Modeling avian full annual cycle distribution and population trends with citizen science data

Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range-wide extents for two main reasons. First, landscape-scale process...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Ecological applications Ročník 30; číslo 3; s. 1 - 16
Hlavní autori:	Fink, Daniel, Auer, Tom, Johnston, Alison, Ruiz-Gutierrez, Viviana, Hochachka, Wesley M., Kelling, Steve
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States John Wiley and Sons, Inc 01.04.2020 Ecological Society of America John Wiley and Sons Inc
Predmet:	Abundance Animal breeding Animal populations area of occurrence biodiversity monitoring bird distributions bird migration birds Breeding seasons citizen science Conservation Data collection eBird full annual cycle Hylocichla mustelina Landscape landscapes Modelling Neotropics population trends Populations Seasons Species surveys Trends Wildlife conservation Wood Thrush eBird bird distributions biodiversity monitoring population trends abundance citizen science full annual cycle area of occurrence bird migration Wood Thrush
ISSN:	1051-0761, 1939-5582
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Abstract	Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range-wide extents for two main reasons. First, landscape-scale processes that affect populations vary throughout the year and across species’ ranges, requiring high-resolution, year-round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long-distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra-annual estimates of the range, intraannual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non-breeding seasons. The range-wide population trajectories for Wood Thrush show a close correspondence between breeding and nonbreeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range-wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non-breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra- and interannual distributional dynamics for broadly distributed, highly mobile species.
AbstractList	Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range‐wide extents for two main reasons. First, landscape‐scale processes that affect populations vary throughout the year and across species’ ranges, requiring high‐resolution, year‐round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year‐round, range‐wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long‐distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra‐annual estimates of the range, intra‐annual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non‐breeding seasons. The range‐wide population trajectories for Wood Thrush show a close correspondence between breeding and non‐breeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range‐wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non‐breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra‐ and interannual distributional dynamics for broadly distributed, highly mobile species. Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range‐wide extents for two main reasons. First, landscape‐scale processes that affect populations vary throughout the year and across species’ ranges, requiring high‐resolution, year‐round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year‐round, range‐wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush ( Hylocichla mustelina ), a long‐distance Neotropical migrant and species of conservation concern, using data from the citizen science project eB ird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra‐annual estimates of the range, intra‐annual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non‐breeding seasons. The range‐wide population trajectories for Wood Thrush show a close correspondence between breeding and non‐breeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range‐wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non‐breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra‐ and interannual distributional dynamics for broadly distributed, highly mobile species. Information on species' distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range-wide extents for two main reasons. First, landscape-scale processes that affect populations vary throughout the year and across species' ranges, requiring high-resolution, year-round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long-distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra-annual estimates of the range, intra-annual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non-breeding seasons. The range-wide population trajectories for Wood Thrush show a close correspondence between breeding and non-breeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range-wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non-breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra- and interannual distributional dynamics for broadly distributed, highly mobile species.Information on species' distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range-wide extents for two main reasons. First, landscape-scale processes that affect populations vary throughout the year and across species' ranges, requiring high-resolution, year-round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long-distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra-annual estimates of the range, intra-annual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non-breeding seasons. The range-wide population trajectories for Wood Thrush show a close correspondence between breeding and non-breeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range-wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non-breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra- and interannual distributional dynamics for broadly distributed, highly mobile species. Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range-wide extents for two main reasons. First, landscape-scale processes that affect populations vary throughout the year and across species’ ranges, requiring high-resolution, year-round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long-distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra-annual estimates of the range, intraannual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non-breeding seasons. The range-wide population trajectories for Wood Thrush show a close correspondence between breeding and nonbreeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range-wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non-breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra- and interannual distributional dynamics for broadly distributed, highly mobile species.
Author	Johnston, Alison Ruiz-Gutierrez, Viviana Kelling, Steve Hochachka, Wesley M. Fink, Daniel Auer, Tom
AuthorAffiliation	1 Cornell Lab of Ornithology Cornell University Ithaca New York 14853 USA
AuthorAffiliation_xml	– name: 1 Cornell Lab of Ornithology Cornell University Ithaca New York 14853 USA
Author_xml	– sequence: 1 givenname: Daniel surname: Fink fullname: Fink, Daniel – sequence: 2 givenname: Tom surname: Auer fullname: Auer, Tom – sequence: 3 givenname: Alison surname: Johnston fullname: Johnston, Alison – sequence: 4 givenname: Viviana surname: Ruiz-Gutierrez fullname: Ruiz-Gutierrez, Viviana – sequence: 5 givenname: Wesley M. surname: Hochachka fullname: Hochachka, Wesley M. – sequence: 6 givenname: Steve surname: Kelling fullname: Kelling, Steve
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/31837058$$D View this record in MEDLINE/PubMed
BookMark	eNqFkV1rFDEUhgep2A8F_4Ay4I03s-Z7khuhlPoBFb3QSwlnkkybJZusyUzL-utNu-uqRTE3STjP--acvMfNQUzRNc1TjBYYIfLKwXpBEBcPmiOsqOo4l-SgnhHHHeoFPmyOS1miugghj5pDiiXtEZdHzdcPybrg42UL1x5iO84htBDjDKE1GxNca32Zsh_myadYK7Zdp_Uc4O46ZRdtaW_8dNUaP_nvLrbFeBdN1cEEj5uHI4Tinuz2k-bLm_PPZ--6i49v35-dXnSGKSo6wQXrQVpACo1OYCugF3WeYbAWSWkUANieI2mdwnZAGGQvDaEjKC6G0dKT5vXWdz0PK2eNi1OGoNfZryBvdAKv_6xEf6Uv07Xusewx49Xg5c4gp2-zK5Ne-WJcCBBdmosmnGPFGevl_1FKmVCCUlXRF_fQZZpzrD9RKcU4Q0SQSj3_vfl91z9D-vWiyamU7MY9gpG-zV_X_PVt_hVd3ENrLHdZ1bF9-Jug2wpufHCbfxrr89NPO_7Zll-WKeU9T4SihBFGfwD1Xsq_
CitedBy_id	crossref_primary_10_1038_s41598_024_80838_9 crossref_primary_10_1111_ddi_13259 crossref_primary_10_1002_eap_2510 crossref_primary_10_1016_j_biocon_2020_108653 crossref_primary_10_1016_j_ecolind_2022_109244 crossref_primary_10_1080_00063657_2022_2026876 crossref_primary_10_1111_ddi_13499 crossref_primary_10_1093_evolut_qpae058 crossref_primary_10_1002_ecy_4256 crossref_primary_10_1073_pnas_2220980120 crossref_primary_10_1111_ibi_13321 crossref_primary_10_1016_j_cub_2023_01_066 crossref_primary_10_1111_ddi_13785 crossref_primary_10_1111_cobi_14346 crossref_primary_10_58843_ornneo_v35i2_657 crossref_primary_10_1016_j_avrs_2025_100281 crossref_primary_10_1093_jrsssa_qnae108 crossref_primary_10_1016_j_biocon_2020_108826 crossref_primary_10_3390_d17080557 crossref_primary_10_1111_csp2_13281 crossref_primary_10_1111_gcb_16492 crossref_primary_10_1111_ecog_06378 crossref_primary_10_1080_21564574_2021_2019838 crossref_primary_10_1093_ornithapp_duaf030 crossref_primary_10_1093_ornithapp_duad011 crossref_primary_10_1016_j_agee_2025_109616 crossref_primary_10_3390_s24082597 crossref_primary_10_1016_j_ecoser_2025_101733 crossref_primary_10_2903_sp_efsa_2024_EN_9000 crossref_primary_10_3390_d15030404 crossref_primary_10_1016_j_cub_2023_03_024 crossref_primary_10_1016_j_biocon_2022_109523 crossref_primary_10_6339_24_JDS1152 crossref_primary_10_1002_eap_2815 crossref_primary_10_1016_j_avrs_2023_100140 crossref_primary_10_1155_2024_3022927 crossref_primary_10_1007_s10980_024_01813_3 crossref_primary_10_1111_gcb_16443 crossref_primary_10_1111_geb_70052 crossref_primary_10_1111_1365_2664_13971 crossref_primary_10_1111_jbi_14093 crossref_primary_10_1038_s41893_024_01365_z crossref_primary_10_1111_2041_210X_14272 crossref_primary_10_1007_s10651_021_00508_1 crossref_primary_10_1088_2752_664X_ac7eb5 crossref_primary_10_1111_geb_13767 crossref_primary_10_1038_s41598_022_23603_0 crossref_primary_10_3389_fenvs_2021_710396 crossref_primary_10_1080_15230406_2023_2293891 crossref_primary_10_1016_j_jenvman_2025_124838 crossref_primary_10_1111_tgis_12901 crossref_primary_10_1002_fee_70003 crossref_primary_10_1016_j_tree_2023_05_001 crossref_primary_10_1016_j_jtherbio_2023_103472 crossref_primary_10_1093_evolut_qpad112 crossref_primary_10_1111_csp2_12772 crossref_primary_10_3390_birds4040028 crossref_primary_10_1038_s41598_024_64912_w crossref_primary_10_1002_ecs2_3994 crossref_primary_10_1093_ornithapp_duaa064 crossref_primary_10_1111_cobi_14376 crossref_primary_10_1016_j_biocon_2021_108974 crossref_primary_10_1017_S0959270924000121 crossref_primary_10_1016_j_pecon_2023_02_001 crossref_primary_10_1002_eap_2679 crossref_primary_10_1002_jwmg_22324 crossref_primary_10_1016_j_jnc_2025_126970 crossref_primary_10_2903_sp_efsa_2022_EN_7762 crossref_primary_10_1371_journal_pone_0321496 crossref_primary_10_1111_geb_13070 crossref_primary_10_1016_j_jhydrol_2024_132264 crossref_primary_10_1111_ecog_05495 crossref_primary_10_1038_s41597_022_01635_5 crossref_primary_10_1016_j_cub_2023_11_033 crossref_primary_10_1126_science_adn4381 