Species composition and community structure of a typical mixed broad-leaved-Korean pine (Pinus koraiensis) forest plot in Liangshui Nature Reserve, Northeast China

2013 ◽  
Vol 20 (4) ◽  
pp. 470-481 ◽  
Author(s):  
Xu Lina ◽  
Jin Guangze
Keyword(s):  
Community Structure ◽  
Species Composition ◽  
Northeast China ◽  
Nature Reserve ◽  
Pinus Koraiensis ◽  
Forest Plot ◽  
Korean Pine

scholarly journals Height-diameter relationship for Pinus koraiensis in Mengjiagang Forest Farm of Northeast China using nonlinear regressions and artificial neural network models

2019 ◽  
Vol 65 (No. 4) ◽  
pp. 134-143 ◽  
Author(s):  
Tuan Nguyen Thanh ◽  
Tai Dinh Tien ◽  
Hai Long Shen
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Northeast China ◽  
Tree Height ◽  
Pinus Koraiensis ◽  
Accurate Estimation ◽  
Korean Pine ◽  
Ann Models ◽  
Artificial Neural ◽  
Forest Farm

Korean pine (Pinus koraiensis Sieb. et Zucc.) is one of the highly commercial woody species in Northeast China. In this study, six nonlinear equations and artificial neural network (ANN) models were employed to model and validate height-diameter (H-DBH) relationship in three different stand densities of one Korean pine plantation. Data were collected in 12 plots in a 43-year-old even-aged stand of P. koraiensis in Mengjiagang Forest Farm, China. The data were randomly split into two datasets for model development (9 plots) and for model validation (3 plots). All candidate models showed a good perfomance in explaining H-DBH relationship with error estimation of tree height ranging from 0.61 to 1.52 m. Especially, ANN models could reduce the root mean square error (RMSE) by the highest 40%, compared with Power function for the density level of 600 trees. In general, our results showed that ANN models were superior to other six nonlinear models. The H-DBH relationship appeared to differ between stand density levels, thus it is necessary to establish H-DBH models for specific stand densities to provide more accurate estimation of tree height.

scholarly journals Height Growth of Korean Pine Seedlings Planted under Strip-Cut Larch Plantations in Northeast China

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Toshiaki Owari ◽  
Shinichi Tatsumi ◽  
Liangzhi Ning ◽  
Mingfang Yin
Keyword(s):  
Northeast China ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Height Growth ◽  
Pinus Koraiensis ◽  
Stand Age ◽  
Seedling Height ◽  
Korean Pine ◽  
Open Site ◽  
Pine Seedlings

To develop two-storied forest management of larch plantations in Northeast China, this study examined the height growth of Korean pine (Pinus koraiensisSieb. et Zucc.) seedlings planted under strip-cut larch canopies. We measured the height growth of the underplanted seedlings 4 years after planting. The larch canopies were of varying stand age (12, 17, and 37 years) and strip-cut width (4.5, 6.0, and 7.5 m). We measured the seedling height growth in an open site (i.e., a site with no canopy). Underplanted seedlings had a smaller height growth (12.1–20.1 cm year−1) than the seedlings planted in the open site (23.7 cm year−1). The seedlings underplanted in the wider strip-cuts tended to have greater height growth than the seedlings underplanted in the narrowest strip-cuts. A generalized linear mixed model analysis predicted the greatest seedling height growth in the open site. A 36–47% reduction in annual height growth was predicted for the narrowest strip-cuts (4.5 m) versus the open site, while a 13–36% reduction in annual height growth was predicted for the wider strip-cuts (6.0–7.5 m) versus the open site. To maintain adequate height growth, forest managers are recommended to create wider strip-cuts (i.e., ≥6.0 m) for the purpose of underplanting Korean pine seedlings in larch plantations.

scholarly journals Effects of Topography on Tree Community Structure in a Deciduous Broad-Leaved Forest in North-Central China

Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 53 ◽  
Author(s):  
Hang Shi ◽  
Fenglin Xie ◽  
Quan Zhou ◽  
Xiao Shu ◽  
Kerong Zhang ◽  
...  
Keyword(s):  
Community Structure ◽  
Species Composition ◽  
Dispersal Limitation ◽  
Habitat Associations ◽  
Central China ◽  
Forest Plot ◽  
North Central ◽  
Spatial Factors ◽  
Broad Leaved Forest ◽  
Leaved Forest

Topography strongly influences the compositional structure of tree communities and plays a fundamental role in classifying habitats. Here, data of topography and 16 dominant tree species abundance were collected in a fully mapped 25-ha forest plot in the Qinling Mountains of north-central China. Multivariate regression trees (MRT) were used to categorize the habitats, and habitat associations were examined using the torus-translation test. The relative contributions of topographic and spatial variables to the total community structure were also examined by variation partitioning. The results showed the inconsistency in association of species with habitats across life stages with a few exceptions. Topographic variables [a + b] explained 11% and 19% of total variance at adult and juvenile stage, respectively. In contrast, spatial factors alone [c] explained more variation than topographic factors, revealing strong seed dispersal limitation in species composition in the 25-ha forest plot. Thus, the inconsistent associations of species and habitats coupled with high portion of variation of species composition explained by topographic and spatial factors might suggest that niche process and dispersal limitation had potential influences on species assemblage in the deciduous broad-leaved forest in north-central China.

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

Silva Fennica ◽  
2019 ◽  
Vol 53 (4) ◽  
Author(s):  
Xingji Jin ◽  
Timo Pukkala ◽  
Fengri Li ◽  
Lihu Dong
Keyword(s):  
Northeast China ◽  
Growth Models ◽  
Pinus Koraiensis ◽  
Tree Plantations ◽  
Korean Pine

Pinus koraiensis

Sign in / Sign up

Export Citation Format

Share Document