Ecological correlates of the distribution of territorial Svalbard rock ptarmigan (Lagopus muta hyperborea)

Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In this paper we develop and evaluate statistical habitat models for presence of territorial Svalbard rock ptarmigan ( Lagopus muta hyperborea Sund...

Full description

Saved in:
Bibliographic Details
Published inCanadian journal of zoology Vol. 85; no. 1; pp. 122 - 132
Main Authors Pedersen, Å.Ø, Jepsen, J.U, Yoccoz, N.G, Fuglei, E
Format Journal Article
LanguageEnglish
Published Ottawa, ON National Research Council of Canada 01.01.2007
NRC Research Press
Canadian Science Publishing NRC Research Press
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In this paper we develop and evaluate statistical habitat models for presence of territorial Svalbard rock ptarmigan ( Lagopus muta hyperborea Sundevall, 1845) cocks in spring and apply the best model to assess ptarmigan habitat selection in a larger extrapolated region. Terrain variables were extracted at detailed (10 m digital elevation model (DEM)) and coarse (50 m DEM) scales to compare model performance. Sets of candidate environmental variables related to terrain and vegetation cover were developed and explanatory variables were calculated at increasing distances from the count site to well above the typical size of ptarmigan territory. We used ecological niche factor analysis to describe the difference between used and available sites. Survey sites used by cocks were characterized by a restricted range of altitude, a high degree of terrain heterogeneity, and dense vegetation cover compared with overall site availability in the survey region. We then used model selection criteria (AIC c ) to find the most parsimonious logistic regression models estimating habitat resource selection functions for cocks. Detailed terrain variables were better predictors than coarse terrain variables. The normalized difference vegetation index (NDVI) was a good predictor of presence of territorial cocks, but not as good as the most preferred habitat type. Owing to limited availability of high-quality vegetation maps, the best model containing NDVI and 10 m DEM variables was used for extrapolation of male ptarmigan habitat. Our results show that it is possible to obtain a model with a high ability to rank habitats using a low number of map-derived variables. Such rankings can then be used to improve field sampling designs and are therefore a useful tool for management and conservation of ptarmigan and wildlife in Arctic and alpine areas.
AbstractList Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In this paper we develop and evaluate statistical habitat models for presence of territorial Svalbard rock ptarmigan (Lagopus muta hyperborea Sundevall, 1845) cocks in spring and apply the best model to assess ptarmigan habitat selection in a larger extrapolated region. Terrain variables were extracted at detailed (10 m digital elevation model (DEM)) and coarse (50 m DEM) scales to compare model performance. Sets of candidate environmental variables related to terrain and vegetation cover were developed and explanatory variables were calculated at increasing distances from the count site to well above the typical size of ptarmigan territory. We used ecological niche factor analysis to describe the difference between used and available sites. Survey sites used by cocks were characterized by a restricted range of altitude, a high degree of terrain heterogeneity, and dense vegetation cover compared with overall site availability in the survey region. We then used model selection criteria (AIC^sub c^) to find the most parsimonious logistic regression models estimating habitat resource selection functions for cocks. Detailed terrain variables were better predictors than coarse terrain variables. The normalized difference vegetation index (NDVI) was a good predictor of presence of territorial cocks, but not as good as the most preferred habitat type. Owing to limited availability of high-quality vegetation maps, the best model containing NDVI and 10 m DEM variables was used for extrapolation of male ptarmigan habitat. Our results show that it is possible to obtain a model with a high ability to rank habitats using a low number of map-derived variables. Such rankings can then be used to improve field sampling designs and are therefore a useful tool for management and conservation of ptarmigan and wildlife in Arctic and alpine areas. [PUBLICATION ABSTRACT]
Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In this paper we develop and evaluate statistical habitat models for presence of territorial Svalbard rock ptarmigan (Lagopus muta hyperborea Sundevall, 1845) cocks in spring and apply the best model to assess ptarmigan habitat selection in a larger extrapolated region. Terrain variables were extracted at detailed (10A m digital elevation model (DEM)) and coarse (50A m DEM) scales to compare model performance. Sets of candidate environmental variables related to terrain and vegetation cover were developed and explanatory variables were calculated at increasing distances from the count site to well above the typical size of ptarmigan territory. We used ecological niche factor analysis to describe the difference between used and available sites. Survey sites used by cocks were characterized by a restricted range of altitude, a high degree of terrain heterogeneity, and dense vegetation cover compared with overall site availability in the survey region. We then used model selection criteria (AIC sub(c)) to find the most parsimonious logistic regression models estimating habitat resource selection functions for cocks. Detailed terrain variables were better predictors than coarse terrain variables. The normalized difference vegetation index (NDVI) was a good predictor of presence of territorial cocks, but not as good as the most preferred habitat type. Owing to limited availability of high-quality vegetation maps, the best model containing NDVI and 10A m DEM variables was used for extrapolation of male ptarmigan habitat. Our results show that it is possible to obtain a model with a high ability to rank habitats using a low number of map-derived variables. Such rankings can then be used to improve field sampling designs and are therefore a useful tool for management and conservation of ptarmigan and