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Record W4399787111 · doi:10.3955/046.097.0106

Human and Wildlife Use of Mountain Glacier Habitat in Western North America

2024· article· en· W4399787111 on OpenAlexaff
Scott Hotaling, Jordan Boersma, Neil Paprocki, Alissa K. Anderson, Logan Whiles, Lucy Ogburn, Sophia Kasper, Catharine E. White, Daniel H. Thornton, Peter Wimberger

Bibliographic record

VenueNorthwest Science · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsCoast Mountain College
Fundersnot available
KeywordsWildlifeGlacierHabitatGeographyPhysical geographyWildlife refugeEcologyWildlife managementBiology

Abstract

fetched live from OpenAlex

The global recession of glaciers and perennial snowfields is reshaping mountain ecosystems. Beyond physical changes to the landscape and altered downstream hydrology, the implications of glacier decline for biodiversity are poorly known. Before predictions can be made about how climate change will affect wildlife in glacier-associated ecosystems, a more thorough accounting of the role that glaciers play in species' life histories is needed. In this study, we deployed an elevational transect of wildlife cameras along the western margin of the Paradise Glacier, a rapidly receding mountain glacier on the south side of Mount Rainier, WA, USA. From June to September 2021, we detected at least 16 vertebrate species (7 birds, 9 mammals) using glacier-associated habitats over 770 trap nights. Humans, primarily skiers, were the most common species detected, but we also recorded 99 observations of wildlife (birds and other mammals). These included three species of conservation concern in Washington: wolverine (Gulo gulo), Cascade red fox (Vulpes vulpes cascadensis), and white-tailed ptarmigan (Lagopus leucura). Collectively, our results reveal a rich diversity of wildlife using a single mountain glacier and adjacent habitat in the Pacific Northwest, emphasizing a largely overlooked risk of climate change to mountain biodiversity. We conclude by highlighting the global need for similar studies to better understand the true scale of biodiversity that will be impacted by glacier recession in mountain ecosystems.

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 score0.269
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.249
Teacher spread0.222 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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