Guillermo Trincado

A multilevel individual tree basal area increment model for aspen in boreal mixedwood stands

Based on a multilevel nonlinear mixed model approach, a basal area increment model was developed for individual aspen (Populus tremuloides Michx.) trees growing in boreal mixedwood stands in Alberta. Various stand and tree characteristics were evaluated for their contributions to model improvement. Total stand basal area, basal area of larger trees, and the ratio of target tree height to maximum stand height were found to be significant predictors. When random effects were modeled at the plot level alone, correlations among normalized residuals remained significant. These correlations were successfully removed when random effects were modeled at both plot and tree levels. The predictive abilities of two alternative models were evaluated at the population, plot, and tree levels. At the tree level, a tree measured at the first growth period was used for estimating random parameters, and basal area increments of that tree in future growth periods were subsequently predicted. At the plot level, one to five tr...

Evaluation of population-averaged and subject-specific approaches for modeling the dominant or codominant height of lodgepole pine trees.

Population-averaged (PA) and subject-specific (SS) approaches for modeling the height of dominant or codominant lodgepole pine (Pinus contorta Dougl. ex Loud.) trees were evaluated using six candidate models derived from the Chapman–Richards and logistic functions. The true PA response obtained from separate fits of the models was compared with the typical mean (TM) response computed using only the fixed-effects parameters of the mixed-effects models. Results showed that the TM response had higher prediction errors than the PA response, suggesting that a true PA response and not the TM response is needed to reflect the overall mean response of the model. The SS approach produced improved height predictions relative to the PA approach when evaluated using independent validation data. In addition, the logistic performed better than the Chapman–Richards function, regardless of whether the SS or PA approach was applied. Among the candidate models, the logistic function with the inclusion of site index gave th...

A framework for modeling the dynamics of first-order branches and spatial distribution of knots in loblolly pine trees

A stochastic model to simulate the processes of initiation, diameter growth, death, and self-pruning of branches in loblolly pine (Pinus taeda L.) trees is presented. Information on whorl formation and branch growth was obtained from destructive sampling of whorl sections from 34 trees growing under 10 different initial spacings. Three different components were modeled and hierarchically connected: whorl, branches, and knots. For each new growing season, whorls and branches are assigned stochastically along and around the stem. Thereafter, branch diameter growth is predicted as a function of relative location within the live crown and stem growth. The branch model was linked to an individual-tree growth model, PTAEDA3.1, to simulate the dynamics of first-order branches arising from the main stem. Information on (i) vertical trend of branch diameter along and around the stem, (ii) volume of knots (live and dead portions), and (iii) spatial location, size, and type (live and dead) of knots can be obtained. ...

Cartografía digital de la Reserva Nacional Valdivia a partir de imágenes satelitales Landsat TM

Resumen es: El objetivo del estudio fue desarrollar y evaluar una metodologia de clasificacion digital para la generacion de cartografia tematica en la Reserva Nacio...

Ecuaciones locales y generalizadas de altura-diámetro para pino radiata (Pinus radiata)

Esta investigacion analizo dos tipos de estrategias de modelamiento de la relacion altura-diametro (h/d) para ser utilizadas en labores de inventario. La informacion requerida se obtuvo de 3.492 parcelas temporales establecidas en 105 rodales de precosecha en la provincia de Arauco, VIII Region. El analisis consistio en una evaluacion y comparacion dentro y entre estrategias de modelamiento en base a medidas de precision y sesgo. Adicionalmente, se cuantifico el efecto en la estimacion de alturas totales sobre la prediccion de volumenes y productos. Las ecuaciones locales con 2-parametros fueron mas precisas y estables en terminos de convergencia en comparacion a ecuaciones con 3-parametros. En todas las evaluaciones realizadas las ecuaciones generalizadas presentaron mejores valores de precision y sesgo que las ecuaciones locales. La aplicacion de una prueba t para observaciones pareadas (α = 0,05) detecto diferencias significativas en la prediccion de volumenes totales y comerciales al utilizar ecuaciones locales o generalizadas. Sin embargo, dos de tres productos considerados no indicaron diferencias significativas.

Accounting for serial correlation and its impact on forecasting ability of a fixed- and mixed-effects basal area model: a case study

Successfully accounting for serial correlations has always been a vital part of growth and yield modeling when using repeated measurement data. In this case study, 16 alternative functions addressing the serial correlations of errors from a basal area model of black spruce (Picea mariana (Mill.) B.S.P.) were examined and compared. Results from this study showed that functions incorporated into the fixed and mixed models to account for the serial correlations improved model fit. The serial correlation of the residuals from the fixed model with directly modeled error structure was significantly lower than that from the fixed model without a modeled error structure. For the mixed model, modeling error structure resulted in only a moderate reduction in serial correlation of residuals. The comparison of the fixed and mixed models with and without directly modeling the error structure showed that for fixed model, a substantial improvement in forecasting ability was achieved when the error structure was directly modeled to account for serial correlation, and when the forecasts were adjusted based on the estimated correlation. But for the mixed model, further modeling of the error structure to account for more serial correlation resulted in worsened or comparative forecasting ability of the fitted model.

