Effects of spacing and site quality on tree growth, stand productivity, and biomass allocation of hybrid poplar (Populus spp.) plantations
Bibliographic record
Abstract
Fast-growing trees such as hybrid poplar ( Populus spp.) are characterized by rapid growth and high biomass production. However, their tree productivity can vary depending on tree spacing, site conditions and genotype selection. In this study, we evaluated the impact of site × spacing × clone interaction on tree productivity. We selected plantations of four hybrid poplar clones (747215; Populus trichocarpa Torrey & A. Gray × P. balsamifera L., 915004, 915005; P. balsamifera × P. maximowiczii Henry and 915319; P. maximowiczii × P. balsamifera) established at three spacings (1 × 4 m, 2 × 4 m and 3 × 4 m) across three sites of contrasting productivity in northwestern Quebec, Canada. Increasing spacing from 1 × 4 m to 3 × 4 m led to larger stem and higher mean annual increment (MAI) and above-ground biomass on a per tree basis at the most productive site. In contrast, tree size remained smaller and unchanged across spacings at the least productive site, and for the least productive clone. The proportion of biomass allocated to the stem decreased when spacing increased from 1 × 4 m to 3 × 4 m to the benefit of branches. Hybrid poplar plantations’ productivity was promising, as MAI per hectare reached 20.10 m 3 ha −1 year −1 at narrower spacing (1 × 4 m) at the most productive site for the most productive clone (915319). These findings highlight that site conditions modulate spacing effects and that high-yielding clones with optimal densities can maximize hybrid poplar productivity. • The effects of spacing on productivity and biomass varied depending on the clone and site. • Wider spacing increased per-tree growth at the most productive site and for the most productive clone. • Tree size was small and unchanged at the least productive site and for the least productive clone. • Wider spacing reduced stem biomass allocation and favored branch biomass.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".