Monitoring landed seahorse catch in a changing policy environment
Bibliographic record
Abstract
ESR Endangered Species Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials ESR 27:95-111 (2015) - DOI: https://doi.org/10.3354/esr00643 Monitoring landed seahorse catch in a changing policy environment M. Yasué1,*, A. Nellas2, H. Panes2, A. C. J. Vincent3 1Quest University Canada, 3200 University Blvd., Squamish, BC V8B 0N8, Canada 2Project Seahorse Foundation for Marine Conservation, Gaviola Compound, Maria Theresa Village II, Barangay Guadalupe 6000, Philippines 3Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada *Corresponding author: maiyasue@gmail.com ABSTRACT: For many small-scale, tropical reef fisheries, landed catch may be the only data that can be monitored to assess the impacts of management. This is true for seahorses Hippocampus comes that are obtained as part of a multi-species fishery in the Philippines. Here, because seahorses are locally rare and depleted, it is difficult to attain large enough sample sizes to detect changes over time using underwater surveys. We assessed changes in seahorse sales at 2 sites, from 1996 and 2005 respectively to 2010. The study period covered local and national conservation initiatives that could affect seahorses and dependent fisheries: establishment of marine reserves (1998 onwards), a community-led minimum size limit (MSL: 2002 to 2004) and a national ban on seahorse fishing (from 2004). The MSL appeared to lead to increased sizes of seahorses in trade, as hoped, while the national ban led, perversely, to more fishers selling seahorses. Declines in overall take after 2004 or 2007 (depending on the site) is likely linked to declining seahorse populations rather than reduced effort, especially when one considers the increased number of fishers and the price per seahorse. It is notable that communities decided on the MSL, whereas the government imposed the ban on capturing seahorses. In this small-scale, multi-species fishery, monitoring a wide range of variables intensively over a relatively long time scale allowed us to identify key differences between small-scale and industrial fisheries management, and also to document the biological and social consequences of management action for a depleted, threatened species. KEY WORDS: CITES · MPAs · Marine reserve · Exploitation · Fishing ban · Philippines · Size distribution · Minimum size limits Full text in pdf format Supplementary material NextCite this article as: Yasué M, Nellas A, Panes H, Vincent ACJ (2015) Monitoring landed seahorse catch in a changing policy environment. Endang Species Res 27:95-111. https://doi.org/10.3354/esr00643 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in ESR Vol. 27, No. 2. Online publication date: February 18, 2015 Print ISSN: 1863-5407; Online ISSN: 1613-4796 Copyright © 2015 Inter-Research.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".