Marginal response of non‐structural carbohydrates and increased biomass in a dominant shrub ( <i>Dasiphora fruticosa</i> ) to water table decline in a minerotrophic peatland
Bibliographic record
Abstract
Assessing how dominant peatland species, such as Dasiphora fruticosa, adapt to water table decline is crucial to advance understanding of their growth and survival strategies. Currently, most studies have primarily focused on their growth and biomass, with limited knowledge on the response of non-structural carbohydrates (NSCs) and physiological adaptations of these woody plants under long-term drainage. This study assessed the response of photosynthesis and transpiration rates, biomass, and NSC concentrations (including soluble sugars and starch) in the leaves, stems, and roots of D. fruticosa to long-term drainage in a minerotrophic peatland. The aim was to elucidate the plant response and adaptation mechanisms to water table decline. Dasiphora fruticosa effectively regulated carbon (C) demand and supply by significantly enhancing photosynthesis, transpiration, and biomass accumulation, thereby maintaining stable C storage as the water table declined. There was a notable reduction in soluble sugar concentration in leaves with increasing water table decline, while starch concentrations in all three organs remained relatively constant. Although the concentration of soluble sugars in leaves was consistently higher than that in roots and stems, the relative proportion of soluble sugars and starch gradually decreased in leaves and increased in roots and stems with water table decline. Our findings reveal that D. fruticosa reduces NSC concentrations in leaves while increasing biomass to adapt to water table decline. This acclimation might significantly impact C dynamics in peatlands. Understanding these mechanisms is vital for predicting the dynamics of C sequestration and emission in peatland ecosystems under changing environmental conditions.
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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".