Divergent growth strategies between red algae and kelps influence biomechanical properties
Bibliographic record
Abstract
PREMISE OF THE STUDY: Morphology and material properties are the main components of the mechanical design of organisms, with species groups developing different optimization strategies in the context of their physical environment. For intertidal and subtidal seaweeds, possessing highly flexible and extensible tissues allows individuals to bend and reconfigure in flow, thereby reducing drag. Previous research has shown that aging may compromise these qualities. Tissue age increases with distance from the blade's meristem, which differs in its position on kelps and red algae. Here, we assess whether longitudinal patterns of blade material properties differ between these two algal groups according to tissue age. METHODS: We performed tensile tests on tissues samples excised from various positions along the extent of blades in nine kelp species (basal growth) and 15 species of red algae (apical growth). KEY RESULTS: We found that older tissues were less flexible and extensible than younger tissues in all species tested. As predicted, tissue near the basal meristem in kelp was more flexible and extensible than older tissue at the blade's distal end. The opposite pattern was observed for red algae, with the most flexible and extensible tissues found near the apical meristem at the distal ends of blades. CONCLUSIONS: We propose that divergent patterns in the distribution of material properties along blades may have different consequences for the performance of kelps and red algae. The positioning of younger tissues at the blade base for kelps may enable these species to attain larger body sizes in wave-swept habitats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".