Environmental variation has stronger effects than plant genotype on competition among plant species
Bibliographic record
Abstract
Summary Competition is a key factor affecting the performance and co‐existence of species. Most ecological research on competition treats species’ populations as phenotypically homogenous. However, plant populations typically contain genetic variation for multiple traits and have the potential to rapidly adapt to changing environments. Recent theoretical and empirical research suggests that such variation and evolution may affect the ecological outcome of competitive interactions. We conducted a series of experiments to test the hypothesis whether genetic variation for competitive traits in a native plant (Oenothera biennis) affects the performance and diversity of competing plant species. In greenhouse and field experiments, the presence ofO. biennisreduced the performance and diversity of neighbouring plant species. In greenhouse experiments, we detected heritable variation inO. biennisfor above‐ground and below‐ground growth, andO. biennisvaried genetically in response to competition, indicating the potential for adaptive evolution in response to selection by competitors. Variation amongO. biennisgenotypes also affected the performance of neighbouring plants in the greenhouse, whereby genetic variation inO. biennisshoot : root ratio explained up to 41% of the variation in the performance of an exotic grass (Bromus inermis). Despite effects ofO. biennisgenotype onB. inermisin the greenhouse, variable soil fertility had a much stronger effect on the grass's performance, and there were no effects ofO. biennisgenotype on neighbouring plants in the field. Synthesis. Our results show that interspecific competition affected the biomass and diversity of plants, but heritable variation in competitive ability ofO. biennisis not expected to affect short‐term ecological dynamics in this system. Nevertheless,O. biennishas the potential to influence co‐existence over longer timescales by adapting to competitors.
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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 | 0.001 |
| 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) | 0.004 | 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".