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Reciprocal trophic niche shifts in native and invasive fish: salmonids and galaxiids in Patagonian lakes

2012· article· en· W2137146122 on OpenAlexaff
Cristián Correa, ANDREA P. BRAVO, Andrew P. Hendry

Bibliographic record

VenueFreshwater Biology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsMcGill University
FundersUniversity of California, DavisNational Geographic Society
KeywordsSalmoBrown troutTrophic levelBiologyRainbow troutPredationEcologyTroutLittoral zonePredatory fishForage fishApex predatorFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Summary 1. Rainbow ( Oncorhynchus mykiss ) and brown trout ( Salmo trutta ) are widespread and invasive salmonids with important lethal effects as predators, although indirect effects are also possible. We used stable isotope analyses (δ 15 N, δ 13 C) to explore how the density of invasive trout in 25 Patagonian lakes alters the trophic niche (TN) of a widespread native fish, Galaxias platei (Galaxiidae). We also explored how the density of the galaxiid influences the TN of invasive trout. 2. We quantified two aspects of the TN: (i) the proportion of littoral carbon (PL) and (ii) trophic height (TH) (i.e. the ‘height’ at which the fish feeds in the food web). We related these measures of TN in a given species to the density of other species (as estimated by catch‐per‐unit‐effort). 3. As G. platei body size increased, their PL increased (increasing littoral feeding) in several lakes. However, none of the fish species investigated showed changes in PL with increasing density of the other fish species. TH increased with body size in all three species. In addition, the TH of large G. platei declined with increasing trout density and, reciprocally, the TH of large S. trutta decreased with decreasing G. platei density. 4. The reciprocal effects of native and the invasive fish on TH were as large as a shift of one trophic level. This pattern is consistent with an exhaustion of galaxiid prey for both piscivorous G. platei and S. trutta in lakes with high trout density. 5. These finding support the suggested management strategy of culling trout from overpopulated lakes, which should simultaneously protect native fish and enhance a lucrative sport fishery for large trout.

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 score0.102
Threshold uncertainty score0.914

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 studies0.0000.000
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 head0.011
GPT teacher head0.236
Teacher spread0.224 · 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

Citations67
Published2012
Admission routes1
Has abstractyes

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