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 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">Forestry Engineering Journal</journal-id>
   <journal-title-group>
    <journal-title xml:lang="en">Forestry Engineering Journal</journal-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Лесотехнический журнал</trans-title>
    </trans-title-group>
   </journal-title-group>
   <issn publication-format="print">2222-7962</issn>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="publisher-id">90633</article-id>
   <article-id pub-id-type="doi">10.34220/issn.2222-7962/2024.3/8</article-id>
   <article-categories>
    <subj-group subj-group-type="toc-heading" xml:lang="ru">
     <subject>Природопользование</subject>
    </subj-group>
    <subj-group subj-group-type="toc-heading" xml:lang="en">
     <subject>Nature Management</subject>
    </subj-group>
    <subj-group>
     <subject>Природопользование</subject>
    </subj-group>
   </article-categories>
   <title-group>
    <article-title xml:lang="en">Dynamic model of the growth and yield of pine stands (Pinus sylvestris L.) in the Unzhensky Lowland</article-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Динамическая модель роста и производительности сосновых древостоев (Pinus sylvestris L.) Унженской низменности</trans-title>
    </trans-title-group>
   </title-group>
   <contrib-group content-type="authors">
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Лебедев</surname>
       <given-names>Александр Вячеславович</given-names>
      </name>
      <name xml:lang="en">
       <surname>Lebedev</surname>
       <given-names>Aleksandr Vyacheslavovich</given-names>
      </name>
     </name-alternatives>
     <email>alebedev@rgau-msha.ru</email>
     <bio xml:lang="ru">
      <p>кандидат сельскохозяйственных наук;</p>
     </bio>
     <bio xml:lang="en">
      <p>candidate of agricultural sciences;</p>
     </bio>
     <xref ref-type="aff" rid="aff-1"/>
    </contrib>
   </contrib-group>
   <aff-alternatives id="aff-1">
    <aff>
     <institution xml:lang="ru">Российский государственный аграрный университет,  Московская сельскохозяйственная академия имени К.А. Тимирязева</institution>
    </aff>
    <aff>
     <institution xml:lang="en">Russian State Agrarian University - Moscow Timiryazev Agricultural Academy</institution>
    </aff>
   </aff-alternatives>
   <pub-date publication-format="print" date-type="pub" iso-8601-date="2025-05-12T14:17:26+03:00">
    <day>12</day>
    <month>05</month>
    <year>2025</year>
   </pub-date>
   <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-05-12T14:17:26+03:00">
    <day>12</day>
    <month>05</month>
    <year>2025</year>
   </pub-date>
   <volume>14</volume>
   <issue>3</issue>
   <fpage>127</fpage>
   <lpage>151</lpage>
   <history>
    <date date-type="received" iso-8601-date="2024-06-18T00:00:00+03:00">
     <day>18</day>
     <month>06</month>
     <year>2024</year>
    </date>
    <date date-type="accepted" iso-8601-date="2024-08-14T00:00:00+03:00">
     <day>14</day>
     <month>08</month>
     <year>2024</year>
    </date>
   </history>
   <self-uri xlink:href="http://lestehjournal.ru/en/journal/2024/no-3-55/dynamic-model-growth-and-yield-pine-stands-pinus-sylvestris-l-unzhensky-lowland">http://lestehjournal.ru/en/journal/2024/no-3-55/dynamic-model-growth-and-yield-pine-stands-pinus-sylvestris-l-unzhensky-lowland</self-uri>
   <abstract xml:lang="ru">
    <p>Сосна обыкновенная относится к главным лесообразующим породам Костромской области, поэтому необходимо иметь инструменты, позволяющие принимать обоснованные решения по управлению процессом лесовыращивания, планированию лесопользования, проектированию лесохозяйственных мероприятий и повышению эффективности выполнения древостоями экологических функций. Цель исследования – разработка динамической модели роста и производительности сосновых древостоев Унженской низменности (Костромская область) с использованием данных повторных наблюдений на постоянных пробных площадях. Материалами для исследования являлись данные повторных учетов на 21 постоянной пробной площади Чернолуховского опытного лесхоза и 3 постоянных пробных площадях