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Record W2919678899 · doi:10.1111/conl.12638

Marine protected areas enhance coral reef functioning by promoting fish biodiversity

2019· article· en· W2919678899 on OpenAlex
Zachary M. Topor, Douglas B. Rasher, J. Emmett Duffy, Simon J. Brandl

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConservation Letters · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsSimon Fraser University
FundersSmithsonian Institution
KeywordsCoral reefMarine protected areaBiodiversityHerbivoreEcologyMarine reserveEcosystemMarine ecosystemSpecies richnessResilience of coral reefsReefEcosystem-based managementGeographyFisheryBiologyFishingHabitat

Abstract

fetched live from OpenAlex

Abstract Preserving biodiversity and ecosystem function in the Anthropocene is one of humanity's greatest challenges. Ecosystem‐based management and area closures are considered an effective way to maintain ecological processes, especially in marine systems. Although there is strong evidence that such measures positively affect community structure, their impact on the rate of key ecological processes remains unclear. Here, we provide evidence that marine protected areas enhance herbivory rates on coral reefs via direct and indirect pathways. Using meta‐analysis and a path‐analytical framework, we demonstrate that, on average, protected areas increase the species richness of herbivorous fishes, which, in turn, enhances browsing rates on macroalgae. However, in all three regions studied (the Atlantic, Indian, and Pacific Ocean), a small subset of the herbivore assemblage accounted for the majority of browsing. Our results therefore indicate that ecosystem functioning on coral reefs may respond positively to both area closures and the protection of key species.

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.

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 score0.137
Threshold uncertainty score1.000

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)0.0010.001

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 head0.007
GPT teacher head0.175
Teacher spread0.168 · 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