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Record W2150046775 · doi:10.1139/cjfas-2013-0092

Conditional effects of aquatic insects of small tributaries on mainstream assemblages: position within drainage network matters

2013· article· en· W2150046775 on OpenAlexvenueno aff
Silvia Vendruscolo Milesi, Adriano S. Melo

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsTributarySpecies richnessFaunaEcologyUpstream and downstream (DNA)Abundance (ecology)ConfluenceSubstrate (aquarium)GeographyEnvironmental scienceUpstream (networking)Biology

Abstract

fetched live from OpenAlex

Tributaries may affect fauna in a mainstream by changing bottom substrate and increasing spatial heterogeneity. Additionally, we hypothesized that fauna in the mainstream may be affected by drifting migrants from tributaries. In nine stream networks, we sampled a similar microhabitat immediately upstream and downstream of two confluences. In each network, one confluence was located in the network centre and one in the periphery, and they were distinguished by low and high ratios of tributary size, respectively. We assessed whether the aquatic fauna at sites downstream from confluences was species-richer, distinct in composition and structure, and whether it included the fauna of upstream sites. We found that richness, rarefied richness, and abundance at downstream sites were not higher than at their upstream counterparts. Faunas at downstream sites were not nested subsets of those at upstream sites. Macroinvertebrate assemblage composition and structure differed between downstream and upstream sites in the peripheral confluences (high tributary to mainstream (T:M) ratios), but not in central confluences (low T:M ratios). Thus, effects of small tributaries on receiving mainstreams are dependent on the T:M ratio.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.168
Teacher spread0.160 · 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

Citations89
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicFreshwater macroinvertebrate diversity and ecologyFrench-language works237,207