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Record W2068737918 · doi:10.1080/14634980701551168

Multiple stressors and ecosystem-based management in the Gulf

2007· article· en· W2068737918 on OpenAlexaff
Nuzrat Yar Khan

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsEcosystemEcosystem managementEcosystem healthEnvironmental resource managementEcosystem-based managementMarine ecosystemSustainabilityCoastal managementGeographyFisheryEcologyEcosystem servicesEnvironmental science

Abstract

fetched live from OpenAlex

Rapid and largely unchecked coastal development in the Gulf countries as a result of the oil boom has caused considerable ecological stress in the Gulf ecosystem. Coastal habitats have begun to show symptoms of ecological imbalance generally associated with multiple stressors caused by pollution and habitat destruction: harmful algal blooms and fish kills are of common occurrence in coastal areas, fish stocks are declining, and coastal sediments are contaminated by a variety of toxic chemicals. The present state of the Gulf ecosystem reflects the constraints inherently associated with fragmented jurisdictions in the management of coastal areas at both national and regional levels. Its management is largely driven by management frameworks representing arbitrary jurisdictions of political units rather than a shared vision of the health and sustainability of the entire Gulf ecosystem. In view of the complex, dynamic, and semi-enclosed nature of the Gulf ecosystem, a paradigm shift from resource management characterized by short-term perspectives on small spatial scales to resource management that is ecosystem-based with long-term perspectives, is urgently needed. Since an ecosystem-based management of the Gulf is implicit in the provisions of Kuwait Convention and Kuwait Action Plan, we recommend that ROPME (Regional Organization for the Protection of the Marine Environment), which provides the focal point for regional cooperation under these regional agreements, be provided with a renewed mandate to coordinate an ecosystem-based management of the Gulf.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0040.002
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.246
Teacher spread0.233 · 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

Citations51
Published2007
Admission routes1
Has abstractyes

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