Quantitation of endorhizal fungi in High Arctic tundra ecosystems through space and time: the value of herbarium archives
Bibliographic record
Abstract
Mycorrhizal fungi are widespread in temperate and tropical regions, but generally are thought to be relatively depauperate at high latitudes. The potential impact of global warming on the polar ecosystems has renewed interest in research into tundra soil microbiota. Although logistical impediments limit field access, herbarium accessions are a potential resource for surveying mycorrhizal distribution. We present: (i) a method for examining fungi in roots of herbarium specimens that provides morphological preservation comparable to formalin fixation; and (ii) a multiple quantitation method to assess diverse morphotypes. Arbuscular mycorrhizae, fine endophytes, and septate endophytes were widespread in Asteraceae roots from Axel Heiberg and Ellesmere islands, Arctic Canada, during 2004. Roots from the same species collected from this region since 1982, stored in our herbarium, consistently contained abundant endorhizal fungi. Although 2004 was one of the coolest growing seasons in the survey, mycorrhizal abundance was highest in that year. Endorhizal fungi are likely to be important for plant survival and soil-forming processes in High Arctic tundra environments, and may be sensitive to climate variation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".