Multi-year ecosystem response to hemlock woolly adelgid infestation in southern New England forests
Bibliographic record
Abstract
The introduced hemlock woolly adelgid (HWA) ( Adelges tsugae Annand) has generated widespread tree decline and substantial mortality of eastern hemlock ( Tsuga canadensis (L.) Carrière) throughout the eastern United States. To assess the magnitude of ecosystem response to this disturbance, we conducted a multi-year study of forests with and without damage from HWA. Infested forests had significantly higher HWA-induced foliar loss and significantly lower forest floor C:N ratios and soil organic matter than uninfested forests. There were no significant soil temperature differences among stand types, although infested stands did have lower forest floor soil moisture than uninfested stands. Net nitrification and net N mineralization rates were significantly higher in infested versus uninfested forests by the second and third year of this study, respectively. In addition, total N pools and resin bag capture of NH 4 and NO 3 were significantly higher in infested versus uninfested forests throughout this study. Increases in N were likely due to a combination of factors including enhanced decomposition, reduced uptake of water and N by declining trees, sparse understory vegetation, and N-enriched throughfall from infested canopies. These results confirm that invasive pests can initiate substantial changes in ecosystem function soon after infestation occurs, prior to substantial overstory mortality or understory reorganization.
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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".