Antagonistic climate-land use change interactions shape future distributions of a temperate snake at the northern range limit
Bibliographic record
Abstract
• Our future projections showed a northward range shift for Gray ratsnakes under different scenarios (SSP3-70 & SSP5-85), with gains in habitat suitability resulting from climate change and losses due to land use change. • Our findings suggest complex interactions between climate and land use change, highlighting the importance of understanding the interactive effects of different threats to efficiently implement conservation and management plans. • The Frontenac Arch UNESCO World Biosphere Reserve is projected to remain a key region for Gray ratsnake persistence under climate change, as much of it is predicted to remain suitable because of retained forest cover and climatic suitability. • Conservation efforts should focus on the protection and restoration of habitat to help mitigate the negative effects of climate change for ratsnakes and many other co-distributed ectothermic species in Canada. Climate change presents a substantial threat to biodiversity, driving shifts in species distributions both independently and through interactions with land use change. In Canada, 77% of reptile species are considered at risk, especially near the Canada-U.S. border, where most species are at the northern range limit and where land use changes have been most pronounced. Climate change is expected to impact reptiles in this region, including snakes; however, how it will interact with land use change to affect snake distributions remains uncertain. Here, we used ensemble models, derived from three different SDM models, to investigate the potential effects of climate-land cover/use interactions on the future distribution of range-edge populations of a large threatened colubrid in Canada, Gray ratsnakes ( Pantherophis spiloides ). We showed climate and land cover/use change have an antagonistic effect on future environmental suitability, with greater net gains in suitability from climate alone (37-85%) compared to gains from the combined model (35-81%). Our study revealed that climate change may benefit temperate snakes, like Gray ratsnakes, leading to a northward range-edge shift, but land use change may prevent colonization of new areas and persistence in areas of their current range. Our models showed the Frontenac Arch is projected to be a key region for Gray ratsnake persistence under climate change, as it will mostly remain suitable due to the forest cover. These findings highlight the need for protection and restoration of habitat to help mitigate the negative effects of climate change for ratsnakes and many other similar species in Canada.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".