Modelling between tree and longitudinal variation in green density within Pinus radiata: implications for estimation of MOE by acoustic methods

BackgroundInstruments based on resonance are widely used in the forest industry to predict modulus of elasticity (MOE) and segregate logs of varying quality for different end uses for fast growing softwoods such as Pinus radiata D. Don. Predictions of MOE, made using resonance instruments, often assume a constant green density, ρg, of 1,000 kg m–3. However, little research has been done to test the robustness of this assumption. The objective of this research was to describe changes in predictive precision of MOE as ρg is increasingly well characterised.MethodsLongitudinal measurements of velocity, V, and ρg taken from eighty 17-year old unthinned P. radiata trees growing at two sites in Chile were used to calculate MOE. Predictions of MOE were then made by substituting measurements of ρg for values predicted by the following models (i) Model 1 - assuming a constant ρg of 1,000 kg m−3, (ii) Model 2 - using the mean tree ρg of 914 kg m−3, (iii) Model 3 - using a model with fixed effects to account for the mean longitudinal variation in ρg, (iv) Model 4 - inclusion of previous terms and random effects to account for tree level variation and (v) Model 5 - inclusion of previous effects (in model 4) and a random quadratic term. Differences in MOE determined from measurements of ρg and the five predictions of ρg were expressed as both a percentage difference, (D) and an absolute percentage difference (Da) to assess precision and bias.ResultsAt the tree level, values for mean D and Da (in brackets) were −9.9 (10.4)%, −0.459 (5.49)%, −0.262 (4.15)%, −0.045 (0.232)% and −0.0406 (0.189)%, for Models 1, 2, 3, 4 and 5, respectively. At the log level, considerable longitudinal bias in D was evident for Model 1 where over-prediction of MOE was greatest between relative heights of >0.1–0.4, with D reaching maximum values of −33.8% between relative heights of >0.1–0.2.ConclusionAssuming constant ρg can result in substantial error in estimates of MOE using acoustic instruments particularly when predictions are made at the log level. The mixed effects modelling approach described here demonstrates a useful method for characterising variation in ρg allowing more accurate estimates of MOE to be made using acoustic methods.

Modelos regionales de altura-diámetro para plantaciones jóvenes de Eucalyptus tereticornis en la costa atlántica colombiana

Una importante superficie de plantaciones de Eucalyptus tereticornis se ha establecido en la costa atlantica colombiana. Decisiones de planificacion y estimaciones de disponibilidad futura de madera requieren contar con sistemas de proyeccion de crecimiento. Uno de los componentes de este sistema son modelos capaces de predecir la altura total de los arboles bajo diversas condiciones de edad, sitio y manejo. Esta investigacion tuvo como objetivo construir modelos regionales de altura-diametro para implementar un modelo de simulacion de crecimiento. Se evaluaron diez modelos que se diferenciaron en el numero y tipo de variables predictoras. La informacion requerida fue obtenida de una red de 63 parcelas permanentes establecidas en plantaciones entre 2-8 anos de edad y entre 388-1.640 arboles por hectarea distribuidas en la costa atlantica colombiana. Medidas de sesgo, precision y error probable fueron utilizadas para realizar la evaluacion de los modelos. Durante el proceso de evaluacion no se detectaron diferencias importantes entre los modelos. Sin embargo, los que presentaron como variables predictoras a nivel de rodal la altura y diametro medio de los arboles dominantes mostraron el menor sesgo y error. El modelo regional propuesto por Krumland y Wensel fue seleccionado como el mejor, porque presento los mejores indicadores de ajuste y prediccion.Una importante superficie de plantaciones de Eucalyptus tereticornis se ha establecido en la costa atlantica colombiana. Decisiones de planificacion y estimaciones de disponibilidad futura de madera requieren contar con sistemas de proyeccion de crecimiento. Uno de los componentes de este sistema son modelos capaces de predecir la altura total de los arboles bajo diversas condiciones de edad, sitio y manejo. Esta investigacion tuvo como objetivo construir modelos regionales de altura-diametro para implementar un modelo de simulacion de crecimiento. Se evaluaron diez modelos que se diferenciaron en el numero y tipo de variables predictoras. La informacion requerida fue obtenida de una red de 63 parcelas permanentes establecidas en plantaciones entre 2-8 anos de edad y entre 388-1.640 arboles por hectarea distribuidas en la costa atlantica colombiana. Medidas de sesgo, precision y error probable fueron utilizadas para realizar la evaluacion de los modelos. Durante el proceso de evaluacion no se detectaron diferencias importantes entre los modelos. Sin embargo, los que presentaron como variables predictoras a nivel de rodal la altura y diametro medio de los arboles dominantes mostraron el menor sesgo y error. El modelo regional propuesto por Krumland y Wensel fue seleccionado como el mejor, porque presento los mejores indicadores de ajuste y prediccion.