Using the output from global circulation models to predict changes in the distribution and abundance of cereal aphids in Canada: a mechanistic modeling approach
Bibliographic record
Abstract
Abstract Climate change will alter the abundance and distribution of species. Predicting these shifts is a challenge for ecologists and essential information for the formation of public policy. Here, I use a mechanistic mathematical model of the interaction between grass growth physiology and aphid population dynamics, coupled with the climate change projections from the UK's Hadley Centre HadCM3 global circulation model (GCM) and Canada's Center for Climate Modeling and Analysis CGCM2 GCM to predict the changes in the abundance and distribution of summer cereal aphid populations in wheat‐growing regions of Canada. When used with the HadCM3 projections, the model predicts a latitudinal shift northward in abundances but there is longitudinal variation as well. However, when used with the CGCM2 projections the model predicts that continental regions will see a decline while coastal regions will see an increase in summer cereal aphid populations. These effects are stronger under the higher emissions scenarios.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".