Bayesian integrated species distribution models for hierarchical resource selection by a soaring bird Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.ecoinf.2024.102787
Migratory birds exhibit seasonal geographic range (hereafter, range) dynamics during the annual cycle. Few studies have examined how migratory birds select their habitats for range occupancy at the species level and space use at the individual level simultaneously. We hypothesized that environmental variables directly related to fitness components would affect the range occupancy probabilities of migrants, whereas environment variables related to movements and flights would affect the space use intensities of migrants. We built Bayesian integrated species distribution models (ISDMs) to evaluate the effects of climate conditions, wind conditions, and landcover compositions on the seasonal range dynamics of American white pelicans Pelecanus erythrorhynchos (hereafter, pelican) during summer and winter. The ISDMs estimated the summer range occupancy probabilities of pelicans with Breeding Bird Survey data, winter range occupancy probabilities with Christmas Bird Count data, and summer and winter space-use intensity rates with eBird data jointly. We evaluated the predictive performance of ISDMs using independent datasets of pelican GPS locations. Integrated species distribution models outperformed the occupancy-only models in the predictive performance of occupancy probabilities. Climate conditions had opposite effects on the range occupancy probabilities between the breeding and non-breeding grounds, whereas landcovers had relatively consistent effects on range occupancy probabilities between the seasons.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ecoinf.2024.102787
- OA Status
- gold
- References
- 73
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401798995
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4401798995Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.ecoinf.2024.102787Digital Object Identifier
- Title
-
Bayesian integrated species distribution models for hierarchical resource selection by a soaring birdWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-08-23Full publication date if available
- Authors
-
Ryo Ogawa, Guiming Wang, L. Wes Burger, Bronson K. Strickland, J. Brian Davis, Fred L. CunninghamList of authors in order
- Landing page
-
https://doi.org/10.1016/j.ecoinf.2024.102787Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.ecoinf.2024.102787Direct OA link when available
- Concepts
-
Selection (genetic algorithm), Bayesian probability, Computer science, Resource distribution, Bayesian hierarchical modeling, Resource (disambiguation), Ecology, Distribution (mathematics), Bayesian inference, Machine learning, Artificial intelligence, Biology, Resource allocation, Mathematics, Mathematical analysis, Computer networkTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
73Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4401798995 |
|---|---|
| doi | https://doi.org/10.1016/j.ecoinf.2024.102787 |
| ids.doi | https://doi.org/10.1016/j.ecoinf.2024.102787 |
| ids.openalex | https://openalex.org/W4401798995 |
| fwci | 0.0 |
| type | article |
| title | Bayesian integrated species distribution models for hierarchical resource selection by a soaring bird |
| biblio.issue | |
| biblio.volume | 82 |
| biblio.last_page | 102787 |
| biblio.first_page | 102787 |
| topics[0].id | https://openalex.org/T10895 |
| topics[0].field.id | https://openalex.org/fields/23 |
| topics[0].field.display_name | Environmental Science |
| topics[0].score | 0.9993000030517578 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2302 |
| topics[0].subfield.display_name | Ecological Modeling |
| topics[0].display_name | Species Distribution and Climate Change |
| topics[1].id | https://openalex.org/T10005 |
| topics[1].field.id | https://openalex.org/fields/23 |
| topics[1].field.display_name | Environmental Science |
| topics[1].score | 0.9944000244140625 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2309 |
| topics[1].subfield.display_name | Nature and Landscape Conservation |
| topics[1].display_name | Ecology and Vegetation Dynamics Studies |
| topics[2].id | https://openalex.org/T10012 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.9894000291824341 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1311 |
| topics[2].subfield.display_name | Genetics |
| topics[2].display_name | Genetic diversity and population structure |
| funders[0].id | https://openalex.org/F4320337829 |
| funders[0].ror | |
| funders[0].display_name | National Wildlife Research Center |
