Environmental change in former and present Karner Blue butterfly habitats
Bibliographic record
Abstract
Enrique Gomezdelcampo, AdvisorThe Karner Blue butterfly is a federally endangered species that once was widely distributed throughout 12 states along the northern part of the United States and Ontario, Canada.Now it only exists in seven states.Many factors are considered to have affected the extinction of this species and this study examines the effect of climate change on the persistence of the Karner Blue butterfly.Five sites were selected to study the effect of climate change: Allegan, MI, Fort McCoy, WI, and Saratoga, NY are the three sites that currently have a Karner Blue population while Oak Openings, OH, and Pinery, Ontario are the two sites where the Karner Blue has disappeared.Daily climate data from the 1950s to 2005 were used for calculating 13 climatic indices related to precipitation and temperature.The data were broken into two time periods (pre-1984 and post-1984) to analyze how those indices have changed.Statistical analyses including t-tests and ANOVA and graphs such as time series and box plots were used to compare these indices within two time periods among five sites.The results showed that different indices have changed differently among the five sites.The number of extreme hot days and number of extreme cold days per year have a statistically significant change in the sites where the Karner Blue butterfly disappeared.The precipitation-related indices do not show a statistically significant different trend among the five sites.Temperature seems to have more effect on the existence of the Karner Blue butterfly.Furthermore, butterfly population size and lake effects are also important factors that cannot be neglected.Larger populations seem to have better chances to survive during a dramatic climate change event.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".