<i>Quercus michauxii</i> regeneration in and around aging canopy gaps
Bibliographic record
Abstract
Floodplain forests are subject to frequent windstorms, which create canopy gaps and microtopographic heterogeneity. Forest regeneration may be enhanced when light and microtopographic conditions are both favorable, but slower growing canopy species may still require multiple disturbance events to reach the canopy. In 2001, we revisited a cohort of Quercus michauxii Nutt. seedlings planted in 1995 on pitmound microsites that were constructed in and around canopy gaps to determine patterns of seedling persistence and investigate the effects of canopy openness and microtopography on seedling survival and growth. After 7 years, canopy openness in gap centers had decreased to levels that did not differ from levels in forest canopy. Seedling height and maximum root depth were greatest in gap centers, where light was initially greater but seedling growth rates declined over time. Soil moisture was greater in pits, where establishment and survival were very low. Roots of some seedlings reached from mound surfaces to depths and moisture levels comparable to those of adjacent pits, which might facilitate survival in both floods and droughts. Quercus michauxii can persist on elevated sites in aging gaps, and positive feedback in sites favorable for recruitment can enhance seedling growth; ascent into the canopy will likely require additional canopy-opening events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
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".