Inference about density and temporary emigration in unmarked populations

Few species are distributed uniformly in space, and populations of mobile organisms are rarely closed with respect to movement, yet many models of density rely upon these assumptions. We present a hierarchical model allowing inference about the density of unmarked populations subject to temporary em...

Full description

Saved in:
Bibliographic Details
Published inEcology (Durham) Vol. 92; no. 7; pp. 1429 - 1435
Main Authors Chandler, Richard B, J. Andrew Royle, David I. King
Format Journal Article
LanguageEnglish
Published United States Ecological Society of America 01.07.2011
Subjects
Online AccessGet more information
ISSN0012-9658
1939-9170
DOI10.1890/10-2433.1

Cover

Loading…
Abstract Few species are distributed uniformly in space, and populations of mobile organisms are rarely closed with respect to movement, yet many models of density rely upon these assumptions. We present a hierarchical model allowing inference about the density of unmarked populations subject to temporary emigration and imperfect detection. The model can be fit to data collected using a variety of standard survey methods such as repeated point counts in which removal sampling, double‐observer sampling, or distance sampling is used during each count. Simulation studies demonstrated that parameter estimators are unbiased when temporary emigration is either “completely random” or is determined by the size and location of home ranges relative to survey points. We also applied the model to repeated removal sampling data collected on Chestnut‐sided Warblers (Dendroica pensylvancia) in the White Mountain National Forest, USA. The density estimate from our model, 1.09 birds/ha, was similar to an estimate of 1.11 birds/ha produced by an intensive spot‐mapping effort. Our model is also applicable when processes other than temporary emigration affect the probability of being available for detection, such as in studies using cue counts. Functions to implement the model have been added to the R package unmarked.
AbstractList Few species are distributed uniformly in space, and populations of mobile organisms are rarely closed with respect to movement, yet many models of density rely upon these assumptions. We present a hierarchical model allowing inference about the density of unmarked populations subject to temporary emigration and imperfect detection. The model can be fit to data collected using a variety of standard survey methods such as repeated point counts in which removal sampling, double-observer sampling, or distance sampling is used during each count. Simulation studies demonstrated that parameter estimators are unbiased when temporary emigration is either "completely random" or is determined by the size and location of home ranges relative to survey points. We also applied the model to repeated removal sampling data collected on Chestnut-sided Warblers (Dendroica pensylvancia) in the White Mountain National Forest, U.S.A. The density estimate from our model, 1.09 birds/ha, was similar to an estimate of 1.11 birds/ha produced by an intensive spot-mapping effort. Our model is also applicable when processes other than temporary emigration affect the probability of being available for detection, such as in studies using cue counts. Functions to implement the model have been added to the R package unmarked.
Few species are distributed uniformly in space, and populations of mobile organisms are rarely closed with respect to movement, yet many models of density rely upon these assumptions. We present a hierarchical model allowing inference about the density of unmarked populations subject to temporary emigration and imperfect detection. The model can be fit to data collected using a variety of standard survey methods such as repeated point counts in which removal sampling, double‐observer sampling, or distance sampling is used during each count. Simulation studies demonstrated that parameter estimators are unbiased when temporary emigration is either “completely random” or is determined by the size and location of home ranges relative to survey points. We also applied the model to repeated removal sampling data collected on Chestnut‐sided Warblers (Dendroica pensylvancia) in the White Mountain National Forest, USA. The density estimate from our model, 1.09 birds/ha, was similar to an estimate of 1.11 birds/ha produced by an intensive spot‐mapping effort. Our model is also applicable when processes other than temporary emigration affect the probability of being available for detection, such as in studies using cue counts. Functions to implement the model have been added to the R package unmarked.
