Photosynthetic opportunity cost and energetic cost of a rapid leaf closure behavior in <i>Mimosa pudica</i>
Bibliographic record
Abstract
PREMISE OF THE STUDY: The rapid leaf movement of Mimosa pudica is expected to be costly because of energetic trade-offs with other processes such as growth and reproduction. Here, we assess the photosynthetic opportunity cost and energetic cost of the unique leaf closing behavior of M. pudica. METHODS: In the greenhouse, we employed novel touch-stimulation machines to expose plants to one of three treatments: (1) untouched control plants; (2) plants touch-stimulated to close their leaves during the day to incur energetic costs associated with leaf movement and reduced photosynthesis; (3) plants touched at night to assess the effects of touch alone. M. pudica is nyctinastic and closes its leaves at night; thus, touching at night does not impart additional costs. We directly assessed costs by comparing physical traits. Leaf re-opening response was measured to assess the potential for plant behavioral plasticity to impact photosynthetic opportunity costs. KEY RESULTS: The cost of rapid leaf closure behavior was expressed as a 47% reduction in reproductive biomass accounting for the effect of touch. Touch itself changed physical traits such as biomass, with touched plants being generally bigger. Plants touched at night re-opened their leaflets 26% quicker than plants touched during the day. CONCLUSIONS: We reason that the reproductive allocation costs incurred by M. pudica can be attributed to a combination of photosynthetic opportunity cost and the energetic cost associated with increased stimulation of leaf movement and that behavioral plasticity has the potential to alter photosynthetic opportunity costs.
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 | 0.001 | 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".