Nitrogen availability in soil and forest floor of contrasting types of boreal mixedwood forests
Bibliographic record
Abstract
Boreal mixedwood forests with varying proportions of coniferous and deciduous species are found throughout the North American continent. Maintenance of a deciduous component within boreal forests is currently favoured, as deciduous species are believed to promote faster nutrient turnover and higher nutrient availability. Results of comparisons of deciduous and coniferous forests are, however, inconsistent in supporting this generalization. We compared indices of soil nitrogen (N) availability in the forest floor and mineral soil of deciduous, mixed, and coniferous stands of boreal mixedwood forest in northwestern Alberta. Deciduous stands had higher N availability, reflected by higher pools of NH4-N and inorganic N in the forest floor. Forest floors of deciduous stands also tended to have higher concentrations of microbial N but did not have higher levels of NO3-N or higher rates of net nitrification. Mixed stands showed the highest rates of net N mineralization. Soil N availability was more closely related to litter N content than to litter decomposition rate. The variation among the forest types is likely attributable to vegetation, as topography is fairly uniform, stands do not differ in soil texture, and N-availability indices correlated directly with the proportion of deciduous trees.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".