Difference in Regeneration Conditions in Pinus ponderosa Dominated Forests in Northern California, USA, over an 83 Year Period
Bibliographic record
Abstract
Forest inventories based on field surveys can provide quantitative measures of regeneration such as density and stocking proportion. Understanding regeneration dynamics is a key element that supports silvicultural decision-making processes in sustainable forest management. The objectives of this study were to: 1) describe historical regeneration in ponderosa pine dominated forests by species and height class, 2) find associations of regeneration with overstory, soil, and topography variables, 3) describe contemporary regeneration across various management treatments, and 4) compare differences in regeneration between historical and contemporary forests. The study area, a ponderosa pine (Pinus ponderosae Dougl. ex P. and C. Law) dominated forest, is located within the Blacks Mountain Experimental Forest (BMEF) in northeastern California, United States, which was designated as an experimental forest in 1934. We used 1935 and 2018 field surveyed regeneration data containing information about three species—ponderosa pine, incense-cedar (Calocedrus decurrens (Torr.) Florin) and white fir (Abies concolor (Grod. and Glend)—and four height classes: class 1: 0–0.31 m, class 2: 0.31–0.91 m, class 3: 0.91–1.83 m, and class 4: >1.83 m and <8.9 cm diameter at breast height. We used stocking as proxy for regeneration density in this study. We found that historically, stocking in the BMEF was dominated by shade-intolerant ponderosa pine in height classes 2 and 3. Two variables—overstory basal area per hectare (m2 ha−1) and available water capacity at 150 cm, which is the amount of water that is available for plants up to a depth of 150 cm from the soil surface—were significantly associated with stocking, and a beta regression model fit was found to have a pseudo-R2 of 0.49. We identified significant differences in contemporary stocking among six management scenarios using a Kruskal–Wallis non-parametric one-way ANOVA. Control compartments had the highest stocking followed by burned compartments. In contemporary forest stands, recent treatments involving a combination of burning and thinning resulted in high stocking in height classes 2 and 3. Overall, the stocking in historical BMEF stands was higher than in contemporary stands and was dominated by ponderosa pine.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".