2019 Status of Akia-Maniitsoq caribou population, Central region, West Greenland. Technical Report No. 124

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2019 S a us o Akia-Manii soq ca ibou
popula ion, Cen al egion
Wes G eenland
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Ti le: 2019 S a us o Akia-Manii soq ca ibou popula ion, Cen al
egion, Wes G eenland.
Au ho s: Ch is ine Cuyle 1, Tiago A. Ma ques2, Iú i J.F. Co eia3, Aslak
Jensen4, Hans Mølgaa d5 and Jukka Wagnhol 6
1 Pinngo i ale i ik – 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, 3900 Nuuk, G eenland
5 P.O. Box 122, 3911 Sisimiu , G eenland
6 Tusass, P.O. Box 1002, 3900 Nuuk, G eenland
Se ies: Technical Repo No. 124, 2023
Da e o publica ion: 06 Ap il 2023
Publishe : Pinngo i ale i ik – G eenland Ins i u e o Na u al Resou ces
Financial suppo : Go e nmen o G eenland and Pinngo i ale i ik – G eenland
Ins i u e o Na u al Resou ces
ISBN: 978-87-972977-7-3
ISSN: 1397-3657
EAN: 9788797297773
Co e pho o: Aslak Jensen: One o many la ge ca ibou g oups o he Akia-
Manii soq popula ion, Na ssa ssuaq alley, Cen al egion.
Ci ed as: Cuyle , C., Ma ques, T.A., Co eia, I.J.F., Jensen, A., Mølgaa d,
H. & Wagnhol , J. 2023. 2019 S a us o Akia-Manii soq ca ibou
popula ion, Cen al egion, Wes G eenland. Pinngo i ale i ik
– G eenland Ins i u e o Na u al Resou ces. Technical Repo
No. 124. 93 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 ps://na u .gl/ o skning/ appo e /
Pinngo i ale i ik – G eenland Ins i u e o Na u al Resou ces
P.O. Box 570, 3900 Nuuk, G eenland
Phone: +299 36 12 00
E-mail: in o@na u .gl
www.na u .gl
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2019 S a us o Akia-Manii soq ca ibou
popula ion, Cen al egion,
Wes G eenland
By
Ch is ine Cuyle 1, Tiago A. Ma ques2, Iú i J.F. Co eia3,
Aslak Jensen4, Hans Mølgaa d5 and Jukka Wagnhol 6
1 Pinngo i ale i ik – 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, 3900 Nuuk, G eenland
5 P.O. Box 122, 3911 Sisimiu , G eenland
6 Tusass, P.O. Box 1002, 3900 Nuuk, G eenland
Technical Repo No. 124, 2023
Pinngo i ale i ik – G eenland Ins i u e o Na u al Resou ces
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[Emp y page]
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Table o Con en s
Summa y (English)……………………………………… 8
Eqikkaaneq (kalaallisu ) ………………………………. 9
Resumé (dansk)………………………………………… 11
In oduc ion ……………………………………………. 13
Me hods …………………………………………………. 15
Resul s…………………………………………………… 23
Discussion ……………………………………………… 47
Acknowledgemen s……………………………………... 55
Li e a u e ci ed.………………………………………… 56
Figu es
1.
Bo de s o he Cen al egion, …
Page 13
2.
A ea co e ed by 2019 su ey o he Cen al egion (11,575 km2), which is…
Page 16
3.
The 50 line ansec s used in he 2019 su ey o Cen al egion…
Page 19
4.
Loca ion and g oup size o ca ibou de ec ions ( unca ed da a) …
Page 25
5.
Explo a o y analysis o he numbe o de ec ions by sub-a ea …
Page 26
6.
Explo a o y analysis o g oup size dis ibu ion among de ec ions…
Page 26
7.
Explo a o y analysis o ca ibou encoun e a e pe line ansec …
Page 27
8.
Obse e e ec : his og ams illus a ing de ec ed dis ances o Obse e s …
Page 27
9.
No. ca ibou de ec ions pe co a ia es heli.side, la ligh , and camou lage …
Page 29
10.
No. ca ibou de ec ions pe co a ia es ege a ion/g ound o boulde s…
Page 29
11.
No. ca ibou de ec ions pe co a ia es sola gla e, dead g ound, wea he …
Page 30
12.
Summa y o he equency o ele a ions lown ( unca ed da a).
Page 30
13.
His og am o obse ed ca ibou dis ances o non- unca ed da a and …
Page 31
14.
His og am o Haza d- a e wi h Camou lage as co a ia e o de ec ed …
Page 33
15.
Es ima ed p obabili ies o de ec ion o each obse ed g oup size…
Page 33
16.
Ca ibou densi y (le ) and abundance ( igh ) es ima es wi h co esponding
Page 35
17.
Unusually high numbe s o ca ibou, o en in excep ionally la ge g oups …
Page 40
18.
These 17 ca ibou could be sexed and aged owing o g oups sepa a ion …
Page 40
19.
Obse ed equency o cow-cal pai s o 96 g oups o which…
Page 42
20.
Obse ed ecen snowmobile ac i i y in Akia (No dlande ), which …
Page 45
21.
Pas and p esen ca ibou popula ion size es ima es wi h con idence …
Page 47
22.
Pas and p esen ca ibou densi y es ima es o he Akia-Manii soq …
Page 47
23.
Pas and p esen la e win e bull o cow a ios o he Akia-Manii soq …
Page 50
24.
Pas and p esen la e win e cal (age 10-mon h) ec ui men …
Page 50
25.
Akia sub-a ea, illus a ing ypical condi ions.
Page 58
26.
Fog o e he Manii soq Coas sub-a ea, which p e en ed planned ligh s.
Page 58
27.
Akia sub-a ea o Cen al egion, illus a ing jus no h o G eenland’s …
Page 59
28.
Akia sub-a ea o Cen al egion, illus a ing ugged Akia (No dlande ) …
Page 59
29.
Akia sub-a ea, wes end o line ansec 10, iew ENE.
Page 60
30.
Akia sub-a ea, hin mou h o Niaqungunaq (Fiske jo d) and condi ions …
Page 60
31.
Akia sub-a ea in he alley, Na ssa ssuaq, illus a ing g ound condi ions…
Page 61

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32.
Akia sub-a ea illus a ing g ound condi ions a eas end o line ansec 22…
Page 61
33.
Akia sub-a ea, alley no h o Ilulialik jo d, illus a ing g ound …
Page 62
34.
Akia sub-a ea, iew wes ac oss unnamed peninsula (which is …
Page 62
35.
Manii soq Coas sub-a ea, iew o he no h om line ansec 55, in …
Page 63
36.
Manii soq Coas sub-a ea illus a ing moun ainous e ain and condi ions…
Page 63
37.
Uja assui sub-a ea, illus a ing ypical condi ions o e ain, snow, and …
Page 64
38.
Uja assui sub-a ea on he one day wi h sunshine, iew wes om he …
Page 64
39.
Uja assui sub-a ea, eas end o line ansec 35, iew o wes illus a ing …
Page 65
40.
Uja assui sub-a ea, illus a ing ypical e ain, snow, and sunligh …
Page 65
41.
Uja assui sub-a ea e ain, snow, and la ligh condi ions a he eas …
Page 66
42.
Uja assui sub-a ea, illus a ing ypical e ain, snow, and sunligh …
Page 66
43.
Uja assui sub-a ea, illus a ing ugged highland e ain, snow dep hs …
Page 67
44.
Uja assui sub-a ea, xe ic condi ions o eas end line ansec 32, iew N …
Page 67
45.
Uja assui sub-a ea, I isa oq highlands iew eas owa ds small bay …
Page 68
46.
Uja assui sub-a ea, I isa oq highlands illus a ing almos non-exis en …
Page 68
47.
Place names used ega ding Cen al egion (ca. 64°–66°N; 50°–53°W), …
Page 69
48.
Plo sampling g id example o o al a ea A di ided in o smalle plo s…
Page 70
49.
Example o a pa ch o und a wi h he ansec in he middle…
Page 73
50.
Hal -no mal ( op ow) and haza d- a e (bo om ow) de ec ion unc ions…
Page 75
51.
Possible shapes o he de ec ion unc ion when cosine adjus men s a e….
Page 76
52.
A good model o he de ec ion unc ion should ha e a shoulde …
Page 79
53.
Eigh ca ibou, se e al camou laged agains backg ound, wi hin 200 m o …
Page 84
54.
Th ee ca ibou camou laged agains backg ound, wi hin 100 m om …
Page 84
55.
His og ams o de ec ed dis ances supe imposed wi h es ima ed …
Page 87
56.
The h ee obse e s, D . C. Cuyle …, Aslak Jensen, …, Hans Mølgaa d …
Page 89
57.
AS350 Helicop e iewing windows o he le and igh sides, …
Page 91
Tables
1.
La e win e popula ion pa ame e s, Akia-Manii soq ca ibou popula ion…
Page 14
2.
Summa y o unp ocessed esul s: Su ey o Akia-Manii soq ca ibou …
Page 23
3.
Model compa ison ac oss h ee Con en ional Dis ance Sampling models…
Page 34
4.
Encoun e a e (ER) es ima es pe sub-a ea (s a um) o ca ibou g oups…
Page 35
5.
Es ima es o abundance pe sub-a ea (s a um) o he Akia-Manii soq …
Page 36
6.
Es ima es o densi y pe sub-a ea (s a um) o he Akia-Manii soq …
Page 36
7.
Mo emen o non-mo emen o ca ibou eac ing o helicop e ly-by…
Page 37
8.
De ails o mo emen o non-mo emen o ca ibou eac ing o helicop e …
Page 38
9.
Demog aphics o Akia-Manii soq ca ibou popula ion, Cen al egion …
Page 39
10.
G oup size ela i e o composi ion Akia-Manii soq ca ibou popula ion …
Page 42
11.
App oxima e ele a ions o ca ibou g oups obse ed…
Page 44
12.
Commonly used key unc ions and se ies expansions o de ec ion unc ion.
Page 74
13.
De ec ion unc ion pa ame e s’ es ima es.
Page 87
14.
Recen ca ibou popula ion es ima es & minimum coun s o Wes …
Page 92
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Appendices
1.
Pho os, Cen al egion ae ial su ey condi ions…Ma ch 2019
Page 59
2.
Place names o he Cen al egion
Page 70
3.
S a is ical me hods behind Dis ance Sampling
Page 71
4.
Dis ance Sampling Assump ions – sho summa y
Page 84
5.
Pho os o camou laged ca ibou obse ed Ma ch 2019
Page 85
6.
His og ams o de ec ed dis ances
Page 86
7.
Recommenda ions o imp o ing u u e su eys
Page 89
8.
Recen ca ibou popula ion es ima es & minimum coun s o Wes G eenland
Page 93
Raw da a may be accessed by con ac ing Pinngo i ale i ik – G eenland Ins i u e o Na u al Resou ces,
Depa men o Mammals and Bi ds.
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Summa y (English)
This epo p esen s esul s om he ae ial su ey ca ied ou by helicop e in
ea ly Ma ch 2019, o he Akia-Manii soq ca ibou popula ion inhabi ing he
Cen al egion in Wes G eenland. This popula ion was las su eyed in Ma ch
2010. New es ima es o abundance we e o e due. Helicop e su eys in 2001,
2005 and 2010 used s ip ansec coun s. The Ma ch 2019 helicop e su ey,
howe e , used Dis ance Sampling me hods.
Fo Ma ch 2019, he Akia-Manii soq ca ibou popula ion abundance was
es ima ed a 48,941 ca ibou (95% CI: 37,612 – 63,682; CV = 0.131; SE = 6390), wi h
a densi y o 4.2 ± 0.5 ca ibou/km2 (95% CI: 3.2–5.5). The dis ance sampling
es ima e was p ecise gi en he excellen CV alue (0.13). Su ey co e age was
9.6% ( unca ed da a), which is a ca. i e- old imp o emen om he 2001, 2005,
2010 s ip ansec coun su eys, whe e co e age was always below 2%.
Despi e 18 yea s o ha es managemen aimed a con olling ca ibou
abundance and densi y, by Ma ch 2019 Akia-Manii soq ca ibou popula ion size
was double wha i was in 2010. Con idence In e als o he 2010 and 2019
su ey es ima es do no o e lap, he e o e we conclude he Akia-Manii soq
popula ion size uly doubled o e he nine-yea pe iod, 2010-2019.
The o e all densi y es ima e o he Akia-Manii soq popula ion was 4.2 ca ibou
pe km2. This alue is much g ea e han he managemen ecommended a ge
o 1.2 ca ibou pe km2 (Kingsley & Cuyle 2002, Cuyle e al. 2007). Fu he ,
densi y in he Akia sub-a ea a e aged 6.6 ca ibou pe km2. Exceeding he a ge
ca ibou densi y is assumed o aise he isk o o e g azing and hus decline in
ca ibou abundance.
The la e-win e cal pe cen age and cal ec ui men we e he highes e e
eco ded om helicop e su eys. Values emained high e en a e he
unusually high numbe o o phan cal es (n = 83) we e emo ed om he
calcula ions. The 2019 a io o 49 bulls o 100 cows, e e sed he downwa d
end ( om 58 o 38 bulls pe 100 cows) in 2001-2010 pe iod o animals age > 1-
yea . We conclude he 2019 demog aphics o he Akia-Manii soq popula ion
p o ides po en ial o u he g ow h in abundance, albei no wi hs anding
u u e ca as ophic s ochas ic e en s, including ex eme wea he and pa hogen
ou b eaks.
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En i onmen al condi ions du ing he 2019 su ey p o ided ex ao dina y
camou lage o ca ibou. Pooling en i onmen al co a ia es in o a single index o
camou lage will imp o e de ec ion unc ion modelling. Skilled obse e s and
lying helicop e s low and slow we e c i ical ac o s pe mi ing de ec ion o
ca ibou, speci ically because 25% o all g oups emained s a iona y.
Beyond popula ion pa ame e s, esul s o in e es included ela i ely low
ele a ions, mean 351 m, used by he Akia-Manii soq ca ibou popula ion in ea ly
Ma ch. Among o he hings, his e lec s he ela i e abundance o low
ele a ions in he egion. Fu he , al hough an le s a e ypical on emale ca ibou,
ew (32%) cows possessed an le s in he Akia-Manii soq popula ion.
Eqikkaaneq (kalaallisu )
Uani nalunaa usiami saqqummiunneqa pu nunap immikkoo uani
u u assiissu inik aqu si iusuni qulimiguulik a o lugu Ma sip aalla ilaa -
ne ani 2019-imi u unik kisi sine ni ine ne i . Tu u aakku pineqa u
nunaa a ki aa a qi e pasissuaniippu . Tu u oqa igiiaa kingulle mik kisi si-
igineqa pu ma simi 2010-mi. Taamanikku u u ame lassusiisa missilio -
neqa ne anni ame lanaagaappu . Qulimiigulik a o lugu 2001-imi, 2005-imi,
2010-milu kisi sine ni pe iuseq a o neqa oq assaa oq, qulimiguulimmi
akusa aalajange simasumik kisi se iaaseq, aaguu eqa inneqa oq Dis ance
Sampling me hods.
Akia-Manii sumi u u ma s 2019 48,941-nik (95% CI: 37,612 – 63,682; CV =
0.131; SE = 6390) ame lassuseqa nissaa missiliuunneqa poq, naa so suine -
igullu u u k ad a kilome e -imu , km2-imu , eqimassuseqa nissaa 4.2 ± 0.5
u u /km2 (95% CI: 3.2–5.5) aalajangiunneqa poq. The dis ance sampling
missiliussineq, CV-kisi si ajunngilluinna oq (0.13-ulluni). Nuna kisi si iusoq
qulangiuaa neqa o lu 9.6%-iu oq ( unca ed da a), assuunalu akuneqa poq
u u 2001-imi, 2005-imi 2010-milu kisinneqa ne anni allima iaammik
ame le ia simasu , kisi se iaaseq aanna piaq a o lugu, kisiannili nunap
kisi si igineqa up angissusia ama igu 2 % a aa a simagaa.
Naak ukiuni 18-ini u u ikilisa nia lugi kiisalu ame lassusiisigu
eqimassusiisa aqussinnaale nissaa angunia lugu aqu sisoqa simagalua oq,
aamaa oq ma s 2019-imi 2010-mu sanilliullugu ma lo iaammik
ame lassuseqale simappu . CI (con idence in e al, assa kisi sisi u suigina-
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Figu e 2. A ea co e ed by he 2019 su ey o he Cen al egion (11,575 km2), which is inhabi ed by he
Akia-Manii soq ca ibou popula ion. Fou di e en colou s illus a e he ou sub-a eas, designa ed as
Akia, Manii soq coas , Manii soq inland, and Uja assui . G eenland’s capi al ci y, Nuuk, is he ed
diamond on he ip o g ey peninsula a m in bo om le co ne .

