Guoping Chen, Cong Shi, Shanshan Cheng, Tiejian Zhao, Guoquan Liu, Fuchen Shi. (2017). The structure and soil characteristics of a Pinus tabuliformis planted forest after 60 years of natural development in North China. Silva Fennica vol. 51 no. 1 article id 1709. https://doi.org/10.14214/sf.1709

Keywords: species diversity; Chinese pine; plantation forest; mixed species stands; soil chemical properties; soil microbial community

Highlights: Increasing proportions of broadleaf tree species was shown to affect nutrient content of the forest floor and soil, and the soil microbial community in the process of natural development of Pinus tabuliformis planted forest. In this regard, this study can act as a reference for management of the near-natural transformation of P. tabuliformis planted forests and for the choice of the tree species used.

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This study evaluated the transformation of a Pinus tabuliformis Carrière forest into a near-natural forest after 60 years of natural development. The structure and soil characteristics of P. tabuliformis planted forest, the near-natural forest (coniferous-broadleaved P. tabuliformis mixed forest), and secondary forest (Quercus mongolica Fisch. ex Ledeb. forest) were compared. Tree, shrub and herb species diversity of the mixed and Q. mongolica forests was higher than that of the planted P. tabuliformis forest. Examination of soil characteristics revealed that compared to the pure pine forest, nitrogen (N) and phosphorus (P) concentrations of the mixed and Q. mongolica forests increased in the forest floor and soil, but total carbon (C) concentration decreased in the forest floor, countered by increases in the soil. Furthermore, soil cation exchange capacity (CEC) and pH in the P. tabuliformis forest increased when deciduous broadleaved species were present. Total microbial biomass and bacterial biomass in the soils were greatest in the Q. mongolica forest, followed by the mixed, and then the P. tabuliformis forests. However, fungal biomass did not significantly differ among the three forests. Overall, the findings of this study suggest that different forest types can affect soil microbial biomass and community structure. Meanwhile, the natural development is recommended as a potential management alternative to near-natural transformation of a P. tabuliformis planted forest.

Chen, Department of Plant Biology & Ecology, College of Life Sciences, Nankai University, Weijin Road 94, Tianjin 300071, P.R. China E-mail: guopingchern@mail.nankai.edu.cn
Shi, Graduate School of Agriculture, Hokkaido University, Sapporo, Hokkaido 060-8689, Japan E-mail: cshi1@for.agr.hokudai.ac.jp
Cheng, School of Environment and Energy, Shenzhen Graduate School of Peking University, Shenzhen 518055, China E-mail: 1401213932@sz.pku.edu.cn
Zhao, Baxian Mountain National Nature Reserve, Tianjin 301900, China Received 29 September 2016 Revised E-mail: zhaotiejiann456@sina.com
Liu, Baxian Mountain National Nature Reserve, Tianjin 301900, China Received 29 September 2016 Revised E-mail: liuguoquan01@163.com
Shi, Department of Plant Biology & Ecology, College of Life Sciences, Nankai University, Weijin Road 94, Tianjin 300071, P.R. China E-mail: fcshi@nankai.edu.cn

article id 579, category Research article

Matti Maltamo, Kalle Eerikäinen. (2001). The Most Similar Neighbour reference in the yield prediction of Pinus kesiya stands in Zambia. Silva Fennica vol. 35 no. 4 article id 579. https://doi.org/10.14214/sf.579

Keywords: stand development; difference equations; non-parametric regression; plantation forests

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The aim of the study was to develop a yield prediction model using the non-parametric Most Similar Neighbour (MSN) reference method. The model is constructed on stand level but it contains information also on tree level. A 10-year projection period was used for the analysis of stand growth. First, the canonical correlation matrix was calculated for the whole study material using stand volumes at the beginning and at the end of the growth period as independent variables and stand characteristics as dependent variable. Secondly, similar neighbour estimates were searched from the data categories reclassified according to thinnings. Due to this, it was possible to search for growth and yield series which is as accurate as possible both at the beginning and at the end of the growth period. The reliability of the MSN volume predictions was compared to the volumes predicted with the simultaneous yield model. The MSN approach was observed to be more reliable volume predictor than the traditional stand level yield prediction model both in thinned and unthinned stands.

Maltamo, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: matti.maltamo@forest.joensuu.fi
Eerikäinen, Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: ke@nn.fi

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