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Oceanographic indicators for the occurrence of anchovy eggs inferred from generalized additive models

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초록

Three generalized additive models were applied to the distribution of anchovy eggs and oceanographic factors to determine the occurrence of anchovy spawning grounds in Korean waters and to identify the indicators of their occurrence using survey data from the spring and summer of 1985, 1995, and 2002. Binomial and Gaussian types of generalized additive models (GAM) and quantile generalized additive models (QGAM) revealed that egg density was influenced mostly by ocean temperature and salinity in spring, and the vertical structure of temperature, salinity, dissolved oxygen, and zooplankton biomass during summer in the upper quantiles of egg density. The GAM and QGAM model deviance explained 18.5–63.2% of the egg distribution in summer in the East and West Sea. For the principle component analysis-based GAMs, the variance explained by the final regression model was 27.3–67.0%, higher than the regular models and QGAMs for egg density in the East and West Sea. By analyzing the distribution of anchovy eggs off the Korean coast, our results revealed the optimal temperature and salinity conditions, in addition to high production and high vertical mixing, as the key indicators of the major spawning grounds of anchovies.

Abstract

Three generalized additive models were applied to the distribution of anchovy eggs and oceanographic factors to determine the occurrence of anchovy spawning grounds in Korean waters and to identify the indicators of their occurrence using survey data from the spring and summer of 1985, 1995, and 2002. Binomial and Gaussian types of generalized additive models (GAM) and quantile generalized additive models (QGAM) revealed that egg density was influenced mostly by ocean temperature and salinity in spring, and the vertical structure of temperature, salinity, dissolved oxygen, and zooplankton biomass during summer in the upper quantiles of egg density. The GAM and QGAM model deviance explained 18.5–63.2% of the egg distribution in summer in the East and West Sea. For the principle component analysis-based GAMs, the variance explained by the final regression model was 27.3–67.0%, higher than the regular models and QGAMs for egg density in the East and West Sea. By analyzing the distribution of anchovy eggs off the Korean coast, our results revealed the optimal temperature and salinity conditions, in addition to high production and high vertical mixing, as the key indicators of the major spawning grounds of anchovies.

참고문헌 (34)

