Recruitment tolerance to increased temperature present across multiple kelp clades
Bibliographic record
Abstract
Kelp systems dominate nearshore marine environments in upwelling zones characterized by cold temperatures and high nutrients. Worldwide, kelp population persistence and recruitment success generally decreases with rising water temperatures coupled with low nutrients, making kelp populations vulnerable to impending warming of the oceans. This response to climate change at a global scale, however, may vary due to regional differences in temperature variability, acclimation, and differential responses of kelp species to changing conditions. Culture experiments were conducted on 12 eastern Pacific kelp taxa across geographic regions (British Columbia, central California, and southern California) under three nitrate levels (1, 5, and 10 μmol/L) and two temperatures (12°C and 18°C) to determine sporophyte production (i.e., recruitment success). For all taxa from all locations, sporophytes were always present in the 12°C treatment and when recruitment failure was observed, it always occurred at 18°C, regardless of nitrate level, indicating that temperature is the driving factor limiting recruitment, not nitrate. Rising ocean temperatures will undoubtedly cause recruitment failure for many kelp species; however, the ability of species to acclimatize or adapt to increased temperatures at the warmer edge of their species range may promote a resiliency of kelp systems to climate change at a global scale.
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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) | 0.006 | 0.003 |
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; both teacher heads agree on what is shown here.
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".