Mixed-effects generalized height–diameter model for young silver birch stands on post-agricultural lands

Bronisz, Karol; Mehtätalo, Lauri

doi:10.1016/j.foreco.2020.117901

Cited by 65 publications

(52 citation statements)

References 34 publications

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“…Taper models can be elaborated for the use of the mixed-effects modelling approach. One of the main advantages of this solution is the possibility of implementing random effects during feature prediction, using a small amount of additional measurements in a plot (Pinheiro and Bates 2013;Bronisz and Mehtätalo 2020). In this context, Arias-Rodil et al (2015) indicated that additional section diameters measured between 40% and 60% of the total tree height showed the greatest improvement in volume and diameter predictions.…”

Section: Discussionmentioning

confidence: 99%

“…During analyses heteroscedasticity in the residuals was also included. In the case of heteroscedastic data, analysing likelihood ratio test and solutions containing various functions and predictors, a power-type variance function with tree diameter at breast height as a predictor were applied (De-Miquel et al 2012;Arias-Rodil et al 2015;Bronisz and Mehtätalo 2020).…”

Section: Mixed-effects Taper Modelsmentioning

confidence: 99%

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Taper models for black locust in west Poland

Bronisz¹,

Zasada²

2020

Silva Fenn.

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The diameter at any point on a stem and tree volume are some of the most important types of information used in forest management planning. One of the methods to predict the diameter at any point on a stem is to develop taper models. Black locust ( L.) occurs in almost all forests in Poland, with the largest concentration in the western part of the country. Using empirical data obtained from 13 black locust stands (48 felled trees), seven taper models with different numbers of estimated parameters were analysed for section diameters both over and under bark using fixed and mixed-effects modelling approaches. Assuming a lack of additional measurements, the best fitted taper models were used for the prediction of over bark volume using both methods. The predicted volume was compared with the results from different volume equations available for black locust. The variable-form taper model with eight estimated parameters fitted the data the best. The lowest root mean square error for volume prediction was achieved for the elaborated fixed-effects taper model (0.0476), followed by the mixed-effects taper model (0.0489). At the same time, the difference between the volume relative errors achieved based on the taper models does not differ significantly from the results obtained using the volume equations already available for black locust (two of the three analysed).Robinia pseudoacacia

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Section: Discussionmentioning

confidence: 99%

Section: Mixed-effects Taper Modelsmentioning

confidence: 99%

Taper models for black locust in west Poland

Bronisz¹,

Zasada²

2020

Silva Fenn.

Self Cite

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“…In cases where in there is a lack of measurements, only fixed-effects can be used, yet additional measurements allow random-effects to be predicted [66]. Consequently, it allows for greater predictions accuracy in plots where additional measurements are available [44]. However, in the case of biomass modeling, obtaining additional measurements is troublesome because it is associated with the felling of trees.…”

Section: Discussionmentioning

confidence: 99%

“…Using the fixed part of mixed-effects models provides predictions for a typical plot and in case of nonlinear models it could be biased [42]. However, if even a small amount of local measurements are available, a more accurate random-effect prediction can be used [43,44]. In the multivariate modeling context, such prediction utilizes the cross-model correlations of the model system, thus taking into account the logical interactions between the biomass components.…”

Section: Introductionmentioning

confidence: 99%

Seemingly Unrelated Mixed-Effects Biomass Models for Young Silver Birch Stands on Post-Agricultural Lands

Bronisz

Mehtätalo

2020

Forests

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Secondary succession that occurs on abandoned farmlands is an important source of biomass carbon stocks. Both direct and indirect tree biomass estimation methods are applied on forest lands. Using empirical data from 148 uprooted trees, we developed a seemingly unrelated mixed-effects models system for the young silver birch that grows on post agricultural lands in central Poland. Tree height, biomass of stem, branches, foliage, and roots are used as dependent variables; the diameter at breast height is used as the independent variable. During model elaboration we used restricted cubic spline: 5 knots at the quantiles (0.05, 0.275, 0.5, 0.725, and 0.95) of diameter at breast height provided sufficiently flexible curves for all biomass components. In this study, we demonstrate the use of the model system through cross-model calibration of the biomass component model using tree height measured from 0, 2, 3, and 4 available extreme trees feature in the plot in question. A different number of extreme trees were measured for final model system and our results indicated that for all analyzed components, random-effect predictions are characterized by higher accuracy than fixed-effects predictions.

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“…Generally, h-d models can be defined as simple and generalized. Simple models express height as a function of tree diameter at breast height (Bronisz and Mehtätalo 2020). This modeling approach represents the best equation that can be obtained for specific stand and point in time.…”

Section: Introductionmentioning

confidence: 99%

Investigation of parametric and artificial neural network modeling approaches for total tree height prediction in cedar plantations

Karatepe

Diamantopoulou

Özçelık

et al. 2020

Preprint

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Background: Height-diameter relationships are of critical importance in tree and stand volume estimation. Stand description, site quality determination and proper forest management decisions originate from reliable stem height predictions. Methods: In the context of this work, the prediction ability of the developed height-diameter models was investigated for cedar (Cedrus libani A. Rich.) plantations in Western Mediterranean Region of Turkey. Towards this direction, parametric modeling methods such as fixed-effects, generalized models, and mixed-effects were evaluated. Furthermore, in an effort to come up with the construction of more reliable stem-height prediction models, artificial neural networks were employed using two different modeling algorithms: the Levenberg-Marquardt and the resilient back-propagation. Results: Taking into account the prediction behavior of each respective modelling strategy while using a new validation data set, the mixed-effects model with calibration using 3 trees for each plot seems to be a reliable alternative to the rest standard modelling approaches given the evaluation statistics regarding the predictions of tree heights. Conclusion: Finally, as for providing the most reliable results as compared to the remaining, the resilient propagation algorithm showed its capability of providing more accurate predictions of the tree stem height and thus it can be a reliable alternative to pre-existing modelling methodologies.

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Mixed-effects generalized height–diameter model for young silver birch stands on post-agricultural lands

Cited by 65 publications

References 34 publications

Taper models for black locust in west Poland

Taper models for black locust in west Poland

Seemingly Unrelated Mixed-Effects Biomass Models for Young Silver Birch Stands on Post-Agricultural Lands

Investigation of parametric and artificial neural network modeling approaches for total tree height prediction in cedar plantations

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