The relative photosynthetic contribution of old and new fronds of the wintergreen fern Dryopteris carthusiana, Ontario, Canada<sup>1</sup>
Bibliographic record
Abstract
Goldblum, D. and M. C. Kwit (Department of Geography, Northern Illinois University, DeKalb, IL 60115). The relative photosynthetic contribution of old and new fronds of the wintergreen fern Dryopteris carthusiana, Ontario, Canada. J. Torrey Bot. Soc. 139: 270–282. 2012.—A number of understory species in temperate and boreal forests are characterized by the wintergreen habit which entails retaining leaves for a portion of a second growing season. Several hypotheses have been offered to account for this trait, most commonly: old leaves serve as storage organs for nutrients required for spring growth or old leaves contribute to the overall carbon gain of the plant given their presence in the understory during the period of high radiation prior to canopy leafout. In this study, using field-derived light response curves, plant demographic data, leaf phenological data, and twice-hourly understory light levels, we model the relative contributions of old and new fronds to overall seasonal net carbon gain of a common fern, Dryopteris carthusiana, in a boreal and deciduous forest in Ontario, Canada. Approximately 43% of the total fern carbon gain in the deciduous forest occurs in the 40 days before canopy closure, compared to 46% in the boreal forest during the same period. In the deciduous forest, approximately 30% of the total fern net carbon assimilation occurs at the end of the growing season following overstory leaf fall, which was not the case in the boreal forest. Old fronds contribute 29% of overall carbon gain in the deciduous forest, but substantially more (63%) in the boreal forest. We estimate the total net carbon assimilation by D. carthusiana ferns in the deciduous forest at 90.7 kg C ha−1 for the growing season and 45.5 kg C ha−1 in the boreal forest. Our findings quantify the importance of the wintergreen habit for overall fern seasonal carbon gain, as well as the importance of early season high light conditions for understory plants in deciduous forests.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".