| is_xpac | False |
| apc_list.value | 2510 |
| apc_list.currency | USD |
| apc_list.value_usd | 2510 |
| apc_paid.value | 2510 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 2510 |
| concepts[0].id | https://openalex.org/C81917197 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6204747557640076 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q628760 |
| concepts[0].display_name | Selection (genetic algorithm) |
| concepts[1].id | https://openalex.org/C107673813 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6066272258758545 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q812534 |
| concepts[1].display_name | Bayesian probability |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5152118802070618 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C2781175729 |
| concepts[3].level | 3 |
| concepts[3].score | 0.48724403977394104 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q7315823 |
| concepts[3].display_name | Resource distribution |
| concepts[4].id | https://openalex.org/C191413810 |
| concepts[4].level | 4 |
| concepts[4].score | 0.47003453969955444 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q17100952 |
| concepts[4].display_name | Bayesian hierarchical modeling |
| concepts[5].id | https://openalex.org/C206345919 |
| concepts[5].level | 2 |
| concepts[5].score | 0.46765583753585815 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q20380951 |
| concepts[5].display_name | Resource (disambiguation) |
| concepts[6].id | https://openalex.org/C18903297 |
| concepts[6].level | 1 |
| concepts[6].score | 0.45191603899002075 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[6].display_name | Ecology |
| concepts[7].id | https://openalex.org/C110121322 |
| concepts[7].level | 2 |
| concepts[7].score | 0.42056775093078613 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q865811 |
| concepts[7].display_name | Distribution (mathematics) |
| concepts[8].id | https://openalex.org/C160234255 |
| concepts[8].level | 3 |
| concepts[8].score | 0.34150785207748413 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q812535 |
| concepts[8].display_name | Bayesian inference |
| concepts[9].id | https://openalex.org/C119857082 |
| concepts[9].level | 1 |
| concepts[9].score | 0.27736860513687134 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[9].display_name | Machine learning |
| concepts[10].id | https://openalex.org/C154945302 |
| concepts[10].level | 1 |
| concepts[10].score | 0.27054744958877563 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[10].display_name | Artificial intelligence |
| concepts[11].id | https://openalex.org/C86803240 |
| concepts[11].level | 0 |
| concepts[11].score | 0.2588728666305542 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[11].display_name | Biology |
| concepts[12].id | https://openalex.org/C29202148 |
| concepts[12].level | 2 |
| concepts[12].score | 0.21898645162582397 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q287260 |
| concepts[12].display_name | Resource allocation |
| concepts[13].id | https://openalex.org/C33923547 |
| concepts[13].level | 0 |
| concepts[13].score | 0.1215524673461914 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[13].display_name | Mathematics |
| concepts[14].id | https://openalex.org/C134306372 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7754 |
| concepts[14].display_name | Mathematical analysis |
| concepts[15].id | https://openalex.org/C31258907 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[15].display_name | Computer network |
| keywords[0].id | https://openalex.org/keywords/selection |
| keywords[0].score | 0.6204747557640076 |
| keywords[0].display_name | Selection (genetic algorithm) |
| keywords[1].id | https://openalex.org/keywords/bayesian-probability |
| keywords[1].score | 0.6066272258758545 |
| keywords[1].display_name | Bayesian probability |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.5152118802070618 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/resource-distribution |
| keywords[3].score | 0.48724403977394104 |
| keywords[3].display_name | Resource distribution |
| keywords[4].id | https://openalex.org/keywords/bayesian-hierarchical-modeling |
| keywords[4].score | 0.47003453969955444 |
| keywords[4].display_name | Bayesian hierarchical modeling |
| keywords[5].id | https://openalex.org/keywords/resource |
| keywords[5].score | 0.46765583753585815 |
| keywords[5].display_name | Resource (disambiguation) |
| keywords[6].id | https://openalex.org/keywords/ecology |
| keywords[6].score | 0.45191603899002075 |
| keywords[6].display_name | Ecology |
