Climate change and range restriction of common salamanders in eastern Canada and the United States
Bibliographic record
Abstract
Abstract The sensitivity of amphibian species to shifts in environmental conditions has been exhibited through long‐term population studies and the projection of ecological niche models under expected conditions. Species in biodiversity hotspots have been the focus of ample predictive modeling studies, while, despite their significant ecological value, wide‐ranging and common taxa have received less attention. We focused on predicting range restriction of the spotted salamander (Ambystoma maculatum), blue‐spotted salamander (A. laterale), four‐toed salamander (Hemidactylium scutatum), and red‐backed salamander (Plethodon cinereus) under future climate scenarios. Using bias‐corrected future climate data and biodiversity database records, we developed maximum entropy (MaxEnt) models under current conditions and for climate change projections in 2050 and 2070. We calculated positivity rates of species localities to represent proportions of habitat expected to remain climatically suitable with continued climate change. Models projected under future conditions predicted average positivity rates of 91% (89–93%) for the blue‐spotted salamander, 23% (2–41%) for the spotted salamander, 4% (0.7–9%) for the four‐toed salamander, and 61% (42–76%) for the red‐backed salamander. Range restriction increased with time and greenhouse gas concentration for the spotted salamander, four‐toed salamander, and red‐backed salamander. Common, widespread taxa that often receive less conservation resources than other species are at risk of experiencing significant losses to their climatic ranges as climate change continues. Efforts to maintain populations of species should be focused on regions expected to experience fewer climatic shifts such as the interior and northern zones of species' distributions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".