We applied the Local Yield Table Construction System (LYCS), a computer program that estimates stand growth as a function of various density control strategies, to Cryptomeria plantations in Taiwan. Parameters of the growth model were estimated from permanent plot data on Cryptomeria stands stored in a database at the Experimental Forest of National Taiwan University. The diameter at breast height (DBH) and the number of trees measured in permanent plots were used as parameters to estimate the curve of the DBH growth rate, the effects of stand density on diameter growth, growth in terms of DBH, and diameter distribution. The estimated stand growth could be adapted to the observed values in the permanent plots. Based on these results, yield tables for various stand density control strategies can now be constructed for Cryptomeria stands in Taiwan

Lin, Wen-Liang

Matsumoto, Mitsuo

Nakajima, Tohru

Shiraishi, Norihiko

Tatsuhara, Satoshi

Yang, Yong-Chi

Zheng, Chin-Long

National Chung Hsing University Institutional Repository

 14 Estimation of diameter growth parameters for Cryptomeria plantations in Taiwan using the Local Yield Table Construction System Tohru Nakajima*1,4, Yong-Chi Yang*2, Mitsuo Matsumoto*3, Chin-Long Zheng*2, Satoshi Tatsuhara*1,Wen-Liang Lin*2, and Norihiko Shiraishi*1 *1 Graduate School of Agricultural and Life Sciences, University of Tokyo,    1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan *2 School of Forestry and Resource Conservation, National Taiwan University,    No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan *3 Forestry and Forest Products Research Institute,    1 Matsunosato, Tsukuba, Ibaraki 305-8687, Japan  *4 Corresponding author Tohoku University Tel:+81-22-795-6696 E-mail:toron@mail.tains.tohoku.ac.jp  ABSTRACT  We applied the Local Yield Table Construction System (LYCS), a computer program that estimates stand growth as a function of various density control strategies, to Cryptomeria plantations in Taiwan. Parameters of the growth model were estimated from permanent plot data on Cryptomeria stands stored in a database at the Experimental Forest of National Taiwan University. The diameter at breast height (DBH) and the number of trees measured in permanent plots were used as parameters to estimate the curve of the DBH growth rate, the effects of stand density on diameter growth, growth in terms of DBH, and diameter distribution. The estimated stand growth could be adapted to the observed values in the permanent plots. Based on these results, yield tables for various stand density control strategies can now be constructed for Cryptomeria stands in Taiwan.   Keywords: Cryptomeria plantations, Local Yield Table Construction System, stand density, stand growth   15 INTRODUCTION  The control of stand density by thinning is a main strategy of forest management, and thus to predict stand growth, it is important to consider the various thinning strategies. The Local Yield Table Construction System (LYCS), developed at Tokyo University Forest in Chiba (Konohira, 1995), is a computer program that predicts timber harvest based on various thinning plans (Shiraishi, 1986; Matsumoto, 2005) by using a growth model. Using a parameter estimation methodology (Matsumoto, 1997), LYCS has been applied to Japanese sugi, hinoki, and larch plantations (Tanaka et al., 2004; Nakajima et al., 2007a, b), and has also been used to develop forest management strategies (Nakajima and Shiraishi, 2007). However, no study had applied the system to Cryptomeria forests in other countries. The Experimental Forest of National Taiwan University has data stand volume, height curve parameters, and other aspects of Cryptomeria stands (Yang et al., 1995), but a growth model for estimating diameter growth as a function of density control in these stands had not yet been devised. Thus, we developed a model to estimate the growth parameters of Cryptomeria plantations in Taiwan and evaluated the applicability of the estimated parameters to permanent plot data.    MATERIALS AND METHODS  Data source The data used for parameter estimation were derived from permanent plot data of Cryptomeria stands in the Experimental Forest of National Taiwan University. The data set includes thinning age, number of dominant trees and thinned trees per hectare, mean diameter at breast height (DBH), and mean tree height, all of which were measured approximately every 5 years between 1920 and 1990 at this site. Table 1 summarizes the permanent plots.   