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Record W3112219328 · doi:10.1111/eff.12586

Resource partitioning across a trophic gradient between a freshwater fish and an intraguild exotic

2020· article· en· W3112219328 on OpenAlexaboutno aff
Richard T. Kraus, Joseph D. Schmitt, Kevin R. Keretz

Bibliographic record

VenueEcology Of Freshwater Fish · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTrophic levelPerchEcologyBiologyHypolimnionTrophic cascadePredationIntroduced speciesCompetition (biology)EcosystemIntraguild predationPiscivoreCoregonusFood webFisheryNutrientPredatorEutrophication

Abstract

fetched live from OpenAlex

Abstract The introduction of exotic species has the potential to cause resource competition with native species and may lead to competitive exclusion when resources are limiting. On the other hand, information is lacking to predict under what alternate trophic conditions coexistence may occur. Comparing diets of native yellow perch Perca flavescens and nonindigenous white perch Morone americana , we examined variation in resource partitioning and body condition across a prominent longitudinal nutrient gradient in Lake Erie (north‐eastern United States, Canada). As measured with Analysis of Similarity and Schoener's index, diet similarity declined monotonically from west to east tracking declines in nutrients, productivity and relative abundance of both species. Additionally, diet similarity increased from spring through fall, following seasonal development of stratification and hypolimnetic hypoxia—phenomena which tend to increase spatial overlap between these species. Finally, relative weights of both species peaked in the Central Basin (relative weights > 0.85), which, on average, had intermediate values of prey diversity, ecosystem trophic status and water clarity. Our results highlight that native yellow perch coexist with invasive white perch under a wide range of trophic conditions. Of importance to fishery managers, mesotrophy in the Central Basin correlated with the highest body conditions and intermediate prey resource partitioning, although the effect size was small and variable. While competitive exclusion appears unlikely, the goal of reducing nutrient inputs in Lake Erie could affect not only the distributions of both species but also stakeholder decisions about where to fish.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.999

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)0.0020.000

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 head0.024
GPT teacher head0.233
Teacher spread0.209 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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