Modeling diameter distributions of mixed-species forest stands

Liu, Fuxiang; Li, Fengri; Zhang, Lianjun; Jin, Xingji

doi:10.1080/02827581.2014.960891

Cited by 39 publications

(43 citation statements)

References 29 publications

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“…Una línea de investigación futura debería centrarse en modificaciones realizadas a la función de densidad de Weibull para hacerla aún más flexible, como la propuesta por Lai, Xie, y Murthy (2003) o la generalización denominada "Odd Weibull family" propuesta por Cooray (2006). Otra alternativa sería analizar el empleo de mezclas finitas (finite mixtures) de una misma función o de funciones diferentes que ya han dado buenos resultados en la caracterización de distribuciones diamétricas (Liu, Zhang, Davis, Solomon, & Gove, 2002). En todo caso, el empleo de estas funciones para el modelado de las distribuciones diamétricas futuras, supondría ajustar un mayor número de ecuaciones al contar con más parámetros, lo que añadiría una nueva fuente de error y podría limitar su uso.…”

Section: End Of English Versionunclassified

“…Another alternative would be to analyze the use of finite mixtures of one function or different functions that have already been successful in characterizing diameter distributions (Liu, Zhang, Davis, Solomon & Gove, 2002). In any case, the use of these functions for modeling future diameter distributions, would expect to fit a higher number of equations when having more parameters, which would add a new source of error and could limit its use.…”

Section: Estimación De Los Parámetros De La Distribución Futuramentioning

confidence: 99%

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Caracterización de las estructuras diamétricas de los bosques naturales del noroeste de Durango, México

Corral-Rivas¹,

González²,

Corral-Rivas³

et al. 2015

Rev Cha Se Cie For y del Amb

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T he diameter distribution of 44 permanent plots (conifers and broadleaf trees) was modeled using the three-parameter Weibull and Johnson's S B probability density functions (PDFs) in Santiago Papasquiaro, Durango. Four different methods of fitting parameters were used: maximum likelihood (ML), moments (MM), non-linear regression by ordinary least squares (ONLS) and percentiles (MP). The best method of fitting parameters for conifers and broadleaf trees was the method of moments. In modeling the Weibull PDFs, it was assumed that the location parameter (e) corresponds to the minimum measurable diameter. The scale parameter (λ) was modeled using the method of prediction parameter (PPM) through a linear regression relating to the quadratic mean diameter and dominant height of the stand. Finally, the shape parameter (γ) was indirectly recovered by the method of moments through prediction of the average diameter of the stand. According to the Kolmogorov-Smirnov test (P= 0.05), 71 % of the plots for the group of conifers and 68 % of the plots for the group of broadleaf species come from a population that follows the fitting distribution function. ResumenL a distribución diamétrica de 44 parcelas permanentes (coníferas y latifoliadas) se modeló a través de las funciones de densidad de probabilidad (FDP) Weibull de tres parámetros y S B Johnson, en el municipio de Santiago Papasquiaro, Durango. Para ello, se emplearon cuatro métodos de ajuste de parámetros: máxima verosimilitud, momentos, regresión no lineal por mínimos cuadrados ordinarios y percentiles. El mejor método de ajuste para las especies de coníferas y latifoliadas fue el método de momentos. En el modelado de la FDP Weibull se asumió que el parámetro de localización (e) corresponde al diámetro mínimo inventariable de la distribución. El parámetro de escala (λ) se modeló con el procedimiento de predicción de parámetros a través de un modelo de regresión lineal simple que relaciona γ con el diámetro cuadrático medio y la altura dominante del rodal. Finalmente, el parámetro de forma (γ) fue recuperado indirectamente por el método de momentos a través de la predicción del diámetro medio del rodal. De acuerdo con la prueba de Kolmogorov-Smirnov (P = 0.05), 71 % de las parcelas del grupo de especies de coníferas y 68 % de las parcelas del grupo de latifoliadas provienen de una población que sigue la función de distribución ajustada. Palabras clave: Coníferas, latifoliadas, función Weibull, modelado diamétrico.

