Forest floor microbial community response to tree species and fertilization of regenerating coniferous forests
Bibliographic record
Abstract
We studied the effect of tree species and fertilization on the forest floor microbial community of 15-year-old regenerating forests. We sampled F and H forest floor layers of plots planted to Thuja plicata (Donn ex D. Don.) or Tsuga heterophylla (Raf.) Sarg. on N-poor and N-rich sites, with and without fertilizer treatments. Microbial community composition was assessed using phospholipid fatty acid analysis and by enumerating populations of culturable bacteria and fungi. Potential microbial functioning was assessed using community-level physiological profiling. There was little differentiation of community-level physiological profiles of F and H layers and few differences among the treatments. Total microbial biomass was greater in the F than H layer, and the two layers had distinct phospholipid fatty acid profiles. Site effects were detected mainly in the residual H layer, and tree species effects were seen mainly in the F layer, which has developed since harvesting. The effect of fertilization depended on site and tree species, with very little response in cedar plots, and the greatest effects in hemlock plots, coinciding with the greater growth response of hemlock. These results indicate that differences in plant growth rates, rather than direct effects of fertilization, influenced the microbial communities.
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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 | 0.001 | 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 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".