Mortality and Recovery of Hemlock Woolly Adelgid (Adelges tsugae) in Response to Winter Temperatures and Predictions for the Future
Bibliographic record
Abstract
Eastern (Tsuga canadensis) and Carolina hemlocks (T. caroliniana) of eastern North America have been attacked by the non-native hemlock woolly adelgid (Adelges tsugae Annand) (HWA) since the first half of the 20th century. Unlike most insects, HWA develops through one generation from fall to late winter, exposing this insect to the lethal effects of winter temperatures. The mortality inflicted by winter temperatures on HWA determines the surviving population density as well as its ability to spread to uninfested areas. With the ongoing changes in climate, knowledge of this species’ ability to survive and spread in the future can help land managers prepare for its management. This study began during the winter of 2014 and ended in the spring of 2017. During this period, winter mortality of HWA was recorded at 100 sites from Maine to Georgia (n = 209). Changes in population density from the sistens to the succeeding progrediens generation were recorded at 24 sites (n = 35). Models were developed to predict HWA mortality using the lowest minimum temperature prior to the mortality assessment date, the number of days with mean temperature <−1 °C, and the mean daily temperature of the three days preceding that minimum. Models were also developed to predict population density changes from the overwintering sistens generation to the following progrediens generation. Future projections under climate change showed increases in winter survival and population growth rates over time. Especially towards the northeastern edge of T. canadensis’ distribution as minimum temperatures are predicted to increase at a greater rate. This will result in an increase in density throughout its current distribution and expansion northward causing an increase in its impact on eastern Tsuga spp.
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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 | 0.001 |
| 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) | 0.000 | 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".