A stochastic-statistical approach in long-term forecasting of the national catch
https://doi.org/10.46845/1997-3071-2022-64-36-50
Abstract
Practical activities of research institutes of the Federal Agency for Fishery and other research organizations often involves the necessity to prepare forecasts of a possible national catch for extended time-periods. Different institutions require these forecasts for their business planning and other activities. Generally, accuracy of these deterministic forecasts is low. Moreover, catches of some commercial species are determined by not only biological parameters, but also management decisions that may result in unpredictable consequences. This paper considers the possibility to prepare a long-term forecast of the national catches of commercial species, which depends not only on the state of stocks, but also on economic and political factors. This forecast involves a stochastic-statistical approach that is based on a long-term series of observations over fisheries taking into account some patterns and assumptions. The paper includes analysis of some possible factors that can have a direct impact on sizes of catches and the relation between them. Modelling is based on the Monte-Carlo method and is performed using software designed to assess possible risks when input parameters are uncertain. The result is the most likely scenario for the development of fisheries, indicating the range of forecast uncertainty. As a test example, a long-term forecast for the Russian catch of NA blue whiting (Micromesistius poutassou) up to 2042 was made. For this fish species, the Russian catch sizes may comprise at least 86 000 tons in the long-term. Similar assessments can be made for other commercial species.
About the Author
D. V. Prozorkevich
Polar Branch of FSBSI “VNIRO” (“PINRO” named after N. M. Knipovich)
Russian Federation
Russian Federation
Prozorkevich Dmitry Vladimirovich, PhD in Biology; leading researcher
Murmansk
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For citations:
Prozorkevich D.V. A stochastic-statistical approach in long-term forecasting of the national catch. KSTU News. 2022;(64):36-50. (In Russ.) https://doi.org/10.46845/1997-3071-2022-64-36-50
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