Forest harvesting reduces the soil metagenomic potential for biomass decomposition
Bibliographic record
Abstract
Soil is the key resource that must be managed to ensure sustainable forest productivity. Soil microbial communities mediate numerous essential ecosystem functions, and recent studies show that forest harvesting alters soil community composition. From a long-term soil productivity study site in a temperate coniferous forest in British Columbia, 21 forest soil shotgun metagenomes were generated, totaling 187 Gb. A method to analyze unassembled metagenome reads from the complex community was optimized and validated. The subsequent metagenome analysis revealed that, 12 years after forest harvesting, there were 16% and 8% reductions in relative abundances of biomass decomposition genes in the organic and mineral soil layers, respectively. Organic and mineral soil layers differed markedly in genetic potential for biomass degradation, with the organic layer having greater potential and being more strongly affected by harvesting. Gene families were disproportionately affected, and we identified 41 gene families consistently affected by harvesting, including families involved in lignin, cellulose, hemicellulose and pectin degradation. The results strongly suggest that harvesting profoundly altered below-ground cycling of carbon and other nutrients at this site, with potentially important consequences for forest regeneration. Thus, it is important to determine whether these changes foreshadow long-term changes in forest productivity or resilience and whether these changes are broadly characteristic of harvested 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 | 0.001 | 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 | 0.001 | 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 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".