Neighbour presence, not identity, influences root and shoot allocation in pea
Bibliographic record
Abstract
Competition is a key feature that structures the composition of plant communities. A growing body of evidence is showing that the presence of neighbours, especially belowground neighbours, induces varied morphological responses in plants. However, in many species, it is not known whether neighbour identity also influences plant morphological responses such as biomass allocation patterns. To assess plant response to above- and belowground neighbour presence and identity, we conducted a greenhouse experiment consisting of conspecific (pea; Pisum sativum L.) and heterospecific (oat; Avena sativa L.) neighbours growing with a P. sativum focal plant. Four interaction regimes were constructed including shoot, root, or 'full' interaction (root & shoot) treatments, as well as a control with no interactions permitted. Our results showed that pea plants responded negatively to the presence of neighbours, and in particular, the presence of belowground neighbours. Treatments where belowground interactions were permitted (full and root interactions) had lower root and shoot mass fractions (R:S ratios) than where shoot interactions were permitted. Shoot and root allocation and R:S ratios of focal pea plants were not affected by neighbour identity, suggesting that neighbour presence, but not identity, influenced allocation patterns. The impact on P. sativum of a neighbouring competitor was more prominent than neighbour identity, showing that some plants may not discriminate between the identity of neighbours even though they are capable of responding to their presence.
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 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".