Response and Recovery of Eelgrass (Zostera marina) to Chronic and Episodic Light Disturbance
Bibliographic record
Abstract
Abstract Reduced light availability is a leading cause of seagrass declines worldwide. Light deficiency can be chronic or episodic, where pulsed light stress is punctuated by periods of optimal light. Seagrass resilience to light stress is likely modulated by the durations of light stress and the level of light reduction, yet remains poorly understood. We used a laboratory experiment to examine the response and recovery of Zostera marina to 16 weeks of three types of light disturbance: (i) continuous (C; constant shade), (ii) episodic low (EL; cycles of 4 days shade:3 days no shade), and (iii) episodic high (EH; cycles of 12 days shade:2 days no shade), each implemented at three shade levels (40, 60, and 80% shade). Declines in shoot density and biomass began after 8 weeks and were highest in C and EH disturbance in 60 and 80% shade. Declines were minimal in 40% shade across all light disturbances and in EL across all shade levels. Sheath length responded mainly to shade level, initially increasing in 60 and 80% shade before decreasing. Rhizome carbohydrates initially declined in all light disturbances with 80% shade but did so earlier in C and EH disturbance, and then increased once shoot density decreased. When ambient light was restored, physiological measures recovered, but shoot density, biomass, and morphology did not. Our study showed that shade level strongly modulated Z. marina responses to light disturbance. Not only will chronic high light reduction have negative impacts but pulsed light disturbance can as well, especially when light-stress periods are long and light reduction high.
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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 | 0.001 |
| 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".