying line ansec su ey
o No h egion, Ma ch 2018. The da ase o obse a ions o ca ibou g oup size which included beha iou was n=
1880, while he da ase which included dis ance o he ca ibou g oup om he line ansec was n = 1870.
Kange lussuaq-Sisimiu ca ibou
Ca ibou G oups
Exhibi ing Mo emen
Lacking Mo emen
p – alue
Numbe o g oups
1288
592
% obse a ions
68.5%
31.5%
Mean g oup size
2.54
2.14
< 0.0001
Con idence Le el (95%)
0.106110162
0.112602502
S anda d E o
0.054087919
0.057333656
Median
2
2
Mode
2
1
S anda d de ia ion
1.941145995
1.394988056
Sample Va iance
3.768047773
1.945991677
Maximum
20
10
Minimum
1
1
Dis ance om 0-line1
1283
587
Mean dis ance
539.36 m
663.80 m
< 0.0001
Con idence Le el (95%)
28.5451518127234
39.8522696732454
S anda d E o
14.5503705
20.29116828
Median
300
500
Mode
1500
1500
S anda d de ia ion
521.1795663
491.6161067
Sample Va iance
271628.1403
241686.3964
Maximum
1,500 m
1,500 m
Minimum
50 m
50 m
1 0-line is he cen e o he line ansec lown by helicop e .
Ca ibou beha iou : ligh eac ion o lack he eo
The ca ibou su ey o 2018 was he i s o use digi al audio eco de s o collec he
obse a ion da a. The digi al eco de s pe mi ed including in he da ase wha , i any,
was he beha iou al eac ion o he ca ibou g oup o he helicop e lying a line ansec
40
pas o o e hem. Beha iou could hen be pu in ela ion o g oup size and dis ance om
he ansec line (Table 9).
The e was a signi ican di e ence be ween he size o ca ibou g oups ha exhibi ed
mo emen and hose ha did no , mean 2.5 and 2.1, espec i ely ( S a = 5.104806; wo-
ailed es ing P < 0.0001, = 1.961497638, d = 1548).
Non-mo ing ca ibou g oups a e aged ca. 125 m u he away om he line ansec lown
by he helicop e han hose ca ibou g oups showing mo emen (Table 9). The e was a
signi ican di e ence be ween he mean dis ance o g oups wi h mo emen , 539.36 m,
ela i e o he g oups lacking mo emen , 663.80 m ( S a = -4.983728647; wo- ailed es ing
P < 0.0001, = 1.961944491, d = 1199).
Table 10. Kange lussuaq-Sisimiu ca ibou de ails o mo emen , o lack he eo , in eac ion o helicop e lying line
ansec su ey o No h egion, Ma ch 2018. Da ase o obse a ions ha included ca ibou g oup size, beha iou , and
dis ance om line ansec . Da ase was n= 1,880 g oups, which con ained n = 4,545 indi idual ca ibou.
Kange lussuaq-Sisimiu ca ibou
Ca ego y
G oups
(n = 1,880)
%
Indi iduals
(n = 4,545)
%
Exhibi ing Mo emen
Running away
1000
53.19
2548
56.06
Running away high speed
111
5.90
345
7.59
Walking
92
4.89
188
4.14
App oach*
20
1.06
63
1.39
Con used, ci cling igh ly
20
1.06
39
0.86
Running pa allel o line ansec
18
0.96
38
0.84
Running, la e s anding looking
17
0.96
29
0.64
T o ing away
7
0.37
14
0.31
Mixed: mo emen + lack o
3
0.16
13
0.29
TOTAL
1,288
68.51
3,277
72.10
Lacking Mo emen
S anding s ill
459
24.41
992
21.83
S anding, la e walk app oach*
66
3.51
145
3.19
Lying down
32
1.70
51
1.12
Lying down, la e s ood up
17
0.90
39
0.86
Some lying, o he s s anding s ill
10
0.53
28
0.62
Lying down, la e walk mo emen
8
0.43
13
0.29
TOTAL
592
31.49
1,268
27.90
*App oach mo emen was owa ds he helicop e posi ion.