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The Cen al egion (ca. 64°/64°45’–66°N; 50°–53°W) is sha ed by he Qeqqa a
and Nuuk Kommunia. The only la ge se lemen , which is si ua ed on an island,
is he coas al ci y o Manii soq wi h ca. 2,534 inhabi an s. O he wise, he e a e
h ee small illages, also coas al, which combined con ain a u he ca. 650
people. In 2019, use o snowmobiles was s ill p ohibi ed beyond se lemen
bounda ies. See Appendix 2 o place name de ails.
The Cen al egion is seasonally ice- ee and co e s an a ea o 11,575 km2,
(excluding lakes, i e s, sand, glacie s, and islands) (Fig. 2). P e ious su eys
epo ed a less p ecise la ge land a ea o ca. 15,362 km2, which included lakes,
i e s, and islands (Cuyle e al. 2003, 2005, 2011). The no he n bo de is
o med by wo ice caps (i.e., Kangaamiu Se mia (Sukke oppen Ice Cap) and
Tase siap Se mia) and he wes e n po ion o he Kange lussuaq Fjo d. The
sou he n bo de is amed by he Nuuk jo d (God håbs jo d), which cu en ly
is ice- ee yea - ound o as a as Ilulialik Bay o he Uja assui paa a jo d-a m.
The wes e n bo de is he pe manen ly ice- ee seacoas o he Da is S ai , and
he eas e n bo de is he G eenland Ice Cap.
The coas al opog aphy in he no h is moun ainous. Ele a ions a e o en 1000 o
2000 m and glacie s p edomina e. Midway, he coas is moun ainous wi h peaks
om abou 500 o 1200 m. In he sou h, coas al opog aphy is ugged lowlands
o ele a ions gene ally below 200 m.
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. The ae ial su ey pe iod o he Akia-Manii soq ca ibou popula ion
was 01-12 Ma ch 2019. The pla o m o obse a ion was a helicop e AS350.
Pilo moni o ing o helicop e ada al ime e made main enance o a cons an
al i ude possible by cons an ly adjus ing o e ain ea u es while lying low (40
m, ca. 120 ee ) and slow (ca. 65 km/hou ).
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 , p o essional hun e Aslak Jensen
(G eenland Associa ion o P o essional Hun e s (KNAPK)) om Nuuk and
Sisimiu hun ing o ice Hans Mølgaa d. Cuyle always sa in on and was he
18
da a eco de . Cuyle (Obse e 2) ocused on de ec ing ca ibou di ec ly on
ack line (cen e line, 0-line) be o e animals led o line owing o app oaching
helicop e . Jensen and Mølgaa d (Obse e 1 and 3, espec i ely) we e sea ed in
he ea o he helicop e , on ei he side. The side hey sa on al e na ed each
ime he helicop e was e ueled, which was usually once daily and some imes
wice. Jensen and Mølgaa d could no iew he ack line bu obse ed animals
o all dis ances beyond. Ve bal con ac among he obse e s pe mi ed he
digi al audio eco ding o all obse a ions and, mos impo an ly, p e en ed
any double coun ing o g oups de ec ed by mo e han one obse e . 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 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. Fo each de ec ion, he
audio eco ding included dis ance o (see below) ca ibou g oup, as well as
g oup size and beha io and name o he obse e . G ound su ace and wea he
condi ions we e also eco ded. Manual click-coun e s, logging he numbe o
ca ibou seen by an indi idual obse e , p o ided low- ech back-up o double-
checking he digi al audio obse a ions o each line ansec .
Su ey design
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 (Buckland e al. 2001). Thus, he ansec axis di ec ion (eas -wes
axis) was chosen as pe pendicula o p e iously known animal dis ibu ion
g adien s in Ma ch and he wes -eas clima e g adien om we ma i ime o d y
con inen al. An ini ial line ansec was compu e gene a ed a andom in each
sub-a ea (see below), and he o he s ollowed a 10 o 20 km apa . The line
ansec s lown p o ide he maximum a ea co e age possible gi en he inancial
esou ces a ailable. Because some a p io i ansec s became combined du ing
he su ey, line iden i ica ion numbe s a e no consecu i e.
The su eyed Cen al egion, 11,575 km2, was di ided in o ou sub-a eas,
named Akia (4,150 km2), Manii soq Coas (3,375 km2), Manii soq Inland (2,011
km2) and Uja assui (2,039 km2) (Fig. 2). Sampling design o he 2019 su ey
conside ed 50 sys ema ic pa allel line ansec s ( ack lines lown) o a iable
leng h placed o e he ou sub-a eas (Fig. 3). Line ansec s we e sepa a ed by
10 km, excep ing Manii soq Coas sub-a ea, which we e 20 km.
19
Figu e 3. The 50 line ansec s used in he 2019 su ey o he Cen al egion, Akia-Manii soq ca ibou
popula ion, employing he same ou colou s as applied o he ou sub-a eas in igu e 2: Akia ( ed, 21
lines), Manii soq Coas (blue, 11 lines), Manii soq Inland (o ange, 8 lines), and Uja assui (black, 10
lines). Line ansec s sepa a ed by 10 km, excep Manii soq Coas , which we e sepa a ed by 20 km. Line
ansec numbe ing is no consecu i e, as some a p io i lines became amalgama ed du ing su ey.
The dis ance o a de ec ed ca ibou g oup (objec -o -in e es ) was be o e ca ibou
mo emen occu ed. Tigh ly cohesi e beha io iden i ied g oups o mul iple
indi iduals. Excep ing g oups on he ack line, which was dis ance 0 m,
dis ance was he obse e ’s ins an aneous and subjec i e es ima e o he
dis ance o cen e o he ca ibou g oup. Exac dis ance measu emen om he
ack line (aka 0-line o cen e line) o a ca ibou g oup was e ec i ely ne e
possible because o p ac ical conside a ions (de ails in Cuyle e al. 2021).
The e o e, like all p e ious helicop e ca ibou su eys in G eenland, o dis ance
measu emen pe pendicula o he ack line, we app oxima ed wi h ough
“dis ance bins”, i.e., in me e s, 0-50, 50-100, 100-200, 200-300, 300-400, 400-500,
500-600, 600-700, 700-800, 800-900, 900+. Bin alue eco ded o a g oup was
always he uppe limi o he bin applied. Fo analysis, we did no co ec o he
40m al i ude o he helicop e . Ins ead, we e-coded he epo ed uppe dis ance
alues o mid-dis ance o a speci ic bin owing o h ee easons. Fi s , a ca ibou
g oup could be a any dis ance wi hin he bin., e.g., a g oup eco ded in dis ance
bin 300 m, was loca ed somewhe e be ween 200 and 300 me e s. Second, placing
20
a ca ibou g oup wi hin he co ec bin elied hea ily on obse e abili y o
es ima e dis ance o he obse ed animals in ugged e ain. Thi d, al hough o
le el g ound (i sel a e) he es ima ed di ec line dis ance om obse e (si ing
in helicop e a 40 m al i ude abo e g ound) o a ca ibou g oup would be
g ea e han he pe pendicula dis ance om he ack line o ha g oup, hose
di e ences we e small a 100 m and negligible beyond 200 m (i.e., in me e s 8, 4,
3, 2, 2, 2, 1, 1, and 1). Rega ding he 0-50 m bin, we assumed obse e abili y
su icien o compensa e o 40 m al i ude and assign a pe pendicula 50 m
dis ance co ec ly because immedia ely adjacen o he helicop e / ack line.
Fu he , o aid obse e abili y o es ima e dis ances, be o e s a ing su ey he
helicop e ho e ed a 40m al i ude while each obse e used a “Leica lase ange
inde 1600” o gauge dis ances ac oss le el ai po g ound o a p io i known
pe pendicula dis ances. Then obse e s ma ked hei window wi h masking
ape delinea ing he app oxima e dis ances o each bin. While on su ey, in he
absence o ca ibou and whe e e ical e ain ea u es occu ed, obse e s used
he lase dis ance inde s o es hei abili y o es ima e dis ance, i.e., o he
e ain ea u e. On a e occasions, obse e s we e able o use he lase ange
inde s o de e mine bin dis ance o a de ec ed s a iona y g oup.
Once all eco ded dis ances we e ecoded o mid-dis ance, o model he
de ec ion unc ion all he de ec ions we e pooled ac oss obse e s wi h he
helicop e unc ioning as a single obse e . The pooled da a 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 gi en ha is a a dis ance 𝑦, om he ack 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 ack line o he de ec ed objec . Wi hin DS
me hods, he p obabili y o de ec ion is explained ecu ing o hese obse ed
dis ances (Buckland e al. 2001).
Dis ance sampling
The ca ibou g oup was he selec ed objec -o -in e es on which de ec abili y was
modelled, i.e., indi idual ca ibou wi hin a g oup we e no conside ed. The
indi idual line ansec s we e he sample uni o design-based con en ional DS
analysis o he 2019 su ey. De ails o how his s udy’s DS analyses we e
pe o med a e in Appendix 3. Thus, es ima ed CVs (Coe icien s o Va ia ion)
om he models a e e e ing o he ansec s, and o al CV es ima ion is
ob ained by di iding he es ima ed s anda d e o by he espec i e es ima e.
21
The es ima ed s anda d e o is ob ained as a pooled es ima e o en i e egion
and accoun ing o ansec s and hei a iabili y, i inco po a es he a iance
om he de ec ion unc ion (Buckland e al. 2001).
The eco ded dis ances o he obse ed ca ibou g oups we e used o es ima e a
de ec ion unc ion. Wi h his, bo h he ca ibou de ec ion p obabili y and densi y
wi hin he su eyed a ea could be es ima ed (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 ack 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 ack line o he de ec ed objec . Wi hin
DS 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 DS 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 (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, (Thomas e al. 2010). The model p esen ing he lowes AIC alue
was chosen. De ails ega ding DS heo y, me hods and analysis a e a ailable in
Buckland e al. (2001, 2015), and a b ie e summa y p o ided in Appendix 3,
wi h a summa y o DS assump ions in Appendix 4. Fo analysis, we used R
S a is ical So wa e (h ps://www. -p ojec .o g/).
Demog aphics
Sex, age, and la e-win e cal ec ui men obse a ions we e ob ained a e mos
o he DS su ey was comple ed. All ca ibou sigh ed we e sexed and aged
ollowing a b ie o e pass wi h he helicop e . Sex and age c i e ia ha e
emained unchanged since 2000 (de ails in Cuyle e al. 2011, 2016). B ie ly,
emale sex was de e mined by he p esence o absence o a ul a and/o u ine
pa ch on he ump o bo h adul s and cal es, i.e., an le size, shape, p esence, o
absence, we e no used o de e mine sex. Two age classes we e used, cal (age 
10-mon hs) and adul (age > 1-yea ). Age was de e mined by body size. 10-
mon h-old cal es, male and emale, being conside ably smalle han all o he
age classes in Ma ch. Cal pe cen age is gi en ela i e o he o al numbe o
ca ibou sexed and aged. Cal ec ui men is he alue o la e-win e and
p o ided as he numbe o cal es pe 100 cows. G oup size was based on
p oximi y and g oup cohesion du ing possible ligh esponse. To ob ain

