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Enregistrement W7066715245

Investigating Red Knot Migration Ecology along the Georgia and South Carolina Coasts: Spring 2019 Season Summaries

2019· article· en· W7066715245 sur OpenAlexaboutno aff

Notice bibliographique

RevueW&M Publish (College of William & Mary) · 2019
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueAstrophysical Phenomena and Observations
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWildlifeWildlife refugePopulationEndangered speciesFlywayHabitatEcoregion
DOInon disponible

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). Evidence for the decline is seen in long-term surveys of a major spring staging site (Dunne et al 1982, Clark et al. 1993, Niles et al. 2008) and the largest known over-wintering site (Morrison et al. 2004). In only 30 years, the estimated population has declined from 100,000-150,000 to possibly below 30,000 (Niles et al. 2007) leading some researchers to suggest the population is highly vulnerable to extinction (Baker et al. 2004). 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 band resight program was initiated along the Georgia coastal barrier islands during the fall of 2011 and spring of 2013 and 2015-2016 giving baseline information for those seasons (Lyons et al. 2017, Smith et al. 2017). A trapping and tagging project was initiated in South Carolina in recent years, though there has been no systematic resight effort within the state. The patterns observed in both studies suggest that Red Knots are using the south-Atlantic through Delaware Bay in spring as an open network of staging areas. Recent tagging results in South Carolina have documented direct spring flights from South Carolina to James Bay, suggesting that the south-Atlantic stopovers are more important in the life-cycle of shorebirds than is currently thought. It is currently unknown what percentage of Red Knots use the direct flight strategy vs. stopping in Delaware Bay on their northbound migration. Winter resighting work conducted in South Carolina suggests that virtually no Red Knots wintering along the south-Atlantic use Delaware Bay in spring migration. Although movement and settlement “decisions” are likely influenced by foraging conditions throughout the network, investigations into the factors driving movements during migration is necessary to better understand Red Knot migration ecology. This is critical in developing appropriate stopover models and adaptive management tools for land managers. The Georgia Department of Natural Resources, the South Carolina Department of Natural Resources, the US Fish and Wildlife Service, and The Center for Conservation Biology will initiate a Red Knot tagging and resighting program along the Atlantic Coast of Georgia during the spring of 2019 to be paired with the ongoing programs within Delaware Bay and elsewhere along the flyway. This project will provide critical data that will be used to analyze the ongoing questions regarding Red Knot habitat choice decision making in the south Atlantic Coast in spring. 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. A total of 27,356 Red Knots were detected during daily surveys in spring 2019 along the Georgia and South Carolina Coasts; of those, 4,917 were scanned for flags, and 315 individually banded Red Knots were resighted a total of 523 times from within the spring migrant population. A total of 71 marked to unmarked ratios were recorded during the field season, with an average of 3.6% of Red Knots individually marked over the course of the spring. The rough estimate for the total number of knots cycling through during the spring season is estimated superpopulation size for the spring 2019 season is 8,750 (3.6% of birds tagged and 315 individuals recorded). 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) and the rough estimate of spring migration superpopulation from this study is approximately 8,750 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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,019
Score d'incertitude au seuil0,756

Scores Codex et Gemma par catégorie

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

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 Opus0,008
Tête enseignante GPT0,198
Écart entre enseignants0,190 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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
Publié2019
Routes d'admission1
Résumé présentoui

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