Contrasting effects of plant neighbours on invading <i>Ulmus rubra</i> seedlings in a successional grassland<sup>1</sup>
Bibliographic record
Abstract
Intense competition for soil water can be an important factor regulating rates of woody plant invasion into grasslands that experience periods of drought stress. We conducted a plant neighbour-removal and irrigation experiment in successional grassland at a prairie-forest ecotone in eastern Kansas, U.S.A.: i) to test whether the effects of resident herbaceous vegetation on invading red elm (Ulmus rubra) seedlings varied predictably with water supply, and ii) to assess whether the magnitude and sign of these effects depended on the measure of seedling performance evaluated: seedling survival, growth, or biomass. We found that the impact of neighbours on U. rubra seedlings included strong facilitation, neutral effects, and strong competitive suppression, depending on the level of water supply and on the aspect of plant performance examined. Survival was facilitated by plant neighbours under ambient soil moisture conditions. However, neighbours had no impact on survival in the presence of irrigation, suggesting that facilitation of survival in the absence of irrigation was mediated by neighbour amelioration of water stress. Seedling growth rate was increased by water supply and inhibited by plant neighbours, with the magnitude of inhibition varying independently of water supply. Our results suggest that i) during years of moderate-to-severe drought stress, neighbouring herbaceous plants can have very different impacts on woody seedling recruitment in this grassland and ii) neighbour effects on woody seedling survival should vary more strongly among wet and dry years than neighbour effects on seedling growth do.
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 | 0.001 | 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 | 0.000 |
| 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".