Potential predictability of skipjack tuna (Katsuwonus pelamis) catches in the Western Central Pacific.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
21 02 2020
Historique:
received: 19 11 2019
accepted: 06 02 2020
entrez: 22 2 2020
pubmed: 23 2 2020
medline: 31 12 2020
Statut: epublish

Résumé

The Pacific Island countries have a substantial socio-economic dependency on fisheries. Skipjack tuna is one of the most important species in the Western Central Pacific (WCP) and its catches in this region exhibit a spatio-temporal variability influenced by ocean conditions, mainly the El Niño-Southern Oscillation (ENSO). This study investigates the relationship between skipjack tuna catch amounts and environmental variables in the equatorial Pacific during 1990-2014, and evaluates the potential predictability of the catches based on their statistical relationship. A series of regressed and reconstructed spatial patterns of upper-ocean temperature, salinity, currents and precipitation represent ENSO-like variability, and their principal component time series are used to estimate the predictability of skipjack tuna catches in the Federated States of Micronesia (FSM). ENSO-like variability depicted from 100 m temperature and 5 m salinity in the equatorial Pacific exhibit a significant predictability for the annual catch amount in the FSM for several years with a training period of > 20 years. This suggests that the subsurface temperature or near surface salinity can be a better predictor of ecosystem variability than widely used sea surface temperature. Applications of this result to other species could have broad implications for the fishery industry in the WCP.

Identifiants

pubmed: 32081958
doi: 10.1038/s41598-020-59947-8
pii: 10.1038/s41598-020-59947-8
pmc: PMC7035267
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3193

