Mature Hybrid Poplar Riparian Buffers along Farm Streams Produce High Yields in Response to Soil Fertility Assessed Using Three Methods
Bibliographic record
Abstract
This study had three main objectives: (1) to evaluate the aboveground biomass and volume yield of three unrelated hybrid poplar clones in 9 year-old riparian buffer strips located on four farms of southern Québec, Canada; (2) to compare yield data at 9 years with previous data (at 6 years); (3) to evaluate how soil fertility, measured using three different soil testing methods (soil nutrient stocks, soil nutrient concentrations, soil nutrient supply rates), is related to yield. Across the four sites, hybrid poplar productivity after 9 years ranged from 116 to 450 m3ha−1, for stem wood volume, and from 51 to 193 megagrams per hectare (Mg ha−1), for woody dry biomass. High volume and woody dry biomass yields (26.3 to 49.9 m3ha−1yr-1, and 11.4 to 21.4 Mg ha−1yr-1) were observed at the three most productive sites. From year 6 to 9, relatively high yield increases (8.9−15.1 m3ha−1yr−1) were observed at all sites, but the productivity gap between the less fertile site and the three other sites was widened. Clone MxB-915311 was the most productive across the four sites, while clone DxN-3570 was the least productive. However, at the most productive site, clone MxB-915311 experienced severe stem and branch breakages. Independently of the soil testing method used, available soil P was always the first soil factor explaining volume yield.
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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) | 0.000 | 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".