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Record W2909371389 · doi:10.1071/mf18216

Debris dams as habitat for aquatic invertebrates in forested headwater streams: a large-scale field experiment

2019· article· en· W2909371389 on OpenAlexaff
Brenda R. Baillie, Brendan J. Hicks, Ian D. Hogg, Michael R. van den Heuvel, Mark O. Kimberley

Bibliographic record

VenueMarine and Freshwater Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsInvertebrateDebrisSTREAMSBenthic zoneEcologyHabitatEnvironmental scienceHydrology (agriculture)HydrobiologyAquatic ecosystemBiologyAquatic environmentGeologyOceanography

Abstract

fetched live from OpenAlex

To evaluate the effects of debris dams on aquatic invertebrate communities, we sampled benthic invertebrates in debris dams and riffles in three forested headwater streams in New Zealand. As part of a large-scale field experiment, debris dams were subsequently removed from three treatment sections in each of the streams to assess effects on invertebrate communities. Prior to debris dam removal, total invertebrate densities in debris dams were not significantly different from those in riffles. However, densities of Ephemeroptera, Plecoptera and Trichoptera taxa were significantly higher in debris dams than in riffles. Debris dams contained a higher number of less common taxa (defined as <1% of total catch) and significantly higher densities of shredders. Densities for Coleoptera, Diptera and Trichoptera taxa were significantly higher in the autumn than in the spring. Non-metric multidimensional scaling axis scores indicated that both habitat and season had a significant effect on aquatic invertebrate community composition. At the reach scale, the effects of debris dam removal on the aquatic invertebrate communities were not statistically detectable because debris dams comprised only a small proportion of total habitat. However, these data highlight the importance of debris dams in contributing to the diversity of aquatic invertebrates in forested headwater streams.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.021
GPT teacher head0.305
Teacher spread0.284 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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