crossref_primary_10_1093_ornithapp_duae030 crossref_primary_10_1002_ecy_4175 crossref_primary_10_1038_s41467_023_43046_z crossref_primary_10_1093_ornithapp_duaf001 crossref_primary_10_1111_2041_210X_14052 crossref_primary_10_3389_fevo_2021_568278 crossref_primary_10_1111_cobi_13698 crossref_primary_10_1038_s41598_025_06961_3 crossref_primary_10_1016_j_biocon_2022_109556 crossref_primary_10_1016_j_ecoinf_2022_101629 crossref_primary_10_1016_j_scitotenv_2021_152173 crossref_primary_10_1111_ecog_06735 crossref_primary_10_1111_ele_14496 crossref_primary_10_1111_ecog_06219 crossref_primary_10_1002_wsb_1313 crossref_primary_10_1111_1365_2664_70108 crossref_primary_10_1186_s40462_021_00294_2 crossref_primary_10_1111_1365_2664_14251 crossref_primary_10_3390_ani14162404 crossref_primary_10_1111_geb_13460 crossref_primary_10_1002_eap_2058 crossref_primary_10_2903_sp_efsa_2025_EN_9423 crossref_primary_10_1111_ddi_13634 crossref_primary_10_3390_ijgi11010055 crossref_primary_10_1111_ecog_06769 crossref_primary_10_3390_ani11123426 crossref_primary_10_1111_jbi_14847 crossref_primary_10_1002_ece3_9866 crossref_primary_10_1371_journal_pone_0257226 crossref_primary_10_1007_s10980_025_02081_5 crossref_primary_10_1016_j_avrs_2022_100064 crossref_primary_10_1002_ecs2_4011 crossref_primary_10_1002_inc3_53 crossref_primary_10_3390_d14110905 crossref_primary_10_1002_ecy_4430 crossref_primary_10_1676_21_00024 crossref_primary_10_1016_j_biocon_2024_110801 crossref_primary_10_1111_ele_13817 crossref_primary_10_1093_ornithapp_duaf024 crossref_primary_10_1111_2041_210X_14189 crossref_primary_10_1007_s11252_024_01625_y crossref_primary_10_1093_ornithapp_duac015 crossref_primary_10_1093_ornithapp_duaf025 crossref_primary_10_1111_2041_210X_14186 crossref_primary_10_1016_j_eiar_2025_108029 crossref_primary_10_1038_s41598_022_26586_0 crossref_primary_10_1111_eva_13600 crossref_primary_10_1016_j_cub_2024_12_033 crossref_primary_10_1111_csp2_12975 crossref_primary_10_1111_geb_13567 crossref_primary_10_1111_1365_2664_14077 crossref_primary_10_1038_s41598_023_40626_3 crossref_primary_10_1111_oik_08215 crossref_primary_10_1002_ecs2_3790 crossref_primary_10_1111_1365_2664_14512 crossref_primary_10_1111_ele_13706 crossref_primary_10_1073_pnas_2203511120 crossref_primary_10_1093_auk_ukaa048 crossref_primary_10_3389_fenvs_2025_1461601 crossref_primary_10_1111_2041_210X_14110 crossref_primary_10_1111_brv_13127
Cites_doi	10.1371/journal.pone.0139600 10.1111/ddi.12428 10.2307/2529310 10.1525/auk.2010.09220 10.1073/pnas.1718985115 10.1371/journal.pone.0095565 10.1016/j.biocon.2018.02.027 10.1126/science.aac9180 10.1016/j.biocon.2013.11.003 10.1093/oxfordjournals.pan.a004868 10.1111/j.1469-185X.2011.00216.x 10.1890/14-1826.1 10.1111/brv.12359 10.1609/aimag.v35i2.2533 10.1016/j.biocon.2009.05.006 10.1111/ele.12048 10.1177/001316446002000104 10.1111/ecog.02881 10.1145/2934664 10.1017/S0376892997000088 10.1016/j.rse.2009.08.016 10.1371/journal.pone.0081867 10.1016/j.biocon.2015.06.009 10.1111/ecog.01034 10.1016/j.biocon.2016.09.004 10.1111/gcb.13794 10.1111/2041-210X.12838 10.1002/eap.1918 10.1016/j.biocon.2013.07.037 10.1111/cobi.12956 10.1080/01621459.2013.823775 10.1890/130017 10.1038/s41559-019-0826-1 10.1111/ddi.12698 10.1098/rsbl.2015.0552 10.1146/annurev-ecolsys-112414-054400 10.1073/pnas.1708574114 10.1002/ecs2.2707 10.11613/BM.2012.031 10.1093/ptj/85.3.257 10.1111/j.1365-2699.2010.02345.x 10.1146/annurev-ecolsys-102209-144636 10.1016/j.biocon.2013.12.020 10.1080/01621459.2017.1319839 10.1038/sdata.2018.40 10.1080/014311600210209 10.2307/1941447 10.1111/j.1466-8238.2007.00358.x 10.1145/356924.356930 10.1890/14-1410 10.1609/aaai.v27i1.8484 10.1023/A:1010933404324 10.1038/s41598-019-48851-5 10.1093/biosci/biz010 10.1080/01621459.1996.10476660 10.1016/j.tree.2011.11.006 10.1201/9781315370279 10.1007/978-0-387-84858-7 10.1002/ecy.1967 10.1111/j.2041-210X.2010.00060.x 10.1214/14-AOS1220 10.1890/09-1340.1 10.1093/auk/124.1.96 10.18637/jss.v023.i11
ContentType	Journal Article
Copyright	2019 The Authors 2019 The Authors. published by Wiley Periodicals, Inc. on behalf of Ecological Society of America 2019 The Authors. Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America. Copyright Ecological Society of America Apr 2020
Copyright_xml	– notice: 2019 The Authors – notice: 2019 The Authors. published by Wiley Periodicals, Inc. on behalf of Ecological Society of America – notice: 2019 The Authors. Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America. – notice: Copyright Ecological Society of America Apr 2020
DBID	24P AAYXX CITATION NPM 7QG 7SN 7SS 7ST 7U7 8FD C1K FR3 M7N P64 RC3 SOI 7X8 7S9 L.6 5PM
DOI	10.1002/eap.2056
DatabaseName	Wiley Online Library Open Access CrossRef PubMed Animal Behavior Abstracts Ecology Abstracts Entomology Abstracts (Full archive) Environment Abstracts Toxicology Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biotechnology and BioEngineering Abstracts Genetics Abstracts Environment Abstracts MEDLINE - Academic AGRICOLA AGRICOLA - Academic PubMed Central (Full Participant titles)
DatabaseTitle	CrossRef PubMed Entomology Abstracts Genetics Abstracts Technology Research Database Toxicology Abstracts Animal Behavior Abstracts Algology Mycology and Protozoology Abstracts (Microbiology C) Engineering Research Database Ecology Abstracts Environment Abstracts Biotechnology and BioEngineering Abstracts Environmental Sciences and Pollution Management MEDLINE - Academic AGRICOLA AGRICOLA - Academic
DatabaseTitleList	CrossRef MEDLINE - Academic PubMed AGRICOLA Entomology Abstracts
