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Record W3135265270 · doi:10.1017/s003118202100038x

Effects of multiple stressors on northern leopard frogs in agricultural wetlands

2021· article· en· W3135265270 on OpenAlexaff
David J. Marcogliese, Kayla C. King, Kieran A. Bates

Bibliographic record

VenueParasitology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsConcordia UniversityEnvironment and Climate Change CanadaFisheries and Oceans Canada
Fundersnot available
KeywordsBiologyLeopardStressorWetlandAgricultureEcologyFisheryZoologyAgroforestry

Abstract

fetched live from OpenAlex

Natural and anthropogenic stressors, including parasites and pesticides, may induce oxidative stress in animals. Measuring oxidative stress responses in sentinel species that are particularly responsive to environmental perturbations not only provides insight into host physiology but is also a useful readout of ecosystem health. Newly metamorphosed northern leopard frogs (Lithobates pipiens), a sentinel species, were collected from agricultural and non-agricultural wetlands exposed to varying concentrations of the herbicide atrazine. Significant effects of certain parasites' abundance and their interaction with atrazine exposure on frog oxidative stress were identified. Specifically, increased protein levels were detected in frogs infected with echinostome metacercariae. In addition, the nematode Oswaldocruzia sp. was significantly associated with increased thiol concentration and catalase activity. Significant parasite × atrazine interactions were observed for atrazine exposure and the abundance of Oswaldocruzia sp. on thiol, as thiol concentrations increased with parasite abundance at low atrazine localities and decreased in high atrazine wetlands. In addition, a significant interaction between the abundances of Oswaldocruzia sp. and gorgoderid trematodes on thiol concentrations was observed. These findings demonstrate that studies of oxidative stress on animals in natural ecosystems should account for the confounding effects of parasitism, particularly for amphibians in agricultural landscapes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.231
Teacher spread0.226 · 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 teacher head, 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

Citations11
Published2021
Admission routes1
Has abstractyes

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