Climate refugia along Lake Superior’s shores: disjunct arctic–alpine plants rely on cool shoreline temperatures but are restricted to highly exposed habitat under climate warming
Bibliographic record
Abstract
Abstract Climate refugia can serve as a remnant habitat or stepping stones for species dispersal under climate warming. The largest freshwater lake by surface area, Lake Superior, USA and Canada, serves as a model system for understanding cooling-mediated local refugia, as its cool water temperatures and wave action have maintained shoreline habitats suitable for southern disjunct populations of arctic–alpine plants since deglaciation. Here, we seek to explain spatial patterns and environmental drivers of arctic–alpine plant refugia along Lake Superior’s shores, and assess future risk to refugia under moderate (+3.5 °C) and warmest (+5.7 °C) climate warming scenarios. First, we examined how the interactive effects of summer surface water temperatures and wind affected onshore temperatures, resulting in areas of cooler refugia. Second, we developed an ecological niche model for the presence of disjunct arctic–alpine refugia (pooling 1253 occurrences from 58 species) along the lake’s shoreline. Third, we fit species distribution models for 20 of the most common arctic–alpine disjunct species and predicted presence to identify refugia hotspots. Finally, we used the two climate warming scenarios to predict changes in the presence of refugia and disjunct hotspots. Bedrock type, elevation above water, inland distance, July land surface temperature from MODIS/Terra satellite and near-shore depth of water were the best predictors of disjunct occurrences. Overall, we predicted 2236 km of the shoreline (51%) as disjunct refugia habitat for at least one species under current conditions, but this was reduced to 20% and 7% with moderate (894 km) and warmest (313 km) climate change projections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; both teacher heads agree on what is shown here.
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".