Testing the roles of local adaptation and genetic diversity to improve Giant kelp (<i>Macrocystis pyrifera</i>) restoration
Bibliographic record
Abstract
Climate change is causing significant losses of coastal foundation species globally, heightening the need for their restoration. Despite the urgency, it remains unclear if enhancing genetic diversity by using distant source populations will improve restoration outcomes, or if local sources will perform better regardless of their diversity. We conducted a reciprocal transplant with Giant kelp ( Macrocystis pyrifera ) between a warm and cool microclimate 7 km apart in Barkley Sound, British Columbia, and tracked survivorship and growth over 6 months. We seeded kelp gametophyte cultures from the warm and cool site onto small rocks (i.e. “green gravel”) in a nursery, then outplanted them into experimental plots nearby the sites where the parents were collected. The number of parents used to make the cultures was also manipulated (two vs. 10) to simulate different levels of genetic diversity (average heterozygosity). Overall, we found inconsistent evidence for local adaptation between microclimates, and possibly signs of maladaptation in kelp from the warm site. Kelp from the more genetically diverse population at the cooler site survived 16% better and grew 8% larger regardless of the outplant site. Kelp grew up to 223% larger at the cool site but had higher mortality due to either urchin grazing or gravel turnover from swell. Surprisingly, kelp produced from two‐parent cultures survived 278% better than kelp from 10‐parent cultures at 6 months, despite higher observed rates of selfing. Our study provides new insights into factors influencing the restoration of these important temperate coastal foundation species.
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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".