Source water contributions and hydrologic responses to simulated emerald ash borer infestations in depressional black ash wetlands
Bibliographic record
Abstract
Abstract Forested wetlands dominated by black ash (Fraxinus nigra) are currently threatened by the rapid expansion of the exotic emerald ash borer (EAB;Agrilus planipennis,Coleoptera: Buprestidae) in North America, and very little is known about the hydrology and ecology of black ash wetlands. The ecohydrological response of forested wetlands following a canopy disturbance has the potential to affect critical ecosystem services, and the degree of this effect may largely depend on the wetland's hydrogeological setting. The main objectives of this study were to characterize the hydrologic connectivity of uninfested black ash wetlands and evaluate the water table response to a simulated EAB disturbance. We hypothesized that black ash wetlands in northern Michigan were (a) seasonally connected to, and derived the majority of their water from groundwater, and (b) wetland water tables would be elevated following a simulated EAB infestation due to decreased transpiration with the loss of black ash. The results indicate that the black ash wetland sites received most of their water from groundwater discharge. Significantly smaller site transpiration fluxes and significantly slower rates of drawdown were detected during the growing season in the girdled and ash‐cut treatment sites, and these responses collectively produced significantly elevated wetland water tables when compared to control sites in the latter portions of the growing season. However, the wetlands' strong connection with groundwater sources likely buffered the magnitude of hydrological responses associated with the loss of black ash from the landscape.
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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".