Spatial stock assessment methods: A viewpoint on current issues and assumptions
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Claims the paper makes
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Accurately accounting for population structure in stock assessments can improve model performance and reduce bias.
“Accurately accounting for population structure in stock assessments can improve model performance and reduce bias (Punt, 2019).”
From Impacts of phytoplankton availability on bigeye tuna (Thunnus obesus) recruitment in the Indian Ocean (2024) · cites this paper as Punt, 2019
Cited by
Sorted by citations
Wang, Y., Zhang, Y., Geng, Z., & Zhu, J. (2024) · Frontiers in Marine Science · doi:10.3389/fmars.2024.1392273 · Cited by 2 · see citing works
- Authors
- Punt, A. E.
- Affiliations
- CSIRO Oceans and Atmosphere (AU)
- Corresponding author
- Punt, André E.
- ORCID
- Punt, André E.
- Venue
- Fisheries Research
- Publisher
- Elsevier BV
- Published
- 2019-05
- Volume
- 213
- Pages
- 132-143
- ISSN
- 0165-7836 (ISSN-L)
- OpenAlex
- W2911602249
- Cited by
- 107
- References
- 0
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 16 · 2023: 11 · 2022: 14 · 2021: 17 · 2020: 14 · 2019: 6
- FWCI
- 6.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Fisheries Research (acceptedVersion)
- Funders
- Joint Institute for the Study of the Atmosphere and Ocean
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Marine and fisheries research
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Keywords
- spatial structure, catchability, fishing gear selectivity, parameter estimation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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