Trade-offs across densities and mixture proportions in lodgepole pine-hybrid spruce plantations
Bibliographic record
Abstract
Monocultures tend to yield higher total stand volumes and are simple to manage. Yet, mixed species stands may result in similar stand volumes while providing benefits such as mitigating damage from insects and disease. To understand the effects of stand density and species mixture and their interactions on stand yield, tree size and morphology, and damage in monocultures and mixtures, we analyzed a 25-year-old experiment in interior British Columbia, Canada. The lodgepole pine (Pl)-interior hybrid spruce (Sx) experiment included three densities—1000, 1500, and 2000 stems per hectare (SPH)—and five species mixtures—1:0, 3:1, 1:1, 1:3, and 0:1 Pl:Sx. Results 25 years after stand establishment showed that stand volume was significantly larger with an increasing proportion of Pl across all stand densities. Pl had 10% larger diameters in the 1000 SPH than in the 2000 SPH and when mixed with Sx (1:1). Pl had larger crowns in mixtures regardless of density. Mixture proportion did not affect gall rust incidence or stem form in Pl, but reduced attack in Sx by spruce weevil. Our findings suggest that mixing Pl-Sx and high planting density decrease weevil attacks in Sx, which reduce loss in timber quality. Yet, Pl quality may decrease when mixed with Sx, due to larger Pl crowns. These results may be used to improve the implementation of management strategies that decrease trade-offs between yields, desired market tree sizes, and timber loss from pest and pathogens, while making the stands more resilient to further climate change impact.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".