On predicting sockeye salmon Oncorhynchus nerka runs in the Ozernaya River (Western Kamchatka) based on cohort analysis methodology
https://doi.org/10.15853/2072-8212.2025.76.57-69
EDN: QZCFNY
Abstract
One of possible approaches to modeling sockeye salmon age structure dynamics in the Ozernaya River (Western Kamchatka) is analyzed. The model discussed is a kind of statistical cohort model for mentioned stock unit. Using the abundance of juvenile escapement and the data on the age structure of spawners in the catches and in spawning grounds it allows under given conditions to obtain retrospective abundances for all age groups of sockeye salmon, to evaluate mature stock and to make probabilistic forecast for sockeye salmon run in the Ozernaya River for a short-term feature period (1–2 years).
About the Authors
O. I. Ilyin
Kamchatka Branch of Russian Federal Research Institute of Fisheries and Oceanography
Russian Federation
Russian Federation
Oleg I. Ilyin – Ph. D. (Physics and Mathematics), Leading Researcher
Petropavlovsk-Kamchatsky
A. V. Bugaev
Kamchatka Branch of Russian Federal Research Institute of Fisheries and Oceanography
Russian Federation
Russian Federation
Alexandr V. Bugaev – D. Sc. (Biology), Deputy Head
Petropavlovsk-Kamchatsky
V. A. Dubynin
Kamchatka Branch of Russian Federal Research Institute of Fisheries and Oceanography
Russian Federation
Russian Federation
Vladimir A. Dubynin – Principal Specialist
Petropavlovsk-Kamchatsky
O. V. Zikunova
Kamchatka Branch of Russian Federal Research Institute of Fisheries and Oceanography
Russian Federation
Russian Federation
Olga V. Zikunova – Ph. D. (Biology), Head of the Lab. of Salmonid Fishes
Petropavlovsk-Kamchatsky
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Review
For citations:
Ilyin O.I., Bugaev A.V., Dubynin V.A., Zikunova O.V. On predicting sockeye salmon Oncorhynchus nerka runs in the Ozernaya River (Western Kamchatka) based on cohort analysis methodology. The researches of the aquatic biological resources of Kamchatka and the North-West Part of the Pacific Ocean. 2025;(76):57-69. (In Russ.) https://doi.org/10.15853/2072-8212.2025.76.57-69. EDN: QZCFNY
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