Références

Williams, P. & Terawasi, P. Overview of tuna fisheries in the western and central Pacific Ocean, including economic conditions–2010. WCPFC-SC7-2011/GN WP-1 (2011).
Food and Agriculture Organization. Review of the state of world marine fishery resources 2011. Marine resources - Western Central Pacific. FIRMS Reports. In: Fisheries and Resources Monitoring System (FIRMS), http://firms.fao.org/firms/resource/13333/en (2013).
Brander, K. M. Global fish production and climate change. Proc. Nat. Acad. Sci. USA 104, 19709–19714 (2007).
doi: 10.1073/pnas.0702059104
McIlgorm, A. et al. How will climate change alter fishery governance? Insights from seven international case studies. Mar. Policy 34, 170–177 (2010).
doi: 10.1016/j.marpol.2009.06.004
Lehodey, P., Senina, I., Calmettes, B., Hampton, J. & Nicol, S. Modelling the impact of climate change on Pacific skipjack tuna population and fisheries. Clim. Change 119, 95–109 (2013).
doi: 10.1007/s10584-012-0595-1
Loukos, H., Monfray, P., Bopp, L. & Lehodey, P. Potential changes in skipjack tuna (Katsuwonus pelamis) habitat from a global warming scenario: modelling approach and preliminary results. Fish. Oceanography 12, 474–482 (2003).
doi: 10.1046/j.1365-2419.2003.00241.x
Brill, R. W. A review of temperature and oxygen tolerance studies of tunas pertinent to fisheries oceanography, movement models and stock assessments. Fish. Oceanography 3, 204–216 (1994).
doi: 10.1111/j.1365-2419.1994.tb00098.x
Lehodey, P., Berignac, M., Hampton, J., Lewis, A. & Picaut, J. El Niño Southern Oscillation and tuna in the western Pacific. Nature 389, 715–718 (1997).
doi: 10.1038/39575
McPhaden, M. J. & Picaut, J. El Niño-Southern Oscillation displacements of the western equatorial Pacific warm pool. Science 250, 1385–1388 (1990).
doi: 10.1126/science.250.4986.1385
Picaut, J., Ioualalen, M., Menkes, C., Delcroix, T. & McPhaden, M. J. Mechanism of the zonal displacements of the Pacific warm pool: Implications for ENSO. Science 274, 1486–1489 (1996).
doi: 10.1126/science.274.5292.1486
Clarke, A. J. & Van Gorder, S. ENSO prediction using an ENSO trigger and a proxy for western equatorial Pacific warm pool movement. Geophys. Res. Lett. 28, 579–582 (2001).
doi: 10.1029/2000GL012201
Maes, C. et al. Observed correlation of surface salinity, temperature and barrier layer at the eastern edge of the western Pacific warm pool. Geophys. Res. Lett. 33, L06601 (2006).
doi: 10.1029/2005GL024772
Vincent, D. G. The South Pacific convergence zone (SPCZ): A review. Mon. Weather Rev. 122, 1949–1970 (1994).
doi: 10.1175/1520-0493(1994)122<1949:TSPCZA>2.0.CO;2
Wang, C. C. & Magnusdottir, G. The ITCZ in the central and eastern Pacific on synoptic time scales. Mon. Weather Rev. 134, 1405–1421 (2006).
doi: 10.1175/MWR3130.1
Chen, B., Lin, X. & Bacmeister, J. T. Frequency distribution of daily ITCZ patterns over the western–central Pacific. J. Clim. 21, 4207–4222 (2008).
doi: 10.1175/2008JCLI1973.1
Takahashi, K. & Battisti, D. S. Processes controlling the mean tropical Pacific precipitation pattern. Part II: The SPCZ and the southeast Pacific dry zone. J. Clim. 20, 5696–5706 (2007).
doi: 10.1175/2007JCLI1656.1
Gouriou, Y. & Delcroix, T. Seasonal and ENSO variations of sea surface salinity and temperature in the South Pacific Convergence Zone during 1976–2000. J. Geophys. Res. Oceans 107, SRF 12-1–SRF 12-14 (2002).
doi: 10.1029/2001JC000830
Delcroix, T., Cravatte, S. & McPhaden, M. J. Decadal variations and trends in tropical Pacific sea surface salinity since 1970. J. Geophys. Res. Oceans 112, C03012 (2007).
doi: 10.1029/2006JC003801
Sprintall, J. & Tomczak, M. Evidence of the barrier layer in the surface layer of the tropics. J. Geophys. Res. Oceans 97, 7305–7316 (1992).
doi: 10.1029/92JC00407
Bosc, C., Delcroix, T. & Maes, C. Barrier layer variability in the western Pacific warm pool from 2000 to 2007. J. Geophys. Res. Oceans 114, C06023 (2009).
doi: 10.1029/2008JC005187
Zheng, F., Zhang, R. H. & Zhu, J. Effects of interannual salinity variability on the barrier layer in the western-central equatorial Pacific: A diagnostic analysis from Argo. Adv. Atmo. Sci. 31, 532–542 (2014).
doi: 10.1007/s00376-013-3061-8
Maes, C. & Belamari, S. On the impact of salinity barrier layer on the Pacific Ocean mean state and ENSO. Sola 7, 97–100 (2011).
doi: 10.2151/sola.2011-025
