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Record W1995388783 · doi:10.1071/mf05052

Intraspecific interference in a tropical stream shredder guild

2006· article· en· W1995388783 on OpenAlexaff
Luz Boyero, Richard G. Pearson

Bibliographic record

VenueMarine and Freshwater Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsBC Research (Canada)
Fundersnot available
KeywordsIntraspecific competitionGuildBiologySTREAMSEcologyBiotic componentPlant litterLitterHabitatNicheEcosystemAbiotic component

Abstract

fetched live from OpenAlex

The structure of stream communities is typically thought to be driven by stochastic events such as floods, in contrast with communities in many other systems in which biotic interactions have a major role. However, it is possible that biotic interactions are important in some situations in streams, especially where resources are limited and physical influences are stable for substantial periods. Leaf litter – the main energy source and a distinct habitat in forest streams – constitutes a patchy resource where biotic interactions among and within consumer species are likely to occur. The intraspecific interference in four leaf-eating species (shredders), common in Australian tropical streams, was experimentally examined – Anisocentropus kirramus (Trichoptera : Calamoceratidae), Lectrides varians and Triplectides gonetalus (Trichoptera : Leptoceridae) and Atalophlebia sp. (Ephemeroptera : Leptophlebiidae). All four species showed some degree of intraspecific interference, indicated by lowered leaf breakdown rates when density increased. Breakdown rates per capita decreased exponentially for all species with increased density, with slight differences among species. These differences were more evident when body size was taken into account, with breakdown rates depressed at lower densities for the two species with larger body sizes, T. gonetalus and Atalophlebia sp. Overall breakdown rates did not always increase with higher densities, because they were compensated for by depressed individual breakdown rates. Our results indicate that intraspecific interference can be an important mechanism regulating leaf breakdown in 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.001

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 head0.028
GPT teacher head0.255
Teacher spread0.227 · 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

Citations32
Published2006
Admission routes1
Has abstractyes

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