Table 1. Permanent plot data (1990) Plot Area (ha) Altitude (m) Stand density (stems/ha)Shichuan 0.135 1000 563Mentyan 0.153 1100 503Shitourhwu 0.147 1200 565Sanchianju 0.126 1200 611Shianjin 0.116 990 802Anyntuku 0.118 920 517  16 The plots were 0.116–0.153 ha in area, and located at 920–1200 m elevation. Around 1990, the permanent plots had a density of 503 to 802 trees/ha, and were about 70–80 years old.  Procedures We estimated the growth parameters by applying relational expressions in the LYCS to the aforementioned data sources using the parameter estimation method (Shiraishi, 1986). The relational expressions are summarized below.   Relationship between stand density and mean DBH:  log N + a log D = K,                                              (1)  where D is the DBH in cm and a and K are parameters.  Increment rate of mean DBH:  r = m exp (－n t ),                                        (2)  where r is the increment rate of the mean DBH (%/year), m and n are parameters, and t is stand age.  Growth model for diameter increment using the results from formulas (1) and (2):  r = m exp(–n t ) + p (K – log N  – a log D),                             (3)  where p is the parameter.   Formula (1) was estimated by applying a linear curve to log–log scale plotting of the stem number per hectare and mean DBH. Formula (2) was estimated by applying the growth rate curve of the annual growth rate (%/year) of the DBH, sorted by stand age, to Gompertz functions. Formula (3) shows the growth model for the diameter increment using the results from (1) and (2). In formula (3), parameter p represents the influence of stand density on DBH growth, and all parameters (p, m, and n) were  17 estimated  by applying the nonlinear least-squares method to DBH growth in permanent plots using the methods developed for Japanese sugi and hinoki plantations (Shiraishi, 1986). We used the quasi-Newton method because it is applicable to high nonlinearity (Nakagawa and Koyanagi, 1982).   Then we examined the estimated values using these parameters and the data on Cryptomeria stands in permanent plot in Sanchianju. The plot was established when the stand was 6 years old, and has been measured more than 30 times since then. The latest measurement was taken when the stand was 72 years old. Data on the decreasing number of trees due to thinning or self-thinning have been recorded since the permanent plot was established. We set the observed values of the diameter distribution at stand age 36 as the initial value, and used the data on stand density in LYCS. We compared the estimated values of mean DBH and diameter distribution to the observed values.  Finally, we used an example to predict DBH growth under three stand density control strategies: low (30% of trees thinned at age 15, and 40% at ages 25 and 35), intermediate (20% thinned at age 15, and 30% at ages 25 and 35), and high (20% thinned at age 15, and 30% at age 25).   RESULTS AND DISCUSSION  Growth parameters and adaptability to the permanent plot Table 2 shows the estimated parameters. Parameter p for our study site was 2.3, the same value as that estimated for Cryptomeria at Tokyo University Forest in Chiba (Shiraishi, 1986). This result indicates that the effects of thinning on the diameter growth of Cryptomeria are the same in Japan and Taiwan. Thus, our findings support Nakajima and Shiraishi’s (2007) suggestion that once p is evaluated in one area, it can be used for the same tree species in other areas.  Table 2. The estimated parameters for Cryptomeria plantations in Taiwan d K m n1.025 4.455 4.746 0.033The relationship betweenstand density and meanDBHr = m  exp ( -n t )Increment rate of mean DBHlog N + d  log D  = K  Figure 1 shows the observed and estimated data for the mean DBH, with an error  18 rate of 8.3% on average (maximum 12.6%). The mean DBH was slightly overestimated, with an 8.3% error rate on average.  A period of 30 years, which is a relatively long prediction period, typically has an error rate of about 10% on average. Our error rate falls within this rate, indicating that our method is accurate and can be used for practical prediction of forest resources. In the future, we will work to improve the prediction accuracy by incorporating more elaborate data analyses.    