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Record W2753680248 · doi:10.1002/aqc.2783

An introduction to ‘other effective area‐based conservation measures’ under Aichi Target 11 of the Convention on Biological Diversity: Origin, interpretation and emerging ocean issues

2017· article· en· W2753680248 on OpenAlex

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

VenueAquatic Conservation Marine and Freshwater Ecosystems · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsCouncil of Canadians with Disabilities
Fundersnot available
KeywordsConvention on Biological DiversityIUCN Red ListScope (computer science)BiodiversityEnvironmental resource managementEnvironmental planningConventionVettingCommissionInterpretation (philosophy)Marine protected areaLegislatureGeographyPolitical scienceEcologyHabitatComputer scienceBiologyLawEnvironmental science

Abstract

fetched live from OpenAlex

Abstract The new term ‘other effective area‐based conservation measures’, or OECMs, was introduced into Aichi Biodiversity Target 11 of the Convention on Biological Diversity's (CBD) Strategic Plan by signatory Parties in 2010. In the intervening period much action has been taken on creating protected areas as the key route to delivering area‐based conservation of biodiversity and ecosystem services. Rather less attention has been paid to OECMs due in part to a lack of guidance on what areas should or should not be included under this label. An IUCN World Conservation Congress Resolution in 2012 called on IUCN's World Commission on Protected Areas (WCPA) to assist the CBD by providing technical guidance on interpretation of the wording in Aichi Biodiversity Target 11. IUCN WCPA established a Task Force in 2015 to provide guidance on OECMs, in terrestrial, freshwater and marine habitats. This Task Force has already met several times and has a global membership of more than 100 experts. The official call made by the CBD in 2016 for guidance explicitly recognizes the role of the IUCN Task Force in fulfilling this guidance need. This paper provides the background to OECMs and an initial analysis on the type and nature of measures that may qualify as OECMs under Aichi Target 11. Successful implementation will be dependent on clear principles and guidance, but also on a far better awareness among conservationists and other sectors on the purpose and scope of all 20 Aichi Targets. The paper will also be of value to discussions and implementation of Sustainable Development Goal 14 on the ocean. Some generic examples of areas likely to qualify as OECMs in the ocean are identified, along with an analysis of how OECMs complement and supplement fisheries and other management measures to promote more sustainable use. Greater recognition and reporting is needed on fisheries measures under Aichi Target 6. All fishery management and exclusion zones will not qualify as OECMs, but they can form essential measures towards achieving delivery of greater sustainability within such extractive industries.

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)0.001
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 score0.497
Threshold uncertainty score0.949

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 science0.0000.000
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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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