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Testing the grouper biocontrol hypothesis: A response to Mumby et al. 2013

2013· preprint· en· W258491142 on OpenAlexaff
John F. Bruno, Abel Valdivia, Serena Hackerott, Courtney Cox, Stephaine Green, Isabelle M. Côté, Lad Akins, Craig A. Layman, William F. Precht

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGrouperReefBiologyCoral reefInvasive speciesAbundance (ecology)Introduced speciesEcologyCullingFisheryPredationFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Biotic resistance is the idea that native species negatively affect the invasion success of introduced species. We tested the hypothesis that native grouper are controlling the abundance of exotic lionfish on Caribbean coral reefs by assessing the relationship between the density and biomass of lionfish and native predators at 71 reefs in three biogeographic regions. Our results indicated that: (a) the abundance of lionfish and large grouper are not negatively related, and (b) lionfish abundance is controlled by a number of physical site characteristics, and possibly by culling. Taken together, our results suggest that managers cannot rely on native grouper populations to control the lionfish invasion. Mumby et al. (2013) objected to several aspects of our analysis and conclusions. Here we address their criticisms and argue that our original conclusions are valid.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.100
metaresearch head score (Gemma)0.327
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.100
Threshold uncertainty score0.528

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1000.327
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0030.009
Scholarly communication0.0050.006
Open science0.0070.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0100.001

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 head0.034
GPT teacher head0.237
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2013
Admission routes1
Has abstractyes

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