22
demog aphics and ec ui men alues, on 12 and 13 Ma ch, la ge a eas o he
Cen al egion we e lown, including he sou h coas o Uja assui and Ilulialik,
Akia-No dlande be ween Fiske- and Nuuk jo ds, Na ssa ssuaq Valley and
peninsula, a ea su ounding line 32 and be ween line 32 and 30.
Ele a ions whe e ca ibou de ec ed
Ea ly Ma ch ele a ion use by ca ibou was app oxima ed using GPS da ase o
helicop e ele a ion/posi ion and ma ching imes amps wi h hose o he digi al
audio eco ding o ca ibou obse a ions. GPS and digi al eco de imes amps
we e synch onized be o e he su ey began. Be o e analysis, he helicop e ’s
ligh al i ude o 40 m was sub ac ed om all ele a ions. The ea e , and
lacking a eliable cons an co ec ion ac o , nega i e alues we e dele ed.
Na u al mo ali y
In he pas , i locals/hun e s obse ed se e al ca ibou ca casses in he e ain o
on sea ice, his esul ed in ala m abou an assumed nega i e end o he en i e
popula ion. To pu ca cass obse a ions in o pe spec i e, since 2000, all
echnical epo s o G eenland ca ibou su eys ha e included, o ha speci ic
su ey yea , he expec ed numbe o annual adul ca ibou dea hs esul ing om
na u al mo ali y, i.e., no due o ha es . Age dis ibu ions among ha es ed
G eenland ca ibou popula ions ha e sugges ed a na u al mo ali y o om 8 o
10% pe annum (Loison e al. 2000, Cuyle & Øs e gaa d 2005). Meanwhile,
na u al mo ali y a es om 4 o 8% we e epo ed o No h Ame ican
popula ions wi hou p eda o s (Be ge ud 1967, 1971, Skoog 1968, Kelsall 1968,
Hea d & Ouelle 1994), albei hese a e now conside ed low (Be ge ud e al.
2008) and densi y-independen ac o s, e.g., ad e se wea he , can inc ease
mo ali y (Ga es e al. 1986). Be ge ud (1980) p oposed a s anda d adul
mo ali y a e o 10% o all No h Ame ican ca ibou popula ions, and mo e
ecen ly Be ge ud e al. (2008) sugges ed 7.7% o an inc easing popula ion wi h
p eda o s. La ge p eda o s a e absen in he Cen al egion. Al hough na u al
mo ali y a es a y among yea s (Be ge ud e al. 2008), gi en he abo e, an
assumed s anda d na u al mo ali y a e o 8-10% (Kingsley & Cuyle 2002) o
G eenland ca ibou likely yields a easonable es ima e o annual mo ali y owing
o na u al causes. This a e is applied o he 2019 abundance es ima es o
p o ide wildli e manage s wi h a ough numbe o expec ed ca ibou dea hs due
o na u al mo ali y wi hin he su ey yea .
23
Resul s
Su ey logis ics & unp ocessed da a
The ae ial su ey by helicop e o he Akia-Manii soq ca ibou popula ion
occu ed wi hin he pe iod 01-14 Ma ch, which pe iod was sha ed wi h he
su ey o he Ame alik ca ibou popula ion. Poo wea he made h ee days non-
lyable, as did ai po closu es on wo Sundays. DS da a o he Akia-Manii soq
ca ibou popula ion was ob ained o e six days (01, 05, 06, 07, 09 and 12 Ma ch).
Demog aphics da a was ob ained 12-13 Ma ch. Typical AS350 helicop e s
ca ying h ee passenge s and pilo , e ueling was necessa y a e abou 3 hou s
o ligh ime, an addi ional 15-20 minu es we e possible when wind condi ions
and dis ance o nea es ai po pe mi ed.
Table 2. Summa y o unp ocessed esul s: Su ey o he Akia-Manii soq ca ibou popula ion by helicop e
in he Cen al egion, 01-12 Ma ch 2019.
Pa ame e
Cen al egion sub-a ea
TOTAL
Akia
Manii soq
Coas
Manii soq
Inland
Uja assui
Fligh al i ude (m)
40
40
40
40
40
Fligh speed (km/h )
60-70
60-70
60-70
60-70
60-70
Sub-a ea size (km2)
4,150
3,375
2,011
2,039
11,575
Numbe o lines
21
11
8
10
50
Dis ance lown (km)
423.12
197.26
244.17
241.02
1105.57
S ip wid h1 (m)
1000-1500
1000-1500
1000-1500
1000-1500
1000-1500
Su eyed a ea ca. (km2)
846 - 1,269
394 - 592
488 - 732
482 - 723
2,211 - 3,316
Co e age2
20.4-30.6 %
11.7-17.5 %
24.3-36.4 %
23.6-35.5 %
19.1-28.7 %
Co e age pos - unca ion3
10.2 %
5.8 %
12.1 %
11.8 %
9.6 %
To al ca ibou obse ed
1540
276
391
608
2,815
# G oups obse ed
385
73
116
175
749
Mean g oup size
3.99
3.78
3.37
3.47
3.75
S d De ia ion g oup size
± 3.46
± 3.80
± 1.97
± 2.04
± 3.03
Median g oup size
3
3
3
3
3
Maximum g oup size
25
22
10
15
25
Minimum g oup size
1
1
1
1
1
1 S ip wid h p o ided is o one side o helicop e only. Mus double o o al s ip wid h.
2 Co e age p io o unca ion o s ip wid h o 600 m.
3 Co e age a e unca ion o he s ip wid h o 600 m o DS analyses (see page 24).
The helicop e ligh ime o aled 34 hou s and 38 minu es. This is 10 hou s and
38 minu es mo e han lown in he las Cen al egion su ey, 2010. Time lown
was di ided be ween line ansec DS su ey (25 hou s; 42 minu es) and he
demog aphics su ey (08 hou s; 56 minu es). The 2019 su ey used 50 line
ansec s o a o al dis ance lown o 1,106 km, i.e., Akia 423.1 km, Manii soq
Coas 197.3 km, Manii soq Inland 244.2 km and Uja assui 241 km (Table 2).
24
Gi en he 1,106 km o line ansec s lown, an op imis ic calcula ion o su ey
co e age o he Cen al egion’s su eyed Akia-Manii soq a ea (11,575 km2)
would be 19-29%, i.e., opog aphy pe mi ing and assuming maximum s ip
wid h o 1000-1500 m o ei he side o he helicop e (Table 2). Howe e , o
analyses (see DS analysis, page 24), he s ip wid h was unca ed o 600 m.
Thus, co e age o he Cen al egion su eyed was 9.6% o he inal abundance
and densi y es ima es o he Akia-Manii soq ca ibou popula ion. The obse ed
aw o als we e 749 ca ibou g oups, which included 2,815 ca ibou (Table 2).
Mean g oup size was 3.75 ±3.03 ca ibou, and median g oup size was 3 ca ibou.
Da a p ocessing
The aw da a se was in Excel o ma con aining he su ey a iables, including
egion, sub-a ea, espec i e a eas (km2), ansec iden i ica ion, eco ded
dis ances, g oup size, and GPS coo dina es. Some imes included wi h ca ibou
g oup obse a ions we e ligh cha ac e is ics such as helicop e eloci y and
side, as well as su ey cha ac e is ics such as sola gla e, wea he , snow
co e ing and dep h, dead g ound, and su ace condi ions p o iding camou lage
backg ounds o he ca ibou. All a iables we e p ope ly es uc u ed wi hin R
S a is ical So wa e.
The da a se was subjec o some p io p ocessing be o e analysis. Commen
ields we e dele ed. Va iable names we e e-coded o make hem sensible in R.
One ca ibou obse a ion lacked dis ance. Gi en jus one obse a ion ela i e o
he la ge amoun he da a (n = 749), and since he ac ual impac o using any
gi en dis ance alue is mino , he p agma ic solu ion was o use he a e age
obse ed dis ance. No obse a ions lacked g oup size, so no eplacemen s we e
necessa y. Da a unca ion was se a 0.6 km.
P elimina y analysis dis ance sampling
Fo eliable es ima es o abundance, Buckland e al. (2001) sugges s ha sample
size is a leas 60 o 80 obse a ions and om a minimum o 10 o 20 eplica e
line ansec s. The 2019 ca ibou su ey o he Cen al egion me hese
ecommenda ions. Rega ding obse a ions (de ec ions o g oups o one o mo e
ca ibou), o analysis he un unca ed sample size was 749, while he unca ed
sample size was 734. Simila ly, ega ding he numbe o pa allel ansec lines
sepa a ed by 10 o 20 km, he e we e 50 lines. Time equi ed o comple e a
ansec line depended on o al leng h o he line. The ollowing a e he esul s
o he unca ed da a (n = 734 de ec ions).
25
O he ou sub-a eas, he Akia sub-a ea domina ed in obse a ion equency,
i.e., numbe o de ec ions (ca ibou g oups) pe sub-a ea (Fig. 4, 5). This was
expec ed as Akia was he la ges sub-a ea (ca. 4,150 km2) and ecei ed he
g ea es line ansec dis ance lown ela i e o he sub-a eas, Manii soq coas ,
Manii soq inland, and Uja assui . Fu he , o he ou sub-a eas, Akia possesses
he mos lowlands (ele a ion < 200 m), and he Akia-Manii soq ca ibou
popula ion a e known o p e e lowland ele a ions in la e win e (Cuyle e a.
2017). Al hough ca ibou we e de ec ed on mos o he 50 line ansec s, six line
ansec s lacked ca ibou de ec ions, i.e., line 4 (Akia), lines 51, 52, 53 (Manii soq
Coas ) and lines 31, 34 (Uja assui ).
Figu e 4. Loca ion and g oup size o he de ec ions ( unca ed da a) obse ed along he line ansec s
lown, 2019 su ey o he Akia-Manii soq ca ibou popula ion.
The de ec ed objec s o in e es , i.e., ca ibou g oups, ypically included no mo e
han six animals, while he mos obse ed g oup size was wo animals (n = 193
obse a ions) (Fig. 6). G oups consis ing o less han i e indi iduals made up
73% o he obse a ions, while g oups coun ing less han en indi iduals made
up 96%. La ge g oups we e sca ce and ypically obse ed a g ea e dis ances.
32
De ec ion unc ion models we e i ed o he unca ed da a, i.e., s ip wid h, 𝑤 =
0.60 km, o each side o he helicop e . Fo hese models, e e y combina ion o
key unc ion and adjus men e ms was es ed (Appendix 8). Addi ional
co a ia es assessed we e Camou lage, Boulde s showing h ough he snow
su ace, G oup size, Obse e , Fla ligh , Wea he , Dead g ound, Vege a ion and
G ound showing h ough he snow su ace, Sola Gla e, Helicop e side. G oup
size, as co a ia e, did li le o explain ca ibou de ec ion. Rega dless, we did no
conside con e ing G oup size in o a ca ego ical a iable, e.g., small, medium,
la ge, because much in o ma ion is los o no pe cei able gain, since we can
es ima e a p obabili y o de ec ion o each g oup size when his co a ia e is
included in he model.
A summa y o he in o ma ion om each model i ed o he da a (Table 3)
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)), 𝐴𝐼𝐶,
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 2019 su ey da a o he Akia-Manii soq ca ibou popula ion,
his model has he Haza d- a e unc ion as a key unc ion, Camou lage as a
co a ia e (AIC = 2590.006). The second-bes model was he hal -no mal key wi h
Camou lage as a co a ia e (AIC = 2590.042, i.e., Δ𝐴𝐼𝐶 = 0.037). This s ongly
sugges s ha Camou lage is he ele an co a ia e in de ec abili y.
Thus, we chose he ‘Haza d- a e wi h Camou lage as co a ia e’, which had he
es ima ed a e aged p obabili y o de ec ion o he Cen al egion o 𝑃
a = 0.471
(se = 0.019) (Fig. 14). I is an a e aged es ima e since Camou lage is included in
model. Consequen ly, each Camou lage le el has i s sepa a e de ec ion unc ion,
co esponding o di e en es ima es o p obabili y o de ec ion (Fig. 15).
The e ec o Camou lage was ma ked on es ima ed p obabili y o de ec ion (Fig.
15). When Camou lage co a ia e was low, he es ima ed p obabili y o de ec ion
was g ea es . In e es ingly, medium Camou lage had he lowes de ec ion
p obabili y es ima es, while hose wi h high o ex eme Camou lage had middle
alues o de ec ion p obabili y. La ge g oup sizes (≥ 15 ca ibou) we e ypically
de ec ed when Camou lage was high, which may p o ide a pa ial explana ion.

