The growth and survival of three closely related <i>Myosotis</i> species in a 3-year transplant experiment
Bibliographic record
Abstract
We studied the growth and survival of three closely related species (Myosotis caespitosa C.F. Schultz, Myosotis palustris (L.) L. subsp. laxiflora (Reichenb.) Schubler et Martens, and Myosotis nemorosa Besser) in a 3-year reciprocal transplant experiment. Plants from two populations of each species were transplanted into five experimental localities where one of the three Myosotis species was resident. Young plants were planted into three types of competitive microsites as follows: gap, sparse vegetation, and dense vegetation. The experiment demonstrated differences among the species. It also showed large differences among populations within a species. The relative success of the species differed among individual localities and among different microsites, and the favorableness of microsites differed among localities. The Myosotis species typically had an advantage in localities where the species was resident. Myosotis caespitosa exhibited the highest mortality of its clones, particularly under competition, which corresponds well to its habitat preferences (disturbed and short-term sites), but it also exhibited the ability to spread in gaps by secondary rosettes. Myosotis palustris subsp. laxiflora spreads best clonally, but its clonal spread was most suppressed by competition. This was consistent with its ability to colonize quickly vegetation-free sites along water, but with weak competitiveness in later stages of succession. Myosotis nemorosa exhibited the highest survival rate, which fits with its preference for permanent wet grasslands.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".