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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">vestib</journal-id><journal-title-group><journal-title xml:lang="ru">Известия Национальной  академии наук Беларуси. Серия биологических наук</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of the National Academy of Sciences of Belarus, Biological Series</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1029-8940</issn><issn pub-type="epub">2524-230X</issn><publisher><publisher-name>The Republican Unitary Enterprise Publishing House "Belaruskaya Navuka"</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.29235/1029-8940-2026-71-4-315-331</article-id><article-id custom-type="elpub" pub-id-type="custom">vestib-1034</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>Статьи</subject></subj-group></article-categories><title-group><article-title>Динамика усыхания и устойчивость лесных насаждений к климатическому стрессу: дистанционный мониторинг с применением алгоритмов машинного обучения</article-title><trans-title-group xml:lang="en"><trans-title>Forest loss dynamics and resilience to climate stress: a machine learning approach using remote sensing data</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Роговский</surname><given-names>Н. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Rogovsky</surname><given-names>N. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Роговский Никита Михайлович – мл. науч. сотрудник, аспирант</p><p>ул. Академическая, 27, 220072, г. Минск</p></bio><bio xml:lang="en"><p>Nikita M. Rogovsky – Junior Researcher, Postgraduate Student</p><p>27, Akademicheskaya Str., 220072, Minsk</p></bio><email xlink:type="simple">nikita.rogovski.03@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Груммо</surname><given-names>Д. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Grummo</surname><given-names>D. G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Груммо Дмитрий Геннадьевич – д-р биол. наук, доцент, директор</p><p>ул. Академическая, 27, 220072, г. Минск</p></bio><bio xml:lang="en"><p>Dzmitry G. Grummo – D. Sc. (Biol.), Associate Professor, Director</p><p>27, Akademicheskaya Str., 220072, Minsk</p></bio><email xlink:type="simple">dm.grumo@botany.by</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Институт экспериментальной ботаники имени В. Ф. Купревича Национальной академии наук Беларуси</institution><country>Беларусь</country></aff><aff xml:lang="en"><institution>V. F. Kuprevich Institute of Experimental Botany of the National Academy of Sciences of Belarus</institution><country>Belarus</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>11</day><month>11</month><year>2026</year></pub-date><volume>71</volume><issue>4</issue><fpage>315</fpage><lpage>331</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Роговский Н.М., Груммо Д.Г., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Роговский Н.М., Груммо Д.Г.</copyright-holder><copyright-holder xml:lang="en">Rogovsky N.M., Grummo D.G.</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://vestibio.belnauka.by/jour/article/view/1034">https://vestibio.belnauka.by/jour/article/view/1034</self-uri><abstract><p>Представлен комплексный подход к выявлению и пространственно-временной оценке гибели лесов модельных территорий – Национального парка (НП) «Беловежская пуща» и Полесского государственного радиационно-экологического заповедника (ПГРЭЗ). С применением алгоритма Random Forest для классификации снимков Landsat-5/7/8/9 и Sentinel-2 определены площади погибших насаждений за 2001–2025 гг. В НП «Беловежская пуща» процессы гибели лесов имели распространение на 14,9 тыс. га с пиковым периодом в 2016–2018 гг., в ПГРЭЗ – на 16,4 тыс. га с максимумами в 2003–2006, 2011–2013 и 2016–2018 гг. Наиболее сильную корреляционную связь с масштабом гибели лесов показали взвешенные скользящие средние индекса засухи KBDI с лагом 1 год за 2001–2019 гг. (до 0,68 – в НП «Беловежская пуща» и 0,78 – в ПГРЭЗ). В разрезе экологических групп лесов (ЭГЛ) наименее устойчивыми в НП «Беловежская пуща» оказались леса на бедных песчаных почвах недостаточного (гибель на 27,5 % площади ЭГЛ) и неустойчивого (17,9 %) увлажнения , прежде всего сосновые (до 27,4 %), еловые (до 18,3 %) и березовые (до 49,9 %). В ПГРЭЗ наиболее подверженными к гибели являлись сосновые леса на бедных песчаных почвах недостаточного (28,8 %) и неустойчивого (19,2 %) увлажнения . Выявленные закономерности климатической обусловленности масштабов гибели лесов и степень их устойчивости в разрезе ЭГЛ легли в основу подхода к ежегодному прогнозу потенциала развития лесопатологических процессов.</p></abstract><trans-abstract xml:lang="en"><p>The article presents an integrated approach to identifying and spatiotemporally assessing forest loss in the Belovezhskaya Pushcha National Park (NP) and the Polessky State Radioecological Reserve (PSRR). For the period 2001–2025, the Random Forest algorithm identified forest loss in the Belovezhskaya Pushcha NP over more than 14.9 kha with a peak period in 2016–2018, and in the PSRR over an area of 16.4 kha with maximums in 2003–2006, 2011–2013, and 2016–2018. A correlation analysis of annual forest loss values and drought climate indices revealed that the KBDI drought index with a one-year time lag for 2001–2019 had the strongest correlation (up to 0.68 in the Belovezhskaya Pushcha NP and 0.78 in the PSRR). The least resilient forests were those on poor sandy soils with insufficient moisture (27.5 % of the forest ecological group, FEG, area lost) and unstable moisture (17.9 %), in particular pine (up to 27.4 %), spruce (up to 18.3 %) and birch (up to 49.9 %). In the PSRR, the least resilient were pine forests on poor sandy soils with insufficient (28.8 % of the FEG area) and unstable moisture (19.2 %). Based on the identified ecological and climatic patterns of forest loss development, an approach to annual forecasting of the potential for forest pathological processes has been developed.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>лесные экосистемы</kwd><kwd>заповедные территории</kwd><kwd>гибель лесов</kwd><kwd>изменение климата</kwd><kwd>дистанционное зондирование растительности</kwd><kwd>машинное обучение</kwd><kwd>климатические индексы</kwd></kwd-group><kwd-group xml:lang="en"><kwd>forest ecosystems</kwd><kwd>protected areas</kwd><kwd>forest loss</kwd><kwd>climate change</kwd><kwd>remote sensing of vegetation</kwd><kwd>machine learning</kwd><kwd>climate indices</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Гниненко, Ю. И. Проблема усыхания сосняков и роль вершинного короеда в этом процессе / Ю. И. Гниненко, Н. И. 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