The dynamics of external water conduction in the dryland moss Syntrichia
Bibliographic record
Abstract
Abstract Syntrichia relies on external water conduction for photosynthesis, survival, and reproduction, a condition referred to as ectohydry. Capillarity spaces are abundant in Syntrichia, but the link between function and morphology is complex. The aim of this study was to provide a better understanding of species-specific morphological traits underlying the functions of water conduction and storage. We used an environmental scanning electron microscope and confocal microscopy for observing anatomical characters in the leaves of Syntrichia species. We also measured hydration/dehydration curves to understand the rate of conduction and dehydration by experimental approaches. Syntrichia is an ectohydric moss that can externally transport and store water from the base of the stem using capillary action. We propose a new framework to study ectohydric capabilities, which incorporates three morphological scales and the timing of going from completely dehydrated to fully hydrated. Characters of interest in this model include cell anatomy (papillae development, hyaline basal cells and laminar cells), architecture of the stem (concavity and orientation) and whole clump characteristics (density of stems). We report significant variations in the speed of conduction, water holding capacity and hydration associated with each species studied (11 in total). All Syntrichia species are capable of external water conduction and storage, but the relevant traits differ among species. These results help to understand potential evolutionary and ecological trade-offs among speed of water conduction, water holding capacity, ontogeny, and differing habitat requirements. An integrative view of ectohydry in Syntrichia contributes to understanding the water relationships of mosses.
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) | 0.000 | 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 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".