wildlife in Arctic and alpine areas.Original Abstract: Les modeles explicatifs de l'habitat sont devenus des outils importants de recherche et de gestion pour suivre la repartition spatiale et l'abondance des especes de la faune. Dans notre etude, nous developpons et evaluons des modeles statistiques de l'habitat relies a la presence de males territoriaux de lagopedes de Svalbard (Lagopus muta hyperborea Sundevall, 1845) au printemps et nous utilisons le meilleur modele pour evaluer la selection de l'habitat par les lagopedes dans une region extrapolee plus etendue. L'extraction des variables du terrain a des echelles fine (modele digital d'altitude (A" DEM A") de 10 m) et grossiere (DEM de 50 m) permet de comparer les performances du modele. Nous avons calcule des series de variables environnementales selectionnees reliees au terrain et a la couverture vegetale, ainsi que des variables explicatives a des distances progressivement plus grandes depuis le site de mesure jusque bien au-delA de la taille typique du territoire des lagopedes. L'analyse factorielle de la niche ecologique a servi a decrire les differences entre les sites utilises et les sites disponibles. Les sites de surveillance utilises par les males se caracterisent par une gamme reduite d'altitudes, une forte heterogeneite du terrain et une couverture vegetale plus dense que les sites generalement disponibles dans la meme region. Nous avons ensuite utilise des criteres de selection des modeles (AIC sub(c)) pour choisir le modele de regression logistique le plus parcimonieux qui estime la fonction de selection des ressources de l'habitat par les males. Les variables detaillees de terrain sont de meilleures variables explicatrices que les variables grossieres de terrain. L'indice de vegetation normalise (A" NDVI A") est une bonne variable explicative de la presence de males territoriaux, mais moins que le type d'habitat le plus prefere. A cause de la disponibilite limitee de cartes de la vegetation de bonne qualite, nous avons utilise le meilleur modele incorporant NDVI et DEM de 10 m pour extrapoler l'habitat des lagopedes males. Nos resultats montrent qu'il est possible d'obtenir un modele tout a fait capable d'ordonner les habitats a l'aide d'un petit nombre de variables extraites de cartes geographiques. de telles ordinations peuvent servir a ameliorer les plans d'echantillonnage sur le terrain; ils constituent donc un outil utile pour l'amenagement et la conservation des lagopedes et de la faune en general dans les regions alpines et arctiques. [Traduit par la Redaction]
Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In this paper we develop and evaluate statistical habitat models for presence of territorial Svalbard rock ptarmigan ( Lagopus muta hyperborea Sundevall, 1845) cocks in spring and apply the best model to assess ptarmigan habitat selection in a larger extrapolated region. Terrain variables were extracted at detailed (10 m digital elevation model (DEM)) and coarse (50 m DEM) scales to compare model performance. Sets of candidate environmental variables related to terrain and vegetation cover were developed and explanatory variables were calculated at increasing distances from the count site to well above the typical size of ptarmigan territory. We used ecological niche factor analysis to describe the difference between used and available sites. Survey sites used by cocks were characterized by a restricted range of altitude, a high degree of terrain heterogeneity, and dense vegetation cover compared with overall site availability in the survey region. We then used model selection criteria (AIC c ) to find the most parsimonious logistic regression models estimating habitat resource selection functions for cocks. Detailed terrain variables were better predictors than coarse terrain variables. The normalized difference vegetation index (NDVI) was a good predictor of presence of territorial cocks, but not as good as the most preferred habitat type. Owing to limited availability of high-quality vegetation maps, the best model containing NDVI and 10 m DEM variables was used for extrapolation of male ptarmigan habitat. Our results show that it is possible to obtain a model with a high ability to rank habitats using a low number of map-derived variables. Such rankings can then be used to improve field sampling designs and are therefore a useful tool for management and conservation of ptarmigan and wildlife in Arctic and alpine areas.
Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In this paper we develop and evaluate statistical habitat models for presence of territorial Svalbard rock ptarmigan ( Lagopus muta hyperborea Sundevall, 1845) cocks in spring and apply the best model to assess ptarmigan habitat selection in a larger extrapolated region. Terrain variables were extracted at detailed (10 m digital elevation model (DEM)) and coarse (50 m DEM) scales to compare model performance. Sets of candidate environmental variables related to terrain and vegetation cover were developed and explanatory variables were calculated at increasing distances from the count site to well above the typical size of ptarmigan territory. We used ecological niche factor analysis to describe the difference between used and available sites. Survey sites used by cocks were characterized by a restricted range of altitude, a high degree of terrain heterogeneity, and dense vegetation cover compared with overall site availability in the survey region. We then used model selection criteria (AIC c ) to find the most parsimonious logistic regression models estimating habitat resource selection functions for cocks. Detailed terrain variables were better predictors than coarse terrain variables. The normalized difference vegetation index (NDVI) was a good predictor of presence of territorial cocks, but not as good as the most preferred habitat type. Owing to limited availability of high-quality vegetation maps, the best model containing NDVI and 10 m DEM variables was used for extrapolation of male ptarmigan habitat. Our results show that it is possible to obtain a model with a high ability to rank habitats using a low number of map-derived variables. Such rankings can then be used to improve field sampling designs and are therefore a useful tool for management and conservation of ptarmigan and wildlife in Arctic and alpine areas.
