Herbivory selects for semelparity in a typically iteroparous plant species, Zostera marina
Bibliographic record
Abstract
Recognizing the abiotic and biotic parameters that favor one reproductive \nstrategy over another can reveal much about population dynamics and aid in \nunderstanding diverging traits in different environments. This thesis work \nexplores abiotic and biotic causes for a population of Zostera marina (eelgrass, a \nmarine angiosperm) to partition re productively into subtidal perennial and \nintertidal annual zones. A tidal simulator experiment and field measurements of \nabiotic variables did not support a previous hypothesis that intertidal exposure \nfavors an annual life history. However, experimental exclusion of Branta \ncanadensis (Canada geese) identified an herbivore driven fall mortality event that \noccurs annually. Additional evidence documented plants within this population \nflowering and dying prior to the influx of Canada geese. These cryptic ???true \nannuals??? will over time contribute more progeny to future generations, while \nperennial plants are allocating energy to growth and storage, resources that go \nunutilized following geese grazing. Consumers have been hypothesized as a \nselective force for semelparity (programmed mortality following flowering); \nhowever, this may be the first empirical example of herbivore-mediated selection \ntoward semelparity in any plant species.
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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".