Shifts in morphological traits, seed production, and early establishment of<i>Desmodium nudiflorum</i>following prescribed fire, alone or in combination with forest canopy thinning
Bibliographic record
Abstract
Reintroduction of periodic dormant-season fire and overstory thinning are currently being employed for forest ecosystem management in deciduous forests of eastern North America. These manipulations usually alter the flux of light and the availability of soil nutrients to the perennial herbaceous plants that dominate the understory. We utilized Bayesian statistical methods to examine the effects of prescribed burning (B) and the combination of burning and overstory thinning (T+B) on the morphology, seed production, and early establishment of Desmodium nudiflorum (L.) DC. (Fabaceae) in mixed-oak ( Quercus spp.) forests in southern Ohio. During the fourth growing season after the first fire, plants from thinned and burned (T+B) plots were 62% larger than plants from control plots (C). Both burning alone (B) and T+B treatments decreased specific leaf area (SLA). T+B also resulted in significantly decreased root mass ratio (RMR), and increased leaf mass ratio (LMR), and specific root length (SRL). During the first growing season after a second fire, both B and T+B resulted in significantly increased plant biomass, LMR, individual seed mass, and total seed production, as well as decreased SLA and plant height; in contrast, neither B nor T+B had significant impacts on leaf area ratio or seedling establishment. Prescribed fire, especially when combined with thinning, can result in increases in total biomass, seed size, and seed production, and hence enhance the fitness of this perennial herb in these mixed-oak forests.
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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 | 0.001 |
| 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) | 0.000 | 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".