Ca ibou g oups eac ing o he helicop e ly-by wi h mo emen made up 68.5% o all
obse a ions. Con e sely, 31.5% o all ca ibou g oups exhibi ed li le o no mo emen . The
esul s we e simila when conside ing he absolu e numbe o ca ibou in ol ed (Table 10).
41
O 4,545 indi idual ca ibou, 72.1% exhibi ed mo emen and lack o mo emen 27.9%.
Almos a hi d o all ca ibou obse ed lacked mo emen .
Among he 1146 ‘ unning’ g oups (Table 10), 939 o hose g oups exhibi ed unaba ed
ligh , i.e., hey ne e s opped while wi hin iew o he helicop e . G oup composi ion
(sex, age) was de e mined o 316 o hose g oups and 86% we e composed o cows wi h
cal es. Only 7% we e bull g oups (ju eniles, adul s), wi h he emaining 7% being g oups
o cows only, cal es only, cows and ju enile bulls o adul s o unknown sex.
Conside ing only he 233 ca ibou g oups whose o iginal posi ion was on o wi hin 50 m o
he 0-line, 140 o hose g oups (60%) ne e s opped unning away. Six imes such
unaba ed ligh began while a g oup was a dis an on a sec ion o he 0-line ye o be
lown, e.g., 0.5 o 1.5 km ahead o he helicop e . Meanwhile, 15 g oups lacked mo emen ,
al hough i e o hose g oups did mo e once he helicop e was di ec ly o e op o hem.
In en o hose g oups he ca ibou we e s anding and in i e hey we e lying down.
Table 11. Demog aphics o Kange lussuaq-Sisimiu ca ibou, No h egion, Ma ch 2018.
Pa ame e
Kange lussuaq-Sisimiu ca ibou
Numbe o g oups obse ed
894
Mean g oup size
2.45
Con idence In e al (95%)
0.1148
S anda d E o
0.0585
S anda d De ia ion
1.75
Sample Va iance
3.0605
Median g oup size
2
Mode g oup size
1
Maximum g oup size
12
Minimum g oup size
1
O iginal da a
Remo ed 124 o phan cal es
To al indi iduals sexed & aged (n)
2188
100 %
2064
100 %
Cow (age > 1 yea )
1136
51.92 %
1136
55.04 %
Cal es om p e ious sp ing
476
21.76 %
352
17.05 %
(231 emales)
10.56 %
-
-
(228 males)
10.42 %
-
-
Bull (age > 1 yea )
576
26.33 %
576
27.91 %
(231 adul s, age > 3)
10.56 %
(231 adul s, age > 3)
11.19 %
(202 ju eniles, age 2½)
9.23 %
(202 ju eniles, age 2½)
9.79 %
(143 ju eniles, age 1½)
6.54 %
(143 ju eniles, age 1½)
6.93 %
Rec ui men (cal es / 100 cows)
41.90
30.99
Sex a io (Bull >1 yea / Cow)
0.51
0.51
48
egged win oe uses ha e occasionally been obse ed (Cuyle & Øs e gaa d 2005).
Ne e heless, winning is conside ed uncommon in ca ibou (Skoog 1968, Be ge ud 1969,
Dauphiné 1976). Ei he winning is mo e common han expec ed in he KS ca ibou
popula ion o he ex a cal es also had los hei dam. Conside ing he 124 o phans, hei
su i al in o Ma ch o hei i s win e is ema kable bu no unexpec ed since la ge
p eda o s a e absen in Wes G eenland. I indica es ha ood a ailabili y, quan i y and
quali y we e no a p oblem o KS ca ibou in he mon hs leading up o Ma ch 2018.
Un o una ely, he high numbe o o phan cal es (i.e., missing cows) indica es ha he cal
ec ui men o 42 cal es pe 100 cows is a i icially high. One op ion would be o emo e
he o phan cal es om he da ase , since hese may no su i e, assuming hese ha e a
highe mo ali y a e han cal es wi h dams (Be ge ud e al. 2008). I jus he known 124
o phan cal es a e emo ed om he da ase , hen he e ised demog aphics esul s a e
cows 55%, bulls 28% and cal es 17%, wi h a la e win e cal ec ui men o 31 cal es pe
100 cows and a bull o cow a io o abou 0.51. E en he e ised cal alues a e be e han
he low 2005 and 2010 alues (Tables 1, 11). The Ma ch 2018 demog aphics, e ised o no ,
desc ibe a ca ibou popula ion ha appea s capable o wi hs anding cu en ha es s,
while he cal ec ui men is no high enough o sugges he possibili y o apid popula ion
g ow h. Con e sely, he 2018 cal ec ui men indica es a low isk o u u e popula ion
decline, while he e is po en ial o possible s abili y o slow g ow h (Be ge ud e al. 2008).
