Effect of thinning, fertilization with biosolids, and weather on interannual ring specific gravity and carbon accumulation of a 55-year-old Douglas-fir stand in western Washington
Bibliographic record
Abstract
Marketing timber is shifting from logs, lumber, and veneer measured volumetrically to include carbon storage and energy that are based on dry mass. Conversion between volume and dry mass relies on accurate estimates of wood specific gravity (SG). We measured width and SG of growth rings and their earlywood and latewood components with X-ray densitometry on trees from controlled, thinned, biosolid fertilized, and combined treatments applied to a 55-year-old Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) stand. We developed models to predict interannual SG from climate and treatment effects and compared 20 year changes in dry mass and carbon storage with estimates from biomass equations and from the Wood Handbook average SG. Thinning increased latewood width but did not affect ring SG. Biosolid fertilization increased earlywood and latewood width and decreased ring SG 8% by decreasing earlywood SG, latewood SG, and latewood percentage. SG decreased with increased July soil moisture deficit; alternatively, SG increased with increased July total precipitation. Warmer mean March–May or August–November temperatures also increased SG. Because of the effects on SG, dry mass and carbon storage changes differed from volume changes produced by the treatments. Dry mass estimates using the average Wood Handbook SG or those calculated from biomass equations were inconsistent between treatments, with errors up to 50%.
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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) | 0.001 | 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".