Windthrow modifies soil solution chemistry and nutrient leaching in the Canadian black spruce boreal forest
Bibliographic record
Abstract
Soil solution chemistry is directly related to vegetation nutrition and growth in forest ecosystems. However, the impacts of natural disturbances on boreal forest soil solution composition and nutrient fluxes remain unclear. In this study, we explore the effects of a windthrow on soil solution chemistry collected weekly between 2012 and 2018 during the snow-free period at a Canadian black spruce boreal forest site. We show that the windthrow had an important effect on soil solution chemistry within only a few days, inducing much higher NO 3 − and NH 4 + concentrations and a strong pH drop, persisting up to six years after the disturbance. Following the windthrow, soil solution major ion concentrations (i.e., K + , Ca 2+ , Mg 2+ , Mn 2+ , Cl − , SO 4 2− ) similarly increased but with various intensities and recovery times. This windthrow also occurred on a site receiving a chronic ammonium nitrate treatment as part of a N deposition simulation experiment, which showed that two decades of N treatment had nearly no impacts on soil solution NO 3 − and NH 4 + concentrations. Therefore, our results indicate that windthrows could potentially alter the North American boreal forest soil chemistry much more than elevated N deposition corresponding to 200 years of accelerated ambient N deposition. While this finding needs to be supported by larger studies, it clearly highlights the significance of wind disturbances’ impacts on nutrient cycling and calls for more research as windthrow frequency is predicted to increase with global change.
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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".