Patterns in the occurrence of saprophytic fungi carried by arthropods caught in traps baited with rotted wood and dung
Bibliographic record
Abstract
Fungi from approximately 1700 individual arthropods that had been captured in traps set in aspen-dominated woodland in western Canada and baited with coyote dung, moose dung, white-rotted wood, brown-rotted wood and fiberglass were isolated in pure culture and identified. These data were analysed with principal components analysis (PCA) to determine whether different types of substrate attracted specific arthropods and whether these animals carried unique assemblages of fungi with known proclivities for the new habitat. Mycobiotic agar was used to restrict the numbers of fungi isolated and resulted in the recovery of 1687 isolates representing 65 species across 12 orders. Isolates of cosmopolitan fungal taxa such as species of Cladosporium, Penicillium, and Beauveria were the most numerous. Taxa with predilections for specific substrates, such as Myxotrichum and Cryptendoxyla that are known inhabitants of cellulose-rich materials (i.e. rotted wood), and various representatives of the keratinophilic Onygenales were recovered from arthropods attracted respectively to baits rich in cellulose and keratin. When traps were analysed according to the identity and numbers of arthropods captured, there was considerable overlap among clusters representing specific bait types, with traps baited with coyote dung being the most divergent partly because they captured significantly more arthropods than those baited with moose dung or rotted wood. When bait type was examined according to the identity and numbers of fungi on trapped arthropods the degree of overlap was also high although a few trends could be discerned. In particular traps baited with brown-rotted wood and coyote dung diverged slightly indicating that arthropods visiting these bait types were carrying somewhat different suites of fungi.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".