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Record W2069549472 · doi:10.1002/rra.1052

The effect of experimental flow reductions on macroinvertebrate drift in natural and streamside channels

2007· article· en· W2069549472 on OpenAlexaboutno aff
Alexander B. W. James, Zoë S. Dewson, Russell G. Death

Bibliographic record

VenueRiver Research and Applications · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSTREAMSInvertebrateRiver ecosystemBiological dispersalEcologyEnvironmental scienceHabitatTaxonFlow conditionsEcosystemStream bedHydrology (agriculture)Flow (mathematics)BiologyPopulationGeology

Abstract

fetched live from OpenAlex

Abstract Understanding how much water must remain in a stream to maintain a healthy functioning ecosystem has become an important focus in stream ecology research. The drift of stream invertebrates is important as a mechanism of dispersal, recolonization and as a food source for fish in flowing water. Drift behaviour of stream invertebrates in response to flow reduction was examined in natural and streamside channels in two countries (Canada and New Zealand). We hypothesised that the drift of some taxa would increase following flow reduction as they attempted to avoid unfavourable conditions. Taxa such as Baetis sp. (Ephemeroptera) in Canadian streamside channels and Coloburiscus humeralis (Ephemeroptera) and Austrosimulium sp. (Simulidae) in streams in New Zealand exhibited a short‐term increase in drift following flow reduction. This appears to be in response to decreased velocities and available habitat in flow reduced areas. The majority of taxa displaying this response were filter feeders, suggesting a decline in food delivery with reduced flow contributed to increased drift. Some taxa (e.g. the amphipod Paracalliope fluviatilis) had a sustained increase in drift throughout the reduced flow period, probably because a preference for reduced flows increased their abundance or levels of activity. Water allocation decisions should consider potential impacts on the drift behaviour of the more commonly drifting taxa in a stream. Copyright © 2007 John Wiley & Sons, Ltd.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.311
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), 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

Citations61
Published2007
Admission routes1
Has abstractyes

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