Database_xml	– sequence: 1 dbid: 24P name: Wiley Online Library Open Access url: https://authorservices.wiley.com/open-science/open-access/browse-journals.html sourceTypes: Publisher – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Biology Ecology Environmental Sciences
DocumentTitleAlternate	Daniel Fink et al
EISSN	1939-5582
EndPage	16
ExternalDocumentID	PMC7187145 31837058 10_1002_eap_2056 EAP2056 26932424
Genre	article Journal Article
GrantInformation_xml	– fundername: NASA funderid: NNH12ZDA001N‐ECOF – fundername: AWS Cloud Credits for Research program – fundername: The Wolf Creek Foundation – fundername: Leon Levy Foundation – fundername: NASA grantid: NNH12ZDA001N-ECOF – fundername: ; – fundername: ; grantid: NNH12ZDA001N‐ECOF
GroupedDBID	--- -ET -~X ..I 0R~ 1OB 1OC 2AX 33P 4.4 42X 53G 5GY 85S 8WZ A6W AAESR AAHBH AAHKG AAHQN AAIHA AAIKC AAISJ AAKGQ AAMMB AAMNL AAMNW AANLZ AASGY AAXRX AAYCA AAZKR ABAWQ ABBHK ABCUV ABEFU ABJNI ABLJU ABPFR ABPLY ABPPZ ABPQH ABSQW ABTLG ABXSQ ACAHQ ACCZN ACGFS ACHIC ACHJO ACNCT ACPOU ACSTJ ACUBG ACXBN ACXQS ADBBV ADKYN ADMGS ADNWM ADOZA ADXAS ADZMN AEFGJ AEIGN AENEX AEUPB AEUYR AEYWJ AFAZZ AFBPY AFFPM AFGKR AFWVQ AFXHP AFZJQ AGHNM AGUYK AGXDD AGYGG AHBTC AHXOZ AIDQK AIDYY AILXY AITYG AIURR ALMA_UNASSIGNED_HOLDINGS ALVPJ AMYDB ANHSF AQVQM AZFZN AZVAB BFHJK BMXJE BRXPI CBGCD CS3 CUYZI DCZOG DEVKO DRFUL DRSTM DU5 EBS ECGQY F5P HGLYW H~9 IAO IEA IGH IOF IPSME JAAYA JAS JBMMH JBS JBZCM JEB JENOY JHFFW JKQEH JLEZI JLS JLXEF JPL JPM JST L7B LATKE LEEKS LH4 LITHE LOXES LUTES LYRES MEWTI MV1 MXFUL MXSTM NXSMM O9- P2P P2W ROL RSZ SA0 SUPJJ TN5 UKR V62 WBKPD WH7 WOHZO WXSBR XSW YV5 YYM YYP Z0I ZCA ZO4 ZZTAW ~02 ~KM .-4 24P 29G AAHHS AAYJJ ABYAD ACCFJ ACTWD ADULT ADZOD AEEZP AEQDE AEUQT AI. AIDAL AIWBW AJBDE ALUQN AS~ DDYGU DOOOF EJD EQZMY FVMVE GTFYD HGD HQ2 HTVGU HVGLF IAG IEP ITC JSODD MVM NHB P0- PALCI RJQFR SAMSI VH1 VOH VQA XIH Y6R YXE ZCG AAYXX AIQQE CITATION NPM 7QG 7SN 7SS 7ST 7U7 8FD C1K FR3 M7N P64 RC3 SOI 7X8 7S9 L.6 5PM
ID	FETCH-LOGICAL-c4936-65647a8da090fe61d6a76205bbdd088c9aaad7508de91db01a878c23fa956bfd3
IEDL.DBID	24P
ISICitedReferencesCount	139
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000506075700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1051-0761
IngestDate	Tue Nov 04 01:57:19 EST 2025 Fri Sep 05 17:21:50 EDT 2025 Thu Oct 02 10:00:15 EDT 2025 Wed Aug 13 11:01:41 EDT 2025 Thu Apr 03 06:58:35 EDT 2025 Sat Nov 29 03:26:44 EST 2025 Tue Nov 18 22:31:18 EST 2025 Wed Jan 22 16:35:59 EST 2025 Wed Nov 19 01:46:02 EST 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	3
Keywords	eBird bird distributions biodiversity monitoring population trends abundance citizen science full annual cycle area of occurrence bird migration Wood Thrush
Language	English
License	Attribution-NonCommercial 2019 The Authors. Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c4936-65647a8da090fe61d6a76205bbdd088c9aaad7508de91db01a878c23fa956bfd3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Corresponding Editor: John M. Marzluff.
OpenAccessLink	https://onlinelibrary.wiley.com/doi/abs/10.1002%2Feap.2056
PMID	31837058
PQID	2394540262
PQPubID	2048294
PageCount	16
ParticipantIDs	pubmedcentral_primary_oai_pubmedcentral_nih_gov_7187145 proquest_miscellaneous_2551954478 proquest_miscellaneous_2334696339 proquest_journals_2394540262 pubmed_primary_31837058 crossref_primary_10_1002_eap_2056 crossref_citationtrail_10_1002_eap_2056 wiley_primary_10_1002_eap_2056_EAP2056 jstor_primary_26932424
PublicationCentury	2000
PublicationDate	April 2020
PublicationDateYYYYMMDD	2020-04-01
PublicationDate_xml	– month: 04 year: 2020 text: April 2020
PublicationDecade	2020
PublicationPlace	United States
PublicationPlace_xml	– name: United States – name: Washington – name: Hoboken
PublicationTitle	Ecological applications
PublicationTitleAlternate	Ecol Appl
PublicationYear	2020
Publisher	John Wiley and Sons, Inc Ecological Society of America John Wiley and Sons Inc
Publisher_xml	– name: John Wiley and Sons, Inc – name: Ecological Society of America – name: John Wiley and Sons Inc
References	2017; 40 2015; 38 2019; 10 2014; 173 2014; 171 2013; 8 2001; 45 2017; 114 2015; 46 2017; 31 2018; 9 2010; 20 2018; 5 2013; 16 2011; 128 1984; 16 2010; 114 2019; 69 2008; 23 2019; 29 1977; 33 2012; 27 2014; 9 2012; 22 1992; 2 2014; 12 2014; 169 2018; 221 2007; 124 2019; 9 2019; 3 2010; 37 2011; 2 2012 2011 2000; 21 1997; 24 2015; 11 2017; 24 2015; 10 2017; 23 2008; 17 2009 2005; 85 1996; 91 2016; 17 2017; 213 2016; 59 2010; 41 1992; 73 2014; 42 2015; 350 2015; 25 2015; 191 2014; 109 2017; 93 1960; 20 2018; 113 2017; 98 2001; 9 2018; 115 2019 2014; 35 2017 2016 2015 2014 2013 2009; 142 2016; 26 2012; 87 2016; 22 e_1_2_7_5_1 R Development Core Team (e_1_2_7_55_1) 2017 e_1_2_7_3_1 e_1_2_7_9_1 e_1_2_7_7_1 Johnston A. (e_1_2_7_37_1) 2019 e_1_2_7_19_1 e_1_2_7_60_1 e_1_2_7_17_1 e_1_2_7_62_1 e_1_2_7_15_1 e_1_2_7_41_1 e_1_2_7_64_1 e_1_2_7_13_1 e_1_2_7_43_1 e_1_2_7_66_1 e_1_2_7_45_1 e_1_2_7_68_1 e_1_2_7_47_1 e_1_2_7_26_1 e_1_2_7_49_1 e_1_2_7_28_1 Evans M. (e_1_2_7_18_1) 2011 e_1_2_7_73_1 e_1_2_7_50_1 e_1_2_7_71_1 e_1_2_7_25_1 e_1_2_7_31_1 e_1_2_7_52_1 e_1_2_7_77_1 e_1_2_7_23_1 e_1_2_7_33_1 e_1_2_7_54_1 e_1_2_7_75_1 e_1_2_7_21_1 e_1_2_7_35_1 e_1_2_7_56_1 e_1_2_7_58_1 e_1_2_7_39_1 Mentch L. (e_1_2_7_53_1) 2016; 17 e_1_2_7_6_1 e_1_2_7_4_1 e_1_2_7_8_1 e_1_2_7_16_1 e_1_2_7_61_1 e_1_2_7_2_1 e_1_2_7_14_1 e_1_2_7_42_1 e_1_2_7_63_1 e_1_2_7_12_1 e_1_2_7_44_1 e_1_2_7_65_1 e_1_2_7_10_1 e_1_2_7_46_1 e_1_2_7_67_1 e_1_2_7_48_1 e_1_2_7_69_1 e_1_2_7_27_1 Cleveland W. S. (e_1_2_7_11_1) 1992; 2 e_1_2_7_29_1 Kéry M. (e_1_2_7_40_1) 2015 e_1_2_7_72_1 e_1_2_7_51_1 e_1_2_7_70_1 e_1_2_7_30_1 e_1_2_7_76_1 e_1_2_7_24_1 e_1_2_7_32_1 e_1_2_7_74_1 e_1_2_7_22_1 e_1_2_7_34_1 e_1_2_7_57_1 e_1_2_7_20_1 e_1_2_7_36_1 e_1_2_7_59_1 e_1_2_7_38_1
