High Vulnerability of Rhodolith Bed Frameworks and Underlying Sediment to Ongoing Ocean Climate Change
Bibliographic record
Abstract
ABSTRACT Rhodoliths are non‐geniculate, free‐living coralline red algae that can accumulate on the seafloor and form structurally complex habitats supporting highly biodiverse communities termed rhodolith beds. Limited understanding of key rhodolith kinetical attributes and how they scale with environmental variability limits ability to predict changes in rhodolith bed distribution and abundance in a globally changing ocean climate. We carried out two experiments in an oscillatory wave tank to test the effects of (1) rhodolith (Boreolithothamnion glaciale) density and wave velocity on rhodolith displacement and abrasion over a hard substratum and (2) rhodolith density on rhodolith displacement and the stability of underlying sediment. We established that on a hard substratum, (1) a threshold wave velocity of ~0.3 m s−1 is required to induce noticeable displacement in average‐sized rhodoliths and (2) rhodolith abrasion increases (quasi‐linearly) with wave velocity up to this threshold. We also showed that (3) for a same rhodolith density, rhodolith displacement is at least two times smaller on a sedimentary than hard substratum and (4) the loss of sediment underneath rhodoliths decreases (quasi‐linearly) with an increase in rhodolith density. Rates documented and strong scaling with changes in water motion and rhodolith density indicate that relatively small changes in the density of rhodoliths or hydrodynamic forces can quickly destabilize rhodolith bed frameworks and underlying sediment. These rates can be used to develop predictive models of change in rhodolith bed distribution and abundance that can in turn inform development of more accurate, science‐based rhodolith bed conservation strategies.
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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 | 0.001 |
| 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 | 0.001 |
| 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".