Cited by 23Marine and fisheries researchFish Ecology and Management StudiesMathematical and Theoretical Epidemiology and Ecology Models

Non-parametric modeling reveals environmental effects on bluefin tuna recruitment in Atlantic, Pacific, and Southern Oceans

Open access
Harford, William J., Karnauskas, Mandy, Walter, John F., Liu, Hui·2017·Fisheries Oceanography

Abstract

Environment–recruitment relationships can be difficult to delineate with parametric statistical models and can be prone to misidentification. We use non‐parametric time‐series modeling which makes no assumptions about functional relationships between variables, to reveal environmental influences on early life stages of bluefin tuna and demonstrate improvement in prediction of subsequent recruitment. The influence of sea surface temperature, which has been previously associated with larval growth and survival, was consistently detected in recruitment time series of bluefin tuna stocks that spawn in the Mediterranean Sea, the North Pacific, and the Southern Ocean. Short time series for the Gulf of Mexico stock may have precluded a clear determination of environmental influences on recruitment fluctuations. Because the non‐parametric approach does not require specification of equations to represent system dynamics, predictive models can likely be developed that appropriately reflect the complexity of the ecological system under investigation. This flexibility can potentially overcome methodological challenges of specifying structural relationships between environmental conditions and fish recruitment. Consequently, there is potential for non‐parametric time series modeling to supplement traditional stock recruitment models for fisheries management.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/fog.12205

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The increasing trend in annual recruitment of eastern Atlantic bluefin tuna from the 1970s to the early 2000s has been related to increasing summer temperatures in the Balearic Sea.

    “the increasing trend in annual recruitment from the 1970s to the early 2000s has been related to increasing summer temperatures in the Balearic Sea (Harford et al., 2017)”

    From Pelagic habitat and offspring survival in the eastern stock of Atlantic bluefin tuna (2019) · cites this paper as Harford et al., 2017

    The 'Detecting environmental effects on recruitment' section links July sea-surface temperature near Mediterranean spawning areas to eastern Atlantic bluefin tuna recruitment. But the paper does not establish that recruitment rose from the 1970s to the early 2000s because summer temperatures increased in the Balearic Sea. Its scenario analysis instead reports a state-dependent relationship, negative in 63% of Mediterranean predictions and positive in 37%. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 10

  1. Beamish, R.J., Schnute, J.T., Cass, A.J., Neville, C.M., and Sweeting, R.M. (2004). The Influence of Climate on the Stock and Recruitment of Pink and Sockeye Salmon from the Fraser River, British Columbia, Canada. Trans. Am. Fish. Soc. 133, 1396-1412.
  2. Deyle, E.R., Fogarty, M., Hsieh, C. -h., Kaufman, L., MacCall, A.D., Munch, S.B., Perretti, C.T., Ye, H., and Sugihara, G. (2013). Predicting climate effects on Pacific sardine. Proc. Natl. Acad. Sci. 110, 6430-6435.
  3. May, R.M. (2011). Larval mortality in marine fishes and the critical period concept. In The Early Life History of Fish: The Proceedings of an International Symposium Held at the Dunstaffnage Marine Research Laboratory of the Scottish ... at Oban, Scotland, from May 17-23, 1973, J.H.S. Blaxter, ed. (S.l.: Springer), p.
  4. Mohn, R.K. (1993). Bootstrap estimates of ADAPT parameters, their projection in risk analysis and their retrospective patterns. In Risk Evaluation and Biological Reference Points for Fisheries Management, S.J. Smith, J.J. Hunt, and D. Rivard, eds. (Can. Spec. Publ. Fish. Aquat. Sci. 120), pp. 173-184.
  5. National Climatic Data Center Department of Commerce, Data Support Section/Computational and Information Systems Laboratory/National Center for Atmospheric Research/University Corporation for Atmospheric Research, Earth System Research Laboratory/NOAA/U.S. Department of Commerce, and Cooperative Institute for Research in Environmental Sciences/University of Colorado, 1984: International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Release 2.5, Monthly Summaries. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, CO. [Available online at http://dx.doi.org/10.5065/D6CF9N3F.] Accessed 04 Aug 2014. · DOI
  6. Perretti, C.T., Munch, S.B., and Sugihara, G. (2013). Model-free forecasting outperforms the correct mechanistic model for simulated and experimental data. Proc. Natl. Acad. Sci. 110, 5253-5257.
  7. Quinn, T.J.I., and Deriso, R.B. (1999). Quantitative Fish Dynamics (New York, USA: Oxford University Press).
  8. Sugihara, G., Allan, W., Sobel, D., and Allan, K.D. (1996). Nonlinear control of heart rate variability in human infants. Proc. Natl. Acad. Sci. 93, 2608-2613.
  9. Vert-pre, K.A., Amoroso, R.O., Jensen, O.P., and Hilborn, R. (2013). Frequency and intensity of productivity regime shifts in marine fish stocks. Proc. Natl. Acad. Sci. 110, 1779-1784.
  10. Ye, H., Beamish, R.J., Glaser, S.M., Grant, S.C.H., Hsieh, C., Richards, L.J., Schnute, J.T., and Sugihara, G. (2015a). Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling. Proc. Natl. Acad. Sci. 112, E1569-E1576.

Cited by

Sorted by citations

Authors
Harford, W. J., Karnauskas, M., Walter, J. F., & Liu, H.
Affiliations
  • University of Miami (US)
  • National Oceanic and Atmospheric Administration (US)
  • Texas A&M University at Galveston (US)
Corresponding author
Harford, William J.
Venue
Fisheries Oceanography
Publisher
Wiley
Published
2017-01-06
Volume
26
Issue
4
Pages
396-412
ISSN
  • 1054-6006 (ISSN-L)
  • 1365-2419
OpenAlex
W2569295050
Cited by
23
References
11
Citations by year
2024: 1 · 2023: 5 · 2022: 1 · 2020: 5 · 2019: 3 · 2018: 7 · 2017: 1
FWCI
3.03
Type
journal article
Language
en
Open access
Locations
  • Fisheries Oceanography (publishedVersion)
  • NOAA Institutional Repository (submittedVersion, cc-by)
Funders
NOAA Fisheries Stock Assessment Methods Program
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
bluefin tuna, Thunnus thynnus, recruitment (biology), sea surface temperature, early life stages, larval growth and survival, Mediterranean Sea, North Pacific, Southern Ocean, Gulf of Mexico, stock-recruitment models, fisheries management

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.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review