Role of environmental conditions in structuring the stock trajectory of Thunnus albacares, Th. alalunga and Th. obesus in the South Pacific Region

A. A.  Singh

doi:10.15421/012326

A. A. Singh The University of the South Pacific

Keywords: albacore tuna; bigeye tuna; yellowfin tuna; Atlantic Multidecadal Oscillation; sea surface temperature; regime shift

Abstract

The lifestyle and culture of South Pacific Island countries have been long intertwined with oceanic resources. These countries are heavily dependent on tuna resources for their economies and socioeconomic livelihoods. Despite their importance, the mechanisms behind tuna stock trajectory patterns need to be better understood. With changing climatic and environmental conditions, it has become vital to understand the impact of these changes on tuna resources and if possible include them in long-term tuna harvest and management plans. A significant portion of the stock dynamics of yellowfin tuna (Thunnus albacares), albacore tuna (Th. alalunga) and bigeye tuna (Th. obesus) in the South Pacific Region may possibly be explained only by the environmental factors of sea surface temperature (SST) and Atlantic Multidecadal Oscillation AMO. The relationship of monthly SST and AMO was investigated with time series stock patterns of Th. albacares, Th. alalunga and Th. obesus in the Eastern and Western Pacific Ocean for the years 1972 to 2019. Monthly variables that exhibited significant correlation with CPUE variables were used in the Generalised Linear Model and Generalized Additive Model to reproduce the CPUE trajectory of the three tuna species from 1972 to 2019. Results showed that a significant portion of stock dynamics of Th. albacares, Th. alalunga and Th. obesus can be explained well by two environmental conditions of SST and AMO. This shows that a large portion of tuna variation in the Eastern and Southern Pacific is related to environmental conditions. Models with single variables are evidence of the significant individual effect of SST and AMO on stock time series of each tuna species. Models with two variables had a better fit in comparison to models with a single variable for all tuna stocks. Possibilities of two significantly different patterns in the trajectory of the three tuna species and environmental conditions used in the models were also observed. The trajectory patterns seemed to change around the 1990s and had significantly different means, indicating possible regime shifts. Environmental conditions play a highly significant role in structuring tuna stock trajectory in the South Pacific and need to be included in tuna management / harvest plans to ensure sustainability of this important resource. The importance of regime shifts should be recognised and further investigated for possible inclusion in tuna sustainability plans due to their influence on long-term tuna trajectory patterns.