S ill, s ochas ic ca as ophic e en s could b ing ab up changes in abundance (CAFF 2021).
2018 ca ibou popula ion size & densi y
A 23,303 km2, he No h egion is he la ges o all he ca ibou egions in Wes G eenland.
Due o he high cos o helicop e ime in G eenland, he 2000, 2005 and 2010 s ip coun
su eys co e ed only abou 1% o he No h egion a ea. In 2018 and wi h inc eased
unding, Dis ance Sampling me hods wi h sys ema ic ansec s we e adop ed. This
inc eased a ea co e age o 10.6% (gi en unca ion limi ing s ip wid h o 750 m ei he
side), which con ibu ed o imp o ed es ima e accu acy.
The 2018 KS popula ion es ima e was 60,469 ca ibou (95% CI: 51,932–70,410; SE = 4,501;
CV = 0.074), wi h densi y o ca. 2.59 ca ibou/km2 (95% CI: 2.23–3.02). The Dis ance
Sampling es ima e was excep ionally p ecise (CV = 7.4%), speci ically in ega ds pas less
p ecise es ima es.
On he su ace he 2018 popula ion es ima e is ca. 38.5% lowe han he es ima ed numbe
o KS ca ibou in 2010, i.e., ca. 60,500 e sus 98,300 (Tables 1, 8). Be o e concluding ha a
la ge decline in abundance has occu ed, cau ion is needed because se e al mi iga ing

49
ac o s mus be ecognized. The 2010 su ey had low a ea co e age (1%) and a high
Coe icien o Va iance (CV), (19%). Thus, he 2010 es ima e was likely no as accu a e and
was ce ainly less p ecise han he 2018 su ey. Also, unlike in 2018, he 2010 analyses
used a less e ined a ea, i.e., included lakes, i e s, and islands. The la ge a ea en ailed
would ha e in la ed he 2010 es ima e. These may accoun o he lack o o e lap in he
con idence in e als o he 2010 and 2018 es ima es. Expanding o include he 2005 su ey
es ima e and he o e lap o he con idence in e als sugges s a lack o signi ican
di e ence be ween he 2005-2010 and 2018 popula ion sizes.
Popula ion end can be p edic ed i he same me hods a e epea ed o e a ime se ies o
su eys. Howe e , he 2018 su ey adop ed Dis ance Sampling me hods and analyses o
maximize es ima e accu acy and p ecision. This change o me hods p ecludes end
p ojec ions based on jus he cu en and he 2010 s ip ansec coun su eys. To p edic a
somewha eliable popula ion end, a ime se ies o a leas h ee es ima es is needed and
hese mus be ob ained while epea ing he same me hods. Albei he 2018 Dis ance
Sampling es ima e o ca. 60,469 ca ibou sugges s decline in KS ca ibou abundance and
some decline could be expec ed gi en bo h he poo cal ec ui men o he 2005-2010
pe iod and almos wo decades o ha es managemen aimed a educing KS ca ibou
abundance. Rega dless, he 2018 la e win e cal ec ui men does no suppo u u e
popula ion decline.
The 2018 Dis ance Sampling design-based es ima e, 60,500 ca ibou, was based on he
selec ed 19 line ansec s, which may o e - ep esen some ea u es wi hin he No h
egion, while unde - ep esen ing o he s. In an al e na e app oach, Co eia (2020) applied
Gene alized Addi i e Model (GAM) and Densi y Su ace Model (DSM) o he same 2018
su ey da a and hus conside ed he en i e No h egion. Co eia’s GAM/DSM analyses
esul ed in a 2018 Model-based popula ion size es ima e o 73,895 (95% CI: 65,983-82,757)
KS ca ibou, which had he excep ional CV o 0.037 (3.7%), lowe han ha o Dis ance
Sampling. Gi en he e a e wo es ima es begs he ques ion, which is mos accu a e and
p ecise? Add essing ha issue is beyond he scope o his echnical epo . Ins ead, i is
cu en ly being in es iga ed, equi es addi ional esul s om wo o he Wes G eenland
ca ibou su eys comple ed in 2019, and conclusions ega ding Dis ance Sampling and
Model-based es ima es will be published in a pee - e iewed jou nal.
