Elemental signatures reveal the geographic origins of a highly migratory shark: prospects for measuring population connectivity
Bibliographic record
Abstract
MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 556:173-193 (2016) - DOI: https://doi.org/10.3354/meps11844 Elemental signatures reveal the geographic origins of a highly migratory shark: prospects for measuring population connectivity Wade D. Smith1,5,*, Jessica A. Miller2, J. Fernando Márquez-Farías3, Selina S. Heppell4 1Department of Fisheries and Wildlife, Hatfield Marine Science Center, Oregon State University, 2030 SE Marine Science Drive, Newport, OR 97365, USA 2Department of Fisheries and Wildlife, Coastal Oregon Marine Experiment Station, Hatfield Marine Science Center, 2030 SE Marine Science Drive, Oregon State University, Newport, OR 97365, USA 3Universidad Autonóma de Sinaloa, Facultad de Ciencias del Mar, Paseo Claussen S/N, Col. Centro, 82000 Mazatlán, Sinaloa, Mexico 4Department of Fisheries and Wildlife, Oregon State University, 104 Nash Hall, Corvallis, OR 97331, USA 5Present address: University of British Columbia, Institute for the Oceans and Fisheries, 2202 Main Mall, Vancouver, British Columbia V6T 1Z4, Canada *Corresponding author: w.smith@oceans.ubc.ca ABSTRACT: Distinguishing individual natal origins of highly dispersive species is essential for quantifying the extent of connectivity among spatially separated groups. Variation in the chemical composition of calcified structures has been used to determine natal origins of many organisms but the utility of this approach to sharks and rays has only recently been examined. We evaluated the ability to accurately classify young-of-the-year scalloped hammerhead sharks Sphyrna lewini to their putative natal origins using vertebral elemental signatures and assessed individual, temporal, and spatial variation in vertebral chemistry. Vertebrae were collected from sharks captured in artisanal fisheries along the Pacific coast of Mexico and Costa Rica in 2007 to 2009. Elemental signatures were measured using laser ablation inductively coupled plasma mass spectrometry. Elemental signatures were spatially distinct and served as reliable site-specific markers. Intra-annual variation in natal signatures was detected among and within sites. Natal signatures also differed across years within sites. Inter-annual variation was driven by a single year (2008) and site-specific signatures were similar for 2007 and 2009. Classifications to geographic origins exceeded chance expectations and discrimination among sites was achieved with 39 to 100% success. Classification accuracy improved when data were analyzed at finer spatial and temporal resolution (i.e. year, season, month). Vertebral elemental signatures can successfully distinguish among sharks that have occupied different locations across broad spatial scales, from 10s to >1000 km. Identification of connectivity patterns and key areas of use through intrinsic natal signatures may propel more tractable, spatially explicit approaches to the conservation and management of elasmobranch populations. KEY WORDS: Connectivity · Elemental signature · Intrinsic markers · Natal origin · Philopatry · Population structure · Elasmobranch Full text in pdf format PreviousNextCite this article as: Smith WD, Miller JA, Márquez-Farías JF, Heppell SS (2016) Elemental signatures reveal the geographic origins of a highly migratory shark: prospects for measuring population connectivity. Mar Ecol Prog Ser 556:173-193. https://doi.org/10.3354/meps11844 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 556. Online publication date: September 08, 2016 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2016 Inter-Research.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".