Spatiotemporal Patterns of Distribution and Drivers of Neonicotinoid Insecticide Fate in Canadian Prairie Pothole Wetlands
Notice bibliographique
Résumé
Designed for the protection of major agricultural crops, neonicotinoids are the fastest-growing class of insecticides used against a broad spectrum of insect pests. Although neonicotinoid toxicity toward non-target organisms (e.g., bees, aquatic insects) has been well-studied, less is known about their distribution of use, transport, and fate in North American agroecosystems. This is especially true of neonicotinoid interactions with wetlands in the Canadian Prairies. Between 2009 and 2012, neonicotinoid use as a seed treatment increased by 30% across the Canadian Prairies. During spring 2012 to spring 2013, I sampled water and sediment from 136 wetlands situated in a range of crop types across central Saskatchewan to determine the extent of neonicotinoid contamination. Wetlands situated in oat, canola, and barley fields consistently contained higher neonicotinoid concentrations in water than in grasslands, but no single crop influenced overall detections. Neonicotinoid detections in water varied from 16% (fall 2012) to 91% (spring 2013) with peak concentrations up to 3110 ng/L found in summer. I found numerous detections of neonicotinoids in spring, after ice-off, but before seeding. Through sampling snow, snow meltwater, and soil particulates from previously treated (clothianidin) and untreated fields, meltwater showed the strongest relationship to initial spring concentrations in wetland water. Neonicotinoid concentrations increased with time in shallow temporary wetlands which appeared most at risk for annual contamination. While snowmelt contamination influenced water concentrations in spring, peak concentrations in wetlands were consistently found during summer sampling completed in 2012-2014. Rapid wetland assessments completed on 238 wetlands (summer of 2012 and 2013) revealed key ecological, hydrological and landscape features that influenced neonicotinoid detections and peak concentrations in Prairie wetlands. The results of my exploratory analysis indicated that plant community composition is a key indicator and/or driver of both detection and concentration of neonicotinoids in Prairie wetlands. In particular, specific shallow marsh plants were commonly associated with either higher (e.g., Scirpus validus) or lower (e.g., Mentha arvensis) neonicotinoid concentrations in natural wetlands suggesting wetland macrophytes in this zone may be either indicators of agricultural disturbance intensity or differentially capable of accumulating the insecticide in its tissue. Therefore, in 2014, I conducted an outdoor microcosm experiment to evaluate thiamethoxam uptake from water by Typha latifolia and Alisma triviale using two concentrations over a 7-day period. Experimental results found some trace positive detections but no quantifiable accumulation of the insecticide in plant tissues. This is despite the fact that results of my 2015 field study found species of Typha, Alisma and Equisetum had neonicotinoids more frequently detected in their tissues, at concentrations ranging from 1.01-8.44 ug/kg. My findings demonstrate that neonicotinoid distribution and fate in Canadian Prairie agroecosystems is driven by interactions between ecological, hydrological, and landscape characteristics. Consequently, these drivers regulate neonicotinoid exposure and persistence in ecologically important regional wetlands. In order to effectively conserve these critical waterbodies, conservation planning should consider the importance of maintaining naturally diverse vegetation zones to mitigate insecticide exposure to wetland-dependant organisms.
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 | 0,001 | 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 ».