Water Level Controls on Sap Flux of Canopy Species in Black Ash Wetlands
Bibliographic record
Abstract
Black ash (Fraxinus nigra Marsh.) exhibits canopy dominance in regularly inundated wetlands, suggesting advantageous adaptation. Black ash mortality due to emerald ash borer (Agrilus planipennis Fairmaire) will alter canopy composition and site hydrology. Retention of these forested wetlands requires understanding black ash’s ecohydrologic role. Our study examined the response of sap flux to water level and atmospheric drivers in three codominant species: black ash, red maple (Acer rubrum L.), and yellow birch (Betula alleghaniensis Britt.), in depressional wetlands in western Michigan, USA. The influence of water level on sap flux rates and response to vapor pressure deficit (VPD) was tested among species. Black ash had significantly greater sap flux than non-black ash at all water levels (80–160% higher). Black ash showed a significant increase (45%) in sap flux rates as water levels decreased. Black ash and red maple showed significant increases in response to VPD as water levels decreased (112% and 56%, respectively). Exploration of alternative canopy species has focused on the survival and growth of seedlings, but our findings show important differences in water use and response to hydrologic drivers among species. Understanding how a replacement species will respond to the expected altered hydrologic regimes of black ash wetlands following EAB infestation will improve species selection.
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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) | 0.001 | 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".