Developing growth models for tree plantations using inadequate data – a case for Korean pine in Northeast China

Jin, Xingji; Pukkala, Timo; Li, Fengri; Liu, Dong

doi:10.14214/sf.10217

Cited by 5 publications

(3 citation statements)

References 19 publications

(34 reference statements)

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“…plantations in Heilongjiang Province were 79.7, 16.6 and 16.2 million m 3 , respectively, accounting for 33.6%, 53.6% and 61.3% of the national growing stock of these species in plantations. These conifers are the main species in northeast China in terms of economic return, timber supply and cone production (Jin et al 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Despite the importance of L. olgensis, Pinus sylvestris and Pinus koraiensis in China, few diameter distribution models representing all the Heilongjiang region are available for forest management and planning. Model development has been hindered because permanent plots and silvicultural experiments were not designed for modelling purposes (Jin et al 2019). Published models are often targeted to small geographic areas, specific species and stand structures, thus limiting their wider applicability.…”

Section: Introductionmentioning

confidence: 99%

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Developing Weibull-based diameter distributions for the major coniferous species in Heilongjiang Province, China

Jin

Pukkala

et al. 2023

J. For. Res.

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Diameter distribution models play an important role in forest inventories, growth prediction, and management. The Weibull probability density function is widely used in forestry. Although a number of methods have been proposed to predict or recover the Weibull distribution, their applicability and predictive performance for the major tree species of China remain to be determined. Trees in sample plots of three even-aged coniferous species (Larix olgensis, Pinus sylvestris and Pinus koraiensis) were measured both in un-thinned and thinned stands to develop parameter prediction models for the Weibull probability density function. Ordinary least squares (OLS) and maximum likelihood regression (MLER), as well as cumulative distribution function regression (CDFR) were used, and their performance compared. The results show that MLER and CDFR were better than OLS in predicting diameter distributions of tree plantations. CDFR produced the best results in terms of fitting statistics. Based on the error statistics calculated for different age groups, CDFR was considered the most suitable method for developing prediction models for Weibull parameters in coniferous plantations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Developing Weibull-based diameter distributions for the major coniferous species in Heilongjiang Province, China

Jin

Pukkala

et al. 2023

J. For. Res.

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“…To deal with irregular measurement intervals in this research, an optimization approach originally suggested by and later used by de-Miguel et al (2014), Juma et al (2014) andJin et al (2019) among others, was used to fit the diameter increment and survival models. This method seems to overcome some of the problems related to other methods and has been shown to produce similar models and model parameters to regression analysis .…”

Section: Introductionmentioning

confidence: 99%

Individual-tree growth models for Sitka spruce (Picea sitchensis) in Iceland

Heiðarsson,

Pukkala,

Snorrason

2022

IAS

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Sitka spruce (Picea sitchensis) is one of the main tree species used in forestry in Iceland, growing well in all parts of the country. In view of the importance of Sitka spruce in Iceland, there is need for a reliable growth model that will support multifunctional forest management and planning. This study developed growth models for Sitka spruce using data from permanent sample plots established by the Icelandic Forest Service between 1970 and 2020. The measurement interval on the plots varied from 3 to 16 years. To deal with irregular measurement intervals, an optimization approach was used to recover models for annual diameter increment and survival rate. The aim was to find parameters for diameter increment and survival models that would minimize the difference between the measured and simulated diameter distributions of the plots at the end of the measurement interval (when the simulation begins from the diameter distribution at the beginning of the interval). To enable the simulation of stand development, models for dominant height development and tree height were also developed.

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