Competitive success of natural oak regeneration in clearcuts during the stem exclusion stage
Bibliographic record
Abstract
We sampled dominant and codominant regeneration on 70 clearcuts, 21–35 years old, on the Hoosier National Forest in southern Indiana, USA, to evaluate influence of site variables on the competitive success of natural oak ( Quercus L.) over time. Collected data was compared with data collected on these same sites 20 years prior. Regression tree analysis indicated aspect, natural region, and oak abundance in preharvest stands had the greatest influence on competitive success (relative density, RD) of oak species in the latter sampling, which was then examined across sites as defined by these three variables. Oak RD increased across all mid- and some lower-slope positions, sites on which oaks are expected to be replaced by faster growing species. Drought events between sampling periods apparently contributed to a decline in RD and vigor of yellow-poplar ( Liriodendron tulipifera L.), a major competitor for growing space. Stump sprouts contributed 45% of dominant oak stems. Mean oak diameters were not significantly lower than those of other species groups, with the exception of yellow-poplar in younger stands and at mid-slope positions. Oak species drought tolerance, relative to more mesic species found on these sites, and the large proportion of oak stump sprouts likely contributed to oak competitive success.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".