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Record W4323539462 · doi:10.1139/er-2022-0114

Glacial stream ecosystems and epilithic algal communities under a warming climate

2023· article· en· W4323539462 on OpenAlexaffvenue
Karson Sudlow, Simonne S. Tremblay, Rolf D. Vinebrooke

Bibliographic record

VenueEnvironmental Reviews · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEcosystemMeltwaterDiatomBiodiversityGlacierEcologyEnvironmental scienceClimate changeSTREAMSAbiotic componentGlobal warmingAquatic ecosystemRegime shiftGlacial periodPhysical geographyGeographyBiology

Abstract

fetched live from OpenAlex

Climate change is accelerating the global loss of glaciers with potentially striking consequences for downstream ecosystems. However, there exists limited evidence of the ecological impacts of glacier loss in meltwater streams, particularly in those outside of North America and Europe. We provide a review of the abiotic conditions in glacial streams that are potential factors of their ecosystem function and biodiversity with an emphasis on their key primary producers, namely rock-attached algae or “epilithon”. Here, shrinking glaciers discharge over time less turbid melt waters, resulting in slower moving and more transparent stream conditions that are also warmer and more chemically dilute. We hypothesize that these environmental changes will stimulate epilithic algal growth while also shifting its community structure towards larger and less nutritious taxa. Although such an increase in algal growth may benefit the productive harvestable fish capacity of certain mountain streams, a potential negative trade-off involves the proliferation of nuisance algae (e.g., Didymosphenia geminata), which thrives under clear, nutrient-poor mountain conditions. We advocate the use of long-term ecological monitoring programs and experiments coordinated across global mountain ranges to better predict and understand the ecological consequences of loss of glaciers on mountain stream 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.014

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 head0.026
GPT teacher head0.226
Teacher spread0.200 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2023
Admission routes2
Has abstractyes

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