Puude hooajalise radiaalkasvu mõõtmiskuupäevaks moodustunud osa arvutusmudel Eesti tingimuste jaoks

Q4 Agricultural and Biological Sciences
Andres Kiviste, Allar Padari, Sandra Metslaid
{"title":"Puude hooajalise radiaalkasvu mõõtmiskuupäevaks moodustunud osa arvutusmudel Eesti tingimuste jaoks","authors":"Andres Kiviste, Allar Padari, Sandra Metslaid","doi":"10.2478/fsmu-2022-0014","DOIUrl":null,"url":null,"abstract":"Abstract Knowledge about the seasonal dynamics of tree growth and its relationship with environmental factors is necessary to eliminate the uncertainty due to ongoing climate change and for more precise growth modelling when re-measurements are done periodically. Despite the increasing number of studies monitoring seasonal wood formation, a considerable part of European forests, including Estonia, lacks such information. In this article, we present a date-dependent model for determining the share of seasonal radial growth for the three most common tree species in the region (Scots pine, Norway spruce and silver birch) for Estonian conditions. Since seasonal tree growth monitoring data were unavailable for Estonia, we used published seasonal radial growth data from Lithuania by Dr Adomas Vitas (2011). We tested four functions (Kumaraswamy, Weibull, Gompertz and logistic) on obtained data to approximate the seasonal development of radial growth. Kumaraswamy’s function could track the course of seasonal radial growth gains the best; thus, this function was chosen for further use. We obtained data on intra-annual radial growth from published research studies from neighbouring countries and determined the dates of growth initiation and cessation for Estonian conditions. Finally, we combined Kumaraswamy’s function and the predicted radial growth onset and cessation dates into the model that could predict the seasonal growth course and thus were able to estimate the share of newly formed increment from the dates.","PeriodicalId":35353,"journal":{"name":"Forestry Studies","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forestry Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/fsmu-2022-0014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract Knowledge about the seasonal dynamics of tree growth and its relationship with environmental factors is necessary to eliminate the uncertainty due to ongoing climate change and for more precise growth modelling when re-measurements are done periodically. Despite the increasing number of studies monitoring seasonal wood formation, a considerable part of European forests, including Estonia, lacks such information. In this article, we present a date-dependent model for determining the share of seasonal radial growth for the three most common tree species in the region (Scots pine, Norway spruce and silver birch) for Estonian conditions. Since seasonal tree growth monitoring data were unavailable for Estonia, we used published seasonal radial growth data from Lithuania by Dr Adomas Vitas (2011). We tested four functions (Kumaraswamy, Weibull, Gompertz and logistic) on obtained data to approximate the seasonal development of radial growth. Kumaraswamy’s function could track the course of seasonal radial growth gains the best; thus, this function was chosen for further use. We obtained data on intra-annual radial growth from published research studies from neighbouring countries and determined the dates of growth initiation and cessation for Estonian conditions. Finally, we combined Kumaraswamy’s function and the predicted radial growth onset and cessation dates into the model that could predict the seasonal growth course and thus were able to estimate the share of newly formed increment from the dates.
了解树木生长的季节动态及其与环境因子的关系对于消除持续气候变化带来的不确定性以及在定期重新测量时建立更精确的生长模型是必要的。尽管监测季节性木材形成的研究越来越多,但包括爱沙尼亚在内的相当一部分欧洲森林缺乏这种资料。在本文中,我们提出了一个日期依赖模型,用于确定爱沙尼亚条件下该地区三种最常见树种(苏格兰松、挪威云杉和银桦树)季节性径向生长的份额。由于无法获得爱沙尼亚的季节性树木生长监测数据,我们使用了Adomas Vitas博士(2011年)在立陶宛发表的季节性径向生长数据。我们对获得的数据测试了四种函数(Kumaraswamy, Weibull, Gompertz和logistic),以近似径向生长的季节性发展。Kumaraswamy函数对季节性径向生长过程的跟踪效果最好;因此,选择这个函数作进一步使用。我们从邻国发表的研究中获得了年内径向生长的数据,并确定了爱沙尼亚条件下生长开始和停止的日期。最后,我们将Kumaraswamy函数与预测的径向生长开始和停止日期结合到模型中,该模型可以预测季节生长过程,从而能够从日期中估计新形成的增量份额。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Forestry Studies
Forestry Studies Agricultural and Biological Sciences-Forestry
CiteScore
0.70
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信