Geographic distribution of needle litter microfungi in British Columbia
Bibliographic record
Abstract
The geographic distribution of microfungal diversity associated with needle litter was investigated in British Columbia, south-western Canada. A total of 77 microfungal species were isolated from needle litters of nine tree species in Pseudotsuga, Tsuga, Picea, and Abies collected in 25 coniferous forest sites that varied in climatic conditions and geographic locations. The nonmetric multidimensional scaling ordination showed the segregation of microfungal species composition between the study sites and needle species, which was significantly correlated to the latitude, elevation, mean annual temperature, and mean temperature at coldest and warmest months of the sites. Major microfungal species showed variable responses to these environmental factors: Trichoderma polysporum and Penicillium miczynskii tended to occur at higher elevations and latitudes and lower temperatures, compared with other species of the same genera. In contrast to the species composition, the mean number of species was not significantly affected by needle species, geographic locations, or climatic conditions. Applying variation partitioning to disentangle the relative effect of the environmental and spatial factors indicated the role of not only climatic but spatial factors in structuring fungal assemblages, suggesting the contribution of such non-niche processes as priority effect and dispersal limitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".