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Record W3016901586 · doi:10.1139/cjfas-2019-0346

Invaders induce coordinated isotopic niche shifts in native fish species

2020· article· en· W3016901586 on OpenAlexvenueno aff
Jane S. Rogosch, Julian D. Olden

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIntroduced speciesBiologyTrophic levelEcologyIsotope analysisEcological nicheInvasive speciesMesopredator release hypothesisLepomisNicheHabitatPredation

Abstract

fetched live from OpenAlex

Food-web investigations inform management strategies by exposing potential interactions between native and nonnative species and anticipating likely outcomes associated with species removal efforts. We leveraged a natural gradient of compositional turnover from native-only to nonnative-only fish assemblages, combined with an intensive removal effort, to investigate underlying food-web changes in response to invasive species expansion in a Lower Colorado River tributary. Nonnative fishes caused coordinated isotopic niche displacement in native fishes by inducing resource shifts toward lower trophic positions and enriched carbon sources. By contrast, nonnative fishes did not experience reciprocal shifts when native fishes were present. Asymmetrical outcomes between native and nonnative fishes indicated species displacement may result from competitive or consumptive interactions. Native species’ isotopic niches returned to higher trophic levels after nonnative green sunfish (Lepomis cyanellus) removal, indicating removal efforts can support trophic recovery of native fishes like desert suckers (Catostomus clarkii) and roundtail chub (Gila robusta). Using stable isotope analysis in preremoval assessments provides opportunities to identify asymmetric interactions, whereas postremoval assessments could identify unintended consequences, like mesopredator release, as part of adaptive decision making to recover native fishes.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.219
Teacher spread0.188 · 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

Citations38
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicIsotope Analysis in EcologyFrench-language works237,207