Influence of moisture, nutrients, and distance from stream on early-stage mass loss of western red cedar leaf litter in headwater riparian forests
Bibliographic record
Abstract
Western red cedar (Thuja plicata Donn ex D.Don) is a dominant species in forests of the Pacific Northwest in North America, but little is known about its decomposition in riparian habitat. We experimentally tested how early-stage mass loss of cedar leaf litter varied with distance from the stream (five distances from 1 to 40 m away) and responded to nutrient and water additions near four headwater streams in southwestern British Columbia. We ran three coarse-mesh litterbag trials in durations between five months to one year from January 2013 and January 2014. Litterbags were either untreated or given the following treatments: water additions during dry summer months, nitrogen and phosphorus additions, or additions of both. Control litterbags lost 21% initial mass over 12 months (January 2013 – January 2014), 20% over five months (January 2013 – June 2013), and 15% over eight months (June 2013 – January 2014). Rates of mass loss did not increase with water in any trial but did increase with nutrients in the 12-month trial. Litter located 40 m from the stream lost 7% more mass than that located 1 m away in this same trial. Our study indicates that cedar leaf litter mass loss responded primarily to nutrient additions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".