Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach

Despite the numerous studies on year-to-year variation of tree growth, the physiological mechanisms controlling annual variation in growth are still not understood in detail. We studied the applicability of data-driven approach i.e. different regression models in analysing high-dimensiona...

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Main Authors: Kulmala, Liisa, Žliobaitė, Indre, Nikinmaa, Eero, Nöjd, Pekka, Kolari, Pasi, Kabiri Koupaei, Kourosh, Hollmén, Jaakko, Mäkinen, Harri
Format: Article
Language:English
Published: Finnish Society of Forest Science 2016-01-01
Series:Silva Fennica
Online Access:https://www.silvafennica.fi/article/1680
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spelling doaj-300c53391c674da0b6b723c76f986c102020-11-25T02:36:17ZengFinnish Society of Forest ScienceSilva Fennica2242-40752016-01-0150510.14214/sf.1680Environmental control of growth variation in a boreal Scots pine stand – a data-driven approachKulmala, LiisaŽliobaitė, IndreNikinmaa, EeroNöjd, PekkaKolari, PasiKabiri Koupaei, KouroshHollmén, JaakkoMäkinen, Harri Despite the numerous studies on year-to-year variation of tree growth, the physiological mechanisms controlling annual variation in growth are still not understood in detail. We studied the applicability of data-driven approach i.e. different regression models in analysing high-dimensional data set including continuous and comprehensive measurements over meteorology, ecosystem-scale water and carbon fluxes and the annual variation in the growth of app. 50-year-old Scots pine stand in southern Finland. Even though our dataset covered only 16 years, it is the most extensive collection of interactions between a Scots pine ecosystem and atmosphere. The analysis revealed that height growth was favoured by high water potential of the tree and carbon gain during the bud forming period and high water potential during the elongation period. Diameter growth seemed to be favoured by a winter with high precipitation and deep snow cover and a spring with high carbon gain. The obtained models had low generalization performance and they would require more evaluation and iterative validation to achieve credibility perhaps as a mixture of data-driven and first principle modeling approaches.https://www.silvafennica.fi/article/1680
collection DOAJ
language English
format Article
sources DOAJ
author Kulmala, Liisa
Žliobaitė, Indre
Nikinmaa, Eero
Nöjd, Pekka
Kolari, Pasi
Kabiri Koupaei, Kourosh
Hollmén, Jaakko
Mäkinen, Harri
spellingShingle Kulmala, Liisa
Žliobaitė, Indre
Nikinmaa, Eero
Nöjd, Pekka
Kolari, Pasi
Kabiri Koupaei, Kourosh
Hollmén, Jaakko
Mäkinen, Harri
Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach
Silva Fennica
author_facet Kulmala, Liisa
Žliobaitė, Indre
Nikinmaa, Eero
Nöjd, Pekka
Kolari, Pasi
Kabiri Koupaei, Kourosh
Hollmén, Jaakko
Mäkinen, Harri
author_sort Kulmala, Liisa
title Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach
title_short Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach
title_full Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach
title_fullStr Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach
title_full_unstemmed Environmental control of growth variation in a boreal Scots pine stand – a data-driven approach
title_sort environmental control of growth variation in a boreal scots pine stand – a data-driven approach
publisher Finnish Society of Forest Science
series Silva Fennica
issn 2242-4075
publishDate 2016-01-01
description Despite the numerous studies on year-to-year variation of tree growth, the physiological mechanisms controlling annual variation in growth are still not understood in detail. We studied the applicability of data-driven approach i.e. different regression models in analysing high-dimensional data set including continuous and comprehensive measurements over meteorology, ecosystem-scale water and carbon fluxes and the annual variation in the growth of app. 50-year-old Scots pine stand in southern Finland. Even though our dataset covered only 16 years, it is the most extensive collection of interactions between a Scots pine ecosystem and atmosphere. The analysis revealed that height growth was favoured by high water potential of the tree and carbon gain during the bud forming period and high water potential during the elongation period. Diameter growth seemed to be favoured by a winter with high precipitation and deep snow cover and a spring with high carbon gain. The obtained models had low generalization performance and they would require more evaluation and iterative validation to achieve credibility perhaps as a mixture of data-driven and first principle modeling approaches.
url https://www.silvafennica.fi/article/1680
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