Relative importance of suppression‐based and tolerance‐based competition in an invaded oak savanna
Bibliographic record
Abstract
Summary Invasive species dominate many ecosystems but the competitive strategies underlying this dominance are unclear. Are invasive species generalist competitors, or do they only thrive in certain environments? Do they occur mainly post‐disturbance or can they persist throughout succession? We tested the relative importance of resource acquisition (competitive suppression ability) and the ability to tolerate reduced resource levels (competitive tolerance ability) among four C3 perennial grass species in an invaded oak savanna. Two species ( Poa pratensis and Dactylis glomerata ) are exotic invaders and are thought to have replaced the two native species ( Bromus carinatus and Elymus glaucus ) as dominants. Using glasshouse and field experiments we tested whether the two strategies were maintained with changing resource levels and successional conditions, and their relative roles in explaining exotic dominance. The relative importance of suppression‐ and tolerance‐based competition shifted with neighbour density, burning and planting order. Further, the relative importance of particular plant traits changed depending on the imposed conditions, and the exotic dominants were only competitively superior under certain circumstances. Competitive suppression ability was maintained with changing resource levels but was confined to post‐disturbance conditions. When planting of neighbours was delayed, the early establishing targets were dominant regardless of species, fertility and neighbour density. Competitive tolerance ability determined long‐term patterns of relative abundance and coexistence, but only under the current field conditions of low fertility and limited disturbance. Alteration of these conditions changed the relative abundance of the four grasses, and would probably reconfigure species patterns in the oak savanna community generally. Exotic dominance is presently determined by tolerance‐based competitive traits interacting with the long‐term absence of disturbance. Dominance is therefore contingent on the interaction of competitive strategies, resource availability and disturbance history rather than any one factor alone. Exotic flora dominate all stages of succession in this savanna because there exists both early (suppression) and late (tolerance) successional specialists. The identity of the dominant changes with succession based on the competitive strategy it employs. This result highlights the importance of examining the historical context of invaded communities and tracking their successional status over time.
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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".