Plantation performance of chestnut hybrids and progenitors on reclaimed Appalachian surface mines
Bibliographic record
Abstract
Reclamation of surface mined sites to forests is a preferred post-mining land use option, but performance of planted trees on such sites is variable. American chestnut ( Castanea dentata (Marsh.) Borkh.) is a threatened forest tree in the eastern USA that may become an important species option for mine reclamation. Chestnut restoration using backcross hybrids that incorporate blight resistance may be targeted to the Appalachian coal mining region, which corresponds closely with the species’ native range. Thus, it is important to understand how chestnut hybrids perform relative to progenitors on reclamation sites to develop restoration prescriptions. Seeds of parents and three backcross generations of chestnut (100% American, 100% Chinese, and BC 1 F 3 , BC 2 F 3 , and BC 3 F 2 hybrids) were planted into mine soils in West Virginia, USA with shelter treatments. Survival for all stock types was 44% after 8 years (American 39%, Chinese 77%, BC 1 F 3 40%, BC 2 F 3 28%, and BC 3 F 2 35%). Height for all stock types was 33 cm after 8 years (American 28 cm, Chinese 67 cm, BC 1 F 3 30 cm, BC 2 F 3 21 cm, and BC 3 F 2 20 cm). At another site a year later, seedlings of the chestnut stock types were planted into brown (pH 4.6) or gray sandstone (pH 6.3) mine soils and seedling survival across all stock types was 58% after 7 years. Chinese had the highest survival at 82%, while the others ranged from 38 to 66%. Height was 63 cm for all stock types after 7 years. More advanced backcross hybrids (BC 2 F 3 and BC 3 F 2 ) had the lowest vigor ratings at both sites after 7–8 years. Our results indicate that surface mines in Appalachia may provide a land base for planting blight-resistant chestnuts, although Chinese chestnut outperformed American chestnut and later generation backcross hybrids. As blight-resistant chestnuts establish and spread after planting, chestnut trees may become a component of the forest canopy again and possibly occupy its former niche, but their spread may alter future forest stand dynamics.
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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 | 0.001 |
| 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".