Abstract_FL Les modèles explicatifs de l'habitat sont devenus des outils importants de recherche et de gestion pour suivre la répartition spatiale et l'abondance des espèces de la faune. Dans notre étude, nous développons et évaluons des modèles statistiques de l'habitat reliés à la présence de mâles territoriaux de lagopèdes de Svalbard (Lagopus muta hyperborea Sundevall, 1845) au printemps et nous utilisons le meilleur modèle pour évaluer la sélection de l'habitat par les lagopèdes dans une région extrapolée plus étendue. L'extraction des variables du terrain à des échelles fine (modèle digital d'altitude (« DEM ») de 10 m) et grossière (DEM de 50 m) permet de comparer les performances du modèle. Nous avons calculé des séries de variables environnementales sélectionnées reliées au terrain et à la couverture végétale, ainsi que des variables explicatives à des distances progressivement plus grandes depuis le site de mesure jusque bien au-delà de la taille typique du territoire des lagopèdes. L'analyse factorielle de la niche écologique a servi à décrire les différences entre les sites utilisés et les sites disponibles. Les sites de surveillance utilisés par les mâles se caractérisent par une gamme réduite d'altitudes, une forte hétérogénéité du terrain et une couverture végétale plus dense que les sites généralement disponibles dans la même région. Nous avons ensuite utilisé des critères de sélection des modèles (AIC c ) pour choisir le modèle de régression logistique le plus parcimonieux qui estime la fonction de sélection des ressources de l'habitat par les mâles. Les variables détaillées de terrain sont de meilleures variables explicatrices que les variables grossières de terrain. L'indice de végétation normalisé (« NDVI ») est une bonne variable explicative de la présence de mâles territoriaux, mais moins que le type d'habitat le plus préféré. À cause de la disponibilité limitée de cartes de la végétation de bonne qualité, nous avons utilisé le meilleur modèle incorporant NDVI et DEM de 10 m pour extrapoler l'habitat des lagopèdes mâles. Nos résultats montrent qu'il est possible d'obtenir un modèle tout à fait capable d'ordonner les habitats à l'aide d'un petit nombre de variables extraites de cartes géographiques. De telles ordinations peuvent servir à améliorer les plans d'échantillonnage sur le terrain;; ils constituent donc un outil utile pour l'aménagement et la conservation des lagopèdes et de la faune en général dans les régions alpines et arctiques.
Audience Academic
Author Pedersen, Å.Ø
Jepsen, J.U
Fuglei, E
Yoccoz, N.G
Author_xml – sequence: 1
  givenname: Å.Ø
  surname: Pedersen
  fullname: Pedersen, Å.Ø
  email: ashild.pedersen@ib.uit.no
  organization: University of Tromsø, Department of Biology, 9037 Tromsø, Norway
– sequence: 2
  givenname: J.U
  surname: Jepsen
  fullname: Jepsen, J.U
  email: jane.jepsen@ib.uit.no
  organization: Norwegian Polar Institute, Polar Environmental Centre, 9296 Tromsø, Norway
– sequence: 3
  givenname: N.G
  surname: Yoccoz
  fullname: Yoccoz, N.G
  email: nigel.yoccoz@ib.uit.no
  organization: University of Tromsø, Department of Biology, 9037 Tromsø, Norway
– sequence: 4
  givenname: E
  surname: Fuglei
  fullname: Fuglei, E
  email: eva.fuglei@npolar.no
  organization: Norwegian Polar Institute, Polar Environmental Centre, 9296 Tromsø, Norway
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18656795$$DView record in Pascal Francis
BookMark eNqV0vFr1DAUB_AiE7xN8V8oE6cTOpOmbdofx5g6OBSc_hxe09dezl7TvaTD-deb8w715ilIfggJn3x5vLzD6GCwA0bRU87OOBfV62-sSHglH0QznpUsEWkpDqIZY6xMMsH4o-jQuWU4FpKzWbS81La3ndHQx9oSYQ8eXWzb2C8wbozzZOrJGzv8uEMi4y2ZoK9voa-Bmpis_hKPHmhlOhjil3Po7Di5eDV5iBd3I1JtCeH0cfSwhd7hk-1-FH1-c_np4l0y__D26uJ8nuhcVj4p6kxiled1KtuyxTSVmmW8EahlXgpRQ14zkAIAsWixaWRZgKzqQoc3DFgmjqKTTe5I9mZC59XKOI19DwPaySle5VlepWmAx_fg0k40hNpUmrKsYllZBvRsgzroUZmhtZ5ArxPVOS9EVoQoFlSyR3U4IEEf_qc14XrHH-_xejQ36nd0tgeF1eDK6L2ppzsPgvH41XcwOaeurj_-h32_a59vGwUuDEpLMGjj1EhmBXSneFnkhazyX13QZJ0jbJU2HtbDEwo3veJMrUdUhRENvyCDf3HP_4z8Q77ayIE0oUMgvfgHPvk73iI1Nq34DvDp_y4
CODEN CJZOAG
CitedBy_id crossref_primary_10_1016_j_apgeog_2016_09_025
crossref_primary_10_1007_s10336_015_1282_6
crossref_primary_10_1007_s10336_013_1001_0
crossref_primary_10_1007_s10344_009_0258_3
crossref_primary_10_1016_j_rse_2016_07_012
crossref_primary_10_1007_s10344_016_0987_z
crossref_primary_10_1093_beheco_arp205
crossref_primary_10_1002_jwmg_276
crossref_primary_10_1007_s10344_013_0766_z
crossref_primary_10_1007_s10344_011_0537_7
crossref_primary_10_2981_wlb_00239
crossref_primary_10_3390_rs9121234
crossref_primary_10_1111_ddi_12096
crossref_primary_10_2981_wlb_00241
Cites_doi 10.1016/S0304-3800(00)00354-9
10.2193/0084-0173(2005)160[1:CEOHDO]2.0.CO;2
10.1111/j.1523-1739.2006.00354.x
10.2307/3676631
10.1098/rspb.2005.3218
10.1046/j.1365-2656.1999.00351.x
10.1007/978-1-4757-3462-1
10.1111/j.1751-8369.1985.tb00510.x
10.14430/arctic1570
10.1046/j.1365-2664.2002.00700.x
10.3354/cr023081
10.1007/s10584-005-9017-y
10.1890/0012-9658(2002)083[2027:ENFAHT]2.0.CO;2
10.1016/S0169-5347(99)01593-1
10.2307/2404188
10.1111/j.0021-8901.2004.00899.x
10.1016/0034-4257(95)00142-5
10.1890/1051-0761(2000)010[1861:RSOVPS]2.0.CO;2
10.1016/S0169-5347(01)02205-4
10.1139/z02-023
10.2307/3802794
10.3402/polar.v18i2.6597
10.2307/1552148
10.1080/01431160110113890
10.1111/j.1523-1739.2005.00148.x
10.14430/arctic1572
10.1111/j.1365-2664.2005.01098.x
10.1007/s10750-006-0042-2
10.2307/177101
10.1139/z05-075
10.14430/arctic1575
10.2193/0022-541X(2006)70[347:RSFBOU]2.0.CO;2
10.1016/S0304-3800(00)00322-7
10.1080/0143116042000192358
10.1080/01431160110113854
10.1023/A:1021354914494
10.14430/arctic1239
10.14430/arctic906
10.1201/9781420010404
10.1007/s003000000188
10.1007/s10531-004-0444-2
10.1016/j.tree.2005.05.011
10.1007/978-1-4757-3121-7
10.1029/2003GL018268
10.1038/163688a0
10.1177/0049124104268644
10.1676/04-036.1
10.1016/S0304-3800(02)00205-3
10.1016/j.foreco.2004.04.014
10.1029/2001JD000986
10.2307/3676630
10.1890/04-0608
10.1007/BF00292508
10.1111/j.1461-0248.2005.00792.x
10.1016/S0304-3800(02)00200-4
ContentType Journal Article
Copyright 2007 INIST-CNRS
COPYRIGHT 2007 NRC Research Press
Copyright National Research Council of Canada Jan 2007
Copyright_xml – notice: 2007 INIST-CNRS
– notice: COPYRIGHT 2007 NRC Research Press
– notice: Copyright National Research Council of Canada Jan 2007
DBID AAYXX
CITATION
IQODW
ISN
ISR
3V.
