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Record W3120421020 · doi:10.1111/gcb.15510

Rock glaciers and related cold rocky landforms: Overlooked climate refugia for mountain biodiversity

2021· article· en· W3120421020 on OpenAlexaff
Stefano Brighenti, Scott Hotaling, Debra S. Finn, Andrew G. Fountain, Masaki Hayashi, David B. Herbst, Jasmine E. Saros, Lusha M. Tronstad, Constance I. Millar

Bibliographic record

VenueGlobal Change Biology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of Calgary
FundersU.S. Forest ServiceNational Science Foundation
KeywordsLandformGlacierRock glacierBiodiversityPhysical geographyGeologyClimate changeGlacial landformEarth scienceEcologyGeographyGeomorphologyMoraineOceanography

Abstract

fetched live from OpenAlex

Mountains are global biodiversity hotspots where cold environments and their associated ecological communities are threatened by climate warming. Considerable research attention has been devoted to understanding the ecological effects of alpine glacier and snowfield recession. However, much less attention has been given to identifying climate refugia in mountain ecosystems where present-day environmental conditions will be maintained, at least in the near-term, as other habitats change. Around the world, montane communities of microbes, animals, and plants live on, adjacent to, and downstream of rock glaciers and related cold rocky landforms (CRL). These geomorphological features have been overlooked in the ecological literature despite being extremely common in mountain ranges worldwide with a propensity to support cold and stable habitats for aquatic and terrestrial biodiversity. CRLs are less responsive to atmospheric warming than alpine glaciers and snowfields due to the insulating nature and thermal inertia of their debris cover paired with their internal ventilation patterns. Thus, CRLs are likely to remain on the landscape after adjacent glaciers and snowfields have melted, thereby providing longer-term cold habitat for biodiversity living on and downstream of them. Here, we show that CRLs will likely act as key climate refugia for terrestrial and aquatic biodiversity in mountain ecosystems, offer guidelines for incorporating CRLs into conservation practices, and identify areas for future research.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.235
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations127
Published2021
Admission routes1
Has abstractyes

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