Preliminary Analysis on Site Index of Sugi (Cryptomeria japonica) Planted Forests Using the National Forest Inventory Data in Kyushu Island

Mitsuda, Yasushi; Kitahara, Fumiaki

doi:10.15684/formath.14.003

Cited by 4 publications

(5 citation statements)

References 18 publications

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“…Furthermore, height growth curve models derived from the GC and DE methods assume that shapes of height growth curves do not vary with site index (i.e., monomorphic curve), whereas the COM method adopts the polymorphic height growth curve in which shapes of height growth curves vary with site index. Past studies have shown the advantages of polymorphic height growth curves over monomorphic curves (Kayahara et al, 1998;Mitsuda and Kitahara, 2015). However, the greatest barrier in utilizing the COM method is the application of the Bayesian calibration using the MCMC method.…”

Section: Discussionmentioning

confidence: 99%

Comparing Methods for Developing Site Index Prediction Model of Sugi (Cryptomeria japonica) Planted Stand

Mitsuda

Tsutsumi

2018

FORMATH

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Abstract:This study aimed to compare three methods for developing site index prediction model for specific species for a given site using environmental factors as explanatory variables. The following methods were compared in this study: (1) guide curve based method, (2) difference equation based method, and (3) combined site index prediction and height growth curve models method. The site index models were parameterized by the three methods with a permanent plot data and then evaluated for accuracy and practicability in model prediction using the stem analysis data. Root mean squared error and Spearman's rank correlation coefficient were used as statistics representing model accuracy and practicability; values obtained for the model derived from combined method were 4.468 and 0.754, respectively, which indicated that it was the best among the three models.

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Section: Discussionmentioning

confidence: 99%

Comparing Methods for Developing Site Index Prediction Model of Sugi (Cryptomeria japonica) Planted Stand

Mitsuda

Tsutsumi

2018

FORMATH

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“…Ontogeny may essentially be the integration of unobservable effects; therefore, we prefer to assume that the features are unobserved. The previous research (Katakura et al., 2005) also provided anamorphic growth curve sets for the two species without using this specific information, as similar estimates based on this principle are often conducted (Mitsuda & Kitahara, 2015; Nishizono et al., 2014).…”

Section: Methodsmentioning

confidence: 99%

“…Even in such cases, we can often identify the age of a given individual, for example, by counting the number of tree rings or the number of rings in the otolith of fish. As a result, we can often collect the nonchronological data of many individuals, and we must estimate the growth curve set using the nonchronological data (Edminster, Mathiasen, & Olsen, 1991; Mitsuda, 2014; Mitsuda & Kitahara, 2015; Nishizono, Kitahara, Iehara, & Mitsuda, 2014).…”

Section: Introductionmentioning

confidence: 99%

Estimating polymorphic growth curve sets with nonchronological data

Moriguchi

2020

Ecology and Evolution

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When we collect the growth curves of many individuals, orderly variation in the curves is often observed rather than a completely random mixture of various curves. Small individuals may exhibit similar growth curves, but the curves differ from those of large individuals, whereby the curves gradually vary from small to large individuals. It has been recognized that after standardization with the asymptotes, if all the growth curves are the same (anamorphic growth curve set), the growth curve sets can be estimated using nonchronological data; otherwise, that is, if the growth curves are not identical after standardization with the asymptotes (polymorphic growth curve set), this estimation is not feasible. However, because a given set of growth curves determines the variation in the observed data, it may be possible to estimate polymorphic growth curve sets using nonchronological data. In this study, we developed an estimation method by deriving the likelihood function for polymorphic growth curve sets. The method involves simple maximum likelihood estimation. The weighted nonlinear regression and least‐squares method after the log‐transform of the anamorphic growth curve sets were included as special cases. The growth curve sets of the height of cypress (Chamaecyparis obtusa) and larch (Larix kaempferi) trees were estimated. With the model selection process using the AIC and likelihood ratio test, the growth curve set for cypress was found to be polymorphic, whereas that for larch was found to be anamorphic. Improved fitting using the polymorphic model for cypress is due to resolving underdispersion (less dispersion in real data than model prediction). The likelihood function for model estimation depends not only on the distribution type of asymptotes, but the definition of the growth curve set as well. Consideration of these factors may be necessary, even if environmental explanatory variables and random effects are introduced.

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“…Climatic conditions are also a critical factor determining site productivity at the macro scale; therefore, the relationships between site productivity and climatic factors have been studied (e.g. Coops et al, 1998;Iverson et al, 1997;Mitsuda and Kitahara, 2015;Tickle et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Growth Responses to Climatic Conditions of Sugi (<i>Cryptomeria japonica</i>) and Hinoki (<i>Chamaecyparis obtusa</i>) Using a Carbon Balance-Based Growth Model

Mitsuda

Hosoda

Iehara

2017

FORMATH

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Abstract:This paper aimed to reveal differences in growth response to climatic condition between sugi (Cryptomeria japonica) and hinoki (Chamaecyparis obtusa) by comparing parameters of a carbon balancebased growth model. Seven carbon balance-based growth model parameters related to the rate of photosynthesis, temperature and humidity controls were parameterized by a Bayesian calibration using growth data derived from permanent plots. A hierarchical Bayes model was applied to this parameterization, where the common parameter was estimated first and the species-specific parameters were derived from the common parameter thereafter. Simulated light-response curves using estimated parameters were similar and the photosynthetic rate of sugi was higher than that of hinoki. The patterns of response to temperature represented by estimated parameters were different between sugi and hinoki; sugi responded rapidly to changes in temperature while hinoki responded relatively slowly, resulting in a higher tolerance to low temperature than sugi. Estimated parameters indicated that the photosynthetic rate controlling function for humidity could not be implemented for either species in the model. The parameterization of a carbon balance-based growth model revealed differences in the potential photosynthetic ability and response to temperature of sugi and hinoki. However, we could not represent the control effect of humidity on the photosynthetic rate.

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Preliminary Analysis on Site Index of Sugi (Cryptomeria japonica) Planted Forests Using the National Forest Inventory Data in Kyushu Island

Cited by 4 publications

References 18 publications

Comparing Methods for Developing Site Index Prediction Model of Sugi (Cryptomeria japonica) Planted Stand

Comparing Methods for Developing Site Index Prediction Model of Sugi (Cryptomeria japonica) Planted Stand

Estimating polymorphic growth curve sets with nonchronological data

Comparison of Growth Responses to Climatic Conditions of Sugi (<i>Cryptomeria japonica</i>) and Hinoki (<i>Chamaecyparis obtusa</i>) Using a Carbon Balance-Based Growth Model

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