Thinning effect on understory community and photosynthetic characteristics in a subtropical <i>Pinus massoniana</i> plantation
Bibliographic record
Abstract
Thinning forest stands changes biotic and abiotic conditions, subsequently altering understory communities including their photosynthetic characteristics. We investigated the effects of thinning (25% basal area decrease) in a subtropical Pinus massoniana Lamb. plantation at two post-thinning times: 0.5 years (PT 0.5 ) and 2.5 years (PT 2.5 ). Thinning (PT 0.5 and PT 2.5 ) significantly increased understory density (+104.9% and +142.4%, respectively), aboveground biomass (+191.1% and +239.2%, respectively), the Shannon–Wiener index, and the Pielou index and decreased the Simpson index (p < 0.05). Species richness significantly increased at PT 0.5 and decreased at PT 2.5 (p < 0.05). Photosynthetic characteristics of new and old leaves of three dominant species (Woodwardia japonica (Linn. f.) Sm., Dryopteris championii (Benth.) C. Chr., and Dicranopteris dichotoma (Thunb.) Bernh.) showed different variations at 0.5 and 2.5 years after thinning, depending on their various adaptive strategies. Generally, thinning improved leaf carbon fixation capacity of these dominant plants (except W. japonica old leaves). Leaf photosynthetic characteristics of these species exhibited some common changes with respect to leaf morphological attributes and chlorophyll content. Thinning increased new-leaf length (or width) and reduced old-leaf chlorophyll b concentration at PT 0.5 but reduced new-leaf length, specific leaf area, and all-leaf chlorophyll concentration at PT 2.5 . In conclusion, thinning is a useful tool for increasing understory abundance and carbon fixation capacity of some fern species.
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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) | 0.000 | 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 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".