Carbon and nitrogen elemental and isotopic patterns in macrofungal sporocarps and trees in semiarid forests of the south‐western USA
Bibliographic record
Abstract
Summary Previous studies in humid forests have shown that the 13C and 15N isotopic composition differs between ectomycorrhizal (ECM) and saprotrophic (SAP) fungi, and that this ECM–SAP ‘divide’ may provide a useful tool for evaluating fungal trophic status. We evaluated whether this method could delineate the trophic status of fungi in two semiarid, temperate forests of the south‐western USA. This technique could be particularly valuable in arid regions where the functional roles of fungi can be difficult to assess because of infrequent sporocarp production. Our data were consistent with the existence of an ECM–SAP divide, although δ13C values were more useful than δ15N values in separating trophic status. Saprotrophic fungi consistently had higher δ13C values than their presumed substrates; however, the degree of 15N enrichment in SAP sporocarps was highly variable. Comparison of 11 sporocarp species common to both sites showed that δ15N values were higher in one of the forests, even though the δ15N values of foliage from common understorey and overstorey trees were similar between forests. We conclude that assessment of the isotopic compositions of fungal sporocarps and their substrates is helpful for elucidating ecological relationships in semiarid forests.
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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 | 0.000 |
| 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) | 0.000 | 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".