Long-term effects of tanoak competition on Douglas-fir stand development
Bibliographic record
Abstract
In 1- to 2-year-old Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco var. menziesii) plantations near Cave Junction and Glendale, Oregon, sprout clumps of tanoak (Lithocarpus densiflorus (Hook. & Arn.) Rehd.) and other hardwoods were removed with herbicides in April 1983 to leave relative covers of 0%, 25%, 50%, or 100% of the nontreated cover, which averaged 15%. In 1996 (Cave Junction) and 1998 (Glendale), precommercial thinning (PCT) of Douglas-fir and cutting of nonconifer woody species were operationally applied across the four densities of tanoak. In 2005, Douglas-fir in 0% relative cover of tanoak averaged 5–8 cm larger at breast height and 3–6 m taller, and had two to four times the net stand volume of those growing in 100% relative cover. From 1999 to 2005, Douglas-fir stand growth accelerated more rapidly in tanoak relative covers of 0% and 25% than in covers of 50% and 100%. Differential development of Douglas-fir and hardwoods in relative covers of 0%, 25%, and 100%, followed by selection of crop trees via PCT, resulted in three distinct stand structures: pure stands of Douglas-fir with a single canopy layer 12–16 m tall, mixed stands with overstory Douglas-fir (12 m) and midstory hardwoods (7 m), and mixed stands with a single canopy layer (8–9 m).
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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".