Evaluation of the Copper River Delta Dusky Canada Goose Survey and the Pacific Flyway's Management Index
Notice bibliographique
Résumé
The Copper River Delta (CRD) in south-central Alaska is the primary breeding area for dusky Canada geese (Branta canadensis occidentalis). The Alaska Department of Fish and Game (ADFG), United States Forest Service (USFS), and United States Fish and Wildlife Service (USFWS) conduct breeding-ground surveys to inform the Pacific Flyway Council harvest management decisions and regulations. The current management index (described in detail below) uses aerial survey counts corrected for detection by the long-term average ratio of aerial counts to ground-based nest counts. Because of the 1964 earthquake that resulted in uplift and subsequent vegetation growth, the aerial detection of geese has been thought to decrease through time and the use of a constant correction factor is suspect. During the summer of 2020, personnel from the 3 agencies met to discuss the appropriateness of the index as it was currently calculated. The greatest concern identified was in the use of a constant detection correction derived from sparse historic data, and this report is an attempt to evaluate the components of the detection correction constant, as well as the management index in general, and provide potential alternatives going forward. Because the detection correction involves a ratio of the ground-based nest estimates to aerial-observed indicated pairs (hereafter 'ratio' or 'ground-to-air ratio'), change in the ratio could be due to change in either the numerator or denominator. Therefore, we evaluated methods and any change in methods or protocol associated with all survey components. Our goal is to evaluate the current design of surveys, the calculation of the management index, and to assess change in various components of the index, not to provide detailed recommendations for re-design of a survey. Such a re-design should take place in a separate effort after this evaluation, and after a general approach, perhaps different than the current one, is decided upon by the various stakeholders. Previous attempts at examining the ratio and change in ground-to-air ratio was limited to simple linear regression between air and ground point estimates calculated at the scale of each nest plot strata (Hodges 2007). This made the assumption that the relationship is linear, that the nest strata are the appropriate scale to calculate the ratio, that all point estimates are equally estimated, and a mean ratio across time is appropriate for calculating a correction factor. Because there is now more data available and more statistical techniques available to estimate the relationship between nests and aerially-observed geese, we also estimated the ratio at various scales and using different techniques to see if this leads to different conclusions. We were primarily concerned with annual variation in the ratio and distinguishing true process variation in this ratio from sampling variance (statistical noise). Current treatment of the ratio ignores annual (process) variation in the ratio, and we feel strongly that this is not appropriate if there is evidence for annual variation. Because annual variation in the ratio has never been estimated, we attempt to estimate this and apply it to the calculation of the management index.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».