Understory Vegetation Dynamics across a Poplar Plantation Chronosequence in Reclaimed Coastal Saline Soil
Bibliographic record
Abstract
Although the understory vegetation abundance, diversity, and composition associated with stand development in natural forests have been well reported, only a few studies have examined the age-related changes of understory vegetation in fast-growing planted forests in reclaimed soils. This study measured the understory vegetation and soil variables in 8-, 12-, and 18-year-old poplar plantations in reclaimed coastal saline soil of Eastern China. This study examined how the abundance, diversity, and composition changed with stand development and the soil variables. Further, structural equation modeling (SEM) was used to evaluate the direct and indirect factors influencing the abundance and plant diversity throughout stand development. Herb abundance was significantly higher in the youngest and oldest stands, whereas shrub abundance was higher in the middle-aged stands. Shannon’s diversity index was significantly higher in the youngest stand for herbs, whereas it was highest in the middle-aged stands for shrubs. A multivariate analysis revealed that the herb and shrub composition were influenced by the stand age, total soil carbon and soil pH. The most parsimonious SEM model showed the negative direct effects of the stand age and the negative indirect effects of the stand age via the soil variables on shrub abundance, shrub diversity, and herb diversity, suggesting that the increase of overstory biomass with the stand age reduces resources available for the understory. Our results revealed that understory diversity and composition might change with stand development mediated by the changes in understory light and soil resources in fast-growing plantations.
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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 | 0.000 | 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 | 0.001 |
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".