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Estimating terrestrial contribution to stream invertebrates and periphyton using a gradient‐based mixing model for δ<sup>13</sup>C

2009· article· en· W2040811605 on OpenAlexafffund
Joseph B. Rasmussen

Bibliographic record

VenueJournal of Animal Ecology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPeriphytonInvertebrateMixing (physics)Environmental scienceEcologyBiologyPhysicsAlgae

Abstract

fetched live from OpenAlex

1. This paper outlines a gradient-based model that can be used for isotopic signature source partitioning, even if source signatures are not distinct, as long as their spatial gradients differ. A model of this type is applied to the partitioning of autochthonous vs. allochthonous contribution to stream invertebrate delta(13)C signatures, which has often been confounded by overlap in source signatures. 2. delta(13)C signatures of inorganic carbon and most autochthonous production exhibit pronounced gradients along rivers, being depleted relative to terrestrial signatures in upstream reaches, and enriched downstream. Terrestrial detritus, by contrast, exhibits no gradient. Thus terrestrial food consumption reduces downstream signature slopes in proportion to the amount of terrestrial food consumed. 3. The gradient-based mixing model produces estimates of the proportion of terrestrial consumption (p(T)) from signature slopes of consumers; p(T) estimates for invertebrate primary consumers were: herbivore/grazers (0.15) <filterers (0.38), collector/gatherers (0.43) <shredders (0.85). 4. Periphyton (epilithon), a mixture of attached algae, bacteria and detritus, exhibited a weaker downstream slope than attached algae. p(T) values calculated for periphyton relative to pure algal signatures were 0.32 implying approximately 30% allochthonous content. The slope for herbivore/grazers calculated relative to periphyton signatures was >1, indicating selective assimilation of the autochthonous component from the biofilms.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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 designSimulation or modeling
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

Citations81
Published2009
Admission routes2
Has abstractyes

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