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Record W4412181127 · doi:10.1101/2025.07.06.663341

Do allochthonous flows explain deviations from the Redfield ratio in lakes?

2025· preprint· en· W4412181127 on OpenAlexaff
Benôıt Pichon, Frédéric Guichard, Isabelle Gounand

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Lakes or streams show strong deviations of their stoichiometry compared to the Redfield ratio measured in oceans. Allochthonous inflows of resources might contribute to those deviations directly, by changing composition of detritus in ecosystems, but also indirectly, by shaping local community dynamics and stoichiometric constrains within aquatic ecosystems. Here, we developed a stoichiometric model to understand those direct and indirect mechanisms through which allochthonous inflows affect seston stoichiometry. Our results emphasize that increasing allochthonous inflows promotes heterotrophic functioning, and relax decomposer’ carbon limitation. This release of stoichiometric constrain of decomposers (i) destabilizes the aquatic ecosystem by promoting competition between phytoplankton and decomposers, (ii) decreases the ability of the lake to regulate allochthonous flows, and (iii) push seston stoichiometry away from the Redfield ratio. Our study emphasize how the quantity and the stoichiometry of inflows shape community dynamics and the elemental constraints within the ecosystem, and open perspectives for stoichiometry at the landscape extent.

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)0.001
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.013
GPT teacher head0.213
Teacher spread0.200 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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