Back to the future: Climate change effects on habitat suitability of <scp> <i>Parnassius apollo</i> </scp> throughout the Quaternary glacial cycles
Bibliographic record
Abstract
Abstract Alpine grasslands above the treeline are severely threatened by climate change, mainly due to forest expansion driven by warmer conditions. Analogous lowland grasslands experience severe reductions due to land‐use abandonment and forest encroachment. To address how climate change impacted open‐areas insects, we used Parnassius apollo as a model, a butterfly with wide Palearctic distribution inhabiting both alpine and low‐altitude steppe grasslands. We modelled upper Pleistocene range changes from the Last Interglacial (130 Kya) to the present and future (2050/2070), using medium and high greenhouse gas emission rates for the latter. We combined bioclimatic variables (Worldclim, Paleoclim, Chelsa) with distribution records of P. apollo and two of its most often used larval host plants ( Sedum album ; Hylotelephium telephium ) to formulate species distribution models (SDMs) via the Maximum entropy method. We estimated a substantial range expansion during cold periods (last glacial maximum, 22 Kya) and contractions in warmer periods. Including the host plants in the models brought reduced suitable areas estimate, possibly due to differences in climatic requirements of hosts and the butterfly. Future projections of the extent of suitable climates are surprisingly better than would be expected from a warming climate, likely because the current distribution, especially at lower elevations, is probably restricted by habitat loss due to land abandonment and afforestation. We recommend preventing afforestation in critical habitats across Europe and Asia, and increasing survey activities to perform more accurate SDMs.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".