An assessment of phosphorus limitations to soil nitrogen availability across forest ecosystems of north coastal British Columbia
Bibliographic record
Abstract
The wet, slow-growing forests of western redcedar (Thuja plicata Donn ex D. Don) and salal (Gaultheria shallon Pursh) on the north coast of British Columbia are characteristically low in available phosphorus (P) compared with more productive forest ecosystems. It has been suggested that declining P availability can eventually limit soil biological activity and restrict nitrogen (N) cycling. We investigated this potential link between P availability and N cycling for three forest types (cedarsalal, hemlock lanky moss and spruce sword fern) covering a wide gradient in site productivity. Forest floors (upper 20 cm) and mineral soils (20 cm depth) were collected from five replicate sites of each forest type and incubated for 20 weeks at field moisture content with and without an amendment of NaH2PO4. We found that organic P concentrations of both forest floors and mineral soils were positively correlated to extractable inorganic N concentrations (unamended soils over 20 weeks). The addition of P to the low-productivity cedarsalal soils led to significant increases in extractable inorganic N in the forest floors and mineral soils. P amendments led to either a smaller or nonsignificant increase in extractable N for moderately and highly productive soils. Soil respiration of CO2 and respiration quotients were substantially reduced in forest floors with a P amendment, suggesting N mineralization was governed by exoenzyme allocation rather than decomposition rates. These results demonstrate a possible enhancement in N supplies with an application of P to low-productivity cedarsalal forests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".