7QG
7QP
7QR
7SN
7SS
7TK
7X2
7X7
7XB
88A
88E
88I
8AF
8AO
8FD
8FE
8FH
8FI
8FJ
8FK
8FQ
8FV
8G5
ABUWG
AEUYN
AFKRA
ATCPS
AZQEC
BBNVY
BEC
BENPR
BHPHI
BKSAR
C1K
CCPQU
DWQXO
FR3
FYUFA
GHDGH
GNUQQ
GUQSH
HCIFZ
K9.
LK8
M0K
M0S
M1P
M2O
M2P
M3G
M7P
MBDVC
P64
PCBAR
PHGZM
PHGZT
PJZUB
PKEHL
PPXIY
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
Q9U
RC3
DOI 10.1139/z06-197
DatabaseName CrossRef
Pascal-Francis
Gale In Context: Canada
Gale In Context: Science
ProQuest Central (Corporate)
Animal Behavior Abstracts
Calcium & Calcified Tissue Abstracts
Chemoreception Abstracts
Ecology Abstracts
Entomology Abstracts (Full archive)
Neurosciences Abstracts
Agricultural Science Collection
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
Biology Database (Alumni Edition)
Medical Database (Alumni Edition)
Science Database (Alumni Edition)
STEM Database
ProQuest Pharma Collection
Technology Research Database
ProQuest SciTech Collection
ProQuest Natural Science Journals
Hospital Premium Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
Canadian Business & Current Affairs Database
Canadian Business & Current Affairs Database (Alumni)
Research Library
ProQuest Central (Alumni)
ProQuest One Sustainability (subscription)
ProQuest Central UK/Ireland
Agricultural & Environmental Science Collection (subscription)
ProQuest Central Essentials
Biological Science Collection
eLibrary Curriculum
ProQuest Central
Natural Science Collection
Earth, Atmospheric & Aquatic Science Collection
Environmental Sciences and Pollution Management
ProQuest One Community College
ProQuest Central
Engineering Research Database
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
ProQuest Research Library
SciTech Premium Collection
ProQuest Health & Medical Complete (Alumni)
Biological Sciences
Agriculture Science Database
ProQuest Health & Medical Collection
Medical Database
Research Library (subscription)
Science Database
CBCA Reference & Current Events
Biological Science Database
Research Library (Corporate)
Biotechnology and BioEngineering Abstracts
Earth, Atmospheric & Aquatic Science Database
ProQuest Central Premium
ProQuest One Academic (New)
ProQuest Health & Medical Research Collection
ProQuest One Academic Middle East (New)
ProQuest One Health & Nursing
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest Central Basic
Genetics Abstracts
DatabaseTitle CrossRef
Agricultural Science Database
Research Library Prep
ProQuest Central Student
ProQuest Central Essentials
elibrary
ProQuest AP Science
SciTech Premium Collection
ProQuest Central China
Environmental Sciences and Pollution Management
CBCA Complete (Alumni Edition)
ProQuest One Applied & Life Sciences
ProQuest One Sustainability
Health Research Premium Collection
Natural Science Collection
Health & Medical Research Collection
Biological Science Collection
Chemoreception Abstracts
ProQuest Central (New)
ProQuest Medical Library (Alumni)
ProQuest Science Journals (Alumni Edition)
ProQuest Biological Science Collection
ProQuest One Academic Eastern Edition
Earth, Atmospheric & Aquatic Science Database
Agricultural Science Collection
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
Biological Science Database
Ecology Abstracts
Neurosciences Abstracts
ProQuest Hospital Collection (Alumni)
Biotechnology and BioEngineering Abstracts
Entomology Abstracts
ProQuest Health & Medical Complete
ProQuest One Academic UKI Edition
Engineering Research Database
ProQuest One Academic
Calcium & Calcified Tissue Abstracts
ProQuest One Academic (New)
Technology Research Database
ProQuest One Academic Middle East (New)
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest One Health & Nursing
Research Library (Alumni Edition)
ProQuest Natural Science Collection
ProQuest Pharma Collection
ProQuest Biology Journals (Alumni Edition)
ProQuest Central
Earth, Atmospheric & Aquatic Science Collection
ProQuest Health & Medical Research Collection
Genetics Abstracts
Health and Medicine Complete (Alumni Edition)
ProQuest Central Korea
Agricultural & Environmental Science Collection
CBCA Complete
ProQuest Research Library
ProQuest Central Basic
ProQuest Science Journals
CBCA Reference & Current Events
ProQuest SciTech Collection
ProQuest Medical Library
Animal Behavior Abstracts
ProQuest Central (Alumni)
DatabaseTitleList Agricultural Science Database
Ecology Abstracts

CrossRef
Database_xml – sequence: 1
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Zoology
EISSN 1480-3283
0008-4301
EndPage 132
ExternalDocumentID 1249185091
A163465920
18656795
10_1139_z06_197
z06-197
Genre Feature
GeographicLocations Svalbard
Arctic Region
GroupedDBID 02
08R
0R
186
1AW
29B
2XV
3V.