33
Figu e 14. His og am o Haza d- a e wi h Camou lage as co a ia e o de ec ed dis ances wi h he
es ima ed de ec ion unc ion o e laid.
Figu e 15. Es ima ed p obabili ies o de ec ion o each obse ed g oup size pe Camou lage ob ained wi h
he i ed model).
34
Table 3. Model compa ison ac oss he h ee Con en ional Dis ance Sampling models and models conside ing di e en co a ia es u he explaining de ec ion.
Key unc ion
Fo mula ( a iable)
𝒙𝟐 p- alue
𝑷
a
se (𝑷
a)
AIC
∆AIC
Haza d- a e
Camou lage
0.000
0.471
0.019
2590.006
0.000
Hal -no mal
Camou lage
0.000
0.453
0.012
2590.006
0.037
Hal -no mal
Boulde s showing h ough snow
0.000
0.456
0.013
2590.006
7.794
Hal -no mal
G oup size
0.002
0.458
0.013
2590.006
8.211
Hal -no mal
G oup size + Obse e
0.001
0.458
0.013
2600.209
10.204
Haza d- a e
Boulde s showing h ough snow
NA
0.448
0.020
2600.420
10.414
Hal -no mal wi h cosine adjus men e m o o de 2
1
0.000
0.426
0.019
2604.323
14.318
Haza d- a e wi h He mi e polynomial adjus men e m o o de 4
1
0.000
0.402
0.032
2604.566
14.561
Haza d- a e wi h cosine adjus men e m o o de 2
1
0.000
0.429
0.019
2604.722
14.716
Hal -no mal
Fla ligh
0.000
0.461
0.013
2605.587
15.582
Haza d- a e wi h simple polynomial adjus men e ms o o de 4,6
1
0.000
0.398
0.034
2605.946
15.941
Hal -no mal wi h simple polynomial adjus men e m o o de 4
1
0.000
0.451
0.021
2606.378
16.372
Hal -no mal
Wea he
0.000
0.460
0.013
2606.469
16.464
Uni o m wi h cosine adjus men e ms o o de 1,2,3
NA
0.000
0.427
0.020
2606.608
16.602
Hal -no mal
1
0.000
0.462
0.013
2606.810
16.804
Haza d- a e
G oup Size
0.000
0.458
0.020
2606.884
16.878
Hal -no mal
Dead g ound
0.000
0.461
0.013
2606.923
16.917
Hal -no mal
Vege a ion/G ound h ough snow
0.000
0.460
0.013
2606.991
16.985
Haza d- a e
G oup size + Obse e
0.000
0.452
0.020
2607.879
17.873
Hal -no mal
Sola gla e
0.000
0.462
0.013
2608.513
18.508
Hal -no mal
Helicop e side
0.000
0.462
0.013
2608.704
18.699
Hal -no mal
Obse e
0.000
0.462
0.013
2608.774
18.768
Uni o m wi h simple polynomial adjus men e ms o o de 2,4,6,8
NA
0.000
0.458
0.023
2610.950
20.944
Haza d- a e
Fla ligh
0.000
0.446
0.020
2614.757
24.751
Haza d- a e
Dead g ound
0.000
0.447
0.020
2615.115
25.109
Haza d- a e
Wea he
0.000
0.455
0.020
2615.783
25.778
Haza d- a e
Obse e
0.000
0.442
0.020
2617.808
27.802
Haza d- a e
Helicop e side
0.000
0.449
0.020
2619.033
29.027
Haza d- a e
Sola Gla e
0.000
0.450
0.020
2619.190
29.184
Haza d- a e
Vege a ion/G ound h ough snow
0.000
0.454
0.020
2619.800
29.795
Uni o m wi h He mi e polynomial adjus men e m o o de 2,4,6
NA
0.000
0.661
0.035
2708.504
118.498
No e: Fo mula, explana o y a iables = 1 o no co a ia es. NA is o Uni o m Key. Chi-squa e p- alue, NA = no enough deg ees o eedom o he GOF es , hus
he ‘NA’ alues. (Deg ees o eedom calcula ed conside ing model pa ame e s, hese a y conside ing which key unc ion is used and how many/which explana o y
a iables conside ed.)
35
The es ima es o encoun e a es indica e ha he Akia sub-a ea had he mos ca ibou,
since i s es ima e was la ge han he o he sub-a eas (Table 4). Conce ning he design-
based es ima es o ca ibou abundance and densi y, Akia is also he sub-a ea p esen ing
mo e ca ibou (Tables 5, 6, Fig. 16).
Table 4. Encoun e a e (ER) es ima es pe sub-a ea (s a um) o ca ibou g oups o he Akia-Manii soq ca ibou
popula ion, conside ing ou s a a, se en bins, and a de ec ion unc ion i ed wi h Camou lage as a co a ia e.
Sub-a ea
Encoun e a e
S anda d E o (se)
Coe icien o Va ia ion (c )
Akia
0.918
0.145
0.158
Manii soq Coas
0.409
0.131
0.321
Manii soq Inland
0.475
0.140
0.294
Uja assui
0.746
0.105
0.141
TOTAL
0.662
0.071
0.108
Figu e 16. Ca ibou densi y (le ) and abundance ( igh ) es ima es wi h co esponding con idence in e als o he ou
sub-a eas, Akia, Manii soq Coas , Manii soq Inland, and Uja assui , and inally o he o al Cen al egion.
In Ma ch 2019, he Cen al egion had an es ima ed popula ion size o 48,941 ca ibou (95%
CI: 37,612 – 63,682) (Table 5, Fig. 16). Sum o abundance es ima es o each sub-a ea equals
o al es ima ed abundance o he egion. CV o 0.13 is excellen and indica es he Akia-
Manii soq ca ibou abundance es ima e o 2019 is accu a e. The design–based densi y
es ima e o he whole su ey egion was 4.23 ca ibou/km2, wi h 95% CI: 3.23 – 5.50 (Table
6, Fig. 16).
36
Table 5. Es ima es o abundance pe sub-a ea (s a um) o Akia-Manii soq ca ibou popula ion in he Cen al egion,
Ma ch 2019, conside ing ou s a a, se en bins and Haza d- a e de ec ion unc ion wi h Camou lage as a co a ia e.
Sub-a ea
Abundance
Es ima e
S anda d
E o (se)
Coe icien o
Va ia ion (c )
95% Con idence In e al
Lowe
Uppe
Akia
27,286
5306
0.194
18,276
40,737
Manii soq coas
7,205
2323
0.322
3,456
15,024
Manii soq inland
6,037
1978
0.328
2,853
12,777
Uja assui
8,412
1257
0.149
5,992
11,809
TOTAL
48,941
6390
0.131
37,612
63,682
Table 6. Es ima es o densi y pe sub-a ea (s a um) o Akia-Manii soq ca ibou popula ion in he Cen al egion,
Ma ch 2019, conside ing ou s a a, se en bins and Haza d- a e de ec ion unc ion wi h Camou lage as a co a ia e.
Sub-a ea
Densi y
Es ima e
S anda d
E o (se)
Coe icien o
Va ia ion (c )
95% Con idence In e al
Lowe
Uppe
Akia
6.575
1.279
0.194
4.404
9.816
Manii soq coas
2.135
0.688
0.322
1.024
4.452
Manii soq inland
3.002
0.984
0.328
1.419
6.354
Uja assui
4.126
0.616
0.149
2.939
5.791
TOTAL
4.228
0.552
0.131
3.249
5.502
Ca ibou ligh eac ion o lack he eo
Like he No h egion su ey o 2018 (Cuyle e al. 2021), he Akia-Manii soq ca ibou
popula ion su ey o 2019 used digi al audio eco de s o collec 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 io al
eac ion o he ca ibou g oup o he helicop e lying a line ansec pas o o e hem.
Beha io could hen be pu in ela ion o g oup size and dis ance om he line ansec .
Beha io was eco ded o a o al o 683 g oups, which in ol ed 2,551 ca ibou.
The size o ca ibou g oups ha exhibi ed mo emen was signi ican ly di e en om hose
ha did no mo e, mean g oup size 3.98 ca ibou o mo ing and 3.00 o non-mo ing (
S a = -4.767; wo- ailed - es ing: P < 0.0001, = 1.965, d = 477). Fu he , non-mo ing
ca ibou g oups we e gene ally 100 m u he om line ansec lown by he helicop e
han ca ibou g oups showing mo emen (Table 7). The e was a signi ican di e ence
be ween he mean dis ance o g oups wi h mo emen , 199.02 m, and g oups lacking
mo emen , 299.42 m ( S a = 7.577; wo- ailed es ing P < 0.0001, = 1.968, d = 304).
Ca ibou g oups eac ing o he helicop e ly-by wi h mo emen made up 74.8% o all
obse a ions o which beha io was epo ed. Con e sely, 25.2% o all ca ibou g oups
exhibi ed li le o no mo emen . A qua e o all ca ibou g oups obse ed lacked
mo emen . Pe cen ages change when conside ing he absolu e numbe o ca ibou
37
in ol ed. The e we e 2,551 ca ibou in he 683 g oups (Table 7) o which beha io was
epo ed, and o hose ca ibou, 79.8% (n=2,035) mo ed and 20.2% (n=516) did no mo e.
Table 7. Mo emen o non-mo emen o ca ibou eac ing o helicop e ly-by, Ma ch 2019. Da ase ha included g oup
size, beha io , and dis ance om ack line was n= 683.
Pa ame e
Akia-Manii soq ca ibou popula ion
Mo emen
Non-Mo emen
p – alue
Numbe o g oups
511
172
% G oup Obse a ions
74.8%
25.2%
GROUP SIZE
Mean
3.98
3.00
< 0.0001
Con idence Le el (95%)
0.2762
0.2975
S anda d E o
0.1406
0.1507
Median
3
2
Mode
2
2
S anda d de ia ion
3.1780
1.9765
Sample Va iance
10.0997
3.9064
Maximum
25
16
Minimum
1
1
Numbe o ca ibou in ol ed
2035
516
DISTANCE 1
Mean
199.02 m
299.42 m
< 0.0001
Con idence Le el (95%)
13.4252
22.4071
S anda d E o
6.8335
11.3515
Median
200
300
Mode
50
300
S anda d de ia ion
154.4726
148.8738
Sample Va iance
23861.7858
22163.4027
Maximum
850
750
Minimum
50
50
1 Dis ance om he line ansec lown by helicop e .
Among he 441 ‘ unning’ g oups (Running- away, high speed, pa allel, la e s anding,
Table 8), 431 g oups exhibi ed unaba ed ligh , i.e., hey ne e s opped while wi hin iew
o he helicop e . Rough g oup composi ion (cal , adul ) was de e mined o 202 o hose
g oups and eco ded cal p esence in 85.6%, wi h emaining 14.4% g oups adul s only.
Conside ing only he 113 ca ibou g oups whose o iginal posi ion was on he line ansec
(n = 50) o wi hin 50 m o he line ansec (n=63), 110 o hose g oups (97.3%) ne e
s opped unning away om he helicop e . The emaining h ee g oups (2.7%) ini ially an
away bu hen s opped, looked a he helicop e and an no u he . A cal was p esen in
wo o hose h ee g oups.

