Emerald ash borer invasion of riparian forests alters organic matter and bacterial subsidies to south Michigan headwater streams
Bibliographic record
Abstract
Emerald ash borer (EAB) has killed millions of ash trees in the United States and Canada, yet impacts on terrestrial-aquatic linkages are largely unknown. Ash tree death along streams creates canopy gaps, increasing light to riparian plants and potentially affecting organic matter subsidies. Six EAB-related canopy gaps along streams across a gradient of timing of EAB invasion in Michigan were characterized for coarse woody material (CWM), terrestrial and aquatic leaf litter and their associated bacterial communities, and macroinvertebrates upstream, downstream, and at the center of the gap. Stream sites downstream of EAB-related canopy gaps had significantly lower dissolved oxygen and macroinvertebrate diversity than sites upstream and at the gaps. Yet there was no difference in CWM or aquatic leaf litter, likely due to downstream movement of organic matter from upstream riparian sources. Low abundance bacterial amplicon sequence variants unique to gap or forest were detected in leaves and leaf litter, suggesting that EAB-related canopy gaps altered leaf-associated bacterial communities. Overall, EAB invasion indirectly impacted some variables, while organic matter dynamics were resistant to change.
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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 | 0.001 | 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".