Vialard, J. & Delecluse, P. An OGCM study for the TOGA decade. Part II: Barrier-layer formation and variability. J. Phys. Oceanogr. 28, 1089–1106 (1998).
doi: 10.1175/1520-0485(1998)028<1089:AOSFTT>2.0.CO;2
Folland, C. K., Renwick, J. A., Salinger, M. J. & Mullan, A. B. Relative influences of the interdecadal Pacific oscillation and ENSO on the South Pacific convergence zone. Geophys. Res. Lett. 29, 21–1 (2002).
doi: 10.1029/2001GL014201
Juillet‐Leclerc, A. et al. SPCZ migration and ENSO events during the 20th century as revealed by climate proxies from a Fiji coral. Geophys. Res. Lett. 33, L17710 (2006).
doi: 10.1029/2006GL025950
Choi, K. Y., Vecchi, G. A. & Wittenberg, A. T. Nonlinear zonal wind response to ENSO in the CMIP5 models: Roles of the zonal and meridional shift of the ITCZ/SPCZ and the simulated climatological precipitation. J. Clim. 28, 8556–8573 (2015).
doi: 10.1175/JCLI-D-15-0211.1
Kim, K.-Y. & North, G. R. EOFs of harmonizable cyclostationary processes. J. Atmos. Sci. 54, 2416–2427 (1997).
doi: 10.1175/1520-0469(1997)054<2416:EOHCP>2.0.CO;2
Kim, K.-Y., North, G. R. & Huang, J. EOFs of one-dimensional cyclostationary time series: Computation, examples, and stochastic modeling. J. Atmos. Sci. 53, 1007–1017 (1996).
doi: 10.1175/1520-0469(1996)053<1007:EOODCT>2.0.CO;2
Behrenfeld, M. J. et al. Biospheric primary production during an ENSO transition. Science 291, 2594–2597 (2001).
doi: 10.1126/science.1055071
Park, J.-Y., Kug, J.-S., Park, J., Yeh, S.-W. & Jang, C. J. Variability of chlorophyll associated with El Niño–Southern Oscillation and its possible biological feedback in the equatorial Pacific. J. Geophys. Res. 116, C10001 (2011).
doi: 10.1029/2011JC007056
Radenac, M.-H., Léger, F., Singh, A. & Delcroix, T. Sea surface chlorophyll signature in the tropical Pacific during eastern and central Pacific ENSO events. J. Geophys. Res. Oceans 117, C04007 (2012).
doi: 10.1029/2011JC007841
Na, H., Jang, B.-G., Choi, W.-M. & Kim, K.-Y. Statistical simulations of the future 50-year statistics of Cold-Tongue El Niño and Warm-Pool El Niño. Asia-Pac. J. Atmos. Sci. 47, 223–233 (2011).
doi: 10.1007/s13143-011-0011-1
Pauly, D. & Zeller, D. (Editors) Sea Around Us Concepts, Design and Data (seaaroundus.org) (2015).
Vali, S. et al. Reconstruction of total fisheries catches for the Federated States of Micronesia (1950-2010). Fisheries-Centre of The University of British Columbia, Working paper #2014-06 (2014).
Good, S. A., Martin, M. J. & Rayner, N. A. EN4: Quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates. J. Geophys. Res. Oceans 118, 6704–6716 (2013).
doi: 10.1002/2013JC009067
Carton, J. A., Chepurin, G. A. & Chen, L. SODA3: A new ocean climate reanalysis. J. Clim. 31, 6967–6983 (2018).
doi: 10.1175/JCLI-D-18-0149.1
Xie, P. & Arkin, P. Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bul. Am. Meteorol. Soc. 78, 2539–2558 (1997).
doi: 10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2
Garnesson, P., Mangin, A., Fanton d’Andon, O., Demaria, J. & Bretagnon, M. The CMEMS GlobColour chlorophyll a product based on satellite observation: multi-sensor merging and flagging strategies. Ocean Sci. 15, 819–830 (2019).
doi: 10.5194/os-15-819-2019
Kim, K. Y., Hamlington, B. & Na, H. Theoretical foundation of cyclostationary EOF analysis for geophysical and climatic variables: concepts and examples. Earth-Sci. Rev. 150, 201–218 (2015).
doi: 10.1016/j.earscirev.2015.06.003
Kim, K. Y. Statistical prediction of cyclostationary processes. J. Clim. 13, 1098–1115 (2000).
doi: 10.1175/1520-0442(2000)013<1098:SPOCP>2.0.CO;2

Auteurs

Jihwan Kim (J)

School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea.

Hanna Na (H)

School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea. hanna.ocean@snu.ac.kr.
Research Institute of Oceanography, Seoul National University, Seoul, Republic of Korea. hanna.ocean@snu.ac.kr.

Young-Gyu Park (YG)

Korea Institute of Ocean Science and Technology, Busan, Republic of Korea.

Young Ho Kim (YH)

Department of Oceanography, Pukyong National University, Busan, Republic of Korea.

Articles similaires

Robotic Surgical Procedures Animals Humans Telemedicine Models, Animal

Odour generalisation and detection dog training.

Lyn Caldicott, Thomas W Pike, Helen E Zulch et al.
1.00
Animals Odorants Dogs Generalization, Psychological Smell
Animals TOR Serine-Threonine Kinases Colorectal Neoplasms Colitis Mice
Animals Tail Swine Behavior, Animal Animal Husbandry

Classifications MeSH