Gi en he Dis ance Sampling es ima e o 60,500 ca ibou and he Model-based es ima e o
73,895 p esen ed by Co eia (2020), we can be ce ain ha despi e 18 yea s o ha es
managemen o he con a y, he KS ca ibou popula ion size emains la ge in ela ion o
50
he a ea a ailable, 23,303 km2. The o e all 2018 es ima e o KS ca ibou densi y was 2.6
ca ibou pe km2. Gi en good cal ec ui men , popula ion decline is no expec ed in he
immedia e u u e. As wi h he 2000, 2005 and 2010 su eys, he 2018 KS ca ibou densi y
exceeded he ecommended managemen a ge densi y o 1.2 ca ibou pe km2, abo e
which he e is assumed an inc eased isk o o e g azing leading o ca ibou decline
(Kingsley & Cuyle 2002, Cuyle e al. 2007). In No h Ame ica, when o e g azing played a
majo ole, ca ibou declines ook place o e 15 o 20 yea s (Schae e e al. 2016, Soullie e &
Hammel 2015). Ne e heless, e en a e almos wo decades ha e passed wi h high
densi ies exceeding he a ge , he e is no s ong e idence o ex ensi e o e g azing o
decline in he KS ca ibou. Since in 2018 ec ui men imp o ed o a leas 31 cal es pe 100
cows, despi e an o e all densi y o 2.6 ca ibou pe km2, i appea s ha ange condi ions in
he No h egion suppo a highe densi y han expec ed. Pending addi ional esul s om
wo o he Wes G eenland ca ibou su eys comple ed in 2019, he a ge densi y o
ca ibou managemen will ecei e e-e alua ion ega ding wha le el is compa ible wi h
demog aphics ha acili a e sus ainable popula ions and ha es s.
Acknowledgemen s
This p ojec was inanced p ima ily by he G eenland Go e nmen and o he wise by he
G eenland Ins i u e o Na u al Resou ces, Nuuk G eenland. G a e ul hanks go o Ai
G eenland Cha e and hei helicop e pilo Kå e Be li o his sa e lying. Thanks also o
he G eenland Associa ion o P o essional Hun e s (KNAPK) o p o iding an expe ienced
obse e , excellen a spo ing ca ibou despi e poo de ec ion condi ions. We also hank
Josephine Nymand o e iew o he manusc ip , and Emma K is ensen o e iew o he
summa y. The summa y was ansla ed in o Danish by Anna Haxen and o G eenlandic
by Emma K is ensen.
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Columbia. 140 pp.
Be ge ud A.T. 1971. The popula ion dynamics o New oundland ca ibou. Wildl. Monog . 25: 55 pp.
Be ge ud A.T. 1980. A e iew o he popula ion dynamics o ca ibou and wild eindee in No h Ame ica.
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54
Appendix 1
S a is ical me hods behind Dis ance Sampling
This appendix p esen s he basic building blocks and easoning behind Dis ance Sampling
(DS) design-based me hods, ollowed by some de ails. This summa y o s a is ical
me hods is om Co eia (2020).
Fundamen al concep s
Be o e en e ing in o he de ailed heo y behind he Dis ance Sampling me hodology, we
p esen a simple design, which is quad a o plo sampling (Buckland e al. 2001;
Ma ques, 2009).
In plo sampling, a egion o in e es wi h o al a ea 𝐴, is di ided in o small plo s o a ea
𝑎𝑝𝑙𝑜𝑡 (Fig. 14). Some o hese small plo s a e andomly chosen o sampling and he o al
numbe o indi iduals wi hin hese, 𝑛𝑝𝑙𝑜𝑡, is eco ded.
Figu e 14. Plo sampling g id example o o al a ea
𝐴
di ided in o smalle plo s o a ea
𝑎
𝑝𝑙𝑜𝑡
.
