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Cumulative Effects of Climate Warming and Other Human Activities on Freshwaters of Arctic and Subarctic North America

2006· review· en· W2150396738 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAMBIO · 2006
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEnvironmental scienceSubarctic climateArcticClimate changeSnowmeltSnowPermafrostArctic ecologyFreshwater ecosystemEcosystemPhysical geographyEcologyOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

Despite their generally isolated geographic locations, the freshwaters of the north are subjected to a wide spectrum of environmental stressors. High-latitude regions are especially sensitive to the effects of recent climatic warming, which have already resulted in marked regime shifts in the biological communities of many Arctic lakes and ponds. Important drivers of these limnological changes have included changes in the amount and duration of snow and ice cover, and, for rivers and lakes in their deltas, the frequency and extent of spring floods. Other important climate-related shifts include alterations in evaporation and precipitation ratios, marked changes in the quality and quantity of lake and river water inflows due to accelerated glacier and permafrost melting, and declining percentages of precipitation that falls as snow. The depletion of stratospheric ozone over the north, together with the clarity of many Arctic lakes, renders them especially susceptible to damage from ultraviolet radiation. In addition, the long-range atmospheric transport of pollutants, coupled with the focusing effects of contaminant transport from biological vectors to some local ecosystems (e.g., salmon nursery lakes, ponds draining seabird colonies) and biomagnification in long food chains, have led to elevated concentrations of many persistent organic pollutants (e.g., insecticides, which have never been used in Arctic regions) and other pollutants (e.g., mercury). Rapid development of gas and oil pipelines, mining for diamonds and metals, increases in human populations, and the development of all-season roads, seaports, and hydroelectric dams will stress northern aquatic ecosystems. The cumulative effects of these stresses will be far more serious than those caused by changing climate alone.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.857
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.256
Teacher spread0.240 · 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