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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">tinro</journal-id><journal-title-group><journal-title xml:lang="ru">Известия ТИНРО</journal-title><trans-title-group xml:lang="en"><trans-title>Izvestiya TINRO</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1606-9919</issn><issn pub-type="epub">2658-5510</issn><publisher><publisher-name>ТИНРО</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26428/1606-9919-2024-204-722-744</article-id><article-id custom-type="edn" pub-id-type="custom">RQTAGT</article-id><article-id custom-type="elpub" pub-id-type="custom">tinro-986</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>МЕТОДИКА ИССЛЕДОВАНИЙ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>METHODS OF INVESTIGATIONS</subject></subj-group></article-categories><title-group><article-title>Векторные авторегрессионные пространственно-временные (VAST) модели распределения биомассы трески Gadus macrocephalus (Gadidae) с учетом придонной температуры воды в Западно-Беринговоморской зоне</article-title><trans-title-group xml:lang="en"><trans-title>Vector Autoregressive Spatio-Temporal (VAST) models for biomass distribution of pacific cod Gadus macrocephalus (Gadidae) considering water temperature at the sea bottom in the West Bering Sea zone</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0920-5312</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кулик</surname><given-names>В. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Kulik</surname><given-names>V. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кулик Владимир Владимирович, кандидат биологических наук, заведующий лабораторией</p><p>690091, г. Владивосток, пер. Шевченко, 4</p></bio><bio xml:lang="en"><p>Vladimir V. Kulik, Ph.D., head of laboratory</p><p>4, Shevchenko Alley, Vladivostok, 690091</p><p> </p></bio><email xlink:type="simple">vladimir.kulik@tinro.vniro.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0003-5910-6512</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Савин</surname><given-names>А. Б.</given-names></name><name name-style="western" xml:lang="en"><surname>Savin</surname><given-names>A. B.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Савин Андрей Борисович, кандидат биологических наук, ведущий научный сотрудник</p><p>690091, г. Владивосток, пер. Шевченко, 4</p></bio><bio xml:lang="en"><p>Andrey B. Savin, Ph.D., leading researcher</p><p>4, Shevchenko Alley, Vladivostok, 690091</p></bio><email xlink:type="simple">andrey.savin@tinro.vniro.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Тихоокеанский филиал ВНИРО (ТИНРО)</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Pacific branch of VNIRO (TINRO)</institution><country>Russian Federation</country></aff></aff-alternatives><aff xml:lang="ru" id="aff-2"><institution>Тихоокеанский филиал ВНИРО (ТИНРО)</institution><country>Russian Federation</country></aff><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>08</day><month>10</month><year>2024</year></pub-date><volume>204</volume><issue>3</issue><fpage>722</fpage><lpage>744</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Кулик В.В., Савин А.Б., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Кулик В.В., Савин А.Б.</copyright-holder><copyright-holder xml:lang="en">Kulik V.V., Savin A.B.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://izvestiya.tinro-center.ru/jour/article/view/986">https://izvestiya.tinro-center.ru/jour/article/view/986</self-uri><abstract><p>На основе материалов донных тралений с 1977 по 2021 г., проведённых до глубины 400 м, показана высокая статистическая значимость придонной температуры воды T и глубины места D для моделирования распределения биомассы трески в Западно-Беринговоморской зоне во всех проверенных моделях. Наилучшей обобщающей способностью обладали векторные авторегрессионные пространственно-временные (VAST) модели, включающие нелинейные зависимости уловов трески от T и D. Корреляция плотностей трески в тестовом наборе данных с оценками плотностей в моделях VAST была выше, чем таковая с оценками биомасс из более простых моделей, настроенных на полном наборе данных. Использование моделей VAST позволяет получить непрерывные временные ряды биомассы трески с оценкой их неопределенности и статистических весов самих моделей относительно тестовых данных. Полученный усредненный ряд динамики биомассы ансамблевым методом с учетом статистических весов моделей совместно с ранее опубликованными оценками биомасс позволяют установить в обобщенной модели прибавочной продукции в пространстве состояний с Байесовым подходом динамику отклонений биологических процессов от стационарных допущений и приблизительно оценить объем трески, не учитываемый этими процессами. Доля такой трески резко выросла в 2016 г. до 40 % и к 2018 г. достигла максимума в 49 %, что значительно отклоняется от стационарных допущений, но затем эта доля начала снижаться. Анализ годовых тенденций из эмпирических ортогональных функций T выявил резкие изменения основных мод T в эти годы. Таким образом, неоднократно высказанная гипотеза о перераспределении трески Берингова моря из-за изменения площади акватории с низкой температурой воды у дна здесь впервые проверена статистическими методами в пространстве. В связи с найденной высокой ошибкой биологических процессов сделан вывод о невозможности точного прогнозирования динамики биомассы трески без прогнозирования распределения придонной температуры воды в пространстве.</p></abstract><trans-abstract xml:lang="en"><p>High statistical significance of water temperature at the sea bottom T and depth D for distribution of pacific cod in the West Bering Sea fishing zone is found in several tested models tuned on the data of bottom trawl surveys conducted in the period between 1977 and 2021 not deeper than 400 m. The vector autoregressive spatio-temporal (VAST) models which included nonlinear dependencies of cod catches from T and D have the best generalization ability. Correlation between predicted by VAST models and observed distribution density of cod in the test data set are higher than that in simpler models trained using the full set of data. The VAST models produce continuous time series of cod biomass with estimates of their uncertainty and statistical weights of the model configurations relative to the test data. After stacking with statistical weights and previously published estimates of biomass, the obtained time series allow to estimate dynamics of biological processes deviations from stationary assumptions and to estimate approximately the volume of “extra” cod not considered by these processes in the Bayesian State-Space Surplus Production Model. The portion of “extra” cod increased sharply above 40 % in 2016 and reached the maximum of 49 % by 2018, then began to decrease. Sharp changes in the main EOF modes for T are revealed in these years. Thus, the hypothesis of cod redistribution in the Bering Sea due to changes of the cold pool area at the bottom was tested for the first time by statistical methods in space. Due to high errors of forecasts based on analysis of biological processes only, there is impossible to predict accurately dynamics of the cod biomass without predicting the water temperature distribution at the bottom of shelf.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>Берингово море</kwd><kwd>треска</kwd><kwd>GLM</kwd><kwd>GLMM</kwd><kwd>GAM</kwd><kwd>GAMM</kwd><kwd>VAST</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Bering Sea</kwd><kwd>pacific cod</kwd><kwd>statistical models (GLM</kwd><kwd>GLMM</kwd><kwd>GAM</kwd><kwd>GAMM</kwd><kwd>VAST)</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование не имело спонсорской поддержки.</funding-statement><funding-statement xml:lang="en">The study was not sponsored.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Аксютина З.М. 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