Spatio‐temporal pattern of specific gravity of mangrove diaspore: implications for upstream dispersal
Bibliographic record
Abstract
Mangrove plants, which develop highly productive forests on tropical–subtropical coastlines and river estuaries, rely mainly on river and sea water currents for their diaspore dispersal. Mangrove diaspores are basically dispersed in brackish to sea waters; thus whether they sink or float during the dispersal period could be changed dynamically, both spatially and temporally, depending on the salinity to which they are exposed, as well as on their specific gravity (SG). We found that the SG of diaspores of two mangrove species, Rhizophora stylosa and Bruguiera gymnorrhiza , which are dominant species and form a typical zonation ( B. gymnorrhiza in inland areas and R. stylosa in more seaward areas) in the study area, changed spatially and temporally. Bruguiera gymnorrhiza gradually lost its SG in accordance with elapsed time, while R. stylosa lost its SG in the first 6 h and gained gradually according to elapsed time. Hydrodynamic simulation of dispersal patterns, in combination with observed specific gravity changes of both diaspores and river water, demonstrated that the spatio‐temporal pattern of specific gravity change was closely related to the difference in dispersal behaviors between the species. The diaspore of B. gymnorrhiza generally disperses upstream, and covers wider ranges than that of R. stylosa , at least in the early phase of dispersal. These dispersal behaviors agreed well with the distribution pattern of the species across estuaries in the study site. To date, hydrochory has been considered to be a mostly passive process governed by the dynamics of water current and subsequent sediment movement, with fixed diaspore characteristics such as shape and buoyancy. The present study shed new light on an active and dynamic process in hydrochory and found that the buoyancy of diaspores may be controlled by changes in their spatial and temporal SG.
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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 | 0.001 | 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".