Author Chandler, Richard B
David I. King
J. Andrew Royle
Author_xml – sequence: 1
  fullname: Chandler, Richard B
– sequence: 2
  fullname: J. Andrew Royle
– sequence: 3
  fullname: David I. King
BackLink https://www.ncbi.nlm.nih.gov/pubmed/21870617$$D View this record in MEDLINE/PubMed
BookMark eNo1j81Kw0AUhQep2B9d-AI6L5A6_5lZSlFbKLjQrsNN56ZEm0mYSRZ5e4PVuzlw-Ticb0lmoQ1IyD1na24de-IsE0rKNb8iC-6kyxzP2YwsGOMic0bbOVmm9MWm48rekLngNmeG5wuy3YUKI4YjUijboaceQ6r7kULwtMemayPEkWJTnyL0dRtoHegQGojf6GnXdsP5951uyXUF54R3f7kih9eXz80227-_7TbP-wyM1i4z3kovpGeVFcq6EkAwgzmIXJbg80oprY12GhWvrEd5dF5NbjhBJUphxYo8XHq7oWzQF12spzFj8a80AY8XoIK2gFOsU3H4EIybSd4Zp634Ab1dV6E
CitedBy_id crossref_primary_10_1002_jwmg_615
crossref_primary_10_1371_journal_pone_0224438
crossref_primary_10_1016_j_ecolind_2019_105546
crossref_primary_10_1016_j_gecco_2020_e01128
crossref_primary_10_1371_journal_pone_0130153
crossref_primary_10_1002_eap_2632
crossref_primary_10_1214_12_AOAS610
crossref_primary_10_1002_ecs2_3815
crossref_primary_10_1002_eap_1549
crossref_primary_10_1016_j_gecco_2019_e00780
crossref_primary_10_1038_srep35920
crossref_primary_10_3389_fevo_2023_1250785
crossref_primary_10_1016_j_agee_2017_03_022
crossref_primary_10_1080_01584197_2017_1401903
crossref_primary_10_1111_ddi_12968
crossref_primary_10_1371_journal_pone_0094406
crossref_primary_10_1371_journal_pone_0152977
crossref_primary_10_1007_s13157_018_1082_x
crossref_primary_10_1002_ecy_3204
crossref_primary_10_3389_fevo_2021_643845
crossref_primary_10_1038_s41598_020_62661_0
crossref_primary_10_1371_journal_pone_0252231
crossref_primary_10_1642_AUK_17_181_1
crossref_primary_10_1007_s10531_012_0244_z
crossref_primary_10_1002_ecs2_2334
crossref_primary_10_1002_env_1149
crossref_primary_10_7717_peerj_17889
crossref_primary_10_1214_14_AOAS801
crossref_primary_10_1111_1365_2664_13529
crossref_primary_10_1111_ddi_12456
crossref_primary_10_1111_geb_12216
crossref_primary_10_1071_WR19232
crossref_primary_10_1016_j_scitotenv_2021_149406
crossref_primary_10_1111_acv_12264
crossref_primary_10_1650_CONDOR_15_28_1
crossref_primary_10_1038_s41598_021_84010_5
crossref_primary_10_1080_02755947_2016_1254127
crossref_primary_10_1111_2041_210X_12518
crossref_primary_10_1675_063_037_0306
crossref_primary_10_1214_24_AOAS1911
crossref_primary_10_1371_journal_pone_0117216
crossref_primary_10_1371_journal_pone_0229965
crossref_primary_10_1371_journal_pntd_0008367
crossref_primary_10_3390_rs12010038
crossref_primary_10_1017_S0959270924000066
crossref_primary_10_1002_jwmg_22701
crossref_primary_10_1002_jwmg_21970
crossref_primary_10_1670_21_016
crossref_primary_10_1111_1365_2664_13053
crossref_primary_10_1371_journal_pone_0118330
crossref_primary_10_1002_ecs2_2791
crossref_primary_10_1525_auk_2012_11093
crossref_primary_10_1650_CONDOR_13_085_1
crossref_primary_10_1007_s00267_017_0837_0
crossref_primary_10_1111_2041_210X_13570
crossref_primary_10_1016_j_ecolmodel_2018_02_007
crossref_primary_10_1007_s10531_023_02553_7
crossref_primary_10_1017_S0959270916000277
crossref_primary_10_1002_ece3_4780
crossref_primary_10_1007_s10531_018_1529_7
crossref_primary_10_1890_15_0385_1
crossref_primary_10_24072_pcjournal_528
crossref_primary_10_1016_j_biocon_2013_12_028
crossref_primary_10_1080_15230430_2021_1994103
crossref_primary_10_1002_wsb_1060
crossref_primary_10_3389_fevo_2021_665792
crossref_primary_10_1080_19425120_2014_982334
crossref_primary_10_1002_jwmg_21450
crossref_primary_10_1071_WF13062
crossref_primary_10_3390_f10020084
crossref_primary_10_1016_j_mambio_2017_08_001
crossref_primary_10_1890_11_1400_1
crossref_primary_10_1670_14_075
crossref_primary_10_1002_ecs2_2028
crossref_primary_10_1016_j_ecolind_2021_108170
crossref_primary_10_1111_2041_210X_13192
crossref_primary_10_1890_14_0959_1
crossref_primary_10_1002_jwmg_499
crossref_primary_10_1016_j_ecolmodel_2016_08_012
crossref_primary_10_1002_wmon_1070
crossref_primary_10_1007_s10531_020_02006_5
crossref_primary_10_1177_1940082918754777
crossref_primary_10_1016_j_avrs_2023_100080
crossref_primary_10_1111_ecog_06581
crossref_primary_10_1002_ecs2_3067
crossref_primary_10_1017_S0959270921000368
