Biomass allocation of <i>Vincetoxicum rossicum</i> and <i>V. nigrum</i> in contrasting competitive environments
Bibliographic record
Abstract
PREMISE: Understanding how drought and biomass allocation patterns influence competitive ability can help identify traits related to invasiveness and guide management. Vincetoxicum nigrum and V. rossicum are increasingly problematic herbaceous perennial vines in the northeastern United States and southeastern Canada. METHODS: Using a greenhouse experiment, we investigated how biomass allocation and competition intensity of Vincetoxicum spp. responded to four competitive regimes at two levels of soil water availability in the presence of conspecific or congeneric neighbors. RESULTS: Soil moisture was the most important influence on growth and biomass allocation. Vincetoxicum nigrum had a greater capacity for growth and reproduction than V. rossicum, especially under drought. Drought reduced the probability of reproduction for V. rossicum. Vincetoxicum rossicum had a higher root-to-shoot ratio than V. nigrum under adequate soil moisture. This difference more than doubled under drought. Under interspecific competition, V. nigrum maximized its biomass, while V. rossicum limited aboveground growth and reproduction. Root-only competition increased shoot and root biomass relative to shoot-only competition. The effects of root and shoot competition were additive under interspecific competition, but interacted under intraspecific competition (negative interaction under drought and positive interaction under sufficient soil moisture). CONCLUSIONS: Management strategies targeting mixed populations of V. rossicum and V. nigrum are most important under ample water availability. Under drought conditions, strategies focused on V. nigrum should effectively limit Vincetoxicum growth and seed reproduction. Phenotypic plasticity and the positive competition intensity associated with drought in monocultures may contribute to drought resistance in these invasive species.
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 | 0.000 | 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".