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Record W4400644639 · doi:10.1016/j.envpol.2024.124563

Variability of faecal microbiota and antibiotic resistance genes in flocks of migratory gulls and comparison with the surrounding environment

2024· article· en· W4400644639 on OpenAlexfundno aff
Dayana Jarma, Oriol Sacristán‐Soriano, Carles Borrego, Francisco Hortas, Juan Manuel Peralta‐Sánchez, José Luís Balcázar, Andy J. Green, Esteban Alonso, Alexandre Sànchez-Melsió, Marta I. Sánchez

Bibliographic record

VenueEnvironmental Pollution · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersGeneralitat de CatalunyaUniversidad de CádizAgencia Estatal de InvestigaciónMinisterio de Ciencia, Innovación y UniversidadesCentres de Recerca de CatalunyaCanadian Institute for Advanced Research
KeywordsFlockBiologyWetlandEcologyHabitatMobile genetic elementsMicrobiomeResistance (ecology)Gene

Abstract

fetched live from OpenAlex

Gulls commonly rely on human-generated waste as their primary food source, contributing to the spread of antibiotic-resistant bacteria and their resistance genes, both locally and globally. Our understanding of this process remains incomplete, particularly in relation to its potential interaction with surrounding soil and water. We studied the lesser black-backed gull, Larus fuscus, as a model to examine the spatial variation of faecal bacterial communities, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) and its relationship with the surrounding water and soil. We conducted sampling campaigns within a connectivity network of different flocks of gulls moving across functional units (FUs), each of which represents a module of highly interconnected patches of habitats used for roosting and feeding. The FUs vary in habitat use, with some gulls using more polluted sites (notably landfills), while others prefer more natural environments (e.g., wetlands or beaches). Faecal bacterial communities in gulls from flocks that visit and spend more time in landfills exhibited higher richness and diversity. The faecal microbiota showed a high compositional overlap with bacterial communities in soil. The overlap was greater when compared to landfill (11%) than to wetland soils (6%), and much lower when compared to bacterial communities in surrounding water (2% and 1% for landfill and wetland water, respectively). The relative abundance of ARGs and MGEs were similar between FUs, with variations observed only for specific families of ARGs and MGEs. When exploring the faecal carriage of ARGs and MGEs in bird faeces relative to soil and water compartments, gull faeces were enriched in ARGs classified as High-Risk. Our results shed light on the complex dynamics of antibiotic resistance spread in wild bird populations, providing insights into the interactions among gull movement and feeding behavior, habitat characteristics, and the dissemination of antibiotic resistance determinants across environmental reservoirs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.236
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2024
Admission routes1
Has abstractyes

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