The densi y wi hin each plo , 𝐷𝑝𝑙𝑜𝑡, is he numbe o indi iduals pe uni a ea o he
espec i e plo so, by de ini ion, i is gi en by
Equa ion (1)
whe e 𝑎 is he o al a ea sampled wi hin 𝐴. (i.e., 𝑎 = 4 ⋅ 𝑎𝑝𝑙𝑜𝑡 = 4𝑘𝑚2 o Fig. 14) Since a
andom design was used, he densi y is a ep esen a i e es ima e, by design, o he o al
a ea 𝐴. Hence, an es ima e o he abundance, 𝑁
, can be ob ained by simply mul iplying
𝐷
plo by he o al a ea 𝐴,
Equa ion
(2)
55
𝑃
The DS me hodology is an ex ension o quad a -based sampling me hods. The de ail ha
c ea es he b idge om one me hodology o he o he is he ac ha he me hod desc ibed
abo e assumes ha e e y indi idual o in e es is de ec ed (Mille e al. 2016). F equen ly,
his assump ion canno be me , speci ically i among he indi iduals o in e es he e a e
animals impossible o obse e owing o low sigh abili y. Se e al ac o s cause low
sigh abili y, including opog aphical ba ie s, wea he condi ions, g ound su ace
condi ions and many o he s ela ed o obse e aining and su ey design. The
p opo ion o indi iduals ha we e no de ec ed can be es ima ed using he de ec ion
unc ion i ed o he obse ed dis ances (Thomas e al. 2002). Once his p opo ion is
es ima ed, i can be conside ed o ob ain mo e accu a e es ima es and hen, an
ex apola ion o a wide egion can be done simila ly as shown in Equa ion (2).
In Dis ance Sampling, his p opo ion o de ec ed objec s in he a ea 𝑎 is de ined as he
p obabili y o de ec ion, 𝑃𝑎. The e o e, a densi y es ima e can be ob ained as pe Equa ion
(1) by adjus ing 𝑛𝑝𝑙𝑜𝑡 by 𝑃𝑎, i.e., by co ec ing he de ec ions o hose ha we e missed.
Since he la e canno be known, in gene al, an es ima e mus be also ob ained, hus
Equa ion
(3)
whe e 𝑃
a is an es ima e o 𝑃𝑎 ob ained om he dis ance da a, and 𝑎 is he a ea o he
sampled egion. Usually 𝑎 = 2𝑤𝐿, wi h 𝑤 as he unca ion dis ance, o bo h sides o he
cen eline, and he o al ansec leng h 𝐿 = ∑𝑙𝑗
𝑘
𝑗=1 , whe e 𝑙 is he leng h o ansec 𝑗.
Abundance can be de e mined using a easoning analogous o ha abo e (Equa ion 2).
The unca ion dis ance is de ined as he dis ance beyond which dis ances a e no
eco ded. This can be de ined in he ield o a he analysis s age.
The coe icien o a ia ion o 𝐷
, c𝑣(𝐷
), is ela ed wi h wo andom componen s
e e ed abo e, encoun e a e (𝑛𝑝𝑙𝑜𝑡/𝐿), and 𝑃
a, plus a hi d one ha is he es ima e o he
expec ed size o de ec ed clus e s (𝐸
 (𝑠)). Assuming independence be ween hese, he
o me is gi en by
Equa ion
(4)
An app oxima ion o he s anda d e o o 𝐷
, 𝑠𝑒(𝐷
), is de ined as
Equa ion
(5)
56
Once hese a e ob ained, an app oxima e 100(1 − 𝛼)% con idence in e al (CI) can be
de e mined by
Equa ion
(6)
Whe e is he quan ile o he N(0,1) dis ibu ion 1.96
o a 95% con idence in e al). Howe e , he dis ibu ion o he 𝐷
is posi i ely skewed,
hus an in e al assuming ha 𝐷
 is log-no mally dis ibu ed has be e co e age.
Acco ding wi h Buckland e al. (2015), a 100(1-alpha)% con idence in e al can be gi en by
Equa ion
(7)
whe e
Equa ion
(8)
and
Equa ion
(9)
Fo u he de ails see Buckland e al. (2001) and Buckland e al. (2015).
