Coprophilous fungi as paleo indicators for moose presence after introduction to Newfoundland
Bibliographic record
Abstract
To study the non-native moose (Alces alces) population on Newfoundland, successfully introduced in 1904, a paleolimnological approach was used: coprophilous fungal spores were isolated in two 210Pb-dated lake sediment cores to compare with historical abundance numbers for moose. We predicted that, as commonly practiced with megafauna, coprophilous spores would correspond with abundance data. Cores from two ponds were sectioned at 0.25 cm intervals resulting in ~3-4 years in each slice of sediment from ~1850 to 2021. The counts were numerically treated for each spore type and the spore total by two different methods in 24 samples from each core: 1) as a percent of the tracer Lycopodium present and 2) as an accumulation rate. Coprophilous spores counted in this study include Podospora, Sordaria, Sporomiella, Arnium, Coniochaeta, Ascodesmis, and Delitschia. Results corresponded between moose abundance and spores for Little Crow Pond, but were less promising for Pitcher Pond, possibly due to dating error. Our prediction was supported by the similar trends of coprophilous spore abundance and moose population estimates through time, serving as a validation of these spores as a proxy for large herbivores. With further research, this method may be applicable to the native caribou (Rangifer tarandus).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".