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Record W2981491913 · doi:10.1002/aqc.3067

Marine protected areas in southern China: Upgrading conservation effectiveness in the ‘eco‐civilization’ era

2019· article· en· W2981491913 on OpenAlexaff
Laurence J. McCook, Jiansheng Lian, Xinming Lei, Zhu Chen, Guifang Xue, Put Ang, Xiong Zhang, Hui Huang

Bibliographic record

VenueAquatic Conservation Marine and Freshwater Ecosystems · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersCentre of Excellence for Coral Reef Studies, Australian Research CouncilAustralian Research CouncilChinese Academy of Sciences
KeywordsMarine protected areaMarine conservationEnvironmental planningEnvironmental resource managementBusinessChinaEcosystem servicesEnforcementEnvironmental protectionGeographyEcosystemEnvironmental scienceEcologyHabitat

Abstract

fetched live from OpenAlex

Abstract China has undergone massive economic development over the last several decades, but at the cost of serious environmental degradation, including to coastal and marine ecosystems. This paper describes the governance arrangements for management of coastal and marine areas of southern, mainland China and Hong Kong, especially marine protected areas (MPAs). Although not widely recognized internationally, there are 123 designated MPAs spread across the South China Sea coast. However, the effectiveness of these MPAs in conservation of ecosystem goods and services is seriously limited by a familiar range of pressures, including limited resources, insufficient enforcement and massive coastal development. Recent developments in national policy include integration of all protected areas (including marine) under a single agency, a range of limits on coastal development and water pollution, and the strategy of ‘eco‐civilization’ to balance environmental management with economic development. If successfully implemented, these policies would profoundly change the course of marine environments in China, with globally significant consequences. Recommendations for improving MPA performance in China include: ensuring that marine systems are not overwhelmed within the new national jurisdiction, and maintaining and enhancing marine capacity; increased resourcing, supported by comprehensive and systematic economic valuations of ecosystem goods and services and natural capital; upgraded enforcement of existing environmental laws and regulations, combined with further refinement and development, especially around cumulative impact management; a particular focus on major reduction in water pollution in all forms; integration of marine management between Hong Kong SAR and surrounding Guangdong Province; and enhanced community engagement, participation and education. Finally, much greater, collaborative engagement by the international community with Chinese marine management and conservation would bring major, and very mutual, benefits.

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 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 score0.411
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.192
Teacher spread0.184 · 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.

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

Citations20
Published2019
Admission routes1
Has abstractyes

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