The role of bigleaf maple in soil chemistry and nutrient dynamics in coastal temperate forests
Bibliographic record
Abstract
The influence of bigleaf maple (Acer macrophyllum Pursh) in a forest dominated by Douglas-fir [Pseudotsuga menziessi (Mirb.)Franco] and western hemlock [Tsuga heterophylla (RAF.)Sarg.] was studied in a paired-plot design through an examination of the annual contribution of bigleaf maple litterfall to nutrient flux, its rate of decay, and its properties within the forest floor and mineral soil.Compared to conifer plots, bigleaf maple plots had litterfall significantly higher in all elements, and faster litter decomposition.Forest floor measurements revealed significantly higher pH and contents of N. Mineral soils beneath bigleaf maple had a lower bulk density, higher CEC, and total, mineralizeable and available N, compared to conifer plots.This suggests that bigleaf maple has the potential to increase nutrient cycling and availability in deciduousconifer mixed stands, and may be a desirable species in temperate coastal 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".