Changes in DOC and DON fluxes in response to harvest intensity of black-spruce-dominated forest ecosystems in northwestern Ontario
Bibliographic record
Abstract
The current study was conducted to quantify and compare dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) fluxes through black-spruce-dominated forests, to compare the source/sink characteristics of sphagnum- versus feathermoss-dominated forest floors, and to identify changes in DOC and DON flow patterns occurring as a result of clearcut harvesting. After 2 yr of pre-harvest monitoring, replicated, experimental harvests of varying intensities of biomass removals were conducted followed by 4 yr of post-harvest sampling. Prior to harvest, the upland site type, dominated by feathermoss, was a significant source of DOC and DON, whereas, the wet-sphagnum-dominated sites exported minor amounts of these solutes. After harvest, DOC and DON fluxes peaked in the second year, but then dropped off significantly to at or below pre-harvest levels. On the upland site type, chipper debris appeared to be a major source of DOC and DON generating fluxes well above the pre-harvest levels. On the wetter site types, it appeared that microclimate differences between harvest treatments had a stronger influence on DOC and DON production than did the amount or type of harvest residue. Full-tree harvesting did not significantly alter the production of DOC and DON when compared with stem-only harvesting on the sites included in this study. Key words: DOC, DON, forest floor leachate, black spruce, harvesting response
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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 | 0.001 | 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".