References

Bell, J. D., Allain, V., Allison, E. H., Andréfouët, S., Andrew, N. L., Batty, M. J., Blanc, M., Dambacher, J. M., Hampton, J., Hanich, Q., Harley, S., Lorrain, A., McCoy, M., McTurk, N., Nicol, S., Pilling, G., Point, D., Sharp, M. K., Vivili, P., & Williams, P. (2015). Diversifying the use of tuna to improve food security and public health in Pacific Island countries and territories. Marine Policy, 51, 584–591.
Bell, J. D., Senina, I., Adams, T., Aumont, O., Calmettes, B., Clark, S., Dessert, M., Gehlen, M., Gorgues, T., Hampton, J., Hanich, Q., Harden-Davies, H., Hare, S. R., Holmes, G., Lehodey, P., Lengaigne, M., Mansfield, W., Menkes, C., Nicol, S., Ota, Y., Pasisi, C., Pilling, G., Reid, C., Ronneberg, E., Gupta, A. S., Seto, K. L., Smith, N., Taei, S., Tsamenyi, M., & Williams, P. (2021). Pathways to sustaining tuna-dependent Pacific Island economies during climate change. Nature Sustainability, 4(10), 900–910.
Chambers, L. E., Barnard, P., Poloczanska, E. S., Hobday, A. J., Keatley, M. R., Allsopp, N., & Underhill, L. G. (2017). Southern hemisphere biodiversity and global change: Data gaps and strategies. Austral Ecology, 42(1), 20–30.
Christensen, J. (2016). Illegal, unreported and unregulated fishing in historical perspective. In: Manez, K. S., & Poulsen, B. (Eds.). Perspectives on oceans past. Springer, Dordrecht. Pp. 133–153.
Coulter, A., Cashion, T., Cisneros-Montemayor, A. M., Popov, S., Tsui, G., Le Manach, F., Schillere, L., Palomaresa, M. L. D., Zellerf, D., & Pauly, D. (2020). Using harmonized historical catch data to infer the expansion of global tuna fisheries. Fisheries Research, 221, 105379.
Enfield, D. B., Mestas-Nuñez, A. M., & Trimble, P. J. (2001). The Atlantic Multidecadal Oscillation and its relation to rainfall and river flows in the continental U.S. Geophysical Research Letters, 28(10), 2077–2080.
Fox, J. (2015). Applied regression analysis and generalized linear models. Sage Publications.
Fromentin, J. M., & Powers, J. E. (2005). Atlantic bluefin tuna: Population dynamics, ecology, fisheries and management. Fish and Fisheries, 6(4), 281–306.
Gianelli, I., Orlando, L., Cardoso, L. G., Carranza, A., Celentano, E., Correa, P., de la Rossa, A., Dono, F., Haimovici, M., Horta, S., Jaureguizar, A. J., Jorge-Romero, G., Lercari, D., Martinez, G., Pereyra, I., Silveira, S., Vogler, R., & Defeo, O. (2023). Sensitivity of fishery resources to climate change in the warm-temperate Southwest Atlantic Ocean. Regional Environmental Change, 23(2), 49.
Hou, X., Ma, S., Tian, Y., & Zhang, S. (2022). The effects of trans-basin climate variability on skipjack tuna in the Northwest Pacific Ocean: Causal and nonstationary. Frontiers in Marine Science, 9, 1116.
Johnson, J. E., Allain, V., Basel, B., Bell, J. D., Chin, A., Dutra, L. X. C., Hooper, E., Loubser, D., Lough, J., Moore, B. R., & Nicol, S. (2020). Impacts of climate change on marine resources in the Pacific Island Region. In: Kumar, L. (Ed.). Climate change and impacts in the Pacific. Springer, Cham. Pp. 359–402.
Lan, K.-W., Lee, M.-A., Chou, C.-P., & Vayghan, A. H. (2018). Association between the interannual variation in the oceanic environment and catch rates of bigeye tuna (Thunnus obesus) in the Atlantic Ocean. Fisheries Oceanography, 27(5), 395–407.
Lee, P. F., Chen, I. C., & Tzeng, W. N. (2005). Spatial and temporal distribution patterns of bigeye tuna (Thunnus obesus) in the Indian Ocean. Zoological Studies, 44(2), 260–270.
Mediodia, H. J., Kahui, V., & Noy, I. (2020). Sea surface temperature and tuna catch in the Eastern Pacific Ocean under climate change. CESifo Working Paper Series, 8533.
Mori, A. S., Suzuki, K. F., Hori, M., Kadoya, T., Okano, K., Uraguchi, A., Muraoka, H., Sato, T., Shibata, H., Suzuki-Ohno, Y., Koba, K., Toda, M., Nakano, S., Kondoh, M., Kitajima, K., & Nakamura, M. (2023). Perspective: Sustainability challenges, opportunities and solutions for long-term ecosystem observations. Philosophical Transactions of the Royal Society B, 378(1881), 20220192.
Oh, T. G., Sakuramoto, K., Hasegawa, S., & Suzuki, N. (2005). Relationship between sea-surface temperature and catch fluctuations in the Pacific stock of walleye pollock in Japan. Fisheries Science, 71(4), 855–861.
Ovando, D., Libecap, G. D., Millage, K. D., & Thomas, L. (2021). Coasean approaches to address overfishing: Bigeye tuna conservation in the Western and Central Pacific Ocean. Marine Resource Economics, 36(1), 91–109.
Öztürk, B. (2015). Nature and extent of the illegal, unreported and unregulated (IUU) fishing in the Mediterranean Sea. Journal of Black Sea/Mediterranean Environment, 21(1), 67–91.