4.4
42X
53G
5GY
5RE
5RP
7X2
7X7
85S
88A
88E
88I
8AF
8AO
8CJ
8FE
8FH
8FI
8FJ
8FQ
8G5
9M8
AAYJJ
ABDBF
ABFLS
ABPPZ
ABPTK
ABUWG
ACGFS
ACGOD
ACIWK
ACNCT
ACPRK
ADBBV
ADKZR
AENEX
AFKRA
AFMIJ
AFRAH
AGCDD
ALMA_UNASSIGNED_HOLDINGS
ATCPS
AZQEC
B4K
BBAFP
BBNVY
BCR
BCU
BEC
BENPR
BES
BHPHI
BKSAR
BLC
BPHCQ
BVXVI
CAG
COF
CS3
D1J
D8U
DWQXO
DZ
EAD
EAP
EAS
EBD
EBS
ECC
EDH
EJD
EMK
EPL
ESX
F5P
FA8
FYUFA
G8K
GNUQQ
GUQSH
HCIFZ
HZ
H~9
IAG
IAO
ICQ
IEA
IEP
IOF
ISE
ISN
ISR
ITC
KM
L7B
LK8
M0K
M0L
M1P
M2O
M2P
M2Q
M3C
M3G
M7P
MBDVC
MV1
MYA
NMEPN
NRXXU
NYCZX
O9-
OHM
OHT
OVD
P2P
PADUT
PCBAR
PEA
PQEST
PQQKQ
PQUKI
PRG
PRINS
PROAC
PSQYO
PV9
QF4
QM4
QM9
QN7
QO4
QRP
RIG
RRCRK
RRP
RZL
S10
SJFOW
TN5
TWZ
U5U
UHB
VQP
WH7
X
XHC
XJT
ZCG
ZY4
-DZ
-~X
00T
0R~
6J9
AAHBH
AAYXX
ABDPE
ABJNI
ACGFO
ACUHS
ADXHL
AEGXH
AEUYN
AIAGR
ALIPV
APEBS
CCPQU
CITATION
DATHI
HMCUK
HZ~
IPNFZ
ONR
PHGZM
PHGZT
TEORI
UKHRP
VQG
ZCA
~02
~KM
IQODW
PJZUB
PPXIY
PQGLB
PMFND
7QG
7QP
7QR
7SN
7SS
7TK
7XB
8FD
8FK
C1K
FR3
K9.
P64
PKEHL
Q9U
RC3
PUEGO
ID FETCH-LOGICAL-c579t-6b47e955b27f8fe227c041d3ec75833ba5b0a73aaee6fedd786a79b6c9550a043
IEDL.DBID 7X7
ISSN 0008-4301
1480-3283
IngestDate Sun Aug 24 03:42:19 EDT 2025
Sat Aug 23 13:52:27 EDT 2025
Tue Jun 17 22:07:55 EDT 2025
Fri Jun 13 00:14:47 EDT 2025
Tue Jun 10 15:34:27 EDT 2025
Tue Jun 10 21:00:59 EDT 2025
Fri Jun 27 06:03:25 EDT 2025
Fri Jun 27 05:29:55 EDT 2025
Mon Jul 21 09:14:23 EDT 2025
Tue Jul 01 00:57:25 EDT 2025
Thu Apr 24 22:57:00 EDT 2025
Wed Nov 11 00:32:49 EST 2020
Thu May 23 14:20:21 EDT 2019
IsPeerReviewed true
IsScholarly true
Issue 1
Keywords Logistic regression
Vertebrata
Territorial behavior
Spatial distribution
Statistical model
Environmental factor
Male
Population dynamics
Plant cover
Habitat selection
Aves
Population density
Language English
License http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
CC BY 4.0
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c579t-6b47e955b27f8fe227c041d3ec75833ba5b0a73aaee6fedd786a79b6c9550a043
Notes SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
PQID 220490488
PQPubID 15719
PageCount 11
ParticipantIDs nrcresearch_primary_10_1139_z06_197
crossref_primary_10_1139_z06_197
gale_infotracgeneralonefile_A163465920
pascalfrancis_primary_18656795
gale_infotracmisc_A163465920
proquest_miscellaneous_19545922
gale_infotraccpiq_163465920
gale_incontextgauss_ISR_A163465920
gale_infotracacademiconefile_A163465920
gale_incontextgauss_ISN_A163465920
crossref_citationtrail_10_1139_z06_197
proquest_journals_220490488
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 20070100
2007-01-00
2007
20070101
PublicationDateYYYYMMDD 2007-01-01
PublicationDate_xml – month: 1
  year: 2007
  text: 20070100
PublicationDecade 2000
PublicationPlace Ottawa, ON
PublicationPlace_xml – name: Ottawa, ON
– name: Ottawa
PublicationTitle Canadian journal of zoology
PublicationTitleAlternate Revue canadienne de zoologie
PublicationYear 2007
Publisher National Research Council of Canada
NRC Research Press
Canadian Science Publishing NRC Research Press
Publisher_xml – name: National Research Council of Canada
– name: NRC Research Press
– name: Canadian Science Publishing NRC Research Press
References Pearce C.M. (atypb43/ref43) 1991; 44
Hansen U. (atypb25/ref24) 1991; 44
Johnson C.J. (atypb33/ref32) 2006; 70
atypb36/ref36
atypb6/ref5
Hirzel A.H. (atypb27/ref26) 2002; 83
atypb29/ref28
atypb50/ref50
