Global evidence that cold rocky landforms support icy springs in warming mountains
Bibliographic record
Abstract
Abstract Climate change is reducing the extent of cold aquatic habitats and their unique biodiversity in mountain areas. However, a variety of cold rocky landforms (CRLs) are thermally buffered and feed cold springs (<2 °C) that may represent climate refugia for cold-adapted organisms. These landforms, hitherto overlooked by freshwater research, include rock glaciers, debris-covered glaciers, talus slopes, protalus ramparts, and young moraines. Here, we investigated the warm-season water temperature of 228 springs from clean (ice) glaciers, CRLs, and reference slopes (not sourced by any of these features) in 13 mountain ranges of Europe, South America, and North America. Only springs from glaciers (90%) and CRLs (45%) had average stream temperatures below the thermal optimum for coldwater organisms of 2 °C. Springs fed by CRLs were 3 °C–5 °C (up to 9 °C) colder than those from nearby reference slopes. In general, cold springs were rarer in Mediterranean/semi-arid climates than in temperate and sub-polar climates. Landforms comprising barren and coarse rocky surfaces or ice/rock mix, having a simple or absent soil/vegetation structure, and higher likelihood of permafrost more often supported cold springs. When water temperatures were compared to air temperature, most CRL springs were thermally buffered against warm periods, cumulative heat, and daily temperature fluctuations. With cold conditions maintained in a variety of climates and mountain landscapes, CRL springs in mountains likely have high conservation value. We call for integrated ecological and hydrological research for these ecosystems, aimed at understanding their potential as climate refugia.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".