Toward an environmental predictor of tuna recruitment
Open accessAbstract
Bigeye tuna are of global economic importance and are the primary target species of Hawaii's most valuable commercial fishery. Due to their high commercial value, bigeye tuna are relatively well studied and routinely assessed. Larval and adult bigeye surveys have been conducted for many years and are supported by ongoing research on their physiology and life history. Yet, modeling stock dynamics and estimating future catch rates remain challenging. Here, we show that an appropriately lagged measure of phytoplankton size is a robust predictor of catch rates in Hawaii's bigeye tuna fishery with a forecast window of four years. We present a fishery‐independent tool with the potential to improve stock assessments, aid dynamic fisheries management, and allow Hawaii's commercial longline fishing industry to better plan for the future.
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The 'critical period' hypothesis was also borne out in the study of Woodworth-Jefcoats and Wren (2020).
“The “critical period” hypothesis was also borne out in the study of Woodworth-Jefcoats and Wren (2020).”
From Impacts of phytoplankton availability on bigeye tuna (Thunnus obesus) recruitment in the Indian Ocean (2024) · cites this paper as Woodworth-Jefcoats and Wren, 2020
The Results report significant correlations between phytoplankton size four years earlier and bigeye tuna catch rates in Hawaii’s longline fishery. The Discussion links this finding to the hypothesis that food availability during early life affects survival, but the study did not directly measure survival during that critical period. The finding is consistent with the hypothesis rather than a direct demonstration of it. (LLM, conf=0.83)
Experimental — accuracy not yet measuredIn Woodworth-Jefcoats and Wren (2020), MD50 was identified as an environmental driver of bigeye tuna recruitment and can be an informative predictor of bigeye tuna catch rates in Hawaii's deep-set longline fishery with a 4-year forecast window.
“In their study, MD50 was identified as an environmental driver of bigeye tuna recruitment and can be an informative predictor of bigeye tuna catch rates in Hawaii’s deep-set longline fishery with a 4-year forecast window, aligning with the results of our study.”
From Impacts of phytoplankton availability on bigeye tuna (Thunnus obesus) recruitment in the Indian Ocean (2024) · cites this paper as Woodworth-Jefcoats and Wren, 2020
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Cites
Reglero, P., Tittensor, D., Álvarez-Berastegui, D., Aparicio-González, A., & Worm, B. (2014) · Marine Ecology Progress Series · doi:10.3354/meps10666 · Cited by 106 · see citing works
Flagged first, then by citations
Research works printed but not linked: 25
- R E FE R E N C E S Abascal, F. J., Peatman, T., Leroy, B., Nicol, S., Schaefer, K., Fuller, D. W., & Hampton, J. (2018). Spatiotemporal variability in bigeye vertical distribution in the Pacific Ocean. Fisheries Research, 204, 371-379. https://doi.org/10.1016/j.fishr es.2018.03.013 · DOI
- Ayers, A. L., Hospital, J., & Boggs, C. (2018). Bigeye tuna catch limits lead to differential impacts for Hawaii longliners. Marine Policy, 94, 93-105. https://doi.org/10.1016/j.marpol.2018.04.032 · DOI
- Barnes, C., Irigoien, X., De Oliveira, J. A. A., Maxwell, D., & Jennings, S. (2011). Predicting marine phytoplankton community size structure from empirical relationships with remotely sensed variables. Journal of Plankton Research, 33, 13-24. https://doi.org/10.1093/plank t/ fbq088 · DOI · Paper page
- Bigelow, K., Musyl, M. K., Poisson, F., & Kleiber, P. (2006). Pelagic longline gear depth and shoaling. Fisheries Research, 77, 173-183. https://doi. org/10.1016/j.fishr es.2005.10.010 · DOI
- Blanchard, J. L., Heneghan, R. F., Everett, J. D., Trebilco, R., & Richardson, A. J. (2017). From bacteria to whales: Using functional size spectra to model marine ecosystems. Trends in Ecology & Evolution, 32(3), 174-186. https://doi.org/10.1016/j.tree.2016.12.003 · DOI
- Block, B. A., & Stevens, E. D. (2001). Tuna physiology, ecology, and evolu- tion, 1st ed. San Diego, CA: Academic Press.
