Factors influencing loblolly pine stand health in Fort Benning, Georgia, USA
Bibliographic record
Abstract
Loblolly pine (LBP; Pinus taeda L.) stands provides two-thirds of the existing federally protected red-cockaded woodpecker (RCW; Picoides borealis) habitat in Fort Benning, Georgia, USA. However, LBP in this area is suspected to face a forest decline issue, which may risk the sustainability of the RCW population. Land managers are attempting to convert LBP stands to longleaf pine (Pinus palustris Mill.), which once dominated the landscape, however the transition has to be gradual so current RCW habitat is maintained until longleaf pine stands sufficiently support RCW populations. It is critical to identify environmental factors influencing LBP health and convert LBP stands under poor environment to longleaf pine first. We installed 90 plots (30 × 30 m2) in mature (>38 years) loblolly pine forests and measured aspect, slope, soil texture, soil (pH, organic matter, cation exchange capacity, and exchangeable phosphorus, potassium, magnesium, and calcium) and foliar (nitrogen and phosphorus) nutrient, diameter at breast height, light exposure, and crown vigor class (CVC; 1 = good, 2 = fair, and 3 = poor). Stand age, site index, and burning and thinning history were retrieved from existing inventory data. Our results show that site index was the main factor in determining LBP health. Site index showed significant correlation with percentage of LBP in CVC1 (p = 0.04) and CVC3 (p = 0.07). Percentage of LBP in CVC3 tended to decrease as soil texture became finer. Poorer site index and coarser soil likely resulted in water stress during periods of drought leading to higher %CVC3 LBP. Based on these results, conversion to longleaf pine should start from LBP stands on coarser soil (or lower site index) at Fort Benning.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".