<i>Picea rubens</i>growth at high versus low elevations in the Great Smoky Mountains National Park: evaluation by systems modeling
Bibliographic record
Abstract
For half a century, red spruce ( Picea rubens Sarg.), a commercially and ecologically important boreal tree species, has experienced growth decline and high mortality in eastern North America. A tree growth systems model, ARIM (annual radial increment model), was developed to evaluate responsible factors for red spruce growth in the Great Smoky Mountains National Park. The dominant cause at higher elevations (1800–2000 m) was found to be air pollution involving high-frequency acidic rain and cloud immersion. The identified causes at lower elevations (1450–1700 m) were insufficient solar absorption due to photoinhibition, drought stress resulting from reduced precipitation and high evapotranspiration due to warmer temperatures, and minor effects of air pollution. The ARIM exemplifies a complex systems concept and methodology for evaluating multivariable factors in tree growth systems. ARIM provides a general model structure that incorporates complex direct and indirect interactions for tree system studies and quantitatively integrates knowledge and data from different disciplines by developing a new set of indices, the relative basis index values. The ARIM results implicate comprehensive habitat-dependent directions for long-term conservation policies and management of red spruce with environmental changes, climate change, and air pollution in the Great Smoky Mountains National Park.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".