Lack of relationship between below‐ground competition and allocation to roots in 10 grassland species
Bibliographic record
Abstract
Summary A field experiment in a native grassland in Central Alberta, Canada, tested whether plants alter relative allocation to roots vs. shoots in response to below‐ground competition, and whether the mass of a species’ root system accounts for interspecific differences in below‐ground competitive response. Seedlings of each of 10 native species were transplanted into the naturally occurring vegetation in the field at the start of the growing season. Root interactions between the target plants and their neighbours were manipulated through the use of PVC root exclusion tubes, with target plants grown with or without potential root interactions with their neighbours. Neighbour shoots were also tied back, forcing any target–neighbour interactions to be below ground. Below‐ground competition generally reduced plant growth, with its relative magnitude varying among species. An allometric analysis indicated that competition below ground did not result in an increase in the relative biomass allocated to roots for any of the 10 target species. This is counter to the growth‐balance hypothesis (and optimal foraging theory). Below‐ground competition did increase root : shoot ratios, but this was due to reduced plant size (small plants have larger root : shoot ratios), rather than adaptive plasticity. A species’ below‐ground competitive ability was not related to its root system size. Although this finding is counter to commonly made assumptions, it is supported by other work demonstrating below‐ground competition to be generally size‐symmetric. Despite the majority of plant–plant interactions in grasslands being below ground, our understanding of plant competition above ground is significantly more robust. Several wide‐spread assumptions regarding below‐ground competition are suspect, and more multispecies studies such as this are required to provide a fuller picture of how plants respond to, and compete for, soil resources.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".