MétaCan
Menu
Retour à la cohorte
Enregistrement W3024795690 · doi:10.13140/rg.2.2.17163.82729

Investigating Red Knot Migration Ecology Along The Georgia Coast: Fall 2015 And Spring 2013, 2015-16 Season Summaries

2017· article· en· W3024795690 sur OpenAlexaboutno aff
F. M. Smith

Notice bibliographique

RevueW&M Publish (College of William & Mary) · 2017
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueMarine and fisheries research
Établissements canadiensnon disponible
Organismes subventionnairesU.S. Geological SurveyU.S. Fish and Wildlife ServiceVirginia Commonwealth UniversityNational Fish and Wildlife FoundationSouthern Company
Mots-clésSpring (device)EcologyKnot (papermaking)GeographyBiologyEngineering

Résumé

récupéré en direct d'OpenAlex

The rufa subspecies of the Red Knot (Calidris canutus) has declined significantly in the past 35 years, leading to federal listing (US Fish and Wildlife Service Federal Register Vol. 79 No. 238, 2014a) under the Endangered Species Act in the United States (16 U.S.C. 1531 et. seq) and Canada (COSEWIC 2007, SARA 2007). The determination of regional population estimates and identification of major stopover sites are considered to be the highest priority for the Georgia Department of Natural Resources State Wildlife Action Plan (2015), the Atlantic Flyway Shorebird Business Strategy (Winn et al. 2013), the US Shorebird Plan (Brown et al. 2001), the USFWS Red Knot Spotlight Species Action Plan (2010), and the Western Hemisphere Shorebird Reserve Network (WHSRN) Red Knot Conservation Plan for the Western Hemisphere (Niles et al. 2010a). The Georgia Department of Natural Resources State Wildlife Action Plan ranks the Red Knot as a high priority species (with state status of “Rare”) and ranks research of the Red Knot as one of the primary conservation actions needed within the state. A large percentage (3-6%) of Red Knots have been previously captured and tagged with unique 2 to 3 digits alpha-numeric bands. This marked population allows for mark-resight studies of migratory populations of Red Knots with no capturing involved. We detected a total of 43,686 Red Knots during daily surveys in spring 2016 along the Georgia Coast; of those, 10,029 were scanned for flags, and 1,255 individually banded Red Knots were resighted within the spring migrant population. A total of 158 marked to unmarked ratios were recorded during the field season, with an average of 3.8% of Red Knots individually marked over the course of the spring. The estimated superpopulation size for the spring 2016 season is 11,948 Red Knots (95% credible interval: 9,821 – 16,405). The mean Minimum-length-of-stay (MINLOS) for Red Knots staging in Georgia was 9.8day±11.1SD. A total of 3,805 Red Knots were detected on daily surveys during fall migration 2015; of those, 2,231 individuals were scanned for flags, and 140 individually banded Red Knots were resighted within that group. A total of 78 marked to unmarked ratios were recorded during the field season, with an average 3.4% of Red Knots banded. A total of 68 individuals were identified during the fall season, which was not enough data to analyze the population migrating through the Georgia Coast in fall 2015. We determined relative use along the Georgia Coast in spring and fall migration through a combination of aerial and ground based surveys. We created a GIS database of all encounters of Red Knots along the barrier Island chain, totaling 299 locations and 98,155 Red Knots mapped. The Georgia Coast is a major stopover area annually for rufa Red Knots in spring migration and in certain years in fall migration. The superpopulation utilizing the coast in fall migration can exceed 23,000 birds (Lyons et al. 2017 in press) and the estimates of spring migration superpopulation from this study ranges between 8,000 and 14,000 birds. The total estimated population of rufa Red Knots is 42,000 birds (Andres et al. 2012), suggesting that a high percentage of rufa knots are using the Georgia Coast in spring and in some years fall migration. There appears to be less variation in spring migration superpopulations between years than in fall migration, suggesting a more stable (but less abundant) food source for spring migrants.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,121
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,002
Communication savante0,0000,002
Science ouverte0,0010,002
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,017
Tête enseignante GPT0,247
Écart entre enseignants0,230 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueW&M Publish (College of William & Mary)Même sujetMarine and fisheries researchTravaux en français237 207