References_xml	– year: 2011 – volume: 142 start-page: 2282 year: 2009 end-page: 2292 article-title: eBird: A citizen‐based bird observation network in the biological sciences publication-title: Biological Conservation – year: 2009 – volume: 40 start-page: 913 year: 2017 end-page: 929 article-title: Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure publication-title: Ecography – volume: 124 start-page: 96 year: 2007 end-page: 106 article-title: Incorporating availability for detection in estimates of bird abundance publication-title: Auk – volume: 24 start-page: 460 year: 2017 end-page: 472 article-title: Correcting for bias in distribution modeling for rare species using citizen science data publication-title: Diversity and Distributions – volume: 20 start-page: 37 year: 1960 end-page: 46 article-title: A coefficient of agreement for nominal scales publication-title: Educational and Psychological Measurement – volume: 20 start-page: 2131 year: 2010 end-page: 2147 article-title: Spatiotemporal exploratory models for broad_scale survey data publication-title: Ecological Applications – volume: 22 start-page: 717 year: 2016 end-page: 730 article-title: Novel seasonal land cover associations for eastern North American forest birds identified through dynamic species distribution modelling publication-title: Diversity and Distributions – volume: 41 start-page: 149 year: 2010 end-page: 172 article-title: Citizen science as an ecological research tool: challenges and benefits publication-title: Annual Review of Ecology, Evolution, and Systematics – volume: 10 start-page: e02707 year: 2019 article-title: Spatial modeling of Audubon Christmas Bird Counts reveals fine‐scale patterns and drivers of relative abundance trends publication-title: Ecosphere – volume: 25 start-page: 1749 year: 2015 end-page: 1756 article-title: Abundance models improve spatial and temporal prioritization of conservation resources publication-title: Ecological Applications – volume: 2 start-page: 143 year: 2011 end-page: 154 article-title: Comparing spatially‐varying coefficients models for analysis of ecological data with non‐stationary and anisotropic residual dependence publication-title: Methods in Ecology and Evolution – volume: 9 start-page: 137 year: 2001 end-page: 163 article-title: Logistic regression in rare events data publication-title: Political Analysis – volume: 5 start-page: 180040 year: 2018 article-title: A suite of global, cross‐scale topographic variables for environmental and biodiversity modeling publication-title: Scientific Data – volume: 45 start-page: 5 year: 2001 end-page: 32 article-title: Random forests publication-title: Machine Learning – year: 2014 – volume: 42 start-page: 1693 year: 2014 article-title: Local case‐control sampling: efficient subsampling in imbalanced data sets publication-title: Annals of Statistics – volume: 12 start-page: 5 year: 2014 end-page: 14 article-title: Macrosystems ecology: understanding ecological patterns and processes at continental scales publication-title: Frontiers in Ecology and the Environment – volume: 3 start-page: 539 year: 2019 article-title: Essential biodiversity variables for mapping and monitoring species populations publication-title: Nature Ecology & Evolution – volume: 213 start-page: 280 year: 2017 end-page: 294 article-title: Contribution of citizen science towards international biodiversity monitoring publication-title: Biological Conservation – volume: 26 start-page: 424 year: 2016 end-page: 437 article-title: Effects of breeding versus winter habitat loss and fragmentation on the population dynamics of a migratory songbird publication-title: Ecological Applications – volume: 171 start-page: 1 year: 2014 end-page: 8 article-title: Using citizen science to estimate lichen diversity publication-title: Biological Conservation – volume: 31 start-page: 1350 year: 2017 end-page: 1361 article-title: Using citizen science butterfly counts to predict species population trends publication-title: Conservation Biology – volume: 93 start-page: 600 year: 2017 end-page: 625 article-title: Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale publication-title: Biological Reviews – volume: 350 start-page: 1255 year: 2015 end-page: 1258 article-title: Protected areas and global conservation of migratory birds publication-title: Science – volume: 59 start-page: 56 year: 2016 end-page: 65 article-title: Apache Spark: a unified engine for big data processing publication-title: Communications of the ACM – volume: 87 start-page: 661 year: 2012 end-page: 685 article-title: Landscape moderation of biodiversity patterns and processes‐eight hypotheses publication-title: Biological Reviews – volume: 114 start-page: 168 year: 2010 end-page: 182 article-title: MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets publication-title: Remote Sensing of Environment – volume: 8 start-page: e81867 year: 2013 article-title: Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach publication-title: PLoS ONE – volume: 38 start-page: 358 year: 2015 end-page: 369 article-title: Towards a taxonomy of spatial scale‐dependence publication-title: Ecography – volume: 37 start-page: 1851 year: 2010 end-page: 1862 article-title: Predicting species distributions from checklist data using site‐occupancy models publication-title: Journal of Biogeography – volume: 98 start-page: 2837 year: 2017 end-page: 2850 article-title: Spatial and temporal