Stock assessment of loggerhead and leatherback sea turtles and An assessment of the impact of the pelagic longline fishery on the loggerhead and leatherback sea turtles of the Western North Atlantic
Bibliographic record
Abstract
On September 7, 2000 the National Marine Fisheries Service announced that it was reinitiating consultation under Section 7 of the Endangered Species Act on pelagic fisheries for swordfish, sharks, tunas, and billfish. 1 Bycatch of a protected sea turtle species is considered atake under the Endangered Species Act (PL93-205). On June 30, 2000 NMFS completed a Biological Opinion on an amendment to the Highly Migratory Pelagic Fisheries Management Plan that concluded that the continued operation of the pelagic longline fishery was likely to jeopardize the continued existence of loggerhead and leatherback sea turtles.2 Since that Biological Opinion was issued NMFS concluded that further analyses of observer data andadditional population modeling of loggerhead sea turtles was needed to determine more precisely the impact of the pelagic longline fishery on turtles. 3,4 Hence, the reinitiation of consultation.The documents that follow constitute the scientific review and synthesis of information pertaining to the narrowly defined reinitiation of consultation: the impact of the pelagic longline fishery on loggerhead and leatherback sea turtles The document is in 3 parts, plus 5 appendices.Part I is a stock assessment of loggerhead sea turtles of the Western North Atlantic. Part II is a stock assessment of leatherback sea turtles of the Western North Atlantic. Part III is an assessment of the impact of the pelagic longline fishery on loggerhead and leatherback sea turtlesof the Western North Atlantic.These documents were prepared by the NMFS Southeast Fisheries Science Center staff and academic colleagues at Duke University and Dalhousie University. Personnel involved from the SEFSC include Joanne Braun-McNeill, Lisa Csuzdi, Craig Brown, Jean Cramer, Sheryan Epperly, Steve Turner, Wendy Teas, Nancy Thompson, Wayne Witzell, Cynthia Yeung, and also Jeff Schmid under contract from the University or Miami. Our academic colleagues, Ransom Myers, Keith Bowen, and Leah Gerber from Dalhousie University and Larry Crowder and Melissa Snover from Duke University, also recipients of a Pew Charitable Trust Grant for aComprehensive Study of the Ecological Impacts of the Worldwide Pelagic Longline Industry, made significant contributions to the quantitative analyses and we are very grateful for their collaboration. We appreciate the reviews of the stock definition sections on loggerheads andleatherbacks by Brian Bowen, University of Florida, and Peter Dutton, National Marine Fisheries Service Southwest Fisheries Science Center, respectively, and the comments of the NMFS Center of Independent Experts reviewers Robert Mohn, Ian Poiner, and YouGan Wang on the entire document. We also wish to acknowledge all the unpublished data used herein which were contributed by many researchers, especially the coordinators and volunteers of the nesting beach surveys and the sea turtle stranding and salvage network and the contributors to the Cooperative Marine Turtle Tagging Program. (PDF contains 349 pages)
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".