Nutritional response of sugar maple seedlings to water stress under highly nitrogen‐enriched soil conditions
Bibliographic record
Abstract
Abstract Background Temperate forests of eastern North America will be increasingly affected by chronic atmospheric nitrogen deposition, elevated temperatures, and drought events that will expose trees to moisture‐stressed conditions in non‐nitrogen‐limited soils. Yet, little is known regarding the response of sugar maple‐dominated forests to moisture stress under non‐nitrogen‐limiting conditions. Aims The objective of this greenhouse study was to analyze the effects of moisture stress on the nutrition and growth of sugar maple seedlings growing on base‐poor forest soils that were strongly fertilized with nitrogen. Methods One‐year‐old sugar maple seedlings were grown with and without water stress on soils from a sugar maple stand that had been fertilized for 15 years at a rate of 85 kg N ha−1 y−1. Results Decreased moisture availability decreased total, leaf, root and stem biomass, and root/stem ratio. Leaf concentrations of N, P, Ca, and Mg and root concentrations of K, Ca, and Mg were 6% to 23% significantly lower under stressed versus unstressed conditions despite no changes in N, P, K, and Mg concentrations in the soil. Only soil Ca concentration was negatively affected by the moisture stress treatment. Soil and leaf δ15N and the k‐factor (i.e., isotopic discrimination effect of 15N‐labeled sources of N between roots and soil) that was used to assess N‐use efficiency of sugar maple seedlings did not differ between water stress treatments. Conclusions Our results indicate that decreasing root biomass of sugar maple seedlings under moisture stress in non‐nitrogen‐limiting situations would decrease their ability to take up nutrients that are necessary for growth and induce lower concentrations in leaves and roots. Expected severe drought events could substantially limit nutrient uptake capacity of sugar maple seedlings on sites that are subject to chronic atmospheric N‐deposition, which would contribute to dieback in sugar maple stands.
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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".