2022
DOI: 10.14214/sf.10544
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Two subject specific modelling approaches to construct base-age invariant polymorphic site index curves with varying asymptotes

Abstract: For constructing growth and yield models the concept of site index as measure of productivity is crucial. Here, we use nonlinear mixed-effects models (NLME) with random individual effects and nonlinear models with dummy variables as fixed individual effects (NLFE) to fit mechanistic growth functions to stem analysis data of the economically most important tree species in Zhongtiaoshan forest region, China. The Richards and Lundqvist function are formulated into five dynamic equations (R1, R2, L1, L2 and L3) ap… Show more

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Cited by 3 publications
(4 citation statements)
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“…This is consistent with the findings from a study by Wang et al (2007) that including the random effects improved the dominant height model when compared to a similar model with all parameters considered as fixed. Cieszewski and Strub (2018), Socha et al (2021), andSprengel et al (2022) compared nonlinear fixed-effects and nonlinear mixedeffects modeling approaches found better behaviour with nonlinear effects with GADA. The distributional assumptions on residuals were not compatible with the nonlinear mixedeffects formulation of Lundqvist-Korf function.…”
Section: Summary and Model Applicationmentioning
confidence: 99%
See 1 more Smart Citation
“…This is consistent with the findings from a study by Wang et al (2007) that including the random effects improved the dominant height model when compared to a similar model with all parameters considered as fixed. Cieszewski and Strub (2018), Socha et al (2021), andSprengel et al (2022) compared nonlinear fixed-effects and nonlinear mixedeffects modeling approaches found better behaviour with nonlinear effects with GADA. The distributional assumptions on residuals were not compatible with the nonlinear mixedeffects formulation of Lundqvist-Korf function.…”
Section: Summary and Model Applicationmentioning
confidence: 99%
“…Other established studies that employ the nonlinear mixed effects modeling approach include (Bailey and Clutter, 1974;Huang et al, 2009;Ni and Zhang, 2007;Nothdurft et al, 2006;Ou et al, 2016;Sharma and Parton, 2007;Sharma et al, 2018;Temesgen et al, 2008). Cieszewski and Strub (2018), Socha et al (2021), andSprengel et al (2022) compared nonlinear fixed-effects and nonlinear mixed-effects modeling approaches and highlighted the behaviour of the two approaches. This study investigates both fixed and mixed-effects models.…”
Section: Introductionmentioning
confidence: 99%
“…In this approach, the basic model is expanded so that two of its parameters are expressed according to the site by a theoretical variable X, which is assumed to include the site productivity factors. GADA derives dynamic equations that reproduce polymorphic SI curves with multiple asymptotes with higher biological realism (Cieszewski, 2021;Socha, Tyminska-Czabańska, Grabska, & Orzel, 2020;Sprengel, Spiecker, & Wu, 2022).…”
Section: Introductionmentioning
confidence: 99%
“…En este enfoque, el modelo base se expande para que dos de sus parámetros se expresen en función del sitio mediante una variable teórica X, la cual se asume que engloba los factores de la productividad del sitio. La DAG permite derivar ecuaciones dinámicas que reproducen curvas de IS polimórficas con múltiples asíntotas de mayor realismo biológico (Cieszewski, 2021;Socha, Tyminska-Czabańska, Grabska, & Orzel, 2020;Sprengel, Spiecker, & Wu, 2022).…”
Section: Introductionunclassified