Optimizing growth chamber conditions for maintaining Arctic<scp>lichen‐dominated</scp>biocrusts
Bibliographic record
Abstract
Optimizing growth chamber conditions for Arctic lichen biocrusts will create new opportunities to assess and prioritize reclamation techniques given the challenges associated with conducting arctic field work. Our study is the first to examine growth chamber conditions for optimizing survival and growth of Arctic lichen biocrusts, as measured by changes in lichen cover. We assessed effects of substrate crossed with substrate depth, substrate sterilization, lichen inoculation and community composition, and watering frequency in four concurrent experiments over 6 weeks on survival of arctic biocrusts collected from Diavik Diamond Mine Inc., Northwest Territories, Canada. Mixed species declined less than Flavocetraria cucullata , and substrate affected F. cucullata survival over time. Live lichen cover declined least with a 3‐day watering frequency and substrate depth of 1 cm. Sterilization did not affect lichen survival, and no contamination was observed over 6 weeks. Our results highlight the challenges of maintaining and growing lichens under controlled conditions, as only a few treatments showed increases in cover. Our research shows that even short‐term growth chamber experiments have potential to screen reclamation treatments prior to field assessments, permitting reclamation scientists to optimize limited time and resources while in the field.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".