38
Table 8. De ails o mo emen o non-mo emen o ca ibou eac ing o helicop e ly-by, Ma ch 2019. Da ase o
obse a ions, which included ca ibou g oup size, beha io , and dis ance om line ansec , was n= 683 g oups, which
con ained n = 2,551 indi idual ca ibou.
Akia-Manii soq ca ibou popula ion
Ca ego y
G oups
(n = 683)
%
Indi iduals
(n = 2,551)
%
Exhibi ing Mo emen
Running away
405
59.3
1652
64.8
Running away high speed
13
1.9
65
2.5
Walking
38
5.6
124
4.9
App oach*
8
1.2
29
1.1
Con used (jos ling/ci cling)
14
2.0
31
1.2
Running pa allel o line ansec
13
1.9
55
2.2
Running, la e s anding looking
10
1.5
49
1.9
T o ing away
9
1.3
25
1.0
Mixed: some mo ed, o he s did no 1
1
0.1
5
0.2
TOTAL
511
74.8
2035
79.8
Lacking Mo emen
S anding s ill
156
22.8
476
18.7
S anding, la e walking
3
0.4
8
0.3
Lying down
7
1.0
13
0.5
Lying down, la e s ood up
4
0.6
11
0.4
Some lying, o he s s anding s ill
1
0.1
6
0.2
Lying down, la e walking
1
0.1
2
0.1
TOTAL
172
25.2
516
20.2
*App oach mo emen (walking, o ing, unning) was owa ds helicop e while looking a helicop e .
1Mixed = di e en beha io by membe s wi hin same g oup, e.g., some unning owa ds o he s, which s ood s ill and
looked a he helicop e .
Demog aphics & ec ui men
Sex, age, and la e-win e cal ec ui men da a we e collec ed in sepa a e speci ic e o s
ha we e no pa o he line ansec DS da ase . On he 12 h and 13 h o Ma ch 2019, and
using ca. 8 hou s helicop e ligh ime, we sexed and aged 276 g oups o ca ibou, o a
o al o 1257 animals, in he Akia-Manii soq ca ibou popula ion (Table 9). Cows we e ca.
50% o he popula ion, ollowed by bulls (age >1-yea ) a ca. 24% and cal es a 26%. The
cal pe cen age may be conside ed a i icially high owing o he la ge numbe o cal es
lacking hei dam, i.e., o phan cal es.
While ob aining demog aphics o Akia-Manii soq ca ibou popula ion, we obse ed a
loose agg ega ion o nume ous ca ibou on he lowland la s (ele a ion < 200 m) a he
no h end o he Na ssa ssuaq Valley (Fig. 17). Mos o hese g oups o ca ibou we e no
sexed and aged because hey we e oo la ge, e.g., la ges > 50 animals. The high g oup size
combined wi h he con usion o cons an jos ling change o posi ions among he leeing
39
ca ibou, made i di icul o sex and age all g oup membe s. Fu he , g oups leeing he
helicop e o en mixed o spli apa o eg oup wi h ye o he g oups be o e sex/age
de e mina ion was comple e. Whe e g oup sepa a ion and size pe mi ed, demog aphics
we e ob ainable (Fig. 18).
Table 9. Demog aphics o Akia-Manii soq ca ibou popula ion, Cen al egion, Ma ch 2019.
Pa ame e
Akia-Manii soq ca ibou popula ion
Numbe o g oups obse ed
276
GROUP SIZE
Mean
4.55
Con idence In e al (95%)
0.3896
S anda d E o
0.1979
S anda d De ia ion
3.29
Sample Va iance
10.8079
Median g oup size
4
Mode g oup size
3
Maximum g oup size*
24
Minimum g oup size
1
DEMOGRAPHIC
All da a
83 o phan cal es emo ed
To al sexed & aged (n)
1257
100 %
1174
100 %
Cow (age >1 yea )
624
49.6 %
624
53.15 %
Cal es om p e ious sp ing
326
25.9 %
243
20.70 %
(148 emales)
11.77 %
-
-
(171 males)
13.60 %
-
-
(7 unknown)
0.56 %
-
-
Bull (age >1 yea )
307
24.4 %
307
26.15 %
(145 adul s age >3)
11.54 %
(145 adul s age >3)
12.35 %
(162 ju eniles 1< age <3)
12.89 %
(162 ju eniles 1< age <3)
13.80 %
Rec ui men (cal es / 100 cows)
52.24
38.94
Sex a io (Bull age >3 yea /Cow)
0.23
0.23
Sex a io (Bull age >1 yea /Cow)
0.49
0.49
* This is maximum o only hose g oups ha we e sexed and aged. I was no possible o sex and age he indi iduals in
he exceedingly la ge g oups on he la s o he Na ssa ssuaq Valley (Fig. 17).
40
Figu e 17. Unusually high numbe s o ca ibou, o en in excep ionally la ge g oups we e obse ed on he low ele a ion
(< 200 m) la s o he alley, Na ssa ssuaq, Cen al egion, ea ly Ma ch 2019: Le a e 45 ca ibou, abo e igh 33 and
below 14. Sex and age de e mina ion was only possible on he la e .
Figu e 18. These 17 ca ibou could be sexed and aged owing o g oup sepa a ion and ela i ely small g oup sizes, i.e., six
(le ), nine ( o eg ound) and wo (in dis an backg ound).
41
Cal lacking hei dam
The demog aphics da a collec ion included a o al o 326 cal es (Table 9). Only 243 cal es
(74.5% o all cal es obse ed) we e in he company o cows, while 83 cal es (25.5% o all
cal es obse ed) appea ed o be o phans, i.e., lacking a dam/cow.
O he 83 cal es, 52 (16% o all cal es obse ed) we e designa ed ‘ ue’ o phans. P ima ily
because hey we e soli a y indi iduals (n = 4) o in he company o o he cal es (n = 30
cal es, 10 g oups), always wi h no olde ca ibou nea by. O phan pai s we e obse ed i e
imes, and iple once. Fou o phans oge he we e obse ed h ee imes. The maximum
o phan g oup size was i e cal es and was obse ed once. The a io o o phan emales o
males was almos 50:50, as he e we e 16 emale and 18 male o phans. Secondly, ‘ ue’
o phans we e also conside ed hose in he company o bull only g oups (n = 18, 14
g oups). A single o phan cal was p esen in 11 o he bull g oups. The e we e six o phans
p esen in ju eniles-only bull g oups (n=5), eigh p esen in adul bull g oups (n=5) and
ou in mixed ju enile plus adul bull g oups (n=4).
The emaining 31 cal es, ou o he abo e 83, we e designa ed ‘possible’ o phans because
hese we e ‘ex a’ cal es obse ed in he company o cow-cal pai s, i.e., o 20 cow-cal
g oups (n = 117 ca ibou; 43 cows, 74 cal es) he numbe o cal es exceeded he numbe o
cows. The g oup composi ion o hal o hese g oups consis ed o a single cow ollowed
by wo cal es. Fi e cow-cal g oups included mul iple pai s and jus one ‘ex a’ cal . Two
cow-cal g oups included mul iple pai s and wo ‘ex a’ cal es. A u he wo cow-cal
g oups included mul iple pai s and h ee ‘ex a’ cal es. Finally, one cow-cal g oup wi h
mul iple pai s included six ‘ex a’ cal es. The esul was a 31 (9.5%) ‘possible’ o phan
cal es.
Al hough only one o phan was in isibly poo body condi ion, owing o possible o aging
di icul ies we suspec ha he 83 o phan cal es ha e less chance o su i ing hei i s
win e han cal es wi h hei dams. I hese o phan cal es a e emo ed om he da ase ,
hen he esul ing demog aphics becomes cows ca. 53%, bulls (age > 1-yea ) ca. 26% and
cal es ca. 21%, wi h cal ec ui men educed o ca. 39 cal es pe 100 cows (Table 9).
G oup size & composi ion
The sex and age composi ion o ca ibou g oups may ha e in luenced g oup size. The
esul s we e almos iden ical o g oups o all bulls (ju eniles and adul s) and hose
con aining only adul bulls (age > 3-yea s) (Table 10). The g oups o ju enile bulls (1-yea
< age < 3-yea ) had he lowes mean g oup size, 1.60 animals. The highes mean g oup size
48
Ca ibou de ec ion
Incomple e o pa chy snow co e , subs a es (including g ass, bushes, g ound) poking o
showing h ough a hin snow laye , ocky e ain, ligh /shadow condi ions, and
occasionally og, whe he alone o in combina ions a e no mal du ing ae ial su ey in
Wes G eenland (Cuyle e al. 2005, 2007, 2011, 2016, 2021, 2023). Condi ions we e simila
in 2019 and as usual made he well camou laged ca ibou a challenge o de ec . S a iona y
ca ibou exace ba ed he de ec ion di icul y. The almos wes -eas o ien a ion o he line
ansec s used in 2019 mean ha in sunny condi ions sola gla e in he eyes o he
obse e on he sou h- acing side o he helicop e equi ed pola ized sunglasses. Despi e
he use o pola ized sunglasses, de ec abili y o ca ibou may ha e been educed (Fig. 11).
We ecommend ha u u e DS su eys combine all co a ia es con ibu ing o he ca ibou
becoming camou laged in o he e ain (e.g., Figs. 9, 10, 11), in o a single index o
camou lage (e.g., ex eme, high, medium, low, none). Combined, we expec his will
imp o e how ca ibou “in isibili y” in e ac s wi h Key Func ions o model he de ec ion
unc ion. Rega dless, gi en obus DS da a, he in luence o co a ia es on de ec abili y is
small and unlikely o signi ican ly al e inal abundance and densi y es ima es.
Ca ibou beha iou - ligh esponse o ca ibou g oups
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. Since ligh esponses by
he ca ibou may in luence whe he an obse e de ec s hem, in 2019 he line ansec da a
included whe he he helicop e ly-by elici ed a ligh mo emen esponse om he
ca ibou g oup o whe he hey we e s a iona y.
Abou 75% o he obse ed ca ibou g oups exhibi ed mo emen in esponse o he
helicop e ly-by, while abou 25% did no , which included some on he ack line. This
la ge p opo ion o s a iona y ca ibou g oups unde lines he impo ance o skilled
obse e s able o de ec ca ibou despi e he ex ao dina y deg ee ca ibou a e camou laged
o ypical backg ound condi ions. F om expe ience we know ha obse e skill can only
succeed in de ec ing camou laged ca ibou p esen i he helicop e is lying ‘low & slow’,
as he cu en s udy did. Because s a iona y animals make up almos 1/4 o all ca ibou
g oups obse ed and include some on he line ansec i sel (whe e o DS analyses all
ca ibou p esen mus be de ec ed), de ec ing non-mo ing ca ibou is essen ial o a oid
unde es ima ing popula ion size.

