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Record W3091467056 · doi:10.1101/2020.10.01.322370

Widespread agrochemicals differentially affect zooplankton biomass and community structure

2020· preprint· en· W3091467056 on OpenAlexafffund
Marie‐Pier Hébert, Vincent Fugère, Beatrix E. Beisner, Rowan D. H. Barrett, Graham Bell, B. Jesse Shapiro, Viviane Yargeau, Andrew Gonzalez, Gregor F. Fussmann

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsMcGill Genome CentreUniversité de MontréalUniversité du Québec à Trois-RivièresMcGill UniversityUniversité du Québec à Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaLiber Ero FoundationGroupe de recherche interuniversitaire en limnologieNational Geographic Society
KeywordsBiomass (ecology)ZooplanktonAgrochemicalGlyphosateEcosystemPesticideEcotoxicologyCommunity structureEcologyEnvironmental scienceSpecies richnessBiologyAgronomyAgriculture

Abstract

fetched live from OpenAlex

Abstract Anthropogenic environmental change is causing habitat deterioration at unprecedented rates in freshwater ecosystems. Despite increasing more rapidly than other agents of global change, synthetic chemical pollution –including agrochemicals such as pesticides– has received relatively little attention in freshwater biotic assessments. Determining the effects of multiple agrochemicals on complex community and ecosystem properties remains a major challenge, requiring a cross-field integration of ecology and ecotoxicology. Using a large-scale array of experimental ponds, we investigated the response of zooplankton community properties (biomass, composition, diversity metrics) to the individual and joint presence of three widespread agrochemicals: the herbicide glyphosate, the neonicotinoid insecticide imidacloprid, and fertilisers. We tracked temporal variation in community biomass and structure (i.e., composition, diversity metrics) along single and combined pesticide gradients (each spanning eight levels), under low (mesotrophic) and high (eutrophic) nutrient-enriched conditions, and quantified (i) agrochemical interactions, (ii) response threshold concentrations, and (iii) community resistance and recovery. We found that major zooplankton groups differed in their sensitivity to pesticides: ≥3 µg/L imidacloprid impaired copepods, rotifers collapsed at glyphosate levels ≥0.3 mg/L, whereas some cladocerans were highly tolerant to pesticide contamination. Glyphosate was the most influential driver of community properties, with biomass and community structure responding rapidly but recovering unequally over time. Zooplankton biomass showed little resistance when first exposed to glyphosate, but rapidly recovered and even increased with glyphosate concentration; in contrast, richness declined in more contaminated ponds but failed to recover. Our results show that the biomass of tolerant taxa compensated for the loss of sensitive species, conferring greater resistance upon subsequent exposure; a rare example of pollution-induced community tolerance in freshwater metazoans. Overall, zooplankton biomass appears to be more resilient to agrochemical pollution than community structure, yet all community properties measured in this study were affected at glyphosate levels below common water quality guidelines in North America.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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

Citations4
Published2020
Admission routes2
Has abstractyes

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