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Record W6963496238 · doi:10.18739/a26m3356r

Metal Concentrations in Tundra Seep, Tributary and River Waters of the Western Brooks Range, Alaska, 2022-2023

2024· dataset· en· W6963496238 on OpenAlexaff

Bibliographic record

VenueCalifornia Digital Library · 2024
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSTREAMSTributaryTundraEcosystemHabitatWatershedThermokarstAquatic ecosystemSubsistence agriculture

Abstract

fetched live from OpenAlex

Historically characterized by pristine streams that support robust populations of Arctic grayling, Dolly Varden, and chum salmon, the southern slopes of the Brooks Range provide valuable economic and subsistence resources for local communities. However, since 2019, dozens of formerly clear-running streams have turned turbid and orange with iron precipitates. Seeps have been identified in the tundra and in upland rock formations. Limited data show very low pH in seep water (less than 3.0), downslope vegetation mortality, and dramatic declines in juvenile fish abundance in affected headwaters. The causes of this rapidly spreading degradation of pristine streams remains unknown. The proliferation of turbid orange streams west of the Dalton Highway ( greater than 30 since 2019) is a threat to wilderness characteristics, drinking water, subsistence resource availability, and a growing commercial salmon fishery in northwest Alaska. With many terrestrial and aquatic species dependent upon the seasonal influx of salmon, the loss of fish habitat could induce ecosystem collapse, despite the protections afforded by a vast network of National Parks and Preserves. The degradation of formerly pristine streams is occurring at such a rapid pace that we may soon lose the opportunity to compare affected with nearby unaffected streams. This comparison is essential to develop the mechanistic, causal understanding that would allow us to predict which streams will turn next and the threats to downstream villages. The community of Kiana, for instance, sits at the confluence of the Squirrel and Kobuk Rivers. At least two streams in the Squirrel watershed have turned since 2020, while two large tributaries of the Kobuk turned in 2019. The Squirrel and large Kobuk tributaries, like the Salmon River, produce much of the fish harvested by Kiana residents. This dataset includes field measurements of pH, specific conductivity, dissolved oxygen and turbidity, along with laboratory measurements of metal concentrations in acidified water samples from tundra seeps, tributaries and rivers in the western Brooks Range. The watersheds that were sampled include Timber Creek, Tukpahlearik Creek, Salmon River, Kallarichuk River, Kobuk River and Devil's Lake, which is the drinking water source for the village of Kotzebue, Alaska.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.194
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.199
Teacher spread0.186 · 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 designNot applicable
Domainnot available
GenreDataset

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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