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Record W4391754132 · doi:10.1080/11956860.2024.2311819

Heterotroph removal alters the difference in plant biomass among plant species compositions in systems with different N availability

2023· article· en· W4391754132 on OpenAlexvenueno aff
Xile Xu, Xueyi Wu, Jinqi Yu, Jingwen Tao, Luping Yang, Kai Shen, Yi Wu, Wenjuan Han

Bibliographic record

VenueEcoscience · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsFungicideMonocultureBiomass (ecology)BiologyAgronomyBotanyHorticulture

Abstract

fetched live from OpenAlex

We studied the effects of heterotroph removal on the relationship between species composition and plant biomass in systems with different N availability. Two understory herb species (Ophiopogon bodinieri and Lophatherum gracile) were grown in monocultures and mixture, and heterotroph removal treatments (control, insecticide, fungicide, and fungicide-insecticide combination) were performed on each plant species composition in systems without or with N addition. Results showed that (1) in systems without N addition, the plant biomass of O. bodinieri monoculture was higher than that of the mixture under insecticide and fungicide-insecticide treatments, but this difference disappeared in systems with N addition. (2) In systems without N addition, fungicide and insecticide application increased leaf area but decreased root length and root tips of O. bodinieri monocultures. In systems with N addition, fungicide and insecticide application increased root tips of O. bodinieri monocultures and root diameter of mixtures. (3) In systems without N addition, fungicide and insecticide application increased the soil pH of O. bodinieri monocultures. In systems with N addition, fungicide application decreased the soil K concentration of O. bodinieri monocultures. Our findings suggest that heterotroph removal alters the difference in plant biomass among plant species compositions in systems with different N availability.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

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 communication0.0000.001
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 head0.025
GPT teacher head0.202
Teacher spread0.177 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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