Fungal community assessment in Canadian arctic soils from Alexandra Fiord, Ellesmere Island, Nunavut.
Bibliographic record
Abstract
Fungal communities in arctic soils tend to be less diverse compared to the communities in temperate forest soils due to the harsher environmental conditions. Even in a single arctic site such as Alexandra Fiord, considered a terrestrial arctic oasis, fungal diversity is expected to be lower compared to soils in less extreme environments. We hypothesized that variations in environmental factors would play an important role in determining fungal community structure, as the Alexandra Fiord soils exhibits considerable environmental variation in a small geographic area. To test this hypothesis, we collected soil samples from three sites across the landscape and performed length-heterogeneity polymerase chain reaction (LH-PCR) analyses using ITS3 and NLB4 primers, which have been used successfully to characterize complex communities. Our results showed that there were large relative differences in fungal community structure between the sites. At the Alexandra Fiord Highland Dolomitic site diversity was low with genotypes relatively evenly distributed, whereas Alexandra Fiord Highland Granitic and Alexandra Fiord Lowland sites had higher diversity and a less even distribution of genotypes with a few occurring at a high frequency and many rare species. Among environmental variables, soil moisture, temperature, DOC, DON, C:N ratio and soil pH were significant influential factors in determining fungal community structure. Among these environmental factors, pH showed the strongest correlation with the fungal community data. --P. ii.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".