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Record W2154292251 · doi:10.1890/110246

Is global ocean sprawl a cause of jellyfish blooms?

2012· review· en· W2154292251 on OpenAlexaff
Carlos M. Duarte, Kylie A. Pitt, Cathy H. Lucas, Jennifer E. Purcell, Shin-ichi Uye, Kelly L. Robinson, Lucas Brotz, Mary Beth Decker, Kelly R. Sutherland, Alenka Malej, Laurence P. Madin, Hermes Mianzán, Josep María Gili, Verónica Fuentes, Dacha Atienza, Francesc Pagès, Denise L. Breitburg, Jennafer C. Malek, William M. Graham, Robert H. Condon

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2012
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicMarine Invertebrate Physiology and Ecology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJellyfishScyphozoaUrban sprawlCnidariaHabitatLimitingFisheryEnvironmental scienceOceanographyEcologyBiologyCoralGeology

Abstract

fetched live from OpenAlex

Jellyfish (Cnidaria, Scyphozoa) blooms appear to be increasing in both intensity and frequency in many coastal areas worldwide, due to multiple hypothesized anthropogenic stressors. Here, we propose that the proliferation of artificial structures – associated with (1) the exponential growth in shipping, aquaculture, and other coastal industries, and (2) coastal protection (collectively, “ocean sprawl”) – provides habitat for jellyfish polyps and may be an important driver of the global increase in jellyfish blooms. However, the habitat of the benthic polyps that commonly result in coastal jellyfish blooms has remained elusive, limiting our understanding of the drivers of these blooms. Support for the hypothesized role of ocean sprawl in promoting jellyfish blooms is provided by observations and experimental evidence demonstrating that jellyfish larvae settle in large numbers on artificial structures in coastal waters and develop into dense concentrations of jellyfish‐producing polyps.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.215
Teacher spread0.199 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations325
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Ecology and the EnvironmentSame topicMarine Invertebrate Physiology and EcologyFrench-language works237,207