| keywords[7].id | https://openalex.org/keywords/distribution |
| keywords[7].score | 0.42056775093078613 |
| keywords[7].display_name | Distribution (mathematics) |
| keywords[8].id | https://openalex.org/keywords/bayesian-inference |
| keywords[8].score | 0.34150785207748413 |
| keywords[8].display_name | Bayesian inference |
| keywords[9].id | https://openalex.org/keywords/machine-learning |
| keywords[9].score | 0.27736860513687134 |
| keywords[9].display_name | Machine learning |
| keywords[10].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[10].score | 0.27054744958877563 |
| keywords[10].display_name | Artificial intelligence |
| keywords[11].id | https://openalex.org/keywords/biology |
| keywords[11].score | 0.2588728666305542 |
| keywords[11].display_name | Biology |
| keywords[12].id | https://openalex.org/keywords/resource-allocation |
| keywords[12].score | 0.21898645162582397 |
| keywords[12].display_name | Resource allocation |
| keywords[13].id | https://openalex.org/keywords/mathematics |
| keywords[13].score | 0.1215524673461914 |
| keywords[13].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.1016/j.ecoinf.2024.102787 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S195809937 |
| locations[0].source.issn | 1574-9541, 1878-0512 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1574-9541 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Ecological Informatics |
| locations[0].source.host_organization | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_name | Elsevier BV |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_lineage_names | Elsevier BV |
| locations[0].license | cc-by-nc |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Ecological Informatics |
| locations[0].landing_page_url | https://doi.org/10.1016/j.ecoinf.2024.102787 |
| locations[1].id | pmh:oai:doaj.org/article:c6e9141e46084578ae3d7d1eee3dc7c1 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Ecological Informatics, Vol 82, Iss , Pp 102787- (2024) |
| locations[1].landing_page_url | https://doaj.org/article/c6e9141e46084578ae3d7d1eee3dc7c1 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5101447704 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-6991-5976 |
| authorships[0].author.display_name | Ryo Ogawa |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ryo Ogawa |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5048689531 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-5002-0120 |
| authorships[1].author.display_name | Guiming Wang |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Guiming Wang |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5070951030 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | L. Wes Burger |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | L. Wes Burger |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5073180940 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-3119-2514 |
| authorships[3].author.display_name | Bronson K. Strickland |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Bronson K. Strickland |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5048064168 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-2598-3192 |
| authorships[4].author.display_name | J. Brian Davis |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | J. Brian Davis |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5015789904 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-6035-3313 |
| authorships[5].author.display_name | Fred L. Cunningham |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Fred L. Cunningham |
| authorships[5].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1016/j.ecoinf.2024.102787 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Bayesian integrated species distribution models for hierarchical resource selection by a soaring bird |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10895 |
| primary_topic.field.id | https://openalex.org/fields/23 |
| primary_topic.field.display_name | Environmental Science |
| primary_topic.score | 0.9993000030517578 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2302 |
| primary_topic.subfield.display_name | Ecological Modeling |
| primary_topic.display_name | Species Distribution and Climate Change |
| related_works | https://openalex.org/W786367546, https://openalex.org/W4220780651, https://openalex.org/W3119278052, https://openalex.org/W2376454223, https://openalex.org/W2407375987, https://openalex.org/W3049691116, https://openalex.org/W2505726097, https://openalex.org/W2010643158, https://openalex.org/W2106867672, https://openalex.org/W3081214562 |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1016/j.ecoinf.2024.102787 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S195809937 |
