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Record W2125542191 · doi:10.1139/f06-181

Shaking and moving: low rates of sediment transport trigger mass drift of stream invertebrates

2007· article· en· W2125542191 on OpenAlexvenueno aff
Chris Gibbins, Damià Vericat, Ramón J. Batalla, Carlos Mario Gómez Gómez

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersLeverhulme Trust
KeywordsBed loadInvertebrateEnvironmental scienceSedimentHydrology (agriculture)GeologySediment transportHyperconcentrated flowEcologyGeomorphologyBiologyGeotechnical engineering

Abstract

fetched live from OpenAlex

During floods, river invertebrates may be swept downstream in large numbers. This so-called "catastrophic drift" leads to a major redistribution of animals, as well as reduced fitness and increased mortality among drifters. We present the first field evidence of the role of sediment movement in triggering catastrophic drift. Experiments indicate that the loss of invertebrates from the bed becomes exponential when shear stress reaches the threshold that entrains bedload. However, we found that low rates of bedload are sufficient to rapidly denude patches of riverbed of their invertebrates and so trigger mass drift. Such low bedload rates occur during small floods. As small floods occur frequently, our results suggest that episodes of catastrophic drift are frequent. This conclusion is counterintuitive, as the persistence of invertebrate communities on riverbeds suggests that such events cannot be truly catastrophic. Moreover, the drift losses that we observed occurred in the absence of significant geomorphic disturbance; this is inconsistent with the notion of catastrophic drift being a response to hydrological disturbance events. We argue that a new definition of catastrophic drift is needed, a definition based not on drift magnitude or the triggering role of sediment movement, but on the population consequences of downstream displacement.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.913

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 studies0.0000.002
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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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 teacher head, 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

Citations73
Published2007
Admission routes1
Has abstractyes

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