Wood ash amendments as a potential solution to widespread calcium decline in eastern Canadian forests
Bibliographic record
Abstract
Decades of acidic deposition have depleted soil calcium (Ca) stocks over large areas of eastern Canada. The recovery of soil Ca levels has been limited despite substantial reductions in acidic deposition and will likely take many decades because rates of loss (owing to soil leaching, timber harvesting, and forest regeneration) may equal or exceed those of supply (via atmospheric input and natural mineral weathering). As low soil Ca levels may adversely affect local biota with relatively high Ca requirements, affected sites may benefit from supplementation with an alternative Ca source. A growing body of evidence suggests that the application of wood ash to Ca-deficient forest soils can help counteract the loss of Ca and other nutrients from the soil while boosting forest productivity. Yet the use of wood ash as a forest soil amendment is currently restricted in Canada, and the costs of obtaining permits and transporting/applying the ash make landfilling a more economically viable option. Here, we explore the potential of wood ash amendments in terms of their risks and benefits, dose and application frequency, time to see benefits, and longevity of benefits. After considering these topics in the context of Ca-deficient, acidified forest soils across eastern Canada, we propose that the potential benefits of ash amendments in these areas likely outweigh the risks. Future studies are needed to clarify both the short- and long-term effects of wood ash addition on different tree species in both natural and managed forests, as well as the potential benefits for carbon capture and implications for Ca-deficient aquatic ecosystems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".