| best_oa_location.source.issn | 1574-9541, 1878-0512 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1574-9541 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Ecological Informatics |
| best_oa_location.source.host_organization | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_lineage_names | Elsevier BV |
| best_oa_location.license | cc-by-nc |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Ecological Informatics |
| best_oa_location.landing_page_url | https://doi.org/10.1016/j.ecoinf.2024.102787 |
| primary_location.id | doi:10.1016/j.ecoinf.2024.102787 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S195809937 |
| primary_location.source.issn | 1574-9541, 1878-0512 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1574-9541 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Ecological Informatics |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_lineage_names | Elsevier BV |
| primary_location.license | cc-by-nc |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Ecological Informatics |
| primary_location.landing_page_url | https://doi.org/10.1016/j.ecoinf.2024.102787 |
| publication_date | 2024-08-23 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W3100738394, https://openalex.org/W1969126720, https://openalex.org/W2782948097, https://openalex.org/W1996083730, https://openalex.org/W2766749574, https://openalex.org/W3045671053, https://openalex.org/W2045506756, https://openalex.org/W4303629053, https://openalex.org/W6636249141, https://openalex.org/W1519813988, https://openalex.org/W2159720663, https://openalex.org/W2954318470, https://openalex.org/W2766717906, https://openalex.org/W3135392674, https://openalex.org/W2895556550, https://openalex.org/W1906551997, https://openalex.org/W2914719245, https://openalex.org/W2902748977, https://openalex.org/W6800944329, https://openalex.org/W2738345813, https://openalex.org/W2921800633, https://openalex.org/W3025949386, https://openalex.org/W2977733304, https://openalex.org/W2910146384, https://openalex.org/W6745404000, https://openalex.org/W2982619951, https://openalex.org/W2117445811, https://openalex.org/W2923362954, https://openalex.org/W1976124802, https://openalex.org/W2090588949, https://openalex.org/W2572670970, https://openalex.org/W4283204865, https://openalex.org/W2606554433, https://openalex.org/W2557668118, https://openalex.org/W2884767309, https://openalex.org/W2935813505, https://openalex.org/W2909556308, https://openalex.org/W1980497251, https://openalex.org/W2177312970, https://openalex.org/W1985020050, https://openalex.org/W2168113371, https://openalex.org/W4311479070, https://openalex.org/W2565806513, https://openalex.org/W6602806946, https://openalex.org/W2753306976, https://openalex.org/W2150847344, https://openalex.org/W2975358440, https://openalex.org/W4379744358, https://openalex.org/W2986514133, https://openalex.org/W2001539110, https://openalex.org/W2971952230, https://openalex.org/W3031740805, https://openalex.org/W2050775311, https://openalex.org/W2909344926, https://openalex.org/W2155931823, https://openalex.org/W1669701678, https://openalex.org/W2405211609, https://openalex.org/W2267014717, https://openalex.org/W2905502390, https://openalex.org/W3183744011, https://openalex.org/W7074659591, https://openalex.org/W3041630665, https://openalex.org/W2900012881, https://openalex.org/W2295501321, https://openalex.org/W2585078730, https://openalex.org/W2897732030, https://openalex.org/W2297380129, https://openalex.org/W2582743722, https://openalex.org/W2765429401, https://openalex.org/W3197156684, https://openalex.org/W4247288491, https://openalex.org/W1544024454, https://openalex.org/W1508643945 |
| referenced_works_count | 73 |
| abstract_inverted_index.We | 38, 72, 144 |
| abstract_inverted_index.at | 26, 33 |
| abstract_inverted_index.in | 166 |
| abstract_inverted_index.of | 54, 70, 84, 97, 117, 149, 154, 170 |
| abstract_inverted_index.on | 92, 178, 195 |
| abstract_inverted_index.to | 45, 60, 80 |
| abstract_inverted_index.Few | 13 |
| abstract_inverted_index.GPS | 156 |
| abstract_inverted_index.The | 109 |
| abstract_inverted_index.and | 30, 62, 89, 107, 133, 135, 186 |
| abstract_inverted_index.for | 23 |
| abstract_inverted_index.had | 175, 191 |
| abstract_inverted_index.how | 17 |
| abstract_inverted_index.the | 10, 27, 34, 50, 66, 82, 93, 112, 146, 163, 167, 179, 184, 200 |
| abstract_inverted_index.use | 32, 68 |
| abstract_inverted_index.Bird | 121, 130 |
| abstract_inverted_index.data | 142 |