P obabili y o de ec ion
Gi en he abo e, he p obabili y o de ec ing an objec , gi ing ha i is wi hin he a ea
co e ed by he ansec s, 𝑃
a, needs o be es ima ed. Fo his p ojec , he objec o in e es
consis s in ca ibou g oups.
To illus a e he impo ance o his p obabili y, conside ha an obse e walks ac oss a
la ge pa ch o und a and de ec s 8 ca ibou (Fig. 15). While discussing wi h he local
biologis , and conside ing he biologis ’s expe ience, he/she will s a e ha , on a e age,
only one hi d o all ca ibou p esen a e de ec ed (i.e., 𝑃
a = 1/3) meaning ha p obably
he e we e a ound 24 ca ibou wi hin ha pa ch o und a and 16 ha e been missed. Tha is
whe e Dis ance Sampling is use ul, since i allows a igo ous amewo k o he es ima ion
o Pa and hen an es ima e o abundance can be ob ained as shown in Equa ion (3).
57
Figu e 15. Example o a pa ch o und a wi h he ansec in he middle. Blue do s ep esen eigh obse ed ca ibou,
while o ange do s ep esen he 16 unde ec ed ones. The lines pe pendicula o he ansec ep esen he eco ded
dis ances.
Dis ance Sampling me hods
The de ec ion unc ion, 𝑔(𝑦), desc ibes he p obabili y o de ec ing an objec o in e es
gi en ha i is a a dis ance 𝑦, om he cen eline (also known as 0-line), hus being a non-
inc easing unc ion o 𝑦 (Buckland e al. 2015).
Fo line ansec s, 𝑦 is he pe pendicula dis ance om he 0-line o he de ec ed objec .
Wi hin Dis ance Sampling me hods, he p obabili y o de ec ion is explained ecu ing o
hese obse ed dis ances (Buckland e al. 2001). Some imes co a ia es may be added o
explain hei ela ionship wi h he de ec ion p obabili y. In his si ua ion, we a e wi hin
he Mul iple Co a ia e Dis ance Sampling (MCDS) amewo k (Buckland e al. 2001).
Con en ional Dis ance Sampling
Con en ional Dis ance Sampling (CDS) occu s when no addi ional co a ia es a e added o
he model. Once he de ec ion unc ion is es ima ed, 𝑃
a can be ob ained ia he ollowing
equa ion
Equa ion (10)
whe e 𝜋(𝑦)= 1
𝜔 and, he e o e, used o es ima e densi y using Equa ion (3). Fo 𝑔(𝑦) i is
also speci ied a lexible semi-pa ame ic model, composed by a key unc ion and some
64
on Mises es and he 𝜒2 Goodness-o -Fi es (GOF es ). The likelihood a io es can also
be used bu , since i is only applicable o nes ed models, AIC is he ecommended me hod
(Ma ques e al. 2007). A p ope model should be simple wi h an adequa e i wi hou
o e i ing he da a.
Akaike In o ma ion C i e ion
The ela i e i o al e na i e models may be e alua ed ecu ing o AIC, o AICc, in case
o small samples, p o iding a small sample bias co ec ion (Buckland e al. 2001). These
c i e ia can be de e mined as ollows
Equa ion (15)
Equa ion (16)
whe e
ℒ
is he likelihood unc ion, 𝑞 is he numbe o es ima ed pa ame e s in he model,
and 𝑛 is he sample size. This measu e p o ides a ade-o be ween bias and a iance.
AIC includes wo e ms, one ela ed wi h he i ed model, and he o he wo king as a
penal y conside ing he excess o pa ame e s in he model (B ewe e al. 2016).
Kolmogo o -Smi no es
The Kolmogo o –Smi no es is one o he es s ha can be applied o he de ec ion
unc ion o assess model i (Buckland e al. 2004). This es is only applicable o
con inuous da a, being p e e able o he 𝜒2 GOF es o MCDS me hods.