  1. Alheit J, "Population synchronies within and between ocean basins : Apparent teleconnections and implications as to physical–biological linkage mechanisms", J Mar Syst, 79, pp.267~285 (2010)
  2. Alvarez-Fernandez S, "Temporal changes in plankton of the North Sea : community shifts and environmental drivers", Mar Ecol Prog Ser, 462, pp.21~38 (2012)
  3. Basilone G, "Effect of habitat conditions on reproduction of the European anchovy(Engraulis encrasicolus)in the Strait of Sicily", Fish Oceanogr, 15, pp.271~280 (2006)
  4. Boyra G, "Modelling the vertical distribution of eggs of anchovy(Engraulis encrasicolus)and sardine(Sardina pilchardus)", Fish Oceanogr, 12, pp.381~395 (2003)
  5. Chen C, "Chemical and physical fronts in the Bohai, Yellow and East China seas", J Mar Syst, 78, pp.394~410 (2009)
  6. Choi S, "Biomass estimation of anchovy(Engraulis japonicus)by acoustic and trawl survey during spring seasons in the southern Korean waters", J Kor Soc Fish Res, 4, pp.20~29 (2001)
  7. Denis V, "Spatio-temporal analysis of commercial trawler data using General Additive models : patterns of Loliginid squid abundance in the north-east Atlantic", ICES J Mar Sci, 59, pp.633~648 (2002)
  8. Fasiolo M, "Version 1.3.2. Package ‘qgam’ R-3.4.2;2020", ~
  9. Hao W, "Tidal front and the convergence of anchovy(Engraulis japonicus)eggs in the Yellow Sea", Fish Oceanogr, 12, pp.434~442 (2003)
  10. Hoeffle H, "Variability of northeast Arctic cod(Gadus morhua)distribution on the main spawning grounds in relation to biophysical factors", ICES J Mar Sci, 71, pp.1317~1331 (2014)
  11. Bérengère Husson, "Suitable habitats of fish species in the Barents Sea", Fisheries Oceanography, 29(6), pp.526~540 (2020), Wiley[DOI]
  12. 정희동, "한국 남서해역에서 조석전선의 변동과 저수온역 확장기작", 해양환경안전학회지, 15(4), pp.289~296 (2009), 해양환경안전학회
  13. Kang J, "Distribution of plankton related to the mesoscale physical structure within the surface mixed layer in the southwestern East Sea, Korea", J Plankton Res, 26, pp.1515~1528 (2004)
  14. Kim J, "Distribution of anchovy eggs and larvae off the western and southern coasts of Korea", Bull Korean Fish Soc, 21, pp.139~144 (1983)
  15. Kim J, "Vertical distribution of anchovy, Engraulis japonica eggs and larvae", Bull Korean Fish Soc, 21, pp.139~144 (1988)
  16. Kim J, "Temporal variation of seasonality of egg production and the spawning biomass of Pacific anchovy, Engraulis japonicus, in the southern waters of Korea in 1983-1994", Fish Oceanogr, 10, pp.297~310 (2001)
  17. Kim J, "Spatial distribution of early life stages of anchovy(Engraulis japonicus)and hairtail(Trichiurus lepturus)and their relationship with oceanographic features of the East China Sea during the 1997–1998 El Niño Event", Estuar Coast Shelf Sci, 63, pp.13~21 (2005)
  18. 김수암, "Climate Variability and Its Effects on Major Fisheries in Korea", Ocean Science Journal, 42(3), pp.179~192 (2007), 한국해양과학기술원
  19. 김상우, "다중위성 및 현장관측을 이용한 동해남부 연안용승 발생 전후의 해양환경 특성", 해양환경안전학회지, 16(4), pp.345~352 (2010), 해양환경안전학회
  20. Kim D, "Impact of an anticyclonic eddy on the summer nutrient and chlorophyll a distributions in the Ulleung Basin, East Sea(Japan Sea)", ICES J Mar Sci, 69, pp.23~29 (2011)
  21. Li S, "A Generalized Additive Model Combining Principal Component Analysis for PM2.5 Concentration Estimation", ISPRS Int J Geo-Inf, 6, pp.248~ (2017)
  22. Lim J, "Studies on the occurrence and distribution of eggs and larvae anchovy in the Korean waters", Bul Fish Res Dev Agency, 16, pp.73~86 (1977)
  23. Liu X, "Comparison between two GAMs in quantifying the spatial distribution of Hexagrammos otakii in Haizhou Bay, China", Fish Res, 218, pp.209~217 (2019)
  24. Murase H, "Application of a generalized additive model(GAM)to reveal relationships between environmental factors and distributions of pelagic fish and krill : a case study in Sendai Bay, Japan", ICES J Mar Sci, 66, pp.1417~1424 (2009)
  25. Park J, "Distribution of anchovy, Engraulis japonica(Houttuyn), in the coastal waters of Kangwon Province in Korea", Bull Korean Soc Fish Tech, 32, pp.223~234 (1996)
  26. Park J, "The relationship between oceanographic and fishing conditions for anchovy, Engraulis japonica, in the southern sea of Korea", J Korean Soc Fish Res, 6, pp.46~53 (2004)
  27. Sokal R, "Biometry: The Principles and Practice of Statistics in Biological Research" (1995), W. H. Freeman and Co.
  28. Somarakis S, "Daily egg production of anchovy in European waters", ICES J Mar Sci, 61, pp.944~958 (2004)
  29. Stoner A, "Spatially explicit analysis of estuarine habitat for juvenile winter flounder : combining generalized additive models and geographic information systems", Mar Ecol Prog Ser, 213, pp.253~271 (2001)
  30. Suh Y, "Study of a recurring anticyclonic eddy off Wonsan coast in northern Korea using satellite tracking drifter, satellite ocean color and sea surface temperature imagery", J Kor Soc Rem Sens, 16, pp.211~220 (1999)
  31. Vaz S, "Modelling species distributions using regression quantiles", J Appl Ecol, 45, pp.204~217 (2008)
  32. Waldock C, "The shape of abundance distributions across temperature gradients in reef fishes", Ecol Lett, 22, pp.685~696 (2019)
  33. Wood S, "Version 1.8-31, 2019 ‘mgcv’ R-3.4.2", ~
  34. Zhao J, "A comparison between two GAM models in quantifying relationships of environmental variables with fish richness and diversity indices", Aquat Ecol, 48, pp.297~312 (2014)

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