Long-Term Enrichment of Stress-Tolerant Cellulolytic Soil Populations following Timber Harvesting Evidenced by Multi-Omic Stable Isotope Probing
Bibliographic record
Abstract
Soil management is vital for maintaining the productivity of commercial forests, yet the long-term impact of timber harvesting on soil microbial communities remains largely a matter of conjecture. Decomposition of plant biomass, comprised mainly of lignocellulose, has a broad impact on nutrient cycling, microbial activity and physicochemical characteristics of soil. At ‘Long-term Soil Productivity Study’ sites in California dominated by Ponderosa pine, we tested whether clear-cut timber harvesting, accompanied by varying degrees of organic matter (OM) removal, affected the activity and structure of the cellulose-degrading microbial populations sixteen years after harvesting. Using a variety of experimental approaches, including stable isotope probing with 13C-labelled cellulose in soil microcosms, we demonstrated that harvesting led to a decrease in net respiration and cellulolytic activity. The decrease in cellulolytic activity was associated with an increased relative abundance of thermophilic, cellulolytic fungi (Chaetomiaceae), coupled with a decreased relative abundance of cellulolytic bacteria, particularly members of Opitutaceae, Caulobacter and Streptomycetaceae. In general, harvesting led to an increase in stress-tolerant taxa (i.e. also non-cellulolytic taxa), though our results indicated that OM retention mitigated population shifts via buffering against abiotic changes. Stable-isotope probing improved shotgun metagenome assembly by 20-fold and enabled the recovery of ten metagenome-assembled genomes of cellulolytic bacteria and fungi. Our study demonstrates the putative cellulolytic activity of a number of uncultured taxa and highlights the mineral soil layer as a reservoir of uncharacterized diversity of cellulose-degraders. It also and contributes to a growing body of research showing persistent changes in microbial community structure in the decades following forest harvesting.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".