Metasequoia is a relict plant and is known as a “living fossil”. Therefore, we cannot apply the same function to all the tree height-dbh models. The proper parameters can improve the data fitting of models. In this process, the choice of parameters is a key factor in making errors in models. The correct choice of allometry models is the key in accurate prediction. In tree height and dbh relationships, there is a correlation between tree height and growing conditions, forest density, tree age, basal area and dominant tree height and dbh. However, changes in tree height and dbh may lead to a deviation in the predicted tree height. The non-linear function fitting is relatively easier, so the non-linear tree height-dbh functions are widely used in the prediction of tree height. evaluated the main species of Alberta by using 20 non-linear tree height-dbh models. An individual tree growth model is the basis of a forest growth and production forecast. These studies mainly focus on artificial forests, natural forests and pure forests. There are currently many studies on tree height-dbh models, and some tree height-dbh models of common tree species have achieved good effects in application. This method neglects the possible large deviation in estimating biomass by allometry. The allometry equation of tree height and dbh is usually used in estimating tree height. Therefore, it is very necessary to construct a simple and accurate tree height-dbh model to estimate the height of trees. At the same time, it takes time and effort to measure tree height since there are some limitations caused by observational error and visual disturbance, which increases the cost of the forest survey. Accurate tree height and dbh are necessary conditions for evaluating biomass and are of great importance for the research of forest growth models based on physiological ecology.Ĭompared with dbh, the observation of tree height is often affected by the complexity of the distribution of forest vegetation, forest density and landform. They are usually used to calculate the volume, site index, forest growth and yield and to estimate forest volume, biomass and carbon stock. Tree height and dbh are the two most important factors in surveys, production and management of forest resources and research on forest ecosystems. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Relevant data are within doi: 10.6084/m9.figshare.4956284.įunding: This work was supported by Study on Extracting Forest Management Information and Modeling by Using Digital Camera ) and the Study on Spatial Environmental Effect Model and Forestation Decision Support System for Forest Vegetation in Beijing ( ). Received: JanuAccepted: JPublished: August 17, 2017Ĭopyright: © 2017 Liu et al. PLoS ONE 12(8):Įditor: Ben Bond-Lamberty, Pacific Northwest National Laboratory, UNITED STATES (2017) Development and evaluation of height diameter at breast models for native Chinese Metasequoia. In this study, the method of developing the recommended models for predicting the tree height of native Metasequoias aged 50–485 years is statistically reliable and can be used for reference in predicting the growth and production of mature native Metasequoia.Ĭitation: Liu M, Feng Z, Zhang Z, Ma C, Wang M, Lian B-l, et al. Other variables such as tree height, main dbh and altitude, etc can also affect models. The amount of data is also an important parameter what can improve the reliability of models. Although tree age is not the most important variable in the study of the relationship between tree height and dbh, the consideration of tree age when choosing models and parameters in model selection can make the prediction of tree height more accurate. The results show that the allometry equation of tree height which has diameter at breast height as independent variable can better reflect the change of tree height in addition the prediction accuracy of the multivariate composite models is higher than that of the single variable models. These models were divided into two groups of single models and multivariate models according to the number of independent variables. We studied 53 fitted models, of which 7 were linear models and 46 were non-linear models. A total of 5503 Chinese Metasequoia trees were used in this study. Accurate tree height and diameter at breast height (dbh) are important input variables for growth and yield models.
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