| abstract_inverted_index.have | 15 |
| abstract_inverted_index.that | 40 |
| abstract_inverted_index.wind | 87 |
| abstract_inverted_index.with | 119, 128, 140 |
| abstract_inverted_index.Count | 131 |
| abstract_inverted_index.ISDMs | 110, 150 |
| abstract_inverted_index.birds | 1, 19 |
| abstract_inverted_index.built | 73 |
| abstract_inverted_index.data, | 123, 132 |
| abstract_inverted_index.eBird | 141 |
| abstract_inverted_index.level | 29, 36 |
| abstract_inverted_index.range | 5, 24, 51, 95, 114, 125, 180, 196 |
| abstract_inverted_index.rates | 139 |
| abstract_inverted_index.space | 31, 67 |
| abstract_inverted_index.their | 21 |
| abstract_inverted_index.using | 151 |
| abstract_inverted_index.white | 99 |
| abstract_inverted_index.would | 48, 64 |
| abstract_inverted_index.Survey | 122 |
| abstract_inverted_index.affect | 49, 65 |
| abstract_inverted_index.annual | 11 |
| abstract_inverted_index.cycle. | 12 |
| abstract_inverted_index.during | 9, 105 |
| abstract_inverted_index.models | 78, 161, 165 |
| abstract_inverted_index.range) | 7 |
| abstract_inverted_index.select | 20 |
| abstract_inverted_index.summer | 106, 113, 134 |
| abstract_inverted_index.winter | 124, 136 |
| abstract_inverted_index.(ISDMs) | 79 |
| abstract_inverted_index.Climate | 173 |
| abstract_inverted_index.between | 183, 199 |
| abstract_inverted_index.climate | 85 |
| abstract_inverted_index.effects | 83, 177, 194 |
| abstract_inverted_index.exhibit | 2 |
| abstract_inverted_index.fitness | 46 |
| abstract_inverted_index.flights | 63 |
| abstract_inverted_index.pelican | 155 |
| abstract_inverted_index.related | 44, 59 |
| abstract_inverted_index.species | 28, 76, 159 |
| abstract_inverted_index.studies | 14 |
| abstract_inverted_index.whereas | 56, 189 |
| abstract_inverted_index.winter. | 108 |
| abstract_inverted_index.American | 98 |
| abstract_inverted_index.Bayesian | 74 |
| abstract_inverted_index.Breeding | 120 |
| abstract_inverted_index.breeding | 185 |
| abstract_inverted_index.datasets | 153 |
| abstract_inverted_index.directly | 43 |
| abstract_inverted_index.dynamics | 8, 96 |
| abstract_inverted_index.evaluate | 81 |
| abstract_inverted_index.examined | 16 |
| abstract_inverted_index.grounds, | 188 |
| abstract_inverted_index.habitats | 22 |
| abstract_inverted_index.jointly. | 143 |
| abstract_inverted_index.opposite | 176 |
| abstract_inverted_index.pelican) | 104 |
| abstract_inverted_index.pelicans | 100, 118 |
| abstract_inverted_index.seasonal | 3, 94 |
| abstract_inverted_index.seasons. | 201 |
| abstract_inverted_index.Christmas | 129 |
| abstract_inverted_index.Migratory | 0 |
| abstract_inverted_index.Pelecanus | 101 |
| abstract_inverted_index.estimated | 111 |
| abstract_inverted_index.evaluated | 145 |
| abstract_inverted_index.intensity | 138 |
| abstract_inverted_index.landcover | 90 |
| abstract_inverted_index.migrants, | 55 |
| abstract_inverted_index.migrants. | 71 |
| abstract_inverted_index.migratory | 18 |
| abstract_inverted_index.movements | 61 |
| abstract_inverted_index.occupancy | 25, 52, 115, 126, 171, 181, 197 |
| abstract_inverted_index.space-use | 137 |
| abstract_inverted_index.variables | 42, 58 |
| abstract_inverted_index.Integrated | 158 |
| abstract_inverted_index.components | 47 |
| abstract_inverted_index.conditions | 174 |
| abstract_inverted_index.consistent | 193 |
| abstract_inverted_index.geographic | 4 |
| abstract_inverted_index.individual | 35 |
| abstract_inverted_index.integrated | 75 |
| abstract_inverted_index.landcovers | 190 |
| abstract_inverted_index.locations. | 157 |
| abstract_inverted_index.predictive | 147, 168 |
| abstract_inverted_index.relatively | 192 |
| abstract_inverted_index.(hereafter, | 6, 103 |
| abstract_inverted_index.conditions, | 86, 88 |
| abstract_inverted_index.environment | 57 |
| abstract_inverted_index.independent | 152 |
| abstract_inverted_index.intensities | 69 |
| abstract_inverted_index.performance | 148, 169 |
| abstract_inverted_index.compositions | 91 |
| abstract_inverted_index.distribution | 77, 160 |
| abstract_inverted_index.hypothesized | 39 |
| abstract_inverted_index.non-breeding | 187 |
| abstract_inverted_index.outperformed | 162 |
| abstract_inverted_index.environmental | 41 |
| abstract_inverted_index.probabilities | 53, 116, 127, 182, 198 |
| abstract_inverted_index.occupancy-only | 164 |
| abstract_inverted_index.probabilities. | 172 |
| abstract_inverted_index.erythrorhynchos | 102 |
| abstract_inverted_index.simultaneously. | 37 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.04383464 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |