Physiological mechanisms facilitating morphological plasticity across hydrodynamic gradients in kelps
Bibliographic record
Abstract
Some kelp species exhibit morphological plasticity across gradients of hydrodynamic forcing. Such kelps tend to grow narrow, flat blades in fast flow and broad, undulate blades in slow flow. This plasticity is an adaptive phenomenon that allows the kelps that show it to continuously reduce drag while enhancing productivity. While the functional consequences of this phenomenon have been relatively well studied, the developmental mechanisms that underlie it are poorly understood. The primary goal of this thesis is to improve our understanding of the developmental processes facilitating morphological plasticity across hydrodynamic gradients in kelps. I first conducted several experiments where I applied tension to blade tissue of the kelp Nereocystis luetkeana in various ways to better characterize the growth response to mechanical stimulation normally imposed by drag. The results of these experiments suggest that plasticity in kelps is probably regulated at the scale of individually stimulated cells and that changes in blade morphology are likely brought about through changes in the direction of cell growth and/or division (Ch. 2). I then examined the effects of auxin on Nereocystis blade growth and morphology and considered whether auxin could play a role in mediating kelp plasticity. I found that auxin can have morphogenic effects in Nereocystis blade tissue that are remarkably similar to the effects of tension (Ch. 3). Next, I tested whether culturing the kelp Macrocystis pyrifera in reduced concentrations of Ca²⁺ could inhibit the growth response to mechanical loading, which would suggest that Ca²⁺ signaling might play a role in regulating plasticity. No evidence arose that reducing the ambient Ca²⁺ concentration could inhibit plasticity (Ch. 4). Furthermore, all Ca²⁺ reductions greater than 50% proved lethal for kelps (Ch. 4). Finally, I investigated how prevalent phenotypic plasticity across hydrodynamic gradients is in various algal groups and considered whether mechanisms of flow perception could limit the evolution of such plasticity. I found that (1) researchers examining intraspecific variation across flow gradients in seaweeds usually have not tested for plasticity and (2) verified plasticity has been documented more frequently in brown algae with intercalary growth than it has in other macroalgae (Ch. 5).
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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 | 0.001 | 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".