The presence of American beech litter can alter the growth response of sugar maple seedlings to drought
Bibliographic record
Abstract
Abstract In late successional forests of North America, sugar maple ( Acer saccharum Marsh.) and American beech ( Fagus grandifolia Ehrh.) form a complex ecosystem with intricate interactions. Over the last few decades, several studies have reported a marked increase in American beech dominance relative to sugar maple. Recent evidence suggests that extreme events such as drought could accelerate sugar maple's maladaptation to climate change and favor American beech in its replacement dynamics. In this study, we conducted a greenhouse experiment to investigate the effects of soil water stress and American beech presence on sugar maple seedling growth, structural physiology, leaf nitrogen, and chlorophyll. The seedlings were subjected to the following treatments independently and in combination for 82 days: soil water stress; soil originating from stands with American beech proliferation; soil sterilization; and presence of American beech litter. The results revealed that soil water stress was the primary factor significantly reducing sugar maple seedling growth, which also resulted in an increased root‐to‐shoot ratio. The presence of soil from stands with American beech proliferation did not exacerbate this negative effect. Soil sterilization, initially expected to reduce seedling growth by eliminating mycorrhizal associations, actually improved seedling growth. This suggests that adverse biotic processes, such as pathogens, were present in the soils regardless of their origin, and their negative effects outweighed the potential benefits from mycorrhization. The addition of American beech litter mitigated the effects of soil water stress but also introduced allelopathic compounds that hindered seedling growth. Overall, this study highlighted the complex interactions affecting sugar maple seedling growth, emphasizing that drought is a major limiting factor.
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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 | 0.000 |
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 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".