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Oxygen measurements in the burrows of freshwater insects

2001· article· en· W2164111227 on OpenAlexafffund
Fei Wang, André Tessier, Landis Hare

Bibliographic record

VenueFreshwater Biology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMayflyBurrowBenthic zoneOxygenSedimentEnvironmental chemistryBioturbationWater columnOxygen saturationEcologyEnvironmental scienceLimiting oxygen concentrationBiologyChemistryLarva

Abstract

fetched live from OpenAlex

1. Thin‐tipped micro‐electrodes were used to measure oxygen concentrations in the burrows of two common aquatic insects, the mayfly Hexagenia limbata and the alderfly Sialis velata . Both species maintain their surroundings oxygenated by drawing water from above the sediment surface into their tubes. 2. The temporal pattern of oxygen in the burrows differed between the species. The constant high oxygen concentration (>75% of air saturation) measured in the tubes of the mayfly suggest that this animal pumps water almost continuously, which is consistent with its high oxygen requirements. In contrast, oxygen concentration in burrows of the alderfly fluctuated widely over time, suggesting that this animal irrigates only irregularly, probably because it can tolerate short periods of low oxygen concentration in its burrow. 3. The interval between pumping episodes by the alderfly decreased with increasing temperature, a result of increased oxygen consumption by the animal and by sediment at high temperature. 4. Based on the tube dimensions, oxygen penetration depth and animal density in lakes, we estimate that Hexagenia could create an oxic micro‐environment equivalent to 3–35% of the volume of the surface oxidized sediment layer created by molecular diffusion. The mosaic of oxic micro‐environments created by the burrowing and irrigation of freshwater animals could influence chemical and biological processes in sediments, the fluxes of materials between the sediment and the overlying water column, and the exposure of benthic animals to sedimentary contaminants.

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 score0.600
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.036
GPT teacher head0.230
Teacher spread0.194 · 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

Citations79
Published2001
Admission routes2
Has abstractyes

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