Results of using climate-oceanological predictors in a Random Forest model for the forecast of stock abundance dynamics of pink salmon runs in Western Kamchatka
https://doi.org/10.15853/2072-8212.2022.65.42-51
Abstract
An improvement of the forecast of pink salmon runs is one of the most actual problems in management of salmon stocks of Kamchatka. Algorhythm of Random Forest with the use of iterative selection of most important climate-oceanological predictors seem to be promising. Three authenticly influental predictors have been found for the model of Random Forest at the error of the forecast of 28%. Verification of the obtained results used alternative methods of selection of the best predictors. Obtained results have demonstrated possibility of the use of considered climate-oceanological predictors in modeling the forecasts of stock abundance dynamics of pink salmon in Western Kamchatka.
About the Authors
M. G. Feldman
Kamchatka Branch of Russian Federal Research Institute of Fisheries and Oceanography (KamchatNIRO)
Russian Federation
Russian Federation
Mark G. Feldman – Ph. D. (Biology), Leading Researcher
Petropavlovsk-Kamchatsky
A. V. Bugaev
Kamchatka Branch of Russian Federal Research Institute of Fisheries and Oceanography (KamchatNIRO)
Russian Federation
Russian Federation
Alexandr V. Bugaev – Dr. of Science (Biology), Deputy Director
Petropavlovsk-Kamchatsky
O. B. Tepnin
Kamchatka Branch of Russian Federal Research Institute of Fisheries and Oceanography (KamchatNIRO)
Russian Federation
Russian Federation
Oleg B. Tepnin – Head of Division
Petropavlovsk-Kamchatsky
References
1. Bugaev A.V., Tepnin O.B. Productivity of Pacific salmon: effects of water temperature conditions during first wintering in the North Pacific basin. Trudy VNIRO, 2015, vol. 158, pp. 89–111. (In Russian)
2. Bugaev A.V., Tepnin O.B., Radchenko V.I. Climate variability and Pacific salmon productivity in Russian Far East. The researches of the aquatic biological resources of Kamchatka and of the north-west part of the Pacific Ocean, 2018, vol. 49, pp. 5–50. (In Russian)
3. Bugaev A.V., Feldman M.H., Tepnin O.B., Koval M.V. Water surface temperature anomalies in the western North Pacific – potential climatic predictor of Pacific salmon runs in Kamchatka. Problems of Fisheries, 2021, vol. 22, № 4, pp. 46–62. (In Russian)
4. Feldman M.H. Using the decisions of the random forest algorithm for the purposes of forecasting pink salmon runs on North-Eastern Kamchatka. The researches of the aquatic biological resources of Kamchatka and of the north-west part of the Pacific Ocean, 2020, vol. 59, pp. 76–96. (In Russian)
5. Feldman M.H., Bugaev A.V. Modern principles of pink salmon (Oncorhynchus gorbuscha) stocks management in the Kamchatka Region (population dynamics, forecasting, fishing regulation). Problems of Fisheries, 2021, vol. 22, no. 4, pp. 86–95. (In Russian)
6. Feldman M.G., Shevlyakov E.A. Survival of Kamchatka pink salmon as result of combined influence of density regulation and environmental factors. Izvestia TINRO, 2015, vol. 182, pp. 88–114. (In Russian)
7. Feldman M.G., Shevlyakov E.A., Artukhina N.B. Evaluation of the Pacific salmon spawning escapement parameters for the river basins of West Kamchatka. The researches of the aquatic biological resources of Kamchatka and of the north-west part of the Pacific Ocean, 2019, vol. 52, pp. 50–78. (In Russian)
8. Breiman L. Random Forests. Machine Learning, 2001, no. 45 (1), pp. 5–32. Kursa M. Boruta for those in a hurry. Online article, 2020, 6 p. (https://cran.r-project.org/web/packages/ Boruta/vignettes/inahurry.pdf)
9. Kursa M., Rudnicki W. Feature Selection with the Boruta Package. Journal of Statistical Software, 2010, vol. 36 (11), pp. 2–12.
10. Linkin M.E., Nigam S. The North Pacific Oscillation – West Pacific Teleconnection Pattern: Mature – Phase Structure and Winter Impacts. Journal of Climate, 2008, vol. 21 (9), pp. 1979–1997.
11. Mantua N., Hare S., Zhang Y., Wallace J., Francis R.A. Pacific interdecadal climate oscillation with impacts on salmon production. Bull. Amer. Meteor. Soc., 1997, № 78, pp. 1069–1079.
12. Mantua N.J., Hare S.R. The Pacific Decadal Oscillation. Journal of Oceanography, 2002, vol. 58, pp. 35–44.
13. Thompson D.W.J., Wallace J.M. The Arctic Oscillation signature in the wintertime geopotential height and temperature fields. Geophysical Research Letters, 1998, № 25, pp. 1297–1300.
Review
For citations:
Feldman M.G., Bugaev A.V., Tepnin O.B. Results of using climate-oceanological predictors in a Random Forest model for the forecast of stock abundance dynamics of pink salmon runs in Western Kamchatka. The researches of the aquatic biological resources of Kamchatka and the North-West Part of the Pacific Ocean. 2022;1(65):42-51. (In Russ.) https://doi.org/10.15853/2072-8212.2022.65.42-51
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