010203040506030 50 70Stand age (years)Mean DBH (cm)ＰｒｅｄｉｃｔｅｄＯｂｓｅｒｖｅｄ Fig. 1. Mean diameter comparison between the observed and estimated data  Figure 2 compares the estimated and observed diameter distributions. Setting the initial diameter distribution at age 36, we predicted the diameter distribution of the stand at age 68. The distribution at age 36 is shown in the figure as a solid line, while the predicted and observed values at age 68 are represented by a dotted line and thick line, respectively. Even though the curves at 24 to 30 cm DBH did not match, the prediction was accurate, and goodness of fit was observed between the predicted and observed diameter distributions.   Example of a density control plan  We used an example to predict DBH growth under the various stand density controls shown in Fig. 3. At age 60, the densities at the final cutting of low-, intermediate-, and high-density stands were 504, 784, and 1120 stems/ha, respectively, and their mean DBHs were 41.3, 34.9, and 30.7 cm, respectively. In summary, stands of higher densities had smaller mean DBHs. This result is logically consistent and matches current forest management assumptions. Predicting DBH as a function of  19 various types of density control strategies using the parameters described above will help develop a thinning plan for Cryptomeria timber production.     0204060801001200 20 40 60 80Diameter class (cm)FrequencyAge 36(Observed)Age 68(Observed)Age 68(Predicted) Fig. 2. Distribution comparison between the observed and estimated data  050010001500200025000 20 40 60Stand age (years)Stand density (stems/ha)051015202530354045Mean DBH (cm)  20 □ Intermediate-density control plan ● Low-density control plan × High-density control plan Fig. 3. Comparison of estimated values with a variety of density control plans CONCLUSIONS   We applied the LYCS to a Cryptomeria plantation in Taiwan. The estimated values were adjustable to the observed data in the permanent plots at the Experimental Forest of National Taiwan University, regarding not only mean DBH but also diameter distribution. Thus, we confirmed that these parameters can be used to estimate Cryptomeria plantation growth under various types of stand density control strategies.  LITERATURE CITED  Konohira Y. 1995. Definition of the system yield table. J For Plann 1: 63–67. Matsumoto M. 1997. Construction of yield tables for sugi (Cryptomeria japonica) in Kumamoto district using LYCS. J For Plann 3: 55–62. Matsumoto M. 2005. Developing the Local Yield Table Construction System for Microsoft Excel. Trans For Technol 764: 18–22. [in Japanese] Nakagawa T, Koyanagi Y. 1982. Analysis of experimental data by the nonlinear least-squares method. Tokyo: University of Tokyo Press. 206 p. [in Japanese] Nakajima T, Shiraishi N. 2007. Application of the Local Yield Table Construction System to a timber self-supply production strategy in Ise Shrine Forest with a special focus on the “Shikinen Sengu Ceremony.” J Jpn For Soc 89: 21–25. [in Japanese with English summary] Nakajima T, Matsumoto M, Ishibashi S. 2007a. Estimating the growth parameter of Hokkaido larch plantation forest. Hokkaido J For Res 55: 89–91. [in Japanese] Nakajima T, Matsumoto M, Kanomata H, Takezoe K, Hiroshima T, Tatsuhara S, Shiraishi N, Lee JS. 2007b. The estimation of plantation forest resources focusing on the long rotation silvicultural practices in the management unit level: a case study in First Memorial Forest of Ise Jingu. Kyushu J For Res 60: 6–8. Shiraishi N. 1986. Study on the growth prediction of even-aged stands. Bull Tokyo Univ For 7: 199–256. [in Japanese with English summary] Tanaka K, Sasakawa H, Matsumoto M. 2004. Leading parameters for the Local Yield Table Construction System. Jpn For Soc 115: 607. [in Japanese] Yang Y, Nagumo H, Yao Y, Ohsato S, Lin W, Tatsuhara S, Lin H, Suzuki M. 1995. Comparison of the growth and development of Cryptomeria plantations in the  21 Chiba Forest of Tokyo University and the Experimental Forest of Taiwan University: the analysis of 70-year data from the permanent sample plots. In: Sakai H, Ide Y, editors. Proceedings of the IUFRO International Workshop on Sustainable Forest Management. Tokyo: the University Forests, the University of Tokyo. p 146–166. 

Estimation of diameter growth parameters for Cryptomeria Plantations in� Taiwan Using the Local Yield Table Construction System

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Estimation of diameter growth parameters for Cryptomeria Plantations in� Taiwan Using the Local Yield Table Construction System

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