Thinning and Gap Harvest Effects on Soil, Tree and Stand Characteristics in Hybrid Poplar Bioenergy Buffers on Farmland
Bibliographic record
Abstract
Linear bioenergy buffers planted with fast-growing trees along field edges are increasingly used to address challenges related to sustainable biomass production, climate change mitigation (i.e., carbon storage and microclimate regulation), water quality protection, and forest habitat connectivity in agricultural landscapes. This study assessed: (1) the extent to which 15 m wide hybrid poplar bioenergy buffers (1666 stems/ha) with closed canopy responded to thinning (diamond pattern of tree removal); (2) the regrowth of poplars from cut stumps following gap harvesting; (3) the effects of harvesting treatments on soil microclimate and nutrient availability; and (4) the spatiotemporal pattern of tree growth in unthinned plots. After three post-thinning years, results showed a strong growth response of seven-year-old hybrid poplar trees to thinning (12% increase in diameter and 30% increase in individual stem volume), accompanied by a slight decline in stand productivity. Gap harvesting was not an effective treatment to regenerate the stand from shoots growing from cut stumps because of the high deer browsing. Overall, thinning had marginal effects on soil nutrients and microclimate, compared with gap harvesting, which increased soil temperature, soil moisture, and the availability of several macro and micronutrients. However, harvest effects on soil nutrients were mostly observed during the first postharvest year, with the exception of soil nitrate, which was lowest in the gap treatment during the second postharvest year. Finally, the spatial pattern observed in tree growth between the buffer rows suggests that other more operational thinning patterns (row or corridor thinning) need to be evaluated in linear buffers.
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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".