Impact of management treatments on waterfowl use of dense nesting cover in the Canadian parklands
Notice bibliographique
Résumé
Abstract Periodic treatment of established stands of dense nesting cover (DNC) is a recommended practice to maintain cover quality, but little information exists on the magnitude and duration of treatment effects on nesting waterfowl. During 1998–2001, we examined the effect of management treatments on vegetative characteristics and waterfowl nest success and density in fields of DNC seeded to introduced and native grass and forb mixes in the parklands of Saskatchewan and Manitoba. We measured vegetation height–density and litter depth within fields and located and monitored 1,927 duck nests within 33–42 fields/yr ranging in size from 6 ha to 62 ha. We considered a series of models examining the influence of grass type and management treatment (GTMT) and years post‐management (YPM) on vegetative characteristics, nest success, and nest density while including covariates potentially affecting these response variables. Visual obstruction and litter depth were lowest in native‐burned fields and greatest in introduced‐hayed fields. Visual obstruction was low the year following management, peaked 2–3 YPM, and remained at intermediate levels through ≥6 YPM. Litter depth remained low for the first 3 YPM and increased thereafter. Nest success and nest density varied little among GTMT. Nest success was high (14.3%) the year following a management treatment, low (6.5%) at 2 YPM, and moderate thereafter. Nest success decreased with percent cropland in the surrounding landscape. Nest density was 0.7 nests/ha the first year following management, increased to approximately 1.3 nests/ha in years 2–3, and declined back to approximately 0.7 nests/ha for ≥6 YPM. Nest density decreased with field size and increased with the area of small wetlands, percent cropland, and percent wetland within surrounding landscapes. Nest density tracked vegetation density as expected and our results indicate a possible trade‐off between nest density and nest success. Given ancillary data on small mammal and insect prey in our study fields, and evidence from other studies, we speculate that DNC fields may act as prey reservoirs during years of peak vegetative density with a consequent reduction in nest survival. Therefore, management to increase waterfowl production based on our results needs to consider the interaction of treatment effects, competing habitats, and surrounding landscape composition. © 2011 The Wildlife Society.
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 | 0,000 | 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) | 0,001 | 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 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 ».