crossref_primary_10_1111_jofo_12116
crossref_primary_10_1676_16_108_1
crossref_primary_10_1002_ecs2_4954
crossref_primary_10_1650_CONDOR_14_108_1
crossref_primary_10_1002_ecy_4292
crossref_primary_10_1002_ecs2_3725
crossref_primary_10_1002_eap_1692
crossref_primary_10_1002_ece3_9173
crossref_primary_10_7717_peerj_5827
crossref_primary_10_1371_journal_pone_0164755
crossref_primary_10_1371_journal_pone_0062326
crossref_primary_10_1016_j_biocon_2016_04_002
crossref_primary_10_1111_ddi_12932
crossref_primary_10_1016_j_ecoinf_2022_101629
crossref_primary_10_1371_journal_pone_0302040
crossref_primary_10_1002_jwmg_943
crossref_primary_10_1016_j_ecolmodel_2020_108965
crossref_primary_10_1038_s41598_017_18343_5
crossref_primary_10_1111_jofo_12066
crossref_primary_10_1371_journal_pone_0281535
crossref_primary_10_1002_wmon_1083
crossref_primary_10_1038_s41598_023_43184_w
crossref_primary_10_1111_2041_210X_12432
crossref_primary_10_1111_evo_12037
crossref_primary_10_1017_S0030605318001515
crossref_primary_10_1656_045_031_0315
crossref_primary_10_1111_nrm_12024
crossref_primary_10_1111_ele_13729
crossref_primary_10_1002_ecs2_2402
crossref_primary_10_1111_2041_210X_14332
crossref_primary_10_1111_2041_210X_13881
crossref_primary_10_1007_s10651_021_00510_7
crossref_primary_10_1093_jme_tjz018
crossref_primary_10_1111_2041_210X_14296
crossref_primary_10_1093_ornithapp_duab054
crossref_primary_10_1007_s13253_023_00598_3
crossref_primary_10_1371_journal_pone_0319351
crossref_primary_10_1002_eap_2455
crossref_primary_10_1002_wlb3_01017
crossref_primary_10_1038_s41598_021_01518_6
crossref_primary_10_1371_journal_pone_0151033
crossref_primary_10_1002_jwmg_22622
crossref_primary_10_1002_jwmg_1022
crossref_primary_10_1111_biom_12961
crossref_primary_10_1093_condor_duy023
crossref_primary_10_1111_2041_210X_12601
crossref_primary_10_1080_01584197_2020_1773859
crossref_primary_10_1098_rsos_150561
crossref_primary_10_1111_2041_210X_12840
crossref_primary_10_1139_cjfas_2023_0373
crossref_primary_10_1002_wics_1625
crossref_primary_10_1890_ES12_00034_1
crossref_primary_10_1016_j_scitotenv_2018_06_107
crossref_primary_10_1017_S0959270915000088
crossref_primary_10_51492_cfwj_110_13
crossref_primary_10_61350_sbj_33_74
crossref_primary_10_1002_jwmg_21249
crossref_primary_10_1002_ece3_6522
crossref_primary_10_1093_jmammal_gyz017
crossref_primary_10_1163_15685306_bja10097
crossref_primary_10_1650_CONDOR_15_217_1
crossref_primary_10_1016_j_biocon_2024_110474
crossref_primary_10_1675_063_042_0203
crossref_primary_10_1111_aec_13516
crossref_primary_10_1002_jwmg_21094
crossref_primary_10_1016_j_foreco_2023_121147
crossref_primary_10_1111_1365_2664_12610
crossref_primary_10_1111_2041_210X_12333
crossref_primary_10_1111_2041_210X_13026
crossref_primary_10_1111_ecog_07560
crossref_primary_10_1650_CONDOR_13_072_1
crossref_primary_10_1016_j_biocon_2024_110914
crossref_primary_10_1016_j_foreco_2021_119708
crossref_primary_10_1002_ecs2_3953
crossref_primary_10_1111_ddi_12790
crossref_primary_10_1111_2041_210X_12572
crossref_primary_10_1002_ecs2_2586
crossref_primary_10_1007_s10336_024_02151_6
crossref_primary_10_2981_wlb_00287
ContentType Journal Article
DBID FBQ
CGR
CUY
CVF
ECM
EIF
NPM
DOI 10.1890/10-2433.1
DatabaseName AGRIS
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
DatabaseTitle MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
DatabaseTitleList MEDLINE

Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
– sequence: 3
  dbid: FBQ
  name: AGRIS
  url: http://www.fao.org/agris/Centre.asp?Menu_1ID=DB&Menu_2ID=DB1&Language=EN&Content=http://www.fao.org/agris/search?Language=EN
  sourceTypes: Publisher
DeliveryMethod no_fulltext_linktorsrc
Discipline Biology
Ecology
Environmental Sciences
EISSN 1939-9170
EndPage 1435
ExternalDocumentID 21870617
US201600196958
Genre Research Support, U.S. Gov't, Non-P.H.S
Research Support, Non-U.S. Gov't
Journal Article
GeographicLocations White Mountain National Forest
United States
GeographicLocations_xml – name: White Mountain National Forest
– name: United States
GroupedDBID ---
-~X
.-4
0R~
0VX
1OB
1OC
29G
2AX
2KS
33P
3V.