- Bograd, S. J., Kang, S., Di Lorenzo, E., Horii, T., Katugin, O. N., King, J. R., … Batchelder, H. (2019). Developing a social-ecological-environmental system framework to address climate change impacts in the North Pacific. Frontiers in Marine Science, 6, 333. https://doi.org/10.3389/ fmars.2019.00333 · DOI
- Barale, J. F. R. Gower, & L. Alberotanza (eds). Oceanography from Space: Revisited (pp. 273-287). Dordrecht, the Netherlands: Springer. https://doi.org/10.1007/978-90-481-8681-5_16 · DOI
- Hobday, A. J., Spillman, C. M., Eveson, J. P., & Hartog, J. R. (2016). Seasonal forecasting for decision support in marine fisheries and aquaculture. Fisheries Oceanography, 25(Suppl 1), 45-56. https://doi. org/10.1111/fog.12083 · DOI
- Howell, E. A., Kobayashi, D. R., Parker, D. M., Balasz, G. H., & Polovina, J. J. (2008). TurtleWatch: A tool to aid in the bycatch reduction of loggerhead turtles Caretta caretta in the Hawaii-based pelagic long- line fishery. Endangered Species Research, 5, 267-278. https://doi. org/10.3354/esr00096 · DOI
- Kume, S. (1969). Ecological studies on bigeye tuna -V: A critical review on distribution, size composition and stock structure of bigeye tuna in the North Pacific Ocean (north of 16°N). Bulletin of the Far Seas Fisheries Research Lab, 1, 57-75.
- Lehodey, P., Chai, F., & Hampton, J. (2003). Modelling climate-related variability of tuna populations from a coupled ocean-biogeochem- ical-populations dynamics model. Fisheries Oceanography, 12, 483- 494. https://doi.org/10.1046/j.1365-2419.2003.00244.x · DOI · Paper page
- Lehodey, P., Senina, I., Sibert, J., Bopp, L., Calmettes, B., Hampton, J., & Murtugudde, R. (2010). Preliminary forecasts of Pacific bigeye tuna population trends under the A2 PICC scenario. Progress in Oceanography, 86, 302-315. https://doi.org/10.1016/j.pocean.2010.04.021 · DOI
- Llopiz, J. K., & Hobday, A. J. (2015). A global comparative analysis of the feeding dynamics and environmental conditions of larval tunas, mackerel, and billfishes. Deep-Sea Research II, 113, 113-124. https:// doi.org/10.1016/j.dsr2.2014.05.014 · DOI · Paper page
- Muhling, B. A., Lamkin, J. T., Alemany, F., García, A., Farley, J., Ingram, G. W., … Carrion, R. L. (2017). Reproduction and larval biology in tunas, and the importance of restricted area spawning grounds. Reviews in Fish Biology and Fisheries, 27, 697-732. https://doi.org/10.1007/ s1116 0-017-9471-4 · DOI · Paper page
- Shimizu, Japan: Far Seas Fisheries Research Laboratory, 1985(3), 99. Pacific Islands Fisheries Science Center (2019a). Hawaii DAR Dealer Reporting System Data. https://inport.nmfs.noaa.gov/inpor t/item/5610 Pacific Islands Fisheries Science Center (2019b). The Hawaii and California- based Pelagic Longline Vessels Annual Report for 1 January -31 December, 2018. Data Report DR-19-047. https://doi.org/10.25923/ dq48-ef09 Pacific Islands Fisheries Science Center (2019c) Hawaii Longline Logbook, https://inport.nmfs.noaa.gov/inpor t/item/2721 · DOI
- Pikitch, E. K., Santora, C., Babcock, E. A., Bakun, A., Bonfil, R., Conover, D. O., … Sainsbury, K. J. (2004). Ecosystem-based fishery manage- ment. Science, 305(5682), 346-347. https://doi.org/10.1126/scien ce.1098222 · DOI
