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Give Shark Sanctuaries a Chance

2013· letter· en· W2329015138 on OpenAlexaff
Demian D. Chapman, Michael Frisk, Debra L. Abercrombie, Carl Safina, Samuel H. Gruber, Elizabeth A. Babcock, Kevin A. Feldheim, Ellen K. Pikitch, Christine A. Ward‐Paige, Brendal Davis, Steven Kessel, Michael R. Heithaus, Boris Worm

Bibliographic record

VenueScience · 2013
Typeletter
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsUniversity of WindsorDalhousie University
Fundersnot available
KeywordsFisheryZoologyBiology

Abstract

fetched live from OpenAlex

Several developing nations have established shark sanctuaries, most commonly in the form of a moratorium on both commercial shark fishing and the export of shark products in Exclusive Economic Zones ([ 1 ][1]). In her Letter Shark sanctuaries: Substance or spin? (21 December 2012, p. [1538][2]), L. N. K. Davidson raises concerns that this ambitious strategy might be doomed to exist only on paper and could discourage investments in other types of shark fisheries management. We agree that enforcement will determine whether these shark sanctuaries live up to their promise, as is true of any new management regime. We disagree, however, with the argument that shark sanctuaries are more challenging to enforce or are less likely to be successful than typical fisheries management strategies, especially considering that even basic information such as fishery catch is often unknown and underestimated in developing countries ([ 2 ][3]). Shark fisheries management is notoriously difficult and resource intensive, owing to the extreme vulnerability of sharks to over-exploitation ([ 1 ][1]). The countries that have successfully managed shark fisheries all possess substantial research, assessment, monitoring, and enforcement capacity devoted to fisheries management ([ 1 ][1]). Developing nations typically have much smaller fisheries management capacity; what they do have is national capacity to detect illicit trade of contraband items (i.e., police, maritime authority, port authority, and customs). By making all shark products illegal, national authorities can work with their fisheries agencies to enforce the moratorium. Enforcing catch or size limits on shark fisheries is more complicated and will generally fall almost entirely under the purview of the fisheries agency on its own. There is cause for optimism about the conservation potential of well-enforced shark sanctuaries nested within broader international management efforts. Smaller-scale marine protected areas have been shown to benefit certain inshore shark species, while other species tend to return to certain areas on a regular basis ([ 3 ][4]–[ 6 ][5]). These studies suggest that large protected areas may benefit these populations and match biological and governance scales. Well-enforced shark sanctuaries clearly have great potential for shark conservation, and we suggest that the international community and funding agencies should help those developing nations that pursue this approach to ensure that this promise is realized. 1. [↵][6] 1. C. A. Ward-Paige 2. et al ., J. Fish. Biol. 80, 5 (2012). [OpenUrl][7] 2. [↵][8] 1. K. Kelleher , Discards in the world's marine fisheries: An update (FAO Fisheries Technical Paper 470, Rome, 2005); [www.fao.org/docrep/008/y5936e/y5936e00.htm][9]. 3. [↵][10] 1. M. E. Bond 2. et al ., PLoS One 7, 3 (2012). [OpenUrl][11] 4. 1. W. D. Robbins 2. et al ., Curr. Biol. 16, 23 (2006). [OpenUrl][12][CrossRef][13] 5. 1. R. E. Hueter 2. et al ., J. Northw. Atl. Fish. Sci. 35, 239 (2005). [OpenUrl][14] 6. [↵][15] 1. C. A. Ward-Paige 2. et al ., PLoS One 5, 8 (2010). [OpenUrl][16] [1]: #ref-1 [2]: /lookup/doi/10.1126/science.338.6114.1538 [3]: #ref-2 [4]: #ref-3 [5]: #ref-6 [6]: #xref-ref-1-1 View reference 1 in text [7]: {openurl}?query=rft.jtitle%253DJ.%2BFish.%2BBiol.%26rft.volume%253D80%26rft.spage%253D5%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [8]: #xref-ref-2-1 View reference 2 in text [9]: http://www.fao.org/docrep/008/y5936e/y5936e00.htm [10]: #xref-ref-3-1 View reference 3 in text [11]: {openurl}?query=rft.jtitle%253DPLoS%2BOne%26rft.volume%253D7%26rft.spage%253D3%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [12]: {openurl}?query=rft.jtitle%253DCurr.%2BBiol.%26rft.volume%253D16%26rft.spage%253D23%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.cub.2005.12.009%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [13]: /lookup/external-ref?access_num=10.1016/j.cub.2005.12.009&link_type=DOI [14]: {openurl}?query=rft.jtitle%253DJ.%2BNorthw.%2BAtl.%2BFish.%2BSci.%26rft.volume%253D35%26rft.spage%253D239%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [15]: #xref-ref-6-1 View reference 6 in text [16]: {openurl}?query=rft.jtitle%253DPLoS%2BOne%26rft.volume%253D5%26rft.spage%253D8%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx

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)0.010
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.086
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0100.012
Open science0.0020.009
Research integrity0.0180.016
Insufficient payload (model declined to judge)0.0860.039

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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 designNot applicable
Domainnot available
GenreCommentary

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".

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Citations34
Published2013
Admission routes1
Has abstractyes

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