Landscape‐level environmental stressors contributing to the decline of Poweshiek skipperling ( <scp> <i>Oarisma poweshiek</i> </scp> )
Bibliographic record
Abstract
Abstract 1. The Poweshiek skipperling [ Oarisma poweshiek (Parker, 1870; Lepidoptera: Hesperiidae)] is a federally endangered butterfly that was historically common in prairies of the upper Midwestern United States and Southern Manitoba, Canada. Rapid declines over the last 20 years have reduced the population numbers to four verified extant sites. The causes of Poweshiek skipperling decline are unknown. 2. We aggregated all known Poweshiek skipperling occurrence records to examine the spatiotemporal patterns of Poweshiek skipperling decline. Ecological niche models were developed for five time frames (1985, 1990, 1995, 2000 and 2005) and three spatial extents (eastern occupied range, western occupied range and total occupied range). We used a backward elimination method to investigate the effects of climate and land use on the ecological niche of Poweshiek skipperling. 3. Predictors of occurrence changed over time and across the geographical extent of Poweshiek skipperling. Land use covariates were retained in east models. In the west and total extent, climate variables contributed the most to model predictive power for the 1985, 1990 and 1995 models; land use variables contributed the most to model predictive power in the 2000 and 2005 models. 4. During the rapid decline in Poweshiek skipperling population numbers occurring at the turn of the century, probability of Poweshiek skipperling presence was being driven by proportion of natural land cover and distance to nearest grassland/wetland. Our results suggest that these land use variables are important landscape‐level variables to consider when developing risk assessments of extant populations and potential reintroduction sites.
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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) | 0.001 | 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".