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 of O. biennis reduced the performance and diversity of neighbouring plant species. In greenhouse experiments, we detected heritable variation in O. biennis for above‐ground and below‐ground growth, and O. biennis varied genetically in response to competition, indicating the potential for adaptive evolution in response to selection by competitors. Variation among O. biennis genotypes also affected the performance of neighbouring plants in the greenhouse, whereby genetic variation in O. biennis shoot : root ratio explained up to 41% of the variation in the performance of an exotic grass ( Bromus inermis ). Despite effects of O. biennis genotype on B. inermis in the greenhouse, variable soil fertility had a much stronger effect on the grass's performance, and there were no effects of O. biennis genotype 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 of O. biennis is not expected to affect short‐term ecological dynamics in this system. Nevertheless, O. biennis has the potential to influence co‐existence over longer timescales by adapting to competitors.
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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".