Richardson E. (atypb49/ref49) 2005; 83
Edwards T.C. (atypb15/ref14) 2005; 86
atypb58/ref58
atypb5/ref4
Unander S. (atypb56/ref56) 1985; 16
atypb35/ref34
Nielsen S.E. (atypb42/ref42) 2004; 199
Dettmers R. (atypb13/ref12) 1999; 63
atypb62/ref62
atypb44/ref44
atypb46/ref46
atypb17/ref16
atypb3/ref2
atypb28/ref27
Nellemann C. (atypb39/ref39) 1995; 48
atypb40/ref40
Pettorelli N. (atypb47/ref47) 2005; 272
atypb22/ref21
atypb14/ref13
Forbes B.C. (atypb19/ref18) 1999; 18
Wang G.M. (atypb61/ref61) 2002; 23
atypb11/ref10
atypb51/ref51
atypb65/ref65
Unander S. (atypb57/ref57) 1985; 3
Eide N.E. (atypb16/ref15) 2001; 24
atypb30/ref29
atypb63/ref63
atypb52/ref52
atypb34/ref33
Johnson C.J. (atypb32/ref31) 2005; 160
Steen J.B. (atypb55/ref55) 1985; 16
atypb9/ref8
atypb23/ref22
Buckland S.T. (atypb7/ref6) 1993; 30
atypb38/ref38
atypb12/ref11
atypb66/ref66
atypb2/ref1
atypb8/ref7
atypb41/ref41
atypb1/ref111
Cotter R.C. (atypb10/ref9) 1999; 52
atypb20/ref19
atypb4/ref3
atypb24/ref23
atypb26/ref25
atypb64/ref64
atypb37/ref37
Gould W. (atypb21/ref20) 2000; 10
atypb53/ref53
atypb31/ref30
atypb48/ref48
Ferguson R.S. (atypb18/ref17) 1991; 44
atypb60/ref60
Simpson E.H. (atypb54/ref54) 1949; 163
atypb59/ref59
atypb45/ref45
References_xml – ident: atypb23/ref22
  doi: 10.1016/S0304-3800(00)00354-9
– volume: 160
  start-page: 1
  year: 2005
  ident: atypb32/ref31
  publication-title: Wildl. Monogr.
  doi: 10.2193/0084-0173(2005)160[1:CEOHDO]2.0.CO;2
– ident: atypb1/ref111
– ident: atypb24/ref23
  doi: 10.1111/j.1523-1739.2006.00354.x
– ident: atypb36/ref36
– volume: 16
  start-page: 198
  year: 1985
  ident: atypb56/ref56
  publication-title: Ornis Scand.
  doi: 10.2307/3676631
– volume: 272
  start-page: 2357
  year: 2005
  ident: atypb47/ref47
  publication-title: Proc. R. Soc. Biol. Sci.
  doi: 10.1098/rspb.2005.3218
– ident: atypb41/ref41
  doi: 10.1046/j.1365-2656.1999.00351.x
– ident: atypb26/ref25
  doi: 10.1007/978-1-4757-3462-1
– volume: 3
  start-page: 239
  year: 1985
  ident: atypb57/ref57
  publication-title: Polar Res.
  doi: 10.1111/j.1751-8369.1985.tb00510.x
– volume: 44
  start-page: 49
  year: 1991
  ident: atypb43/ref43
  publication-title: Arctic
  doi: 10.14430/arctic1570
– ident: atypb51/ref51
  doi: 10.1046/j.1365-2664.2002.00700.x
– ident: atypb45/ref45
– volume: 23
  start-page: 81
  year: 2002
  ident: atypb61/ref61
  publication-title: Clim. Res.
  doi: 10.3354/cr023081
– ident: atypb52/ref52
  doi: 10.1007/s10584-005-9017-y
– volume: 83
  start-page: 2027
  year: 2002
  ident: atypb27/ref26
  publication-title: Ecology
  doi: 10.1890/0012-9658(2002)083[2027:ENFAHT]2.0.CO;2
– ident: atypb4/ref3
  doi: 10.1016/S0169-5347(99)01593-1
– volume: 30
  start-page: 478
  year: 1993
  ident: atypb7/ref6
  publication-title: J. Appl. Ecol.
  doi: 10.2307/2404188
– ident: atypb34/ref33
  doi: 10.1111/j.0021-8901.2004.00899.x
– ident: atypb2/ref1
– ident: atypb17/ref16
– ident: atypb28/ref27
– ident: atypb12/ref11
  doi: 10.1016/0034-4257(95)00142-5
– ident: atypb9/ref8
– volume: 10
  start-page: 1861
  year: 2000
  ident: atypb21/ref20
  publication-title: Ecol. Appl.
  doi: 10.1890/1051-0761(2000)010[1861:RSOVPS]2.0.CO;2
– ident: atypb65/ref65
  doi: 10.1016/S0169-5347(01)02205-4
– ident: atypb29/ref28
  doi: 10.1139/z02-023
– volume: 63
  start-page: 815
  year: 1999
  ident: atypb13/ref12
  publication-title: J. Wildl. Manag.
