Tree bole mineralization rates of four species of the Canadian eastern boreal forest: implications for nutrient dynamics following stand-replacing disturbances
Bibliographic record
Abstract
To assess nutrient dynamics in decomposing logs of trembling aspen (Populus tremuloides Michx.), white birch (Betula papyrifera Marsh.), white spruce (Picea glauca (Moench) Voss), and jack pine (Pinus banksiana Lamb.), we monitored mass losses and changes in N and P contents in dead boles from a chronosequence of sites following stand-replacing disturbances. To assess the importance of wood decomposition to nutrient cycling, we compared net estimates of nutrient release from logs with net nutrient immobilization in live-tree biomass of stands as a function of time since disturbance. Mineralization rates were 0.060, 0.053, 0.038, and 0.020·year –1 for trembling aspen, white birch, white spruce, and jack pine logs, respectively. Trembling aspen boles released large quantities of N and P during the first year of decomposition (51 kg·ha –1 of N and 7 kg·ha –1 of P, assuming a bole volume of 150 m 3 ·ha –1 ). White birch boles acted initially as a nutrient sink and delayed the release of immobilized nutrients until a period when the stand's net nutrient immobilization rates were highest. Jack pine boles appeared to be intermediate in terms of their contribution as a sink or a source of nutrients but, in mature stands, provided up to 40% of N and 26% of P immobilized annually in tree biomass. As pure stands of white spruce are rare in boreal Quebec, information on nutrient accumulation in white spruce stands was not available.
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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 | 0.001 |
| 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".