Responses to a fluctuating environment: effects of water depth on growth and biomass allocation in <i>Eleocharis cellulosa </i>Torr. (Cyperaceae)
Bibliographic record
Abstract
Fluctuating water levels, which characterize freshwater marshes of the Florida Everglades, U.S.A., constrain growth in emergent macrophytes. We studied acclimation of Eleocharis cellulosa Torr. (Cyperaceae) in mesocosms to water depths of 7 and 54 cm and to switching between these water depths. After 80 weeks at fixed depths, deepwater plants produced (i) taller, thicker, and fewer shoots; (ii) fewer ramets; (iii) less biomass; and (iv) greater shoot biomass relative to root and rhizome biomass. Despite large differences in shoot lengths between water depths, shoot heights above the water surface were similar. Emergent shoot tissues had thick secondary walls in the epidermal cells and several palisade layers beneath; submerged shoots lacked this anatomy. When shallow-water plants were transferred to deep water, shoots elongated rapidly, with younger shoots elongating more than older ones. When deepwater plants were transferred to shallow water, emergent shoots quickly died and were replaced by new shoots. Overall, plants exposed to rapid changes in water level adjusted biomass allocation patterns after 9 weeks towards those of control plants in their new environment, but deepwater plants responded more slowly than shallow-water plants. These shifts may allow E. cellulosa to produce shoots that optimize biomechanical support and aeration.Key words: biomass allocation, Eleocharis cellulosa, Everglades, gas exchange, shoot demography, wetland plants.
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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 | 0.000 | 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".