Conside ing he cumula i e dis ibu ion unc ion (c.d. .) 𝐹 (𝑥) = 𝑃 (𝑋 ≤ 𝑥) and he empi ical
c.d. . (e.d. .) 𝑆(𝑥), he null hypo hesis o be es ed is 𝐻0 ∶ 𝐹 (𝑥) = 𝐹0(𝑥), ∀𝑥. The al e na i e
hypo hesis s a es ha bo h unc ions di e o a leas some alue o 𝑥. In p ac ice, 𝐹 (𝑥) is
eplaced by i s es ima e, and 𝐻0 s a es ha he assumed model is he ue model o he
da a (Buckland e al. 2004). The la ges absolu e di e ence be ween 𝐹
(𝑥) and 𝑆(𝑥), deno ed
𝐷𝑛, is he es s a is ic (Gibbons and Chak abo i 2011). The co esponding 𝑝- alue can be
app oxima ed by
Equa ion (17)

65
C amé - on Mises es
Simila o he Kolmogo o -Smi no es , he C amé - on Mises es sha es he same null
hypo hesis and basis on di e ences be ween c.d. . and e.d. . Howe e , ins ead o
conside ing only he la ges di e ence be ween he wo unc ions, his es is based on
hei en i e ange (Buckland e al. 2004). The es s a is ic can be gi en by
Equa ion (18)
Chi-squa e Goodness-o -Fi es
The 𝜒2 Goodness-o -Fi es (Buckland e al. 2001, 2015) compa es he obse ed
equencies, ni, wi h he expec ed equencies unde he model E(ni) and i is gi en by
Equa ion (19)
unde he null hypo hesis (H0) o good model i ing, i.e., he di e ence be ween he
obse ed (ni) and expec ed (E(ni)) coun s is close o ze o. In Equa ion (19), n is he o al
numbe o obse a ions, u is he numbe o g oups (o bins) wi hin he dis ance da a, and q
is he numbe o model pa ame e s es ima ed. Rejec H0 i 𝑋𝑜𝑏𝑠
2 > 𝑋1−𝛼;(𝑢−𝑞−1)
2, wi h he
la e ep esen ing he 1–𝛼 quan ile om a 𝜒2 dis ibu ion wi h u-q-1 deg ees o eedom.
As he numbe o pa ame e s o he i ed model inc eases, he bias dec eases, bu he
sampling a iance inc eases (Buckland e al. 2001). While he Goodness-o -Fi es esul s
should be conside ed in he analysis o dis ance da a, hey will be o limi ed alue in
selec ing a model since hese es s a e sensi i e o heaping. The e o e, ca e is needed in
choosing sui able dis ance in e als.
I da a a e collec ed wi h no ixed 𝜔, i is possible ha a ew ex eme ou lie s will be
eco ded. These alues a e no use ul, and he da a should he e o e be unca ed. This can
be checked using he dis ances’ his og am, and whe he he e is e idence o heaping o
no (Buckland e al. 2001; Cou u ie e al. 2018).
66
Goodness-o -Fi es s allow o mal es ing o whe he a de ec ion unc ion model p o ides
an adequa e i o he da a. Since he GOF es canno be used on con inuous da a, unless
g ouped, i is o limi ed use o es ing MCDS models (Buckland e al. 2015), being use ul
o es ing models using CDS me hods. Howe e , i dis ances a e no g ouped, hey mus
i s be ca ego ized in o g oups o allow he es o be conduc ed. Thus, he e is a
subjec i e aspec o he es , and di e en analys s, using di e en g oup cu poin s, may
each di e en conclusions abou he model adequacy. In con as , he Kolmogo o –
Smi no and C amé – on Mises es s can only be applied o con inuous da a (Buckland e
al. 2015).
67
Appendix 2
Dis ance Sampling Assump ions – sho summa y
Line ansec Dis ance Sampling assump ions and design a e desc ibed in
Buckland e al. (1993) and a summa y o he assump ions o su ey o la ge
he bi o es in G eenland p o ided below a e om Cuyle e al. (2016).
1. All ca ibou on he 0-line a e de ec ed. This is c i ical and mus be ue.
2. Ca ibou a e andomly dis ibu ed. (Lacking his will no bias
abundance es ima es i he ansec lines a e andomly placed, which
hey we e.)
3. De ec ion o ca ibou is independen . (Al hough de ec ion was
dependen in ou su ey, he lines had andom s a -end poin s, so his
assump ion is no iola ed).
