Implications of a predicted shift from upland oaks to red maple on forest hydrology and nutrient availability
Bibliographic record
Abstract
Fire suppression has facilitated the spread of red maple ( Acer rubrum L.), a fire-sensitive, yet highly adaptable species, in historically oak-dominated forests of the eastern United States. Here, we address whether a shift from upland oaks to red maple could influence forest hydrology and nutrient availability because of species-specific effects on precipitation distribution and inorganic nitrogen (N) cycling. In eastern Kentucky, we measured seasonal variations in red maple, chestnut oak ( Quercus montana Willd.), and scarlet oak ( Quercus coccinea Münchh.) throughfall and stemflow quantity and quality following discrete precipitation events, and we assessed net N mineralization rates in underlying soils over a 2-year period (2006–2008). Throughfall was 3%–9% lower underneath red maple than both oaks, but red maple generated 2–3× more stemflow. Consequently, NH 4 + throughfall deposition was less under red maple than chestnut oak, whereas stemflow-derived nutrient inputs were substantially larger for red maple than both oaks. Soils underlying red maple had 5–13× greater winter net nitrification rates than soils under both oaks and 20%–30% greater rates of seasonal net ammonification than soils under chestnut oak. These findings suggest a spatial redistribution of water and nutrients via precipitation as red maple dominance increases and point to stemflow as an important mechanism that may foster red maple competitive success, further bolstering the mesophication process in the United States.
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".