  doi: 10.2307/3802794
– ident: atypb38/ref38
– volume: 18
  start-page: 367
  year: 1999
  ident: atypb19/ref18
  publication-title: Polar Res.
  doi: 10.3402/polar.v18i2.6597
– ident: atypb40/ref40
  doi: 10.2307/1552148
– ident: atypb11/ref10
  doi: 10.1080/01431160110113890
– ident: atypb66/ref66
  doi: 10.1111/j.1523-1739.2005.00148.x
– volume: 44
  start-page: 66
  year: 1991
  ident: atypb18/ref17
  publication-title: Arctic
  doi: 10.14430/arctic1572
– ident: atypb37/ref37
  doi: 10.1111/j.1365-2664.2005.01098.x
– ident: atypb14/ref13
  doi: 10.1007/s10750-006-0042-2
– ident: atypb62/ref62
  doi: 10.2307/177101
– volume: 83
  start-page: 860
  year: 2005
  ident: atypb49/ref49
  publication-title: Can. J. Zool.
  doi: 10.1139/z05-075
– volume: 44
  start-page: 94
  year: 1991
  ident: atypb25/ref24
  publication-title: Arctic
  doi: 10.14430/arctic1575
– volume: 70
  start-page: 347
  year: 2006
  ident: atypb33/ref32
  publication-title: J. Wildl. Manag.
  doi: 10.2193/0022-541X(2006)70[347:RSFBOU]2.0.CO;2
– ident: atypb20/ref19
– ident: atypb44/ref44
  doi: 10.1016/S0304-3800(00)00322-7
– ident: atypb53/ref53
  doi: 10.1080/0143116042000192358
– ident: atypb59/ref59
  doi: 10.1080/01431160110113854
– ident: atypb35/ref34
  doi: 10.1023/A:1021354914494
– volume: 48
  start-page: 172
  year: 1995
  ident: atypb39/ref39
  publication-title: Arctic
  doi: 10.14430/arctic1239
– volume: 52
  start-page: 23
  year: 1999
  ident: atypb10/ref9
  publication-title: Arctic
  doi: 10.14430/arctic906
– ident: atypb64/ref64
  doi: 10.1201/9781420010404
– volume: 24
  start-page: 132
  year: 2001
  ident: atypb16/ref15
  publication-title: Polar Biol.
  doi: 10.1007/s003000000188
– ident: atypb30/ref29
  doi: 10.1007/s10531-004-0444-2
– ident: atypb46/ref46
  doi: 10.1016/j.tree.2005.05.011
– ident: atypb58/ref58
  doi: 10.1007/978-1-4757-3121-7
– ident: atypb50/ref50
– ident: atypb31/ref30
  doi: 10.1029/2003GL018268
– volume: 163
  start-page: 688
  year: 1949
  ident: atypb54/ref54
  publication-title: Nature (London)
  doi: 10.1038/163688a0
– ident: atypb8/ref7
  doi: 10.1177/0049124104268644
– ident: atypb63/ref63
  doi: 10.1676/04-036.1
– ident: atypb3/ref2
  doi: 10.1016/S0304-3800(02)00205-3
– volume: 199
  start-page: 51
  year: 2004
  ident: atypb42/ref42
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2004.04.014
– ident: atypb60/ref60
  doi: 10.1029/2001JD000986
– volume: 16
  start-page: 191
  year: 1985
  ident: atypb55/ref55
  publication-title: Ornis Scand.
  doi: 10.2307/3676630
– ident: atypb48/ref48
– volume: 86
  start-page: 1081
  year: 2005
  ident: atypb15/ref14
  publication-title: Ecology
  doi: 10.1890/04-0608
– ident: atypb6/ref5
  doi: 10.1007/BF00292508
– ident: atypb22/ref21
  doi: 10.1111/j.1461-0248.2005.00792.x
– ident: atypb5/ref4
  doi: 10.1016/S0304-3800(02)00200-4
SSID ssj0006710
Score 1.8753233
Snippet Predictive habitat models have become important research and management tools for monitoring the spatial distribution and abundance of wildlife species. In...
