Breeding Habitat Structure And Use By Kansas-Occurring Black Rail
Notice bibliographique
Résumé
Two subspecies of Black Rail Laterallus jamaicenis occur in the United States, and neither has been studied extensively. Of the two, the Eastern subspecies L. j. jamaicenis has a larger range, but has been studied to a lesser degree than the California subspecies (L. j. coturniculus Eastern Black Rail are known to breed at several locations in Kansas, but as in other inland populations, precisely where these individuals overwinter is unknown. Additionally, little information is available on characteristics of breeding habitat for inland Eastern Black Rail populations, and few studies have investigated the effect of habitat management techniques on these populations. Eastern Black Rail are rnost often observed in Kansas at Quivira National Wildlife Refuge NWR and private lands surrounding it. Call playback surveys were conducted in the summers of 2009 and 2010 to locate breeding individuals and identify nesting habitat. Drift-fences and traps were set in locations where individual Black Rail were detected, and sound samples were used to attract individuals for capture. Rectrices and body coverts were plucked from similar regions on two captured individuals and used for deuterium stable isotope analysis. Coverts had average deuterium values of -86.2 and -77.8 per mil, respectively. These values are more typical for southern Canada and portions of the western United States. These feather values suggest that Kansas occurring Black Rail either winter away from the Gulf Coast, in contrast to current understanding, or grow feathers during or soon after spring migration. Quivira NWR and surrounding private lands use prescribed burning, grazing and haying to manage vegetation in the wet-meadow habitat that the rails typically occupy. To characterize breeding habitat, I quantified vertical vegetation structure, water presence and depth, and plant height in areas where Black Rail responded during playback surveys. A Kruskal-Walis one-way analysis of variance was used to compare these variables among 13 treatment types. Although test results indicated these variables were significantly different among treatment types, a nonparametric Tukey's post-hoc test could not detect where the differences occurred. A backward stepwise (Wald) logistic regression indicated higher percentages of dead vegetation in upper vertical layers and plant height positively influenced rail presence, whereas a higher percentage of living vegetation at lower layers negatively influenced rail presence (Nagelkerke R Square 0.57, p < 0.001). Black Rail were most often detected in sections witl1 moderate levels of disturbance (e.g., burned annually, burned and grazed), while areas with higher levels of disturbance ( e.g., annual haying, haying and burning) did not appear to possess suitable habitat, as no rails were detected in these locations. J:vloderately disturbed areas, such as those burned every two years, might contain the mosaic of living and dead vegetation necessary for Black Rail nesting habitat in this portion their breeding range.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».