Higher-order bud production increases tillering capacity in the perennial caespitose grass Scribner’s Panicum (<i>Dichanthelium oligosanthes</i>)
Bibliographic record
Abstract
The persistence and dynamics of perennial grass populations strongly depend on tiller recruitment from the bud bank. Because of the structural organization of grasses as populations of phytomers, bud production and tillering are constrained by morphology. An infrequent trait observed in only a few caespitose grasses is the branching of buds to produce higher-order buds prior to tiller development. We studied bud bank dynamics in Dichanthelium oligosanthes (Schult.) Gould a C3 perennial caespitose grass widely distributed in the eastern Great Plains. A hierarchy of bud development occurred in D. oligosanthes, with primary buds branching to produce secondary, tertiary, and quaternary buds. This higher-order bud production increased the overwintering propagule supply for spring recruitment by 4.5 times, and more than half of successful tiller recruits originated as higher-order buds. The temporal patterns of higher-order bud production and development suggest that growing season length may be an important factor determining the extent of higher-order bud production and subsequent year tiller natality in D. oligosanthes. Higher-order bud production likely has important consequences for the population dynamics of grasses. It may increase bud bank densities and tillering capacity, buffer population dynamics, and increase intraclonal tiller densities and resource consolidation in caespitose grasses.
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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".