Forest dynamics and climate sensitivity of an endangered Carolina hemlock community in the southern Appalachian Mountains, USA
Bibliographic record
Abstract
During the last century, the eastern United States has functionally lost two major tree species (American chestnut and American elm), two more, eastern and Carolina hemlock, will likely be functionally extinct during much of their ranges by 2050. Carolina hemlock forests are geographically limited to high elevations in the southern Appalachian Mountains and are considered to be endangered. We collected forest stand, composition, and tree age data at the beginning of a hemlock woolly adelgid (HWA) infestation. Prior to the arrival of HWA, Carolina hemlocks were healthy and densely populated in the overstory and understory. While Carolina hemlock regenerated successfully and continuously from 1850 to 2010, the development of this Carolina hemlock forest will be altered by the HWA and may result in an increase in the density of northern red oak, white oak, mountain laurel, and Catawba rhododendron. Carolina hemlocks prefer cool, wet summers with older trees experiencing greater reductions in radial growth than younger trees during droughts. This study demonstrates that dendrochronological techniques can provide critical annual information on Carolina hemlock forest development and tree age–climate response. Our results provide a multicentury perspective for conservation efforts and management of Carolina hemlock forests in the southern Appalachian Mountains.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".