The Distribution of Cool Spots as Microrefugia in a Mountainous Area
Bibliographic record
Abstract
It has recently been proposed that microrefugia played an important role in species survival during past climate change events. However, the current distributions of microrefugia remain largely unknown. Wind-hole sites are areas affected by preferential flows of cool air generated in interstitial spaces created by rock fragments or colluvia. Alpine plant species occurring in lowland wind-hole sites isolated from alpine zones may be relicts of the last glacial period. Hokkaido, northern Japan, is known to contain many wind-hole sites in which alpine plant species can occur. Here we surveyed 55 wind-hole sites in the Kitami region, eastern Hokkaido, and observed two alpine plant species (lingonberry, Vaccinium vitis-idaea, and Labrador tea, Rhododendron groenlandicum ssp. diversipilosum var. diversipilosum) in 14 wind-hole sites. Statistical modeling showed that wind-hole sites are likely to occur in areas with high maximum slope angles and volcanic rock cover, and concave surfaces. Our predictions of wind-hole site distributions suggest that such topographic conditions are common in our study area, and that many undiscovered wind-hole sites exist. Ignoring microhabitats may greatly underestimate species distributions in topographically complex regions, and dispersed cool spots may also function as stepping stones and temporal habitats for cold-adapted species. Because these localized unique habitats usually occur in economically unproductive sites, identifying and protecting potential microrefugia (cool spots) would be a robust and cost-effective mitigation of climate change impacts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 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".