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Enregistrement W2560443772 · doi:10.2134/csa2015-60-9-2

Do soils and geology always protect groundwater from bacterial contamination?

2015· article· en· W2560443772 sur OpenAlexaboutno aff
Madeline Fisher

Notice bibliographique

RevueCSA News · 2015
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueSoil erosion and sediment transport
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWater tableGroundwaterGeologistVadose zoneSurpriseGeologyEnvironmental scienceSociologyGeotechnical engineeringPaleontology

Résumé

récupéré en direct d'OpenAlex

Photo courtesy of Emmanuelle Arnaud Countless ways exist for water-borne bacteria to die or get stuck in soil and geologic sediments. This is why scientists tend to assume that a thick layer of these materials will keep pathogens in surface-applied manures from seeping down into groundwater. University of Guelph geologist Emmanuelle Arnaud and her colleagues thought so, too—until they conducted the work that appears in the September–October issue of the Journal of Environmental Quality. To their surprise, they detected E. coli bacteria in groundwater one week after an application of liquid swine manure on a farm field, even though 12 m of soil and glacial sediments lay in between. So surprised were they, in fact—especially by the apparent speed of the microbes’ movement—that “we spent a lot of time thinking: Is this really plausible?” says Arnaud, who led the research with her student, Anna Best. “It requires further testing, but I think it's a fair hypothesis for future work—that this is indeed happening. Now we have to figure out exactly how it can happen and how prevalent it may be elsewhere.” Arnaud points out that soil scientists often study the fate of bacterial contaminants in the uppermost soil layers. People also routinely find bacteria in drinking water wells. But rarely has research examined what's occurring in the middle region—or the vadose zone—which extends from the land surface to the top of the groundwater table. “So, ours was a very basic hypothesis,” she says. “Will we find bacteria making their way down and what are some of the factors that affect their transport?” Those questions are becoming more critical as animal agriculture intensifies around the globe. But they gained especial importance in Ontario after an outbreak of E. coli O157:h7 and Campylobacter was linked to groundwater contamination by manure-borne pathogens. As part of a larger study of non-point source pollution of groundwater by both nitrate and E. coli, Arnaud and an interdisciplinary team carried out their work with funding from the Ontario Ministry of Agriculture and Rural Affairs. Although the scientists did detect low levels of E. coli in groundwater before and after their experiment, what they observed one week after the manure application was a spike in E. coli concentrations that lasted for about five weeks. Because the scientists didn't fingerprint the E. coli, they can't conclusively say that the bacteria cultured from the groundwater came from the manure. But the timing is persuasive. “To us, it's a really telling signal: We applied the manure, and a week later the bacteria showed up,” Arnaud says. “That's super-fast travel.” This paper is part of a JEQ special collection on Microbial Transport and Fate in the Subsurface The question then became: Why was it so fast? The geologic materials underlying the research site are fairly coarse-grained and permeable. So, “if bacteria were going to get through, they would get through in a place like this,” Arnaud says. At the same time, their calculations indicate that bacteria in bulk matrix water would take four to seven years to travel through the site's 12 m of sediments, even assuming the materials all fell into the upper range of estimated permeability. The team therefore suspects that preferential flow pathways are behind the quicker transport. The site isn't tile-drained, but previous research there uncovered movement of fecal bacteria through soil macropores. Below the soil, the researchers also found areas of coarse-grained materials that are likely connected to fractures in the bedrock. And there may be fractures in finer-grained deposits that would otherwise be expected to slow water flow and protect the underlying aquifer. If this type of geological information were collected more often, Arnaud thinks it could improve estimates of microbial transport rates through the subsurface and help refine the vulnerability maps that scientists use to determine the susceptibility of aquifers to contamination. At the very least, the matter deserves a closer look. “We can't take these results too far. The next step would be to do actual tracer studies and then check if we can replicate those fast [transport] times,” Arnaud says. “But it's nice to start to put numbers on this and to ask: Should we rethink how we perceive these thicker vadose zones?” Adapted from Arnaud, E., A. Best, B. Parker, R. Aravena, and K. Dunfield. 2015. Transport of Escherichia coli through a thick vadose zone. J. Environ. Qual. 44(5). Access the full article online at https://doi.org/10.2134/jeq2015.02.0067

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,465
Score d'incertitude au seuil0,852

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,040
Tête enseignante GPT0,225
Écart entre enseignants0,185 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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