Biomass and Volume Yield in Mature Hybrid Poplar Plantations on Temperate Abandoned Farmland
Bibliographic record
Abstract
In this study, we developed clone-specific allometric relationships, with the objective of calculating volume and biomass production after 13 years in 8 poplar plantations, located across an environmental gradient, and composed of 5 unrelated hybrid poplar clones. Allometry was found to be very similar for clones MxB-915311, NxM-3729 and DNxM-915508, all having P. maximoviczii parentage. Clones DxN-3570 and TxD-3230 also had a similar allometry; for a given DBH they have a lower stem volume, stem biomass and branch biomass than P. maximoviczii hybrids. Strong Site × Clone interactions were observed for volume and woody biomass growth, with DxN and TxD hybrids only productive on low elevation fertile sites, whereas P. maximovizcii hybrids were also very productive on higher elevation sites with moderate to high soil fertility. At the site level (5 clones mean), yield reached 27.5 and 22.7 m3/ha/yr. on the two best sites (high fertility and low elevation), confirming the great potential of southern Québec (Canada) for poplar culture. The productivity gap between the most and least productive sites has widened from year 8 to year 13, highlighting the need for high quality abandoned farmland site selection in terms of climate and soil fertility. Although clone selection could optimize yield across the studied environmental gradient, it cannot fully compensate for inadequate site selection.
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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 | 0.001 | 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 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".