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Record W3005538658 · doi:10.3354/meps13251

High predatory efficiency and abundance drive expected ecological impacts of a marine invasive fish

2020· article· en· W3005538658 on OpenAlexaff
EM DeRoy, Ryan Scott, NE Hussey, HJ MacIsaac

Bibliographic record

VenueMarine Ecology Progress Series · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsGrouperBiologyAbundance (ecology)PredationEcologyRelative species abundanceFisheryInvasive speciesForagingPredatorHabitatEpinephelusIntroduced speciesPopulationFish <Actinopterygii>

Abstract

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The ecological impacts of invasive species are highly variable and mediated by many factors, including both habitat and population abundance. Lionfish Pterois volitans are an invasive marine species which have high reported detrimental effects on prey populations, but whose effects relative to native predators are currently unknown for the recently colonized eastern Gulf of Mexico. We used functional response (FR) methodology to assess the ecological impact of lionfish relative to 2 functionally similar native species (red grouper Epinephelus morio and graysby grouper Cephalopholis cruentata ) foraging in a heterogeneous environment. We then combined the per capita impact of each species with their field abundance to obtain a Relative Impact Potential (RIP). RIP assesses the broader ecological impact of invasive relative to native predators, the magnitude of which predicts community-level negative effects of invasive species. Lionfish FR and overall consumption rate was intermediate to that of red grouper (higher) and graysby grouper (lower). However, lionfish had the highest capture efficiency of all species, which was invariant of habitat. Much higher field abundance of lionfish resulted in high RIPs relative to both grouper species, demonstrating that the ecological impact of lionfish in this region will be driven mainly by high abundance and high predator efficiency rather than per capita effect. Our comparative study is the first empirical assessment of lionfish per capita impact and RIP in this region and is one of few such studies to quantify the FR of a marine predator.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.000

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 head0.007
GPT teacher head0.202
Teacher spread0.194 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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