drivers of avian population dynamics across the annual cycle publication-title: Ecology – year: 2015 – volume: 169 start-page: 31 year: 2014 end-page: 40 article-title: The eBird enterprise: an integrated approach to development and application of citizen science publication-title: Biological Conservation – volume: 11 start-page: 20150552 year: 2015 article-title: A call for full annual cycle research in animal ecology publication-title: Biology Letters – volume: 115 start-page: E3192 year: 2018 end-page: E3200 article-title: Population trends in Vermivora warblers are linked to strong migratory connectivity publication-title: Proceedings of the National Academy of Sciences USA – volume: 91 start-page: 14 year: 1996 end-page: 28 article-title: Statistics in epidemiology: the case‐control study publication-title: Journal of the American Statistical Association – volume: 73 start-page: 1943 year: 1992 end-page: 1967 article-title: The problem of pattern and scale in ecology: the Robert H. MacArthur award lecture publication-title: Ecology – volume: 9 start-page: 1 year: 2019 end-page: 9 article-title: Modeling spatially and temporally complex range dynamics when detection is imperfect publication-title: Scientific Reports – volume: 29 start-page: e01918 year: 2019 article-title: The power to detect regional declines in common bird populations using continental monitoring data publication-title: Ecological Applications – volume: 24 start-page: 38 year: 1997 end-page: 49 article-title: A review of methods for the assessment of prediction errors in conservation presence/absence models publication-title: Environmental Conservation – volume: 46 start-page: 523 year: 2015 end-page: 549 article-title: Seven shortfalls that beset large‐scale knowledge of biodiversity publication-title: Annual Review of Ecology, Evolution, and Systematics – volume: 114 start-page: 11175 year: 2017 end-page: 11180 article-title: High‐intensity urban light installation dramatically alters nocturnal bird migration publication-title: Proceedings of the National Academy of Sciences USA – volume: 191 start-page: 38 year: 2015 end-page: 49 article-title: A novel citizen science approach for large‐scale standardised monitoring of bat activity and distribution, evaluated in eastern England publication-title: Biological Conservation – volume: 128 start-page: 87 year: 2011 end-page: 98 article-title: Analysis of the North American breeding bird survey using hierarchical models publication-title: Auk – start-page: 574392 year: 2019 article-title: Best practices for making reliable inferences from citizen science data: case study using eBird to estimate species distributions publication-title: bioRxiv – volume: 33 start-page: 159 year: 1977 end-page: 174 article-title: The measurement of observer agreement for categorical data publication-title: Biometrics – volume: 2 start-page: 309 year: 1992 end-page: 376 article-title: Local regression models publication-title: Statistical Models in S – year: 2016 – volume: 9 start-page: 88 year: 2018 end-page: 97 article-title: Accounting for observer expertise improves ecological inference from citizen science data publication-title: Methods in Ecology and Evolution – volume: 109 start-page: 991 year: 2014 end-page: 1007 article-title: Estimation and accuracy after model selection publication-title: Journal of the American Statistical Association – volume: 69 start-page: 170 year: 2019 end-page: 179 article-title: Using semistructured surveys to improve citizen science data for monitoring biodiversity publication-title: BioScience – year: 2012 – volume: 16 start-page: 187 year: 1984 end-page: 260 article-title: The quadtree and related hierarchical data structures publication-title: ACM Computing Surveys (CSUR) – volume: 16 start-page: 4 year: 2013 end-page: 16 article-title: The problem of pattern and scale in ecology: what have we learned in 20 years? publication-title: Ecology Letters – volume: 17 start-page: 145 year: 2008 end-page: 151 article-title: AUC: a misleading measure of the performance of predictive distribution models publication-title: Global Ecology and Biogeography – volume: 35 start-page: 19 year: 2014 end-page: 30 article-title: Crowdsourcing meets ecology: hemisphere‐wide spatiotemporal species distribution models publication-title: AI Magazine – volume: 27 start-page: 130 year: 2012 end-page: 137 article-title: Data‐intensive science applied to broad‐scale citizen science publication-title: Trends in Ecology & Evolution – volume: 85 start-page: 257 year: 2005 end-page: 268 article-title: The kappa statistic in reliability studies: use, interpretation, and sample size requirements publication-title: Physical Therapy – volume: 173 start-page: 144 year: 2014 end-page: 154 article-title: Statistical solutions for error and bias in global citizen science datasets publication-title: Biological Conservation – volume: 21 start-page: 1331 year: 2000 end-page: 1364 article-title: Global land cover classification at the 1 km spatial resolution using a classification tree approach publication-title: International Journal of Remote Sensing – volume: 10 start-page: e0139600 year: 2015 article-title: Can observation skills of citizen scientists be estimated using species accumulation curves? publication-title: PLoS ONE – volume: 22 start-page: 276 year: 2012 end-page: 282 article-title: Interrater reliability: the kappa statistic publication-title: Biochemia Medica – volume: 23 start-page: 5284 year: 2017 end-page: 5296 article-title: Global change and the distributional dynamics of migratory