Macrofungus communities correlate with moisture and nitrogen abundance in two old-growth conifer forests, Olympic National Park, Washington, USA
Bibliographic record
Abstract
We characterized the epigeous macrofungus communities in two old-growth conifer forests by collecting sporocarps. Despite the similarity in dominant tree species in the two forests, the macrofungus communities were very different. At the drier, nitrogen-poor Deer Park area, the macrofungi were dominated by ectomycorrhizal species in the genera Cortinarius, Tricholoma, Hydnellum, Suillus, and Sarcodon. At the wetter, higher nitrogen Hoh Valley, the macrofungi were characterized by ectomycorrhizal species in different genera, such as Inocybe, Russula, Amanita, Boletus, and Phaeocollybia, and saprotrophic fungi accounted for a greater proportion of the community. Species richness was similar at the two areas, but sporocarp production was much higher at Deer Park. We propose that (i) these community differences developed over a long time; (ii) they are largely related to differences in ecosystem moisture and nitrogen abundance; and (iii) within the ectomycorrhizal fungi, possible causal mechanisms involve mycelial morphology and carbon allocation within the symbioses. The apparent response to relatively small but presumably long-term differences in nitrogen abundance suggests that sporocarp production by macrofungi could be an effective bioindicator and should be considered in determination of critical loads for atmospheric nitrogen deposition to temperate and boreal forests.Key words: critical nitrogen loads, ectomycorrhizal fungi, macrofungi, macrofungus communities, nitrogen, old-growth conifer forests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".