SourceID proquest
gale
pascalfrancis
crossref
nrcresearch
SourceType Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 122
SubjectTerms Animal and plant ecology
Animal behavior
Animal populations
Animal, plant and microbial ecology
Animals
Aves
Behavior
Biological and medical sciences
Data collection
Demecology
Environmental conditions
Environmental protection
Factor analysis
Field study
Fundamental and applied biological sciences. Psychology
Habitat selection
Habitats
Heterogeneity
Lagopus
Management tools
Ptarmigans
Rocks
Spatial distribution
Vegetation cover
Vertebrata
Wildlife
Wildlife management
Title Ecological correlates of the distribution of territorial Svalbard rock ptarmigan (Lagopus muta hyperborea)
URI http://www.nrcresearchpress.com/doi/abs/10.1139/z06-197
https://www.proquest.com/docview/220490488
https://www.proquest.com/docview/19545922
Volume 85
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1Lb9QwELagFRIcUHmpS8tiASpwiJqHEyenqq22KgitUEulFRfL8WMLlCTdJBd-PTOJd9moLdedz1k_xuOxPf6GkHeB0lEah8qTWkmPhTbyUmsCj-PqHUSpz3QXIDtNTi_Y51k8c7E5tQurXNrEzlDrUuEZ-X4Y4h0VqNtBde1h0ii8XHUZNO6TTWQuw4guPlvtt8AO92QELAVTA8to_2Y2AJ9n_w9mn0Gip7XFyJnkR8VCOaKdS4yUlDV0lu2zXNww2N0qdLJFHjv3kR724_2E3DPFU_Lge9kdjj8jPydqacyowrwbV-hK0tJS8POoRpJcl9-q-w1ZGZEkBNDnoHE5aAuFBe0XrRoJCjCXBf3wBROltDX93TaSXsKudQFaY-TH5-TiZPLt-NRz2RQ8FfOs8ZKccZPFcR5yC8MRhlz5LNCRURxfXuUyzn3JIymNSazRmqeJ5FmeKCjjS59FL8hGURZmm9DIREwrKMi1YRKjFLWRuJWMrdQ2YyOyt-xWoRzVOGa8uBLdliPKBPS_gP4fEboCVj27xk3IGxwXgVwVBQbDzGVb1-LT-VQcgi_J8FrYvxN0NgC9dyBbQm2UdA8QoE3IgTVA7gyQqvpxLdakewPpvOcHv-0zuwMgTFw1EL9dU7W72__6NpSTikrbERkPlPTfl1Jw1nkWQ3OWWiucharFaj7BH6ykWEMMuitM2dYCyQChouHL_5bfIQ_78248ltolG82iNa_AUWvycTcdx2TzaDL9evYXJT0_Xg
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLZGJ8R4QFy1srFZXMZ4iJYmTpw8IDSgU8tKhXaRJl6MYzsdMJKuaYXgP_EfOSdxSqNtvO2159j15eRc7OPvEPK8o7QfBZ5ypFbSYV7qO1FqOg5H693xI5fpMkF2GPaO2YeT4GSJ_KnfwmBaZa0TS0Wtc4Vn5Dueh3dUIG5vxucOFo3Cy9W6gkYlFfvm10-I2IrX_fewvS88b6979K7n2KICjgp4PHXChHETB0Hi8RRG5XlcuayjfaM4PkBKZJC4kvtSGhOmRmsehZLHSaigjStd5kO_N8gy8yGSaZHlt93hp4O56g95BX_AIlBuYLirV7od8LJ2fmO9G4SWWjB_1gjczibKQvucYm6mLGB70qquxgUTUdq9vbvkjnVY6W4lYffIksnuk5uf8_I4_gH51lW1-qQKK32cofNK85SCZ0k1wvLailrlb4gDibAkwH0IMp6AfFIwod_peCpB5EYyo9sDLM0yK-iP2VTSU4iTJyCnRr56SI6vZakfkVaWZ2aVUN_4TCtoyLVhEvMitZEYvAap1GnM2mSrXlahLLg51tg4E2WQ48cC1l_A-rcJnTOOKzyPiyxPcV8EomNkmH4zkrOiEP3DodgF75XhRbR7JdNBg-mlZUpzGI2S9skDzAlRtxqcaw1ONf56LhaoWw3qqEIkv6yb9QYjqArVID9bELWr5795GZelirFO22SjIaT_eoogPOBxANOppVZYnViI-RcMfzCn4ggxzS8z-awQCD8IA_Ue_7f9JrnVO_o4EIP-cH-NrFSn7Xgotk5a08nMPAE3cZps2I-Tki_XrQ_-AkkZfK0
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLbGEAgeEFdRNjaLy4CHqLk4dfKA0MRWrWyqEGNStRfj-NIBI-maVgj-Gf-OcxKnNNrG217jY8eX43Oxj79DyItA6SiJQ-VJraTHQht5iTWBx1F7B1HiM10FyA57e0fswygerZA_zVsYDKtsZGIlqHWh8Iy8G4Z4RwXs1rUuKuLjTv_d5MzDBFJ40dpk06g5ZN_8-gneW_l2sANL_TIM-7uf3-95LsGAp2KezrxexrhJ4zgLuYUehiFXPgt0ZBTHx0iZjDNf8khKY3rWaM2TnuRp1lNQx5c-i6Dda-Q6j-IAtxgfLXw90AE1EAJLQMyBCq_f6wZgb3V_Y-YbBJlaUoROHdzOp8qB_JxglKYsYaFsnWHjnLKoNGD_LrnjTFe6XfPaPbJi8vvkxnFRHcw_IN92VSNIqcKcH6doxtLCUrAxqUaAXpdbq_qGiJAIUALUh8DtGXAqBWX6nU5mEphvLHP6-gCTtMxL-mM-k_QEPOYpcKyRbx6SoyuZ6EdkNS9y85jQyERMK6jItWESIyS1kejGxlZqm7IO2WqmVSgHc47ZNk5F5e5EqYD5FzD_HUIXhJMa2eM8yTNcF4E4GTmy3FjOy1IMDodiG-xYhlfS_qVEn1pErxyRLaA3SrrHDzAmxN9qUa61KNXk65lYKt1qlY5rbPKLmllvEYLQUK3i50usdvn4Ny-icqViom2HbLSY9F9LCTgKPI1hOA3XCicdS7HYy_CDRSn2EAP-clPMS4FAhNDR8Ml_62-SmyAFxMFguL9GbtXH7ng6tk5WZ9O5eQr24izbqHYmJV-uWhT8BZf4f30
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Ecological+correlates+of+the+distribution+of+territorial+Svalbard+rock+ptarmigan+%28Lagopus+muta+hyperborea%29&rft.jtitle=Canadian+journal+of+zoology&rft.au=PEDERSEN%2C+A.+%C3%98&rft.au=JEPSEN%2C+J.+U&rft.au=YOCCOZ%2C+N.+G&rft.au=FUGLEI%2C+E&rft.date=2007&rft.pub=National+Research+Council+of+Canada&rft.issn=0008-4301&rft.volume=85&rft.issue=1&rft.spage=122&rft.epage=132&rft_id=info:doi/10.1139%2Fz06-197&rft.externalDBID=n%2Fa&rft.externalDocID=18656795
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0008-4301&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0008-4301&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0008-4301&client=summon