bird populations wintering in Central America publication-title: Global Change Biology – volume: 221 start-page: 151 year: 2018 end-page: 159 article-title: Using opportunistic citizen science data to estimate avian population trends publication-title: Biological Conservation – volume: 23 start-page: 1 year: 2008 end-page: 31 article-title: PresenceAbsence: An R package for presence‐absence model analysis publication-title: Journal of Statistical Software – volume: 9 start-page: e95565 year: 2014 article-title: Acoustic telemetry validates a citizen science approach for monitoring sharks on coral reefs publication-title: PLoS ONE – year: 2017 – volume: 17 start-page: 841 year: 2016 end-page: 881 article-title: Quantifying uncertainty in random forests via confidence intervals and hypothesis tests publication-title: Journal of Machine Learning Research – volume: 113 start-page: 1228 year: 2018 end-page: 1242 article-title: Estimation and inference of heterogeneous treatment effects using random forests publication-title: Journal of the American Statistical Association – year: 2013 – ident: e_1_2_7_38_1 doi: 10.1371/journal.pone.0139600 – volume-title: R: A language and environment for statistical computing year: 2017 ident: e_1_2_7_55_1 – ident: e_1_2_7_77_1 doi: 10.1111/ddi.12428 – ident: e_1_2_7_46_1 doi: 10.2307/2529310 – volume: 2 start-page: 309 year: 1992 ident: e_1_2_7_11_1 article-title: Local regression models publication-title: Statistical Models in S – ident: e_1_2_7_56_1 – ident: e_1_2_7_64_1 doi: 10.1525/auk.2010.09220 – ident: e_1_2_7_44_1 doi: 10.1073/pnas.1718985115 – ident: e_1_2_7_73_1 doi: 10.1371/journal.pone.0095565 – ident: e_1_2_7_32_1 doi: 10.1016/j.biocon.2018.02.027 – ident: e_1_2_7_59_1 doi: 10.1126/science.aac9180 – ident: e_1_2_7_68_1 doi: 10.1016/j.biocon.2013.11.003 – ident: e_1_2_7_17_1 – ident: e_1_2_7_42_1 doi: 10.1093/oxfordjournals.pan.a004868 – ident: e_1_2_7_70_1 doi: 10.1111/j.1469-185X.2011.00216.x – ident: e_1_2_7_35_1 doi: 10.1890/14-1826.1 – volume-title: Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS: Volume 1: Prelude and Static Models year: 2015 ident: e_1_2_7_40_1 – ident: e_1_2_7_43_1 doi: 10.1111/brv.12359 – ident: e_1_2_7_22_1 doi: 10.1609/aimag.v35i2.2533 – volume: 17 start-page: 841 year: 2016 ident: e_1_2_7_53_1 article-title: Quantifying uncertainty in random forests via confidence intervals and hypothesis tests publication-title: Journal of Machine Learning Research – ident: e_1_2_7_67_1 doi: 10.1016/j.biocon.2009.05.006 – ident: e_1_2_7_9_1 doi: 10.1111/ele.12048 – ident: e_1_2_7_12_1 doi: 10.1177/001316446002000104 – start-page: 574392 year: 2019 ident: e_1_2_7_37_1 article-title: Best practices for making reliable inferences from citizen science data: case study using eBird to estimate species distributions publication-title: bioRxiv – ident: e_1_2_7_57_1 doi: 10.1111/ecog.02881 – ident: e_1_2_7_76_1 doi: 10.1145/2934664 – ident: e_1_2_7_19_1 doi: 10.1017/S0376892997000088 – ident: e_1_2_7_27_1 doi: 10.1016/j.rse.2009.08.016 – ident: e_1_2_7_5_1 doi: 10.1371/journal.pone.0081867 – ident: e_1_2_7_54_1 doi: 10.1016/j.biocon.2015.06.009 – ident: e_1_2_7_63_1 doi: 10.1111/ecog.01034 – ident: e_1_2_7_10_1 doi: 10.1016/j.biocon.2016.09.004 – ident: e_1_2_7_45_1 doi: 10.1111/gcb.13794 – volume-title: The birds of North America year: 2011 ident: e_1_2_7_18_1 – ident: e_1_2_7_36_1 doi: 10.1111/2041-210X.12838 – ident: e_1_2_7_3_1 doi: 10.1002/eap.1918 – ident: e_1_2_7_4_1 doi: 10.1016/j.biocon.2013.07.037 – ident: e_1_2_7_65_1 – ident: e_1_2_7_13_1 doi: 10.1111/cobi.12956 – ident: e_1_2_7_16_1 doi: 10.1080/01621459.2013.823775 – ident: e_1_2_7_30_1 doi: 10.1890/130017 – ident: e_1_2_7_34_1 doi: 10.1038/s41559-019-0826-1 – ident: e_1_2_7_58_1 doi: 10.1111/ddi.12698 – ident: e_1_2_7_49_1 doi: 10.1098/rsbl.2015.0552 – ident: e_1_2_7_33_1 doi: 10.1146/annurev-ecolsys-112414-054400 – ident: e_1_2_7_71_1 doi: 10.1073/pnas.1708574114 – ident: e_1_2_7_52_1 doi: 10.1002/ecs2.2707 – ident: e_1_2_7_51_1 doi: 10.11613/BM.2012.031 – ident: e_1_2_7_66_1 doi: 10.1093/ptj/85.3.257 – ident: e_1_2_7_41_1 doi: 10.1111/j.1365-2699.2010.02345.x – ident: e_1_2_7_14_1 doi: 10.1146/annurev-ecolsys-102209-144636 – ident: e_1_2_7_8_1 doi: 10.1016/j.biocon.2013.12.020 – ident: e_1_2_7_74_1 doi: 10.1080/01621459.2017.1319839 – ident: e_1_2_7_2_1 doi: 10.1038/sdata.2018.40 – ident: e_1_2_7_28_1 doi: 10.1080/014311600210209 – ident: e_1_2_7_47_1 doi: 10.2307/1941447 – ident: e_1_2_7_48_1 doi: 10.1111/j.1466-8238.2007.00358.x – ident: e_1_2_7_62_1 doi: 10.1145/356924.356930 – ident: e_1_2_7_69_1 doi: 10.1890/14-1410 – ident: e_1_2_7_21_1 doi: 10.1609/aaai.v27i1.8484 – ident: e_1_2_7_6_1 doi: 10.1023/A:1010933404324 – ident: e_1_2_7_61_1 doi: 10.1038/s41598-019-48851-5 – ident: e_1_2_7_39_1 doi: 10.1093/biosci/biz010 – ident: e_1_2_7_7_1 doi: 10.1080/01621459.1996.10476660 – ident: e_1_2_7_31_1 doi: 10.1016/j.tree.2011.11.006 – ident: e_1_2_7_72_1 – ident: e_1_2_7_75_1 doi: 10.1201/9781315370279 – ident: e_1_2_7_29_1 doi: 10.1007/978-0-387-84858-7 – ident: e_1_2_7_60_1 doi: 10.1002/ecy.1967 – ident: e_1_2_7_24_1 doi: 10.1111/j.2041-210X.2010.00060.x – ident: e_1_2_7_50_1 – ident: e_1_2_7_25_1 doi: 10.1214/14-AOS1220 – ident: e_1_2_7_20_1 doi: 10.1890/09-1340.1 – ident: e_1_2_7_15_1 doi: 10.1093/auk/124.1.96 – ident: e_1_2_7_23_1 – ident: e_1_2_7_26_1 doi: 10.18637/jss.v023.i11
SSID	ssj0000222
Score	2.6459932
Snippet	Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations.... Information on species' distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations....