49
Ca ibou g oups ha exhibi ed mo emen in esponse o he helicop e ly-by had a mean
g oup size o 4. This was signi ican ly (p < 0.0001) la ge han he non-mo ing ca ibou
mean g oup size o 3. Also, g oups ha exhibi ed mo emen we e close o he helicop e
han g oups ha did no mo e (Table 9). As wi h p e ious ae ial su eys, his a es s o
excep ional obse e abili y o de ec ca ibou despi e beha io displayed. Explana ions o
lack o mo emen among ca ibou u he away om he helicop e would include ha a
g ea e dis ances he helicop e may be pe cei ed by he ca ibou as less h ea ening.
Addi ionally, g oup composi ion may be in ol ed.
Fo ca ibou g oups ha an om he helicop e , mos exhibi ed unaba ed ligh eac ion,
i.e., hey ne e s opped while we could see hem. This was speci ically ue o hose
g oups whose o iginal posi ion was he ack line i sel . Cal p esence appea s o be an
impo an ac o de e mining whe he unaba ed ligh occu s, since ca. 86% o unaba ed
ligh in ol ed g oups wi h cal es.
Demog aphics
In ea ly Ma ch 2019, he Akia-Manii soq ca ibou popula ion’s demog aphics sugges ed a
composi ion ha p o ides po en ial o u he g ow h in abundance, albei
no wi hs anding u u e ca as ophic s ochas ic e en s, including pa hogen ou b eaks and
ex eme wea he .
Ra io o bulls o cows appea ed o be eco e ing om he 2001 o 2010 bull decline (Fig.
23). The 2019 cal pe cen age and ec ui men (numbe cal es pe 100 cows) we e he
highes since helicop e su eys began in 2001 (Fig. 24). The 2019 alues emained high
e en a e emo ing he su p isingly high numbe o o phan cal es (n = 83). Fu he , he
2019 pe cen age o cal es was simila o he high 1998 le el (Table 1) ob ained om
g ound su ey. The 2019 le el o cal ec ui men s ongly sugges s he possibili y o
u u e popula ion g ow h (Be ge ud e al. 2008).
A discussion o Akia-Manii soq’s demog aphics in 2019 would no be comple e wi hou
discussing ha ¼ o all obse ed cal es we e o phans. Al hough he la e win e cal
ec ui men was ini ially ca. 52 cal es pe 100 cows, he high incidence o o phan cal es
(n=83), ca. 25% all cal es obse ed, b ough cal ec ui men alue down o 34 cal es pe
100 cows. I is no un easonable o assume ha o c ea e hose o phans a simila numbe o
cows died be o e he 2019 su ey occu ed. This sugges s wo possibili ies. Fi s , ha some
pa hogen inc eased mo ali y among cows bu no hei cal es, and no among bulls.
50
Common sense makes his unlikely since ca ibou pa hogens a e no so selec i e. The
second possibili y is ha hun e s ha es ing om he Akia-Manii soq ca ibou popula ion
p edominan ly selec ed only he cow om cow-cal pai s.
Figu e 23. Pas and p esen la e win e bull o cow a ios o he Akia-Manii soq ca ibou popula ion. Bull classi ica ion
includes bo h ju eniles, 1-yea < age < 3-yea , and adul s, age > 3 yea s.
Figu e 24. Pas and p esen la e win e cal (age 10-mon h) ec ui men (numbe cal es pe 100 cows) and cal
pe cen age o he Akia-Manii soq ca ibou popula ion. Column 2019a included all cal es obse ed, while 2019b
emo ed all o phan cal es (n = 83).
58
45
38
49
100 100 100 100
0
20
40
60
80
100
120
2001 2005 2010 2019
Numbe o ca ibou
Yea
Bull
Cows
31
24 23,2
52,24
38,94
17 14 14,4
25,9
20,7
0
10
20
30
40
50
60
2001 2005 2010 2019a 2019b
Cal ec ui men o pe cen age
Yea
Cal es / 100 Cows
Pe cen age
51
Ele a ion
Albei ele a ion da a was only app oxima e gi en he limi a ions o he GPS de ice and
misma ch be ween helicop e and ca ibou posi ions, du ing he 2019 ae ial su ey, ca ibou
o he Akia-Manii soq popula ion we e obse ed a ele a ions o mean 361 m ±246 wi h
he mode being 156 m. This use o ela i ely low ele a ions in la e win e (Ma ch) is
suppo ed by 2008-2010 GPS eleme y da a om o Akia-Manii soq cows, mean
ele a ion ca. 200 m (Cuyle e al. 2017). This may e lec a ca ibou p e e ence o low
ele a ions o jus ha he Cen al egion has mo e a ailable lowland habi a han is usual
in Wes G eenland, i.e., Akia sub-a ea is mos ly < 200 m ele a ion (Figs. 1, 2). The ca ibou
a e likely o p e e low ele a ions because o a highe quali y and quan i y o a ailable
win e o age, which would be expec ed o lowland ele a ions a he la i ude o he
Cen al egion (Kö ne 2007). Use o low ele a ions may also sugges ha win e
dis u bance by humans on he Akia-Manii soq popula ion is minimal.
The win e 2019 ca ibou hun ing season o he Cen al egion was 01-15 Feb ua y, ending
2-weeks be o e he 2019 su ey began. The simila la e win e ele a ion use ac oss yea s
sugges s Akia-Manii soq ca ibou a e no using high ele a ions o a oid hun e s.
Meanwhile, he Akia-Manii soq ca ibou popula ion is no eadily accessible o humans,
ega dless o season because he Cen al egion can only be eached by boa . Speci ically
o win e , snowmobile use is p ohibi ed o e he en i e egion, ende ing hese ehicles
illegal o win e hun ing season anspo o ec ea ional use.
Ne e heless, and despi e being illegal, snowmobile use on he Akia (No dlande ) a ea o
he Cen al egion was obse ed in Ma ch 2019 (Fig. 20). The same was obse ed du ing
he p e ious su ey o 2010, when snowmobile use was associa ed wi h high ha es
numbe o ca ibou (Cuyle e al. 2011). In bo h 2010 and 2019, high numbe s o ca ibou in
unusually la ge g oups we e obse ed on he low ele a ion (< 200 m) la s in he no he n
po ion o he Na ssa ssuaq Valley, Cen al egion (Fig. 17). As sugges ed ea lie (Cuyle
e al. 2011), his ca ibou agg ega ion may be he esul o animals a oiding he snowmobile
ac i i y in he ex ensi e lowlands o Akia (No dlande ). Un o una ely o he ca ibou,
Akia (No dlande ) is a p ime win e o aging habi a (Cuyle e al. 2017), which is opposi e
G eenland’s capi al ci y, Nuuk, and illegal snowmobile use may be common. The
abno mally la ge agg ega ion o ca ibou in he Na ssa ssuaq Valley sugges s ha cu en
le els o snowmobile dis u bance a e su icien o cause a oidance beha io , albei o
ano he lowland a ea a he han o highe ele a ions.
52
All he abo e may explain why he Akia-Manii soq ca ibou popula ion a e aged
ele a ions ca. 300 m lowe han he Ame alik ca ibou popula ion, which we e also
su eyed in Ma ch 2019 (Cuyle e al. 2023). The e should be less access by humans o he
Akia-Manii soq ca ibou popula ion, and hei Na ssa ssuaq Valley appea s o p o ide
hem wi h a emo e and la ge lowland a ea whe e hey can a oid win e hun e s o
snowmobile ec ea ion. The cu en emo eness o he Na ssa ssuaq Valley will change i
human access inc eases. Un il hen, ele a ion use by he Akia-Manii soq popula ion will
no likely be in luenced by human dis u bance.
La e-win e an le possession
Bulls
As expec ed o ca ibou popula ions, adul (age > 3-yea s) bulls om he Akia-Manii soq
popula ion lacked an le s in Ma ch, while mos , 87%, ju enile bulls e ained one o bo h
hei an le s om he p e ious au umn. Thus, la e-win e an le possession among bulls
age > 1 yea o he Akia-Manii soq popula ion is simila o bulls in bo h he
Kange lussuaq-Sisimiu and Ame alik ca ibou popula ions (Cuyle e al. 2021, 2023).
Howe e , in hose same h ee popula ions, an le possession a ied o la e-win e male
cal es (age < 1-yea ). An le possession in male cal es was poo , 40%, in he Akia-
Manii soq popula ion. In con as , an le possession in male cal es was common and
simila in male cal es o he Kange lussuaq-Sisimiu and Ame alik popula ions a 86.2%
and 87.5%, espec i ely (Cuyle e al. 2021, 2023).
Cows
Al hough among wild ca ibou popula ions in No h Ame ica, 98% o cows ha e an le s in
la e win e (Kelsall 1968, Reime s 1993, Be ge ud e al. 2008), an le possession among
cows in ca ibou popula ions o Wes G eenland is highly a iable and o en exhibi s a high
pe cen age o polled cows, i.e., no an le s (Thing e al. 1986, Cuyle e al. 2002, 2021). In
No h Ame ica, decline in he pe cen age o an le ed cows has been a ibu ed o
o e g azed ange, because ha is a majo ac o causing poo cow body condi ion, which
p ecludes an le g ow h (Gaa e & Skogland 1980, Reime s 1983, Thing e al. 1986,
Be ge ud e al. 2008). In Wes G eenland, ange condi ion is no he majo ac o
in luencing he numbe o polled cows (Cuyle e al. 2021).
Albei polled (an le s lacking) cows a e common among ca ibou popula ions in Wes
G eenland, he Akia-Manii soq popula ion a exceeds he no m, i.e., jus 32% o cows had
an le s in la e win e 2019. Ins ead, mos cows a e polled (68%). This was also e lec ed in
an le possession o absence among emale cal es, and o a lesse ex en e en male cal es.
53
The 2019 esul s o poo an le possession among Akia-Manii soq cows a e suppo ed by
1998 obse a ions o 19% an le ed Akia-Manii soq cows (Cuyle unpublished).
Lack o an le s in Akia-Manii soq cows is in sha p con as o he si ua ion in No h
Ame ica. The e, an le possession is assumed o con e dominance among la ge
agg ega ions o ca ibou ha mus eed by c a e ing h ough deep snow (Kelsall 1968,
Reime s 1993, Be ge ud e al. 2008). Ne e heless, Be ge ud e al. (2008) p esen ed e idence
ha a high pe cen age o polled cows would be expec ed in popula ions ha had small
g oup sizes and li le dependence on c a e ing. Akia-Manii soq ca ibou do ha e small
g oup sizes, mean 3.75 ± 3.0 s anda d de ia ion. Fu he , xe ic condi ions occu in inland
a eas and can esul in negligible snow dep h co e ing ood esou ces in he Uja assui
sub-a ea and anywhe e adjacen he G eenland Ice Cap (Appendix 1, Figs. 31-34, 37-46).
Thus, he pe cen age o polled Akia-Manii soq cows may be un ela ed o ange condi ion,
bu a he e lec a educed need o he dominance con e ed by an le s.
Wi h only 32% o cows possessing an le s in 2019, he Akia-Manii soq popula ion is in
sha p con as o ei he o he o he wo la ge ca ibou popula ions (Kange lussuaq-
Sisimiu and Ame alik) ha ha e been su eyed in Wes G eenland. Fo example, o he
same su ey yea , 2019, 92% o Ame alik cows had an le s (Cuyle e al. 2023), and
al hough no as g ea a di e ence, in 2018, an le ed Kange lussuaq-Sisimiu cows we e
54% (Cuyle e al. 2021).
I is no able ha despi e cows being p edominan ly polled in Ma ch 2019, he Akia-
Manii soq popula ion had an excellen pe cen age o cal es and cal ec ui men . High cal
numbe s con adic any assump ion ha cows a e in poo body condi ion (e.g., owing o
o e g azed ange) a he he opposi e is indica ed. We sugges ha an inhe i ed ai may
be he majo in luence causing p edominan ly polled Akia-Manii soq cows.
Snowmobile use Akia-No dlande
Akia-No dlande is a peninsula o ugged lowlands jus opposi e G eenland’s capi al ci y,
Nuuk, on he no h side o Nuuk (God håb) jo d. The e a e no pe manen human
habi a ions, bu he e a e nume ous ec ea ional summe houses/cabins. Despi e he
con inued p ohibi ion on snowmobile use o his a ea, ecen snowmobile ac i i y was
obse ed. Snowmobile use was i s obse ed in Ma ch 1997 (Cuyle unpublished) and
was ex ensi e du ing he 2010 ca ibou win e ha es (Cuyle e al. 2011).