4.4
42X
53G
5GY
692
6TJ
7X2
7X7
7XC
85S
88A
88E
88I
8CJ
8FE
8FH
8FI
8FJ
8G5
8R4
8R5
8WZ
A.K
A6W
AAESR
AAFWJ
AAHHS
AAHKG
AAIHA
AAISJ
AAJUZ
AAKGQ
AANLZ
AASGY
AAXRX
AAZKR
ABBHK
ABCUV
ABCVL
ABEFU
ABGFU
ABJNI
ABLJU
ABPFR
ABPLY
ABPPZ
ABPTK
ABRJW
ABTLG
ABUWG
ABYAD
ACAHQ
ACCFJ
ACCZN
ACGFO
ACGFS
ACGOD
ACKIV
ACKOT
ACNCT
ACPOU
ACPRK
ACSMX
ACSTJ
ACTWD
ACUBG
ACXBN
ACXQS
ADBBV
ADDAD
ADKYN
ADOZA
ADULT
ADXAS
ADZLD
ADZMN
ADZOD
AEEZP
AEGXH
AEIGN
AENEX
AEQDE
AESBF
AEUPB
AEUQT
AEUYR
AFAZZ
AFBPY
AFDAS
AFFPM
AFKRA
AFMIJ
AFRAH
AFXHP
AFZJQ
AGNAY
AGUYK
AIAGR
AIDAL
AIHXQ
AIURR
AIWBW
AJBDE
ALMA_UNASSIGNED_HOLDINGS
ALUQN
AMYDB
AS~
ATCPS
AZFZN
AZQEC
AZVAB
B-7
BBNVY
BCR
BCU
BEC
BENPR
BES
BFHJK
BHPHI
BKOMP
BKSAR
BLC
BMXJE
BPHCQ
BRXPI
BVXVI
C1A
CBGCD
CCPQU
CS3
CUYZI
CWIXF
D0L
D1J
DCZOG
DDYGU
DEVKO
DOOOF
DRFUL
DRSTM
DU5
DWIUU
DWQXO
E.L
EBS
ECGQY
EJD
F5P
FBQ
FVMVE
FYUFA
GNUQQ
GTFYD
GUQSH
HCIFZ
HF~
HGD
HMCUK
HQ2
HTVGU
HVGLF
IAG
IAO
IEA
IEP
IGH
IGS
IOF
IPO
ITC
JAAYA
JAS
JBMMH
JBS
JBZCM
JEB
JENOY
JHFFW
JKQEH
JLEZI
JLS
JLXEF
JPL
JPM
JSODD
JST
KQ8
LATKE
LEEKS
LITHE
LK8
LOXES
LU7
LUTES
LYRES
M0K
M0L
M1P
M2O
M2P
M7P
MEWTI
MV1
MVM
MW2
N9A
NHB
NXSMM
O9-
OK1
OMK
P2P
P2W
PALCI
PATMY
PCBAR
PQQKQ
PRG
PROAC
PSQYO
PYCSY
Q2X
QZG
R05
RJQFR
ROL
RSZ
RWL
RXW
SA0
SAMSI
SJFOW
SJN
SUPJJ
TAE
TN5
U5U
UBC
UHB
UKHRP
UKR
V62
VOH
VQA
WBKPD
WH7
WHG
WOHZO
WXSBR
WYJ
XIH
XSW
Y6R
YR2
YV5
YXE
YYM
YYP
YZZ
Z0I
ZCA
ZCG
ZO4
ZZTAW
~02
~KM
AAHBH
AAHQN
AAMNL
AAYCA
ABDQB
ABPQH
ABXSQ
ACHIC
ADMHG
AEUYN
AFQQW
AFWVQ
AHBTC
AHXOZ
AILXY
AITYG
ALIPV
ALVPJ
AQVQM
CGR
CUY
CVF
ECM
EIF
HGLYW
IPSME
NPM
VXZ
YIN
Z5M
ID FETCH-LOGICAL-a6559-6d83d23d0f82489baa206e7a273bad7f44556595e41f8de3c9d4243e06ebe3282
ISSN 0012-9658
IngestDate Wed Feb 19 02:36:34 EST 2025
Wed Dec 27 19:00:21 EST 2023
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 7
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-a6559-6d83d23d0f82489baa206e7a273bad7f44556595e41f8de3c9d4243e06ebe3282
Notes http://dx.doi.org/10.1890/10-2433.1
OpenAccessLink https://onlinelibrary.wiley.com/doi/pdfdirect/10.1890/10-2433.1
PMID 21870617
PageCount 7
ParticipantIDs pubmed_primary_21870617
fao_agris_US201600196958
PublicationCentury 2000
PublicationDate July 2011
PublicationDateYYYYMMDD 2011-07-01
PublicationDate_xml – month: 07
  year: 2011
  text: July 2011
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