SourceID	pubmedcentral proquest pubmed crossref wiley jstor
SourceType	Open Access Repository Aggregation Database Index Database Enrichment Source Publisher
StartPage	1
SubjectTerms	Abundance Animal breeding Animal populations area of occurrence biodiversity monitoring bird distributions bird migration birds Breeding seasons citizen science Conservation Data collection eBird full annual cycle Hylocichla mustelina Landscape landscapes Modelling Neotropics population trends Populations Seasons Species surveys Trends Wildlife conservation Wood Thrush
Title	Modeling avian full annual cycle distribution and population trends with citizen science data
URI	https://www.jstor.org/stable/26932424 https://onlinelibrary.wiley.com/doi/abs/10.1002%2Feap.2056 https://www.ncbi.nlm.nih.gov/pubmed/31837058 https://www.proquest.com/docview/2394540262 https://www.proquest.com/docview/2334696339 https://www.proquest.com/docview/2551954478 https://pubmed.ncbi.nlm.nih.gov/PMC7187145
Volume	30
WOSCitedRecordID	wos000506075700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVWIB databaseName: Wiley Online Library customDbUrl: eissn: 1939-5582 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000222 issn: 1051-0761 databaseCode: DRFUL dateStart: 19970101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1La9wwEB7apIVe-t7GbRpUKO3JRJZlST6GZpceQlhKU_ZSjF6mC8UJ2U0g-fWdsb3eLk1CIRfboLGxrXl8kkbfAHxUwvlouE6dtjzFeB1SU7gMOySI2oegfbsr7ceRPj42s1k57bMqaS9Mxw8xTLiRZbT-mgzcusX-mjQ0WqKbLNRD2M6y3FDZBiGnay_crSAgfMDhMo7VV8SzXOyv7twIRV024k048990yb9hbBuHJs_u8wXP4WmPPtlBpy4v4EFsXsLjrh7lFV6NfX81Gq83wOENvQdYvIKfVDyNtrAze4maxWj6nnXEpsxf4UNZICrevooWtgR2NtQIY8s2A5fR5C_z8-X8Ojasj8GMclVfw8lk_P3L17Qv0ZB6WeYqRTQotTXB8pLXUWVBWfSuvHAuBPRfvrTWBgQlJsQyC45n1mjjRV5bHJe5OuQj2GpOm7gDTDmEGiLyoLSSJYbJmlZ4BQpxmZUxJPB51VuV7_nLqYzG76pjXhYV_s-K_mcCHwbJs46z4waZUdvhg4BQJWFLmcDuSgOq3pwXFdWPR2grlMBnD81oiLS6Ypt4ekEyuVTozvLyDpmCyHyk1CaBN51SDS9AzlXzAlv0hroNAkQEvtnSzH-1hOCIL3QmiwQ-tep260dX44Mpnd_-r-A7eCJofqHNVNqFreX5RXwPj_zlcr4432sNDo96ZvZg-_Db5OToD5Q9MWA
linkProvider	Wiley-Blackwell
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB6VAioX3tuGFjASglNUx3HsRJwqtFURy2oPBfWCIsd2xEpVWnW3lcqvZyZOsl1REBKnRPLk6Xl8tsffALxVorI-5zqutOExxmsX51mVYIc4UVvntG13pX2b6Ok0PzkpZhvwod8LE_ghhgk3sozWX5OB04T0_oo11Bvim8zUHbgrMciQkgs5W7nhsISA-AHHyzhY75lnudjvr1yLRSEd8Tag-Xu-5E0c2waiw0f_9QmP4WGHP9lBUJgnsOGbp3A_VKS8xrOx7c5G49UWOLyg8wGLZ_CdyqfRJnZmrlC3GD2MBWpTZq_xpswRGW9XRwtbHDsfqoSxZZuDy2j6l9n5cv7TN6yLwoyyVZ_D18Px8cejuCvSEFtZpCpGPCi1yZ3hBa-9Spwy6F95VlXOoQezhTHGISzJnS8SV_HE5Dq3Iq0Njsyq2qUj2GzOGr8DTFUINoTnTmklCwyUNa3xChTiMim8i-B9312l7RjMqZDGaRm4l0WJ_7Ok_xnBm0HyPLB23CIzant8EBCqIHQpI9jrVaDsDHpRUgV5BLdCCbz30IymSOsrpvFnlySTSoUOLS3-IpMRnY-UOo9gO2jV8ALkXjXPsEWv6dsgQFTg6y3N_EdLCY4IQycyi-Bdq29__OhyfDCj44t_FXwNW0fHXybl5NP08y48EDTb0OYt7cHm8uLSv4R79mo5X1y8aq3vF_DlMsM
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3da9swED-6dCt72Xdar92mwdieTGVZlmz2VNaEjYUQxjr6MowsySxQ3NCkhe6v352_0rBuDPZkg87Gsu7jJ-n0O4A3ShTWp1yHhTY8xHjtwjQpIhwQJ0rrnLb1qbRvEz2dpqen2WwL3ndnYRp-iH7BjSyj9tdk4H7hysM1a6g3xDeZqDuwLamGzAC2j7-MTyZrR9xsIiCCwBkzTtc77lkuDrtnN6JRk5B4G9T8PWPyJpKtQ9H44X914hE8aBEoO2pU5jFs-eoJ3GtqUl7j3ci2d8PR-hAcPtB6geVT-E4F1OgYOzNXqF2MlvBZQ27K7DW-lDmi420raWGLY4u-Thhb1Vm4jBaAmZ2v5j99xdo4zChf9RmcjEdfP3wM2zINoZVZrEJEhFKb1Bme8dKryCmDHpYnReEc-jCbGWMcApPU-SxyBY9MqlMr4tLg3KwoXTyEQXVe-T1gqkC4ITx3SiuZYagsaZdXoBCXUeZdAO-64cpty2FOpTTO8oZ9WeT4P3P6nwG87iUXDW_HLTLDesR7AaEywpcygINOBfLWpJc51ZBHeCuUwHf3zWiMtMNiKn9-STKxVOjS4uwvMgkR-kip0wB2G63qP4AcrOYJtugNfesFiAx8s6Wa_6hJwRFj6EgmAbyt9e2Pnc5HRzO6Pv9XwVewMzse55NP08_7cF_QckOduHQAg9XFpX8Bd-3Var68eNma3y--pDPZ
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=Modeling+avian+full+annual+cycle+distribution+and+population+trends+with+citizen+science+data&rft.jtitle=Ecological+applications&rft.au=Fink%2C+Daniel&rft.au=Auer%2C+Tom&rft.au=Johnston%2C+Alison&rft.au=Ruiz-Gutierrez%2C+Viviana&rft.date=2020-04-01&rft.pub=John+Wiley+and+Sons%2C+Inc&rft.issn=1051-0761&rft.eissn=1939-5582&rft.volume=30&rft.issue=3&rft.spage=1&rft.epage=16&rft_id=info:doi/10.1002%2Feap.2056&rft.externalDocID=26932424
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1051-0761&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1051-0761&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1051-0761&client=summon