Recovery trends and predictions of Fraser fir (<i>Abies fraseri</i>) dynamics in the Southern Appalachian Mountains
Bibliographic record
Abstract
The endemic Fraser fir (Abies fraseri (Pursh) Poir.) is found in only seven montane regions in the southern Appalachians above ca. 1500 m elevation. Due to widespread insect-caused mortality from the invasive balsam woolly adelgid (Adelges piceae Ratzeburg), as well as possible impacts from climate change and atmospheric pollution, the future of Fraser fir populations remains uncertain. Long-term monitoring programs have been in place since the 1980s, and here we present the first predictive population models for endemic Fraser fir populations using the inventory data from Great Smoky Mountains National Park, which contains 74% of extant Fraser fir forests. Using two kinds of population data (understory density counts and overstory census data), we model Fraser fir population dynamics on five different mountaintops as a stage-structured matrix model with transition parameters estimated using hierarchical Bayesian inference. We predict robust recovery over the next several decades for some Fraser fir populations, particularly where mature overstory fir has persisted throughout the last two decades, and continued decline for populations at the lowest elevations. Fraser fir densities are already low at these lower elevations, suggesting that this population is vulnerable to local extirpation.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".