- Polovina, J. J., & Woodworth, P. A. (2012). Declines in phytoplank- ton cell size in the subtropical oceans estimated from satel- lite remotely-sense temperature and chlorophyll, 1998-2007. Deep-Sea Research II, 77-80, 82-88. https://doi.org/10.1016/j. dsr2.2012.04.006 · DOI
- Saha, K., Zhao, X., Zhang, H.-M., Casey, K. S., Zhang, D., Baker-Yeboah, S., … Relph, J. M. (2018). AVHRR Pathfinder version 5.3 level 3 collated (L3C) global 4 km sea surface temperature for 1981-Present. NOAA National Centers for Environmental Information. Dataset., https:// doi.org/10.7289/v52j68xx · DOI · Paper page
- Sathyendranath, S., Grant, M., Brewin, R. J. W., Brockmann, C., Brotas, V., Chuprin, A.… Zibordi, G. (2018) ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 3.1 Data. Centre for Environmental Data Analysis 04 July 2018. https://doi. org/10.5285/9c334 fbe6d 424a7 08cf3 c4cf0 c6a53f5 · DOI
- Sculley, M., Ijimi, H., & Chang, Y.-J. (2018). A Base-case Model in Stock Synthesis 3.30 for the 2018 North Pacific Swordfish (Xiphias gladius) Stock Assessment. Pacific Islands Fisheries Science Center (PIFSC) Working Paper, WP-18-005. https://doi.org/10.7289/V5/WP-PIFSC -18-005 · DOI
- Tommasi, D., Stock, C. A., Pegion, K., Vecchi, G. A., Methot, R. D., Alexander, M. A., & Checkley, D. M. (2017). Improved manage- ment of small pelagic fisheries through seasonal climate predic- tion. Ecological Applications, 27, 378-388. https://doi.org/10.1002/ eap.1458 · DOI
- Woodworth-Jefcoats, P. A., Blanchard, J. L., & Drazen, J. C. (2019). Relative impacts of simultaneous stressors on a pelagic marine eco- system. Frontiers in Marine Science, 6, 383. https://doi.org/10.3389/ fmars.2019.00383 · DOI
- Woodworth-Jefcoats, P. A., Polovina, J. J., & Drazen, J. C. (2018). Synergy among oceanographic variability, fishery expansion, and longline catch composition in the central North Pacific Ocean. Fishery Bulletin, 116, 228-239. https://doi.org/10.7755/FB.116.3.2 · DOI
- Wren, J. L. K., & Polovina, J. J. (in review) A fishery-dependent recruitment and forecast index for bigeye tuna (Thunnus obesus) in the Hawai'i-based longline fishery.
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
- Woodworth‐Jefcoats, P. A., & Wren, J. L. K.
- Affiliations
- NOAA National Marine Fisheries Service (US)
- Corresponding author
- Woodworth‐Jefcoats, Phoebe A.
- Venue
- Fisheries Oceanography
- Publisher
- Wiley
- Published
- 2020-07-22
- Volume
- 29
- Issue
- 5
- Pages
- 436-441
- ISSN
- 1054-6006 (ISSN-L)
- 1365-2419
- OpenAlex
- W3044428993
- Cited by
- 7
- References
- 1
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2020: 1
- FWCI
- 0.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Fisheries Oceanography (publishedVersion, cc-by)
- NOAA Institutional Repository (submittedVersion, cc-by)
- 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
- Life Sciences › Agricultural and Biological Sciences › Aquatic Science › Aquaculture Nutrition and Growth
- Keywords
- bigeye tuna, phytoplankton cell size, environmental predictors, catch rates, stock assessment, fisheries management, longline fishing
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