Experimental dominant plant removal results in contrasting assembly for dominant and non‐dominant plants
Bibliographic record
Abstract
Understanding why communities appear deterministically dominated by relatively few species is an age-old debate in ecology. We hypothesised that the dominant and non-dominant species in a community are governed by different assembly mechanisms where environmental conditions influence dominant species more than non-dominant species. Further, dominant plants moderate the environment where non-dominant species thrive, diminishing the influence of environmental filtering and increasing the influence of limiting similarity for non-dominant species. We tested these hypotheses by removing two dominant species in five temperate meadows. We found that the composition of the non-dominants diverged while the new dominants converged over time. Phylogenetic analyses suggested that habitat filtering and limiting similarity drove the new dominant species simultaneously. Conversely, non-dominant community assembly appeared more unpredictable. These suggest that dominant species converged towards a predictable environmentally driven optimum, while non-dominant species thrive in a moderated habitat, which probably reduced non-dominant species predictability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".