The combined effects of low light and low water on seedling growth vary in their severity based upon tree species and seedling traits
Bibliographic record
Abstract
Environmental stresses rarely occur in isolation; in fact, plants often combat multiple stresses at once. Moreover, while most studies examining the combined effect of different factors have focused on greenhouse experiments, comparing experimental results with field studies is necessary to validate results. Here, we examine the effect of low water and light on the growth of Acer rubrum, Acer saccharum, and Quercus rubra in a greenhouse and the field. We tested whether the combined effects were additive, synergistic, or antagonistic and studied whether these responses were mediated by functional traits. In the greenhouse we found an additive effect of the two stresses across species; however, individual species responded differently with A. rubrum showing additive and A. saccharum and Q. rubra showing antagonistic effects. Species were unique in their trait responses, but species with antagonistic effects tended towards more acquisitive strategies belowground. Our field results partially matched our greenhouse findings, with water and light stress resulting in additive effects in all species except for A. saccharum. Our results suggest that A. saccharum and Q. rubra may be better equipped to cope with low light and water, and that studies should be careful to extrapolate from greenhouse studies on multiple stress response alone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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".