![]() Stand-level variables incorporated into generalized H-DBH models include i.e. There are two basic types of models to describe the relationship between H and DBH (Lei et al., 2009 Zang et al., 2016a): one is basic model, assuming that tree height is completely dependent on DBH (Soares and Tomé, 2002 Gómezgarcía et al., 2014 Mehtätalo et al., 2015), and the other is generalized model, assuming that tree height is not only dependent on DBH but also dependent on other tree and stand-level variables (Soares and Tomé, 2002 Temesgen and Gadow, 2004 Newton and Amponsah, 2007 Huang et al., 2009). To save time and expense, tree height is usually measured in a subsample of trees first, and then the species-specific H-DBH models would be used to overcome the lack of information about unmeasured tree height (Gómez-García et al., 2015 Monteiro et al., 2016 Zang et al., 2016a). Information on the height of urban trees is essential for tree management (McPherson and Peper, 2012), but is often ignored in municipal tree layer inventories (Rust, 2014). Individual diameter at breast height outside bark (DBH, measured 1.3 m above ground level) and tree height (H) are key variables in forestry applications and are used to study forest structure (Curtis, 1967), to estimate timber volume and carbon storage (Curtis, 1967 McPherson and Peper, 2012), site index and other important variables (Peng et al., 2001). This finding may be attributable to differing biological properties of the similar alkaline tolerance species. Additionally, we first reported that soil pH as a covariate variable in H-DBH model and our generalized NLME model implied that the difference in the H-DBH relationship caused by pH varies among different stands. The basic NLME model could be calibrated when there were 3 or more tree height measurements, depending on the required level of accuracy and investigation cost. Taking predicted accuracy and investigation cost into account, we recommend generalized non-linear mixed-effects model (NLME) when there were two or less tree height measurements taken in a given stand. Several sampling designs aimed at minimizing height measurement were tested in terms of accuracy and applicability. ![]() Four model forms were evaluated: (i) basic models (which only used DBH as predictor variable) (ii) generalized models (which used DBH and other predictor variables based on the best basic model) (iii) a mixed-effects model based on the best basic model and (iv) a mixed-effects model based on the generalized model. Here, we compared model forms and approaches for predicting H as a function of DBH and additional stand level covariates variables. Increasingly, H-DBH models are being developed for urban forests, providing tools to forest management and ecosystem services estimation. However, tree height measurement is time consuming, and the recommended procedure is to use estimates from tree height (H) - diameter at breast height (DBH) models. Tree height is a key variable in forest monitoring studies and for forest management. ![]()
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