Interactions between deadwood and soil characteristics in a natural boreal trembling aspen – jack pine stand<sup>1</sup>This article is one of a selection of papers from the International Symposium on Dynamics and Ecological Services of Deadwood in Forest Ecosystems.
Bibliographic record
Abstract
Decaying wood contribution to the heterogeneity of forest soils could depend on tree species and wood decay stage. The study was conducted in an 85-year-old trembling aspen ( Populus tremuloides Michx.) – jack pine ( Pinus banksiana Lamb.) forest in northwestern Quebec, Canada. Trees, snags, logs, and forest floor originating from wood buried within the forest floor (lignic FF) and from fine litter (alignic FF) were inventoried in fifteen 400 m2 plots (nine jack pine and six trembling aspen). Chemical properties of alignic and lignic FF and logs were measured and relative nutrient availability in the mineral soil assessed under logs and under lignic and alignic FF using PRS probes. No significant differences between forest covers were found for the proportion of C and nutrients contained in deadwood (snags, logs, and lignic FF) relative to tree biomass plus necromass (deadwood plus alignic FF) content. Lignic FF was characterized by a higher C/N ratio and exchangeable acidity than alignic FF and its nutrient concentrations were between those of alignic FF and logs. Differences in wood characteristics may explain some of the differences in forest floor properties observed between trembling aspen and jack pine. Nutrient availability in the mineral soil was affected by the overlaying materials and could reflect differences in the dynamics of individual nutrients.
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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) | 0.001 | 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".