Pilling, G. M., Harley, S. J., Nicol, S., Williams, P., & Hampton, J. (2015). Can the tropical Western and Central Pacific tuna purse seine fishery contribute to Pacific Island population food security? Food Security, 7(1), 67–81.
Post, V., & Squires, D. (2020). Managing bigeye tuna in the Western and Central Pacific Ocean. Frontiers in Marine Science, 7, 619.
R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
Rayner, N. A. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., & Kaplan, A. (2003). Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research: Atmospheres, 108(D14), 4407.
Reid, C. (2019). Tuna resource management – economic implications and trade-offs in achieving maximum sustainable yield for bigeye and yellowfin tuna in the Western and Central Pacific Ocean. Pacific Economic Bulletin, 21(3), 31–45.
Sakuramoto, K. (2005). Does the ricker or beverton and holt type of stock-recruitment relationship truly exist? Fisheries Science, 71, 577–592.
Sakuramoto, K. (2012). A new concept of the stock-recruitment relationship for the Japanese sardine, Sardinops melanostictus. The Open Fish Science Journal, 5(1), 60–69.
Sakuramoto, K. (2021). Reproductive success in fish stocks can be reproduced by environmental factors alone. Open Access Library Journal, 8, e7636.
Sambah, A. B., Noor’izzah, A. U. R. U. M., Intyas, C. A., Widhiyanuriyawan, D., Affandy, D. P., & Wijaya, A. (2023). Analysis of the effect of ENSO and IOD on the productivity of yellowfin tuna (Thunnus albacares) in the South Indian Ocean, East Java, Indonesia. Biodiversitas, 24(5), 2689–2700.
Seto, K., & Hanich, Q. (2018). The Western and Central Pacific Fisheries Commission and the new conservation and management measure for tropical tunas. Asia-Pacific Journal of Ocean Law and Policy, 3(1), 146–151.
Singh, A. A., Sakuramoto, K., & Suzuki, N. (2015a). Impact of climatic factors on albacore tuna Thunnus alalunga in the South Pacific Ocean. American Journal of Climate Change, 4(4), 295–312.
Singh, A. A., Sakuramoto, K., Suzuki, N., & Alok, K. (2018). Climate-related variability and stock-recruitment relationship of the North Pacific albacore tuna. Polish Journal of Natural Sciences, 33, 131–154.
Singh, A. A., Sakuramoto, K., Suzuki, N., Roshni, S., Nath, P., & Kalla, A. (2017). Environmental conditions are important influences on the recruitment of North Pacific albacore tuna, Thunnus alalunga. Applied Ecology and Environmental Research, 15(1), 299–319.
Singh, A. A., Suzuki, N., & Sakuramoto, K. (2015b). Influence of climatic conditions on the time series fluctuation of yellowfin tuna Thunnus albacares in the South Pacific Ocean. Open Journal of Marine Science, 5(3), 247–264.
Syamsuddin, M., Saitoh, S. I., Hirawake, T., Syamsudin, F., & Zainuddin, M. (2016). Interannual variation of bigeye tuna (Thunnus obesus) hotspots in the Eastern Indian Ocean off Java. International Journal of Remote Sensing, 37(9), 2087–2100.
Taboada, F. G., Park, J. Y., Muhling, B. A., Tommasi, D., Tanaka, K. R., Rykaczewski, R. R., Stock, C. A., & Sarmiento, J. L. (2023). Anticipating fluctuations of bigeye tuna in the Pacific Ocean from three‐dimensional ocean biogeochemistry. Journal of Applied Ecology, 60(3), 463–479.
Varea, R., Piovano, S., & Ferreira, M. (2020). Knowledge gaps in ecotoxicology studies of marine environments in Pacific Island Countries and Territories – A systematic review. Marine Pollution Bulletin, 156, 111264.
Vayghan, A. H., Lee, M. A., Weng, J. S., Mondal, S., Lin, C. T., & Wang, Y. C. (2020). Multisatellite-based feeding habitat suitability modeling of albacore tuna in the Southern Atlantic Ocean. Remote Sensing, 12(16), 2515.
Wang, Y., Zhang, F., Geng, Z., Zhang, Y., Zhu, J., & Dai, X. (2023). Effects of climate variability on two commercial tuna species abundance in the Indian Ocean. Fishes, 8(2), 99.
World Bank (2016). Tuna fisheries. Pacific possible series. Background paper No. 3. World Bank Group, Washington.
Wu, Y. L., Lan, K. W., & Tian, Y. (2020). Determining the effect of multiscale climate indices on the global yellowfin tuna (Thunnus albacares) population using a time series analysis. Deep Sea Research Part II: Topical Studies in Oceanography, 175, 104808.
Wu, Y. L., Lan, K. W., Evans, K., Chang, Y. J., & Chan, J. W. (2022). Effects of decadal climate variability on spatiotemporal distribution of Indo-Pacific yellowfin tuna population. Scientific Reports, 12(1), 13715.
Zuur, A. F., Ieno, E. N., & Elphick, C. S. (2010). A protocol for data exploration to avoid common statistical problems. Methods in Ecology and Evolution, 1(1), 3–14.