Soil and Nutrient Cycling Responses in Riparian Forests to the Loss of Ash (Fraxinus spp. L) from Emerald Ash Borer (Agrilus planipennis, Fairmaire)
Bibliographic record
Abstract
Emerald ash borer (EAB) is an alien invasive species that is spreading across Canada and the United States killing ash trees. In riparian forests where ash may be abundant; loss of ash can induce significant structural changes; including the creation of canopy gaps; changes in light penetration; expansion of ground vegetation; and alteration of soil nitrogen and carbon cycling. In 2014 and 2015, we examined the effects of EAB-caused gaps in riparian forests on soil nutrient dynamics. Two sites with different infestation timelines, a “new” site (mortality in past 2–3 years) and an “old” site (infested 10 years previous) were selected to determine temporal differences in effects of canopy gaps created by ash loss on litterfall, herbaceous ground vegetation, and soil nutrient cycling. Within both sites, plots with clustered dead ash (canopy gap plots—CG) were paired with nearby plots of full canopy and no ash (canopy closed plots—CC), and differences between paired plots determined. Total litterfall was observed at all sites but was only significant at the new infestation site. Reductions in leaf litter deposition in CG plots resulted in reduced N and C flux to the forest floor but soil C and N concentrations, and nitrogen mineralization rates, were not significantly different between CG and CC plots. Nitrate concentration in soil solution was significantly greater in CG plots compared to CC plots at the new infestation sites but showed the opposite trend at the old infestation sites. Herbaceous ground vegetation biomass was significantly greater (up to 10×) in CG plots than in CC plots. Overall, despite changes to riparian forest canopy structure and litterfall, there was no significant difference in soil nutrient cycling between EAB-induced canopy gaps and closed canopy plots after 10 years, suggesting a high resilience of riparian forest soils to EAB infestation
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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 | 0.001 |
| 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".