54
O he species obse ed
Du ing he ea ly Ma ch 2019 su ey mul iple species o he han ca ibou we e obse ed.
P a migan and ha es we e ela i ely abundan and appea ed o suppo a heal hy a c ic
ox popula ion. Gy alcons, sea eagles and snowy owls we e also obse ed. Al hough
since ca. 2000 local knowledge has epo ed muskox p esence in he Cen al egion o
Wes G eenland, like all p e ious ae ial su eys o his egion, no muskoxen we e
obse ed du ing he ea ly Ma ch 2019 su ey.
The e we e wo ae ial su eys conduc ed in ea ly Ma ch 2019, i.e., his s udy’s Cen al
egion and ano he in he Sou h egion (Cuyle e al. 2023). Al hough he su eys occu ed
almos simul aneously, each o he obse ed species (o he han ca ibou) we e mo e
nume ous in he Cen al egion han in he Sou h (Cuyle e al. 2023). Fo example, he e
we e h ee imes mo e p a migan in he Cen al egion and almos wice as many ha es.
No unexpec edly hen ega ding p eda o s, he e we e ou imes he numbe o a c ic
oxes and se e al a ian p eda o s in he Cen al egion. S ill, he Cen al egion’s a ea o
su ey e o (Table 2) was 2.4 imes g ea e han o he Sou h egion (Cuyle e al. 2023).
This pa ially explains he g ea e numbe o obse a ions. Howe e , i emains ha he
Cen al egion had mo e p a migan and oxes as well as a ian p eda o s. La e win e 2019
habi a condi ions in he Cen al egion suppo ed a g ea e abundance o se e al species
han condi ions in he Sou h egion.
Acknowledgemen s
This p ojec was inanced p ima ily by he Go e nmen o G eenland and by
Pinngo i ale i ik – 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 S ig E ick o his sa e lying.
Fo p o iding expe ienced obse e s, excellen a spo ing ca ibou despi e poo de ec ion
condi ions, hanks a e also due he G eenland Associa ion o P o essional Hun e s
(KNAPK) and he G eenland Fishe ies and License Con ol (GFLK). We also hank Rikke
Guldbo g Hansen and La s Wi ing o cons uc i e e iew o he manusc ip .
55
Li e a u e ci ed
A onsson M., Heiðma sson S., Jóhannesdó i H., Ba y T., B aa J., Bu ns C.T, Coulson S.J., Cuyle C., Falk
K., Helgason H., Lá usson K.F., Lawle J.P., Kulmala P., MacNea ney D., Obe ndo e E., Ra olainen V.,
Schmid N.M., Solo ie M., Coon C. & Ch is ensen T. 2021. S a e o he A c ic e es ial biodi e si y
epo . Conse a ion o A c ic Flo a and Fauna In e na ional Sec e a ia , Aku ey ik, Iceland.ISBN 978-
9935-431-94-3. 123 pp.
Be ge ud A.T. 1967. Managemen o Lab ado ca ibou. J. Wildl. Manage. 31:621-642.
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.
P oc. 2nd Reindee /Ca ibou Symp., 556-581. T ondheim: Di ek o a e o Vil og Fe sk anns isk.
Be ge ud A.T., Lu ich S.N. & Camps L. 2008. The e u n o ca ibou o Unga a.. McGill-Queen’s Uni e si y
P ess, Mon eal & Kings on, London, I haca. 586 pp.
B ewe M.J., Bu le A. & Cooksley S.L. 2016. The ela i e pe pe o mance AIC, AICc
and BIC in he p esence o
unobse ed he e ogenei y. Me hods in Ecology and E olu ion 7(6): 679–692.
Buckland S.T., Ande son D.R., Bu nham K.P. & Laake J.L. 1993. Dis ance Sampling: Es ima ing
Abundance o Biological Popula ions. Sp inge .
Buckland S.T., Ande son D.R., Bu nham K.P., Laake J.L., Bo che s D.L. & Thomas L. 2001. In oduc ion o
Dis ance Sampling. Ox o d: Ox o d Uni e si y P ess.
Buckland S.T., Ande son D.R., Bu nham K.P., Laake J.L.,
Bo che s D.L. & Thomas
L. 2004. Ad anced
Dis ance Sampling: Es ima ing abundance o biological popula ions. Ox o d Uni e si y P ess.
Buckland S.T., Rexs ad E.A., Ma ques T.A. & Oedeko en C.S. 2015. Dis ance Sampling: Me hods and
Applica ions. Sp inge .
CARMA (Ci cum A c ic Rangi e Moni o ing & Assessmen ne wo k). www.ca ma.ca .is/
Co eia I.J.F. 2020. Es ima ing ca ibou abundance in Wes G eenland using dis ance sampling me hods. MSc.
Thesis. Uni e si y o Lisbon, Po ugal. 63 pp.
Cou u ie S., Dale A., Wood B. & Snook J. 2018. Resul s o a Sp ing 2017 ae ial su ey
o he To nga Moun ains
Ca ibou He d. Technical epo , To nga Wildli e, Plan s and
Fishe ies Sec e a ia .
Cuyle C. 2020. Biologisk ådgi ning o ensdy - og moskusokse angs i 2020. Pinngo i ale i ik –
G eenland Ins i u e o Na u al Resou ces ha es ad ice documen o he Go e nmen o G eenland
(GN 40-59/40-00-02-42), 4 pp. Supplemen a y ma e ials, 26 pp.
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. G eenland Ins i u e o Na u al Resou ces. Technical
Repo No. 117. 79 pp.
Cuyle , C., Ma ques, T.A., Co eia, I.J.F., Jensen, A., Mølgaa d, H. & Wagnhol , J. 2023. 2019 S a us o
Ame alik ca ibou popula ion, Sou h egion, Wes G eenland. Pinngo i ale i ik – G eenland Ins i u e o
Na u al Resou ces. Technical Repo No. 125. 109 pp.
Cuyle C., Nagy J. & Zingle sen K. 2017. Seasonal mo emen and ac i i y o Akia-Manii soq ca ibou cows in
Wes G eenland as de e mined by sa elli e. Pinngo i ale i ik – G eenland Ins i u e o Na u al
Resou ces. Technical Repo No. 99. 94 pp.
56
Cuyle C., Nymand J., Jensen A. & Mølgaa d H.S. 2016. 2012 s a us o wo Wes G eenland ca ibou
popula ions, 1) Ame alik, 2) Qeqe a sua siaa . G eenland Ins i u e o Na u al Resou ces Technical
Repo No. 98, 179 pp.
Cuyle L.C., Rosing M., Egede J., Hein ich R. & Mølgaa d H. 2005. S a us o wo Wes G eenland ca ibou
popula ions; 1) Akia-Manii soq, 2) Kange lussuaq-Sisimiu . Pinngo i ale i ik – G eenland Ins i u e o
Na u al Resou ces. Technical Repo No. 61. Pa I-II, 64+44 pp.
Cuyle C., Rosing M., Hein ich R., Egede J. & Ma hæussen L. 2007. S a us o wo Wes G eenland ca ibou
popula ions 2006, 1) Ame alik, 2) Qeqe a sua siaa . G eenland Ins i u e o Na u al Resou ces.
Technical epo No. 67. 143 pp. (Pa I: 1-74; Pa II: 75-143).
Cuyle C., Rosing M., Linnell J.D.C., Loison A., Inge sle T. & Landa A. 2002. S a us o he Kange lussuaq-
Sisimiu ca ibou popula ion (Rangi e a andus g oenlandicus) in 2000, Wes G eenland.
Pinngo i ale i ik – G eenland Ins i u e o Na u al Resou ces. Technical Repo No. 42. 52 pp.
Cuyle C., Rosing M., Linnell J.D.C., Lund P.M., Jo dhøy P., Loison A. & Landa A. 2003. S a us o 3 Wes
G eenland ca ibou popula ions; 1) Akia-Manii soq, 2) Ame alik & 3) Qeqe a sua siaa .
Pinngo i ale i ik – G eenland Ins i u e o Na u al Resou ces. Technical Repo No. 46. 74 pp.
Cuyle C., Rosing M., Mølgaa d H., Hein ich R. & Raund up K. 2011. S a us o wo wes G eenland ca ibou
popula ions 2010; 1) Kange lussuaq-Sisimiu & 2) Akia-Manii soq. G eenland Ins i u e o Na u al
Resou ces. Technical Repo No. 78. 158 pp. (Pa I: 1-86; Pa II: 87-158).
Cuyle L.C. & Øs e gaa d J. 2005. Fe ili y in wo Wes G eenland ca ibou popula ions 1996/97: Po en ial o
apid g ow h. Wildli e Biology. 11(3): 221-227.
Gaa e E. & Skogland T. 1980. Lichen- eindee in e ac ion in a simple case model. P oc. 2nd In e na ional
Reindee /Ca ibou symposium 47-56. T ondheim: Di ek o a e o il o e sk anns isk.
Gibbons J.D. & Chak abo i S. 2011. Nonpa ame ic S a is ical In e encing. Chapman & Hall.
Ga es C.C., Adamczewski J. & Mulde s R. 1986. Popula ion dynamics, win e ecology and social
o ganiza ion o Coa s Island ca ibou. A c ic. 39(3): 216-222.
Hea d D.C. & Ouelle J.P. 1994. Dynamics o an in oduced ca ibou popula ion. A c ic. 47(1): 88-95.
Jepsen B.I, Siegismund H.R. & F edholm M. 2002. Popula ion gene ics o he na i e ca ibou (Rangi e a andus
g oenlandicus) and he semi-domes ic eindee (Rangi e a andus a andus) in Sou hwes e n G eenland:
E idence o in og ession. Conse a ion Gene ics. 3: 401-409.
Kelsall L.B. 1968. The Ca ibou. O awa: Queen’s P in e .
Kingsley M.C.S. & Cuyle C. 2002. Ca ibou ha es 2002: ad iso y documen . Pinngo i ale i ik – G eenland
Ins i u e o Na u al Resou ces, Nuuk. 12 pp.
Kö ne C. 2007. The use o ‘al i ude’ in ecological esea ch. T ends Ecol. E ol. 22: 569–574.
Linnell J.D.C., Cuyle C., Loison A., Lund P.M., Mo z eld K.G., Inge sle T. & Landa A. 2000. The scien i ic
basic o managing he sus ainable ha es o ca ibou and muskoxen in G eenland o he 21s Cen u y:
an e alua ion and agenda. Technical Repo 34, G eenland Ins i u e o Na u al Resou ces,
Pinngo i ale iffik.
Loison A., Cuyle C., Linnell J.D.C. & Landa A. 2000. The ca ibou ha es in Wes G eenland, 1995-1998.
Pinngo i ale i ik – G eenland Ins i u e o Na u al Resou ces. Technical Repo No. 28. 33 pp.
57
Mille D.L., Rexs ad E., Thomas L., Ma shall L. & Laake J. L. 2016. Dis ance Sampling in R.
Jou nal o
S a is ical So wa e
89(1): 1–28.
Ma ques T.A., Buckland S.T., Bo che s D.L., Rexs ad E. & Thomas L. 2011. Dis ance Sampling. In e na ional
Encyclopedia o S a is ical Science, 1: 398–400.
Ma ques T.A., Thomas L., Fancy S.G. & Buckland S.T. 2007. Imp o ing es ima es o bi d densi y using
mul iple co a ia e dis ance sampling. The Auk 124(4): 1229–1243.
Naalakke suisu . 2019. P ess elease 11 Janua y 2019: Fangs a muskoxen og ensdy in e 2019 (Hun ing o
muskoxen and ca ibou win e 2019) Bilag 4. h ps://naalakke suisu .gl/da/Naalakke suisu /Nyhede
Pollock K.H., Nichols J.D., B ownie C. & Hines J.E. 1990. S a is ical in e ence o cap u e- ecap u e
expe imen s. Wildli e Monog aphs 107: 3–97.
Poole K.G., Cuyle C. & Nymand J. 2013. E alua ion o ca ibou Rangi e a andus g oenlandicus su ey
me hodology in Wes G eenland. Wildli e Biology 19: 225–239.
Reime s E. 1983. G ow h a es and body size di e ences in Rangi e , a s udy o causes and e ec . Rangi e 3:
3-15.
Reime s E. 1993. An le less emales among eindee and ca ibou. Can. J. Zool. 71: 319-325.
Skoog R.O. 1968. Ecology o he ca ibou (Rangi e a andus g an i) in Alaska. Ph.D. Thesis. Uni e si y o
Cali o nia a Be keley, 699 pp.
Thing H., Olesen C.R. & Aas up P. 1986. An le possession by wes G eenland emale ca ibou in ela ion o
popula ion cha ac e is ics. Rangi e , Special Issue 1: 297-304.
Thomas L., Buckland S.T., Bu nham K.P., Ande son D.R., Laake, J.L., Bo che s D.L. &
S indbe g S. 2002.
Dis ance Sampling.
Encyclopedia o En i onme ics
1: 544–552.
Thomas L., Buckland S.T., Rexs ad E.A, Laake J.L., S indbe g S., Hedley S.L., Bishop J.R.B., Ma ques
T.A. & Bu nham K.P. 2010. Dis ance so wa e: design and analysis o dis ance sampling su eys o
es ima ing popula ion size. J. Appl. Ecol. 47(1): 5-14.
64
Cen al egion ae ial su ey condi ions, Ma ch 2019
Figu e 37. Uja assui sub-a ea, illus a ing ypical condi ions o e ain, snow, and sunligh p esen o mos o he
line ansec s. Pho o A. Jensen.
Figu e 38. Uja assui sub-a ea on he one day wi h sunshine, iew wes om he eas end o line ansec 27,
illus a ing ugged highland e ain and lack o snow. Pho o C. Cuyle .

