Assessment of calcium status in Maine forests: review and future projection
Bibliographic record
Abstract
Forest harvesting and acidic deposition can cause substantial decreases in the calcium (Ca) inventory of forest soils if such losses are not replenished through mineral weathering, atmospheric deposition, or fertilization. The net balance between losses and gains defines the forest Ca status. Site-specific studies have measured Ca pools and fluxes in Maine forests, but no synthesis has been published. In this paper, I review the literature on forest Ca and assess the current status and potential future trends. Forest soils in Maine are currently at lesser risk of Ca depletion compared with many forest soils in the central and southeastern United States, because levels of acidic deposition and rates of Ca accumulation in trees are lower in Maine. The rate of Ca accumulation in trees is reduced in Maine as a result of lower growth rates and a higher proportion of conifer trees that require less Ca than hardwoods. However, field-scale biogeochemical studies in Maine and New Hampshire, and regional estimates of harvest removals and soil inventories coupled with low weathering estimates, indicate that Ca depletion is a realistic concern in Maine. The synthesis of site-specific and regional data for Maine in conjunction with the depletion measured directly in surrounding areas indicates that the Ca status of many forest soils in Maine is likely declining. Ca status could decrease further in the future if forest growth rates increase in response to climate trends and recovery from insect-induced mortality and excessive harvesting in recent years. Proposed climate change induced reductions in spruce and fir and increases in hardwoods would also increase the risk of Ca depletion.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".