Moss protonemata are dispersed by water, wind, and snails
Bibliographic record
Abstract
Premise of the Study Mosses produce asexual propagules, which are dispersed, thus allowing population establishment and maintenance. However, it is unknown if or how protonemata—one of their asexually produced propagules—are dispersed. Moss protonemata were exposed to three dispersal vectors (water, wind, and snails) to describe the dispersal capability and survival after dispersal. Methods The protonemata of mosses Callicostella belangeriana and Taxiphyllum taxirameum were splashed with water drops from a 1 or 2 m height, exposed to two wind velocities (V 1 = 2.74 mps and V 2 = 3.76 mps), and fed to terrestrial snails. Dispersal of protonemata was described for wind and water by studying the dispersal distance and the relationships between protonemata sizes and dispersal distances. Survival after dispersal was recorded for the three vectors. Key Results Water and wind dispersed protonemata up to 80 and 265.5 cm, respectively. The protonemata dispersed the farthest distance when splashed by 2 m drops and hit by V 2 wind velocities. No, or little, relationship between protonemata size and dispersal distance was found for the water and wind vectors. Protonemata survived and became established after dispersal: survival was high when dispersed by water and snails, but was low for wind. Conclusions For the first time, it was shown that protonemata are dispersed mostly close to the source, which is suggested to aid in moss population maintenance.
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) | 0.000 | 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) | 0.001 | 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".