Forecasting the response of spruce budworm defoliation to climate change in Ontario
Bibliographic record
Abstract
Predicting the effect of climate change on insect populations is critical to improve the reliability of forest management plans, wood supply projections, and pest protection programs. In this study, we use an empirical model to relate the spatial distribution of past defoliation by spruce budworm ( Choristoneura fumiferana Clem.) in Ontario to bioclimatic variables. We then apply data from six climate change scenarios to this model to project potential changes in the distribution of defoliation for 2011–2040. The spatial distribution of historical defoliation was found to be related to winter maximum and minimum temperatures, forest content in balsam fir ( Abies balsamea (L.) Mill.) and white spruce ( Picea glauca (Moench) Voss), and spring and summer minimum temperatures. All six climate change scenarios project broadly similar changes in the spatial patterns of defoliation: (i) an extension of the northern limit of defoliation as far as available data go or close to it, (ii) a decrease in the frequency of defoliation in the center of the historical defoliation belt, and (iii) a persistence of the southern limit of defoliation. This leads to a projected increase of the total area defoliated of between 22.8% and 25.5%, while the mean frequency of defoliation, calculated over the whole study area, would slightly increase (+1%) or decrease (–17.7% to –2.9%).
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".