4. No ca ibou mo emen p io o de ec ion. The me hod is a ‘snapsho ’
me hod. In p ac ice his assump ion is no iola ed i he obse e
mo es as e han he animal, e.g., i mo emen o ca ibou o he nex
ansec line o be su eyed is ende ed impossible, which i was.
5. Dis ance measu emen s a e exac . P o ided dis ance measu emen s a e
app oxima ely unbiased, bias in line ansec es ima es ends o be
small in he p esence o measu emen e o s. In ou su ey we binned
he obse a ions in o dis ance in e als which dec eases measu emen
e o .
6. Clus e s (ca ibou g oups) close o he 0-line a e accu a ely sized.
7. O he assump ions include hose o o he su ey ypes, e.g., ha each
popula ion is closed, being con ined wi hin a clea ly de ined a ea.
68
Appendix 3
Recommenda ions o imp o ing u u e su eys.
Ae ial su ey me hods & design
The 10.6% su ey co e age in 2018 p omo es accu acy o abundance es ima es
and should be con inued in u u e o acili a e e alua ing popula ion ends.
The ligh al i ude could be educed o 30-35 m. The ligh al i ude o 40m
while obse e s scanned he landscape ou o 1000-1500m om he 0-line was
men ally exhaus ing. This was because he amoun o e ain o be scanned
was oo g ea o e en he ela i ely slow speed lown (60-70 km/hou ), gi en
he high deg ee o backg ound camou lage ha hides ca ibou. Al hough an
al i ude o 30-35m likely will cause amoun o ‘dead’ g ound o inc ease, he
Dis ance Sampling will mi iga e o any ca ibou missed, p o ided ha dead
g ound is no on he line (which he e is no eason o expec i migh be).
Meanwhile, obse e abili y o judge co ec dis ance bin may imp o e. I is
he au ho ’s expe ience ha wi hou p ac ice people commonly misjudge
dis ance. Looking down om abo e can exace ba e his endency. A lowe
angle o he e ain could p o ide a mo e (no mal) ho izon al line-o -sigh o
he animals and may inc ease binning accu acy.
The iming o ae ial su eys could emain ea ly Ma ch because i coincides
wi h annual minimum ca ibou mo emen (a oids double coun ing), and
enough day leng h o lying he pilo maximum o 7-hou s pe day.
Expe ience om eigh su eys since 2000 has illus a ed ha snow co e and
dep h is a iable ega dless o he win e pe iod chosen.
Demog aphics
When lying line ansec s, dis ance and o he ac o s o en make
iden i ica ion o cal es impossible, esul ing in an unde es ima e o cal
numbe . He d s uc u e da a mus con inue o be collec ed in e o s sepa a e
om lying he line ansec s o Dis ance Sampling.
Logis ics
Check whe he o he helicop e op ions a e a ailable. To da e, he smalles
helicop e a ailable is he AS350 om Ai G eenland (Cha e ). The AS350
pe mi s limi ed ision o ea obse e s, owing o he small window size
con aining se e al ba /s u s, and which unde cold ambien empe a u es
always og wi h ice- os . These ac o s educe isibili y o e ain.
69
Appendix 4
Pho og aphs o KS ca ibou su ey condi ions Ma ch 2018
Figu e 19. Rugged e ain wi h good sunli condi ions (abo e), and excellen , almos comple e snow
co e wi h shadows (below). Pho os C. Cuyle .

70
Ca ibou su ey condi ions Ma ch 2018
Figu e 20. Po ions o line ansec s lown ac oss high ele a ions, Sisimiu Sou h sub-a ea. Pho os C.
Cuyle .
71
Ca ibou su ey condi ions Ma ch 2018
Figu e 21. Fla ligh combined wi h g ound showing h ough hin laye o snow. Pho os C. Cuyle .
72
Ca ibou su ey condi ions Ma ch 2018
Figu e 22. Vege a ion poking h ough hin snow laye in la ligh (abo e) o wi h shadows (below).
Pho os C. Cuyle .
73
Ca ibou su ey condi ions Ma ch 2018
Figu e 23. Thin snow laye wi h g ound showing h ough (abo e), o ocks and ege a ion (below).
Pho os C. Cuyle .