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Section: End Of English Versionunclassified

Section: Estimación De Los Parámetros De La Distribución Futuramentioning

confidence: 99%

Caracterización de las estructuras diamétricas de los bosques naturales del noroeste de Durango, México

Corral-Rivas¹,

González²,

Corral-Rivas³

et al. 2015

Rev Cha Se Cie For y del Amb

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“…Much research has been done on the utilization of various theoretical functions for diameter distribution modeling, such as Gram-Charlier series (Cajanus 1914), geometrical series, proposed by de Liocourt, an exponential form of the de Liocourt model (Meyer and Stevenson 1943;Meyer 1952;Leak 1964), Pearson distributions (Schnur 1934), Pearl-Reed growth curves (Osborne and Schumacher 1935;Nelson 1964), gamma distribution (Nelson 1935), lognormal distribution (Bliss and Reinker 1964), beta distribution (Clutter and Bennett 1965;McGee and Della-Bianca 1967;Lenhard and Clutter 1971), Weibull distribution (Bailey and Dell 1973) , logit-logistic distribution (Wang and Rennols 2005), SB Johnson distribution (Hafley and Shreuder 1977;Siekierski 1992) and Birnbaum-Saunders distribution (Podlaski 2008). Recently, there were also a few results published on the use of the mixture distribution for the modeling of tree diameter distribution in stands with more complex structure (Zhang et al 2001;Liu et al 2002;Zasada and Cieszewski 2005;Podlaski 2010;Podlaski 2011). Nowadays, because of its properties and advantages, one of the most frequently used has been the Weibull distribution, especially in its 3-parameter and, if necessary, truncated version (see Merganič and Sterba 2006).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the double normal distribution for tree diameter distribution modeling

Zasada¹

2013

Silva Fenn.

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The double normal distribution consists of two normal distributions truncated at their means and then combined in such a way, that points of truncation now become the overall distribution mode. So far, parameters of the double normal distribution have been estimated exclusively using the method of moments. This study evaluates the maximum likelihood method for the estimation of the double normal distribution parameters in Scots pine stands in Poland, and compares it to the results of the method of moments and the two-parameter Weibull distribution fitted using the maximum likelihood method and the method of moments. Presented results show that it is not recommended to use the maximum likelihood method of parameter fitting with Nelder-Mead and quasi-Newton optimization algorithms for the double normal distribution for small samples. However, it can be used for large samples, giving the fit comparable to the two-parameter Weibull distribution and providing parameters having sound practical and biological meaning. In the case of smaller samples for the double normal distribution it is recommended to apply the maximum likelihood method with the alternative simulated annealing optimization algorithm, use the method of moments or substitute the described distribution with the more flexible and robust Weibull distribution. For the smaller samples, the method of moments was superior to the maximum likelihood method.

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“…3. Species are then assigned to the resulting standardized DBH-HT pairs using a finite mixture distribution (Zhang et al 2001;Liu et al 2002) relative DBHs of the species mixtures. Four different stand types, based on species composition, were created (Table 1).…”

Section: Stand Ideotypesmentioning

confidence: 99%

An imputation/copula-based stochastic individual tree growth model for mixed species Acadian forests: a case study using the Nova Scotia permanent sample plot network

et al. 2017

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Modeling diameter distributions of mixed-species forest stands

Cited by 39 publications

References 29 publications

Caracterización de las estructuras diamétricas de los bosques naturales del noroeste de Durango, México

Caracterización de las estructuras diamétricas de los bosques naturales del noroeste de Durango, México

Evaluation of the double normal distribution for tree diameter distribution modeling

An imputation/copula-based stochastic individual tree growth model for mixed species Acadian forests: a case study using the Nova Scotia permanent sample plot network

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