Back to the basics: using density series to test regulation versus limitation for invasive plants
Bibliographic record
Abstract
Numerous hypotheses have been invoked to explain invasion in plant communities. Here, we use a fundamental tool from plant ecology, density series in situ, to explore whether a reasonable starting point for highly successful invasive plant species is to consider regulation (biotic effects) and limitation (environmental constraints). To explore the utility of density series to understanding invasion we present a case study using C. solstitialis , a perfect candidate since it is a prolific seed producer and invasive in many grasslands globally. Using seed addition into existing vegetation in three grasslands with densities of up to 6500 seeds per m 2 , we found no evidence for regulation via intra or interspecific interference but large differences amongst sites. This strongly suggests that in this species limitations imposed by the environment are the only constraints. Hence, we propose that an excellent starting point for ecologists studying invasion should involve back to the basics experiments on novel species to determine whether other hypotheses need be invoked.
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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 | 0.001 |
| 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 | 0.001 |
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".