Diverging soil peroxidase activity under ectomycorrhizal versus arbuscular mycorrhizal conifers with increasing C:N and exchangeable manganese
Bibliographic record
Abstract
Ectomycorrhizal (EM) fungi purportedly contribute to the enzymatic decay of soil organic matter (SOM), in contrast to arbuscular mycorrhizal (AM) stands where SOM turnover may be more fully governed by free-living saprotrophic fungi. We tested this distinction in a 30-year-old mixedwood conifer trial by comparing total peroxidase activity (including manganese-peroxidase [MnP]), fungal communities and mass of the humus layer between Pseudotsuga menziesii (EM host), Thuja plicata (AM host), and a 50:50 mixture across a natural productivity gradient. Total peroxidase and MnP activity diverged between hosts as humus C:N ratio increased, culminating in 3- to 4-fold greater enzyme activity under P. menziesii on low fertility soils. This soil effect also correlated positively with exchangeable Mn, highlighting a possible further restriction on SOM turnover under EM stands. Peroxidase activity was well aligned with a subset of abundant EM fungal species, notably Piloderma olivaceum and Piloderma sphaerosporum , suggesting a much greater enzymatic contribution by these symbiotic fungi in comparison to saprotrophic fungi under T. plicata . After three decades, mass of the humus layer averaged 2.15 kg OM m −2 and did not yet differ among stand types. However, a 3-fold range in humus mass in correlation with declining soil fertility under P . menziesii suggests that select EM fungal taxa engaged in organic N liberation can limit SOM accumulation. This research highlights the adaptive ligninolytic enzymatic capacity of EM fungal communities and underscores how dual soil properties (low N or high Mn availability) may enhance peroxidase production and SOM turnover in EM 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 | 0.000 | 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) | 0.000 | 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".