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Record W2972954146 · doi:10.1139/facets-2018-0033

Science should not be left behind during the design of a marine protected area: meeting conservation priorities while integrating stakeholder interests

2019· article· en· W2972954146 on OpenAlexafffundvenueabout
Manuel Muntoni, Rodolphe Devillers, Mariano Koen‐Alonso

Bibliographic record

VenueFACETS · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsFisheries and Oceans CanadaMemorial University of Newfoundland
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMarine protected areaStakeholderCompromiseProcess (computing)Boundary (topology)Environmental resource managementMarine conservationBusinessFishingEnvironmental planningFish <Actinopterygii>FisheryEnvironmental scienceComputer scienceEcologyPolitical science

Abstract

fetched live from OpenAlex

Marine protected areas (MPAs) design is a complex process that typically involves diverse stakeholders, requiring compromise between diverging priorities. Such compromises, when not carefully understood, can threaten the ecological effectiveness of MPAs. Using the example of the Canadian Laurentian Channel MPA, we studied a planning process from initial scientific advice to the final MPA. We analysed the impacts of successive boundary modifications to the draft MPA, often made to accommodate extractive industries, on the protection of seven species initially identified as potential conservation priorities. We also quantified the potential economic impacts of changes in boundary modifications on the fisheries industry. Results show that reducing the proposed MPA size by 33.4% helped reduce the potential economic impact on the fishing industry by 65.5%, but it resulted in up to 43% decrease in protection of species of conservation priority. Changes in MPA boundary delineation during the design were not subjected to formal scientific reviews, raising questions on the potential effectiveness of this MPA. Better integration of science in MPA design is required to help assess the impacts that trade-offs made during stakeholder consultations can have on the MPA ecological effectiveness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.408
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.245
Teacher spread0.169 · 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.

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

Citations7
Published2019
Admission routes4
Has abstractyes

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