Supporting Pollinators in Canola Fields: The Role of Landscape Composition for Honey Bee Nutrition and Wild bee Diversity
Notice bibliographique
Résumé
The global decline of pollinator populations poses a significant threat to terrestrial biodiversity and human food security. This crisis is largely driven by the intensification of agriculture, which replaces diverse, resource-rich landscapes with simplified monocultures. This change creates a basic contradiction: farming, which often relies on pollination services, is also damaging the ecological foundations needed to support healthy pollinator communities. This issue is particularly evident in the Canadian Prairies, where the conversion of native grasslands into one of the world's largest canola-producing regions has been extensive. These agroecosystems offer a massive but short-lived floral blooms that are insufficient to sustain pollinators throughout their life cycles. Despite the region's economic reliance on pollination, there is a critical knowledge gap regarding the structure of wild bee communities and the floral resources available to them within these highly modified landscapes. To further investigate, this thesis established two interconnected primary objectives. The first was to quantify the abundance, species richness, and community composition of wild bees across the Saskatchewan canola belt and to determine their relationship with the surrounding landscape structure, particularly the proportion of semi-natural habitat (SNH). The second, complementary objective was to use managed honey bees (Apis mellifera) as landscape-level bio-samplers to identify the key floral resources sustaining the entire pollinator assemblage. This integrated study was conducted at ten agricultural sites across Saskatchewan during the 2024 season. Wild bees were collected monthly (June-August) using a combination of pan and vane traps, while corbicular pollen was simultaneously collected from honey bee colonies at the same locations. The taxonomic identity of pollen was determined using DNA metabarcoding. Landscape composition was quantified from satellite imagery, and the data were analyzed using Generalized Linear Models (GLMs) and multivariate methods to assess the influence of landscape and seasonality. We identified 54 species of wild bees. We found a strong positive correlation between SNH and wild bee abundance and species richness. Populations declined precipitously in landscapes with less than 10% SNH. These findings provide a consistent picture: pollen analysis revealed that approximately 80% of the floral resources collected by honey bees came from non-crop forbs and shrubs within these SNH patches. The overall pollen diet was dominated by Brassica, Melilotus, and Syringa but showed significant seasonal variation. This confirms that canola alone is insufficient for season-long nutrition. Consequently, pollen diversity was significantly higher in more heterogeneous landscapes. This research provides clear, actionable evidence that even small, remnant patches of semi-natural habitat are not marginal lands but critical life-support systems within intensive agroecosystems. They provide the essential nesting sites and continuous floral nutrition required to maintain both wild and managed bees’ populations. Therefore, the conservation and restoration of SNH should be considered a fundamental strategy for building agricultural resilience, ensuring sustainable crop pollination, and safeguarding biodiversity in the Canadian Prairies and similar systems worldwide.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».