An assessment of direct and indirect effects of climate change for populations of the Rocky Mountain Apollo butterfly (Parnassius smintheus Doubleday)
Bibliographic record
Abstract
Abstract Climate change is occurring and insects are responding. Current challenges for ecologists and managers are predicting how organisms will respond to continuing climate change and determining how to mitigate potential negative effects. In contrast to broad scale predictions for climate change involving the distribution of species, in this article we highlight the many ways in which local populations of the Rocky Mountain Apollo butterfly (Parnassius smintheus Doubleday) are predicted to respond to climate change. Using experimental and observational data collected over the past 15 years, we detail both direct and indirect effects. In addition, we identify limitations in our knowledge restricting the ability to predict how populations will respond to climate change. Some changes, such as warmer winter temperatures, may have beneficial effects; however, most of the effects of climate change will be detrimental. Variability in snow cover during the overwintering period and habitat loss due to forest encroachment have the largest potential negative effects.
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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 | 0.001 | 0.002 |
| 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".