Мантуровского участка государственного заповедника «Кологривский лес». Для моделирования роста по средней высоте и среднему диаметру проанализировано 15 динамических уравнений, а для моделирования изреживания древостоев – 14 уравнений. Полученные регрессионные уравнения для прогнозирования динамики средних высот и диаметров, естественного изреживания в совокупности формируют модель роста и производительности сосновых древостоев, которая относится к категории эмпирических моделей прогнозирования таксационных характеристик на уровне отдельного древостоя, а ее преимуществами являются инвариантность относительного базового возраста и возможность давать прогнозы в широком диапазоне значений начальных параметров. Разработанная модель может служить альтернативой традиционным таблицам хода роста при проектировании и обосновании лесохозяйственных мероприятий, при таксации лесов методом актуализации, а также для принятия управленческих решений при ведении хозяйства в сосновых лесах. В сочетании с дополнительными уравнениями может входить в состав более сложных моделей, позволяющих прогнозировать структуру древостоев, товарный и углерододепонирующий потенциал, воздействие лесохозяйственных мероприятий.</p>
   </abstract>
   <trans-abstract xml:lang="en">
    <p>Scots pine is one of the main forest-forming species in the Kostroma region, therefore it is necessary to have tools that allow one to make informed decisions on managing the forest growing process, planning forest management, designing forest management activities and increasing the efficiency of forest stands performing environmental functions. The purpose of the study is to develop a dynamic model of growth and yield of pine stands in the Unzhensky Lowland (Kostroma region) based on repeated observations on permanent trial plots. The data for modeling the growth and yield of pine stands were materials from repeated censuses on 21 permanent trial plots of the Chernolukhovsky experimental forestry enterprise and 3 permanent trial plots of the Manturovo section of the Kologrivsky Forest Nature Reserve. To model growth by average height and average diameter, 15 dynamic equations based on 9 basic functions were analyzed, and to model thinning of forest stands, 14 dynamic equations were analyzed. The resulting regression equations for predicting the dynamics of average heights and diameters, thinning together form a model of growth and yield of pine forest stands, which belongs to the category of empirical models for predicting stand characteristics at the level of an individual forest stand, and its advantages are the invariance of the relative base age and the ability to give forecasts over a wide range of initial parameter values. The developed model can serve as an alternative to traditional tables of course of growth when designing and justifying forestry activities, when forests inventory using the updating method, as well as for making management decisions when managing pine forests. In combination with additional equations, it can be part of more complex models that allow predicting the structure of forest stands, commercial and carbon sequestration potential, and the impact of forestry activities.</p>
   </trans-abstract>
   <kwd-group xml:lang="ru">
    <kwd>сосна обыкновенная</kwd>
    <kwd>Pinus sylvestris L.</kwd>
    <kwd>модель роста древостоев</kwd>
    <kwd>повторные наблюдения</kwd>
    <kwd>постоянная пробная площадь</kwd>
   </kwd-group>
   <kwd-group xml:lang="en">
    <kwd>Scots pine</kwd>
    <kwd>Pinus sylvestris L.</kwd>
    <kwd>forest stand growth model</kwd>
    <kwd>repeated observations</kwd>
    <kwd>permanent trial plot</kwd>
   </kwd-group>
   <funding-group>
    <funding-statement xml:lang="ru">исследование выполнено за счет гранта Российского научного фонда № 23-76-01016, https://rscf.ru/project/23-76-01016/.</funding-statement>
    <funding-statement xml:lang="en">this study has been supported by the grants the Russian Science Foundation, RSF 23-76-01016, https://rscf.ru/en/project/23-76-01016/.</funding-statement>
   </funding-group>
  </article-meta>
 </front>
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