65
Cen al egion ae ial su ey condi ions, Ma ch 2019
Figu e 39. Uja assui sub-a ea, eas end o line ansec 35, iew o wes illus a ing snow dep h and la ligh . Pho o
A. Jensen.
Figu e 40. Uja assui sub-a ea, illus a ing ypical e ain, snow, and sunligh condi ions o line ansec s 36, 35 and
33. No e he a he xe ic landscape, iew o he wes wi h he la ge lake, Tase ssuaq, in backg ound. Pho o A. Jensen.
66
Cen al egion ae ial su ey condi ions, Ma ch 2019
Figu e 41. Uja assui sub-a ea e ain, snow, and la ligh condi ions a he eas end o line ansec 36, iew o he
wes . Pho o A. Jensen.
Figu e 42. Uja assui sub-a ea, illus a ing ypical e ain, snow, and sunligh condi ions in a a he xe ic landscape,
iew no hwes om line ansec 33 owa ds he la ge lake, Tase ssuaq, in a backg ound. Pho o A. Jensen.
67
Cen al egion ae ial su ey condi ions, Ma ch 2019
Figu e 43. Uja assui sub-a ea, illus a ing ugged highland e ain, snow dep hs and sunligh ypical o line ansec
30. Simila condi ions exis ed o line ansec s 27, 29, 31 and 28. This iew sou hwes om line ansec 30 owa ds
Innajua oq (Bi d Moun ain) in le backg ound. Pho o A. Jensen.
Figu e 44. Uja assui sub-a ea, I isa oq highlands, xe ic condi ions o eas end line ansec 32, iew N ac oss he
many ozen lakes and edge o G eenland Ice Cap in o eg ound. Pho o A. Jensen.
68
Cen al egion ae ial su ey condi ions, Ma ch 2019
Figu e 45. Uja assui sub-a ea, I isa oq highlands iew eas owa ds small bay in he Uja assui Kange lua jo d.
Thin snow laye wi h g ound showing h ough. Pho o C. Cuyle .
Figu e 46. Uja assui sub-a ea, I isa oq highlands illus a ing almos non-exis en snow laye , iew wes owa ds
Innajua oq (Bi d Moun ain) in a -le backg ound. Pho o A. Jensen.
69
Appendix 2
Place names o he Cen al egion
Figu e 47. Place names used ega ding Cen al egion (ca. 64°–66°N; 50°–53°W), which is inhabi ed by he Akia-
Manii soq ca ibou popula ion.

70
Appendix 3
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)
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 DS 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
𝑎
𝑝𝑙𝑜𝑡
(Fig. 48). 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 48. 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 ⋅ 𝑎
𝑝𝑙𝑜𝑡
= 4𝑘𝑚
2
o Fig. 48)
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
b
e
ob ained
b
y
simply
mul iplying
𝐷

plo by he
o al
a
ea
𝐴
,
Equa ion
(2)
71
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 DS, 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
𝑃
𝑎
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
ack line, and he o al ansec leng h
𝐿 = ∑𝑙
𝑗
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
,
c
𝑣
(𝐷
),
is
ela ed
wi h
w
o
andom
comp
onen
s
e e ed
ab
o
e,
encoun
e
a e
(
𝑛
𝑝𝑙𝑜𝑡
/𝐿
),
and
𝑃
󰆹
a
, plus
a
hi d
one
ha
is
he
es ima e
o
he
exp
ec ed
size o de ec ed clus e s (
𝐸
󰆹
(
𝑠)
).
Assuming
independence
b
e
w
een
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)
72
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
b
y
he
ansec s,
𝑃

a
,
needs
o
b
e
es ima ed.
F
o
his
p o
jec ,
he
ob
jec
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. 49). 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 DS is use ul, since
i allows a igo ous amewo k o he es ima ion o
P
a and hen an es ima e o abundance can
be ob ained as shown in Equa ion (3).
73
Figu e 49.
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 ack line (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 DS 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
mo
del.
Once
he
de ec ion
unc ion
is
es ima ed,
𝑃

a can
b
e
ob ained
ia
he
ollo
wing
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
80
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
𝐻
0
∶ 𝐹 (𝑥) = 𝐹
0
(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
b
e
w
een
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)

81
C amé - on Mises es
Simila ly 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).
82
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).
83
Appendix 4
Dis ance Sampling Assump ions – sho summa y
Line ansec DS assump ions and design a e desc ibed in Buckland e al.
(1993) and a summa y o he assump ions in ela ion o ca ibou su ey 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 line ansec s 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
line ansec 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.
84
Appendix 5
Pho os o c
amou laged ca ibou
obse ed Ma ch 2019.
Figu e 53. Eigh ca ibou, se e al camou laged agains backg ound, wi hin 200 m o helicop e . Pho o
A. Jensen.
Figu e 54. Th ee ca ibou camou laged agains backg ound, wi hin 100 m om helicop e . Pho o A.
Jensen.
85
Appendix 6
His og ams o de ec ed dis ances
His og ams o de ec ed dis ances supe imposed wi h es ima ed de ec ion
unc ions o all unca ed i ed models, p esen ed o de as in Table 3

86
87
Figu e 55. His og ams o de ec ed dis ances supe imposed wi h es ima ed de ec ion unc ions o all
unca ed i ed models.
The pa ame e es ima es and a iabili y associa ed wi h hem (Table 13), wi h
Ex eme as he e e ence le el o compa ison. Illus a es ha High
camou lage has a lowe (nega i e) bu simila (es ima e close o 0) de ec ion
p obabili y as Ex eme camou lage. Medium camou lage has a mo e nega i e
es ima e and hus lowe p obabili y o de ec ion ela i e o Ex eme and High.
Fu he , Low camou lage, being posi i e, means he p obabili y o de ec ion is
g ea e when compa ed wi h Ex eme camou lage (as also shown in Fig. 15).
Table 13. De ec ion unc ion pa ame e s’ es ima es.
Es ima e
S anda d E o
In e cep
-1.353
0.115
Camou lage High
-0.089
0.122
Camou lage Medium
-0.571
0.140
Camou lage Low
0.371
0.226
No e: Es ima es a e on log scale.
88
Appendix 7
Recommenda ions o imp o ing u u e su eys
Ae ial su ey me hods & design
The 9.6% su ey co e age o he 2019 Dis ance Sampling (DS) su eys o he
Akia-Manii soq ca ibou popula ion p omo es accu acy o abundance
es ima es and should be con inued in he u u e o pe mi e alua ing
popula ion ends. 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 . Demog aphic (sex, age, cal ec ui men ) da a mus con inue o be
collec ed in e o s sepa a e om lying he line ansec s o DS.
Fligh al i udes om 30 o 40 m pe mi scanning he landscape o ca ibou
e en ou o 1000-1500m om he ack line wi hou dead-g ound in e e ing.
Jus be awa e he deg ee o which he ca ibou a e ex emely camou laged
agains he ypical backg ounds. This can cause obse e a igue, men al
exhaus ion, e en a he ela i ely slow speeds lown (60-70 km/hou ). Any
‘dead’ g ound causing ca ibou de ec ions o be missed, will likely be
mi iga ed by he DS analysis.
T aining and es ing, obse e abili y o judge co ec dis ance bin is necessa y
o imp o emen o his impo an a iable. 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. Fla e ain may p o ide a mo e (no mal)
ho izon al line-o -sigh o he animals, which may inc ease binning accu acy.
Howe e , e ain ha slopes away, ei he up o down, con uses obse e s’
abili y o judge dis ance om ack line o animals. The s eepe he slope, he
g ea e he e o s.
The iming o ae ial su eys could emain ea ly Ma ch because ha 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.
In G eenland, helicop e s a e seldom a ailable a sho no ice. Book abou 3-5
mon hs ahead and ea i m booking se e al imes he ea e . Fo es ima ing
he necessa y window (da es) ha helicop e is booked o su ey, i s
calcula e he numbe o days equi ed o su ey. Then, add days o allow o
89
se e al non- lying days owing o pilo lying hou s going o e weekly limi ,
ai po closu es on Sundays, and poo wea he . Fo he la e a minimum 3-4
days should be alloca ed.
Book su ey obse e s ea ly (Fig. 56), abou six mon hs in ad ance, o ensu e
he p obabili y o ob aining he obse e s you equi e. A ibu es would
include p e ious expe ience de ec ing supe bly camou laged ca ibou, and
p o en lack o nausea, e.g., a sea o in helicop e s. E en he usually seda e
helicop e maneu e s o ansec lines can illici nausea in some. Meanwhile,
he non-s op ab up lying maneu e s equi ed o ca ibou demog aphics
cause nausea in mos pe sons.
No e: E en p e ious helicop e expe ience, including animal li e cap u e, does
no gua an ee lack o nausea du ing sha p maneu e s speci ic o ca ibou
demog aphics wo k.
Figu e 56. The h ee obse e s, D . Ch is ine Cuyle , scien i ic leade (le ), Aslak Jensen, comme cial
hun e (cen e ), and Hans Mølgaa d, Sisimiu hun ing o ice ( igh ).
S anda diza ion o da a collec ion ega ding su ace condi ions
P io o 2019, he co a ia es (including deg ee o camou lage, % snow co e ,
snow dep h, icing, isibili y, ligh ing (e.g., la ligh , shadow), p esence o
boulde s and hei size, ege a ion poking h ough snow laye s, e c.) we e
eco ded wi hou s anda diza ion and o en ad hoc. In con as he 2019
su ey used speci ic s anda dized quali a i e e ms o make he co a ia es
a ailable o analyses. E alua ions o all en i onmen al co a ia es we e
s anda dized o jus i e easy quali a i e e ms: Ze o, Low, Medium, High,
and Ex eme. Howe e , he e we e oo many co a ia es o pe mi eco ding
each wi h e e y de ec ion o he objec -o -in e es (ca ibou).