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Record W1977251478 · doi:10.3354/meps08234

Fatty acids tracers for native and invasive macroalgae in an experimental food web

2009· article· en· W1977251478 on OpenAlexafffund
JR Kelly, RE Scheibling, Sara J. Iverson

Bibliographic record

VenueMarine Ecology Progress Series · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsDalhousie University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaU.S. Forest ServiceNatural Environment Research CouncilKillam TrustsArmy Research OfficeCanadian Forest ServiceDalhousie UniversityUniversity of Warwick
KeywordsBiologyStrongylocentrotus droebachiensisCarcinus maenasFood webSea urchinKelpFisheryKelp forestEcologyTrophic levelZoologyDecapodaCrustacean

Abstract

fetched live from OpenAlex

We assessed the potential of fatty acid (FA) markers for tracing primary production from an invasive green alga (Codium fragile ssp. fragile) and a native kelp (Saccharina longicruris) through 2 trophic levels in an experimental food web: a primary consumer, the green sea urchin Strongylocentrotus droebachiensis, and 2 secondary consumers, the native rock crab Cancer irroratus and invasive green crab Carcinus maenas. Sea urchins fed the 2 algal species had distinct gonadal FA compositions, and contained markers of each alga. Crabs of each species were then fed the gonads of sea urchins which had been fed either S. longicruris or C. fragile, and their hepatopancreases were analyzed. We were able to distinguish crabs of both species with C. fragile at the base of the food chain using the marker FAs 16:3n-3 and 18:3n-3. The overall FA composition of the hepatopancreas differed with diet in the green crab but not the rock crab. Our results suggest that 16:3n-3 may be a useful marker for tracing C. fragile production in grazers and some secondary consumers in rocky subtidal habitats in the Northwest Atlantic, but signal attenuation with each trophic transfer will limit the utility of this approach in higher consumers.

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 score0.020
Threshold uncertainty score0.772

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 communication0.0000.001
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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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

Citations24
Published2009
Admission routes2
Has abstractyes

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