Resource and non‐resource root competition effects of grasses on early‐ versus late‐successional trees
Bibliographic record
Abstract
Summary This study assessed the effects of resource (i.e. nutrients) and non‐resource (i.e. interference for space) competition from fine roots of competing grasses on the growth, morphology and architecture of fine roots of four tree species of varying successional status: Populus deltoides ¥ P. balsamifera (a hybrid), Betula papyrifera , Acer saccharum and Fraxinus americana . We tested the general hypothesis that tree fine‐roots are affected by both below‐ground resource and non‐resource competition from non‐self plants, and the more specific hypothesis that this effect is stronger in early‐successional tree species. The experiment was conducted in split‐containers where half of the roots of tree seedlings experienced either below‐ground resource competition or non‐resource competition, or both, by grasses while the other half experienced no competition. The late‐successional tree species A. saccharum and F. americana were mostly affected by resource competition, whereas the early‐successional P. deltoides ¥ balsamifera and B. papyrifera were strongly affected by both resource and non‐resource competition. Non‐resource competition reduced fine‐root growth, root branching over root length (a measure of root architecture) and specific root length (a measure of root morphology) of both early‐successional species. Synthesis . This study suggests that early‐successional tree species have been selected for root avoidance or segregation and late‐successional tree species for root tolerance of competition as mechanisms to improve below‐ground resource uptake in their particular environments. It also contradicts recent studies showing perennial and annual grasses tend to overproduce roots in the presence of non‐self conspecific plants. Woody plants, required to grow and develop for long periods in the presence of other plants, may react differently to non‐self root competition than perennial or annual grasses that have much shorter lives.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".