Belowground herbivory decreases shoot water content and biomass of <i>Lolium perenne</i> seedlings under nutrient-poor conditions
Bibliographic record
Abstract
Belowground herbivory under nutrient-poor conditions is known to significantly decrease plant biomass and root:shoot ratios. However, the mechanisms behind the changes in belowground plant–herbivore interactions that occur under different nutrient conditions remain unclear. We performed a pot experiment using Lolium perenne L. and the third-instar larva of Popillia japonica Newman. The experiment used a three-way factorial randomized-block design; the three factors were nutrient amount (rich/poor), nutrient heterogeneity (homogeneous/heterogeneous), and belowground herbivore (present/absent). Relative water content (RWC) of shoots under nutrient-poor conditions was smaller than that under nutrient-rich conditions, and a single herbivory significantly reduced the RWC under the nutrient-poor conditions. Plant biomass was larger under nutrient-rich conditions than under nutrient-poor conditions. A herbivore decreased plant biomass more under nutrient-poor conditions than under nutrient-rich conditions. Nutrient heterogeneity had no effect on plant biomass, but herbivory and nutrient amount interactively affected root proliferations to nutrient patches. Plants were smaller under nutrient-poor conditions; thus, a larger proportion of the roots was removed by a belowground herbivore. A loss of a larger proportion of roots would cause the small RWC, which restricts compensatory growth. Consequently, growth of L. perenne is more severely limited by a belowground herbivore under nutrient-poor conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".