PublicationTitle Ecology (Durham)
PublicationTitleAlternate Ecology
PublicationYear 2011
Publisher Ecological Society of America
Publisher_xml – name: Ecological Society of America
References Ecology. 2014 Mar;95(3):794
References_xml – reference: - Ecology. 2014 Mar;95(3):794
SSID ssj0000148
Score 2.457821
Snippet Few species are distributed uniformly in space, and populations of mobile organisms are rarely closed with respect to movement, yet many models of density rely...
SourceID pubmed
fao
SourceType Index Database
Publisher
StartPage 1429
SubjectTerms Animal Migration - physiology
Animals
birds
Computer Simulation
Ecosystem
home range
Models, Biological
Passeriformes - physiology
Population Density
probability
surveys
Time Factors
Title Inference about density and temporary emigration in unmarked populations
URI https://www.ncbi.nlm.nih.gov/pubmed/21870617
Volume 92
hasFullText
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT9wwELa6rZC4oELLq4B84LYKJH7kcaQ8tEVqJQQrcVvZsY32sGEFy4H--o4fSVwKAnpJotixvP4mzszszDcI7QtSpFJonjCdVwkT2iRVKmvrEigzariRxOY7__yVj8bs_Jpf91VRXXbJQh7Uv5_NK_kfVOEe4GqzZN-BbDco3IBrwBeOgDAc34TxjzZbL8QXKxuNvvCMSj3nlJ5NbwLO02b40MxsRI4azrvSXfd_uedrz8oEmufJw53Lou58Bceek-EuysgfRn_ZPPrQ5PM4SjIqm-LC54OXVvWO06L1M4S9MyOJpYqJ986KRDJSRBthxvzk_tmhyyp1zoKEMEoPsrgPLO585qACvaOwutXrrU_IstumARqA2WDroFrnTccmxsKH2f-QQDQFMzrs5uPIof0YoG0YcfvE3HBqx9VntBLsBXzkwV9FH3SzhpZ8BdFHuApwraH10z5lER4Ie_b9FzTqpAQ7KcFBSjBgiTspwb2U4GmDWynBkZR8ReOz06vjURLqZyQiB0MxyVVJFaEqNSVhZSWFIGmuC3g9qRSqMIxxbukkNctMqTStK8VgFTR0kpqCLb6OPja3jd5EWIIeZwfjVW6gj4RTKkTNcq4N1yXdQpuwVhNxA1-myfiSWN5Cx7zEyy204RdwMvf8KZN2gbdfbPmGll3QpHN17aBPBl5YvQva30LuocHZ94s9h-wfpjVV1w
linkProvider National Library of Medicine
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=Inference+about+density+and+temporary+emigration+in+unmarked+populations&rft.jtitle=Ecology+%28Durham%29&rft.au=Chandler%2C+Richard+B&rft.au=Royle%2C+J+Andrew&rft.au=King%2C+David+I&rft.date=2011-07-01&rft.issn=0012-9658&rft.volume=92&rft.issue=7&rft.spage=1429&rft_id=info:doi/10.1890%2F10-2433.1&rft_id=info%3Apmid%2F21870617&rft_id=info%3Apmid%2F21870617&rft.externalDocID=21870617
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0012-9658&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0012-9658&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0012-9658&client=summon