Seasonal variation in water sources of the riparian tree species <i>Acer negundo</i> and <i>Betula nigra</i>, southern Appalachian foothills, USA
Bibliographic record
Abstract
Determining which water sources a plant accesses throughout a year is an important step in understanding how changes in source characteristics affect utilization by plants. Water sources of Acer negundo L. and Betula nigra L. of the foothills of the southern Appalachians Mountains were examined during one full year, including the phenological stages of leaf bolt, flowering, and leaf senescence and abscission. Source utilization was monitored, comparing the isotopic composition of water samples from woody tissue with those of possible water sources at the site. Species used deep ground and shallow soil water, with a greater reliance on deeper sources during the late growing season. Betula nigra was typically more depleted in δ 2 H than all water sources measured, while values from A. negundo were more variable throughout the study. Intraspecifically, isotopic values did not vary monthly or seasonally for either species (P > 0.56), while interspecific values were different for December, January, and July samplings (P < 0.02). Positive relationships occurred between air temperature and isotopic values of both species (P < 0.04), and may reflect increased evaporation from the upper soil layers at warmer temperatures, which both species appeared to use. An inability to sample all sources prevented the application of mixing models and may weaken conclusions.
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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".